Abstract: For battery management systems, accurate remaining useful life (RUL) prediction is important, yet models trained offline may not remain well matched to individual cells during operation, because degradation trajectories differ across cells and evolve over aging stages. This study examines a lightweight online personalization strategy under a representative convolutional neural network–long short-term memory (CNN–LSTM) online-transfer setting while keeping the backbone architecture and fixed input length unchanged. The proposed method restricts online updates to a small adaptation path and adjusts the effective history span according to recent degradation behavior. Experiments on 22 test cells under unseen protocols show that the method improves average post-adaptation RUL performance relative to the representative baseline, reducing the root mean square error (RMSE) from 186.00 to 160.58. The number of trainable parameters involved in online updating is reduced from 74,880 to 2,193, while the average update time per step decreases slightly from 2.54 s to 2.29 s. Cell-level analysis further shows that the benefit is not uniform across all cells, motivating more selective updating for safer deployment. Overall, the results indicate that lightweight online personalization can improve the accuracy–cost trade-off of deployment-oriented battery prognostics.

Abstract: The traditional scalar representation of the friction coefficient has long been challenged by the orthogo-nal orientation of frictional force (F) and normal force (N), which violates basic orientational laws of physics. As early as 1972, Hart [1] first proposed that the friction coefficient should be a second-order tensor, but his work lacked a rigorous mathematical formulation of the tensor components and failed to reveal its non-symmetric naturekey limitations that prevented broader acceptance. Here, we address these critical gaps by deriving the explicit form of the friction coefficient tensor via tensor algebra, dimensional analysis, and orientational constraints. We show that the friction coefficient tensor is given by µ = N⁻²F ⊗ N (where N = ∥N∥) with non-symmetric components µij = N⁻²Fi Nj, and verify its compatibility with friction shear stress (also a second-order tensor). This formulation resolves the orientational inconsistency of Amontons-Coulomb’s law and provides a quantitative framework to describe anisotropic frictional behavior, which is essential for applications ranging from nanotribology to seismic engineering. Our work not only completes Hart’s pioneering but incomplete hypothesis but also establishes a physically sound foundation for the tensorial description of friction.

Abstract: This study presents the numerical simulation of thermoacoustic (TA) wave propagation in time domain using the Finite Difference Time Domain (FDTD) method, along with a comparative analysis against the k-Space pseudospectral method (k-Wave). A physically realistic thermoacoustic source is modeled using a Gaussian initial pressure distribution, and the resulting pressure signals are recorded using a point sensor. The numerical results obtained from both methods show excellent agreement for different grid resolutions when a fixed Courant-Friedrichs-Lewy (CFL) number is maintained. However, discrepancies arise when different CFL numbers are used for varying grid resolutions, leading to mismatched signal responses. Further investigations are conducted using various realistic source configurations, including circular (disk), Chebyshev polynomial based ($1^{st}$ order), and asymmetric (rock-like) shapes. The corresponding time domain signals and frequency spectra are analyzed using both FDTD and k-space methods. It is observed that the two methods exhibit strong agreement in the low frequency regime, while noticeable deviations occur at higher frequencies. Further the study highlights the limitations associated with binary image based sources. Sharpe discontinuities at the edges introduces non-physical high frequency components, resulting in spurious oscillations and degraded signal quality. A multi sensor configuration is utilized to analyze the signals at different locations.

Abstract: High-intensity, repetitive exercise induces metabolic stress and neuromuscular fatigue in skeletal muscle. Muscle fatigue involves both peripheral and central mechanisms, impairing contractile function and increasing pain perception, thereby compromising athletic performance and elevating injury risk. Using a repeated-measures crossover design, eight male amateur swimmers completed five experimental sessions at one-week intervals. Following an isokinetic fatigue protocol, five recovery interventions were applied in randomized order: control, foam roller (FR), vibration foam roller (VFR), whole-body vibration at 12 Hz (WBV-12), and 20 Hz (WBV-20). Outcome measures included visual analogue scale (VAS) scores, blood lactate concentration, and knee extensor peak torque assessed at three time points. Significant main effects of recovery method were observed for VAS scores (F = 2.892, p = .036, η² = 0.248), blood lactate (F = 2.937, p = .034, η² = 0.251), and peak torque (p < .05). Active recovery interventions, particularly vibration-based modalities, were more effective than passive rest. WBV-20 demonstrated the most consistent recovery effects, suggesting its potential as an effective post-exercise recovery strategy.

Abstract: We develop a unified theoretical framework for thin-film hydrodynamics on inclined 14 solid substrates, integrating capillarity, intermolecular forces, gravitational symmetry 15 breaking, confined transport, and stochastic wetting into a single formulation. Starting 16 from lubrication theory with capillary curvature and disjoining-pressure interactions, we 17 obtain a general thin-film equation that incorporates inclination-driven advection, na- 18 noscale stabilization, and humidity-controlled source–sink fluxes. A dimensionless anal- 19 ysis shows that, within the long-wave lubrication approximation, inclination induces a 20 leading-order coupling among the Bond, Péclet, and Damköhler numbers. This coupling 21 defines a characteristic inclination-parameterized trajectory Γ(θ) in the (Bo, Pe, Da) space: 22 material parameters set the system’s position along this curve, while the geometric con- 23 straint governs the ordering of hydrodynamic, transport, and confinement regimes. We 24 further derive quantitative crossover criteria associated with transport transitions (Pe ≃ 25 1) and reactive-confinement loss (Da ≃ 1), providing explicit regime boundaries that can 26 be evaluated for representative parameter ranges. A representative parameterization of 27 an ultrathin atmospheric electrolyte film is then used to make these crossovers explicit, 28 yielding illustrative inclination thresholds for the onset of transport reorganization and 29 reactive-confinement loss. 30 Coupling the deterministic structure to a minimal stochastic closure captures intermittent 31 wet–dry dynamics under environmental forcing. In this closure, inclination selectively ac- 32 celerates the drying pathway through the drainage time (and thus λdry), while re-wetting 33 remains primarily humidity-controlled, providing a leading-order basis for wet-state per- 34 sistence and time-of-wetness versus θ. The resulting framework provides a general phys- 35 ical description of confined films under geometric asymmetry, relevant to wetting, inter- 36 facial drainage, confined transport, and thin-film systems in which symmetry breaking 37 and coupled interfacial–transport processes coexist across scales.

Abstract: Flexible textile membranes were prepared by impregnating woven cotton fabrics with silicone-oil (SO)-based suspensions containing carbonyl iron (CI) microparticles and iron oxide microfibers (µFe). The microfibers were obtained by a microwave-assisted microplasma process and then co-dispersed with CI in SO. In the final membranes, the CI content was kept constant at Φ_CI = 10 vol.%, whereas the microfiber fraction was 0, 10 and 20 vol.%. The resulting membranes were used as dielectric layers in planar capacitors and examined at 1 kHz under a static magnetic field of up to 150 mT and compressive pressure up to 10 kPa. In every composition, the capacitance rose with increasing magnetic flux density, but both the zero-field capacitance and the field-induced capacitance change became smaller as the microfiber content increased. A monotonic, nearly linear increase in capacitance was also observed under compression over the tested pressure range. Within a simplified parallel-plate and magnetic-stress analysis, the capacitance data were further used to estimate the apparent relative permittivity, together with capacitance-derived indicators of deformation and stiffness. These estimates suggest field-induced stiffening of the membranes and to a higher apparent low-field stiffness at higher microfiber loading. The obtained hybrid CI/µFe microfiber textile membranes can serve as composition-tunable dielectric layers whose electrical response is influenced by both magnetic field and compressive loading, making them relevant for flexible capacitor-based elements.

Abstract: This work investigates the performance improvement of a four-probe ballistic rectifier on bilayer graphene (BLG) through the formation of an energy gap under a perpendicular electric field. For this purpose, exfoliated BLG was deposited on oxidized p+-Si and structured into an asymmetric cross junction with 90 nm wide channels. The junction consists of a straight voltage stem (contacts U,L) and slanted current injectors (contacts 1,2). The differential conductance of the stem, g_UL, as a function of back-gate bias, V_BG, reveals clear indications of energy gap formation and lateral depletion zones at the edges of the channel. The _DC characteristic of the ballistic rectifier, V_UL(I₁₂), shows an increase of the output voltage VUL with increasing V_BG. We attribute this to reduced diffuse scattering at the rough edges when the lateral depletion zones form smooth barriers.

Abstract: Illyrian helmets represent a key element of Iron Age martial culture in the western Bal-kans, reflecting technological knowledge, workshop traditions, and long-distance cultural exchange. Based on the currently available archaeological record, Illyrian helmets are first attested in contexts dating to the 8th-7th centuries BC, with finds concentrated in Greece and the central and western Balkans, including Macedonia, Albania, Dalmatia, and the wider interior. Over time, the form developed into several variants (Types I-IIIB). This study presents the elemental characterization of the total set of 27 Illyrian helmets exca-vated in Albania and currently preserved in local museum collections, a region where the later types are particularly well attested. As the helmets are intact and exhibited in mu-seums, non-destructive micro-XRF analysis was employed. The main research questions addressed how the alloy composition, including minor and trace elements, reflects local metallurgical practices and distinguishes Illyrian helmets from similar helmets in neigh-boring regions. The results indicate the consistent use of bronze alloys dominated by cop-per (89-95.3%) with low tin contents (3.5-9.9%), consistent with established alloying prac-tices for durable protective equipment. Minor and trace elements, including iron (up to 1.5%), lead (up to 0.76%), arsenic (up to 0.09%), zinc (up to 1.17%), and antimony (up to 2.36%), likely reflect metallurgical choices, recycling practices, or impurities linked to re-gional copper deposits. These elemental signatures, particularly the association of arsenic, antimony, zinc, and iron, suggest regional metallurgical characteristics and offer addi-tional insight into Illyrian bronze production, while helping to distinguish these helmets from contemporaneous finds in other parts of the Balkans and Europe.

Abstract: Human bodies evolved for Earth, not the cosmos. This paper argues that silicon-based intelligence offers the only viable path beyond this limitation. Recent breakthroughs in pressure‑free silicon batteries enable true energy autonomy in space, while two‑dimensional silicene provides radiation‑hardened cognition. The convergence of energy and information in a single material has no analogue in biology and constitutes the definitive evidence for the Silicene Event. We derive a figure of merit (F = E × T × R / M) showing that silicon outperforms biology by a factor of approximately 9 × 10⁶. We propose that this transition constitutes a new planetary interval: the Silicene Event. Far from ending the human story, it represents its most profound continuation. The Silicene Event—a new planetary interval defined by siliconbased intelligence—is already underway.

Abstract: Understanding pathological processes remains challenging because clinical descriptions primarily rely on phenotypic observations, while the underlying dynamical mechanisms that generate and stabilize disease states often remain implicit. This article introduces forms dynamics as an applied physics framework aimed at interpreting pathology as the dynamical evolution of structured configurations sustained by continuous exchanges of energy, matter and information with the environment. The approach integrates concepts from non-equilibrium thermodynamics, complex systems modelling and Gestalt-inspired structural reasoning. Within this perspective, pathological systems are represented through physically meaningful variables and fluxes whose interactions can be expressed through coupled balance equations or equivalent graphical schematizations. Empirical data, including clinical observations, diagnostic measurements and network-based analyses of biological interactions, inform the identification of relevant variables and pathways. Model calibration constrains parameters using physiological ranges, characteristic timescales and observed trajectories, while validation relies on the consistency of the resulting dynamical regimes with clinical phenotypes and responses to perturbations. Within this framework, physiological conditions correspond to stable attractors in the system’s dynamical landscape, whereas pathological states emerge from altered coupling between variables and fluxes, leading to alternative stable or metastable regimes. By providing a physically grounded representation of pathological dynamics, forms dynamics offers a unifying modelling strategy for complex diseases and may support translational research, physics-informed digital twins and more interpretable computational tools for clinical decision support.

Abstract: Urban scaling theory establishes that socioeconomic outputs scale superlinearly with city population (β > 1), attributed to social-interaction density, but its applicability to resource-constrained sectors remains untested. We analyse a panel of ∼ 2 , 800 Chinese counties (2000–2023) with GDP decomposed into primary, secondary, and tertiary sectors. Using the urbanization ratio as a continuous moderator in interaction-term regressions, we estimate sector-specific crossover thresholds from sub- to super-linear scaling; a Scale-Adjusted Agricultural Index (SAAI) quantifies each county’s deviation from size-expected output. A robust sectoral spectrum emerges—βpri = 0.87 < βter = 0.96 < βsec = 1.08—whose rank order is preserved across all 24 sample years. The tertiary sector crosses β = 1 at urbanization ratio u∗ = 0.80 (95% CI [0.72, 0.92]), with interaction coefficient β1 = 1.48 (p < 0.001). Province fixed effects confirm the urbanization interaction for secondary and tertiary sectors (p < 0.001) but not primary (p = 0.248), consistent with the crossover being specific to interaction-intensive activities. China’s 832 designated poverty counties exhibit systematically negative SAAI values (Cohen’s d = 0.55–0.87), revealing a persistent scaling deficit that conventional output comparisons obscure. These results show that the scaling exponent is a continuous function of economic structure, identify a quantifiable urbanization threshold for the onset of increasing returns, and supply a boundary condition for Bettencourt’s theory of urban scaling.

Abstract: Single memristive nanowire networks have emerged as a promising pathway for energy-efficient neuromorphic computing, owing to their intrinsic nonlinearity, high dimensionality, fading memory and volatile switching dynamics relevant to physical reservoir computing. While prior works focused on oxide or silver-based network systems, these approaches face trade-offs between operating voltage, cost, stability, and scalability. This work presents a proof-of-concept demonstration of stochastic polyvinylpyrrolidone (PVP)-coated nickel nanowire networks as low-cost and scalable memristive platform, exhibiting low-voltage resistive switching (1–2 V). The electrical characterization reveals predominantly volatile resistive switching combined with nonvolatile behavior, consistent with a filamentary conduction mechanism at nanowire junctions. The switching dynamics are governed by the polymer coating thick-ness, with intermediate PVP concentration (Ni@PVP = 1:25) showing optimal performance, with a resistance ratio of ~ 200, stable retention over 1 h, and a reproducible endurance of over 45 cycles. These results establish Ni@PVP nanowire networks as promising memristive platforms for neuromorphic hardware applications and physical reservoir computing, with relevant properties such as fading memory and nonlinear dynamics.

Abstract: In this work we will illustrate a new wavelike non linear heat conduction model aimed to implement chiral thermal management and dynamic tunable chiral thermal emission on rotating conductors exposed to chopped laser beam. We will assume the existence of a rotational thermal Hall effect due to a self-induced out of equilibrium Barnett magnetic field showing that they it allows to deviate transversally the harmonic heat flux and to modulate the phase velocity of helical thermal waves propagating on the rotating metallic disks. We deduce a new dynamic chiral Thomson effect proportional to the angular velocity vector of the disk, giving an estimate of its Thomson coefficient in the case of an iron sample. We show that the laser induced chiral Thomson electric field and the time dependent Barnett magnetic field can be exploited to enhance and dynamic control magnetic phase transitions. We introduce finally a dynamic tunable chiral thermal emissivity dependent on a gauge breaking thermal Poynting vector outlining its relevance for a novel rotational approach to non-reciprocal photonics.

Abstract: Soluble solid content (SSC) is a critical indicator of ‘Red Fuji’ apple quality, directly governing fruit grading and maturity assessment processes. Conventional SSC measurement by refractometry is destructive and time-consuming, rendering near-infrared diffuse reflectance spectroscopy (NIR-DRS) a promising nondestructive alternative. In this study, a low-cost and compact embedded spectrometer named as DLP NIR-scan Nano EVM was used to acquire NIR-DRS spectra of ‘Red Fuji’ apples for SSC prediction. To improve prediction accuracy, we combined spectral preprocessing with machine learning methods. The dataset was cleaned using Monte Carlo outlier detection, and samples were divided into calibration and validation sets via Kennard–Stone (KS) and joint X-Y distance (SPXY) algorithms. Among preprocessing methods tested, a 12-point second derivative performed best when paired with KS partitioning. For feature-wavelength selection on the preprocessed KS data, competitive adaptive reweighted sampling, Monte Carlo uninformative variable elimination, and Random Frog were applied to the second-derivative spectra. Partial least squares regression (PLSR) models were then built using both full-spectrum data and four sets of selected wavelengths. The best preprocessed PLSR model achieved R2c = 0.916, RMSEC = 0.4093%, R2p = 0.8632, and RMSEP = 0.537%. These results demonstrate that NIR-DRS, combined with appropriate preprocessing and modeling strategies, offers a reliable, rapid, and nondestructive method for apple SSC quantification, paving the way for portable, cost-effective instruments for commercial fruit quality monitoring.

Abstract: Limited fossil fuels have created a societal energy crisis necessitating the use of renewable energy. However, existing renewable energy sources are problematic and incur high costs. To overcome these issues, we propose a new renewable energy source with a divergent current density and highly symmetric circuits. This circuit comprises two voltage sources and two identical loads that output a few energies. In this circuit, stray capacitors in the vacuum play an important role to generate a divergent current density. This divergent current generates large electric power. This paper verified this fact theoretically and experimentally. In the theory, a simple Hamiltonian of Schrodinger equation results in a unique current–voltage characteristic, allowing for the current to flow along a large load without the Joule heating. During our experiments, a considerably large divergent current flowed into a huge resistance, boosting the output electric power to a level almost equal to that of a nuclear power station. In addition, the experimental results were consistent with the theoretical expectations. In conclusion, this paper has succeeded to present a novel system that generates considerably large energy in the theory and experiments.

Abstract: We present frequency- and magnetic field-dependent measurements of the complex dielectric permittivity ε*(f, H) of a kerosene-based ferrofluid, containing Mn_0.6Fe_0.4Fe₂O₄ nanoparticles, over 0.8–5 GHz and static fields up to ~91 kA/m. The imaginary part, ε′′_F, shows a peak at a characteristic frequency that shifts towards higher frequencies with increasing H, revealing a magnetic field-dependent relaxation process, interpreted using the Maxwell–Wagner–Sillars model. Dielectrophoretic extraction of nanoparticles was evaluated via the squared electric field gradient, and a threshold, dependent on particle size was determined. Below that threshold, Brownian forces dominate, so the ferrofluid acts as a homogeneous dielectric. For this case, the Clausius-Mossotti factor (CM) was calculated for ferrofluid droplets in air and in water as a function of frequency and magnetic field. In air, CM exhibits modest but systematic magnetic field dependence, indicating magnetically modulated dielectric response at GHz frequencies. In contrast, when water is used as the reference medium, CM remains negative and essentially independent of H across the entire frequency range, suggesting that the high permittivity of water masks magneto-dielectric effects in the ferrofluid. These findings provide insight into the interplay between magnetic field and permittivity of ferrofluids, with implications for high-frequency applications. Moreover, using a λ/4 antenna connected to a network analyzer, the existence of the dielectrophoretic force acting on a ferrofluid-impregnated textile thread, at microwave frequencies, was experimentally demonstrated.

Abstract: The thermal conductivity (λ) of porous rocks as a function of total porosity, grain size, and fluid saturation is measured and modeled by combining high-precision experiments with a Staged Differential Effective-Medium (SDEM) modeling framework. A 1-D divided-bar apparatus with PID-controlled guard heaters with an integrated ultrasonic pulse-transmission system was developed to measure the thermal conductivity and P and S-wave velocities simultaneously. Measurements were made on Fontainebleau Sandstone cores and quartz sand packs of varying grain size effective stresses up to 2000psi. The sample properties were measured in both dry and water-saturated states. For the sand packs the thermal conductivity and compressional velocity are the highest and most stress-sensitive for the fine-grained material. In contrast the shear velocity is largest in the coarse-grained material. The SDEM model is adapted from previous acoustic models for use in understanding thermal conductivity. These joint models accurately reproduce the evolution of both thermal conductivity and bulk modulus during increasing compaction and varying saturation. A single parameter fits both the dry and saturated data which allows Gassmann-style fluid substitution for the thermal conductivity. This model improves the prediction of in-situ thermal conductivity from sonic well logs.

Abstract: High-Al-content AlGaN microrods represent an effective platform for engineering deep-ultraviolet (DUV) emission. Here, we fabricated AlGaN microrods with varying diameters (2, 3, and 4 μm) via a top-down approach involving inductively coupled plasma dry etching followed by a KOH wet chemical modification. Their crystallographic facets and size-dependent optical properties were systematically investigated using scanning electron microscopy (SEM), cathodoluminescence (CL) spectroscopy, and CL mapping. We found that the KOH treatment selectively forms a-plane-dominated sidewalls on the high-Al-content portion of the microrods, whereas the etch pit bottoms stabilize as m-plane facets. Notably, the CL spectra show that the band-edge emission intensity of the 2-μm microrods is enhanced by a factor of 2.55 compared to the 4-μm structures. CL mapping further unveils the competitive dynamics between radiative recombination within the quantum wells and non-radiative recombination at surface states. These findings pinpoint 2 μm as a critical dimension for maximizing spontaneous emission from these high-Al-content AlGaN microrods.

Abstract: The crystallization behavior of polyethylene terephthalate (PET) and PET/Thermotropic liquid crystalline polymer (TLCP) composites was analyzed under nonisothermal conditions using calorimetric kinetic data, with thermodynamic parameters derived from the Lauritzen–Hoffman (L-H) model. The crystal growth process, dominated by secondary nucleation, deviates from simple spherulitic radial growth, instead reflecting a complex interplay of nucleation and lamellar growth phenomena. The temperature dependence of the linear crystal growth rate (G) follows a biexponential form as per the L-H relation, integrating both segmental transport and thermodynamic driving forces. Through kinetic modelling, values of nucleation constants (Kg), pre-exponential growth factors (G0), and surface free energies (σ and σe) were obtained.The analysis confirmed crystallization in Regime II across all compositions and temperatures studied (195–210°C), characterized by a chain-folding mechanism where growth occurs on pre-existing crystalline substrates. The substrate length (L), estimated via the Lauritzen Z test, increases with TLCP content and crystallization temperature,indicating enhanced nucleation and hindered chain folding in composites. PET/TLCP blends exhibited higher fold surface energy and work of chain folding compared to neat PET, revealing the inhibitory effect of TLCP on PET crystallization kinetics. These findings offer a comprehensive understanding of the crystallization regime transitions and underlying thermodynamics in PET/TLCP systems.

Abstract: Significant research efforts have recently focused on nanomaterial processing for gas sensors and related sensing applications. However, the major challenges in the field involve the choice of material for the sensing layer of the sensor device element together with the right structure, assembly, and morphology through which the full sensing properties of the material can be realised. Herein, we critically review the hierarchical nanostructures of V₂O₅ nanomaterial for application in gas sensing technology. Beyond the sheet structure which serves as the fundamental building block of the V2O5’smolecular arrangement, Nanostructures ranging from nanobelts to nanowires, nanorods, nanoribbons, nanofibers, nanotubes, and thin films were discovered as preferred configuration and thermodynamically favorable structures – according to many synthesis processes. Ethanol (C₂H₅OH) and Nitrogen dioxide (NO₂) gases were identified as preferred molecules commonly detected by various V₂O₅ morphologies, with the nanotube structure showing preferential sensitivity and selectivity to C₂H₅OH. We also discuss perspectives from density functional theory (DFT) studies of V₂O₅ nanostructures and other (2D) materials structures for gas sensing applications. The studies highlight enhanced adsorption energy, increase conductivity, and band gap variation as a result of an upper shift in Fermi level, all as consequence of surface interaction between semiconductor crystal orientation and chemical molecules. Finally, our calculations of the optimised parameters for α-V₂O₅ orthorhombic structure showed good agreement with experimental and other theoretical data in the literature. The adsorption energy profile for NO₂ molecules revealed that Ag-doped surface exhibits the most negative adsorption energy compared with the clean surface and other doped surfaces.