Other

Abstract:
Brush cytology is widely used for sampling mucosal surfaces, particularly during gastrointestinal endoscopy to detect malignancies in the pancreas and bile ducts. During brushing, mucus and detached cells are collected in the bristles through capillary action and flow eddies. However, a low cellular yield often limits diagnostic sensitivity. This work explores electrostatic interactions between cancer cells and oppositely charged bristles to enhance cell capture. Modifying the polyamide (PA) bristles with the polycation poly(ethylenimine) (PEI) enhanced their electrostatic affinity for negatively charged cancer cells. A physical analysis of electrostatic attraction and brushing induced hydrodynamic drag quantified forces on epithelial cancer cells near a charged bristle and the mucosal surface. Hydrodynamic drag increased with brushing velocity, and specific regions were identified where electrostatic attraction significantly contributes to cell trapping and balances the hydrodynamic forces. In vitro experiments with HeLa cells showed a 2-fold increase in attachment to the modified brush. Ex vivo brushing of porcine stomach tissue confirmed the approach, showing an ≈5-fold increase in cellularity, as verified by histology. These findings indicate that exploiting electrostatic attraction between cancer cells and oppositely charged bristles can significantly enhance the sensitivity and specificity of cytological brushing in a simple, efficient, and cost-effective manner.

Keywords:
endoscopic, brush cytology, electrostatic trapping, malignancy, biliary

Abstract:
This work analyzes the deformable discrete element method (DDEM) as a tool for modeling linear-elastic properties of single crystals of cubic symmetry. DDEM is an extension of the standard DEM, in which particles deform under stress. Through this deformation, an interaction between two particles becomes dependent on other interactions in which these particles participate. This nonlocal characteristic gives DDEM an enhanced ability to model solid materials. The present analysis is mainly focused on the simple cubic (SC) pattern of identical spherical DDEM particles bonded by cohesion, in the small-strain regime. It is shown that the majority of crystals of cubic symmetry can be modeled by this pattern in a numerically stable way. When simple geometric patterns other than SC are considered, it is argued that DDEM is able to represent the linear-elastic properties of all cubic crystals satisfying the Born stability criteria. This is an improvement upon the standard DEM, in which many cubic materials of high anisotropy cannot be modeled using simple particle arrangements. A number of numerical tests, complemented by analytical investigations, are performed to validate the approach and estimate its accuracy.

Keywords:
Discrete element method, Deformable particles, Cubic anisotropy, Linear elasticity, Crystal, NiAl

Abstract:
This study investigates the influence of crystallographic orientation on fracture behavior and the resulting mechanical anisotropy in a alloy crystal containing radiation-induced defects, using molecular dynamics (MD) simulations. Crack propagation is analyzed in irradiated samples with three selected high-symmetry crystallographic orientations to show how radiation-induced defects modify local deformation mechanisms and amplify mechanical anisotropy. The investigation focuses on the anisotropic nature of the ductile-to-brittle transition (DBT) driven by radiation-induced defects by simulating fracture behavior under tensile loading. Fracture resistance is quantitatively evaluated using a traction–separation (T–S) approach to extract the atomic-scale fracture energy under realistic defect conditions. The results reveal a strong crystallographic orientation dependence in the evolution of deformation and fracture behavior during DBT. The crystal lattice orientation governs dislocation activity and defect interactions, which in turn regulate local plasticity mechanisms, strain localization, slip system activation, and fracture resistance, thereby driving the development and enhancement of mechanical anisotropy in irradiated materials. It is further shown that radiation-induced embrittlement cannot be explained solely by defect accumulation, but rather by orientation-sensitive interactions among dislocations, defects, and fracture process zones. A key novelty of this work lies in integrating radiation-induced defect evolution with orientation-dependent fracture within an atomistic T–S analysis, enabling quantitative assessment of atomic-scale fracture resistance under realistic defect conditions.

Keywords:
Crack propagation, Radiation defects, MD simulations, Cr-rich alloy, T–S law, Atomic-scale fracture energy

Abstract:
This paper proposes a novel velocity estimation technique and integrates it with the particle filter to achieve precise positioning of an object moving within a magnetic anomaly field. To estimate the position in GNSS-denied environments, acceleration measurements acquired from the inertial measurement unit are combined with magnetic field measurements and a magnetic anomaly map. The magnetic field measurements are utilized at two levels. First, Bayesian data fusion is applied to process the rate of change of the magnetic field along the object’s trajectory in order to refine the velocity acquired from the inertial measurement unit. This refined velocity estimation serves as an input for the propagation model of the particle filter, which subsequently uses the magnetic field measurement and the magnetic anomaly map to estimate the object’s position. The proposed method was tested for navigating an unmanned aerial vehicle (UAV) using the ArduPilot simulator across a variety of realistic scenarios. The results demonstrate the efficacy of Bayesian-based velocity estimation in enhancing the classical particle filter approach, leading to a substantial reduction in the mean trajectory error. The developed method improves GNSS-independent positioning and navigation and holds promise for applications in various aircraft and robotic systems.

Keywords:
Magnetic anomaly navigation, Particle Filter, Bayesian inference, Unmanned aerial vehicle, Sensor fusion

Abstract:
Mode decomposition is a widely adopted data-driven strategy in modal analysis. It is an essential tool for identifying modal parameters and understanding the dynamic behavior of systems. However, existing mode decomposition methods often suffer from modal aliasing and lack clear physical interpretability. This study introduces a time-domain constrained mode decomposition method that employs a linear combination of free response signals to extract clean intrinsic mode functions and accurate modal parameters. A constraint matrix, derived from the autoregressive model of single-mode signals, is used to form a characteristic constraint equation and determine the decomposition coefficients. The influence of the autoregressive calculation time interval on the stability of Prony polynomial solutions is analyzed to determine the order and form of the constraint filter. Furthermore, combining the constraint filter with a low-pass FIR filter improves the noise robustness of the proposed method. For modal identification, the preliminary eigenvalues are determined using the Yule-Walker equation, followed by iterative elimination of spurious eigenvalues and refinement through the application of multi-objective constraint filters. Ultimately, the proposed method enables accurate, adaptive, and physically interpretable signal decomposition and modal parameter identification. Statistical results from numerical simulations validate its robustness to noise and stability, while comparisons with other mode decomposition techniques confirm that it achieves complete signal decomposition. Experimental verification using a frame test model further demonstrates the accuracy of the proposed method in modal identification.

Keywords:
Mode decomposition, Autoregressive model, Modal identification, Signal processing, Constraint filter

Abstract:
Molten carbonate electrolysis (MCE) is a promising high-temperature route to upgrade CO2-rich biogas into a higher heating value fuel while enabling CO2 separation and utilization. This paper proposes and experimentally evaluates a biogas upgrading concept based on a three-cell MCE stack operated on synthetic biogas mixtures. The stack is fed with CH4/CO2/H2O at the cathode and air at the anode and powered by external electricity, representative of surplus renewable power. Electrochemical performance is assessed through current-voltage characteristics and steady-state operation at selected current densities, while product-gas compositions are quantified by gas chromatography. The results demonstrate stable stack operation on biogas-type feeds and show that MCE can simultaneously remove CO2 and enrich the cathodic stream in H2 (and CO), thereby increasing the lower heating value compared with the raw biogas. From the measured data, key process indicators such as CO2 removal degree, gas upgrading factor, and specific electrical energy consumption are derived and discussed. The study establishes molten carbonate electrolysis as a viable and flexible option for biogas upgrading and valorization, particularly in systems coupled to intermittent renewable electricity. Unlike conventional separation-based routes (water scrubbing, PSA, membranes) that vent the captured CO2, or SOE-based power-to-methane systems that require a separate methanation reactor, MCE simultaneously removes CO2 and generates H2/CO within a single high-temperature unit. The present results provide the first experimental evidence that a multi-cell MCE stack can serve as a viable and load-flexible pathway for biogas upgrading and valorization, particularly when coupled with intermittent renewable electricity.

Keywords:
Molten carbonate electrolysis, Biogas upgrading, CO2 separation, High-temperature electrochemical conversion, Syngas and hydrogen enrichment

Abstract:
Rheumatoid arthritis (RA) is a chronic autoimmune disease driven by synovial immunopathology, where innate immune activity and neurobiological remodeling necessitate timely and precise diagnostic interventions. While
thermography provides a non-invasive window into the altered perfusion and thermal dynamics associated with such joint inflammation, its clinical adoption has been hindered by the computational demands of traditional
AI. We address this by proposing a novel Spiking Neural Network (SNN) framework that aligns diagnostic automation with the event-driven nature of physiological signals. By encoding spatial temperature patterns into
temporally structured spike trains, our approach introduces a biologically inspired static-to-dynamic translation, where temporal structure is computationally derived from spatial thermal distributions rather than directly measured inter-frame dynamics. To ensure statistical rigor, a strict patient-level data split was applied to a dataset of
291 healthy controls and 186 RA patients. We evaluated three SNN paradigms:Tempotron, Surrogate Gradient Learning (SGL), and Bio-Inspired Active Learning (BAL) to optimize the trade-off between diagnostic precision and efficiency. The Tempotron learning rule achieved a peak validation accuracy of up to 90.62% on a fixed patient-level split, demonstrating superior sensitivity to spatio-temporal signatures, while SGL offered the most efficient training convergence (563 s). Notably, our framework exhibits strong potential for reduced energy demands compared to traditional frame-based architectures. As one of the first studies to explore the intersection of neuromorphic computing and thermographic signatures associated with synovial inflammation, this study demonstrates the potential of spiking neural networks as lightweight and biologically inspired tools for automated RA screening in resource-constrained settings.

Keywords:
Spiking neural networks (SNN), Rheumatoid arthritis (RA), Thermographic imaging, Bio-inspired learning algorithms, Green AI, Neuromorphic computing

Abstract:
Activated carbons (ACs) are very attractive in terms of the preparation of electrode materials for supercapacitors (SCs). Their slurries are frequently deposited on the conductive current collectors. However, this approach is time-consuming and often requires multiple steps. To overcome these inconveniences, this work presents that the ACs can be successfully deposited on the stainless steel discs with the electrophoresis deposition (EPD) method using a small content of chitosan (CS) (∼0.7 wt %) as binder. Moreover, the second objective of this work is to check the compatibility of the obtained AC/CS electrodes with the poly(vinylidene fluoride-cohexafluoropropylene) (PVDF-HFP) gel polymer electrolytes (GPEs) filled with three different salts (LiClO4, NaClO4, and Mg(ClO4)2) dissolved in propylene carbonate. The use of GPEs enables long-term and safe operation up to 10,000 cycles with a capacitance retention over 55% at an electrochemical stability window of 2.6 V for all investigated cells. Nevertheless, the SC cell containing the NaClO4 salt reveals the greatest electrochemical performance. It achieves a specific capacitance of 35.1 F g–1 (measured at 2 A g–1), capacitance retention of 84.5% after extended charge–discharge cycling, and an energy density of 35.1 W h kg–1 at a power density of 5.2 kW kg–1. The obtained results indicate that EPD and a low-content CS can be effectively used to prepare AC-based electrodes for SCs equipped with GPEs

Abstract:
Fullerene-based polymer nanocomposites are promising candidates for micro- and nanoelectromechanical systems (MEMSs/NEMSs) due to their tunable mechanical performance and high surface-to-volume ratios. At the nanoscale, interfacial stresses strongly influence the effective elastic response, yet quantitative interface parameters are rarely available for continuum modeling. In the current investigation, a molecular dynamics (MD)-based calibrated micromechanics framework is developed to predict the bulk modulus of fullerenepoly(methyl methacrylate) (PMMA) nanocomposites that incorporate interface stress effects. Atomistic representative volume elements (RVEs) containing individual fullerene nanoparticles embedded in a polymer matrix are generated using controlled molecular packing and systematically equilibrated. The bulk moduli of both isolated fullerenes and fullerene-PMMA RVEs are extracted from energy-volume relationships using a Birch-Murnaghan equation of state. These MD results are used to calibrate a size-dependent micromechanics model and to extract the surface Lamé modulus of the polymer-fullerene interface directly. The extracted surface Lamé modulus remains nearly constant (approximately 19 N/m) across all investigated fullerene sizes. In contrast, the interfacial contribution to the effective bulk modulus increases significantly for smaller nanoparticles due to their higher surface to volume ratios. The calibrated model accurately reproduces MD predictions and provides a physically grounded multiscale link between atomistic interfacial behavior and continuum elastic properties. The proposed framework offers a predictive tool for the rational design of surface-dominated nanocomposites in MEMS/NEMS applications.

Keywords:
molecular dynamics simulation, nanocomposites, interface effect, micromechanics

Abstract:
In this paper, a strictly variational, rate-independent micropolar (or Cosserat, equivalently) crystal-plasticity framework is developed, aimed at capturing the spontaneous emergence of deformation bands in metallic single crystals. The incremental energy minimization approach is extended to encompass the Cosserat model of crystal plasticity at small strain by embedding it in the thermodynamic framework of gradient plasticity with energetic forces. It is shown that all balance equations and constitutive inequalities, including the consistency conditions, are then retrieved by minimizing the derived incremental energy function. The energetic preference of deformation banding is predicted analytically when the cross-hardening of slip systems exceeds their self-hardening and the band wavelength exceeds the established minimum value. To enhance clarity of the main concept, the simplest version of the Cosserat crystal plasticity is employed, and the examples are calculated using a plane-strain model in which the twelve fcc slip systems are reduced to three effective plastic slip mechanisms. The implementation of the incremental energy minimization scheme within the finite element numerical code has enabled automatic reproduction of deformation bands without resorting to artificial perturbations or geometric imperfections. In contrast to the more frequently analyzed case of isolated shear bands, the entire domain becomes filled with a laminated pattern formed by deformation bands with alternating slip-system activity. The simulations demonstrate the capacity of the Cosserat crystal plasticity model, when embedded in the incremental energy minimization approach, to predict and regulate complex deformation patterns, incorporating internal interfaces and length-scale effects.

Keywords:
Crystal plasticity, Small strain, Slip-system selection, Path instability, Microstructure formation, Finite element method

Abstract:
Accurate determination of hanger rod tension in large suspended steam boilers of combined heat and power plants is essential for maintaining safe load distribution, preventing structural instability, and ensuring long-term operational reliability. This study proposes a vibration-based method for non-invasive tension identification, explicitly adapted to the boundary conditions and suspension configurations encountered in combined heat and power plants. The approach integrates in-house developed, battery-powered wireless accelerometers, deployed in an operational environment of combined heat and power plants, to acquire high-resolution, multidimensional vibration data suitable for both rapid inspections and continuous monitoring.
A comparative assessment of analytical formulations, including ideal string, Euler-Bernoulli beam and Timoshenko beam models, is conducted to identify the representation most appropriate for the dynamic behaviour of hanger rods under realistic operating constraints. The selected model is validated through experimental investigations on a full-scale installation of combined heat and power plants. Benchmarking against the industry-standard hydraulic “lift-off” method demonstrates the accuracy and reliability of the proposed procedure.
The results confirm that the developed system constitutes a robust, rapid, and cost-effective alternative to conventional techniques, reducing measurement time while preserving high accuracy. The findings address three critical questions: (i) the selection of a suitable vibration-based method analytical model for hanger rods of combined heat and power plants, including long-term operation units; (ii) the feasibility of quick and straightforward in situ tension measurements in rods without prior load history; and (iii) the potential for substantial reduction in measurement time compared with the “lift-off” method. The validated methodology provides a basis for future normative guidelines on hanger rod tension assessment in of combined heat and power plants.

Keywords:
Steam boilers, Structural health monitoring, Axial force estimation, Modal analysis, Industrial diagnostics

Abstract:
Conducting polymer–transition metal hybrid materials are highly promising supercapacitor electrodes. Herein, we report the one-step electrosynthesis of a ternary electrode based on polyaniline (PANI) co-doped with Cu2+ and Co2+ ions. Using X-ray photoelectron spectroscopy (XPS), elemental composition of the prepared materials were determined. While the crystalline structure and functional groups were identified using diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). Scanning Electron Microscopy (SEM) analysis demonstrated a distinct morphological shift from the typical fibrous network of pure PANI to a unique microflower structure in the PANI-(Cu-Co). Electrochemical measurements of the PANI-0.1 M (Cu-Co) electrode in 0.5 M HCl exhibit a higher specific capacitance of 610 mF cm⁻2 at 1 mA cm⁻2 current density, significantly higher than pure PANI (209 mF cm⁻2 / 254.21F g⁻1). In line with electrochemical impedance spectroscopy (EIS), dispersion-corrected density functional theory (DFT) calculations revealed a reduced HOMO-LUMO band gap, indicating better charge transfer. These results demonstrate that adding Cu-Co greatly improves PANI electrochemical performance as well as demonstrating its suitability as an optimized electrodes for advanced supercapacitors.

Keywords:
Polyaniline, Cu–Co doping, Supercapacitors, Hybrid electrodes, Electro polymerization, Density functional theory

Abstract:
This paper critically evaluates the current state-of-the-art material, LiAlO2, used in the matrices of molten carbonate fuel cells (MCFC) and explores alternative material solutions to extend their operational lifetime and efficiency. Despite its prevalent use due to high stability and corrosion resistance, LiAlO2 fails to meet the long-term operational demands of MCFCs. This study extends the discourse beyond the conventional LiAlO2/K2CO3: Li2CO3 system, proposing optimizations in matrix structures through the integration of various material-matrix solutions. We delve into the fundamental aspects influencing matrix strength, including particle size, surface tension, and thermal expansion coefficients, to understand their impact on the mechanical integrity and functionality of the matrix in highly corrosive environments. Theoretical insights and experimental validations are presented to support the feasibility of alternative materials in enhancing MCFC performance. This paper not only contributes to the material science field by addressing the limitations of current MCFC technologies but also opens new avenues for the development of more robust and efficient fuel cell systems.

Keywords:
Molten carbonate fuel cells (MCFC), LiAlO2 matrix, Material optimization, Surface tension, Thermal expansion coefficients, Mechanical strength

Abstract:
Equiatomic AlCoCrFeNi high-entropy alloy (HEA) and its rhenium-modified variant (AlCoCrFeNi–1 at% Re) were synthesized via mechanical alloying followed by hot pressing. This study demonstrates that minor, classical alloying with only 1 at% Re significantly enhances mechanical and thermal stability without altering the base processing route. Both alloys exhibited a dual-phase FCC–BCC structure with M₂₃C₆ carbides. Rhenium promoted Cr–Re solid solution formation during milling, refined the post-sintering microstructure, improved densification, and modified lattice parameters. The Re-containing alloy showed nearly a threefold increase in flexural strength at room temperature and moderate improvements in tensile strength at room and elevated temperatures (750–900 °C). Dilatometry and post-deformation XRD analyses revealed temperature-induced phase evolution. The Re-modified alloy exhibited smoother thermal expansion behavior and improved high-temperature stability. The principal advantage of this investigation lies in demonstrating that a minor Re addition effectively enhances the strength and microstructural stability of mechanically alloyed and hot-pressed HEAs without complex processing modifications.

Keywords:
Mechanical alloying, Rhenium, High-entropy alloys, High-temperature tests, Hot-pressing

Abstract:
Recent advances in single-cell technologies have revealed the dynamic and heterogeneous nature of host-pathogen interactions at the single-cell level. This review explores how cellular variability—both within clonal bacterial populations and among genetically identical host cells—gives rise to distinct infection outcomes, from pathogen clearance to persistence across multiple biological scales, from single cells to tissues and the whole organism. We highlight the conceptual and technological progress that has enabled the dissection of these interactions at single-cell resolution, including microscopy, single-cell transcriptomics, proteomics, and emerging dual RNA-seq and spatial approaches. Drawing on examples from well-characterized bacterial pathogens like Listeria monocytogenes, Salmonella enterica, and Mycobacterium tuberculosis, we discuss how stochastic gene expression, intrinsic and extrinsic factors, as well as tissue context shape the variable activation of the immune responses and ultimately determine the outcomes of host-pathogen interactions. We argue that the outcome of single-cell interactions is shaped by a combination of host states, bacterial-intrinsic features, and the local microenvironment. We further discuss how computational and mathematical modeling can integrate these heterogeneous single-cell events across spatial scales, linking intracellular variability with tissue-level pathogenesis and progression of infection. Gaining insight into and controlling these layers of variability holds promise for the development of more precise, context-dependent antimicrobial strategies.

Keywords:
host-pathogen interactions, single-cell biology, cellular heterogeneity, infection biology, Listeria monocytogenes, Salmonella enterica, Mycobacterium tuberculosis

Abstract:
Nickel–titanium (NiTi) shape memory alloys (SMAs) with a nominal composition of 50.8 at% Ni and 49.2 at% Ti were fabricated using the as-fabricated laser powder bed fusion (LPBF) technique. This study focuses on the impact of post-processing heat treatments—specifically solution annealing and aging at 500 °C for 1 and 20 h—on phase transformation behavior and functional performance. Phase analysis (XRD) was conducted at room temperature (~ 25 °C), while uniaxial tensile testing was performed at both room (~ 25 °C) and sub-zero (–20 °C) temperatures. Differential scanning calorimetry (DSC) was carried out over a wide temperature range to evaluate the thermal behavior of the material. The results indicate that heat treatment conditions significantly affect transformation temperatures, phase constitution, and mechanical response. Depending on the treatment and test temperature, the microstructure varied from fully austenitic to fully martensitic or mixed-phase states. These variations manifested as distinct features in the stress–strain behavior, particularly in terms of martensitic transformation and superelasticity. The study demonstrates the feasibility of fine-tuning functional properties in LPBF-produced NiTi SMAs through optimized thermal processing strategies.

Abstract:
The design and optimisation of electrode and electrolyte materials to tune the properties of capacitors is a complex task with often unexpected outcomes. In this work, we assessed the electrochemical performance of a new carbon material, Graphene MesoSponge® (GMS), in combination with a flexible electrolyte, ionogel built from polyvinylalcohol polymer matrix and ionic liquid (IL) with ethylmethylimidazolium cations and bisulfate anions. From the electrochemical characterisations employing cyclic voltammetry, electrochemical impedance spectroscopy, and galvanostatic charge-discharge, we established the superior performance of GMS compared to the activated carbon reference material. To gain insights into the unique chemistry of GMS structure and composition that lead to favourable electrochemical properties, we conducted density functional theory (DFT) simulations to examine the interactions of IL with the GMS material using nanoscale, periodic models of the pristine and two different defect site-containing graphene sheets. The dominant interactions in these systems are a network of H-bonds and dispersive interactions, similar in both systems, but favouring curved graphene due to its structural complementarity with IL ions. Changes to the electron density distributions relative to those of the separate components and the superimposed effect of cations/anions and polymer matrix interactions were used as the atomic-scale measure of surface wettability.

Abstract:
The rise in global carbon dioxide levels necessitates efficient, low-pollution energy technologies. Solid Oxide Fuel Cells (SOFCs) are promising energy converters, and their electrical performance is strongly influenced by the electrode microstructure. This study presents a comprehensive multiscale, experimentally grounded optimization pipeline for SOFC electrodes to maximize the electrical power density, integrating microscale and macroscale approaches. The methodology combines tomography-based microstructure characterization, computational homogenization, multiphysics simulations, model order reduction, and machine-learning-based surrogate modeling. Anode samples with fine, medium, and coarse grain sizes are analyzed using high-dimensional morphological descriptors to characterize microstructure morphology. Partial least squares discriminant analysis reduces the descriptor space to enable efficient surrogate modeling and generation of artificial microstructures by interpolation in the reduced space. Effective conductivities and permeability are computed by first-order homogenization and incorporated into a macroscopic fuel cell model to predict the power density. The proposed framework links microstructural information to macroscopic electrical performance within a nested optimization loop, enabling systematic exploration of physically realistic microstructural variants. Using a Ni-YSZ anode as a case study, the approach identifies the most suitable microstructure characteristics within an experimentally limited design space and provides a flexible optimization framework that can be adapted to different databases, models, and objective functions.

Keywords:
Optimization pipeline, Solid oxide fuel cells, Electrode microstructure, Multiscale modeling, Multiphysics modeling, Surrogate modeling

Abstract:
A comprehensive finite element-meshfree multiscale numerical framework is developed to investigate the size-dependent nonlinear asymmetric instability behavior of carbon nanofiber (CNF)-silicon carbide (SiC) nano-particle hybrid reinforced micro-arches subjected to radial concentrated loads applied at different positions. At the nanoscale, a finite-element-based homogenization strategy employing 3D periodic representative volume elements (RVEs) is developed to compute the effective elastic properties of nanocomposites reinforced with SiC nanoparticles and cylindrical CNFs, accounting for interphase characteristics. These homogenized material constants are subsequently incorporated into a nonlocal strain gradient theory (NSGT)-based radial point interpolation meshfree formulation, enhanced with an adaptive background decomposition integration approach to capture load location-sensitive nonlinear stability responses accurately. Numerical results demonstrate a pronounced multiscale coupling effect: increasing the CNF volume fraction from 1% to 4% results in approxi-
mately a 52% enhancement in all critical limit point loads, while increasing the SiC nanoparticle content from 1% to 5% increases them by nearly 29%. The relative interphase thickness provides a moderate gain of approximately 4.8%, and increasing the CNF aspect ratio strengthens the instability resistance by about 12.8%.
Conversely, increasing the SiC nanoparticle diameter results in a nearly 10.9% reduction in load-carrying capacity, indicating the superior reinforcing efficiency of smaller nanoparticles at a fixed volume fraction. Overall, the proposed framework successfully captures the highly nonlinear, curvature-sensitive, and size-dependent
instability characteristics of hybrid CNF-SiC micro-arches, offering a powerful predictive tool for the optimal design of advanced micro-scale structural components

Keywords:
Nonlinear stability, Meshfree approach, Size dependency, Finite element method, Hybrid composites

Abstract:
The rapid development of large language models (LLMs), including ChatGPT, Gemini, and Copilot, has led to their increasing use in health communication and patient educa-
tion. However, their growing popularity raises important concerns about whether the lan-guage they generate aligns with recommended readability standards and patient health literacy levels. This review synthesizes evidence on the readability of medical information generated by chatbots using established linguistic readability indices. A comprehensive search of PubMed, Scopus, Web of Science, and Cochrane Library identified 4209 records, from which 140 studies met the eligibility criteria. Across the included publications, 21 chatbots and 14 readability scales were examined, with the Flesch–Kincaid Grade Level and Flesch Reading Ease being the most frequently applied metrics. The results demon-strated substantial variability in readability across chatbot models; however, most texts
corresponded to a secondary or early tertiary reading level, exceeding the commonly rec-ommended 8th-grade level for patient-facing materials. ChatGPT-4, Gemini, and Copilot
exhibited more consistent readability patterns, whereas ChatGPT-3.5 and Perplexity pro-duced more linguistically complex content. Notably, DeepSeek-V3 and DeepSeek-R1 gen-
erated the most accessible responses. The findings suggest that, despite technological ad-vances, AI-generated medical content remains insufficiently readable for general audi-
ences, posing a potential barrier to equitable health communication. These results under-score the need for readability-aware AI design, standardized evaluation frameworks, and future research integrating quantitative readability metrics with patient-level comprehen-
sion outcomes.

Keywords:
medical chatbots, readability, health communication, digital health, artificial intelligence

Abstract:
As environmental pollution continues to rise, it is of great importance to ensure proper living conditions for humans. Along with rising electricity consumption, pollution from the magnetic field generated by electrical equipment and transmission lines is also increasing. The potential health effects of exposure to power frequency magnetic fields are referenced at levels of 0.2 µT to 3 µT in many countries. This study focuses on the magnetic field generated by indoor medium-voltage/low-voltage transformer substations. As the magnetic field in apartments above indoor substations exceeds the reference level, certain measures are to be taken. The so-called active shields are made of a closed current-carrying loop, a control system, and magnetic field sensors. They mitigate the magnetic field to the reference level. However, these shields continuously consume electric power. Therefore, the aim of this work is to develop a technique for designing energy-efficient active shields. The properties of these active shields are determined by solving an optimization problem that minimizes active power. Triangular, quadrangular, pentagonal, and hexagonal shapes of current-carrying loops are under study. Results show that using geometrically complex designs of active shields, particularly hexagonal ones, may be beneficial for energy-efficient and high-performance mitigation of the transformer substation magnetic field. Thus, the power consumption of the active shield is reduced from 50 W to 2.3 W when mitigating the magnetic field of the substation under study.

Keywords:
Magnetic field, Shielding, Transformer substation, Energy efficiency , Active power , Reference level , Optimization

Abstract:
In this study, we investigate the electronic and optical properties of silicon-doped β-Ga2O3 using first-principles calculations. Four key defect configurations were analyzed: substitutional Si on a tetrahedral Ga site (SiGaI), interstitial Si (Sii9), and the interstitial Si–Ga vacancy complexes Sii9–1VGaI and Sii9–2VGaI. We confirm that the substitutional SiGaI acts as a shallow donor, raising the Fermi level into the conduction band, which is consistent with experimental data. In contrast, the interstitial Sii9 introduces a midgap level and exhibits a smaller Bader charge compared to the substitutional case, deviating from the +4-oxidation state typically observed experimentally. Crucially, complex formation with Ga vacancies stabilizes the interstitial species. The Sii9–1VGaI complex retains n-type behavior with a redshifted absorption edge. The Sii9–2VGaI complex, however, introduces deeper states and a further reduced optical absorption edge below 4 eV. The comparable Bader charge and negative formation energy of these two complexes indicate that they can coexist with substitutional donors under implantation conditions. Our results provide novel insight into the mechanism behind the experimentally observed dual nature of Si in β-Ga2O3.

Keywords:
complex defects, density functional theory, effective band structure, Fermi energy, Ga2O3, optical absorption

Keywords:
Reliable AI, Physics informed neural networks, Robust loss, Collocation-based robust variational physics informed neural networks, Finite element method, Navier–stokes equations, Cavity flow problem

Abstract:
This study deals with the problem of optimizing the geometry and motion of a two-segment articulated ichthyoid propulsor for autonomous underwater vehicles. The considered propulsor mimics the undulating body and caudal fin motion of a swimming fish; thus, the thrust and sideforce that are generated exhibit undesirable oscillations. The formulas for these hydrodynamic forces, which were derived in the author's previous work, are presented. For selected values of the mean thrust and the swimming speed, two problems of minimizing the thrust (1) and the sideforce (2) variance are solved by systematically searching the set of feasible solutions. Two considered objective functions lead to quite different results regarding the optimal geometry and motion of the propulsor. The propulsor minimizing the thrust variance should have the first segment shorter than the second one, and the propulsive fin should spread over almost the entire length of the second segment. When the objective is minimizing the sideforce variance, the first segment should be described by a length greater and the amplitude smaller than that of the second segment, and the propulsive fin should be small. For both objective functions, the optimal motion of the propulsor strongly depends on the swimming speed and generated thrust. Generating greater thrust at higher swimming speeds requires reducing the vibration period.

Keywords:
ichthyoid propulsor, fish swimming, autonomuos underwater vehicle, elongated body theory, optimization

Abstract:
In this study, tubular specimens of Inconel 625 and Inconel 718 were additively manufactured using the Laser Engineered Net Shaping (LENS) technique. Their initial yield surfaces were experimentally determined under biaxial stress loading at 0.005% and 0.01% plastic offset strain. Uniaxial tensile tests showed yield strengths of 509 MPa and 461 MPa, with Young’s moduli of 180 GPa and 171 GPa for Inconel 625 and Inconel 718, respectively. Yield surfaces, fitted using the Szczepiński anisotropic criterion, revealed elliptical shapes with axis ratios below 1.73, confirming moderate anisotropy. Inconel 625 exhibited nearly symmetric yield strengths in tension and compression, with a higher tensile-direction elongation of the surface, whereas Inconel 718 showed stronger directional dependence, reflecting a higher degree of mechanical anisotropy.

Keywords:
Inconel, Yield surface, Additive manufacturing, Laser Engineered Net Shaping

Abstract:
Functionally graded nickel-based coatings represent an advanced surface engineering approach designed to enhance the performance of components operating in high-temperature and harsh environments. Unlike conventional coatings with uniform composition, functionally graded coatings exhibit gradual variations in composition and microstructure across their thickness, enabling improved adhesion, reduced residual stresses, and enhanced multifunctional performance. This review provides a comprehensive overview of recent developments in nickel-based functionally graded coatings, focusing on substrate materials, coating compositions, and manufacturing technologies. Particular attention is given to coatings designed for high-temperature applications and harsh service conditions, including carbide-reinforced composite coatings and MCrAlY-type systems used for oxidation and corrosion protection. Various fabrication methods, including laser cladding, additive manufacturing, electrodeposition, and thermal spraying, are critically discussed in terms of their advantages and limitations. The current state of the art is analyzed with emphasis on coating performance in high-temperature and aggressive environments. Finally, key challenges and future research directions are identified, highlighting the need for improved long-term performance evaluation, advanced manufacturing approaches, and the development of multifunctional gradient coating architectures.

Keywords:
functionally graded coatings, nickel-based coatings, laser cladding, thermal barrier coatings, high-temperature surface engineering

Abstract:
Iron oxide (Fe2O3) is attractive for energy storage due to its low cost, abundance, and eco-friendliness, but suffers from poor cyclic stability and capacitance fading. Here, we systematically investigate how calcination temperature influences the structure, morphology, and electrochemical properties of surfactant-assisted self-assembled iron oxide nanoflowers. Variation of calcination temperature from 300 °C to 600 °C strongly affects the phase, crystal structure, morphology, surface area, porosity, and electrochemical properties of the oxides. The low-temperature calcination of iron oxide at 300 °C leads to a distinctive mesoporous flower-like morphology, high surface area (145.76 m2 g−1), and mixed-phase (maghemite and hematite) composition with low crystallinity, resulting in the highest specific capacitance (182.3 F g−1 at 1 A g−1), low internal resistance with enhanced capacitive behavior. In contrast, samples calcined at higher temperatures than 300 °C exhibit reduced surface area, enhanced phase purity (pure hematite), and diminished electrochemical activity. A low-cost pouch-type asymmetric capacitor is fabricated using Fe2O3 nanoflowers calcined at 300 °C and activated carbon, delivering 24.33 μWh cm−2 energy density, 448.91 μW cm−2 power density, and 78.8% capacitance retention with 97% coulombic efficiency after 10,000 cycles. These results underscore the pivotal role of calcination temperature in optimizing Fe2O3 nanostructures for efficient energy storage.

Keywords:
Iron oxide nanoflowers, Calcination temperaturę, Phase-morphology correlation, Pseudocapacitance, Asymmetric electrochemical capacitor

Abstract:
In this paper, we present an original ultrasonic technique to investigate and discriminate between different kinds of pork meat, i.e., hand-deboned (HD) meat and mechanically separated (MSM) meat. To this end, we measured the speed c of high-frequency f = 5 MHz ultrasonic waves propagating in the examined pork meat samples. The measured speed of longitudinal ultrasonic waves ranged from 1578 to 1610 m/s. Significant statistical differences were found between the speed of ultrasonic waves in the HD pork loin and pork neck, and those in various types of MSM.
The newly proposed measurement (analytical) method, based on the determination of ultrasonic velocity, can be effectively applied to distinguish between manually separated (HD) and mechanically separated (MSM) pork meat. Importantly, the obtained experimental results were supported by a statistical
analysis, showing highly significant correlations between the speed of ultrasonic waves and the content of water, protein, fat and sodium in the measured pork meat samples.

Keywords:
physicochemical parameters of meat, mechanically separated meat (MSM), hand-deboned (HD) meat, speed of sound, protein content, fat content, water content, sodium content

Abstract:
This study advances beyond qualitative strength reduction trends in additive manufacturing fracture studies by establishing quantitative, configuration-based fracture assessment for Binder Jetting Additive Manufactured (BJ-AM) 17–4PH stainless steel with engineered surface cracks. Multiple crack geometries such as edge, inclined, single-corner, and double-corner configurations were precisely implanted in square (7 × 7 mm) and rectangular (3.5 × 14 mm) specimens with identical cross-sectional areas. Experimental investigations demonstrate that fracture resistance is governed by crack configuration and geometry-induced constraint, not crack area alone. Double-corner cracks retained 79–86% strength despite 25% crack area, while single-edge cracks exhibited 46–54% retention with only 20% crack area. Thickness-dependent constraint effects unique to BJ-AM geometries were quantified through comparative testing, revealing rectangular specimens (3.5 mm thickness) exhibit reduced constraint and lower fracture resistance than square specimens (7 mm thickness). J-integral governed elastic-plastic fracture assessment, validated through Extended Finite Element Method simulations predicting failure within ±10%, establishing predictive frameworks for defect-tolerant BJ-AM structural design.

Keywords:
Binder jetting additive manufacturing, Fracture toughness, J-integral, Extended finite element method, Surface cracks, 17–4PH stainless steel

Abstract:
This study presents the results of investigations on the influence of raw material type and synthesis method of cadmium yellow on the electrokinetic potential of pigment particles and the sedimentation stability of the resulting dispersions
in various chemical environments. Pigments were synthesized from cadmium salts (chloride, sulfate, nitrate, and carbonate) using sodium sulfide or elemental sulfur as sulfur sources. Two synthesis routes were applied: (1) precipitation of
the pigment from solution, followed by filtration, drying at 60 °C, and calcina-tion at 600 °C in acidic and alkaline media; and (2) direct reaction of cadmium carbonate with sulfur at 600 °C. The materials were characterized using Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). The zeta potential of
the particles was measured at different pH values, and dispersion stability was evaluated by turbidimetric analysis (Turbiscan). The obtained pigments were mixtures of compounds, with cadmium sulfide (CdS) being the predominant component. The chemical composition depended on the synthesis route and the
calcination process. A correlation was found between the electrokinetic potential,sedimentation stability, and chemical composition of the pigments. Calcination significantly affected surface properties, while the presence of chloride, sulfite,
sulfate, and carbonate species modified the electrokinetic potential. Acidic envi-ronments were found to enhance the sedimentation stability of cadmium-based pigments. The findings highlight the importance of synthesis conditions for the
surface chemistry, electrokinetic behavior, and sedimentation stability of cad-mium-based pigments in aqueous systems.

Abstract:
This study introduces a proof-of-concept methodology for evaluating pressure-dependent non-linear acous- tic properties of liver tissue. The proposed non-linearity index (NLI) is derived from echo amplitudes obtained at two substantially different acoustic pressures. Unlike previous harmonic-based approaches, the method relies solely on the fundamental frequency band, allowing clinical implementation without additional system mod-ifications. The image acquired for the lower pressure is then amplified to correct for the pressure difference between the beams. Next, the NLI is estimated as a ratio of local amplitudes of the amplified low-pressure
image (ALPI) to the high-pressure image (HPI). In the case of nonlinear media some energy of the wave is transferred from the pulse fundamental frequency to higher harmonics, which affects mainly the HPI. With the harmonics being filtered out from the signal, the HPI amplitude becomes lower than the ALPI amplitude.As a result, the NLI becomes higher than 1 and increases with the non-linearity of the imaged tissue. The
hydrophone measurements were compared to the simulation (k-Wave) of the ultrasonic field in water and veg-
etable oil. Next, we performed NLI imaging of healthy and fatty livers using SonixTouch (Ultrasonix) systems and two acoustic pressures of 390 kPa and 1590 kPa. Preliminary studies – imaging healthy and fatty livers using SonixTouch (Ultrasonix) systems were performed on the 4 livers of the authors of the article showed that for ‘healthy’ livers the NLI was below 1.1, while in one of the authors with previously diagnosed steatosis falling between score 1 and 2, the NLI locally exceeded 1.3.These results show that the obtained NLI values increase with the degree of steatosis, which agrees with theoretical expectations based on tissue B/A coefficients. The work emphasizes methodological feasibility and physical consistency rather than clinical validation, given the limited number of volunteers and ethical restrictions on patient recruitment.

Keywords:
ultrasound imaging, abdominal ultrasound

Abstract:
Ensuring effective protection for payloads during aerial operations—whether involving drones, helicopters, or airdropped objects—remains a critical challenge due to their widespread commercial and military use. This paper proposes an adaptable airbag-based protection system equipped with innovative semi-passive valve for controlled gas outflow. The introduced valve incorporates a custom-shaped shutter vent and, unlike typical kinematics-driven solutions such as metering pins, utilizes pressure-driven motion of a mobile valve’s piston during the landing process. The predesigned dynamics of the valve’s piston enables the required change in the shutter vent area, allowing precise outflow control and consequently ensuring desired force and deceleration profiles. Optimal valve design is achieved through a hybrid analytical–numerical method, iteratively alternating between an analytical system model and CFD simulations of gas outflow. It is demonstrated that the proposed adaptable system dissipates the entire impact energy and maintains protected object’s deceleration at almost constant level, achieving efficiency comparable to semi-active systems. As a result, it effectively minimizes overloads during emergency landings and increases safety of passengers and payloads.

Abstract:
In this review, a comprehensive analysis of aluminide coatings for nickel-based superalloys was performed with the particular emphasis on their processing, microstructural evolution, and performance under high-temperature conditions. Nickel-based superalloys are widely used in power engineering and aerospace industries; however, their susceptibility to oxidation and hot corrosion necessitates advanced surface protection strategies. Aluminide coatings offer effective protection through the formation of stable and adherent alumina scales. The review systematically evaluates major deposition techniques, including chemical vapour deposition (CVD), pack cementation, slurry aluminizing, and advanced hybrid methods, highlighting their influence on coating structure and properties. Special attention is given to the relationship between processing parameters, microstructure, and functional performance, including oxidation resistance, corrosion behaviour, and mechanical properties such as hardness and fatigue life.

Keywords:
aluminide coatings, nickel-based superalloys, chemical vapour deposition, pack cementation, slurry aluminizing, high-temperature oxidation

Abstract:
The oxygen evolution reaction (OER) using noble metal-based catalysts faced significant commercialization challenges due to the scarcity and substantial expense of these noble metals. Thus, the development of an efficient OER electrocatalyst for proton exchange membrane (PEM) water electrolyzers is still a challenging task. Herein, we present a facile approach to preparing cobalt phthalocyanine anchored on N-doped Co3O4 carbon network (Co3O4-NC) derived from metal organic framework (MOF). This strategy facilitates fast electron transfer and modulates the electronic structure. This improved electron transport induced by CoPc plays a significant role in enhancing OER, requiring only an overpotential of 1.2 V to deliver a current density of 1000 mA cm−2 with excellent stability. The Co3O4-NC2 Pc catalyst shows excellent durability during PEM water electrolysis and delivers industrially required current density of 1000 mA cm−2 at a potential of 1.66 V, outperforming commercial RuO2. The results of this research are twofold. Firstly, they promote green and low-carbon development. Secondly, they inject new vitality into the development of hydrogen energy technologies.

Keywords:
noble-metal free catalyst, oxygen evolution, phthalocyanine doped metal oxide, proton exchange membrane, water electrolysis

Abstract:
Present investigation systematically quantifies the role of interior defect morphology on tensile fracture behavior in Binder Jetting Additive Manufactured (BJAM) 17-4 PH stainless steel. Unlike prior investigations relying on stochastic natural defects, BJAM is uniquely employed to fabricate tensile specimens with five precisely controlled interior defect geometries such as spherical, disc-shaped, ellipsoidal, inclined ellipsoidal, and two-spherical at the mid-gauge location of round and square cross-sectional configurations. These artificial defects, occupying 16–35% of the gross cross-sectional area, serve as morphologically defined analogues of shrinkage porosities typical of conventional steel castings. A novel shape-independent empirical net section yielding method is developed that directly correlates projected defect area to fracture stress across all five defect geometries and both cross-sectional configurations. Results demonstrate that tensile strength reduction is governed by projected defect area independent of defect shape, with predictions falling within ±10% for the majority of configurations, providing a practically applicable fracture stress prediction tool for defect containing BJAM components. 3D finite element simulations coupled with a ductile damage model are implemented to accurately predict crack initiation sites and experimental load–displacement responses, achieving excellent agreement with experimental findings and providing independent computational validation of the empirical framework.

Keywords:
Binder jetting additive manufacturing, Ductile damage model, Interior defects, Shrinkage porosity, 17-4PH steel

Abstract:
In the present exploration, by unifying the simplified unit cell (SUC) micromechanical approach with the isogeometric numerical technique, a new solution model is developed to examine the small-scale dependent nonlinear stability feature of fuzzy fiber reinforced composite (FFRC) microplates under in-plane axial compression. A notable structural feature of this hybrid composite is the presence of uniformly aligned radially grown carbon nanotubes (CNTs) on the surfaces of the glass fibers, all of equal length, together with the interphase area between the nanotubes and the polymer material. Additionally, the interphase region between CNTs and the matrix is modeled as a distinct phase. To capture the influence of material microstructure, the effective elastic constants are first predicted using the SUC micromechanics model, while size-dependent effects are incorporated through the modified strain gradient theory. These material characteristics are then combined with an isogeometric plate formulation to enable accurate and efficient numerical analysis of FFRC microplates with different geometries and boundary conditions. The results show that the presence of CNTs as well as the interphase region significantly enhances both the buckling resistance and postbuckling stability through improving the stiffness and load transfer capability, particularly when the interphase becomes thicker or stiffer. The examination also highlights the influence of glass fiber volume fraction as well as the role of strain gradient tensors in enhancing the load-bearing capability. Overall, the proposed framework provides a consistent link between micromechanical design features and structural-scale stability performance of FFRC microstructures.

Keywords:
Micromechanical model, Fuzzy fiber-reinforced composite, Size dependency, Interphase region

Abstract:
Niobium nitride (δ-NbN) coatings were deposited on AISI 316L austenitic steel using reactive DC magnetron sputtering. This study investigates the effects of air oxidation on the surface morphology, topography, roughness, nanohardness, adhesion, and wear resistance of NbN coatings. Their microstructure and thickness were analyzed by scanning electron microscopy (SEM), while surface morphology and roughness were assessed using atomic force microscopy (AFM), and surface topography was assessed by an optical profilometer. Nanohardness was measured using a Berkovich indenter. Adhesion was evaluated via progressive-load scratch testing and Rockwell indentation (VDI 3198 standard). Wear resistance was assessed using the “ball-on-disk” method. Both as-deposited and oxidized NbN coatings improved the mechanical performance of the substrate surface. Air oxidation led to the formation of an orthorhombic Nb2O5 surface layer, which increased surface roughness and reduced hardness. However, the brittle oxide also contributed to a lower coefficient of friction. Despite reduced adhesion and increased surface development, the oxidized coating exhibited a significantly lower wear rate than the uncoated steel, though several times higher than that of the non-oxidized NbN. Considering its good wear and corrosion performance, along with the bioactivity confirmed in earlier research, the oxidized NbN coating can be considered a promising candidate for biomedical applications.

Keywords:
Nb2O5, NbN, magnetron sputtering, oxidation, adhesion, wear, surface engineering

Abstract:
Transition metal borides are attracting increasing interest due to their unique properties. They are not only characterised by very high hardness, but also considerable chemical and thermal stability. Silver, on the other hand, is a good material for increasing electrical and thermal conductivity, wear resistance and has antibacterial properties due to its biological characteristics. Combining these two materials can provide superhard bilayers with increased functional properties. In this study, it was decided to synthesise Ag/WB2.5, Ag/W0.76Ti0.24B2.5 coatings and compare their properties to the individual components. The silver coating was produced by pulsed laser deposition (PLD), while the WB2.5 and W0.76Ti0.24B2.5 coatings were formed by high-power pulsed magnetron sputtering (HiPIMS). To determine the mechanical properties, nanoindentation tests, adhesion of the coatings by scratch -test and wear resistance by abrasion in reciprocating motion were tested. In all cases, the silver film contributed to an increase in the wear resistance of the materials without major changes in the hardness results of the materials. In addition, the Ag/W0.76Ti0.24B2.5 film showed very good adhesion to the substrate. Human hand wiping simulator was also carried out using - Tribotouch. After 36 000 cycles Ag/W0.76Ti0.24B2.5 coating was slightly deformed, which was not visible macroscopically. This result is more than three times greater than for the pure silver film. It was also decided to carry out corrosion tests in an environment of 0.9% NaCl. The Ag/W0.76Ti0.24B2.5 bilayer has very good corrosion resistance, similar to pure silver.

Keywords:
Granular materials, Thermal, Electric, Discrete element method, Explicit time integration

Abstract:
W 2024 roku zaczęło obowiązywać rozporządzenie Unii Europejskiej w sprawie stopniowego wycofywania gazu izolacyjnego – heksafluorku siarki – stosowanego w układach wysokiego napięcia. Związek ten uważa się za bardzo silny gaz cieplarniany. Z tego powodu zaistniała pilna potrzeba znalezienia alternatywnego gazu, który mógłby zastąpić dotychczasowe rozwiązanie. W artykule przedstawiono wyniki wstępnych badań gazów, które mogłyby być wykorzystane w układach wysokiego napięcia. W specjalnie zaprojektowanym układzie ciśnieniowym wyposażonym w układ elektrodowy przeprowadzono pomiary wyładowań niezupełnych metodą akustyczną oraz pomiary wytrzymałości elektrycznej. Badania przeprowadzono przy kilku różnych poziomach nadciśnienia. Porównano wyniki wytrzymałości powietrza, dwutlenku węgla, azotu i argonu.

Keywords:
wytrzymałość elektryczna, wyładowania niezupełne, gazy elektroizolacyjne, emisja akustyczna

Abstract:
Monkeypox is a reemerging zoonotic disease that has been spreading worldwide. Different approaches are being conducted to find effective treatments for this disease. To accelerate therapeutic discovery, we propose telomere-binding protein (TBP) as a potential drug target because of its important role during virus maturation. Using computational biology and biophysics techniques, the MPXV TBP was modeled, and a library of FDA-approved drugs and phytocompounds was screened using a rigorous ensemble docking protocol; conformational sampling was enhanced by enumerating, for each ligand, ionization states, tautomerism, and ring conformations. Our results present a new approach to drug selection against MPXV, with six potential inhibitors: CHEMBL3894860, CHEMBL461101, CHEMBL2103870, PNSC125, PNSC305, and PNSC123, which can be taken as lead compounds for experimental testing, for example, in plaque reduction assays and qPCR in MPXV-infected cells to determine EC50, CC50, and selectivity index (SI) values.

Keywords:
drug screening, ensemble docking, Monkeypox virus, telomere binding protein

Abstract:
W artykule omówiono konkluzje raportu amerykańskiego Departamentu Stanu
dotyczącego zagrożeń wynikających z nieuregulowanego rozwoju sztucznej inteligencji.
Raport ostrzega bardzo dobitnie przed najróżniejszymi przyszłymi zagrożeniami
stojącymi przed całym światem w wyniku niekontrolowanego rozwoju nowych
technologii informatycznych, mocno akcentując w szczególności możliwość
zniszczenia całej ludzkości przez globalnie niekontrolowane zastosowania AI.
Druga część artykułu dotyczy problematyki mającej potencjalnie również wielkie
znaczenie dla naszej przyszłości, a mianowicie nowego urządzenia łączącego mózg
z komputerem. Urządzenie to o nazwie Neuralink przesyła bezprzewodowo sygnały
mózgowe do specjalnego programu, który je dekoduje, rozpoznając ludzkie
myśli. Przy wielu niezaprzeczalnych zaletach olbrzymim zagrożeniem są możliwości
wykorzystywania przez osoby niepożądane dostępu do myśli człowieka
w celu naruszenia jego prywatności. Konkluzją artykułu jest stwierdzenie o konieczności
prowadzenia szerokich prac dotyczących regulacji mających na celu
bezpieczny rozwój AI i korzystne dla społeczeństw jej zastosowania.

Keywords:
sztuczna inteligencja, globalne zagrożenia, interfejs mózg-komputer, potrzeba globalnych regulacji

Abstract:
Wykorzystywanie sztucznej inteligencji, a jej generatywnej postaci w szczególności, nabiera olbrzymiego znaczenia w procesach edukacyjnych na wszystkich poziomach. W obliczu zachodzących zmian niezbędna jest obecnie głęboka refleksja dotycząca treści i sposobów prowadzenia edukacji. Często artykułowane optymistyczne poglądy na temat coraz szerszego, edukacyjnego wykorzystywania AI nie są wolne od bardzo poważnej krytyki, wskazującej na możliwe znaczące słabości tego procesu, zaburzającego u uczniów zdolności poznawcze i umiejętności krytycznego myślenia, pozwalając im ominąć kluczowe czynności niezbędne do rozwijania wiedzy i umiejętności.

Keywords:
współczesna edukacja, wykorzystywanie sztucznej inteligencji, zróżnicowane opinie ekspertów

Abstract:
Accurate prediction of many-body dispersion (MBD) interactions is essential for understanding the van der Waals forces that govern the behavior of many complex molecular systems. However, the high computational cost of MBD calculations limits their direct application in large-scale simulations. In this work, we introduce a machine learning surrogate model specifically designed to predict MBD forces in polymer melts, a system that demands accurate MBD description and offers structural advantages for machine learning approaches. Our model is based on a trimmed SchNet architecture that selectively retains the most relevant atomic connections and incorporates trainable radial basis functions for geometric encoding. We validate our surrogate model on datasets from polyethylene, polypropylene, and polyvinyl chloride melts, demonstrating high predictive accuracy and robust generalization across diverse polymer systems. In addition, the model captures key physical features, such as the characteristic decay behavior of MBD interactions, providing valuable insights for optimizing cutoff strategies. Characterized by high computational efficiency, our surrogate model enables practical incorporation of MBD effects into large-scale molecular simulations.

Abstract:
One of the most promising green solutions to the growing need for renewable, environmentally friendly and not expensive energy sources, that can replace fossil fuels, is oxygen production during water electrolysis. The authors present gold and gold-semiconductor electrodes based on periodic self-assembled polystyrene spheres template for efficient oxygen evolution reaction (OER) via water splitting. The two-dimensional ordered Au crystal (OAuC) exhibits onset overpotential 1.63 V vs. RHE (reversible hydrogen electrode) with small Tafel slope of 76 mV dec−1 with excellent stability profile. The distinct ordered feature of the OAuC confers promising potential as electrocatalyst for OER.

Keywords:
Alkaline media, gold periodic electrodes, oxygen evolution reaction, water electrolysis

Abstract:
Current graph neural network (GNN) model-stealing methods rely heavily on queries to the victim model, assuming no hard query limits. However, in reality, the number of allowed queries can be severely limited. In this paper, we demonstrate how an adversary can extract a GNN with very limited interactions with the model. Our approach first enables the adversary to obtain the model backbone without making direct queries to the victim model and then to strategically utilize a fixed query limit to extract the most informative data. The experiments on eight real-world datasets demonstrate the effectiveness of the attack, even under a very restricted query limit and under defense against model extraction in place. Our findings underscore the need for robust defenses against GNN model extraction threats.

Keywords:
recycled materials, end-of-life tiers, rubber, fibres, concreto

Abstract:
Ultrasound (US) is a widely used imaging modality due to its availability, relatively low cost, and high frame rate. However, the quality of US images is usually considered inferior compared to other modalities, which can make image interpretation and the development of computer-aided diagnostic systems more challenging. In this work, we propose a deep reinforcement learning approach for US image denoising. Our method employs a software agent that learns to select both the location and types of interpretable image processing filters to apply. We demonstrate that the agent effectively reduces speckle noise in homogeneous regions while preserving or enhancing the structural details at the boundaries between such regions. Compared to other deep learning methods, our approach is based on well-known and simple filtering operations, making the denoising process more transparent and easier to interpret.

Keywords:
reinforcement learning, ultrasound, despeckling, image enhancement

Abstract:
The electrochemical performance of cobalt-based supercapacitor electrodes is often limited by the relatively smooth surface of pristine nickel foam substrates. To overcome this limitation, a microstructurally engineered nickel foam scaffold was fabricated by introducing a porous nickel microparticle interlayer via screen printing. Cobalt nanostructures were hydrothermally grown on the modified substrate, forming a hierarchical electrode (Co@NF-M), which was systematically compared with electrodes prepared on commercial nickel foam (Co@NF). Structural and spectroscopic analyses supported the formation of predominantly crystalline spinel Co3O4, characterized by mixed Co2 + /Co3+ oxidation states. Morphological analysis further demonstrated a porous cobalt nanostructure anchored onto a roughened nickel scaffold, providing abundant active sites and facilitating electrolyte penetration and ion diffusion. Electrochemical impedance spectroscopy indicated a reduced charge-transfer resistance and improved electron transport compared to the conventional Co@NF electrode. As a result, the Co@NF-M electrode exhibited superior electrochemical performance, delivering specific capacitances of 1278, 1184, 1003, and 602 F g−1 at 0.5, 1, 5, and 10 A g−1, respectively. Furthermore, the symmetric Co@NF-M//Co@NF-M device retained 95% of its initial capacitance after 3000 cycles, demonstrating excellent cycling stability. The enhanced performance is attributed to the engineered nickel scaffold, which promotes more uniform cobalt growth and improves interfacial contact while facilitating electron and ion transport.

Keywords:
Cobalt oxide, Symmetric supercapacitor, Cycling stability, Tailored Nickel foam, Pseudocapacitor behavior