Search Results (635)

As one of the core technologies in modern national defense and security fields, infrared stealth technology aims to realize the controllable regulation of the radiation characteristics of targets in the infrared band. This paper focuses on a novel electrochromic device with a structure of WO₃/nickel mesh/Al³⁺-Zn²⁺gel electrolyte/zinc foil. The structural composition and working mechanism are systematically analyzed, and the infrared stealth regulation performance is emphatically studied. The WO₃ thin film and device structure were characterized by scanning electron microscopy (SEM). The infrared emissivity modulation and optical response properties of the device were measured using an infrared thermal imager and a UV-Vis-NIR spectrophotometer. The prepared WO₃ film exhibits a dense spherical morphology, indicating excellent uniformity and compactness. After 1000 cycles, the areal capacitance of the device remains 83.7% of its initial value, demonstrating good cycling stability. Under the voltage regulation of −0.1 V to 1.1 V, the emissivity ε of the device at the typical mid-wave infrared wavelength of 4.0 μm decreases from 0.89 (−0.1 V) to 0.67 (1.1 V), with an absolute modulation amplitude Δε of 0.22. At the typical long-wave infrared wavelength of 8.7 μm, ε decreases from 0.96 (−0.1 V) to 0.69 (1.1 V), with an absolute modulation amplitude Δε of 0.29. The electrochromic switching times for coloring and bleaching are 10.1 s and 2.44 s, respectively. According to infrared thermal imaging tests, in the temperature range of 30–40 °C, the surface temperature difference ΔT between the colored state and bleached state increases from 4.3 °C to 4.6 °C. The maximum regulation amplitude reaches 4.6 °C at 40 °C. The device achieves efficient regulation of infrared emissivity through the electrochromic effect, providing a new device design strategy for infrared stealth technology. Full article

The tomato hind (Cephalopholis sonnerati) is a marine aquaculture fish species with high economic value. Elucidating the mechanisms underlying its growth regulation is crucial for the development of the aquaculture industry. To analyze the biological mechanisms underlying growth differences, individuals with extreme body sizes at 8 months of age from the same batch were selected in this study. A combined experiment of “body size × feeding status” was constructed, and transcriptome sequencing and weighted gene co-expression network analysis (WGCNA) were performed on brain and muscle tissues. The results showed that 2553 differentially expressed genes (DEGs) were identified between individuals with distinct body sizes, which were significantly enriched in growth regulation pathways such as PI3K–Akt, MAPK, and FoxO. Feeding differences affected 4480 genes, which were significantly enriched in signaling pathways including the insulin signaling pathway. WGCNA further identified co-expression modules (brown4, blue, coral1) significantly correlated with growth, as well as hub genes including pik3r1 and eif4ebp2. Comprehensive analysis demonstrated that the growth regulation of C. sonnerati operates as a cascade network. Brain tissues perceive signals through neuroactive ligand–receptor interactions and integrate and transduce these signals via core pathways including Ras–MAPK and PI3K–Akt. Finally, growth processes are executed in muscle tissues by regulating glycogen metabolism, protein synthesis, and other processes, which are precisely regulated by terminal processes such as cellular senescence. Among them, pik3r1 and eif4ebp2, as key molecular switches, play a central role in integrating upstream signals and precisely regulating downstream growth programs. This study preliminarily clarifies the molecular mechanism network of growth differences in C. sonnerati, providing a theoretical basis and candidate genes for the genetic improvement of its growth traits. Full article

This study examines the design, manufacturing, and testing of planar PCB inductors (spiral and toroid), including multilayer PCB toroid configurations. These inductors are intended for environments with strong magnetic fields, such as high-energy physics experiments and medical applications, where traditional inductors with ferromagnetic cores are unsuitable. Twelve inductor samples were manufactured and tested. The focus was on maximizing inductance and evaluating performance in a high-frequency DC-DC step-down converter. Key parameters measured included inductance, resistance, thermal performance, electromagnetic interference (EMI), and frequency-dependent behavior in multilayer PCB implementations. The results showed that planar spiral inductors handled higher currents and achieved better efficiency, reaching up to 74.86%. Planar toroid inductors were more tolerant of added shielding, maintaining their inductance, while multilayer toroid designs exhibited reduced DC resistance but increased frequency dependence and sensitivity to parasitic effects. Overall, planar inductors were found to be viable for applications where ferromagnetic cores are unsuitable. Further optimization of geometry, layer configuration, and manufacturing processes could enhance their performance. Full article

Tubular flux-switching permanent-magnet linear machines (TFSPMLMs) are difficult to optimize using a single core material because conventional axial laminations suffer from severe in-plane eddy-current loss, whereas soft magnetic composites (SMCs) exhibit lower permeability and higher hysteresis loss. To address this trade-off, three hybrid SMC–laminated steel core configurations were investigated: H1, with radially laminated steel in the yoke; H2, with axially laminated steel in the tooth; and H3, with circumferential laminated steel segments. A reference SMC model (R1) and the three hybrid models were comparatively evaluated using three-dimensional finite element analysis (3D FEA). H1 and H2 showed degraded performance due to an interfacial micro-gap along the main flux path and additional in-plane eddy currents in the laminated steel regions. To mitigate these limitations, circumferential segmentation was applied to the laminated steel parts. With eight segments, H2 achieved a thrust force of 278.8 N, comparable to that of R1, while reducing iron loss by 22.5%; even a two-segment structure provided noticeable improvement. Among the investigated models, H3 showed the best overall performance by avoiding a micro-gap on the main flux path, achieving 285.5 N, and 3.9% higher thrust force and 18% lower iron loss than R1. These results indicate that H3 is the most effective hybrid-core configuration for maximizing both thrust force and loss reduction, whereas segmented H2 is an attractive practical option when manufacturability and low-loss operation are considered. Full article

Maritime Autonomous Surface Ships (MASS) are progressing from proof-of-concept to engineering test and initial application phases due to advancements in intelligent sensing, automatic control, and communication technologies. However, numerous studies have shown that the improvement of automation level does not linearly reduce human factor risks. Instead, it exhibits more complex evolutionary characteristics at the medium automation level. In particular, MASS Level 2 (MASS L2) features a “system-dominated, human-supervised” operational mode, and its human factor risks have become one of the key factors restricting the safe operation, large-scale application and sustainable long-term deployment of autonomous ships. This study employs a systematic literature review to analyze 89 core articles (2020–2025) and summarizes the theoretical basis, risk characteristics, and evolutionary trends of human factor risk research in MASS L2. The review results indicate that the current research consensus has gradually shifted from the traditional “human error”-centered explanatory paradigm to a systematic understanding of “information mismatches, opacity, and coupling failures in the human-machine-shore collaborative system”. Typical human factor risks in MASS L2 are mainly manifested as the degradation of supervisory cognition and situation awareness, imbalance in trust in automation, vulnerability in mode switching and takeover, skill degradation, and structural risks in ship-shore collaboration. Based on these findings, this study constructs a classification system and a comprehensive analysis framework for human factor risks in MASS L2, reveals the interaction relationships and dynamic evolution mechanisms among different risk types from a system-level perspective, and further discusses the limitations of existing research in terms of methods, data, and engineering applicability. Finally, considering the development trends of autonomous ship technology, this study proposes future research directions in human factor theoretical modeling, dynamic risk assessment, system design, and operation management. This study aims to provide a systematic knowledge framework for human factor risk research in MASS L2 and offer references for the safety design, safety management, and development of higher-level automation of autonomous ships, while supporting the sustainable and safe advancement of the global intelligent shipping industry. Full article

Wireless power transfer (WPT) systems have garnered significant market attention owing to their broad applicability in portable electronic devices, electric vehicles, unmanned aerial vehicles, biomedical implants, and related fields. In these systems, operating frequency and efficiency are critical factors affecting both transmission efficiency and transmission distance, making high-frequency operation an important trend for improving overall WPT performance. However, elevating the switching frequency also introduces notable challenges, including increased switching losses in power devices, limited load adaptability, and poor anti-misalignment capability, which in practice often lead to degraded system efficiency and unsatisfactory waveform quality. Accordingly, this paper proposes a high-frequency inverter power supply system capable of operating at a maximum output voltage frequency of 25 KHz. Under conditions of a 10 KHz output frequency and a 20 KΩ load, the system achieves a peak efficiency of 94.01%. A prototype was implemented through the integration of a software algorithm based on ARM Cortex-M3 core control with a hardware architecture consisting of a driving circuit, a full-bridge inverter, and a switchable filtering module. This work offers practical design insights for the development of future high-frequency, high-voltage inverter systems, while also providing valuable experimental data to support further research in this area. Full article

To reduce the computational burden of 3D finite element analysis for hybrid-flux high-speed switched reluctance motors (HFHSRMs), a quasi-3D parameterized equivalent magnetic network (EMN) is proposed. A parameterized radial–circumferential cross-grid is used to discretize the stator, air-gap, and rotor regions, and axial coupling branches are introduced to represent key 3D flux paths. Rotor rotation and rotor dislocation are implemented through a circumferential node-shift mapping, thereby avoiding topology reconstruction at different rotor positions. Core nonlinearity is incorporated using a piecewise fit of measured B–H data, and sparse-matrix assembly is adopted to improve solution efficiency. Based on the proposed EMN, key electromagnetic quantities are evaluated, including air-gap flux density, static characteristics, and dynamic characteristics. The results are validated against 3D finite element method (FEM) and prototype experiments. In the prototype experiments, the EMN prediction errors of key quantities are within 6%. In addition, computational efficiency is significantly improved compared with the 3D FEM, enabling rapid parameter iteration and early-stage design evaluation for HFHSRMs. Full article

Multi-Key Fully Homomorphic Encryption (MK-FHE) is essential for secure multi-party computation but currently faces significant scalability bottlenecks due to linear computational growth and low bootstrapping throughput. To address these limitations, we propose DMBB-RCB, a novel fully homomorphic, bit-wise Dynamic Multi-Key Block-Binary Ring-Compact Bootstrapping scheme. Our contribution is threefold. First, we integrate the Block Binary Distribution into the dynamic setting, reducing the complexity of the core blind rotation operation from O(P⋅n) to O(p⋅k) (where k ≪ n) by leveraging key sparsity. Second, we implement an amortized ring packing strategy that aggregates multiple Learning with Errors (LWE) ciphertexts into the coefficients of a single Ring Learning with Errors (RLWE) polynomial, enabling the parallel refreshing of messages. Third, we introduce a Ring-Compact extraction architecture that natively translates RLWE states into Multi-Key Regev–Gentry–Sahai–Waters (RGSW) ciphertexts via scheme switching. Unlike traditional pipelines that suffer from severe network latency due to interactive multi-party key-switching after each bootstrapping, our architecture keeps the data entirely within the ring domain. This completely eliminates intermediate interaction rounds, enabling depth-unbounded homomorphic evaluations with zero interaction between participants during the computation phase (interaction is strictly reserved for the final joint decryption step). The proposed scheme supports the dynamic addition of participants without parameter re-generation. Theoretical analysis confirms that DMBB-RCB significantly reduces latency and enhances throughput compared to existing dynamic MKHE solutions. Full article

Fire safety plays a vital role in protecting lives, property, and the environment, and it keeps communities and organizations running safely. Many existing fire pump control systems fall short in educational and small-to-medium industrial settings: they often control only one pump at a time, rely heavily on manual monitoring, and come with high costs that limit accessibility. To address these gaps, we developed an affordable, hands-on educational kit that brings real-world fire safety systems into the classroom using modern automation technology. The system is built around a Delta DVP12SA211R PLC chosen for its built-in real-time clock, integrated RS-232/RS-485 ports for reliable communication, and expanded with DVP16SP11R digital I/O and DVP04AD-S2 analog input modules to interface with simulated sensors mimicking smoke detection and water pressure. Students interact with the system through a Delta DOP-110IS HMI, which features Ethernet connectivity for remote observation, electrical isolation for safe operation, and a 200 ms screen update rate to ensure responsive, realistic feedback. The kit enables learners to explore critical emergency scenarios, including automatic switching between jockey and main pumps, low-pressure alerts, and system failover, transforming theoretical concepts into tangible skills. In user evaluations, 57.1% of students with no prior experience reported that the simulations closely mirrored real-world systems, while 80% of those with a fire safety background found the kit reinforced their existing knowledge; notably, 57.1% of instructors rated it as highly effective for teaching core fire safety principles across diverse learner profiles. By integrating industrial-grade hardware with scenario-based learning, this tool not only deepens understanding of fire protection systems but also better prepares future engineers for the practical demands of fire safety and industrial automation careers. Full article

Antimicrobial resistance (AMR) is a growing global health threat with important implications for pediatric populations. Children are frequently exposed to antibiotics in both hospital and community settings, where inappropriate prescribing, suboptimal dosing, and excessive use of broad-spectrum agents remain common. These practices contribute to the emergence of resistant pathogens, increase adverse drug events, and may negatively affect the developing immune system and microbiota. This narrative review summarizes current evidence on pediatric antimicrobial stewardship (AMS), highlighting recent trends in antimicrobial use and key stewardship strategies across inpatient and outpatient care. Core interventions, including prospective audit and feedback, preauthorization, guideline implementation, AWaRe-based prescribing, therapeutic drug monitoring, and early intravenous-to-oral switch, are discussed. The review also examines the expanding role of diagnostic stewardship, focusing on rapid molecular diagnostics, point-of-care testing, and host-response biomarkers to improve differentiation between bacterial and viral infections and support targeted therapy. Despite progress, pediatric AMS faces persistent challenges, such as regional variability in prescribing practices, limited pediatric-specific data for new antimicrobials and diagnostics, and organizational and behavioral barriers. Emerging tools, particularly artificial intelligence, may enhance decision-making and optimize antimicrobial use, although further validation in pediatric settings is needed. Strengthening pediatric AMS is essential to improving care quality and mitigating the impact of AMR. Full article

Taxifolin, a natural flavonoid, consistently exerts cytoprotective effects against various oxidative stresses. In this study, we systematically evaluated its photoprotective efficacy and underlying mechanisms against ultraviolet B (UVB)-induced injury in human immortalized keratinocytes (HaCaT). Cell viability and apoptosis were assessed by MTT, fluorescence staining, and flow cytometry, while integrative transcriptomic and proteomic analyses were employed to identify core pathways and key mediators. Taxifolin exhibited antioxidant capacity comparable to that of ascorbic acid under identical in vitro radical-scavenging assays. Moreover, it displayed a strong absorption peak at 289 nm that overlaps the UVB spectrum (280–320 nm), enabling it to act as a chemical sunscreen. In UVB-challenged HaCaT cells, taxifolin markedly reduced intracellular reactive oxygen species (ROS) and attenuated JNK/p38 MAPK activation, as evidenced by Western blot, thereby breaking the ROS-MAPK vicious cycle. Multi-omics revealed that taxifolin was associated with attenuation of UVB-imposed G1/S arrest concomitant with restored Cyclin expression, while up-regulating MYC, FOXQ1, HMOX1 and AP-1 components c-Jun/c-Fos and thereby switching on a pro-survival transcriptional program. Consequently, apoptosis was suppressed and survival was significantly improved. Collectively, taxifolin integrated chemical filtration, ROS scavenging and signaling modulation to support a multi-target photoprotective network, which provides mechanistic insight into taxifolin-mediated cytoprotection and identifies candidate molecular nodes for further validation. Full article

Clients need to visit project sites periodically during construction to visualize progress and identify deviations from expectations. However, physical site visits are time-consuming, costly, and potentially unsafe, especially for remote and overseas projects. More fundamentally, existing remote-site-visit solutions focus primarily on automatic recognition and visualization, while insufficiently addressing the scientific challenge of how heterogeneous, dynamic site data can be fused and operationalized to support timely, collaborative decision making. This research proposes a framework for clients’ remote site visits. It develops an RASE system that enables multi-source data fusion and real-time collaborative decision support by integrating UAVs, 360° cameras, BIM, and VR/AR technologies. RASE allows clients to synchronize real-world visual data with BIM models within predefined scenes, annotate issues directly on BIM components, and seamlessly switch among heterogeneous image-capture sources to maintain situational awareness in highly dynamic construction environments. The proposed framework emphasizes an operational data-fusion mechanism and an interaction paradigm that reduces the cognitive and coordination burdens of remote decision making. A case study shows that RASE reduces site-visit time by 78.0%, though initial equipment costs increase total expenses by 44.1%. Sensitivity analyses indicate that projects with greater remoteness or higher visit frequency significantly improve both time and cost effectiveness. The core contribution of RASE lies in enabling a scalable, operational data-fusion mechanism that supports collaboration for remote site visits, with the associated issues for the corresponding BIM components. Automatic image and voice recognition functionality may be incorporated with RASE to improve the efficiency of system control, textual input, and BIM association in the future. Full article

Environmental performance constitutes a core dimension of the environmental, social, and governance (ESG) framework; however, empirical evidence for developing economies such as Türkiye remains limited, particularly regarding regime-dependent effects. Accordingly, this study examines the effects of financial stability, economic growth, and industrial production on environmental performance for Türkiye within a Markov-switching error correction and time-varying parameter state–space framework using annual data for 1990–2023. The findings show that financial stability is insignificant in the low error-variance regime but is negatively associated with environmental performance in the high error-variance regime. Economic growth is negatively associated with environmental performance in the low error-variance regime and becomes insignificant in the high error-variance regime. In contrast, industrial production has a positive and statistically significant effect on environmental performance in both regimes. The error correction mechanism indicates that short-run disequilibria are gradually corrected, supporting the existence of long-run convergence. Furthermore, the time-varying parameter state–space estimates indicate that these effects change over time. Overall, the findings indicate that the effects of financial stability, economic growth, and industrial production on environmental performance differ depending on regime periods and changing economic conditions. Full article

Public transportation is the core of easing urban traffic congestion, reducing pollution and advancing smart city transportation intellectualization. Its refined operation relies heavily on accurate, real-time passenger origin–destination (OD) data. However, traditional manual surveys are costly with low sampling rates, while smart card big data lacks alighting information and has deviations, failing to reflect real travel behaviors and becoming a bottleneck for intelligent public transportation development. To address this, this paper proposes a bus passenger boarding/alighting detection and recognition study based on video images and the YOLO algorithm. Aiming at traditional YOLO’s shortcomings in on-vehicle scenarios (insufficient feature extraction, inefficient feature fusion, slow convergence), the baseline YOLOv8n is improved for bus scenarios’ high-density, high-occlusion and variable-target scales: (1) DAC2f structure (deformable attention + C2f) captures occluded passengers’ core features and suppresses background interference; (2) SWD-PAN enables bidirectional cross-scale feature interaction to adapt to scale differences; and (3) WIoUv3 balances sample weights for small targets and non-standard posture passengers. Experiments show that precision, recall and mAP increase by 3.68%, 5.12% and 6.26%, respectively, meeting real-time requirements. The improved YOLOv8 is deeply integrated with DeepSORT to enhance tracking stability. Tests show that MOTA reaches 31.24% (2.6% higher than YOLOv8n, 16.4% higher than YOLO-X) and MOTP reaches 88.06%, solving trajectory breakage and ID switching. This addresses traditional OD data collection pain points, providing technical support for intelligent public transportation refined management and smart city transportation optimization. Full article

Electromagnetic interference (EMI) rectification of grid-tied inverters is crucial for their practical application, and the variable frequency modulation (VFM) technique is a low-cost and simple way for EMI reduction. However, changes in loss and harmonic behaviors make it hard for parameter determination of VFM. In this paper, the parameters required for switching frequency (SF) function are determined for loss optimization of MOSFETs and inductors, while total harmonic distortion (THD) and temperature rise in MOSFETs and inductor core are constrained to guarantee the feasibility of the calculated parameters. Current transient is derived through multidimensional Fourier decomposition (MFD) and characteristics of Bessel function for loss estimation of MOSFET and inductor. Modified Steinmetz equation (MSE) is applied for core loss estimation and AC resistance is considered for copper loss estimation. With the constraints of THD and temperature, the loss optimization problem is solved by the augmented Lagrangian (AL) method. With the assistance of the proposed method, total loss optimization can be realized in feasible regions while the temperature rise in essential components can be restricted to the preset values. Full article