Search Results (20,340)

Electrochemical parameter identification is crucial for evaluating the electrochemical processes in proton exchange membrane water electrolysis (PEMWE). Conventional characterization techniques-including polarization-curve fitting, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and current interruption (CI)-face significant limitations for rapid diagnostics under high-current dynamic operation, arising from constraints in instrument current rating, measurement time, zero-current control, and noise amplification in numerical differentiation. In this study, we present a simple current step (CS) method to accurately identify key electrochemical parameters and perform overpotential breakdown by using a simplified equivalent circuit model with a current source. To address the numerical instability in derivative calculation caused by sampling noise during voltage transient analysis, a physics-informed neural network (PINN) is introduced to enhance signal smoothness while guaranteeing physical consist ency. Compared with standard characterization, the proposed CS-PINN method demonstrates high accuracy, with an error of less than 2% in overpotential breakdown, less than 5.3% in ohmic resistance, and 2.8% in the Tafel slope (at 5 A/cm²). These results confirm that the CS-PINN method provides a fast, accurate, and equipment-friendly route for rapid electrochemical parameter identification in PEMWE. Full article

As urban underground spaces and infrastructure development accelerate, subsurface elements such as buried pipelines, integrated utility tunnels, subway tunnels, cavity defects, and deep-seated hidden hazards become increasingly intertwined. Consequently, urban target detection is characterized by pronounced scale discrepancies, intense environmental interference, and severely confined operational spaces. The transient electromagnetic method (TEM) is highly valuable for rapid surveys and hazard identification in urban underground spaces owing to its inherent advantages, including non-contact operation, adaptability to hardened pavements, high sensitivity to low-resistivity anomalies, and the ability to probe a broad range of depths. In recent years, research has shifted from improving isolated instrumentation to synergistically optimizing sensing platforms, transmitter–receiver systems, anti-interference methodologies, and imaging interpretation workflows. Specifically, small-loop configurations and high-frequency excitation technologies have improved shallow-sounding capabilities in confined urban spaces; anti-interference techniques have increased data reliability in complex noise environments; and apparent resistivity mapping, virtual wave-field migration, and rapid inversion methodologies have enabled profiling results to transition from qualitative identification to fine-scale interpretation. Concurrently, the evolution of ground-towed, UAV-borne, helicopter-borne, and semi-airborne platforms has progressively endowed urban TEM profiling with continuous, mobile, and scenario-specific operational capabilities. Looking to the future, further technical breakthroughs in urban TEM technology are required to improve shallow-resolution, deep-seated penetration, multi-source interference decoupling, and real-time concurrent imaging. Full article

Background: Management of high-grade carotid artery stenosis with concomitant ipsilateral parotid gland tumor presents a rare and challenging surgical condition. Due to the rarity of this dual pathology, standardized guidelines are lacking. Material and Methods: A retrospective study was conducted between January 2020 and May 2025. Six asymptomatic patients with significant carotid stenosis and coexisting ipsilateral Warthin’s tumor underwent simultaneous eversion CEA (carotid endarterectomy) and partial superficial parotidectomy/extracapsular enucleation via a single modified Blair’s incision. Results: Median follow-up was 43 months (range: 12–60 months). Postoperative and long-term survival at median follow-up was 100%, with a 5-year survival rate of 83.3% (one death at 50 months due to myocardial infarction). Disease-free survival at 5 years was 100% for Warthin’s tumor and 83.3% for carotid stenosis. No perioperative transient ischemic attacks (TIA), strokes, hematomas, salivary fistula or iatrogenic cranial nerve injuries occurred. Conclusions: In patients presenting with high-grade carotid stenosis and concomitant ipsilateral Warthin’s tumor, a simultaneous surgical approach is a feasible strategy. This approach eliminates the need for staged interventions, significantly reducing overall anesthetic risk, surgical burden, and healthcare resource utilization. Full article

In this study, an adhesive wear model for a gear drive in mixed elastohydrodynamic lubrication (EHL) is proposed. The mixed-EHL model combines the average Reynolds equation with the ZMC rough-surface contact model to determine the asperity contact pressure. By incorporating the fractional film defect into the Archard wear equation, a wear rate model under mixed EHL is developed and verified against published experimental data. This wear-rate model is subsequently coupled with a transient line-contact mixed-EHL model for gears to establish a tooth-surface wear prediction model that iteratively updates the tooth geometry and contact pressure. The evolution of tooth-surface wear under mixed EHL is investigated, and the resulting wear characteristics are compared with those under dry-contact conditions. The influence of tooth-surface roughness is also systematically evaluated. The results indicate that tooth-surface wear is substantially reduced under mixed EHL and that the maximum wear occurs between the lowest point of single-tooth contact and the pitch point. Increasing surface roughness intensifies wear and shifts the maximum-wear location toward the tooth root. These findings demonstrate that appropriate lubricant selection and effective control of tooth-surface roughness are important for improving the wear resistance of gear drives. Full article

Under ground-based observation geometry, infrared radiant-intensity sequences of space objects are jointly influenced by object micromotion, thermal radiation, time-varying viewing conditions, and atmospheric propagation. Existing simulation studies often prescribe the line of sight or simplify the coupling between viewing geometry and atmospheric attenuation, which limits long-duration ground-based sequence analysis. This study develops a physics-informed framework for generating atmosphere-attenuated infrared radiant-intensity sequences of space objects undergoing precession or tumbling. The framework reconstructs observation geometry from azimuth–elevation–range trajectories, updates facet normals through a unified micromotion attitude model, computes visible projected area and transient facet temperature, and incorporates MODTRAN-derived elevation-dependent atmospheric transmittance. Using this framework, we construct IRPeriodic, an eight-class simulated dataset for long-duration univariate time-series classification. We further propose LPD-Net, which integrates large-kernel residual feature extraction, prototype-guided dynamic temporal alignment, and differential periodic representation to capture long-range waveform morphology, sample-dependent temporal correspondence, and segment-level local variation. On IRPeriodic, LPD-Net achieves an accuracy of 0.8618 ± 0.0057, a macro-F1 of 0.8615 ± 0.0061, and a Matthews correlation coefficient of 0.8426 ± 0.0065, outperforming the evaluated neural-network and ROCKET-type baselines. Ablation and synthetic-noise sensitivity analyses indicate that the performance gain is mainly associated with long-context feature extraction, with additional improvements from dynamic alignment and differential periodic statistics. Auxiliary experiments on selected public UCR datasets suggest that the representation is also competitive for univariate time-series classification. These results demonstrate the effectiveness of LPD-Net on the proposed physics-informed benchmark for long-duration ground-based infrared radiant-intensity sequence classification. Full article

This study investigates the dominant mechanisms governing transient-voltage evolution in hydro–wind–solar hybrid systems to address practical engineering requirements. A quantitative index system is constructed to evaluate the factors affecting system transient voltage, and the impacts of key factors are quantified. Specifically, the voltage drop during system faults is mainly affected by fault location and network structure, whereas post-fault recovery depends more on the collaborative process of dynamic reactive power balance and multi-time-scale control. A multi-level transient voltage quantification method is proposed to identify system influencing factors and weak points. The evaluation system comprises maximum voltage drop depth, voltage recovery time, transient voltage severity index (TVSI), hierarchical aggregation indicators, and system-level SSI indicators. The ability of these indicators to characterize systemic risks and disturbance propagation effects is enhanced by introducing fault-point extreme-value correction. The key mechanisms affecting transient voltage stability of hydro–wind–solar hybrid systems are clarified. Multi-scenario analysis shows that transient voltage risks are mainly concentrated in the 220 kV and 110 kV collection layers and are most sensitive during the recovery stage after fault clearing. Detailed quantitative analyses are conducted on four influencing factors: fault location, wind and solar power output, wind-to-solar ratio, and renewable energy penetration rate. Full article

To address the challenges encountered in the simulation and parameter extraction of distributed-feedback (DFB) lasers, this work starts from the rate equations of the DFB laser to derive its steady-state formulation and small-signal model, and constructs steady-state and transient KAN-based physics-informed neural-network (KAN-PINN) architectures. In the steady state, accurate L-I/I–V curves and $-3\mathrm{dB}$ bandwidth results are obtained. In addition, the parameters of the DFB laser are systematically organized, and a KAN-PINN inverse mode, an adaptive moment estimation (Adam) optimizer-based physical inversion, and a hybrid strategy combining the two are proposed. The extracted parameters show small deviations from the true values, and the simulation results agree well with the actual data. The proposed methodology can be extended to other lasers and even to a broader class of optoelectronic devices for parameter extraction and simulation. Full article

Cliff habitats are characterized by limited and heterogeneous water availability, requiring plants to develop adaptive strategies to cope with drought stress. Opisthopappus longilobus, a cliff-endemic Asteraceae species restricted to the Taihang Mountains of northern China, has evolved under persistent water-limited conditions and represents a valuable model for investigating the molecular mechanisms underlying drought adaptation. However, the transcriptional regulatory networks involved in its drought response remain largely unexplored. In this study, we performed RNA sequencing of O. longilobus leaves under control and drought conditions to investigate drought-responsive regulatory networks. Six RNA-seq libraries were generated, and a total of 5260 differentially expressed genes (DEGs) were identified in response to drought stress. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that these DEGs were mainly associated with phytohormone signal transduction, stress-responsive regulation, defense responses, metabolic reprogramming, and transcriptional regulation. Notably, multiple transcription factor families, including MYB, ERF, and ABF, were enriched among drought-responsive genes, suggesting their involvement in drought adaptation. Furthermore, quantitative RT-PCR was used to validate the RNA-seq results. Among the drought-responsive transcription factors, an R2R3-MYB transcription factor, OlMYB35, was identified as a candidate regulator and was further demonstrated to play a positive role in drought response through transient transformation assays. Taken together, this study provides new insights into drought-responsive regulatory mechanisms in O. longilobus and identifies OlMYB35 as a promising candidate gene for further functional validation and potential application in stress-resilient chrysanthemum breeding. Full article

Background: Late-onset neutropenia (LON) and hypogammaglobulinemia are recognized sequelae of rituximab therapy in B-cell non-Hodgkin lymphoma, and both may leave patients vulnerable to infection once treatment has ended. Methods: Fifty-three patients with newly diagnosed, unfavorable diffuse large B-cell lymphoma (DLBCL) who entered remission on dose-adjusted (DA) R-EPOCH immunochemotherapy were retrospectively evaluated. Neutropenia (absolute neutrophil count < 1.5 × 10⁹/L, CTCAE-graded), hypogammaglobulinemia and infections were registered at treatment completion and 6 and 12 months later. Results: All laboratory parameters changed significantly over time. Most reached their nadir at the end of treatment, whereas the absolute neutrophil count alone reached its lowest value later, at 6 months. Neutropenia, largely mild to moderate, affected 17.6% of patients at treatment completion, 22.4% at 6 months and 7.9% at 12 months. Neutropenia at 6 months was a new event, with no overlap with end-of-treatment neutropenia, and was mostly transient. Hypogammaglobulinemia (IgG < 5 g/L) occurred in 33.3%, 16.7% and 20.0%, respectively; median IgG declined to a nadir at the end of treatment and recovered thereafter, although the deficit tended to persist in the same patients. Post-treatment infections were recorded in 73.6% of patients (mostly respiratory); neutropenia was not associated with infection at any time point, whereas end-of-treatment hypogammaglobulinemia was associated with respiratory infection (p = 0.040). The independent predictors of 6-month neutropenia were a greater number of dose-escalated cycles, lower baseline leukocyte count and the absence of on-treatment infection, whereas 6-month hypogammaglobulinemia was predicted by autologous transplantation and the absence of B symptoms. In exploratory body composition analyses, lower baseline psoas muscle mass was associated with end-of-treatment neutropenia (p = 0.042) and greater muscle loss with other site (skin and gastrointestinal) infection (p = 0.004). Conclusions: After DA-R-EPOCH, LON is a delayed and largely transient event separate from end-of-treatment neutropenia, whereas hypogammaglobulinemia is more persistent and clinically relevant for respiratory infections. Full article

The increasing penetration of renewable energy has significantly intensified the demand for flexible operation of thermal power plants, making dynamic simulation an essential tool for understanding transient behaviors and developing advanced operational strategies for circulating fluidized bed (CFB) power plants. This review critically examines the existing dynamic modeling approaches for industrial-scale CFB power plants, with particular emphasis on their applicability to flexibility studies. Existing CFB flue-gas side models are systematically classified into three categories: 3D physics-based CFD models, behavioral/data-driven models, and semi-empirical mechanistic models. Their characteristics are critically compared in terms of spatial and temporal scales, empirical dependence, model generality, computational and implementation burden, and applicability to CFB flexibility studies. Dynamic modeling of the steam–water cycle is also reviewed, showing that it has reached a relatively mature stage owing to well-established thermo-hydraulic theories and standardized modeling platforms. The current research bottleneck is therefore identified as the dynamic coupling between the flue-gas side and the steam–water cycle for integrated CFB whole-plant simulation. Based on the comparative analysis, semi-empirical mechanistic models are identified as a particularly suitable framework for industrial-scale CFB flexibility studies requiring minute-to-hour transient simulation, physical interpretability, and whole-plant coupling. Finally, future research directions are discussed, highlighting how integrated dynamic models can support CFB flexibility-enhancement technologies and the development of new-generation coal-fired power plants. Full article

The functional expression of plant growth-promoting (PGP) traits in soil actinobacteria is conditioned by abiotic factors, yet the combined effects of pH and temperature on their metabolic profiles and the stability of these profiles after encapsulated formulation and post-processing stress remain insufficiently characterized. This study aimed to evaluate the physiological plasticity of native actinobacteria and the expression of plant growth-promoting (PGP) traits under different pH and temperature conditions, as well as their stability after encapsulation, dehydration, and exposure to UV irradiation. Strains isolated from a semi-arid agricultural soil were analyzed to determine their ability to produce indole-3-acetic acid (IAA), siderophores, and phosphatases, as well as their ability to fix nitrogen, degrade cellulose, and tolerate salt stress. Temperature and pH significantly affected all evaluated PGP traits (p < 0.001), and their expression was not directly associated with biomass production. Two strains, S1 and S4, exhibited the highest overall PGP indices. Strain S1 maximized IAA and siderophore production under neutral conditions (pH 7.0, 30 °C), whereas strain S4 maintained more stable phosphatase activity across the tested pH and temperature ranges. Cell viability remained above 85% after encapsulation and dehydration. Dehydration enhanced IAA and siderophore production in strain S1, while strain S4 exhibited transient metabolic activation under UV irradiation in non-dehydrated capsules. The encapsulation matrix preserved cell viability more effectively than it preserved the complete PGP functional profile, indicating that viability alone is an insufficient criterion for evaluating the technological success of alginate-based bioinoculant formulations. These findings highlight the importance of integrating environmental preconditioning and functional stability assessments into the development of robust microbial bioinoculants adapted to agricultural systems subjected to fluctuating environmental conditions. Full article

This paper comprehensively investigates the ultraviolet (UV) nanosecond laser fabrication of micro-groove textures on planar PEEK surfaces, as well as their surface performance in terms of wettability and frictional properties. Firstly, a three-dimensional finite element model, incorporating a moving Gaussian heat source, solid heat transfer and deformed geometry, was established to simulate the transient temperature field and ablation profile of PEEK during UV laser ablation. The predicted groove depth agreed with the experimental value with a low deviation of 11.19%. Based on the simulation and single-factor experiments, the optimized single-track laser parameters were determined as a laser power of 1.2 W, a scanning speed of 100 mm/s and a repetitive frequency of 100 kHz. Secondly, systematic single-factor and multi-pass laser ablation experiments of PEEK surfaces were conducted to fabricate micro-groove textures with precisely tailored geometric parameters. Furthermore, ablated surface characterization showed that the laser-textured surfaces exhibited increased roughness, apparent crystallinity up to 22.13%, and pronounced anisotropic wettability, with improved liquid spreading along the groove direction and restricted spreading across the grooves. Finally, fretting wear tests under simulated body fluid lubrication were carried out. The research findings reported in this paper provide a systematic theoretical and experimental basis for the application of UV nanosecond laser surface texturing in the fabrication of PEEK-based components. Full article

Mobile robots and autonomous vehicles require tightly regulated direct current (DC) power under rapidly varying load conditions, motivating control strategies that combine fast nonlinear regulation with predictive optimization. This paper proposes a Hybrid Sliding Mode Control and Model Predictive Control (Hybrid SMC + MPC) strategy for a DC-DC buck converter supplying a representative mobile-robot mission load. The controller employs a cascade SMC structure for fast inner-loop regulation and an MPC component that provides finite-horizon duty-cycle correction using planned load information. The MPC problem is formulated in condensed form and solved analytically without an external optimization solver. A Lyapunov-based analysis establishes a sufficient reaching condition for the sliding variable under the ideal averaged-model assumptions, and the condition is verified for the simulated mission. The proposed approach is evaluated in MATLAB using a 10-phase, 10 s load profile with resistance varying from 7 Ω to 100 Ω and is compared with SMC-only, MPC-only, PID, constant-duty, and reconstructed fuzzy-logic benchmarks. In the averaged-model study, the Hybrid SMC + MPC achieves a maximum absolute voltage deviation of 0.388 V, an RMSE of 0.0115 V, and a final-phase mean absolute error of 0.0076 V. It provides the lowest maximum voltage deviation among the principal closed-loop controllers, while PID achieves the lowest RMSE and final-phase error and SMC-only exhibits the shortest mean settling time. Relative to MPC-only, the Hybrid controller reduces the maximum voltage deviation by approximately 43.6% and the mean settling time by approximately 66.1%. An ablation study shows that the MPC contribution substantially improves overall and steady-state regulation accuracy, while load preview primarily reduces the worst-case voltage deviation. Switching-level MATLAB/Simulink validation with explicit 20 kHz PWM and converter parasitics confirms that the output remains within ±2% of the 25 V reference throughout the complete mission, with a maximum absolute deviation of 0.443 V and a maximum steady-state switching ripple of 21.6 mV peak-to-peak. These results demonstrate that the proposed Hybrid SMC + MPC architecture provides a favorable balance between worst-case transient regulation, steady-state accuracy, and predictive control capability for dynamically varying robotic power loads. Full article

Alkaloid biosynthesis is a central topic in plant specialized metabolism because many alkaloids have ecological, pharmacological, and biotechnological relevance. Isoquinoline alkaloids (IAs) and Amaryllidaceae alkaloids (AAs) are both connected to aromatic amino acid metabolism, but they differ in taxonomic distribution, scaffold-forming chemistry, pathway resolution, and biotechnological development. This review compares the historical and methodological trajectories that have shaped IA and AA pathway elucidation, from compound isolation, radiotracer experiments, and biochemical inference to transcriptomics, metabolomics, functional enzymology, isotope-guided active-tissue identification, regulatory studies, and heterologous pathway reconstruction. In IAs, especially benzylisoquinoline alkaloids, broad genomic and transcriptomic resources have supported candidate gene discovery and functional characterization of several branches, including morphinan, protoberberine, benzophenanthridine, and aporphine-related pathways. In contrast, AA biosynthesis has advanced more recently through function-driven approaches that clarified key steps such as N4OMT-mediated 4′-O-methylation, NBS/NR-mediated norbelladine formation, CYP96T-dependent regioselective oxidative coupling, and transient reconstruction of major scaffold-forming branches. Remaining gaps include the unresolved enzymatic formation of 3,4-dihydroxybenzaldehyde in AAs and incomplete functional validation across less-studied IA scaffold classes. By integrating biochemical logic, omics-guided discovery, enzyme evolution, tissue specificity, regulation, and synthetic biology, this review identifies priorities for future alkaloid pathway discovery and sustainable production. Full article

Multiple chemical sensitivity (MCS) is a chronic condition characterized by adverse reactions to low-level environmental chemicals, often resulting in multisystem symptoms triggered by volatile organic compounds (VOCs) emitted from fragranced personal care and household products. The condition raises public health and accessibility concerns, as people with MCS may face barriers to accessing workplaces, healthcare settings, educational institutions, and other public environments. This descriptive cross-sectional study aimed to characterize the chemical exposures participants attributed to the onset of MCS and to subsequent symptom provocation, and to describe the associated symptom patterns. A cross-sectional survey was administered to Canadian residents aged 18 years or older, living with MCS for at least 1 year, with 18 questions assessing exposure history and onset of MCS and symptom provocation. A total of 119 participants completed the survey. Participants most frequently attributed the onset of MCS to the workplace (55%) or home (35%), with (61%) reporting ongoing exposures over time as the most frequently reported circumstance associated with onset. Fragranced products, including perfumes, air fresheners, cleaning products, disinfectants, construction materials, and laundry products, were the exposures most frequently reported in relation to both onset and subsequent symptom triggering. Symptoms involved multiple organ systems, with nearly one-third of participants reporting 11 or more symptoms; cognitive and respiratory symptoms were most prevalent. Nearly three-quarters of participants (74%) reported symptoms associated with third-hand exposure, and 51% reported discarding contaminated items, suggesting that third-hand exposure may represent an underrecognized pathway for symptom provocation. Full article