Search Results (46,395)

:Resonant mass sensors based on micro/nanoelectromechanical systems (MEMS/NEMS) offer a promising approach for label-free gravimetric detection. However, practical applications often require not only high sensitivity but also improved loading repeatability and reduced dependence on mass loading position. In this work, a suspended resonant mass sensor based on a 10 nm-thick Hf_0.5Zr_0.5O₂ (HZO) piezoelectric film is proposed. A central silicon loading platform is introduced to provide a mechanically robust and spatially uniform sensing region. A Kirchhoff plate model incorporating residual stress is established to analyze the effects of residual stress and platform geometry on the resonant characteristics. The device is fabricated by combining SOI micromachining with wet transfer of the ultrathin HZO film. Laser Doppler vibrometry measurements show a first-order resonant frequency of 1.303 MHz and a quality factor of 342, corresponding to an extracted residual stress of approximately 1.319 GPa. Finite element simulations calibrated by experimental parameters indicate a uniform first-mode displacement distribution and a linear frequency response to added mass from 0 to 1 ng. The obtained mass sensitivities are 150.7 Hz/pg and 166.8 Hz/pg from finite element and analytical models, respectively. The proposed structure provides a feasible route toward repeatable pg-level resonant mass sensing based on ultrathin piezoelectric films. Full article

A transient multibody dynamics simulation of rolling-element bearings is the basis for the design of high-speed rotating machinery; however, the established solvers are proprietary, cannot be used with automatic differentiation, and offer no built-in measure of their own physical consistency. We present OpenBEARD, an open-source, fully differentiable transient dynamics solver for angular-contact ball bearings. The solver steps a $40+13Z$-component state (inner ring, cage, and Z balls with quaternion attitude, plus guide-patch, lumped-thermal, and energy-audit states) forward in time under coupled Hertzian contact, Hamrock–Dowson and full-multigrid elastohydrodynamic lubrication, thermal–elastohydrodynamic traction, and centrifugal/press-fit clearance models, using nondimensionalized implicit stiff time integration. A built-in metriplectic conservation audit checks energy closure, the second law per dissipation channel, and the gyroscopic-power identity at every output step. OpenBEARD is cross-verified against two published ADORE references of Gupta. For a high-speed NASA angular-contact ball bearing, the quasi-static contact loads, angles, stresses, and centrifugal force match the published values to within $0.3\%$, and the ball spin and orbital velocities and the spin-axis orientation to ≤0.1%. The inner-race spin-to-roll ratio—a slip-derived secondary quantity that is the most model-sensitive metric in this class of solvers—differs from the NASA quasi-static reference by $8.8\%$. In the separate caged BallBearingTestCase benchmark, the corresponding quasi-static difference is $3.2\%$, and the transient settled value is $\approx 16\%$ above the ADORE step-100 snapshot; these bounded offsets reflect different spin-moment constitutive models. The BallBearingTestCase comparison—a caged bearing under combined thrust and radial load—matches the per-ball contact angles and loads to within $0.23\%$ RMS, and a single published dynamic snapshot (step 100) agrees with the transient contact mechanics to within a few percent. The built-in energy-closure residual stays of order ${10}^{-5}$ with no second-law violations. In the fully transient regime, race control emerges as a dynamical attractor of the coupled traction balance—ball-spin states perturbed by $\pm 12\%$ converge to a single outer-race-control solution—rather than the kinematic hypothesis assumed by quasi-static theory. OpenBEARD is released under the MIT license. Full article

In order to address the issue of rapidly divergent positioning errors of a single-platform inertial navigation system (INS) in GNSS-denied environments, this paper proposes a cross-platform cooperative navigation method based on relative range and angle measurements. The observability of the cooperative navigation system under different motion strategies is investigated using Fisher information matrix (FIM) right null-space analysis combined with singular value decomposition (SVD). The results show that with relative range and angle measurement constraints, all inertial sensor biases can be effectively estimated by two strapdown inertial navigation systems (SINSs) moving along a simple trajectory, thereby improving the navigation accuracy. Experimental results demonstrate that compared to the autonomous navigation mode, the average positioning accuracy of the two SINSs improves by 77.4% and 68.4% respectively after 3 h of cooperative navigation along the prescribed trajectory. Using relative range and angle measurements, the proposed method requires only two SINSs and relatively simple planar motion, without the need for high-precision reference benchmarks, complex three-dimensional excitation trajectories, or turntable modulation. It reduces system complexity and motion requirements, providing an effective and easy-to-implement solution for ground vehicular positioning and orientation and other cross-platform cooperative navigation tasks in GNSS-denied environments. Full article

This study comprehensively investigates the thermal and mechanical degradation behavior of molded glass-fiber-reinforced plastic (GFRP) grating composites subjected to temperatures ranging from 80 °C to 320 °C. Three types of industrially produced GFRP gratings—open-type (OG), thin closed-skin (CG), and thick closed-skin (TCG)—were evaluated using mechanical, microstructural, chemical, and crystallographic analyses. Three-point bending tests revealed that TCG-type specimens exhibited superior thermal resistance, experiencing only a 43.9% loss in strength at 320 °C, whereas OG-type specimens showed significant resin degradation, fiber–matrix decomposition, and microcrack formation at temperatures above 200 °C. Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) analyses revealed significant resin degradation, fiber–matrix decomposition, and microcrack formation. Thermogravimetric analysis (TGA) and Differential Scanning Calorimetry (DSC) confirmed substantial mass loss and structural disintegration at temperatures above 200 °C. Dynamic Mechanical Analysis (DMA) results revealed that the glass transition temperature (Tg) occurred at approximately 115–120 °C. The second-order regression model developed to estimate flexural strength under increasing temperature provided high accuracy (R² > 0.99) for all grating types. It should be noted that this investigation focuses on the short-term thermo-mechanical response under fundamental flexural loading to provide an accurate baseline for preliminary engineering design. The findings emphasize that the effect of temperature should be considered a critical parameter in the structural design of GFRP systems, especially in industrial environments with temperatures above 120 °C. Accordingly, tables for material selection and load-carrying capacity should be recalibrated to account for short-term temperature effects. Full article

This study examined the acute effects of high-intensity interval training (HIIT) and prolonged endurance training (ET) on heart rate variability (HRV) in elite Greco-Roman wrestlers and assessed the usefulness of HRV for monitoring post-exercise recovery. Using a longitudinal, within-subject, repeated-measures design, 13 elite male wrestlers completed two training protocols—differing in intensity, duration, modality, and work–rest structure—in a fixed, non-randomized order (ET on Day 7, HIIT on Day 22), separated by a 15-day washout period. HRV was recorded at baseline, pre-exercise, during training, and 24 h post-exercise, and analyzed with a linear mixed model and Bonferroni-adjusted post hoc comparisons. A significant main effect of Timepoint was found for all HRV parameters (SDNN, RMSSD, LF/HF ratio, and the lnRMSSD-derived HRV Score), reflecting marked reductions during exercise and partial recovery by 24 h (e.g., SDNN decreased by approximately 73% in ET and 82% in HIIT). SDNN also differed significantly between training types overall, but heart rate did not differ between protocols during exercise (p = 0.127). No between-protocol difference for any HRV parameter survived Bonferroni correction at any timepoint, despite a large effect size for the HRV Score during exercise (d = 0.79); the corresponding effect for raw RMSSD, the primary time-domain outcome, was small (d = 0.36) and non-significant. Both protocols showed comparable recovery at 24 h. Because protocol order was fixed rather than randomized, these findings should be interpreted as a comparison between two specific field-based conditioning sessions rather than a controlled test of exercise intensity alone. Full article

Existing metaheuristics for the permutation flow-shop scheduling problem primarily explore the search space directly. This study presents a new decomposition technique that, unlike those methods, repeatedly solves one-machine subproblems and extends their solutions to all machines in order to minimize the makespan objective. To this end, the proposed algorithm solves the one-machine problem using a novel forward-backward procedure and extends its solutions to all machines through recurrent displacement of jobs. The improvement of the current solution proceeds until no optimal permutation for a single machine can improve the overall permutation for all machines, gradually improving current solutions and directing the search towards obtaining high-quality solutions. To further improve the results, any solution proposed by the one-machine solution strategy is refined by a local search process. An innovative triangular mechanism is also proposed for constructing initial solutions, with the aim of providing a high-quality starting point for the algorithm. The results of computational experiments not only demonstrate the efficiency of the one-machine forward-backward technique, but also indicate that the algorithm is both robust and highly effective in solving the standard benchmark instances. Full article

To reduce the computational burden of conventional spectral search direction-of-arrival (DOA) estimation algorithms for acoustic vector sensor arrays (AVSAs), this paper proposes a low-complexity DOA estimation method based on semi-real-valued noise power invariance (SR-NPI). The proposed method is developed for centrosymmetric AVSAs under the required steering-vector parity and pressure-channel conjugate-symmetry conditions after pressure–velocity (PV) co-processing. The AVSA measurements are first preprocessed through PV co-processing, and a pseudo-data covariance matrix is then reconstructed by exploiting the complex conjugate relationship between the true DOAs and their symmetric virtual DOAs. By introducing a scanning source into the reconstructed covariance matrix, a DOA-dependent spatial spectrum is constructed according to the eigenvalue-ordering behavior. Since the reconstructed matrix contains both the true DOAs and the symmetric virtual DOAs, the angular search range can be reduced to one half of the original domain. Under the tested configuration, the proposed method reduces the computational cost to approximately 1.92% of that of the original NPI algorithm. Simulation and sea trial results indicate that SR-NPI can maintain competitive estimation accuracy while significantly reducing computational complexity under the centrosymmetric-array conditions. Full article

Data-driven methods have been extensively used for state of charge (SOC) estimation be-cause of their nonlinear regression capability. However, when the driving cycle differs from the training conditions, their estimation accuracy may deteriorate because of insuf-ficient generalization ability. This problem becomes more pronounced under complex un-seen dynamic conditions, while some data-driven methods also suffer from high compu-tational complexity, which further limits their practical application. To overcome these issues, this study presents a LightGBM-regulated and residual-compensated adaptive ex-tended Kalman filter method for SOC estimation. In the proposed method, battery dy-namics are represented by a second-order equivalent circuit model, while SOC is recur-sively estimated using an adaptive extended Kalman filter (AEKF). LightGBM is used to predict covariance adjustment coefficients for adaptively regulating 𝑄 and 𝑅 , and to compensate for the remaining SOC estimation error after AEKF processing. The proposed method is validated under multiple dynamic driving cycles and different temperature conditions. The experimental results of the main unseen-cycle tests show that the pro-posed method achieves good estimation accuracy and generalization performance under unseen driving cycles, with the maximum error (ME) and root mean square error (RMSE) not exceeding 2.26% and 1.28%, respectively. Full article

As data-center interconnects move to co-packaged optics (CPO), high-power application-specific integrated circuits (ASICs) and heat-sensitive optical engines share a single interposer, and the resulting intra-module thermal coupling overwhelms conventional schedulers. Thermal-aware microservice directed acyclic graph (DAG) scheduling on CPO modules is recast here as a question of symmetry. Whereas a homogeneous-graph policy assumes the full node-permutation symmetry, that symmetry is broken twice: by the distinct task and processor node types, and by the asymmetric ASIC–engine coupling. We therefore propose a heterogeneous-graph Proximal Policy Optimization (PPO) scheduler in which the placement head is permutation-equivariant, the delay head is permutation-invariant, and the parameterization stays invariant to the processor count N. Because these symmetries hold by construction, the policy transfers zero-shot across module sizes. Heterogeneous edge typing and the resistor–capacitor (RC) coupling edge attribute are isolated by a six-test ablation chain. Evaluated on the Alibaba 2021 microservice trace across all module sizes and ambient regimes under the standard auto-cool budget, the proposed scheduler cuts the thermal-violation rate from roughly $98\%$ under the Heterogeneous Earliest-Finish-Time (HEFT) heuristic to about $0.3\%$; at the hot operating point it lowers peak temperature by about $25\%$ and raises DAG completion from about $26\%$ to $100\%$, with the rare residual violations most frequent in the extreme-ambient band. With the env auto-cool budget disabled, a controlled single-axis comparison shows that removing the RC-coupling edge attribute raises the violation rate by over an order of magnitude, isolating its contribution. A single parameter set serves every N without retraining. Full article

In industrial trajectory planning and real-time motion control, quintic B-splines are widely used for corner smoothing owing to their local support and high-order continuity. However, existing evaluation methods mainly rely on basis-function recursion or the de Boor algorithm, with limited attention paid to the analytical properties of fixed-topology continuity-constrained structures. This study reveals that, under geometric symmetry and C³ continuity constraints at the junction points, higher-order derivative control-point structures undergo progressive geometric degeneration, whereby second- and third-order derivatives reduce to one-dimensional forms governed by a single direction. Based on this degeneration property, a closed-form reconstruction method for fixed-topology quintic B-spline corner smoothing is developed, yielding unified closed-form expressions for curve position and first- to third-order derivatives. Mathematical analysis proves equivalence between the proposed reconstruction and the original quintic B-spline representation. Numerical validation and efficiency evaluation demonstrate machine-precision consistency with conventional B-spline evaluation while achieving an approximately 3–7-fold speedup in curve and derivative evaluation. System-level trajectory-planning simulations further confirm reduced geometric computation load. The proposed method provides an efficient analytical evaluation framework for real-time trajectory planning and demonstrates how continuity constraints can be exploited to derive efficient analytical spline representations. Full article

With the widespread adoption of digital images in network transmission and storage, the demand for image privacy protection keeps rising. We propose a robust scheme combining a four-dimensional variable-order fractional hyperchaotic system (4D-VOFHS) and a chess-game play-inspired dynamic mechanism. Firstly, we construct 4D-VOFHS, to overcome inherent limitations of constant-order systems: unlike constant-order systems that are vulnerable to deep-learning-based parameter identification attacks, this system introduces time-varying orders and high-dimensional coupling to enrich nonlinear dynamics. Secondly, inspired by the dynamic strategic interactions within chess gameplay, we design a synchronous encryption framework with a tightly coupled permutation–diffusion mechanism. This design not only significantly enhances the nonlinear complexity, confusion and diffusion performance of the algorithm, but also enables parallel synchronous processing to improve computational throughput. Finally, we propose a block-based collaborative scrambling strategy with multi-chess-piece rules, wherein traversal rules and scrambling operations are not predefined; instead, they are dynamically updated according to the real-time state evolution of the 4D-VOFHS. Through comprehensive correlation analysis and differential attack tests, the presented encryption framework achieves outstanding performance metrics: an average NPCR of 99.6%, a UACI of 33.4%, and an average information entropy of 7.9993. Overall, these results verify the strong cryptographic robustness and practical applicability of the scheme, highlighting its great potential for deployment in real-world color image encryption systems. Full article

This study examines whether a train fire near an evacuation interface in a railway tunnel can create an adverse configuration relevant to evacuation design and collective risk assessment. It focuses on twin single-track tunnels, in which the parallel tunnel serves as a safe area, and evacuation is carried out through cross-passages and boundary portals. If a fire impairs such an interface, evacuees may be forced to continue to a more distant exit. The problem is formulated as a geometric-probabilistic screening task. The model calculates the probability that, after the train has stopped, the fire lies within a tolerance zone around an evacuation interface. The probability is derived analytically using deterministic convolution and verified via Monte Carlo simulation for trains with lengths of 200 m and 400 m. This verification concerns mathematical calculation only, not the physical, smoke, operational, or evacuation assumptions. The geometric probability is linked to collective risk through representative train fire frequencies, external consequence indicators, and selected F/N criteria. With ε = 37 m and portals included as boundary evacuation interfaces of the finite tunnel domain, the adverse-configuration probabilities are similar: approximately 14.0% for the 200 m train and 14.6% for the 400 m train. The difference becomes decisive only after considering the magnitude of the consequences and the traffic intensity. Under the reference assumptions, the 400 m high-occupancy case reaches the selected Dutch criterion at about four train passages per day. A fire near an evacuation interface, therefore, cannot be treated as marginal solely because the tunnel meets the 500 m cross-passage spacing requirement. Acceptability depends on geometry, occupancy, fire frequency, the definition of consequences, traffic intensity, and the selected risk framework. The homogeneous fire-origin distribution is used only as a neutral first-order assumption; more refined spatial fire-origin models and broader comparisons across safety criteria are needed. Full article

Mononuclear nonheme iron(IV)–oxo species supported by mixed nitrogen–sulfur (N/S) ligands remain scarce, despite the prevalence of sulfur donors in biological iron sites and their expected impact on ferryl reactivity and catalyst design. In this work, a seven-coordinate iron(II) complex, [(N₃S₂)Fe^II(ClO₄)₂], bearing a rigid 15-membered N₃S₂ macrocycle, is shown to rapidly generate a mononuclear nonheme Fe^IV=O intermediate upon reaction with m-chloroperbenzoic (m-CPBA) acid in acetonitrile. The Fe^IV=O species forms within ≤2 s and is thermally persistent (t₁/₂ = 4.3 h at 25 °C), albeit in partial yield (~39% Fe^IV=O by Mössbauer spectroscopy), placing it in an intermediate regime between highly reactive but short-lived ferryl species and more inert, long-lived analogues. The intermediate is characterized by Mössbauer spectroscopy (δ = 0.35 mm s⁻¹, ΔE_Q = 0.90 mm s⁻¹, Γ_FWHM = 0.30 mm s⁻¹, relative area = 39.4%), EPR silence, a UV–vis absorption band at 428 nm, and cryogenic high-resolution ESI–MS (m/z 223.510, (N₃S₂)Fe^IV=O²⁺). Stopped-flow kinetic studies reveal saturation behavior that is well described by a pre-equilibrium oxidant-association model and subsequent O–O bond activation, with apparent activation parameters of ΔH^‡ = 17.7 kJ mol⁻¹ and ΔS^‡ = −155 J mol⁻¹ K⁻¹, indicating a highly ordered transition state within the seven-coordinate N₃S₂ framework under the conditions employed. Functionally, the Fe^IV=O species mediates clean oxygen-atom transfer to triphenylphosphine (k₂ = 8.1 × 10⁻² M⁻¹ s⁻¹) with an effective turnover number of ~12 after correction for the Fe^IV=O yield, establishing that this mixed N/S platform is catalytically competent under mild conditions, though less reactive than state-of-the-art all-nitrogen systems. Collectively, these findings identify the seven-coordinate N₃S₂ macrocycle as a mixed-donor platform that moderately extends ferryl lifetime while retaining measurable oxo-transfer reactivity, providing mechanistic guidance for the development of nonheme iron oxidation catalysts that incorporate sulfur donors. Full article

This study addresses the need for dark-current control and stable current response in planar high-purity germanium (HPGe) detectors for low-energy X-ray detection. A device fabrication strategy based on the coupled optimization of near-surface treatment, N/P junction formation, and guard-ring electrode design is proposed. Unlike previous studies that mainly focused on contact-layer fabrication, segmented electrode structures, low-noise readout, or response simulation, this work investigates low-damage near-surface construction, N-type and P-type contact-layer formation, and edge-related leakage-current regulation as an interconnected processing route. The relationship among the near-surface state, junction quality, electrode configuration, and edge-related leakage current is emphasized. Chemical mechanical polishing (CMP) reduced the surface roughness Sa of the HPGe crystal to 6.68 nm, providing a low-damage near-surface foundation for subsequent junction fabrication. On this basis, the optimized Li thermal diffusion process, namely 0.5 Å s⁻¹, 325 °C, and 5 min, formed an N-type contact layer with preserved lattice ordering and favorable electrical properties. B ion implantation combined with rapid thermal processing (RTP) achieved acceptor activation and implantation-damage recovery, and the condition with Rp = 198.1 nm showed relatively better structural recovery and electrical characteristics. After introducing the guard-ring electrode, the dark current of the device at −20 V decreased from 6.5 × 10⁻⁹ A to 2.03 × 10⁻⁹ A, and a stable switching current response was obtained under 12 keV monochromatic synchrotron X-ray irradiation. Geant4 simulations were further used as an auxiliary analysis to evaluate the effect of the guard-ring structure on the simulated response spectra and full-energy peak efficiency (FEPE) for low-energy X-rays. Overall, this study provides experimental evidence for process optimization of planar HPGe detectors with low dark current and stable low-energy current response. Full article

Scrap-based electric arc furnace (EAF) steelmaking powered by on-site variable renewable energy is a key decarbonisation route, but the heteroscedastic, non-Gaussian nature of joint wind–photovoltaic forecast errors makes the EAF—a large, metallurgically constrained load—hard to coordinate with on-site generation under feeder limits. We develop a unified stochastic dispatch and adaptive setpoint-control framework. A chance-constrained dispatch over a zone-wise Beta uncertainty model is propagated through a degree-two polynomial chaos expansion (PCE) and reformulated as a second-order cone programme via the Cantelli inequality, with EAF-specific metallurgical constraints (electrode slew, short-circuit-ratio-tied flicker, stage-dependent melt-power floor, multi-stage tap-to-tap profile) embedded by the same procedure. The EAF setpoint gain is then extracted in closed form—without Jacobian inversion—as a ratio of first-order PCE coefficients, so it inherits the dispatch’s 95% feeder-security guarantee. Calibrated on 24 months of real wind/PV data for a Qingdao site (ERA5 reanalysis vs. archived ECMWF-IFS forecast), which confirms the heteroscedastic premise and a measured wind–PV error correlation of 0.015, the extracted gain scales across the Low–Mid–High zones (medians 6.07, 11.91, 17.22 p.u.) following the operating regime rather than the disturbance magnitude. The scheme bounds worst-case tracking below 1.18 MW per zone (vs. up to 3.34 MW for no droop), satisfies the feeder limit in 100% of realisations, matches model-predictive control without online optimisation, and lowers within-EAF specific CO₂ emissions by 4.4% versus no droop. An out-of-sample test on real records confirms a decisive advantage in the data-rich zones and, candidly, a shortfall in the data-limited high-wind zone. Full article