Latest Publications

Abstract:
In this work, a multi-pressure equivalent fluid (MPEF) approach is applied to model non-conventional acoustic materials that combine different, separate pore networks with contrasting tortuosities. A technique for the informed design of such multi-tortuous materials is proposed. It is based on the observation that broadband performance of such a material can be achieved by tuning the quarter-wavelength resonances corresponding to each network. The material design consists therefore in adding and tailoring the separate pore networks to obtain contrasting tortuosities that evenly distribute these resonances over the desired frequency range. Additional improvement is achieved by independent isotropic scaling of the separate networks. The proposed technique is accurate and also very efficient because it is based on semi-analytical calculations. All this is demonstrated on several examples of multi-tortuous materials which, for simplicity, have an essentially two-dimensional structure. The results obtained in the material design process are verified by Navier-Stokes direct numerical simulations as well as by the MPEF numerical model. Final validation was also carried out experimentally on an additively manufactured sample of one of the multi-tortuous materials designed for this study. The multi-resonance phenomenon observed in sound absorption as well as the experimentally demonstrated anomalous behaviour of the multi-tortuous material backed by an air gap are very well predicted by the modelling and explained in detail on physical grounds.

Keywords:
Multi-resonant acoustic materials, Disconnected pore networks, Multi-pressure model, Tortuosity-based design, Sound absorption

Abstract:
Considerable efforts have been made in recent years to assess the mechanical strength of the matrix in molten carbonate fuel cells (MCFCs), however most studies have been limited to room-temperature testing. This paper introduces methodologies for measuring the compressive strength of the matrix at operational temperatures of 650 °C. The investigation focuses on the fundamental properties of matrices made from different ceramic powders, such as lithium aluminide, aluminium oxide, and yttria-stabilized zirconia (YSZ), which have various powder morphologies. The experimental results were combined with theoretical predictions derived from the classical Young–Laplace law to quantify capillary forces. The findings demonstrate the significant influence of carbonates on the mechanical integrity of the matrix and suggest that structural damage predominantly occurs during assembly or startup of the MCFC. The results show that the morphology of the powder, including particle size and shape, are the key factors reflecting in the final stress-strain response of the matrix. This approach highlights the objective of the present work, which was to integrate the pressureless infiltration of the fabricated porous ceramic pellets with a eutectic carbonate mixture of Li2/K2CO3 and the uniaxial compression at an operating temperature of 650 °C, thereby mimicking the operational conditions of an MCFC.

Keywords:
Molten Carbonate Fuel Cells (MCFC), Ceramic matrices, Compressive strength, Capillary forces

Abstract:
The dependence of transformation pattern in superelastic NiTi tubes on tube outer diameter D and wall-thickness t is investigated through quasi-static uniaxial tension and large-rotation bending experiments. The evolution of outer-surface strain fields is synchronized with global stress-strain and moment-curvature responses using a multi-magnification, high-resolution stereo digital image correlation system at 0.5-2 X magnifications. The transformation patterns exhibit systematic size-dependent behaviors. Under tension and for a specific D, as the diameter-to-thickness ratio D/t decreases, a decreasing number of fat/diffuse helical bands emerge, in contrast to sharp/slim bands in thin tubes. Consequently, the austenite-martensite front morphology transitions from finely-fingered to coarsely-fingered with decreasing D/t. Below a characteristic D/t, front morphology no longer exhibits patterning and phase transformation proceeds via propagation of a finger-less front. Moreover, the transformation pattern exhibits an interrelation between D and D/t, where a front possessing diffuse fingers is observed in a thin but small tube. Under bending, both the global moment--curvature response and transformation pattern exhibit D- and D/t dependence. While wedge-like martensite domains consistently form across all tube sizes, their growth is noticeably limited in smaller and thicker tubes due to geometrical constraints. A gradient-enhanced model of superelasticity is employed to analyze the distinct transformation patterns observed in tubes of various dimensions. The size-dependent behavior is explained based on the competition between bulk and interfacial energies, and based on the energetic cost of accommodating martensite fingers. By leveraging an axisymmetric tube configuration as a reference energy state, the extra energy associated with the formation of fingers is quantified.

Keywords:
Shape memory alloys, Martensitic phase transformation, Digital image correlation, Front morphology, Size effects, Finite-element analysis

Abstract:
This study investigates the effects of low-dose gamma irradiation (50 and 100 kGy) on the mechanical, thermal, and mineralogical properties of cement and geopolymer mortars, with and without barite as a radiation-shielding additive. Mortars were evaluated through flexural and compressive strength testing, thermogravimetric analysis (TG/DSC), X-ray diffraction (XRD), mercury intrusion porosimetry (MIP), and scanning electron microscopy (SEM). Gamma irradiation enhanced flexural strength in cement mortars and had a stabilizing effect on geopolymer systems, with minimal impact on compressive strength across all formulations. XRD and TG/DSC analyses revealed radiation-induced carbonation in cement mortars, marked by increased formation of calcite, vaterite, and aragonite, and a corresponding decline in portlandite. In contrast, geopolymer mortars showed high phase stability, with only minor traces of nahcolite detected. These findings indicate that while cement-based mortars undergo measurable mineralogical changes under gamma exposure, geopolymer mortars, especially those based on fly ash, exhibit superior resistance and are better suited for use in radiation-exposed environments

Keywords:
Geopolymer matrix, Cement matrix, Gamma irradiation, Barite modification, Microstructure, Mechanical properties

Abstract:
Within the framework of the EuroFusion WPMAG project, an automatic laser-welding line was constructed to produce a 1 km long, empty stainless steel jacket demonstrator for the React & Wind (RW) conductor for EU-DEMO. Four 500 m long C-profiles made of 316 L austenitic stainless steel were fabricated from ∼8 m long sections using the manual TIG (Tungsten Inert Gas) welding method. A series of experimental investigations was carried out on the welded samples, including ferrite content measurements, microhardness tests, residual stress measurements, and shape deviation assessments. The results revealed that part of the austenitic structure transformed into ferromagnetic phase—ferrite—around the heat affected zone (HAZ), with up to 7% ferrite observed in the laser welds and up to 10% in the TIG welds. Due to the relative magnetic permeability of ferrite (μᵣ > 1), electromagnetic (EM) forces will be present in that region of the jacket during magnet operation.
The microhardness measurements revealed an increased hardness in the welded region—up to 40.6%—due to material hardening and the presence of harder ferrite in the microstructure. Residual stresses were measured using the hole-drilling technique for both TIG and laser welds, revealing mostly compressive stresses in the TIG welds and tensile stresses in the laser welds. Considerable compressive stresses were introduced into the TIG welds during grinding. To assess the equivalent residual stress, a method of approximating the lower bound of the von Mises residual stress was proposed, revealing increasing values with the depth up to 1 mm, exceeding the initial yield stress at depths greater than 0.5 mm and reaching up to 425 MPa.
The shape deviations around the TIG weld reached 0.41 mm, with deformations toward the centre of the wide side of the jacket, resulting in a concave shape. Such deviations are considerable and could impact subsequent assembly steps of the superconducting Cable-In-Conduit Conductor (CICC).
This study presents a procedure for evaluating weld quality in conductor jackets, focusing on residual stresses, phase transformations, and welding-induced property changes.

Keywords:
Welded jacket, Residual stresses, RW conductor, EU-DEMO

Abstract:
The Coulomb-driven renormalization of electronic compressibility in monolayer MoS2 remains poorly understood at finite temperatures. Using the Rytova–Keldysh potential with a nonlocal dielectric response, we calculate the compressibility as a function of carrier density and temperature in experimentally relevant regimes. The exchange and correlation energies are treated, respectively, within the noninteracting (NI), Hartree–Fock (HF), and random phase approximation (RPA) frameworks. We demonstrate that the RPA, through enhanced screening induced by many-body correlations, yields negative values of the electronic compressibility,
in agreement with recent measurements resolved in temperature and density. At high temperatures (

Keywords:
Graphene, Quantum well, TMDCs, Compressibility TMDCs, Capacity quantum

Abstract:
In this paper, the effect of hafnium, titanium, and molybdenum addition on the microstructure and properties of the aluminide layers deposited by using a chemical vapor deposition process on IN 713C nickel superalloy substrate was discussed. A multi-component aluminide diffusion layer containing Ni–Al, Al–Ti–Ni, and hafnium-rich phases was successfully formed by aluminizing IN 713C nickel superalloy. Subsequently performed corrosion resistance tests confirmed the beneficial effect of the aluminide layer deposited on IN 713C as compared to substrate material. Anticipating improved mechanical response of coated material, density functional theory calculations were performed. It was found that a single Hf/Ti/Mo atom prefers to be positioned within the Al sublattice in the NiAl, and Ni3Al phases. This justifies the presence of the experimentally observed Ni3Hf phase in the Hf-enriched IN 713C. The Hf modification effects on the NiAl, and Ni3Al were further discussed based on the changes of the elastic constants Cij, bulk modulus B, and shear modulus G. The presence of Hf in NiAl causes a decrease of phase’s C12 and C44 values, and increase in the C11 value. It was found that Hf modification of the Ni3Al causes a decrease in the Cij values and a slight decrease of phase’s B/G ratio, indicating a less ductile character of modified phase decohesion.

Keywords:
IN 713C, CVD, Aluminide layer, Corrosion resistance, SEM, Ab initio calculations

Abstract:
The treatment of infected irregular wounds remains one of the most significant challenges in clinical practice. Sprayable hydrogels have attracted considerable attention due to their favorable fitting with irregular wounds. However, the development of hydrogels with programmable anti-bacterial, anti-inflammatory, and regenerative properties to match the healing process still faces severe challenges. Herein, a versatile strategy is demonstrated to develop sprayable and photothermal fiber-embedded hydrogel dressings by incorporating the gold nanorods (AuNRs) and anti-inflammatory drug diclofenac sodium (DS)-loaded poly(lactic-co-glycolic acid) (PLGA) electrospun fibers into the stromal-cell-derived factor 1α (SDF-1α)-immobilized gelatin methacrylate hydrogel. Benefiting from the photothermal conversion property of AuNRs and the suitable glass transition temperature of PLGA short fibers, the hydrogels can not only realize a photothermal anti-bacterial effect, but also photo-triggered on-demand release of DS for anti-inflammatory activity. Furthermore, the sustained release of SDF-1α facilitates endogenous stem cell recruitment. The in vivo experiments demonstrate accelerated healing of infected wounds. The RNA-sequencing analysis reveals that the hydrogel is capable of suppressing the inflammatory response-related pathway. The photo-responsive fiber-embedded hydrogels offer a promising strategy for constructing a photo-triggered programmable therapeutic platform for regenerative medicine.

Abstract:
This paper presents a novel predictive control strategy for the Adaptive Tuned Particle Impact Damper (ATPID), aimed at improving vibration suppression in systems with limited available information. The proposed control algorithm, called the Predictive Control Algorithm (PCA), is based on the prediction and optimization of system dynamics and operates effectively even when system parameters and external excitations are unknown. The only available input for the control process is the measured vibration response of the system. Under this constraint, the PCA accurately estimates the optimal height of the damper in real time, achieving vibration reduction of up to 75%. The algorithm also exhibits a second operational mode: when a theoretical model of the mechanical system is available, the PCA can incorporate this additional knowledge to further enhance control accuracy and performance. The algorithm’s two operating approaches enable its application in a wide range of engineering environments. The robustness of the approach is further validated through sensitivity analyses investigating the impact of variations in particle mass, excitation amplitude, and gravitational conditions. The results obtained from the PCA algorithm show that the height prediction error remains below 10%, with accuracy
increasing in conditions of higher excitation and particle mass. The main novelty of this work is the development of a versatile and fully adaptive predictive control algorithm for ATPID systems, capable of optimizing damper parameters based solely on vibration feedback but also leveraging mathematical system models when available. The proposed control algorithm represents important progress in the development of adaptive mechanical structures employing particle impact damping technology.

Keywords:
Mechanical vibrations, Adaptive damping, Adaptive Tuned Particle Impact Damper, Experimental and numerical investigations, Contact forces, Predictive control algorithm

Keywords:
Parametric predictive control algorithm, Extended horizon adaptive control algorithm, Active magnetic bearing, High-speed rotating machine

Abstract:
Accurate characterization of lunar regolith is essential for planning future surface operations and construction activities. In this work, we compare three 3D measurement techniques for laboratory-scale regolith simulant (LSS) cones: a high-precision handheld laser scanner (HLS), a photogrammetry workflow, and the LiDAR sensor embedded in an iPad Pro. The experiments focused on evaluating the geometric parameters of cone height, base diameter, angle of repose, and volume. HLS and photogrammetry produced closely matching results, with mean observed differences of 0.5 ± 0.4 mm for heights, 0.4 ± 0.2 mm for diameters, and 0.15 ± 0.14° for repose angles. Volumes derived from these two methods differed by less than 1.8 %. By contrast, the iPad LiDAR underestimated cone heights with a mean error of 9.1 ± 2.9 mm and overestimated base diameters by 9.6 ± 6.1 mm, leading to mean angle deviations of 2.63 ± 0.97°. Photogrammetry was intentionally simplified so that its data acquisition time matched that of the HLS, providing a practical efficiency-based comparison rather than maximum accuracy. Although based on single trials, the findings demonstrate that HLS and photogrammetry can deliver consistent results for small regolith features, while low-cost mobile LiDAR remains unsuitable for sub-centimeter measurements. This study highlights the potential of integrating different 3D measurement approaches for rapid regolith assessment, offering insights into future lunar applications.

Keywords:
Lunar soil simulant, LSS, LiDAR, Scanner, Photogrammetry

Abstract:
We introduce a novel microfluidic-based platform that automates single-molecule-sensitive measurements of biomolecular interactions using Fluorescence Correlation Spectroscopy (FCS) combined with FRET and Molecular Brightness Analysis (MBA). The developed system allows for the simultaneous analysis of biomolecule concentration, diffusion coefficient, and equilibrium constant in nanoliter-volume droplets. At the same time, it speeds up the measuring procedure by 5 times compared to the standard one, reduces reactant consumption by 2000 times compared to conventional cuvette-based FCS measurements, and limits the researcher’s intervention to setting up the experiment and calibrating the microscope. We show the performance of the platform by studying DNA–DNA complex formation in response to ionic strength changes, as well as interactions of idarubicin with various nucleic acid complexes. The proposed solution paves the way for the automated optimization of non-covalent reaction conditions, leveraging non-invasive, high-precision statistical methods.

Keywords:
Fluorescence correlation spectroscopy, Microfluidics, Biomolecular interactions, Automation, Diffusion coefficient, Equilibrium constant, DNA hybridization

Keywords:
theranostic, pulmonary delivery, inhaled antibiotics, inhaled antifungals, SPIONs, MRI

Abstract:
In this work, thermomechanical behavior of the superelastic Ti–26Nb, Ti–25Nb–0.3O and Ti–25Nb–0.3N (at. pct) shape memory alloys (SMAs) under load-unload tension was investigated using coupled techniques of infrared thermography and digital image correlation. Local and average characteristics were analyzed in the context of particular deformation stages. In the case of all the SMAs, during loading, first the temperature decreases due to the thermoelastic effect, which can serve to estimate true elastic strain. During further loading, the temperature significantly increases due to the forward stress-induced phase transformation, whereas during unloading, the temperature significantly decreases due to the reverse phase transformation. The average values of the temperature change generated due to the elastocaloric heating and cooling were 15.95 K, 14.94 K, 16.05 K and 17.79 K, 14.44 K, 19.83 K in the case of the Ti–26Nb, Ti–25Nb–0.3O and Ti–25Nb–0.3N SMAs, respectively. The kinematic fields demonstrated that the deformation during loading and unloading is inhomogeneous. It starts with the appearance of thin parallel bands perpendicular to the loading axis. These bands create larger areas with higher strain upon further loading and gradually reappear upon unloading. The results advance the comprehension of the thermal and kinematic aspects of tensile deformation of superelastic Ti-Nb-based SMAs

Abstract:
This study explores matrix-free tangent evaluations in finite-strain elasticity with the use of automatically generated code for the quadrature-point level calculations. The code generation is done via automatic differentiation (AD) with AceGen. We compare hand-written and AD-generated codes under two computing strategies: on-the-fly evaluation and caching intermediate results. The comparison reveals that the AD-generated code achieves superior performance in matrix-free computations.

Keywords:
automatic differentiation, code generation, finite elements, finite-strain elasticity, high-performance computing, matrix-free

Abstract:
Hydrazine oxidation (HzOR) assisted hydrogen production offers a promising
alternative to energy-intensive and sluggish oxygen evolution reaction (OER),
improving its efficiency. However, its practical implementation demands
the development of advanced electrocatalysts capable of overcoming intrinsic
kinetic and charge transfer limitations. Herein, the study reports a hybrid catalyst by anchoring a 

Keywords:
Hydrazine oxidation, Hydrogen evolution, Covalent organic framework, interfacial interaction

Abstract:
Purpose: Chrysanthemum is one of the most popular ornamental plants worldwide. Its breeding remains a highly relevant topic. Nanotechnology significantly and interdisciplinarily contributes to the progress in modern horticulture. To date, there are no studies on the use of the proposed heavy metal-based nanoparticles in mutation breeding of ornamental plants. Methods: CdS NPs, Co3 O4 NPs, and Fe 3O 4@Co NPs were synthesized and applied at a concentration of 75 mg·L −1 in the in vitro internode culture of Chrysanthemum × morifolium (Ramat). Hemsl. ‘Lilac Wonder’. Results: The highest number of adventitious shoots was regenerated on the control and Fe3 O 4@Co NP-treated internodes, whereas the use of CdS NPs and Co3 O 4 NPs hampered regeneration. The NP-treated shoots, compared to the control, accumulated less flavonols and more anthocyanins and polyphenols, and exhibited increased antioxidant capacity. The highest activity of oxidative stress enzymes and the lowest chlorophyll content were noted in CdS NP-treated shoots. The tested nanoparticles also affected the further growth and development of plants during ex vitro greenhouse cultivation. The longest stems were found in Fe 3 O4 @Co NP-treated plants, contrary to CdS NPs and Co3 O4 NPs. The CdS NP-treated plants developed leaves with the smallest surface area, perimeter, length, and width. Evaluation of inflorescences revealed quantitative changes in anthocyanins content. The highest pigment content was found in ligulate flowers of Fe 3 O4 @Co NP-treated plants. One individual with variegated leaves was phenotypically identified within Co3 O 4 NP-treated plants. Genetic variation was detected in 7–8.1% of the plants studied. The SCoT marker system generated more bands and polymorphisms than RAPD. PCoA analysis revealed distinct genetic groupings, with the most altered genotype (treated with CdS NPs) classified as polymorphic by both marker systems. The other 11 polymorphic genotypes did not overlap between RAPD and SCoT analyses. Conclusion: Our results proved that nanoparticles can serve as a novel and valuable tool for plant breeding.

Keywords:
breeding, Chrysanthemum × morifolium, genetic marker, nanobiotechnology, phenotype

Abstract:
Motivated by the spatiotemporal waves of MAPK/ERK activity, crucial for long-range communication in regenerating tissues, we investigated stochastic homoclinic fronts propagating through channels formed by directly interacting cells. We evaluated the efficiency of long-range communication in these channels by examining the rate of information transmission. Our study identified the stochastic phenomena that reduce this rate: front propagation failure, new front spawning, and variability in the front velocity. We found that a trade-off between the frequencies of propagation failures and new front spawning determines the optimal channel width (which geometrically determines the front length). The optimal frequency of initiating new waves is determined by a trade-off between the input information rate (higher with more frequent initiation) and the fidelity of information transmission (lower with more frequent initiation). Our analysis provides insight into the relative timescales of intra- and intercellular processes necessary for successful wave propagation.

Abstract:
This paper introduces an innovative system for the automated creation of free-form modular pavilions. A graph-theoretic Evolutionary Algorithm is implemented to generate floor plans composed of only one basic module. The process is formulated as a constrained multi-objective optimization, where the pavilion structure must be sound, the number of modules and pavilion dimensions are specified, and additional objectives, such as floor-plan roundness, site shape, and obstacle avoidance, are considered. The effectiveness of the proposed approach is demonstrated through examples capturing various scenarios: enforcing circular shapes, maximizing enclosed areas (courtyard size), and avoiding obstacles while maximizing covered areas. Vault-Z is particularly suitable for special types of construction contexts, including temporary structures, post-disaster settlements, and extreme environment outposts. This paper aims to inspire further research on optimization methods for construction systems that enable rapid deployment, reconfiguration, re-use and disassembly.

Keywords:
Vault-Z, Extremely Modular System, Dome, Pavilion, Graph Evolution Algorithm

Abstract:
The AA2124 aluminium alloy-based metal matrix composites (MMCs) reinforced with the silicon carbide (SiC) were examined under tensile creep at 300 °C. The tests were carried out for the materials of different SiC particle size (3 µm and 0.6 µm) and amount (17 vol.% and 25 vol.%). Creep curves under different constant stresses are presented. A high stress sensitivity of the composites tested was identified for a very narrow range of stress values. As a result, a threshold stress range separating the slow and fast creep stages was easily identified at around 5 Mpa for the composite with a larger SiC particle size and lower content and around 1 Mpa for the two other composites. It means that a very small change in stress applied to the structural element at elevated temperatures may lead to its very rapid collapse or even the destruction of the whole structure. The experimental programme was supplemented by the microstructural observations carried out using the scanning electron microscopy providing data necessary for better understanding the damage mechanisms of the material subjected to creep. An influence of voids on the mechanical response and fracture zones was identified. Attention was paid to the nature of degradation of the composites

Keywords:
creep, damage, deformation history, metal matrix composites (MMCs), microstructures

Abstract:
In this work, we investigate Vacuum-Packed Particle (VPP) dampers — granular-core dampers offering tunable damping performance under varying vacuum levels. A comprehensive computational model of the entire VPP damper system is developed using the Discrete Element Method (DEM). A novel discrete-element model of the flexible foil, responsible for consistently transmitting the external pressure resulting from vacuum application, is introduced and implemented by extending the open-source Yade DEM framework. A prototype VPP damper is also designed and experimentally tested, enabling both model calibration and validation of the simulation results. The calibrated DEM model is subsequently employed in a parametric study to assess the influence of material, geometrical, and process parameters on damper performance. All code, along with the associated experimental and simulation datasets, is made available in an open-access repository

Keywords:
Discrete element method, Simulations, Granular damper, VPP, Vacuum-packed particles, YADE DEM

Abstract:
Conventional biometric identification methods relying on Personally Identifiable Information (PII) pose significant challenges concerning privacy and security. Volatile organic compounds (VOCs) in exhaled breath are unique to individuals and can serve as biomarkers for various diseases, making them a promising tool for both bioidentification and clinical diagnostics. This research investigates the feasibility of utilizing VOCs in exhaled breath as biometric identifiers, employing machine learning algorithms for analysis. Additionally, the research investigates the use of VOCs as non-invasive indicators of health status, specifically for estimating BMI and gender. The study involved 94 participants with an average age of 67 years and an average BMI of 28 kg/m². Exhaled breath samples were collected using a portable electronic nose (e-nose) device, which analyzed the VOCs. Machine learning algorithms were applied to the data to assess the feasibility of identifying individuals and estimating BMI and gender based on VOC patterns. The results indicated that VOC patterns could reliably estimate BMI and gender, and potentially distinguish between individuals, suggesting VOCs as a viable tool for bioidentification. The application of machine learning to VOC data showed promise in non-invasive identification and diagnostics. VOCs in exhaled breath offer a novel, non-invasive method for biometric identification and health monitoring. This approach could overcome the limitations of traditional PII, providing a new avenue for personalized medicine. Further research is needed to enhance the accuracy and applicability of this method in diverse populations.

Keywords:
Exhaled breath pattern, Breath analysis, Volatile organic compounds, Algorithms, Artificial intelligence, Biometrics

Abstract:
Artificial Intelligence is rapidly transforming materials science and engineering, offering powerful tools to navigate complexity, accelerate discovery, and optimize material design in ways previously unattainable. Driven by the accelerating pace of algorithmic advancements and increasing data availability, AI is becoming an essential competency for materials researchers. This review provides a comprehensive and structured overview of the current landscape, synthesizing recent advancements and methodologies for materials scientists seeking to effectively leverage these data-driven techniques. We survey the spectrum of machine learning approaches, from traditional algorithms to advanced deep learning architectures, including CNNs, GNNs, and Transformers, alongside emerging generative AI and probabilistic models such as Gaussian Processes for uncertainty quantification. The review also examines the pivotal role of data in this field, emphasizing how effective representation and featurization strategies, spanning compositional, structural, image-based, and language-inspired approaches, combined with appropriate preprocessing, fundamentally underpin the performance of machine learning models in materials research. Persistent challenges related to data quality, quantity, and standardization, which critically impact model development and application in materials science and engineering, are also addressed. Key applications are discussed across the materials lifecycle, including property prediction at multiple scales, high-throughput virtual screening, inverse design, process optimization, data extraction by large language models, and sustainability assessment. Critical challenges such as model interpretability, generalizability, and scalability are addressed, alongside promising future directions involving hybrid physics-ML models, autonomous experimentation, collaborative platforms, and human-AI synergy

Keywords:
Machine learning, Materials modeling, Materials design, Predictive modeling, Deep learning, Supervised learning, Unsupervised learning, Neural networks, Graph neural networks (GNNs), Convolutional neural networks (CNNs), Featurization, Property prediction, Materials discovery, Process Optimization, Autonomous experimentation, Sustainability, Lifecycle assessment, Digital product passport, Data integration, Standardization

Abstract:
Transdermal drug delivery systems (TDDSs) offer non-invasive therapy but face persistent challenges. Artificial intelligence (AI) transforms TDDSs by leveraging machine learning (ML) and predictive analytics to address these barriers. ML models predict drug entrapment with 93.0% accuracy, streamlining development. AI enhances transdermal patch formulations by forecasting drug release kinetics, skin penetration, and stability, minimizing reliance on costly clinical trials. Through virtual screening, AI identifies novel drug candidates and permeation enhancers, accelerating innovation. In microneedle systems, AI optimizes geometries, materials, and drug loading, improving precision and personalization. AI-integrated biosensors enable real-time monitoring, supporting adaptive dosing tailored to individual physiological profiles. Compared to traditional modeling, AI provides superior accuracy and scalability, handling complex datasets to reveal non-linear relationships. Despite challenges like data quality and privacy concerns, AI's integration with 3-dimensional printing and stimuli-responsive materials drives the development of personalized, efficient transdermal therapies. This perspective highlights AI's critical role in advancing therapeutic efficacy and patient-centric care in TDDSs, uniquely combining predictive modeling with real-time monitoring to envision next-generation personalized transdermal delivery systems.

Abstract:
In this paper, fatigue performance of Ti-5553 alloy fabricated using Laser Engineered Net Shaping (LENS) was investigated. Mechanical testing revealed high tensile strength (UTS: 1377 MPa) and good ductility (16 %). Fatigue tests under fully reversed loading expose superior endurance, with crack initiation mechanisms transitioning from surface-induced at high stresses to internal defect-assisted at lower amplitudes. Fractography exposed unmelted particles as initiation sites under moderate cyclic loads. The results establish LENS as a reliable method for manufacturing high-strength Ti-5553 components for high-performance applications.

Keywords:
b-Ti alloys , Direct Energy Deposition (DED)

Abstract:
A novel, template-assisted synthesis strategy for producing hollow polypyrrole (PPy) nanoparticles (H-PPy) with an average diameter of ≈70 nm is reported. Unlike conventional methods, the approach uniquely exploits an in situ reaction between FeCl3 and CaCO3 to simultaneously generate Fe(OH)3 nanoparticles that act as dynamic, self-decomposing templates for PPy deposition. This concurrent template formation and polymer growth restricts Fe(OH)3 particle size via rapid PPy surface encapsulation, facilitating the formation of uniformly dispersed PPy-coated Fe(OH)3 particles (T-PPy). Subsequent removal of unreacted CaCO3 and Fe(OH)3 yields hollow PPy nanoparticles (H-PPy) with a 30% size reduction due to contraction of the soft PPy, resulting in a high surface area morphology. The H-PPy exhibits excellent electrochemical performance as a cathode material in both pouch-type and all-solid-state asymmetric electrochemical capacitors. The specific capacitance of H-PPy calculated by using three electrode electrochemical cell is found to be 158.2 Fg−1 at 1 Ag−1 which is much higher than that of bulk PPy and T-PPy. Areal capacitances of 40.2 and 9.6 mF cm−2 at 0.2 mA cm−2 are obtained for the pouch and solid-state cells, respectively, where activated carbon electrodes are used as anode. The pouch cell demonstrates remarkable cycling stability, retaining 104.6% of its initial capacitance after 15 000 cycles

Abstract:
This article provides a comprehensive review of the chemistry, production technology, and utilization of nanolime. Particular attention is given to the synthesis of Ca(OH)2 nanoparticles through both bottom-up and top-down approaches, highlighting how modern techniques enable precise control of particle size, morphology, and stability. The physicochemical properties of nanolime are discussed in relation to its role as a highly reactive, multifunctional additive, i.a., for cementitious systems, asphalt, and autoclaved products. Its applications are explored with emphasis on performance improvement in construction engineering, including enhanced strength, durability, self-healing potential, and compatibility with low-carbon binders. Beyond construction, nanolime is also examined as a material with relevance to environmental protection, CO2 sequestration, and heritage conservation. The review demonstrates that nanolime is a versatile and strategic material whose properties can be tailored to specific engineering needs, though challenges such as agglomeration, carbonation control, scalability, and long-term durability remain. Future research directions are outlined, focusing on sustainable production methods, functional integration into next-generation binders, and cross-disciplinary applications

Keywords:
nanolime, nanolime synthesis, cement-based materials, CO2 capture, self-healing, heritage conservation

Abstract:
Drought is a leading constraint on plant productivity and will intensify with climate change. Plant acclimation emerges from a multilayered regulatory system that integrates signaling, transcriptional reprogramming, RNA-based control, and chromatin dynamics. Within this hierarchy, non-coding RNAs (ncRNAs) provide a unifying regulatory layer; microRNAs (miRNAs) modulate abscisic acid and auxin circuits, oxidative stress defenses, and root architecture. This balances growth with survival under water-deficient conditions. Small interfering RNAs (siRNAs) include 24-nucleotide heterochromatic populations that operate through RNA-directed DNA methylation, which positions ncRNA control at the transcription–chromatin interface. Long non-coding RNAs (lncRNAs) act in cis and trans, interact with small RNA pathways, and can serve as chromatin-associated scaffolds. Circular RNAs (circRNAs) are increasingly being detected as responsive to drought. Functional studies in Arabidopsis and maize (e.g., ath-circ032768 and circMED16) underscore their regulatory potential. This review consolidates ncRNA biogenesis and function, catalogs drought-responsive modules across model and crop species, especially cereals, and outlines methodological priorities, such as long-read support for isoforms and back-splice junctions, stringent validation, and integrative multiomics. The evidence suggests that ncRNAs are tractable entry points for enhancing drought resilience while managing growth–stress trade-offs.

Keywords:
non-coding RNA, cereals, miRNA, siRNA, circRNA

Abstract:
Triaxial electrospinning was used to fabricate fiber membranes composed of polycaprolactone (PCL), poly(lactic-co-glycolide) (PLGA), and gelatin (GT), designed as carriers for curcumin (Cur) delivery. Here, synthetic polyesters acted as core and shell layers, while GT formed the middle layer containing Cur at varying concentrations. This paper aimed to demonstrate the effect of a shell layer by rearranging the core and shell layers on the kinetics of model drug delivery. In vitro release results indicated the shell layer considerably affected the release behavior, reducing the initial burst release by up to 28% in triaxial fibers compared to coaxial fibers in PLGA-shell forms. The release kinetics were interpreted using the Gallagher–Corrigan model. The membranes were also evaluated for their morphological properties. PLGA-shell-layered triaxial fibers exhibited pore sizes up to approximately 11 µm, small enough to prevent cell migration, while providing higher permeability. The surface wettability analysis of the developed fibers showed that all forms exhibited hydrophilic properties. Furthermore, the cytocompatibility of the fiber membranes was confirmed with the relative cell viability of over 80%. Triaxial fibers with different shell layers displayed similar release trends, yet fibers with the PLGA shell layer demonstrated more favorable performance, attributed to its layer configuration. These findings suggest that the strategic positioning of polymers in triaxial electrospun membranes could be pivotal in optimizing drug delivery systems.

Keywords:
electrospinning, core–shell, triaxial fiber, curcumin, release behavior

Abstract:
Cancer can result from abnormal regulation of cells by their environment, potentially because cancer cells may misperceive environmental cues. However, the magnitude to which the oncogenic state alters cellular information processing has not been quantified. Here, we apply pseudorandom pulsatile optogenetic stimulation, live-cell imaging, and information theory to compare the information capacity of receptor tyrosine kinase (RTK) signaling pathways in EML4-ALK-driven lung cancer (STE-1) and in non-transformed (BEAS-2B) cells. The average information rate through RTK/ERK signaling in STE-1 cells was less than 0.5 bit/hour, compared to 7 bit/hour in BEAS-2B cells, but increased to 3 bit/hour after oncogene inhibition. Information was transmitted by 50–70% of cells, whose channel capacity (maximum information rate) was estimated through in silico protocol optimization. In BEAS-2B cells, channel capacity of the parallel RTK/calcineurin pathway surpassed that of the RTK/ERK pathway. This study highlights information capacity as a sensitive metric for identifying disease-associated dysfunction and evaluating the effects of targeted interventions.

Keywords:
Channel capacity, MAPK pathway, Cancer, EML4-ALK oncogene, Optogenetics

Abstract:
Breast cancer remains the most frequently diagnosed malignancy among women world- wide, with rising incidence and significant biological heterogeneity influencing treatment strategies. Neoadjuvant chemotherapy (NAC) has become a standard option, particularly for aggressive molecular subtypes, underscoring the need for sensitive tools to monitor early treatment response. Conventional imaging (MRI, CT, mammography, and B-mode ultrasound) primarily captures morphological change, often lagging biological alterations. Quantitative ultrasound (QUS) is an emerging modality that characterizes tumor mi- crostructure and yields reproducible, operator-independent biomarkers. This narrative review synthesizes current evidence, clarifies the conceptual framework (spectral, ampli- tude, and attenuation metrics; parametric maps and texture), highlights clinical applications and limitations, and outlines future directions for integrating QUS into NAC response assessment in breast cancer.

Keywords:
breast cancer, neoadjuvant chemotherapy, quantitative ultrasound (QUS), treatment response monitoring

Abstract:
This study focuses on improving the wear resistance of cutting tools and extending their service life under intense mechanical, thermal, and radiation loads in nuclear power plant environments. This research investigates the potential of electrospark alloying (ESA) using W–Zr–B system electrodes obtained from disks synthesised by spark plasma sintering (SPS). The novelty of this work lies in the use of SPS-synthesised W–Zr–B ceramics, which are promising for nuclear applications due to their high thermal stability, radiation resistance and neutron absorption, as ESA electrodes. This work also establishes the relationship between discharge energy, coating microstructure and performance. The alloying electrode material exhibited a heterogeneous microstructure containing WB2, ZrB2, and minor zirconium oxides, with high hardness (26.6 ± 1.8 GPa) and density (8.88 g/cm3, porosity < 10%). ESA coatings formed on HS6-5-2 steel showed a hardened layer up to 30 µm thick and microhardness up to 1492 HV, nearly twice that of the substrate (~850 HV). Elemental analysis revealed enrichment of the surface with W, Zr, and B, which gradually decreased toward the substrate, confirming diffusion bonding. XRD analysis revealed a multiphase structure comprising WB2, ZrB2, WB4, and BCC/FCC solid solutions, indicating the formation of complex boride phases during the ESA process. Tribological tests demonstrated significantly enhanced wear resistance of ESA coatings. The results confirm the efficiency of ESA as a simple, low-cost, and energy-efficient method for local strengthening and restoration of cutting tools.

Keywords:
electrospark alloying, W–Zr–B electrodes, SPS, coatings, phase composition, microstructure, hardness, steel

Abstract:
Coulomb-driven renormalization of electronic spectra in monolayer transition-metal dichalcogenides (TMDCs) remains poorly understood at finite temperature. Using the Rytova-Keldysh potential with a non-local dielectric response, we calculate quasiparticle band-gap renormalization (BGR) and the Fermi-edge absorption spectrum over experimentally relevant carrier densities and temperatures. Exchange and correlation self-energies are treated successively within Hartree-Fock (HF), the random-phase approximation (RPA), and the Hubbard local-field approximation (HFA). Only the HFA, which embeds the G(q) local-field factor, reproduces recent temperature- and densityresolved measurements: it broadens the band gap at low densities and produces a density-induced redshift of the Fermi absorption edge through enhanced screening. The same framework accounts for the nonmonotonic BGR observed in cyclotron resonance experiments on disordered monolayers when disorder-induced thermal broadening is included. The results establish a local-field-corrected many-body theory as the minimal quantitative description of carrier-doped TMDCs and provide a roadmap for engineering interaction-driven electronic phases in two dimensions.

Abstract:
Ocular drug delivery is challenging due to physical and physiological barriers, such as the corneal epithelium and blood–retinal barrier, resulting in limited bioavailability (<5% for eye drops) and fast degradation. For the reason of improving drug delivery to the anterior and posterior ocular segments, this review attempts to assess hydrogel-based systems as versatile systems to overcome these barriers. We thoroughly explore physicochemical and performance characterization approaches (e.g., swelling, rheology, drug release kinetics), hydrogel fabrication methods (e.g., chemical crosslinking, 3D printing), and their uses in new and commercial products. Significant advances highlight the controlled release, mucoadhesion, and biocompatibility of hydrogels, which allow prolonged drug delivery as demonstrated by commercial products such as DEXTENZA® and ReSure® Sealant for corneal sealing and post-operative inflammation control. New technologies provide greater accuracy and less invasiveness. Examples include bioengineered hydrogels for retinal regeneration, systems integrated with nanotechnology, and stimuli-responsive hydrogels (such as pH-sensitive chitosan for glaucoma). By addressing mechanical stability and regulatory criteria, characterization techniques guarantee the suitability of the hydrogel for ocular applications. Hydrogels exhibit considerable promise for personal and least invasive treatments, despite challenges like scalability and high production costs. With implications for improving clinical outcomes and patient compliance through novel biomaterials, this review highlights the important role of hydrogels in ocular drug delivery and offers an outline for future advancements in the treatment of diseases like glaucoma, age-related macular degeneration, and dry eye syndrome.

Abstract:
Azo dyes are synthetic organic compounds widely used in industries such as textiles, printing, and pharmaceuticals. Due to their chemical stability and extensive usage, they are significant environmental pollutants, especially in wastewater. This study investigates the removal of azo dyes from aqueous solutions using a graphene mesoporous sponge (GMS), which is a high-surface sponge-like mesoporous structure predominantly composed of single-layer graphene walls with active sites for dye adsorption. Methylene Blue (MB) and Congo Red (CR) were used to evaluate adsorption performance in aqueous solutions simulating industrial effluents. The adsorption behavior, capacity, and kinetics were studied experimentally, showing that GMS efficiently removes both dyes. Complete decolorization occurred in 30–35 min for both dyes at an initial concentration of 1 mg L−1. A relatively small quantity of GMS successfully removed significant amounts of dye, highlighting its potential to minimize material usage. This efficiency enhances the process’s economic feasibility while contributing to environmental sustainability by reducing the carbon footprint of adsorbent synthesis and usage. These results indicate that GMS is a promising material for wastewater treatment. The experimental results are also aligned with ab-initio molecular dynamics (AIMD) calculations, and they confirm the superior performance of GMS over pristine graphene in dye adsorption.

Keywords:
Methylene Blue, Congo Red, Azo dyes, Adsorption, Carbon, AIMD modelling

Keywords:
Shell, Finite element, Instability, Finite deformation, Bifurcation

Abstract:
Mean field homogenization (MFH) methods are widely employed for homogenizing heterogeneous materials. However, they are limited to predicting effective properties and phase-averaged stresses, failing to capture stresses within individual inclusions. This paper introduces a novel homogenization approach, termed MDMT-Voigt, aimed at addressing this lacuna. The proposed model is validated extensively using finite element analysis (FEA), encompassing virtual Representative Volume Elements (RVEs) with a range of aspect ratios, volume fractions, and orientation distributions. Furthermore, validation is conducted using RVEs derived from experimentally determined microstructures via micro-computed tomography. Across all models considered, the FEA results yield a range of stresses for inclusions with same orientation and aspect ratio which is captured well by the proposed MDMT-Voigt model. Prediction of stresses in individual inclusions represents a significant advancement over conventional MFH methods, offering substantial potential for enhanced micromechanics modelling comparable to full finite element approaches, but at a computational efficiency order of magnitude lower. The paper ends with a demonstration confirming improved micromechanics using the Modified Coulomb criteria

Keywords:
Mean field homogenization, Mori-Tanaka, Micromechanics, Finite element analysis

Abstract:
This work concerns an experimental investigation of the Ti–25Nb and Ti–25Nb–1O (at%) SMAs in the initial stage of tensile deformation using acoustic emission (AE) and digital image correlation (DIC). The stress-strain responses of the considered SMAs are different. The Ti–25Nb SMA exhibits shape memory effect due to the stress–induced martensitic transformation from the cubic β phase to the orthorombic α″ phase. In the case of the Ti–25Nb–1O SMA, the addition of 1 at% of oxygen results in a nonlinear superelastic behavior with small hysteresis and an increased yield stress. The stress-induced phase transformation in the Ti–25Nb–1O SMA is hindered due to the addition of oxygen interstitials. The difference between the deformation mechanisms and the resulting mechanical behaviors of the SMAs was clearly reflected by the recorded AE signals and deformation fields. It was shown that the AE can serve to track the development of the stress–induced phase transformations in the Ti–25Nb and Ti–25Nb–1O SMAs during tension. The AE signals were correlated to the strain fields of the SMAs, which showed a Lüders–type deformation of the Ti–25Nb SMA and a distinct but still inhomogenous deformation of the Ti–25Nb–1O SMA. The results of this study show that DIC and AE techniques are effective tools for monitoring phase transformations of the Ti–25Nb and Ti–25Nb–1O SMAs during tensile loading

Keywords:
Shape memory alloys, Oxygen interstitials, Martensitic transformation, Acoustic emission, Digital image correlation

Abstract:
Operation time and variability in structural, thermal, and environmental loads are important factors affecting the operational safety of power plant structures. Although conventional testing techniques are usually used to assess the level of damage introduced to a structure due to prolonged service, most of them are destructive and time- and costintensive. Therefore, in this paper, a novel approach consisting of Rayleigh optic strain sensors for deformation monitoring under creep conditions is proposed. The suitability of this methodology was assessed during quasi-static loading tests at room temperature, as well as during a long-term creep test at 540 °C under constant stress of 130 MPa, which was performed on a specimen made of 13HMF power engineering steel. The sensor attached to the specimen’s surface was used to monitor strain evolution during 678 days of high-temperature exposure under creep conditions. It was confirmed that the methodology proposed could be successfully used to monitor strain changes under quasi-static and creep conditions, as an excellent agreement between the fiber optic strain sensors and conventional strain recorders was achieved

Keywords:
fiber optic strain sensor, Rayleigh backscattering, creep, strain history monitoring

Keywords:
biomedical applications, drug delivery, nanocarriers, nanomaterials, nanomedicine, nanoparticles, polymeric nanoparticles, tissue regeneration

Abstract:
This study investigates the regulation of tissue growth through mathematical modeling of systemic and local feedback mechanisms. Employing reaction-diffusion equations, the models explore the dynamics of tissue growth, emphasizing endocrine signaling and inter-tissue communication. The analysis identifies critical factors influencing the emergence of spatial structures, bifurcation phenomena, the existence and stability of stationary pulse and wave solutions. It also elucidates mechanisms for achieving coordinated tissue growth. In particular, if negative feedback is sufficiently strong, their final finite size is provided by a stable pulse, otherwise they manifest unlimited growth in the form of a wave. These findings contribute to the theoretical insights into biological processes such as embryogenesis, regeneration, and tumor development, while highlighting the role of feedback systems in maintaining physiological homeostasis.

Abstract:
Steel surface defects in both flat and long products are undesired not only from an aesthetic point of view, but also can lead to severe deterioration of material performance. Manual defect inspection is slow and costly, and thus, automatization of such processes is of interest. Several steel surface defect datasets have been made publicly available so far, and the most famous of them is the Northeastern University (NEU) surface defect database. Many research on surface defect inspection has already been conducted using this dataset, and excellent prediction capabilities were demonstrated in the open literature. More recently, this dataset was extended to account for effects that are expected to occur in real industrial scenarios, such as motion blur, non-uniform illumination, and noise. The extended dataset containing images with those modifications was also made publicly available (E-NEU). In previous papers on the subject, it was shown that using deep learning models trained on the NEU dataset to the E-NEU dataset does not necessarily lead to correct predictions. In this paper, based on the steel surface defects analysis, it is demonstrated that the performance of deep learning architectures can be effectively improved by applying image preprocessing techniques

Keywords:
Surface defects classification, Quality control, Steel Surface, Long products, Flat products

Abstract:
The paper gathers and unifies mechanical stability conditions for all symmetry classes of 3D and 2D materials under arbitrary load. The methodology is based on the spectral decomposition of the fourth-order stiffness tensors mapped to second-order tensors using orthonormal (Mandel) notation, and the verification of the positivity of the so-called Kelvin moduli. An explicit set of stability conditions for 3D and 2D crystals of higher symmetry is also included, as well as a Mathematica notebook that allows mechanical stability analysis for crystals, stress-free and stressed, of arbitrary symmetry under arbitrary loads.

Keywords:
mechanical stability, Born’s stability, 2D materials, Kelvin moduli

Abstract:
In this paper, printing orientation effects on the microstructure and fatigue behavior of SS316L produced via Laser Powder Bed Fusion (LPBF) were studied. Specimens printed in Z (vertical), XY (horizontal), and ZX (45°) orientations were subjected to cyclic loading in the range from ± 300 to ± 500 MPa. EBSD analysis revealed that XY-oriented samples had superior fatigue resistance due to low-angle grain boundaries, while Z-oriented samples showed increased high-angle grain boundaries, leading to early crack initiation.

Abstract:
The paper deals with the notion of stability for thermo-elastoplastic materials
undergoing large strains. The stability analysis is performed by using the
perturbation approach applied to a comprehensive material model derived in a thermodynamic
format. As the main contribution of this paper a stability condition
for a material model incorporating geometrical and material non-linearities under
full thermo-mechanical coupling, without typical simplifying assumptions, is derived,
and a hybrid analytical-numerical verification of the stability condition at a material
point is investigated for the three-dimensional case. Special emphasis is placed on the
quasi-static case, for which a specific stability criterion is derived. The theoretical
analysis is followed by the numerical verification of the obtained condition. The implementation
of the model in the finite element method, using the numerical-symbolic
package AceGen, is also presented in the paper. Two representative three-dimensional
examples are solved, namely a cube under simple shear and a plate with imperfection,
subjected to tension. The obtained results reveal that the type of softening, i.e.,
thermal or material softening, has a significant influence on the stability at a material
point level.

Keywords:
material stability, localization, thermo-elastoplasticity, large strains, finite element method

Abstract:
This study presents a comprehensive 3D and time-dependent simulation of a planar solid oxide fuel cell (SOFC), focusing on the intricate interplay between microstructural characteristics and multiphysics phenomena. The simulation framework integrates detailed microstructural models with advanced multiphysics simulations to capture the coupled effects of electrochemical reactions as well as mass transport and heat transfer within the 3D representative volume elements (RVE) of SOFC porous electrodes generated, and their effective properties are estimated. The energy conversion performances of a SOFC unit are predicted using finite element analysis to solve the governing equations for the coupled phenomena over time. This approach enables us to elucidate the impact of microstructural features such as pore size distribution, tortuosity, and phase connectivity on the overall cell performance. The results demonstrate critical insights into the transient behaviour of the SOFC under various operating conditions, highlighting the importance of microstructural optimisation for enhancing efficiency. This work bridges the gap between microstructural analysis and macroscopic performance prediction, providing valuable guidelines for the design and development of high-performance SOFCs

Abstract:
We numerically investigate the dynamics of polydisperse microbubble clouds driven by ultrasound, focusing on the generation of half-frequency subharmonics (HSH). This study demonstrates that polydispersity in bubble size distributions, in the case of a~cloud with interacting bubbles, greatly expands the frequency range of ultrasound for HSH generation—contrary to identically sized, non-interacting bubbles, where half-frequency subharmonics exist only at a~single excitation frequency corresponding to twice the resonance frequency of an individual bubble. Additionally, we identify a~robust low-frequency subharmonic that is governed by the resonance of the largest bubbles in the cloud. Finally, we thoroughly address issues of numerical instability by conducting stability-aware simulations and independent solver checks, thereby offering practical guidance for the reliable computation of bubble cloud dynamics. These findings provide new insights into the dynamics of bubble clouds, which are relevant to biomedical ultrasound and other phenomena modelled by similar nonlinear differential equations.

Keywords:
nonlinear microbubble dynamics, half-frequency subharmonics, polydispersity, bubble interactions, numerical simulation

Abstract:
The receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein, responsible for engaging the hACE2 receptor, is the principal target of neutralizing antibodies (NAb). To better understand how viral evolution undermines NAb protection, we present a comprehensive, topology-based classification derived from 544 NAbs and 60 nanobody–RBD complex structures. Five major NAb classes, each subdivided into two subclasses, were defined by binding zone, angle of approach, hACE2 competition, and hotspot usage. A systematic mapping of NAb–antigen contacts revealed 91 recurrent hotspot residues, some of which remain fully conserved across all Omicron variants. Leveraging > 2,300 experimentally dissociation constants spanning the Wuhan strain and Omicron lineages, we conducted a comparative affinity analysis across subclasses. NAbs in classes 1–3, which overlap the receptor-binding site, show progressive loss of affinity against Omicron, with many failing to bind recent subvariants due to emergent steric clashes and limited affinity maturation against the ancestral Wuhan RBD. Nonetheless, cases of Abs exhibiting resilience to viral drift have been documented. In contrast, classes 4 and 5 maintain high affinity regardless of their initial affinity for parental strains. Contemporary in-silico epitope predictors captured only ~40% of experimentally defined hotspots, highlighting the need for structure-guided approaches. By introducing a refined topological segmentation of the RBD grounded in previously described but unsystematized regions, our classification captures a broad diversity of NAb binding modes and provides an integrative structural framework that harmonizes prior classification schemes, its relationship with circulating variants, and highlights conserved epitope features relevant to broad-spectrum vaccine and therapeutic NAb design.

Keywords:
Affinity evolution, antibody classification, epitope mapping, neutralizing antibodies, receptor binding domain

Abstract:
Aims: Nicotine, anatabine, and anabasine are the most prevalent alkaloids in Nicotiana species. While nicotine is the main
addictive ingredient in tobacco products, it was also shown to have neuroprotective properties. Mitochondria appear to be one of the targets of nicotine in the cell. These multifunctional organelles are also the first responders to various cellular stresses. Thus, we characterized the impact of tobacco alkaloids on these organelles.
Methods: We investigated the effects of structurally similar alkaloids, anatabine, anabasine, and nicotine, on mitochondrial
function in SH-SY5Y neuroblastoma cells under basal conditions and in the presence of rotenone, a mitochondrial stressor commonly used to model the cellular pathology underlying Parkinson's disease.
Results: We observed changes in mitochondrial behavior, including hyperpolarization, alterations in mitochondrial network morphology, increased mitochondrial turnover rates, and upregulation of mitochondrial biogenesis regulators. The profiles of changes induced by particular alkaloids slightly differed; however, they shared many features with the stress response observed upon treatment with rotenone. Interestingly, the effects of the alkaloids and rotenone were not additive. Moreover, some parameters altered by rotenone were normalized upon cotreatment with the alkaloids.
Conclusions: The results indicate that the investigated alkaloids stimulate mitochondrial stress adaptation. Despite structural similarity, they act through slightly different mechanisms.

Keywords:
anabasine, anatabine, mitochondria, mitochondrial remodeling, nicotine

Abstract:
In patients with testicular germ cell tumours (TGCT), sperm cryopreservation prior to anti-cancer treatment represents the main fertility preservation approach. However, it is associated with a low sperm recovery rate after thawing. Since sperm is a high-energy demanding cell, which is supplied by glycolysis and oxidative phosphorylation (OXPHOS), mitochondrial dysfunctionality can directly result in sperm anomalies. In this study, we investigated the bioenergetic pattern of cryopreserved sperm of TGCT patients in comparison with normozoospermic samples using two state-of-the-art methods: the Extracellular Flux Analyzer (XF Analyzer) and two-photon fluorescence lifetime imaging microscopy (2P-FLIM), in order to assess the contributions of OXPHOS and glycolysis to energy provision. A novel protocol for the combined measurement of OXPHOS (oxygen consumption rate: OCR) and glycolysis (extracellular acidification rate: ECAR) using the XF Analyzer was developed together with a unique customized AI-based approach for semiautomated processing of 2P-FLIM images. Our study delivers optimized low-HEPES modified human tubal fluid media (mHTF) for sperm handling during pre-analytical and analytical phases, to maintain sperm physiological parameters and optimal OCR, equivalent to OXPHOS. The negative effect of cryopreservation was signified by the deterioration of both bioenergetic pathways represented by modified OCR and ECAR curves and the derived parameters. This was true for normozoospermic as well as samples from TGCT patients, which showed even stronger damage within the respiratory chain compared to the level of glycolytic activity impairment. The impact of cryopreservation and pathology are supported by 2P-FLIM analysis, showing a significant decrease in bound NADH in contrast to unbound NAD(P)H, which reflects decreased metabolic activity in samples from TGCT patients. Our study provides novel insights into the impact of TGCT on sperm bioenergetics and delivers a verified protocol to be used for the assessment of human sperm metabolic activity, which can be a valuable tool for further research and clinical andrology.

Keywords:
TGCT, spermatozoa, sperm biochemistry, sperm function, energetic metabolism, oxidative phosphorylation, XF Analyzer, 2P-FLIM, infertility, cancer

Keywords:
rock engineering, stone deterioration, decay function model, monuments, ultrasonic measurements, cyclic ageing

Abstract:
This work compares experimentally measue properties of W-Al-B thin films with mechanical properties, density, and thermal conductivity values calculated using DFT methods. Theoretical modelling was conducted to simulate two WB2 stable structures alloyed with varying amounts of aluminium: α-WB2 (P6/mmm) and ω-WB2 (P63/mmc), as well as α-AlB2 (P6/mmm). Using the HiPIMS-DC magnetron sputtering technique, films with α-WB2 structure and varying aluminium contents were deposited at 400 °C. When layers are composed with x = 1.4% aluminium (where x = at%Al / (at%Al + at%W)), their microstructure changes from amorphous to crystalline columnar. A back transformation to an amorphous microstructure occurs when the amount of aluminium exceeds x = 7.3%. An original method was used for the film density studies, which combined mass measurements and microscopic observation. These measurements were then used to determine the layers' thermal conductivity using the thermoreflectance method. The measured conductivity of the deposited ceramic films range from 3 to 6 W/(mK). Moreover, the obtained films are very hard, e.g. H = 36.1 ± 1.7 GPa for x = 1.4% Al, but exhibit a much lower Young's modulus than the theoretical values. The relatively high H/E⁎ ratio > 0.1 for films with low aluminium content indicates anmore elastic character. Ab-initio calculations showed that, based on the criteria of Cauchy pressure (C12-C44) and Pugh's ratio (B/G), the α-WB2 structure may have a ductile nature in contrast to the other structures. However, the deposited films are rather brittle in nature, resulting from an excess of boron. The fracture toughness measurements show higher KIC values for low aluminium content. They are 3.8 MPa√m for WB2, 2.8 MPa√m for x = 1.4%, and 3 MPa√m for x = 7.3% aluminium

Keywords:
thin films, high-power impulse magnetron sputtering, density, thermal conductivity, fracture toughness, stiffness tensor

Abstract:
Arm-Z to koncepcja hiper-redundantnego manipulatora robotycznego składającego się z identycznych modułów o jednym stopniu swobody (1-DOF) i realizującego dowolne ruchy końcówką w przestrzeni roboczej. Dwie zasadnicze zalety Arm-Z to oszczędność (dzięki masowej produkcji identycznych elementów) oraz odporność na awarie (zepsute moduły mogą być łatwo zastąpione). Z drugiej strony, sterowanie tak bardzo nieliniowym systemem jest znacznie trudniejsze niż typowym manipulatorem przemysłowym i wymaga zastosowania odpowiednich technik optymalizacyjnych. W artykule przedstawiono wstępne wyniki implementacji autorskiego algorytmu opartego na metodzie gradientu prostego do znajdowania trajektorii przejścia między zadanymi stanami Arm-Z. Przykładowym zadaniem dla manipulatora jest bezpieczne wejście do przestrzeni roboczej, inspekcja zadanych pięciu punktów oraz bezpieczne opuszczenie przestrzeni roboczej. Ten eksperyment jest trójwymiarową wersją realizowanej wcześniej inspekcji dwuwymiarowej.

Keywords:
Arm-Z, manipulator hiper-redundantny, inspekcja

Abstract:
W artykule przedstawiono wyniki badań nieniszczących fibrobetonu z dodatkiem włókien stalowych wytworzonego na bazie piasków odpadowych. Belki fibrobetonowe o różnej zawartości włókien stalowych poddane były dwóm rodzajom drgań własnych: drganiom skrętnym i giętnym. Na podstawie przeprowadzonych testów i analizy Fouriera, wyznaczono częstotliwości tych drgań. Posłużyły one do określania dynamicznego modułu sprężystości, dynamicznego modułu odkształcenia postaciowego oraz dynamicznego współczynnika Poissona. Następnie określono wpływ włókien stalowych na te parametry. Badania wykazały, że dodatek włókien stalowych wpływa na zwiększenie dynamicznego modułu sprężystości oraz dynamicznego modułu odkształcenia postaciowego do pewnej krytycznej zawartości włókien, po przekroczeniu której, następuje zmniejszenie wartości tych modułów, ponadto włókna stalowe nie wpływają na wartości dynamicznego współczynnika Poissona.

Keywords:
badania nieniszczące, fibrobeton, moduł sprężystości, odkształcenie postaciowe, współczynnik Poissona, właściwości dynamiczne

Abstract:
The paper presents the results of research on the effect of partially replacing the sand fraction in cement mortar mixes with granulated rubber (GR) from waste tires on the potential for alkali–silica reaction (ASR) occurrence. ASR is a significant durability issue in cement-based composites, which can lead to substantial expansion and cracking in these materials. The study also analyzed the influence of rubber aggregate on the mechanical properties of mortars, particularly compressive and flexural strength, as well as on the microstructure of the mortars. Additionally, the impact of NaOH on the properties of granulated rubber aggregate was evaluated. Reference mortars were prepared using moderately reactive sand (R1) and highly reactive sand (R3), while in the experimental mixes, rubber aggregate was used as a volumetric replacement for a specific sand fraction at levels of 15% and 30%. ASR-related expansion tests were conducted in accordance with the RILEM AAR-2 guidelines. The results showed that partially replacing sand with rubber aggregate effectively reduced ASR-induced expansion, likely due to the rubber’s ability to absorb stress and restrict moisture migration, thereby mitigating the reaction. However, the use of rubber aggregate also led to a decrease in both compressive and flexural strength, which is a typical effect when introducing elastic materials, such as rubber, into cementitious mixes. The findings highlight the potential of granulated rubber from waste tires recycled as a sustainable additive in cement-based materials to control ASR, especially in structures exposed to aggressive environmental conditions. Additionally, the use of this type of aggregate aligns with the principles of the circular economy by utilizing rubber waste and simultaneously delivering both environmental and performance benefits

Keywords:
ASR, durability, internal structure, rubber aggregate, waste tire

Abstract:
Moment-curvature relations for the thermo-mechanical bending of slender beams made of Inconel 718 in the factory-annealed state are determined in the study. The experimentally validated finite element method (FEM) model with the Johnson–Cook material model is used. For the considered conditions of thermo-mechanical processing, the final beam curvature can be estimated as a linear function of the curvature due to the elastic pre-stress. In processing 1mm thick material, using laser power 500W and feed rate 3.33 mm/s, a safe time distance of at least 5.4 minutes is estimated between the presence of high material temperature and the start of precipitation processes

Keywords:
thermo-mechanics, laser-assisted bending, Inconel 718, Johnson-Cook model, curvature

Abstract:
This manuscript proposes a multicriteria approach to the design optimization of adaptive pneumatic impact absorbers. The considered absorber consists of two sealed chambers separated by a piston with an internal valve. Proper valve control affects gas flow between the chambers and ensures a flat reaction force profile over a possibly long piston stroke. The design of such an absorber is defined by three parameters: initial gas pressure, diameter, and length. For a given range of impact conditions, the worst-case maximum deceleration and maximum mass flow rate are used as design criteria in a multicriterial minimization problem. Solutions to this problem provide an optimal balance between impact absorption performance and the technical requirements the valve must meet. An example is considered, which illustrates the Pareto-optimal solutions in the design space and the complex interdependency between initial pressure and absorber diameter at each absorber length. The results demonstrate that a proper choice of design parameters can result in significant performance improvements.

Keywords:
adaptive pneumatic absorbers, impact absorption, design optimization, multi-objective optimization, mass flow rate

Abstract:
A systematic approach to the macroscopic damage analysis of bone-like cellular materials is presented in which damage conditions are expressed as tabularized functions of microstructure geometry parameters. Based on three different strain-based microscopic damage criteria, a large number of cellular microstructures, characterized by different values of geometric parameters, are analysed by the finite element method to determine damage factor values for a number of macroscopic strain states. As a result, an exhaustive database is prepared in which macroscopic damage conditions for a variety of microstructures are presented as tabularized parametric functions of both geometric parameters and strain states. A numerical procedure of data interpolation is proposed as a tool to predict parameterized damage surfaces for any bone-like microstructure. The results are made publicly available in an open data repository to enable further research on their characterization and analytical approximation.

Keywords:
cancellous bone, damage properties, parametric studies, finite element (FE) analysis

Abstract:
In this paper, the key parameters influencing the proper operation of ultrasonic probes for railway rails diagnostics are determined. The goal is to test a set of ultrasonic probes under conditions occurring at high diagnostic speeds. Four issues are studied in more detail. The probe block-rail contact force required to obtain maximum echo level is determined. In the authors’ opinion, the key aspect is the design of the water irrigation nozzle shape in order to produce a laminar couplant flow under the probes. The dependence of the amplitude of the recorded echo on the coupling layer thickness is experimentally investigated. The population of registered signal samples is processed to determine the testing speed limit, which resulted from the loss of data validation ability. The speed limit is calculated based on the average value of the amplitude of the measured signal and the standard deviation of the registered population of amplitudes.
The conducted research allows the authors to conclude that the instrumentation they developed enables the recording of an ultrasonic signal propagating through the tested rail at scanning speed of up to 100 km/h

Keywords:
railway rails diagnostics, ultrasonic examination, ultrasonic probe-rail interface

Abstract:
The aquaculture of Argopecten purpuratus (Peruvian scallop) is a profitable activity with positive impacts on the local economy. However, the development of biofouling on the culture lantern nets generates negative environmental impacts that affect its sustainability. A feasible option aimed at reducing the development of biofouling is to increase the frequency of lantern nets exchange. In this study, we tested whether doubling the lantern net exchange frequency in the final phase of culture reduces biofouling and, in turn, improves the growth and survival of A. purpuratus. For this purpose, in the concession of a company dedicated to the cultivation of A. purpuratus in Samanco Bay, Peru, four 10-floor lantern nets were placed at 25 organisms per floor, divided into two treatments (T1 and T2) with two replicates. One group of these (T1) was exchanged after 30 days, and another group (T2) was maintained until harvest. As a result of the lantern nets exchange, biofouling weight was reduced by 64.6%, survival improved by 10.8%, gonad weight increased by 52.5%, and adductor muscle weight increased by 62.4%, which represents an additional net income of 6582.58 US$ per ha. This study demonstrates the significant benefits of regular lantern net exchanges in mitigating biofouling and enhancing the overall yield and economic viability of A. purpuratus culture, contributing to the advancement of more sustainable aquaculture practices.

Keywords:
Argopecten purpuratus, biofouling, lantern nets, marine cultivation, profitability

Abstract:
The heteroepitaxy of diamond films has received widespread attention; however, its application remains limited owing to the mismatch in properties and structure between diamond and heterogeneous substrates. In this study, diamond films were successfully synthesized on high-entropy alloys (HEAs) substrates using microwave plasma chemical vapor deposition. The resulting diamond films were continuous, uniform, and adhered to the HEAs substrates. The mixed carbides were identified using X-ray diffraction, and the quality of the diamond films was examined using Raman spectroscopy. Moreover, the corrosion test revealed that the diamond/TiZrHfMo samples had excellent electrochemical stability and corrosion resistance with a corrosion potential value of −0.169 V in a 3.5wt% NaCl solution. A multiple regression model was established to evaluate the effects of the structure and growth parameters, which confirmed that the mixing entropy significantly affected the grain size and corrosion properties.

Keywords:
high-entropy alloy, chemical vapor deposition, diamond film, multiple regression model

Abstract:
Advances in high-content microscopy and artificial intelligence (AI) are transforming the quantitative study of infection biology. Automated imaging platforms now enable rapid, large-scale acquisition of host-pathogen interactions across thousands of cells and multiple experimental conditions. When combined with AI-based segmentation, these workflows extract infection-relevant features such as pathogen load, intracellular localization, and host response markers at single-cell resolution. Deep-learning models have proven especially powerful, outperforming classical threshold-based methods under different imaging conditions, reducing reliance on manual annotation, and detecting rare infection outcomes. Beyond robust image analysis, these approaches generate scalable and reproducible datasets that can be integrated with computational modelling and systems biology, providing predictive insight into infection dynamics. This review highlights recent progress in AI-assisted microscopy for bacterial infection and outlines future directions toward multimodal integration, clinical translation, and open-source tool development.

Keywords:
artificial intelligence, machine learning, deep learning, host-pathogen interactions, single-cell biology, cell-to-cell variability, cellular heterogeneity, infection biology

Abstract:
Mathematical methods of information theory provide a useful framework for describing how stimuli are encoded by signaling effectors in biological systems. Yet applying this perspective remains conceptually and computationally challenging, often due to the lack of analytical formulations that connect directly to biophysical models. Here, by deriving closed-form or easily computable information capacity formulas, we quantify how well different signaling models, including binomial, multinomial, Poisson, Gaussian, and Gamma distributions, discriminate among input signals. These expressions clarify how key features such as signal or response range, noise scaling, pathway length, and receiver diversity shape the theoretical limits of sensing. Our results provide intuitive, analytically grounded tools to benchmark and guide the analysis of real signaling systems without requiring computationally expensive mutual information estimation. While motivated by cellular communication, the framework generalizes to any system where noisy input-output relationships constrain transmission fidelity, including synthetic biology, sensor networks, and engineered communication channels.

Abstract:
The present paper discusses mathematical barriers in the development of software for preprocessing of atomistic models of dislocation networks. As a matter of fact, as yet, there are neither analytical nor numerical methods nor programs available which can be used for atomistic reconstruction of complex dislocation networks. Some of the problems to overcome are discussed in this paper. In the previous papers discussed below it was shown that a direct superposition of analytic formulae for displacements of atoms induced by single dislocations does not give possibility to hold the essential geometric properties of the resultant atomistic models. Namely, after the input of first dislocation, the lattice symmetry required to input the next dislocations is usually broken. These inaccuracies compose the mathematical barrier for atomistic reconstruction of advanced dislocation nets. A method developed here has been applied to reconstruction of the dislocation nodes localized in the copper/shaffire interface. In the present case, the partial dislocations are inserted by slips. For comparison, the junction corresponding to the stacking faults obtained by the rigid shifts of copper on the Burgers vector 1/6 ⟨112⟩ are discussed.

Keywords:
dislocations, lattice distortions, finite deformations, atomistic models

Keywords:
radiation transport, Eddington factor, maximum entropy, neural surrogate, hyperbolicity, Marshak problem

Abstract:
While macroscopic experiments on polycrystalline shape memory alloys (SMAs) reveal significant thermomechanical coupling effects arising from the latent heat of transformation, the relevance of thermomechanical couplings in indentation tests remains ambiguous. This ambiguity is further emphasized by the rate effects observed in a number of micro/nano-indentation experiments, thus highlighting the need for a more careful investigation of the thermomechanical interactions at such small scales. With this in mind, the present study aims to demonstrate the role of thermomechanical couplings in indentation-induced martensitic transformation in SMAs. To this end, a simple phenomenological model of pseudoelasticity is employed and finite-element simulations are performed to address two key questions. (1) At which spatial and temporal scales do the thermomechanical couplings arising from the latent heat become effective? (2) To what extent do these couplings influence the indentation response? In connection with the latter, our analysis quantifies the maximal thermal effects that emerge during adiabatic indentation and compares them with those of isothermal indentation.

Keywords:
Pseudoelasticity, Indentation, NiTi, Latent heat, Thermomechanical interactions

Abstract:
The article discloses the method and the results of the metallographic studies and investigation of distribution of the coating elements along the depth of the layers of the high-strength ВЧ50 (VCh50) cast-iron samples, which have been coated by the electrospark alloying (ESA) method with the use of the compact electrode-tools (ETs) having a composition of (90%ВК6 (VK6)+10%1М) and 1М, while the ETs having been manufactured by powder metallurgy (PM) sintering method, as well as applying special technological saturating media (STSM). The metallographic studies have established that the structure of the surface layer consists of three areas, namely, the ‘white’ and transition layers having the thicknesses of 15–75 and 10–20 microns, respectively, and the base metal. The durometric studies have established that the microhardnesses of the ‘white’ layer and the transition zone are within the ranges 6200–13360 and 4290–4900 MPa, respectively. While deepening, the microhardness value is gradually decreasing from the maximum one on the surface of the coating. The highest microhardness values of 13260 and 12800 MPa were obtained, when using the compact electrode-tools made of hard alloy ВК6 (VK6) and the nichrome wire of Х20Н80 (Kh20N80), respectively, and applying the STNS of 0.5%Si+0.5%B+2%Cr+7%Ni+90% petroleum jelly and 5%Si+5%B+90% petroleum jelly, respectively. At the same time, the thickness values of their layers of increased hardness achieve 50 and 90 microns, respectively. The studies of the surface topography have shown that the surface layers of all the samples consist of three characteristic areas, namely, a smooth surface, a rough surface, and a pore. The micro-cracks and pores having sizes up to 1 μm and 1–3 μm, respectively, may sometimes be seen on the sample after the ESA process with the use of the electrodes made of the material of 90%ВК6 (VK6)+10%1M by the PM method. The x-ray spectral analysis has shown that the surface layers of all the samples consist of the base elements and alloying material at all the characteristic points.

Keywords:
electrospark alloying, electrode-tool, metallographic analysis, x-ray spectral analysis, surface layer, coating, structure, microhardness, cracks, pores, continuity

Abstract:
Zbudowanie w 1916 r. w Chabarowsku na rzece Amur najdłuższego mostu w Europie i Azji jest wybitnym osiągnięciem światowej inżynierii. Budowę tego mostu przeprowadziło polskie Towarzystwo Akcyjne Fabryki Machin i Odlewów K. Rudzki i S-ka pod nadzorem polskich inżynierów.

Keywords:
Kolej Transsyberyjska, most w Chabarowsku, most Amurski, Towarzystwo Akcyjne K. Rudzki i S-ka, most stalowy, most kratownicowy, historia inżynierii

Keywords:
antifungal activity, copper oxide, nanotechnology, sustainable agriculture, plant protection

Abstract:
Objective: Focused ultrasound (FUS) with intravenously administered microbubbles (MBs) enables different therapeutic effects, e.g. localized opening of the blood-brain barrier (BBB). Acoustic activation of MBs under FUS induces mechanical effects---primarily stable or inertial cavitation - that can reversibly disrupt endothelial tight junctions without permanent tissue damage. MB acoustic emissions are widely used as indicators of cavitation activity and, by extension, treatment efficacy and safety. While some aspects of microbubble behavior under different exposure conditions are known, the overall influence of various parameter combinations on cavitation dose remains incompletely described. Approach: This study examined how MB concentration (0.0008-0.4% V/V), peak negative pressure (61.5-2600 kPa), pulse duration (95-952 µs), and effective sonication time affect cavitation activity in a flow setup. Cavitation was quantified as a cavitation dose which was divided into three types: stable harmonic (SCD_har), ultraharmonic (SCD_ultra), and broadband (ICD) emissions. Results: SCD_har and ICD increased mostly monotonically with pressure and MB concentration, while SCD_ultra peaked at intermediate values suggesting optimal parameters for the control of the ultrasound BBB opening procedure. Cavitation metrics showed 10% reproducibility. Critically, we found that for fixed effective sonication times, increasing the number of pulses led to significantly change the response of cavitation dose in time. To our knowledge, this relationship has not been studied before, change of pulse length was always related to effective sonication time. Our results suggests that pulse number is an important factor of how MB oscillate, introducing a potentially pivotal control parameter for therapeutic ultrasound.Significance: These findings provide new insights into MB dynamics and highlight pulse count as an underrecognized yet potentially important factor in protocol design. This perspective may inform refinements of FUS treatments, contributing to greater safety, consistency, and efficacy, and represents a step toward optimizing ultrasonic BBB opening strategies.

Keywords:
Microbubbles, Nonlinear oscillations, Ultrasound

Abstract:
Aim This study aimed to evaluate the readability and citation practices of artificial intelligence (AI)-generated responses to questions about human metapneumovirus, a respiratory virus of growing public health concern. Subject and methods Five widely used AI chatbots—ChatGPT-4, Copilot, Gemini,Claude.ai, and Grok—were prompted with 14 standardized questions based on official guidelines from the World Health Organization, the Centers for Disease Control and Prevention, and the Australian National Health and Medical Research Council. Responses were anonymized and assessed using six established readability metrics: Flesch–Kincaid Reading Ease and Flesch–Kincaid Grade Level, Gunning Fog Index, SMOG (Simple Measure of Gobbledygook) Index, Coleman–Liau Index, and Automated Readability Index. Scores were compared to standards recommended by the American Medical Association and the National Institutes of Health. Citation frequency and credibility were also analyzed. Results Among 70 chatbot responses, only one met the recommended readability level. Median readability scores ranged from grade 10.4 to 16.0, indicating high complexity. One chatbot generated the most readable content, while another scored lowest. Only two chatbots included source citations. One cited 68 reliable sources, primarily from health organizations and academic institutions, while the other referenced 31 sources of varying quality. Conclusion AI-generated health content often exceeds recommended readability thresholds and lacks consistent citation practices. These issues may hinder understanding and trust. Improving default readability settings and integrating real-time citation features could enhance the accessibility and credibility of chatbot-based health communication.

Keywords:
Human metapneumoviru, Artificial intelligence, Chatbots , Readability

Abstract:
In the article, due to the conducted research, there have been established the dependences of the quality parameters of the steel part surfaces while nitrocarburizing thereof by the ESA method on the energy parameters of the equipment (discharge energy, Wр) and the technological parameters of the process (labor intensity, τ). The experimental studies have shown that with an increase in the discharge energy there increases the thickness of the strengthened layer, and its microhardness, as well as the surface roughness and its continuity. With an increase in the labor intensity, the thickness of the strengthened layer, its microhardness, and the surface continuity also increase, and the surface roughness almost does not change

Keywords:
electrospark alloying, special technological saturating media, nitrocarburizing, surface layer, quality parameters

Abstract:
Live biotherapeutic products are an emerging novel class of products currently under development to be used for the treatment of clinical challenges such as atopic dermatitis, acne, chronic wounds. Several methods of encapsulation are available to preserve the viability of probiotic bacteria in various harsh environmental conditions. In this work, an innovative microchip electrospinning is developed, which combines microfluidics microchip with electrospinning and enables the preparation of fiber matrices comprising living and functional encapsulated bacteria capable of producing antimicrobial substances. The bacteria are encapsulated into microcapsules, which are immediately within the same process electrospun into hydrophobic fibers. Using confocal microscopy and staining samples with fluorescent dyes, it is confirmed that probiotics are present in fibers. The average concentration of probiotics is 106 bacteria/cm2 in a 1 mm thick matrix. Using an agar overlay assay, it is determined that incorporated probiotics retain their functionality and antimicrobial activity against wound pathogens. This evidence confirms that the electrospun fibers containing microcapsules allow two-way diffusion of substances through pores in fibers (e.g., nutrients in, produced substances out) and support the viability of entrapped bacteria. The electrospun probiotics-loaded fiber matrix developed has potential to be used as a drug delivery system for wound infection treatment.

Keywords:
Microchip electrospinning, Microfluidics, Electrospinning, Probiotics, Wound infection

Abstract:
Burn wound management posed substantial therapeutic challenges due to impaired macrophage polarization dynamics. Metabolic dysfunction in macrophages hindered the transition from glycolysis-driven M1 phenotype to oxidative phosphorylation (OXPHOS)-driven M2 phenotype, result of perpetuating inflammatory reaction to restrain wound healing. Despite all kinds of biomaterials were developed for burn wounds, some critical issues still couldnot be solved, such as limited repair efficacy, strong immunogenicity, and high cost etc. Cellular metabolite α-ketoglutaric acid (AKG) shows good biological activity and can regulate cellular energy metabolism, which is expected to solve the above issues. However, the cellular acid-toxicity of AKG might restrict its wide application in clinic. Therefore, a bioactive electrospinning fiber (PEKUU) was engineered to demonstrate sustained AKG release for modulation of energy metabolism of burn wounds. In vitro assessments confirmed its biocompatibility and effects on keratinocyte and endothelial proliferation, migration and angiogenesis. Meanwhile, PEKUU could attenuated glycolysis-driven M1 polarization, reducing NF-κB-mediated inflammation. While it also could enhance mitochondrial OXPHOS to drive M2 polarization. In vivo experiment showed that PEKUU electrospinning fiber could accelerate epithelialization, collagen remodeling and healing of deep second-degree burn wounds of mice. Finally, proteomics was applied to reveal the underlying mechanism of AKG-mediated metabolic reprogramming, including the coordinated suppression of the glycolytic-NF-κB axes and the potentiation of the OXPHOS and fatty acid oxidation pathways. The dual regulation reshaped macrophage energetics and established a pro-regenerative niche. Overall, PEKUU electrospinning dressing could modulate macrophage polarization state by reprogramming energy metabolism mode, providing a new therapeutic strategy for burn repair.

Keywords:
Burn, Macrophage, Wound healing, Metabolism reprogramming, OXPHOS

Abstract:
Melanin, a widespread natural biopigment, has attracted growing attention owing to its multifunctional properties and potential in novel biomaterials. This review addresses the classification, biological sources, and extraction methodology of natural melanin from animals, plants, fungi, and bacteria, focusing on its physicochemical properties and bioactivities in therapeutic and diagnostic applications. Melanin's broadband ultraviolet (UV) and nearinfrared (NIR) absorbance, strong antioxidant and anti-inflammatory activities, and photothermal conversion efficiency allow its incorporation in photothermal therapy, radioprotection, and wound healing platforms. Moreover, melanin's antimicrobial and antiviral activities that inhibit a diverse array of pathogens indicate its usefulness in surface disinfection and infection prevention. Current advancements in melanin-containing nanoformulations, hydrogels, and microneedle patches highlight their versatility in drug delivery, molecular imaging, and tissue regeneration. Importantly, eco-friendly extraction and utilization of natural melanin advance environmentally friendly approaches in the field of biomedical technology. This review highlights natural melanin's promise as a safe, biocompatible, and multifunctional agent, supporting its use in biomedical applications that address current healthcare challenges.

Abstract:
This study investigates a comprehensive study on the mechanical and microstructural behavior of cementitious mortars modified with a combination of internal carbonation (via solid CO2), calcined clay as a ceramic pozzolanic additive, and bio-based sheep wool fibers. The investigation aimed to explore sustainable routes for enhancing mortar performance while reducing the environmental impact of cement production. A series of mortars incorporating various combinations of dry ice, calcined clay, and wool fibers was prepared and tested to evaluate compressive and flexural strength, porosity, pore size distribution, phase composition, and microstructural morphology. Results demonstrated that internal carbonation significantly promoted matrix densification and compressive strength, increasing fc by approximately 8% compared to the reference. The addition of calcined clay further improved microstructural compactness, reducing total pore volume by 12%, while the incorporation of wool fibers enhanced post-cracking toughness by over 40% despite a 15–30% decrease in compressive strength. SEM and TGA confirmed the formation of calcite and reduced portlandite content, consistent with carbonation and pozzolanic reactions. The findings underscore the potential and limitations of multicomponent eco-modified cement mortars. Optimizing the balance between internal carbonation, pozzolanic reaction, and fiber stability is a key to developing next-generation low-carbon composites suitable for durable and resilient construction applications.

Keywords:
internal carbonation, calcined clay, sheep wool fiber reinforcement, CO2 uptake in cementitious systems, microstructural densification

Abstract:
The paper investigated the effect of electrospark alloying (ESA) on the formation of wear-resistant molybdenum disulfide (MoS2) based coatings for use in face impulse seal (FIS) of pumping equipment operating under conditions of high temperatures, pressure, aggressive environments and radiation exposure. The coatings were obtained on samples of austenitic AISI 321 steel. Two sulfomolybdenation methods have been developed: the first method involves the preliminary application of a sulfur-containing paste before ESA processing with a molybdenum electrode; the second one involves applying the MoS₂ powder and subsequent ESA processing with a molybdenum electrode. The microstructure, microhardness, phase composition and tribological properties of the coatings have been investigated. It was established that the formed coating had a structure comprised of three layers. Those are a porous surface layer, a strengthened layer and a diffusion zone. The maximum microhardness reached 1127 HV at Wp = 3.4 J. The results of tribological tests according to the “ball-disk” scheme showed a decrease in the friction coefficient to 0.0078 on samples obtained by the first ESA method. The obtained results confirm the feasibility of using the ESA methods with the inclusion of molybdenum disulfide in order to increase the operational reliability and durability of FIS units under extreme operating conditions. The proposed technologies can be implemented in production of pumping equipment for nuclear, chemical and energy industries

Keywords:
Electrospark alloying, Molybdenum disulfide, Face impulse seal, Tribotechnical coatings, AISI 321 steel

Abstract:
This paper explores the phenomenon of torsional vibrations of an electric locomotive wheelsets. A dynamic electromechanical drive model has been created and then integrated with the railway wheelset-rail system to simulate self-excited torsional vibrations of the considered system.
Results of these analyses are used in order to confirm that dynamic interaction between electric motors and mechanical systems can be thoroughly investigated when sufficiently reliable physical and mathematical models of these objects are applied. From the computational results, it follows that torsional vibrations of the driven mechanical system essentially influence qualitatively and quantitatively its excitation by the electric drive motors.This motors can be effectively controlled using the U/f = const principle during start-ups under initial drag torques, during synchronization to the nominal operation and under rapid over-loadings. Moreover, the following were observed: negative damping generated by the motor is responsible for operational instability of the entire drive train, and by means of a proper motor control this dangerous effect can be eliminated.

Keywords:
self-excited vibrations, electric locomotive wheelset, torsion vibration, electromagnetic coupling

Abstract:
Tramwaje są niezbędne dla transportu publicznego, jednak nadmierne zużycie kół stwarza poważne wyzwania dla ich żywotności, bezpieczeństwa i konserwacji. Zużycie profilu kół ma istotny wpływ na bezpieczeństwo eksploatacji takich pojazdów szynowych, szczególnie w kontekście ryzyka wykolejenia. W miarę upływu czasu i intensywnej eksploatacji profil koła ulega stopniowej degradacji, co prowadzi do zmian w jego geometrii – zwłaszcza w obszarze obrzeża. Ma to szczególne znaczenie w przypadku pojazdów tramwajowych, których reżim eksploatacji jest zdecydowanie trudniejszy niż w przypadku pojazdów kolejowych. Tramwaje eksploatowane są na łukach o znacznie mniejszych promieniach, a ponadto stosunek masy pojazdu tramwajowego załadowanego pasażerami do masy pojazdu próżnego jest wyższy niż w przypadku pojazdów kolejowych. Zmiana parametrów obrzeża koła w trakcie eksploatacji wpływa na prowadzenie zestawu kołowego w torze. W konsekwencji rośnie prawdopodobieństwo wykolejenia.
W niniejszej pracy zostanie przedstawiony wpływ zmieniającego się w trakcie eksploatacji zarysu zewnętrznego koła na poziom bezpieczeństwa przeciw wykolejeniu tramwaju przy wykorzystaniu autorskiej metodyki oceny tego aspektu eksploatacji tramwajów. W prezentowanych analizach rozważane zostaną konwencjonalne oraz niekonwencjonalne rodzaje układów napędowych stosowanych w tej kategorii pojazdów szynowych.

Keywords:
zużycie kół, bezpieczeństwo przeciw wykolejeniu, pojazdy tramwajowe

Keywords:
Supercapacitors, Polymer gel electrolyte, Host polimer, ELDCs, Carbons

Abstract:
Topology optimization under dynamic constraints is challenging problem requiring special optimization procedures involving solution at each iteration step an eigenvalue problem. In this study we propose simple yet effective procedure of topology optimization under various dynamic loadings. The effectiveness of the proposed methodology is related with quasi-static approximation of the optimization process. Effectiveness of the proposed approach has been demonstrated on a topology optimization of a beam supporting ramp structure. Based on a number of modes it was concluded that proposed method can increase selected natural frequency by a factor of 3.

Keywords:
topology optimization, modal analysis, modular structures, structural dynamics, inertial forces, eigenvalue problem

Keywords:
Supercapacitors, Carbon electrode, Durability, Long cycle life, Carbon modification

Abstract:
A generalization of the Euler’s elastic problem, i.e., finding stationary configurations (planar elasticas) of the Bernoulli’s thin ideal elastic rod with boundary conditions defined through fixed endpoints and/or tangents at the endpoints, for nonlocal stress tensors and the corresponding nonlocal differential constitutive stress-strain relations (nonlocal theory of elasticity) is considered. In the classical (local) Euler-Bernoulli’s beam model the solutions of the governing equations for bending moments and shear forces with static boundary conditions in the case of large deformations can be obtained using Jacobi elliptic functions and incomplete elliptic integrals. It can be shown that even for a simplified nonlocal beam model proposed by Eringen the governing differential equations have much more elaborated form comparing to the local case, which makes the problem of finding the exact analytical solutions of the boundary value problems being quite a challenging task. Nevertheless, some approach based on the iterative integration method of finding an analytical form of the solution is proposed as well as the strongly nonlinear differential equation on the tangent slope angle for the Euler’s elasticas has been derived and analysed.

Keywords:
Euler’s elasticas, Euler-Bernoulli’s beam model, nonlocal differential constitutive stress-strain relations, nonlocal theory of elasticity, incomplete elliptic integrals, Jacobi elliptic functions

Abstract:
Various methods for reconstruction of atomistic models of dislocations and stacking faults in crystalline heterostructures are discussed. In molecular dynamics, for example, the atomistic models of dislocations are often obtained by means of elastic-plastic relaxation of a perfect crystal lattice subjected to external loading. Such a method does not give the possibility for emerging atomistic models of an arbitrarily chosen network of dislocations. This problem concerns many sets of dislocations observed by means of the high-resolution transmission electron microscopy (HRTEM). In this presentation we discuss a deterministic method for obtaining atomistic models of dislocations. The method is based on the sequential inserting of single dislocations into the crystal lattice. In this case, the analytic formulas for gliding of single dislocations in elastic continuum are used. The method is based on the symbolic algebra of elemental lattice distortion tensor fields. Contrary to the linear strain and linear rotation measures, the lattice distortion tensor is the correct measure of finite deformation. Thus, on the basis of lattice distortion tensor field, many different tensor fields of finite strain and finite rotation of the elements of crystal lattice can be determined uniquely. Among others, this enables generation of atomistic models in terms of finite deformation approach.

The method presented here links: (i) the analytic formulas for lattice distortion tensor fields derived from the linear theoryof dislocations, (ii) the finite deformation algebra of distortion fields, and (iii) the atom-by-atom reconstruction of dislocations including their core structures. This method has been implemented in a visual editor of dislocations. Configurations of atoms obtained in this way satisfy the stress equilibrium equations in terms of the linear elasticity. On the other hand, the spatial Burgers vectors of dislocations are stretched and rotated to each other according to the finite deformation theory. During generation of atomistic models, such reconstructed crystal lattice is intersected by the discontinuities corresponding to the insertions of subsequent dislocations along deformed slip planes.

Independently of the atomistic models, a method for generation of finite element (FE) models being the continuous counterpart of the atomistic ones is also discussed. The finite element models discussed are based on the use of the continuous distortion tensor field extracted from 2D or 3D HRTEM images of dislocations. In result, two models are obtained: FE model and the atomistic one which can be embedded in the FE mesh. Such generated atomistic and FE meshes of defects are used as the input data for modelling by means of the ab-initio method, molecular dynamics, statics, and other atomistic methods.

An example of a WYSIWYG editor for generation of atomistic and FE meshes is presented. The program, the Visual Editor of Crystal Defects, has been written with the use of C++, Qt4 and OpenGL. Its successor, Wurtzite, written in Python, is also presented in brief.

Keywords:
dislocations, editor of crystal defects, distortion tensor fields, algebra of dislocations

Keywords:
Smart Airship, Sky Sailing, Aerostat Mobility, Flight Control

Abstract:
This study explores numerically and experimentally innovative control strategies for self-adaptive shock absorbers designed to operate under varying impact conditions. The control problem is addressed with a fundamental constraint – a limited prior knowledge of excitation parameters. To tackle this challenge, state-dependent control methods with progressively enhanced adaptive capabilities are proposed and evaluated numerically. A dedicated experimental setup featuring a pneumatic adaptive shock absorber is developed to ensure validation of the proposed methods and facilitate their comparison. The system incorporates a fast-operating piezoelectric valve with a strain gauge for proportional opening control and enables optimal real-time response to unknown dynamic excitations. The conducted laboratory drop test results confirm the feasibility of the proposed control methods.

Keywords:
Adaptive Impact Absorption, Self-Adaptive System, Pneumatic Shock Absorber

Abstract:
The effectiveness of the patented grip for high-temperature fatigue testing was assessed through the determination of the S-N curve for the full-scale nickel-based turbine blades operating under their environmentally simulated conditions. Before fatigue investigations, a bending test was performed to reflect the stress-displacement characteristics of the component examined. Subsequently, a series of fatigue tests were carried out at 950°C under a cyclic bending for selected values of force amplitude (5.2 kN – 6.6 kN) and frequency equal to 10 Hz. The proposed setup involving a grip fixed to the conventional testing machine was effectively used during high-temperature tests since the service life of the full-scale components was successfully determined

Keywords:
fatigue, high temperature, turbine blade, full-scale fatigue test

Abstract:
Dobór kruszyw mineralnych pod kątem odporności na wystąpienie szkodliwej reakcji alkalia-kruszywo jest jednym ze znanych wymagań stawianych przy projektowaniu betonu trwałego w środowisku wilgotnym, ewentualnie narażonego na oddziaływanie soli odladzających. Znaczenie reaktywności alkalicznej kruszywa drobnego (piasku naturalnego) wzbudza niekiedy kontrowersje. Przeprowadzono badania doświadczalne reaktywności alkalicznej mieszaniny kruszyw o zróżnicowanym składzie mineralnym – grysów szarogłazowych i amfibolitowych z piaskiem naturalnym z różnych kopalń. Do oceny reaktywności kruszyw wykorzystano metodę „Miniature Concrete Prism Test” (MCPT) polegającą na oznaczaniu ekspansji próbek betonu w roztworze NaOH w temperaturze 60°C w okresie do 84 dni. Wyniki badań wykazały znaczny wpływ reaktywności piasku na ekspansję betonu oraz na resztkową wytrzymałość betonu na ściskanie. Wykazano korelację zmierzonej ekspansji próbek z obniżeniem dynamicznego modułu sprężystości betonu. Z uwagi na rozsądnie niedługi czas badania i brak konieczności rozdrabniania kruszywa metoda MCPT okazała się praktyczną alternatywą dla innych metod określania reaktywności alkalicznej kruszywa, oferując jednocześnie możliwość oceny praktycznego stosu okruchowego

Abstract:
The notion of rank of a Boolean function has been a cornerstone in PAC learning, enabling quasipolynomial-time learning algorithms for polynomial-size decision trees. We present a novel characterization of rank, grounded in the well-known Transformer architecture. We show that the rank of a function f corresponds to the minimum number of Chain of Thought (CoT) steps required by a single-layer Transformer with hard attention to compute f. Based on this characterization we establish tight bounds on the number of CoT steps required for specific problems, showing that ℓ-fold function composition necessitates exactly ℓ CoT steps. Furthermore, we analyze the problem of identifying the position of the k-th occurrence of 1 in a Boolean sequence, proving that it requires k CoT steps

Abstract:
This study applies the machine learning technique of multi-agent reinforcement learning for semi-active structural control. The considered structure is a high-rise shear-type building subjected to seismic excitation, where actuators function as viscous dampers with a controllable level of damping. The problem formulation is inherently nonlinear due to the bilinear nature of the control concept. The analytical derivation of optimal semi-active control solutions is seldom feasible, leading to many practical control algorithms being suboptimal and/or heuristic in their formulation. In the framework proposed here, the control algorithm is developed through interaction with the controlled system by applying actions, observing results, and optimizing effects. For this purpose, a multi-agent reinforcement learning Q-network architecture is employed. Verification is conducted through a numerical experiment, utilizing a finite element model of a structure equipped with a tuned mass damper and a controllable viscous damper. The results demonstrate that the proposed method outperforms a conventional, optimally tuned TMD. This study also includes a comparison of the obtained results with those achieved using the typical single-agent approach. The key contribution is to demonstrate a significant improvement in control performance through the application of a multi-agent policy.

Keywords:
Structural control, Reinforcement Learning, Multi-agent, Damping, Vibration

Abstract:
This contribution addresses the problem of adaptively tuning the parameters of semiactive devices to mitigate vibrations in structures subjected to unknown periodic excitation. Using a specially designed reinforcement learning algorithm, the semi-active devices adjust their operating parameters to ensure optimal dissipation of vibrational energy. The algorithm incorporates an efficient gradient-based sequence that ensures rapid convergence of the learning process and enables real-time implementation under varying excitation characteristics. The method is experimentally validated on a frame structure equipped with lockable joints, which can be controlled to adjust their stiffness parameters. Since the developed reinforcement learning algorithm incorporates partial knowledge of the structural model, the first part of the work is focused on formulating a simplified numerical model that is easy to identify and scale.

Keywords:
Vibration attenuation, Reinforcement Learning, Semi-active control, Adaptive structure, Stiffness control

Abstract:
The paper introduces an original method for accurate positioning of an unmanned aerial vehicle (UAV) operating within a magnetic anomaly field. To estimate the UAV’s position in GNSS-denied environments, the proposed positioning method relies on particle filtering with an enhanced velocity propagation model. This approach employs
data fusion of kinematic measurements from the Inertial Measurement Unit (IMU) and magnetic field readings from a scalar magnetometer, which are correlated with a magnetic
anomaly map. Notably, this method utilizes magnetic field measurements in two distinct ways. Firstly, the rate of change of the magnetic field along the UAV’s trajectory is fed to the propagation model where the Bayesian inference is used to fuse the IMU and magnetometer measurements to estimate the particles velocity. Then, the absolute magnetic
field values are compared with a magnetic anomaly map to recompute the particles’ weights and refine the position estimate. The method was tested offline using in-flight recorded data. The analyses demonstrated the high performance of the particle filter with the enhanced velocity propagation model compared to dead reckoning navigation. As a result, the UAV’s position error was significantly reduced. The study also includes a discussion on the method’s robustness under different levels of IMU errors and the accuracy of magnetic field measurements.

Keywords:
magnetic anomaly navigation, Particle Filter, Bayesian inference, unmanned aerial vehicle, sensor fusion

Abstract:
The contribution presents an original method for accurate positioning of an unmanned aerial vehicle (UAV) operating in GPS-denied environment, where GNSS signals may be jammed or spoofed. The proposed approach uses Particle Filtering with an enhanced velocity propagation model to estimate the UAV’s position within a magnetic anomaly field. The velocity is estimated based on data fusion of kinematic measurements from an Inertial Measurement Unit (IMU) and magnetic field readings from a scalar magnetometer, which are compared
with a magnetic anomaly map. Magnetic field measurements are incorporated at two stages. First, the rate of change of the magnetic field along the UAV’s trajectory is introduced into
the propagation model using the Bayesian inference to fuse IMU and magnetometer data for a more accurate velocity estimation. Second, measured magnetic field values are compared with the anomaly map to recalculate the particle weights and refine the position estimate. The proposed
method was validated using in-flight data. The UAV positioning error was significantly reduced. The results confirm the effectiveness of the proposed and emphasize the high performance of the Particle Filter with enhanced velocity propagation model compared to traditional
dead reckoning navigation.

Keywords:
Magnetic Anomaly Navigation, Unmanned Aerial Vehicle, Particle Filter, Sensor Fusion, Bayesian Inference

Abstract:
We propose the first method to show theoretical limitations for one-layer softmax transformers with arbitrarily many precision bits (even infinite). We establish those limitations for three tasks that require advanced reasoning. The first task, Match 3 (Sanford et al., 2023), requires looking at all possible token triplets in an input sequence. The second and third tasks address compositionality-based reasoning: function composition (Peng et al., 2024) and binary relations composition, respectively. We formally prove the inability of one-layer softmax Transformers to solve any of these tasks. To overcome these limitations, we introduce Strassen attention and prove that, equipped with this mechanism, a one-layer transformer can in principle solve all these tasks. Importantly, we show that it enjoys sub-cubic running-time complexity, making it more scalable than similar previously proposed mechanisms, such as higher-order attention (Sanford et al., 2023). To complement our theoretical findings, we experimentally studied Strassen attention and compared it against standard (Vaswani et al, 2017), higher-order attention (Sanford et al., 2023), and triangular attention (Bergen et al. 2021). Our results help to disentangle all these attention mechanisms, highlighting their strengths and limitations. In particular, Strassen attention outperforms standard attention significantly on all the tasks. Altogether, understanding the theoretical limitations can guide research towards scalable attention mechanisms that improve the reasoning abilities of Transformers

Abstract:
Understanding when learning is possible is a fundamental task in the theory of machine learning. However, many characterizations known from the literature deal with abstract learning as a mathematical object and ignore the crucial question: when can learning be implemented as a computer program? We address this question for universal online learning, a generalist theoretical model of online binary classification, recently characterized by Bousquet et al. (STOC´21). In this model, there is no hypothesis fixed in advance; instead, Adversary—playing the role of Nature—can change their mind as long as local consistency with the given class of hypotheses is maintained. We require Learner to achieve a finite numer of mistakes while using a strategy that can be implemented as a computer program. We show that universal online learning does not imply computable universal online learning, even if the class of hypotheses is relatively easy from a computability- theoretic perspective. We then study the agnostic variant of computable universal online learning and provide an exact characterization of classes that are learnable in this sense. We also consider a variant of proper universal online learning and show exactly when it is possible. Together, our results give a more realistic perspective on the existing theory of online binary classification and the related problem of inductive inference

Abstract:
Despite the success of the GōMartini approach in capturing large conformational changes in proteins associated with mechanical forces in the order of hundreds of piconewtons and under different biological environments that affect the protein conformations, a systematic comparison is not yet available between the early implementation in Martini 2 coarse-grained (CG) force field and the recent version in the Martini 3 CG force field. The latter approach has been validated against experimental and all-atom molecular dynamics (AAMD) data and currently can be found in the Martini Force Field Initiative. We validate both approaches in two scenarios where large conformational changes are observed: (1) the thermal unfolding of wheat germ agglutinin domains, which has been extensively characterised through both in vitro experiments and AAMD simulations and (2) the nanomechanics of the Cohesin:dockerin-X domain complex, also studied via single-molecule force spectroscopy, which is crucial for understanding the self-assembly of the multi-enzyme cellulosome complex and function in cellulose-degrading bacteria. Moreover, our observations are contrasted with a recent structure-based approach that employs a new set of Gō interactions denoted as OLIVES in the Martini 3. Finally we aim to provide a comparative analysis that focuses on the ability of these CG models to replicate the intricate dynamics and interactions of proteins during non-equilibrium processes at time scales beyond AAMD simulations. Our results will delineate the pros and limitations of each approach in exploring large conformational changes in proteins and they will offer targeted suggestions for refining these approaches, enhancing their accuracy and predictive capabilities in biomolecular simulations.

Keywords:
MD, Coarse-graininig, Martini 3, GōMartini, Protein, Nanomechanics

Abstract:
The development of acoustic materials with broad spectrum efficiency remains a critical challenge, particularly for achieving effective low-frequency absorption. This study presents a composite sound absorber that combines a dense, conventional felt matrix with additively manufactured 3D printed inclusions designed to enhance low-frequency attenuation. These inclusions, fabricated using cost-effective Fused Filament Fabrication (FFF) technology, feature labyrinthine geometries with high tortuosity, designed to achieve subwavelength resonances. The combination of these elements results in a thin, lightweight, and scalable solution for sound attenuation. The design procedure developed for such composites is based on complex but fully analytical modelling. The composite material exhibits exceptional performance, achieving high levels of absorption at the designed low frequency due to inclusions, while maintaining efficient broadband characteristics of the matrix. The analytical predictions are confirmed experimentally by impedance tube measurements. By leveraging the advantages of additive manufacturing and conventional materials, this work paves the way for economically viable, tailored acoustic solutions.

Keywords:
Acoustic composites, Conventional porous matrix, 3D printed labyrinthine inclusions, Multiscale modelling, Sound absorption

Abstract:
In this paper, a modern, reinforcement learning-based semi-active vibration control strategy is presented. Three different reinforcement learning algorithms are used to determine the control of the vibration process of a cantilever beam modeled as a system of two rigid links connected by a rotational spring. The control is achieved by blocking the connections between the links. This effect is achieved by introducing an equivalent rotational viscous damper. The obtained control signals are compared with the instantaneous optimal control, which greedily transfers the vibration energy from one mode to another. The quality of the control signal obtained using reinforcement learning confirms the ability of such algorithms to obtain results consistent with the analytical solution.

Keywords:
semi-active control, vibration mitigation, reinforcement learning, lockable joints, modal analysis, structural dynamics

Abstract:
The paper presents theoretical and experimental studies on the original multi-resonant sound-absorbing material. A representative geometry of the material contains several channels (disjoint pore networks) of contrasting tortuosity. For the assumed material thickness, one can estimate the quarter-wavelength resonance frequency of each channel based on its tortuosity. The proposed estimate is sufficiently accurate or can be systematically adjusted to eliminate the predictable error. It can therefore be used to design a very effective sound-absorbing layer by tuning the resonance frequencies. This is because the sound absorption peaks for such a layer backed by a rigid wall occur at the resonant frequencies. The tuning is performer by tailoring the shape of the channels to obtain contrasting tortuosities that should distribute their corresponding resonant frequencies over the desired, wide frequency range. In this way, broadband absorption can be achieved. An additional goal of tailoring the channels is to fit them tightly inside the representative space of the material while maintaining their separation. In the proposed material design, all shapes and characteristic sizes are suitable for additive manufacturing, so a sample of the material was 3D printed. It was tested in an impedance tube for sound absorption to validate the theoretical results.

Keywords:
Sound absorption, Separated pore networks, Quarter-wavelength resonances, Acoustic metamaterials

Abstract:
Microfluidic systems offer precise control over fluid flow and microscale environments, making them powerful tools for high-throughput analysis, manipulation, and imaging of cells or droplets. A central aim of our research is to develop microfluidic platforms tailored to the specific needs of biological and medical research. One of our most advanced technologies, currently in commercial prototype development, is a microfluidic system for single-cell oxygen saturation and release imaging. Developed in close collaboration with the University of Oxford, it enables a detailed assessment of red blood cell function [1, 2]. The system was successfully applied to study human kidneys perfused with stored blood during transplantation, where organ respiration was monitored under cold perfusion [3]. The findings revealed a strong correlation between kidney oxygen consumption and erythrocyte oxygen-release
capacity – challenging the conventional notion that oxygen delivery is determined solely by blood flow and oxygen content.
In parallel, we developed microfluidic devices capable of generating mechanical gradients in epithelial tissues through controlled deformation. In partnership with the University Grenoble Alpes, we investigated how curvature influences calcium signaling and gene expression in epithelial monolayers, providing new insights into tissue morphogenesis and mechanotransduction [4].
We also developed systems for single-cell immobilization and manipulation, enabling long-term observation of isolated cells or spheroids in individual
droplet incubators or microscale cell traps, with several hundred replicates achievable in a single experiment.
These cell traps were used to study the formation of immunosuppressive niches in Hodgkin lymphoma by analyzing interactions between CAR-T lymphocytes and cancerous B-cells at single-cell resolution. Finally, we present a static droplet microfluidic incubator designed for dynamic, long-term culture of bacterial and mammalian cells with real-time, singlecell monitoring. Utilizing a controlled coalescence mechanism, the device supports versatile, automated nutrient delivery and waste removal protocols, which can be tailored to the specific requirements of different cell types. In vitro studies confirmed its effectiveness in sustaining long-term cultures of E. coli and A549 epithelial cells under optimized shear stress conditions. The results showed improved cell growth, as well as controllable cell organization—supporting the formation of either confluent monolayers or 3D spheroid-like structures. The device’s modular design allows seamless integration with upstream and downstream microfluidic components, as well as closed-loop feedback control systems. Together, these advances highlight the potential of microfluidics to investigate complex biological phenomena with high precision and throughput, supporting diverse applications in cell biology, transfusion medicine, organ preservation, immunology, and drug discovery.

Abstract:
This research on aluminum matrix FGMs was driven by an application to brake disks, which require advanced materials with improved wear resistance on the outer surface and effective heat dissipation of the graded disk. The AlSi12/Al2O3 composite layers with a stepwise gradient in the volume fraction of alumina reinforcement were prepared by hot pressing (HP) and spark plasma sintering (SPS) techniques. The thermal conductivities of the individual composite layers and the FGM specimens were evaluated experimentally and by numerical simulations using finite element models based on micro-computed X-ray tomography (micro-XCT) images of actual AlSi12/Al2O3 microstructures. An incongruity was identified between the thermal conductivity of the pure AlSi12 samples consolidated by hot pressing and spark plasma sintering. The primary reason for the disparity in thermal conductivity between the SPS and HP samples was ascertained to be the difference in grain size, as revealed by SEM analysis. The micro-XCT-based FEM simulations incorporated the effects of porosity, thermal resistance, and imperfect interfaces between the AlSi12 matrix and the alumina particles. The simulation results align well with the experimental data for various compositions and FGM structures.

Keywords:
Aluminum-Alumina FGMs, Powder Metallurgy, Thermal Conductivity, Micro-XCT, Finite Element Analysis

Abstract:
Microfluidics, a multidisciplinary area bridging physics, biology, and chemistry, has grown remarkably due to its ability to manipulate fluids at microscales [1]. Our work emphasizes the design and refinement of microfluidic devices that enable controlled droplet generation and manipulation [2,3], with practical applications in life sciences and chemical analysis.
By utilizing two-phase flows in confined channels, we engineer systems that exploit droplet-based transport, enabling precise sample encapsulation and reagent handling. Innovative passive control elements and capillary-hydrodynamic circuits are incorporated to guide droplet behavior without external actuation, offering compact and programmable platforms [4–7].
Algorithmic strategies complement our physical designs: digital droplet merging and splitting are used to achieve dynamic concentration control, improving reproducibility and flexibility of biochemical protocols [4,8].
Biomedical applications of our research include microfluidic chambers tailored for cell culture under biomimetic mechanical stress [9]. In collaboration with Université Grenoble Alpes, we investigated epithelial tissue mechanics, revealing how curvature modulates calcium signaling and gene expression. Another system, developed with the University of Oxford, allows us to measure oxygen unloading kinetics from erythrocytes using ultra-fast medium exchange and fluorescence microscopy [10].
These tools have proven effective in real-world scenarios, such as evaluating oxygen delivery efficiency during human kidney perfusion in transplant settings [11]. We demonstrate that red blood cell behavior, rather than blood flow alone, governs tissue oxygenation, contributing to a revised understanding of oxygen delivery metrics [12].
Our results underscore the potential of microfluidic systems not only as precise fluid manipulators, but also as transformative platforms for biological experimentation and diagnostics.

Keywords:
SPIONs nanocomposites, zinc-doped structures, boron-doped structures, melanoma

Abstract:
Accurate preoperative differentiation of thyroid cancer subtypes is essential for optimizing treatment strategies, particularly in the context of rising incidence rates and increasing use of active surveillance. This study investigates quantitative ultrasound biomarkers based on calcification patterns and tumor margins for distinguishing papillary, follicular, and medullary thyroid carcinomas. The analysis included 110 patients with histopathologically confirmed diagnoses. Tumor boundaries were refined using an energy minimization algorithm, and calcifications were classified by size and location. Margin characteristics were quantified using contrast variance. Each feature demonstrated an AUC > 0.75, with combined biomarkers achieving an AUC of 0.92 for follicular carcinoma detection (sensitivity: 0.87, specificity: 0.76). The results highlight the potential of quantitative assessment of calcifications and margins to enhance ultrasound-based classification of thyroid cancer subtypes.

Keywords:
thyroid cancer, ultrasound, calcifications, tumor margins, quantitative imaging, computer-aided diagnosis

Keywords:
antibacterial hybrid mesoporous silica

Keywords:
mesostructured silica materials , rice husk ash upcycling , antiseptic, electrochemical properties

Abstract:
Sintering is a thermally activated process that depends on many technological factors, such as
temperature, time, external pressure, atmosphere, etc. [1]. The progress of sintering, measured by an
increase in the cross-sectional area of the intergrain neck and a decrease in the distance between the
centres of two adjacent grains, leads to an increase in the density of the material. A great increase in
interest in field assisted sintering techniques has been evident in recent years. The main advantage of
the Spark Plasma Sintering technique is the direct resistive heating of graphite elements and
electrically conductive powders [2]. Due to the high heating rates (up to 1000 C/min) and short
dwelling time at the sintering temperature, the limitation of undesirable material reactions and
structural transformations can be obtained.
The goal of the presented work was to investigate the changes in the microscopic and macroscopic
parameters related to the microstructure of the NiAl and NiAl-Al2O3 composites and its dependence
on the sintering parameters (temperature and pressure). The materials were densified using Spark
Plasma Sintering method. The applying of diversified sintering parameters allowed to obtain a
materials with different relative density (from 70.0 to 97.5%). The analyses included SEM investigations
by electron backscatter diffraction to evaluate the crystallographic orientation of NiAl grains and
microcomputed tomography to visualize the grain evolution at different stages of sintering, especially
the grain size, shape and boundary contact features. The application of the electric current resulting in
high temperature and the additional external loading leads to the significant changes in the structure
of sintered materials, such as the occurrence of lattice reorientation resulting in grain growth, increase
in the grain neighbors, or the evolution of grain ellipticity, circularity, grain boundary length, and
fraction.
[1] German, R.M. (1996) Sintering Theory and Practice, A Wiley Interscience Publications, New York,
[2] Trapp, J., Kieback, B. (2019) Fundamental principles of spark plasma sintering of metals: part I
Joule heating controlled by the evolution of powder resistivity and local current densities. Powder
Metallurgy, 62(5), 297 306.

Abstract:
Metal matrix composites (MMCs) are an important class of materials in which the microstructure can
be tailored to have superior properties by comparison with non-reinforced alloys. Depending on the
manufacturing process, MMC can be more complicated than just a two-phase material combination.
Due to solubility and temperature-driven diffusion, another phase is formed between two phases of
the composite, which exhibit properties quite different from those of its surroundings. Such interphase
plays a critical role in the composite. It may not only modify the physical properties of the composite
but also change the quantitative global behavior of the composite material [1].
The proposed research investigates how variations in the plasticity and damage parameters of the
interphase influence the effective mechanical properties of a representative volume element (RVE)
representing a metal matrix composite (MMC). This study is driven by the understanding that the
mechanical properties of the interphase, often not well characterized, can significantly affect the
overall behavior of the composite. To explore this, a finite element (FE) model was employed to
simulate the composite's effective response, with interphase properties ranging from highly brittle
with low ductility and toughness to highly ductile, resembling the matrix material. The numerical
simulations were performed on the example of sintered nickel-silicon carbide composite, where the
interphase characteristics depend on the manufacturing process. The modeling approach utilized
several advanced frameworks:
The Gurson-Tvergaard-Needleman model for the matrix
An elastoplastic model with damage for the interphase/particle
A cohesive zone model for the interface
It shows the significant influence of interphase properties on stress-strain evolution, fracture modes,
and effective composite properties - ultimate tensile strength, fracture strain, and toughness. Each
composite component's deformation and damage behavior (matrix, interphase, particle, interfaces)
has been studied. As the yield stress, hardening curve, and fracture strain of interphase together with
interface strength and its fracture energy evolved, more than six fracture modes have been observed,
which is the key to the mechanical performance of a complex three-phase system.

Abstract:
Silicon carbide (SiC) is characterised by good thermal and electrical conductivity, and high hardness
and mechanical strength. Due to its unique properties SiC is applied as the reinforcement in metal
matrix composites to improve their thermal, mechanical and wear properties. Ni-SiC composites are
widely used in the automotive industry (pistons, brake discs), aviation and aerospace industries
(engine components), as structural materials for the molten salt reactors, as well as in electronics (as the
layered materials).
Comprehensive investigation of the influence of the main process parameters of spark plasma
sintering on the mechanical and microstructural properties of nickel-silicon carbide composites
at various scales. Microstructure analysis performed by scanning and transmission electron
microscopy revealed a significant interfacial reaction between nickel and silicon carbide due to
the decomposition of silicon carbide. The chemical interaction of the matrix and reinforcement
results in the formation of a multicomponent interphase zone formed by silicides (Ni31Si12 or/and
Ni3Si) and graphite precipitates [1]. The influence of SPS on Ni-SiC composites was revealed by
implementing a multiscale experimental tests at three different scales (macroscopic, microscopic,
and nanoscale) [2]. The nanomechanical properties of composite components: metal matrix,
ceramic reinforcement, and the interface have been evaluated by nanoindentation testing. Next,
the deformation, strength, and fracture behaviour of the bonding zone of composite components
was determined by a microcantilever bending test on the microscale. Finally, a uniaxial tensile
test has been carried out to designate the effective mechanical performance of nickel-silicon
carbide composites at a macroscopic level.

Abstract:

Chrysanthemum × morifolium /Ramat./ Hemsl. is one of the most popular ornamental plants in the world, and its breeding remains a highly relevant topic. Recent years have been marked by the intensive development of nanotech-nology. Nanoparticles (NPs) easily interact with cells of living organisms, causing various effects. The research aim was to answer the question of whether nanoparticles can be used in chrysanthemum breeding as factors inducing vari-ability. In the experiment, CdS NPs, Co3O4 NPs, and Fe3O4@Co NPs were applied at the concentration of 75 mg·L-1
in the in vitro culture of internodes of chrysanthemum ‘Lilac Wonder’. The regeneration efficiency was determined,and the biochemical profile and stress response of adventitious shoots were verified. During further ex vitro cultiva-tion in the greenhouse, the color and type of inflorescence were assessed, and biometric measurements of the plants were performed. Genetic variability was verified using RADP and SCoT molecular markers. The use of CdS NPs and Co3O4 NPs limited the regeneration efficiency. The NPs-treated shoots accumulated less flavonols, more anthocyanins and polyphenols, and showed increased antioxidant capacity. The highest activity of oxidative stress enzymes (APOX,GPOX, SOD), and the lowest chlorophyll content were noted in CdS NP-treated shoots. The tested NPs also affected the further growth of plants during ex vitro cultivation. The longest stems were found in plants treated with Fe3O4@Co NPs, contrary to CdS NPs and Co3O4 NPs. The CdS NP-treated plants developed leaves with the smallest surface area,
perimeter, length, and width. Evaluation of inflorescences did not reveal qualitative variations in the color of ligulate
florets, however, quantitative changes related to anthocyanins content were noticed. The highest pigment content was found in ligulate flowers of Fe3O4@Co NP-treated plants. One individual (mutant) was phenotypically identified within Co3O4 NP-treated plants, with variegated leaves. The use of nanoparticles also induced genetic variation, with CdS NPs causing the most distinct polymorphic changes, as confirmed by both RAPD and SCoT markers. While Fe3O4@Co NPs and Co3O4 NPs also generated polymorphic genotypes, their effects were less evident, suggesting that NPs vary in mutagenic potential, but could serve as a novel tool for plant breeding.

Abstract:
As digital technologies become integral to modern education, cybersecurity has become a critical concern for educators, institutions, and policymakers. Schools are increasingly targeted by cyber threats such as phishing, ransomware, data breaches, and cyberbullying. These
incidents disrupt educational continuity and compromise the safety, privacy, and trust of students and staff. This paper explores the evolving cybersecurity landscape in educational environments, identifying systemic vulnerabilities and barriers to implementation—such as limited resources, lack of teacher training, and technological disparities. It highlights current strategies for strengthening cybersecurity, including secure learning management systems, two-factor
authentication, cybersecurity awareness training, and the integration of digital hygiene practices into curricula. A key contribution of this work is its focus on emerging cybersecurity concerns within artificial
intelligence applications, particularly neural networks used in educational tools. We examine vulnerabilities such as adversarial attacks, data poisoning, and model inversion, which threaten the integrity of Artificial Intelligence (AI) -driven learning systems. These issues are addressed through ongoing interdisciplinary research by our team, which aims to identify and mitigate risks at the intersection of education, data science, and neural computation. By combining policy analysis, educational best practices, and technical insights from AI security research, this study proposes a comprehensive, forward-thinking approach to cybersecurity. It advocates for a digital learning ecosystem that is secure, inclusive, and resilient against both current and future cyber threats.

Keywords:
nanoparticles, nanocomposites, SPIONs

Abstract:
This study compares three SNN training methods on MNIST: ANN-to-SNN [1], surrogate gradient backpropagation [2], and Tempotron learning [3]. All were trained under identical conditions. Key hyperparameters were optimized using Optuna, and the best configurations were used for retraining.

This two-stage approach improved accuracy and stability. ANN-to-SNN offered solid baseline performance, BP_Surspike achieved higher accuracy with greater cost, and BP_Tempotron balanced biological realism and efficiency.

These results confirm that learning method choice strongly affects SNN performance. Hyperparameter optimization, supported by Optuna, was key to achieving accuracy and training stability. The study also shows how Tempotron, surrogate gradient backpropagation, and ANN-to-SNN can complement each other in hybrid, biologically plausible SNN frameworks [4].

The author gratefully acknowledges the support of the Institute of Fundamental Technological Research, Polish Academy of Sciences.

Keywords:
spiking neural networks, hyperparameter optimization

Keywords:
poly-ion complex micelles, functional mesoporous materials, thin films

Keywords:
CEID- Effective Correlated Electron-Ion Dynamics

Abstract:
Gradual degradation of brittle composites exhibits different mechanical responses under uniaxial tension and uniaxial compression. In this paper, we analysed cracking processes and failure under quasi-static loading of a two-phase ceramic material made of an Al2O3 and ZrO2 mixture subjected to tension and compression. Constitutive modelling of two-phase ceramic composites obeys the description of: (1) elastic deformations of initially porous material, (2) limited plasticity and (3) cracks initiation and propagation.

Modelling of polycrystalline ceramics at the mesoscopic level under mechanical loading is related to the analysis of a set of grains, i.e. Representative Volume Element (RVE), Fig. 2. The basic elements ofthe defect structure inside a polycrystal are: micro- andmesocracks, kinked and wing cracks. To obtain a macroscopic response of the material, one can calculate averaged values of stress and strain over the RVE using an analytical approach.

High-strain-rate degradation process was illustrated for Al2O3/ZrO2 composite, which was subjected to a short compressive impulse. The pulse duration was 10- 7s, Fig. 3. In the proposed more advanced finite elements formulation, it was necessary to take into account the following data and phenomena appearing inside of the RVE: (1) spatial distribution of the composite constituents, (2) system of grain boundaries/binder interfaces modelled by interface elements, (3) rotation of brittle grains.

In the proposed more advanced finite elements formulation, it was necessary to take into account the following data and phenomena appearing inside of the RVE: (1) spatial distribution of the composite constituents, (2) system of grain boundaries/binder interfaces modelled byinterface elements, (3)
rotation of brittle grains.

Keywords:
impact, experiments, SHPB, numerical model

Abstract:
Nowadays, additive manufacturing (AM) is revolutionizing production, enabling the rapid fabrication of objects in various sizes and shapes, including complex designs such as metallic foam, while significantly reducing material waste. This paper examines the effect of 3D printing parameters (Set A and Set B) on the mechanical behavior of a highly porous random open-cell lattice (HPROCL) in IN718 alloy produced by selective laser melting (PBF-LM). The modified build parameters were applied to reduce manufacturing cost and time while minimizing micro porosity in ligaments by increasing exposure time through reduced laser scanning speed or higher energy density. Furthermore, the researchers investigate ligament deformation, key stages of collapse and stability, its role in impact resistance, and how microstructure influences the hardening behavior of the HPROCL across a wide range of strain rates. The SEM-EDS elemental distribution analysis carried out on the tested specimens enabled to conclude that the foam printed with modified parameters (Set B) contained a lower content of the Laves phase and a higher amount of the δ-phase, which led to an increase in both static and dynamic compressive behavior of HPROCL in IN718 alloy.

Keywords:
Additive manufacturing, Impact resistance, Highly porous random open-cell lattice, Inconel 718

Keywords:
cancellous bone, damage properties, parametric studies

Abstract:
Biomedical image datasets are often scarce, expensive to annotate, and vary in
quality due to differences in imaging hardware and techniques. Generative models, particularly diffusion models, have recently demonstrated strong potential to
synthesize realistic medical images, offering a promising strategy for data augmentation. Yet, their application in clinical contexts requires careful validation, as trust,
interpretability, and reliability are essential when medical decisions are at stake.
This work introduces a human-in-the-loop framework for assessing the reliability
and risks of diffusion models in generating breast ultrasound cancer images. Using a Denoising Diffusion Probabilistic Model (D-DDPM), we jointly generate
ultrasound images and corresponding tumor masks from two benchmark datasets
(BUS-BRA and UDIAT). The evaluation pipeline integrates quantitative image
quality metrics (FID, IS, KID), radiologist interpretation, inter-rater agreement
(Cohen’s/Fleiss’ Kappa, Krippendorff’s Alpha), and alignment with large language
model (LLM) outputs. Results show that while D-DDPM can produce images
that are visually similar to real data and sometimes yield higher agreement among
experts than original images, inter-rater reliability remains weak, particularly for
malignant tumors. Radiologists consistently outperform LLMs in classification,
though majority voting across experts improves diagnostic accuracy. These findings highlight both the promise and risks of diffusion models in medical imaging,
including that synthetic ultrasound data can supplement limited datasets; however,
robust expert validation remains indispensable to ensure clinical trustworthiness
and safe integration.

Abstract:
– Iwo Białynicki-Birula, Łukasz A. Turski; współtwórca Centrum Fizyki Teoretycznej PAN
– Magdalena Załuska-Kotur, Nauczyciel i popularyzator
– Maria Ekiel-Jeżewska, Nauka ma służyć dobru publicznemu
– Robert Firmhofer, Profesor Łukasz Turski. Wspomnienie
http://pauza.krakow.pl/729_2025.pdf

Abstract:
Recent developments in machine learning, together with the increasing availability of high-resolution structural data from cryo-electron microscopy, are positioning molecular simulations at the forefront of studying large biomolecular systems [1]. Together, these meth-ods underscore the need for computational strategies capable of capturing biologically relevant conformational changes over extended timescales. While all-atom molecular dynamics (AA-MD)simulations provide detailed, high-resolution insights, their application to megadalton protein complexes is limited by substantial computational costs.The recently introduced GoMartini 3 approach [2] extends the Martini 3 coarse-grained force field to study conformational changes in protein complexes, offering significant potential for biomedical and therapeutic applications. Here, we discuss alternative strategies that integrate dynamic protein contacts derived from AA-MD to more efficiently explore conformational space.We showcase several molecular studies and validated the new approach by investigating thenanomechanics of nanobodies binding to the SARS-CoV-2 spike protein as well as the long-timescale dynamics of full-length spike variants. The optimized framework is openly available athttp://pomalab.ippt.pan.pl/web/gomartini/index.html

Keywords:
Martini 3, Coarse-graininig, GoMartini 3, Proteins, MD, Free Energy, CV, Nanomechanics

Abstract:
This study explores an efficient decontamination strategy using platinum-coated polystyrene rough-particles as a micron-sized catalyst system for decomposing methylene blue (MB), a common organic pollutant. The synthesized nanomaterials were comprehensively characterized using Nanoparticle Tracking Analysis (NTA), Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM), confirming their morphology, size distribution, and surface properties. The decontamination was performed at the air-water interface through an interface trapping method, with enhanced mixing achieved under a controlled flow environment. The experiments were conducted with a circulation speed of 50 RPM, corresponding to a Reynolds number (NR) of 1686 and a high particle packing fraction of 0.8. Under these operating conditions, complete degradation of MB was achieved within 30 min, significantly faster than the 75 min required for degradation in the bulk phase. The reaction kinetics were analyzed and found to follow the Langmuir–Hinshelwood model, with an estimated rate constant of 0.018 min−1, indicating efficient surface-mediated catalytic activity. Furthermore, an Artificial Neural Network (ANN) model was developed to validate and predict the degradation kinetics, showing a Root Mean Square Error (RMSE) of 5.5 and a high correlation coefficient (R2) of 0.9656, confirming the reliability of the predictive model. This interface-assisted, catalyst-based degradation approach demonstrates a promising, reusable, cost-effective, and environmentally friendly solution for advanced wastewater treatment applications.

Keywords:
Methylene blue, Pt nanoparticles, Air-water interface, Wastewater, ANN modeling, Removal efficiency

Abstract:
This study synthesizes microencapsulated phase change materials (MePCM) from industrial waste-derived expanded polystyrene (EPS) nanoparticles using a surfactant-free Pickering emulsion for building applications in hot climates. EPS nanoparticles, synthesized via optimized nanoprecipitation technique with 70 % sonicator amplitude, serve as the MePCM shell with n-eicosane as the core. Characterizations show EPS nanoparticles with diameter of 150 nm and MePCM sizes predominantly around 12μm. MePCMs exhibit melting and solidification enthalpies of 301.4 J/g and 298.5 J/g, respectively, highlighting their potential for integration into building materials for enhancing thermal management of buildings in hot climate.

Keywords:
Expanded polystyrene, Nanoparticles, Pickering emulsion, Microencapsulated phase change material, Building application

Keywords:
shape memory alloys, interstitials, infrared thermography, digital image correlation

Keywords:
Pseudoelasticity, Phase transformation, Nano-indentation, Thermomechanical coupling

Abstract:
Anthropogenic emissions, particularly from industrial and agriculture activities, have significantly elevated the concentrations of highly toxic Heavy Metals (HMs), such as lead (Pb), cadmium (Cd), and arsenic (As), in the soil, leading to their accumulation in plants. These HMs, when exceeding toxicity thresholds (e.g., Pb >10 mg/kg, Cd >0.5 mg/kg, As >1 mg/kg), disrupt the plant physiology and metabolism. To mitigate this toxicity, plants employ diverse detoxification and sequestration strategies, including mycorrhizal associations, root exudates, cellular compartmentalization, and the production of organic acids, phytochelatins, metallothioneins, proline, stress proteins, and plant hormones. This review aims to critically examine the molecular mechanisms by which key crop plants, such as rice, wheat, maize, and other higher plants, sequester these primary heavy metal contaminants. Additionally, it highlights the role of nanotechnology in enhancing plant resistance and facilitating nano-bioremediation under HMs stress conditions. This review provides valuable insights into innovative clean-up strategies for agriculturally important crops by exploring nanoparticle -mediated remediation mechanisms.

Keywords:
Nano-bioremediation, Heavy metals remediation, HMs ATPase, ZIP family, Phytoremediation, Phytochelatins

Keywords:
numerical homogenization, representative volume element, cement paste