Search Results (2,892)

Although aluminum phosphide nitride/gallium nitride (AlPN/GaN) high electron mobility transistors (HEMTs) have been extensively investigated for high-power and high-frequency applications, systematic studies on their intrinsic radio frequency (RF) noise characteristics remain limited. In this work, the RF noise performance of AlPN/GaN HEMTs is investigated using a physics-based TCAD framework, in which a conventional AlGaN/GaN HEMT is first calibrated against the published electrical characteristics of a fabricated device and subsequently modified by replacing the AlGaN barrier with an AlPN barrier while maintaining identical device geometry and operating conditions. The effects of phosphorus mole fraction, AlPN barrier thickness, and substrate material on intrinsic noise behavior are systematically analyzed to optimize device performance Optimizing the phosphorus composition modifies the polarization-induced charge and carrier confinement at the AlPN/GaN heterointerface, resulting in improved carrier transport and reduced simulated RF noise. A comparative study of silicon (Si) and silicon carbide (SiC) substrates further demonstrates that the superior thermal conductivity and lattice compatibility of SiC improves heat dissipation and suppress defect related fluctuations, resulting in lower intrinsic device noise. The optimized AlPN/GaN HEMT on a SiC substrate achieves a minimum noise figure of 1.8 dB at 20 GHz, demonstrating the effectiveness of barrier engineering and substrate optimization for improving the intrinsic RF noise performance of AlPN/GaN HEMTs and providing design guidelines for next-generation low-noise microwave and RF front-end applications. Full article

Hydrogen fuel-cell forklifts are attracting increasing attention as low-noise and zero-emission alternatives to conventional forklifts. Owing to its high volumetric hydrogen density and favorable safety characteristics, metal-hydride storage shows strong potential for such applications. This work focuses on a hydrogen fuel-cell forklift using metal hydride-based hydrogen storage. A hybrid powertrain model with a PEMFC and battery is developed from thermodynamic and electrochemical formulations. Hydrogen desorption behavior in the storage tank and transient responses of both power sources are considered, and three energy management strategies are evaluated: rule-based, fuzzy logic, and adaptive fuzzy logic strategies. Under typical operating conditions, each strategy satisfies the forklift power demand in simulation. Compared with rule-based control, adaptive fuzzy logic control markedly suppresses fuel-cell power fluctuations. Compared with basic fuzzy logic control, the proposed adaptive strategy improves SOC retention and overall energy distribution. These findings may provide preliminary support for powertrain matching, hydrogen storage system parameter selection, and energy management design in hydrogen fuel-cell forklift applications. Full article

In this work, Intelligent Bidirectional Long Short-Term Memory with Temporal Fusion Transformer-based prediction and Proximal Policy Optimization (IBT-PPO) is proposed in response to the challenges of uncertain renewable generation, fluctuating demand, and inefficient energy scheduling in hybrid renewable energy systems. The algorithm is based on a dual-stage framework that integrates machine learning forecasting with reinforcement learning-based planning. Initially, a hybrid Bi-LSTM-TFT model is employed to generate accurate short-term forecasts of wind power, solar power, and demand, which employs temporal dependencies and multi-horizon patterns. After that, the PPO strategy is designed to optimize scheduling decisions, adaptively balancing battery usage, grid reliance, and renewable dispatch. To enhance robustness, adaptive feature weighting and temporal gating strategies are incorporated, ensuring stable convergence and reduced planning redundancy. Subsequently, the energy allocation is refined through iterative learning to minimize operational cost and maximize renewable penetration. The proposed framework is evaluated as an offline/post hoc forecasting and scheduling approach, with the Bi-LSTM–TFT module exploiting historical temporal representations and the PPO agent optimizing energy-management decisions based on the resulting forecasts. The experimental evaluation is carried out using the Open Power System Data (OPSD) dataset, which provides realistic time-series data for wind, solar, demand, and electricity prices. Thus, the IBT-PPO system integrates multi-horizon probabilistic forecasting and adaptive feature weighting for better prediction and planning accuracy and achieves a 24.1% cost reduction and 95.5% renewable utilization, thereby advancing efficient and intelligent energy prediction and planning. Full article

We propose a resolution-adaptive Bayesian wavelet-denoising method for noisy one-dimensional signals. The main contribution is a spike-and-slab prior whose continuous slab is a mixture of a compactly supported Wendland-type polynomial kernel and the semicircle density, with data-adaptive, resolution-specific mixture weights, produced by a low-dimensional empirical-Bayes trend. The Wendland component concentrates mass near zero and vanishes smoothly at the support boundary, whereas the semicircle component is more dispersed. This construction combines explicit sparsity and support control with an interpretable mechanism for adapting the shrinkage shape across resolutions. Under squared-error loss, we derive the posterior-mean estimator; establish key symmetry, boundedness, continuity, and limiting properties; define pointwise fixed-hyperparameter bias, variance, and risk; and develop an empirical-Bayes estimation procedure. The Wendland contribution has finite-sum expressions under a Laplace working likelihood, while the semicircle contribution is evaluated by stable one-dimensional integration. Simulations using the Bumps, Blocks, Doppler, and HeaviSine signals compare the proposed Gaussian- and Laplace-likelihood versions with universal thresholding, false-discovery-rate (FDR) thresholding, cross-validation (CV), Stein’s unbiased risk estimate (SURE), the Bayesian adaptive multiresolution shrinker (BAMS), and a nonlocal-prior (NLP)-based method. In the primary Gaussian-error simulation study, the Gaussian-likelihood version was the strongest non-NLP method in 24 of the 36 design cells, including 11 of the 12 low signal-to-noise ratio (SNR) cells, and had a substantially more favorable computational profile than the Laplace-likelihood version. Analysis of a seismic acceleration trace from the 2008 Chino Hills earthquake illustrates attenuation of rapid fluctuations and preservation of the dominant acceleration event under the chosen diagnostics. Using the processed channel-1 trace as surrogate truth, the corresponding semi-synthetic validation showed that WS–Gaussian improved on the noisy observation at lower and moderate SNRs but not at the highest SNR. Full article

Current-driven manipulation of magnetic domain walls (DWs) in perpendicularly magnetized nanowires is promising for spintronic memory and logic applications. In this work, micromagnetic simulations are used to investigate the depinning of DMI-stabilized Néel domain walls from a stepped pinning site under unipolar square-pulse current excitation. The effects of current density, pulse frequency, duty cycle, Dzyaloshinskii–Moriya interaction (DMI), and temperature are examined. The results show that pulse frequency and duty cycle strongly influence the oscillatory response of the pinned DW and can promote depinning through efficient coupling with localized DW dynamics. Increasing the current density enhances the oscillation amplitude and facilitates escape from the pinning region, while variations in DMI produce marked changes in pinning stability and magnetic configuration. Thermal fluctuations further modify the depinning behavior, particularly for stronger DMI, where the system evolves from stable pinning to thermally assisted escape and, at higher temperatures, to less stable magnetic states. Overall, the results show that pulse parameters, DMI strength, and temperature jointly control DW depinning and stability, providing further insight into the tuning of current-driven DW transport in geometrically confined spintronic structures. Full article

Ultrasonic vibration-assisted machining (UVAM) can improve the machinability of difficult-to-machine titanium alloys; however, the relationship between machining-load fluctuations, subsurface microstructure, and electrochemical response remains insufficiently established. In this study, a wireless in-situ monitoring system was integrated with electron backscatter diffraction (EBSD), electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, and scanning electrochemical microscopy (SECM) to compare conventional milling (CM), low-excitation UVAM (L-UVAM), and high-excitation UVAM (H-UVAM) of Ti-6Al-4V. Under the investigated conditions, H-UVAM reduced the RMS value of the measured axial load signal by 43.3% compared with CM and decreased the variation in the resultant bending-moment signal. The EBSD results showed a reduction in the mean grain size from 11.67 μm for CM to 10.07 μm for H-UVAM, together with an increase in the measured high-angle grain-boundary fraction from 48.27% to 59.39%. Electrochemical measurements further indicated a lower corrosion current density and a higher fitted barrier resistance for the H-UVAM surface. SECM mapping showed a narrower local current distribution under H-UVAM than under CM. These results demonstrate a consistent association between reduced machining-load fluctuations, modified subsurface crystallographic features, and improved electrochemical response. Because surface roughness, residual stress, tool wear, and passive-film chemistry were not independently quantified, the present work does not attribute the corrosion response exclusively to microstructural changes. Instead, it provides a cross-scale experimental framework for correlating machining dynamics with surface integrity and corrosion-related performance in machined titanium alloys. Full article

Background: Global developmental delay (GDD) affects multiple domains of early childhood development, including gross motor, cognitive and communication skills. Early, intensive, family-centered rehabilitation is considered key to optimizing functional outcomes in affected children. Case Presentation: We report a female child with GDD who began rehabilitation at our institution at 15 months of age, presenting with generalized hypotonia with superimposed fluctuating episodes of hypertonia, poor postural control, absent independent sitting, markedly reduced spontaneous motor activity, and associated cognitive and communication delay. Brain MRI at 7 months showed no parenchymal abnormality, with mildly enlarged extracerebral cerebrospinal fluid spaces and ventricular system. The metabolic and genetic evaluation performed so far, including microarray/MLPA-based screening for common microdeletion syndromes and SMN1/SMN2 genotyping, has not identified a specific underlying etiology. Diagnostic work-up is ongoing. Rehabilitation was delivered as a comprehensive, multidomain program; this report focuses specifically on the child’s motor progression. Intervention: The child underwent the Early Intensive Stojčević-Polovina Rehabilitation Method (EIR-SPM), a high-intensity, continuous approach for children with cerebral palsy, at-risk infants, and other developmental disabilities, built on parental education enabling home-based continuity of therapy. Rehabilitation focus is selected according to the child’s optimal developmental stage—the milestone showing the least abnormal movement patterns and muscle tone—rather than chronological age, with positions progressively adjusted following the trajectory of typical motor development described by Vojta. Results: Gross motor function, monitored using the Gross Motor Function Measure–88 (GMFM-88) at four assessment points from 15 months to 6 years 6 months of age, improved progressively from 10.8% to 48.9%, 64.7%, and finally 73.9%. The child achieved independent kneeling, reciprocal crawling, independent sitting in all positions, independent standing and assisted stepping. Conclusions: In this child with GDD of undetermined etiology, more than five years of intensive, family-centered rehabilitation according to the EIR-SPM were accompanied by substantial and sustained gains in gross motor function and functional independence. This report suggests that meaningful progress remains achievable even when rehabilitation begins later than the period considered optimal within the EIR-SPM framework, and that a family-centered structure may be what makes therapy of this intensity and duration sustainable. Full article

In this work, we present a method for correcting attitude-dependent fluctuations in fixed-bias Langmuir probe ion density measurements from small, spin-stabilized sounding rocket dropsondes. The approach resolves dropsonde attitude using three-axis magnetometer data, observations from the Langmuir probe itself, and an analytical model of the sonde’s rotational motion. Together, these inputs constrain the dropsonde’s angular momentum vector in inertial space and enable reconstruction of its time-resolved attitude without requiring prior knowledge of the sonde’s orientation at deployment. The derived attitude solution is then used to correct the Langmuir probe ion density measurements for orientation-dependent changes in collection geometry caused by the sonde’s precessional motion. This technique is applied to data from the August 2022 Sporadic E Electrodynamics Demonstration (SpEED Demon) sounding rocket campaign, in which four dropsondes were ejected. Validation is performed by comparing attitude-corrected dropsonde ion density measurements to those of the main payload in a near-coincident measurement regime. The corrected data show strong agreement with the main payload observations, demonstrating that this technique can recover physically consistent ion density profiles from spin-stabilized dropsonde measurements. Full article

Modulated by diverse climatic and oceanic forcing factors, the sea ice durations in the nearshore waters of the Bohai and northern Yellow Seas exhibit complex fluctuations on interannual and interdecadal timescales. Systematically analyzing the oscillatory patterns and trend stationarity of long-term sea ice duration series provides robust theoretical and practical guidance for coastal ice disaster early warning, marine industrial safety, and coastal economic sustainability. This study analyzes annual sea ice duration series recorded over 59 winters (1966–2024) at six representative coastal marine stations spanning the full spatial gradient of regional ice regimes across the Bohai and northern Yellow Seas. Isolated missing values were filled by linear interpolation, and the Ljung–Box Q test confirmed that the residual series do not follow a white-noise process. Two categories of stationarity tests—conventional unit root tests and Fourier series expansion-augmented stationarity tests—are adopted to quantify the stationary properties, nonlinear trend transitions, and smooth structural breaks of sea ice durations at each station. The results reveal marked spatial differences in interannual volatility and evolutionary trends among stations: two smooth transitional shifts are identified for Bayuquan (BYQ) and Qinhuangdao (QHD), whereas the remaining stations each exhibit a single shift. Long-term trends range from multistage declining patterns to a rising pattern for Donggang (DGG), while Zhimaowan (ZMW) shows a statistically insignificant trend. This work provides quantitative statistical evidence for sea ice risk evaluation and coastal structural safety protection across the Bohai and northern Yellow Seas, and offers actionable decision-making references for climate change adaptation and integrated coastal zone governance in ice-affected coastal zones worldwide. Full article

Hypoxia is a hallmark of the tumor microenvironment. Under hypoxia, HIF-1$\alpha$ accumulates and promotes both epithelial–mesenchymal transition (EMT) and glycolysis depending on glucose levels. However, how EMT and glycolysis are coordinated by oxygen and glucose abundance is still not well understood. Here, we developed an integrated model to investigate the mechanism underlying the regulation of EMT and glycolysis at varying oxygen and glucose levels. We focused on how the interplay between EMT and glycolysis maintains cell phenotypes. Our results show that hypoxia and sufficient glucose facilitate the transition of cells toward an invasion-associated mesenchymal–glycolytic phenotype. Moreover, enhanced glycolysis promotes the completion of EMT and reinforces the intermediate states. Under glucose-sufficient conditions, the reciprocal promotion between EMT and glycolysis may convert transient hypoxia into persistent mesenchymal memory that maintains the mesenchymal phenotype after reoxygenation. Our work clarifies how metabolic microenvironmental fluctuations are transformed into durable invasion-associated phenotypic states. Our work may provide insights into therapies that target both the EMT and glycolysis pathways. Full article

Plant growth-promoting bacteria (PGPB) are increasingly deployed as biofertilizers, yet the link between an inoculant’s genomic potential and its realized effect on the plant is rarely assessed within an integrative framework that jointly captures the rhizosphere microbiome, plant phenotype, and strain genome. Two Bacillus strains—B. halotolerans 1453 and B. pumilus 630—were applied to wheat and soybean in a factorial pot experiment (2 strains × 2 application methods × 3 frequencies + control, 3–4 replicates). Rhizosphere samples (n = 67 after filtering) were profiled by 16S rRNA sequencing with PICRUSt2 functional prediction and compositional validation (Aitchison PERMANOVA, ALDEx2, ANCOM-BC2). The PGPB gene repertoire was characterized by genome mining (481 marker genes, 14 categories). Wheat phenotype (six traits) and soybean height were analyzed with models appropriate for count data (Negative Binomial and binomial GLMs) for treatment-vs.-control comparisons, and with factorial ANOVA for decomposition into main effects and interactions. Crop identity was the dominant factor shaping both microbiome structure and function (PERMANOVA R² = 14.7% taxonomically and R² = 7.8% functionally, both p < 0.001), with biologically meaningful taxonomic differences between wheat and soybean; strain, application count and method had no significant effect on community composition (R² < 4% each), and co-occurrence networks showed no reliable differences between crops once read depth and sample size were controlled for. Despite this neutrality at the microbiome level, inoculation significantly increased wheat spike count (NB-GLM, all 12 treatments vs. control, padj 0.0002–0.031), ear weight, and stem count, with application count the strongest source of variability and a pronounced strain × application count. Strain 1453 outperformed 630 in spike count (+23.1%, p = 0.012) and ear weight (+20.4%, p = 0.023); we hypothesize that this may be related to its more complete DNRA pathway (narGHI + nirB-nirD) and biocontrol genes (bacE, srfAA). Strain 630 produced a less pronounced effect than strain 1453 but was subject to smaller fluctuations across replicates (CV ≈ 16–21% vs. ≈24–26% for 1453), which may reflect better resilience to environmental fluctuations, possibly due to its confirmed rsbV/rsbW stress-tolerance regulon. Rhizosphere microbiome composition differed clearly by crop (wheat vs. soybean) but showed no detectable response to strain, application method, or application count. Despite this lack of a microbiome signal, inoculation significantly increased wheat spike count and ear weight, with the magnitude and stability of this effect differing by strain. We hypothesize that this strain-dependent difference relates to underlying genomic differences—particularly in nitrogen metabolism (DNRA pathway) and stress-tolerance genes—though this link has not been tested directly and remains a hypothesis for future work. Full article

Panax ginseng (Panax ginseng C.A. Mey.) produces pharmacologically valuable ginsenosides. WD40-repeat (WDR) proteins act as versatile regulators of plant specialized metabolism, yet their biological roles under methyl jasmonate (MeJA) elicitation remain largely uncharacterized in ginseng. In this study, we identified 29 PgWDR family members at the whole-genome level, and systematically analyzed their phylogeny, gene structure, cis-acting promoter elements, as well as organ- and development-dependent expression patterns. Six candidate genes potentially associated with ginsenoside biosynthesis were screened through integrating gene–metabolite correlation analysis and gene co-expression analysis. Under MeJA treatment, three of these candidates showed statistically significant expression responses, while the other three exhibited variable expression fluctuations with no statistical significance. PgWDR24 displayed a positive correlation with key ginsenoside biosynthetic enzyme genes, and a negative correlation with protopanaxadiol-type ginsenoside accumulation. Combined with its predicted nuclear localization, we hypothesize that PgWDR24 participates in the negative modulation of protopanaxadiol-type ginsenoside accumulation, although further genetic functional validation is still required. This work provides valuable candidate genes for deciphering ginsenoside regulatory networks and offers support for molecular-assisted breeding of high-quality ginseng. Full article

Silicon photomultipliers (SiPMs) are widely used in high-energy physics, medical imaging, and other photon-counting applications. While their nonlinear response at high light intensities is well known, its impact on the statistical fluctuations of the detector output remains much less understood. In this work, we develop an analytical framework for the variance of the charge response of passive-quenching SiPMs in the two limiting cases of instantaneous light pulses and pulses much longer than the pixel recovery time. Based on these exact results, we propose a phenomenological model that describes the variance of the SiPM charge response for arbitrary pulse durations while accounting for pixel recovery and correlated noise. The resulting framework is then used to predict the photon-counting resolution over the full dynamic range of the detector. The model is validated through Monte Carlo simulations and experimental measurements performed with laser, LED, and scintillation light sources. The results show that the optimal photon-counting resolution is generally reached well beyond the onset of nonlinear response, since pixel saturation introduces sub-Poissonian fluctuations that partially compensate for the nonlinear compression of the SiPM response. These findings provide a practical framework for predicting photon-counting resolution and optimizing the operation of passive SiPMs over a wide dynamic range. Full article

Hydrogen-powered heavy-duty vehicles (HHDVs) operating under multiple driving conditions are subjected to coupled longitudinal, vertical, and lateral dynamic excitations, which significantly affect their dynamic performance and rollover stability. To investigate these characteristics, a coupled vehicle dynamic model consisting of a vertical dynamic model and a yaw–roll dynamic model was established, and numerical simulations were conducted under multiple operating conditions. The effects of operating condition, road roughness, initial braking speed, and braking deceleration on ride comfort and dynamic tire load were systematically analyzed. Furthermore, rollover stability was evaluated under J-turn, Fishhook, and Double Lane Change (DLC) maneuvers using yaw rate, slip angle, lateral acceleration, and lateral load transfer ratio (LTR) as evaluation indices. The simulation results show that braking causes the greatest deterioration in ride comfort, with the peak human–seat vertical acceleration increasing by 33.10% compared with the constant-speed condition, while acceleration results in a 27.55% increase. Road roughness substantially affects both ride comfort and dynamic tire load. Under braking, the peak front and rear tire dynamic loads on a Class D road are approximately 3.1 and 2.9 times those on a Class B road, respectively. Increasing the initial braking speed intensifies dynamic responses, whereas increasing the braking deceleration effectively suppresses tire dynamic load fluctuations. Among the three steering maneuvers, the Fishhook maneuver exhibits the highest rollover propensity, with the maximum absolute LTR approaching 0.8. These simulation-based findings provide insights into chassis parameter optimization, vehicle dynamic performance evaluation, and rollover prevention of HHDVs under multiple operating conditions. The present study is limited by the lack of experimental validation of the developed dynamic models, and experimental or hardware-in-the-loop validation will be considered in future work. Full article

The transition from single-device characterization to array-level simulation remains a critical challenge in the development of three-terminal synaptic transistors for neuromorphic computing, as most existing simulation studies either extract parameters from a single representative device and apply them uniformly, or rely on weight-update strategies originally designed for two-terminal memristors. Here, we establish an experimentally calibrated behavioral simulation framework based on differential conductance-pair mapping (W = G⁺ − G⁻, where G⁺ and G⁻ denote the conductances of the positive and negative devices of each pair), integrating exponential long-term potentiation/depression (LTP/LTD) update rules with a posteriori screening mechanism (isValid) to systematically investigate how update polarity, step size, nonlinearity, and conductance boundaries regulate network computational efficiency. Through comprehensive simulation on the Neural Circuit Policies network, we demonstrate that the update direction must strictly align with the matrix’s role: the G⁻ channel requires unidirectional long-term depression inhibition, while the G⁺ channel can be frozen or bidirectionally updated. The optimal G⁻LTD and G⁺G⁻LTD strategies achieve accuracies of 0.9208 and 0.9481, respectively. Furthermore, we reveal a unique nonlinear gain effect under long-term depression > 0, where accuracy increases monotonically with nonlinearity level up to 0.9419. Device specification criteria are established: LTP-dominant updates favor large G_max, while LTD-dominant updates favor high G_min, with the G⁻LTD and G⁺G⁻LTD strategies showing accuracy fluctuations within ±0.005 across the tested boundary variations. Finally, the array-level implementation is validated through a functional-correctness check and device-parameter ablation experiments on a 23,715-weight array (47,430 differential conductance elements). This work provides an experimentally calibrated behavioral simulation platform and concrete algorithm-hardware co-design guidelines for future neuromorphic hardware, prioritizing synaptic devices with long-term depression > 0, a moderately elevated G_min, and asymmetric resource allocation toward LTD-side optimization. Full article