Search Results (2,421)

Battery-management systems observe current, terminal voltage, limited temperature measurements, and operating setpoints, but not the internal variables of electrochemical theory, so routine signals generally cannot identify a unique mechanism. We present a human-guided, generative-AI-assisted methodology that translates physics-based expectations into deterministic, auditable screening rules: human scientific authority fixes the physical assumptions, evidence requirements, and permissible claims, artificial intelligence supports development, and runtime evaluation is non-generative. LiFePO₄ is the test case. A Zeng–Bazant current-dependent plateau approximation supplies a physics-based reference, and a bivariate representational precedent motivates a composite, reference-dependent voltage residual that is not identified as thermodynamic work. Eleven observable screens return present, absent within resolution, indeterminate, or unavailable. Four evidence forms are separated. Digitized model curves show the reduced plateau relation tracks its parent phase-field simulation through moderate rates, with a high-rate limitation. Published temperature-conditioned discharge profiles show stable plateau elevation and flattening from 268 to 298 K across 0.5C–2C, with mixed 2C curvature. Measured replicates of a commercial cylindrical cell at two ambient setpoints resolve a within-run surface-temperature depression whose integrated first-law balance is heat-rejection-dominant and compatible with, but not uniquely attributed to, a literature-bounded reversible contribution. Controlled synthetic cases verify deterministic feature recovery and abstention without establishing a mechanism. Full article

Our environment deteriorates primarily due to the emissions of carbon dioxide. Scientists and entrepreneurs promote carbon offset to reduce the emissions. Scientists and investors explore the investments of carbon offset. Some scientists encouragingly construct portfolio selection models but do not completely optimize them. Some scientists encouragingly construct capital asset pricing models (CAPM) but do not completely justify them. Under such contexts, this paper proposes a model of multiple-objective portfolio selection (MOPS) and preliminarily explores multiple-objective capital asset pricing models (MOCAPM). By the classical transition from portfolio selection to CAPM, we introductorily conjecture the extended transition from MOPS to MOCAPM. Specifically, we prove mathematical properties for the model. For instance, its minimum-variance surface is convex, and its feasible region is bounded by the convex surface. We examine whether a point on the minimum-variance surface is nondominated. By the properties, we heuristically prove different tangent planes for MOCAPM (instead of the unique tangent line for CAPM). We tentatively hint the conditions for a unique tangent plane. This paper acts as a footstep of the introductory conjecture. Full article

To address time-varying communication topology, actuator response delay, and limited inter-UAV communication resources in the multi-UAV approach of a maneuvering target, this paper proposes a cooperative rendezvous/tracking control law combining a prescribed-time extended state observer (PTESO) with a dynamic event-triggered mechanism (DET). A three-state PTESO is designed whose observation error converges, within a prescribed time independent of the initial error, into a compact set related to the disturbance upper bound. Along the line-of-sight (LOS) direction, the remaining flight times of the UAVs are driven to consensus within a prescribed time toward a specified arrival instant via a threshold-adaptive DET; along the LOS normal direction, prescribed-time convergence of the elevation and azimuth angle errors is achieved through a time-varying-gain sliding surface. The guidance gains are designed from the worst-case algebraic connectivity of the candidate topology set, ensuring uniform validity under arbitrary switching. After accounting for first-order autopilot inertial dynamics, the command tracking error is proven uniformly ultimately bounded. Simulations of four UAVs cooperatively approaching a maneuvering non-cooperative object under periodic topology switching and actuator delay show an arrival-time deviation below 0.01 s, a terminal position error under 0.08 m, and 75–91 average inter-UAV triggers, outperforming existing prescribed-time/fixed-time cooperative guidance methods. Full article

A fractional graph-evolution model is formulated on a surface-derived thoracic-aortic branch tree and evaluated through multiresolution geometry and controlled joint-parameter experiments. A checksum-tracked source audit separates three model-specific MRI collections from a shared nominal wall surface and confirms that no validated MRI–STL transformation is available. The surface pipeline yields five terminal openings, three junctions, seven semantic branches, refined cross-sections, and an unapproved same-source candidate. Consequently, the instantiated operator is dimensionless and geometry normalized, rather than a calibrated pressure–flow operator. Graphs with 50, 100, 200, and 400 nodes preserve topology; relative to the internal 400-node discretization, the 200-node graph has a 9.20% 95th-percentile discrepancy in the first 12 positive eigenvalues and a 7.58° maximum principal angle for the first 10 modal subspaces. The analysis establishes a Caputo-consistent control-volume reduction, finite-horizon well-posedness for bounded forcing, non-normal augmented dynamics, observation leakage, finite-band phase conditions, and residual power-law stability. In 810 off-grid synthetic experiments, seven parameters are estimated jointly with repeated noise, multistart optimization, profile likelihood, and held-out testing. The median fractional-order error is 0.001304 and the median held-out complex NRMSE is 0.01086. The results support controlled synthetic practical identifiability on a shared nominal anatomy, not measured hemodynamic calibration or physiological-memory identification. Full article

Methane production from water-bearing coal reservoirs is governed not only by methane adsorption capacity but also by the accessibility of adsorption domains and the efficiency of pore-scale transport during pressure depletion. However, the interfacial mechanism by which coal wettability and water occurrence regulate methane adsorption–desorption reversibility remains insufficiently understood. In this study, three representative Ordos Basin coal samples with different pore structures and surface polarities, denoted as OBC-L, OBC-M, and OBC-H, were investigated to explore the pore-scale mechanisms governing water-mediated methane storage and release rather than to establish basin-wide statistical relationships. A combined experimental workflow involving N₂ adsorption–desorption, FTIR and XPS analyses, contact angle and Zeta potential measurements, low-field NMR, high-pressure methane adsorption–desorption tests, kinetic modeling, hysteresis evaluation, and Pearson correlation analysis was used to clarify the coupling among pore structure, coal–water interfacial properties, water occurrence, methane storage, and methane release. The results show that OBC-H possesses the strongest dry-state methane storage potential, with the BET surface area increasing from 5.82 m²/g for OBC-L to 12.94 m²/g for OBC-H and the fitted Langmuir volume (V_L) reaching 22.3 cm³/g. Nevertheless, OBC-H also shows stronger water affinity, as reflected by an increase in the XPS-derived O/C atomic ratio from 0.118 to 0.186, a decrease in contact angle from 82.6° to 51.8°, and an increase in bound water fraction from 46.3% to 69.4%. With the transition from dry to saturated conditions, the fitted V_L of OBC-H decreases from 22.3 to 15.2 cm³/g, while the Langmuir pressure (P_L) increases from 1.38 to 3.00 MPa, indicating a simultaneous reduction in the model-estimated maximum methane adsorption capacity and apparent methane affinity. More importantly, the desorption results demonstrate that high adsorption capacity does not necessarily correspond to high methane deliverability. For OBC-H, the final desorption efficiency decreases from 79.6% to 54.2%, the effective diffusion coefficient decreases from 2.74 × 10⁻¹¹ to 0.86 × 10⁻¹¹ m²/s, and the hysteresis index increases from 12.8% to 36.4% under saturated water conditions. Correlation analysis further confirms that bound water fraction is positively associated with adsorption–desorption hysteresis but negatively associated with desorption efficiency, desorption rate constant, and effective diffusion coefficient. These findings are consistent with two distinct water-mediated constraints: adsorbed/bound interfacial water contributes to surface-site shielding, whereas capillary and saturated water occupation contributes to pore-throat transport restriction; together, these effects reduce methane release efficiency and enhancing desorption irreversibility. This study provides an interfacial interpretation of methane deliverability based on representative water-bearing coal samples and offers a mechanistic basis for understanding wettability- and water-retention-related transport constraints; broader applicability across the Ordos Basin requires validation using a larger number of samples from different coal seams and reservoir settings. Full article

Infrared and visible images provide complementary cues for maritime ship detection, but practical dual-sensor systems often produce image pairs that are not strictly registered. Directly fusing such unregistered pairs may introduce ghosting artifacts, blurred target boundaries, and feature conflicts, especially over weak-texture sea surfaces where reliable correspondence cues are sparse. To address this problem, we propose UA-FusionDet, an unregistered-aware infrared-visible fusion framework with cross-modal feature alignment for maritime ship detection. The proposed framework extracts visible and infrared features with a dual-branch encoder, aligns the visible feature to the infrared reference through cross-modal deformable feature alignment, and suppresses unstable background offsets using sea-surface saliency guidance. Wavelet-guided complementary fusion then decomposes the aligned features into low- and high-frequency sub-bands, enabling frequency-aware fusion of infrared thermal saliency and visible structural details before feeding the fused representation to both a lightweight reconstruction decoder and a ship detection head. The reconstruction decoder provides auxiliary image-level regularization, while the detection branch supervises the task-oriented fused representation with ship bounding-box annotations. UA-FusionDet does not require registration ground truth or fused-image ground truth during training, making it suitable for realistic maritime monitoring scenarios with imperfectly aligned visible and infrared sensors. Experiments on 3132 unregistered visible–LWIR maritime image pairs show that UA-FusionDet achieves a precision of 0.904, a recall of 0.866, an ${\mathrm{mAP}}_{50}$ of 0.912, and an ${\mathrm{mAP}}_{50–95}$ of 0.566, exceeding the strongest competing method by 2.5 and 2.4 percentage points on the two mAP metrics, respectively, while maintaining an inference speed of 52.6 FPS. These results demonstrate that the proposed alignment and fusion framework improves detection accuracy under cross-modal misregistration while retaining practical inference efficiency. Full article

We study prediction-to-decision certification for inverse design with vector-valued response surfaces. An unknown response map is estimated from data, a target response is prescribed, and a decision is obtained by minimizing a target-loss function. The main question is how statistical prediction error and approximate global optimization error propagate to the true decision quality. We prove an end-to-end certificate showing that a high-probability uniform response bound and a certified global-search tolerance imply a high-probability bound on the true excess risk of the selected decision. Under a growth condition, the same event also yields an explicit distance-to-argmin bound. We provide finite-sample ordinary least squares response certificates, conditional ridge certificates with explicit bias decomposition, certified Lipschitz branch-and-bound, and polynomial sum-of-squares formulations. The formal certificate is demonstrated on a controlled synthetic benchmark. A clay-coloration example illustrates the workflow, while the pilot measurements are treated only as local forward-color checks. Full article

Accurate identification of complex crack networks with branching and intersecting topologies remains a challenge in aerospace and civil engineering. Conventional non-destructive testing techniques are constrained by limited coverage and equipment access requirements, while model-based inverse methods face the curse of dimensionality and high computational cost when characterizing intricate crack morphologies. To address these limitations, a Binary-encoded Transformable Modular Component (BTMC) method is proposed, which abstracts complex crack morphologies into combinations of modular components representing elementary crack topological operations and encodes their parameters into a unified binary genotype. This representation converts the high-dimensional continuous inverse problem into a discrete combinatorial optimization task over a bounded search space, and the extended finite element method is coupled with a genetic algorithm for forward analysis and parameter optimization. Numerical simulations covering non-intersecting cracks, intersecting networks, and irregular morphologies beyond the component library demonstrate that the method maintains stable identification accuracy under measurement noise up to 10%. Experimental verification on a metal tensile plate and a wing surface curved-shell structure confirms that the identified configurations are mechanically consistent with the measurements, with the strain-response error on the wing surface reduced from 8.67% for the traditional genetic algorithm to 2.27% for BTMC. Across all test cases, the BTMC method converges in fewer generations with a total identification time of approximately 16 min on average, which provides a computationally efficient framework for online structural health monitoring of aircraft structures. Full article

An analytical approach is developed for calculating a phase diffraction axicon with angularly variable spatial frequency that generates a prescribed light curve without iteratively solving an inverse design problem: the axicon frequency function is obtained directly from the polar equation of the target curve. When the axicon is combined with a lens, the intended curve is formed in the focal plane (Fraunhofer region), whereas in the Fresnel zone the intensity pattern is closely related to the curve’s evolute. We systematize this correspondence for rings, ellipses, spirals and polygonal curves, and derive analytical parameter bounds associated with the appearance of inflection points that qualitatively reshape both the evolute and the diffracted field (including hybrid curve–evolute patterns and “rose”-type contours). The qualitative outcome depends on the curve class/type. For a convex curve without inflections the expected curve is formed in in the far field (or in the focal plane), whereas the Fresnel intensity envelope follows the evolute. If the curve has peculiarities, especially inflection points with unbounded evolute branches, hybrid curve–evolute structure appears, and the focal pattern may itself resemble the evolute. For ellipses and polygonal families we analytically identify parameter intervals that mark this transition. The approach is verified experimentally for polygonal axicons, with attention to fabrication tolerances and to matching camera planes with the simulated propagation distances. Measured intensity distribution patterns agree with the corresponding simulations for both convex contours and curves that contain inflection points. The results are of fundamental interest and of practical value for optical trapping and laser surface structuring, where a compact phase element should deliver a controlled bright contour at a chosen working distance. Full article

Accurate and computationally efficient prediction of radioactive plume dispersion is essential for rapid risk assessment and emergency response in the event of accidental atmospheric releases. This study presents a three-dimensional, mass-conservative numerical framework for simulating mesoscale transport and transformation of radionuclides under varying meteorological conditions. The proposed model is based on the advection–diffusion equation and incorporates key physical processes, including turbulent diffusion, gravitational settling, precipitation washout, radioactive decay, surface absorption, and re-emission. A hybrid numerical scheme is developed that combines a semi-implicit Crank–Nicolson discretization for diffusion terms with a second-order Total Variation Diminishing (TVD) scheme employing a Van Leer limiter for advection. The framework is intended as a computationally tractable engineering model; operational applicability requires further assessment using measured runtime performance and independent physical validation. In addition, a modified parameterization of turbulent-diffusion coefficients is introduced, extending classical Pasquill–Gifford formulations to better represent mesoscale atmospheric behavior with bounded dispersion characteristics. The numerical implementation is verified against an analytical constant-coefficient advection–diffusion solution using concentration-error norms, plume-moment errors, mass-balance analysis, and grid-refinement tests. Additional idealized iodine-131 simulations illustrate the behavior of the framework under moderate-wind and stable atmospheric conditions. The results highlight the dominant role of advective transport and precipitation scavenging under moderate wind conditions, as well as strong localization effects under stable atmospheric stratification. The proposed model provides a practical compromise between the simplicity of Gaussian plume approaches and the high computational cost of full-physics atmospheric models, indicating its potential for rapid engineering calculations, subject to further validation against atmospheric observations and established operational dispersion models. Full article

Population aging has made sarcopenia a growing concern in geriatric health. Protein–polyphenol non-covalent complexes can serve as carrier systems that improve the stability and bioactivity of natural antioxidants. This study refined the preparation parameters for the non-covalent complex of whey protein isolate (WPI) and resveratrol (RES), achieving protein digestibility of 83.60 ± 0.50% and DPPH scavenging of 52.41 ± 0.58% at pH 7.0, a WPI:RES molar ratio of 1:1, and a reaction time of 1.5 h. Relative to free WPI, the complex improved DPPH scavenging by 21.66% while preserving protein digestibility. The binding mode, interaction forces, and conformational evolution were investigated via spectroscopic experiments, docking studies and molecular dynamics simulations. RES selectively bound to the surface of β-lactoglobulin in WPI through hydrophobic interactions and hydrogen bonding, with a docking score of −6.366 kcal/mol and an MM-GBSA binding free energy of −30.48 kcal/mol. The complex maintained a highly stable conformation throughout the 100 ns molecular dynamics simulation. In conclusion, this study elucidated the structural changes of WPI upon non-covalent resveratrol binding. The WPI-RES complex exhibited enhanced DPPH radical scavenging activity while preserving protein digestibility, with potential implications for functional food development in sarcopenia management. Full article

For $0\le \alpha <1$ and $\lambda \ge 0$, we introduce a filtered Janowski-rotated pseudo-Bazilević class of normalized analytic functions in the unit disk. The fractional power is defined through the unique analytic logarithm normalized at the origin, and a first-order differential filter is applied before the rotated Janowski subordination. Explicit formulae for $a_2$ and $a_3$ reduce the direct, logarithmic, inverse, and inverse-logarithmic Fekete–Szego-type functionals to a common Schwarz coefficient template. We derive a fixed-$a_2$ variability disk for $a_3$, Janowski disk containment, a positive-real-part consequence, and branch-free reconstruction formulae. Sharpness and function-level realization are unconditional on the integrable slice $\alpha =0$. For $0<\alpha <1$, the variability disk is exact at the Schwarz-data level and is realized by a function whenever the explicitly reconstructed auxiliary function is nonvanishing. Numerical results, including a two-parameter surface, show the damping effect of $\lambda$ on the base coefficient scales and on representative complete bounds while also displaying their interaction with $\alpha$, the rotation, and the Janowski parameters. Full article

Leaf-level vapor pressure deficit ($VP{D}_{\mathrm{leaf}}$) depends on the temperature of the leaf surface as well as the temperature and humidity of the surrounding air. Therefore, instruments that estimate $VP{D}_{\mathrm{leaf}}$ from a fixed leaf–air temperature offset may introduce condition-dependent errors. This paper presents the development, uncertainty analysis, and validation of a low-cost, single-housing, portable sensor platform that directly measures air temperature ($T_{\mathrm{air}}$), relative humidity ($RH$), and leaf surface temperature ($T_{\mathrm{leaf}}$) via an SHT35 and an MLX90614 infrared thermometer, and computes $VP{D}_{\mathrm{leaf}}$ on-board in real time using an ATmega328-based microcontroller. The platform was validated against a Testo 610 thermo-hygrometer and a FLIR E4 thermal camera on two lettuce (Lactuca sativa L.) cultivars grown at 20–26 °C and 40–70 %RH. Coefficients of determination were $R^2=0.9607$ for $T_{\mathrm{air}}$ and $R^2=0.9382$ for $RH$ ($n=1017$). Leaf temperature and the on-board $VP{D}_{\mathrm{leaf}}$ output itself were validated against reference readings taken during randomly timed site visits on three separate days ($n=250$ after excluding apparent misreads): $T_{\mathrm{leaf}}$ showed $R^2=0.8852$ against the FLIR E4, and the device-computed $VP{D}_{\mathrm{leaf}}$ showed $R^2=0.9100$ against a reference $VP{D}_{\mathrm{leaf}}$ computed from the same reference readings, with a mean bias of $+0.008$ kPa and an RMSE of $0.046$ kPa. A propagation-of-error analysis separately yielded a worst-case $VP{D}_{\mathrm{leaf}}$ uncertainty of $\pm 0.153$ kPa under representative conditions ($T_{\mathrm{air}}=25$ °C, $T_{\mathrm{leaf}}=24$ °C, $RH=65\%$), mainly driven by the $\pm 0.5$ °C infrared sensor tolerance; the empirically observed error was well within this conservative bound. With a cost of USD 83.28, this platform provides a practical and economically accessible tool for real-time monitoring and VPD-informed decision making in vertical farms and greenhouses. Full article

Foundation models for Earth observation are commonly transferred to downstream tasks without explicit attention to the preprocessing mismatch between pretraining and target distributions. This study isolates preprocessing mismatch as a controlled experimental factor in transferring the Hydro multispectral foundation model, a Swin Transformer V2 Base encoder pretrained with SimMIM on Sentinel-2 Level-2A water-body imagery, to the Marine Debris and Oil Spill (MADOS) marine pollution benchmark dataset, processed through ACOLITE Rayleigh reflectance and providing 11 of the 12 spectral bands used during pretraining. The two datasets are therefore produced by different atmospheric correction algorithms under different reflectance conventions, and the resulting per-band statistical discrepancy is quantified as the starting point of the analysis. Three preprocessing dimensions are then systematically varied while all other settings are held constant: input normalisation, spectral band adaptation for the missing B09, and encoder transfer mode. From this, four findings emerge. Normalisation mismatch between training and inference is the single largest source of performance degradation, reducing the mean Intersection over Union (mIoU) by 0.458, more than seven times the largest radiometric perturbation tested. A zero-parameter Frobenius-matched column crop of the patch embedding adapts the 12-band pretrained encoder to the 11-band target, at least as effectively as any learnt linear or nonlinear adapter, at a lower cross-seed variance. Under limited target supervision (1433 training patches against an 87.9 million-parameter encoder), freezing the encoder outperforms both fine-tuning in full and random initialisation training from scratch. The gains of partial unfreezing are attributable to augmented training (very simple copy–paste (VSCP) augmentation, exponential moving average (EMA), and test-time augmentation (TTA)) rather than to encoder adaptation. With matched preprocessing, the frozen encoder reaches 0.600 mIoU and matches the published MariNeXt baseline within seed variability. Mechanistic analysis via band-occlusion attribution and feature-space separability shows that input normalisation determines which spectral bands the encoder relies upon, with the magnitude of the shift correlated to the per-band gap between the source and target distributions. Operationally, preprocessing alignment, rather than architectural modification, carries most of the practical effort in transferring a multispectral foundation model to marine surface segmentation. These results are established for a single encoder–benchmark pair under limited target supervision. The mechanism they identify is more portable than the magnitude reported. A frozen encoder’s representations remain bound to the normalisation statistics of its pretraining dataset, so any transfer that departs from these statistics at inference is predicted to degrade sharply in proportion to the per-band distance between the two distributions. Full article

With continuing advances in interfacial sensing and tunable micro-optics, the potential applications of hemispherical nematic droplets in these fields have received increasing attention. Local variations in surface anchoring can modify their director configurations and thereby produce distinct optical responses. However, the specific manner in which anchoring conditions govern director configurations and defect formation remains poorly understood. Using the Landau–de Gennes theory, we investigate a model of a hemispherical droplet bounded by a curved surface and a planar base, with homeotropic easy-axis orientations prescribed at both interfaces. Four anchoring scenarios are compared: uniform anchoring, continuously varying curved-surface anchoring, localized weak-anchoring bands placed at different positions, and combinations of curved-surface and planar-base anchoring strengths. The results show that droplet size, spherical-cap height, and the strength and spatial position of anchoring all affect the director defect formation. Reducing the curved-surface anchoring strength near the contact line allows the director field to vary more continuously in this region, thereby suppressing the formation of the ring-shaped defect-core region. Distinct configurations, including a split-core structure near the symmetry axis, are obtained when the planar-base anchoring strength is varied under strong curved-surface anchoring. Full article