Search Results (64)

Multi-terminal voltage source converter-based high voltage direct current (VSC-MTDC) technology has become an efficient solution for grid integration of large-scale and long-distance offshore wind power. When onshore grid power fluctuations elevate the DC voltage of VSC-MTDC system, the surplus power causing the DC overvoltage issue can be effectively transferred through the power shifting method. To enhance the power shifting capability of receiving-end converters (RECs) and mitigate DC overvoltage, this paper proposes a coordinated power shifting strategy for VSC-MTDC based on the extended operation region. Firstly, the topology and control model of the VSC-MTDC system integrating offshore wind farms is established. Secondly, considering constraints containing apparent power, AC bus voltage, AC current, and voltage modulation ratio, the extended operation region model with regard to the overload capacity of REC is constructed. Furthermore, the coordinated active power shifting strategy for multiple converters is proposed to cope with onshore grid power fluctuations. Finally, simulation models of three-terminal and six-terminal VSC-MTDC systems are built using PSCAD V5 software. Simulation results show that the proposed strategy can exploit the system’s operational flexibility and reduce the risk of DC overvoltage, thus enhancing the disturbance immunity of VSC-MTDC system against onshore grid fluctuations. Full article

The of personal computer (PC) tasks represents a systems-level challenge that integrates natural language processing, visual perception and mouse–keyboard action control. While existing approaches mainly focus on the application programming interface (API)-based or terminal-based automation, which are incompatible with the majority of applications for the lack of accessible interface. In this article, we propose PCLLM, a novel end-to-end system that automates PC operations by integrating large language models (LLMs) with computer vision techniques to directly control the mouse and keyboard. First, a software knowledge-based prompt engineering method is developed to comprehend software architecture and operational sequences. Second, template matching techniques are integrated for precise element localization, allowing the system to accurately identify and interact. Third, a dual-LLM pipeline is designed to automatically generate the test data, where a questioner LLM generates diverse task commands and the PCLLM executes these tasks, the corresponding process data are recorded automatically for performance evaluation. Finally, PCLLM is further validated through three typically PC applications (Notepad, Wordpad and Calculator), demonstrating its flexible and robust performance towards intelligent PC automation. To evaluate the proposed system, we adopt task completion rate as the primary metric. Experimental results show that PCLLM achieves the highest completion rates of 98.59%, 95.77%, and 52.11% on Notepad for basic, intermediate, and advanced tasks respectively when powered by GPT-4o, outperforming the CogAgent baseline. These results demonstrate the effectiveness of our approach for PC task automation. Full article

During the preliminary design of flight vehicles, i.e., missiles or guided rockets, propulsion system performance serves as a critical determinant of both maximum range and terminal velocity. However, complex grain configurations in solid rocket motors (SRMs) typically require geometric modeling software to obtain burning surface area, which severely constrains efficiency. To address this challenge, this study presents a neural network-enhanced rapid performance prediction and matching optimization framework for solid rocket motors (NN-SRM). In NN-SRM, neural networks are employed to simulate the evolution of key parameters during grain combustion, including burning surface area, grain volume, and moment of inertia. The zero-dimensional internal ballistics equations coupled with one-dimensional steady isentropic flow relations are incorporated into the framework to rapidly obtain thrust curves. A discrete–continuous mixed differential evolution algorithm is further employed to identify the optimal grain configuration that satisfies specific thrust requirements. Results demonstrate that, as for cylindrical, star, and finocyl grains, the neural network achieves R² exceeding 0.95. Finally, thrust matching optimization is conducted on three grains and achieves promising thrust solutions for the conditions of large thrust with short time and small thrust with long time, which demonstrates the effectiveness and practicality of the constructed NN-SRM. Full article

Objectives: This study aimed to compare the retention and fit precision of removable partial denture circumferential clasps fabricated from cast cobalt–chromium, 3D-printed cobalt–chromium, and polyether ether ketone. Methods: A maxillary right first premolar abutment was prepared. Eighty circumferential clasps were allocated into three material groups: cast Co–Cr (n = 20), 3D-printed Co–Cr (n = 20), and PEEK (n = 40). The terminal third of metal retentive clasps was designed to engage 0.25 mm and 0.50 mm undercuts. PEEK clasps were fabricated with two designs: partial (two-thirds) and full-arm undercut engagement. Each group was examined for retentive forces after 1440 cycles (simulating 1 year). Initial and final retentive forces were recorded. Clasp deformation was assessed by measuring inter-arm distance before and after cycling using digital photography and ImageJ software. Results: All clasp groups demonstrated a statistically significant reduction in retention after 1440 cycles (p < 0.05). At both undercut depths, cast and 3D-printed Co–Cr clasps exhibited significantly higher retentive forces than PEEK (p < 0.001). Within the PEEK group, full-arm engagement showed significantly higher retention than partial engagement at the 0.25 mm undercut (p < 0.001), whereas no significant difference was observed between designs at the 0.50 mm undercut (p = 0.406). Fit precision revealed a significant increase in inter-arm distance after cycling (p < 0.05). PEEK clasps exhibited significantly smaller dimensional changes than Co–Cr clasps (p < 0.02). Conclusions: Clasp material, undercut depth, and design significantly influenced retention and fit precision. Co–Cr clasps maintained higher retentive forces, whereas PEEK clasps demonstrated reduced deformation after cycling. Full article

Deep-sea mollusks represent untapped resources for searching novel biologically active peptides effectual against many chronic diseases. Here we presented the identification of four novel angiotensin I-converting enzyme (ACE) inhibitory peptides from the deep-sea mollusk Gigantidas platifrons by using a combined approach of peptidomics and virtual screening. Fifteen protein hydrolysates from five deep-sea macroorganisms were prepared using three different proteases and were determined for their ACE inhibitory activities. Pepsin hydrolysate of G. platifrons protein (GPp) demonstrated the highest inhibition rate against ACE at 400 μg/mL. Then, targeted investigation was conducted on the GPp with peptidomic profiling; more than 3000 peptides were de novo identified, which were then subject to virtual screening using the docking software Smina. Subsequently, 29 peptides were selected and synthesized based on the affinity threshold and the interactions with ACE active sites. More than 58% peptides were biologically active, showing more than 50% inhibition to ACE at 400 μM. Four peptides, LAAHFAR, YAAPYR, NGAGPYGRP, and FTTFGK, exhibited low micromolar inhibition. The most potent peptide, LAAHFAR with an IC₅₀ of 6.01 ± 1.06 μM, was subject to molecular dynamics simulations for revealing atomistic interaction analysis. LAAHFAR forms comprehensively stable hydrogen bonds with the classic active site of ACE, and its N terminal arginine residue is anchored by additional hydrogen bonding to Cys370, Asp377, and Thr372. This study highlights deep-sea mollusks as an important source of novel ACE inhibitory peptides, contributing to the development of new therapeutic ingredients or functional food agents against hypertension. Full article

With the expansion of urban rail transit, increased train operation density, and the large-scale grid integration of renewable energy such as offshore photovoltaic power, traction power supply systems face stricter requirements for operational safety, power supply reliability and energy utilization efficiency. Offshore photovoltaic power, integrated into the traction power supply network via flexible DC transmission technology, promotes renewable energy consumption, but its random and volatile output overlaps with time-varying traction loads, increasing the complexity of DC-side fault characteristics and protection control. Flexible DC technology is a core direction for next-generation traction substations, and three-level converters (key energy conversion units) have advantages over traditional two-level topologies. However, their P-O-N three-terminal DC-side topology introduces new faults (e.g., PO/ON bipolar short circuits, O-point-to-ground faults), making traditional protection strategies ineffective. In addition, wide system current fluctuation (0.5–3 kA) and offshore photovoltaic power fluctuation easily cause fixed-threshold protection maloperation, and the coupling mechanism among modulation strategies, DC bus capacitor voltage dynamics and fault current paths is unclear. To solve these bottlenecks, this paper establishes a simulation model of the system based on the PSCAD/EMTDC(A professional simulation software for electromagnetic transient analysis in power systems V4.5.3) platform, analyzes the transient electrical characteristics of three-level converters under traction and braking conditions for typical faults, clarifies the coupling mechanism, proposes a condition-adaptive fault identification strategy, and designs a reconfigurable fault energy handling system with bypass thyristors and adaptive crowbar circuits. Simulation and hardware-in-the-loop (HIL) experiments show that the proposed scheme completes fault identification and protection within 2–3 ms, suppresses fault peak current by more than 70%, limits DC bus overvoltage within ±10% of the rated voltage, and has good post-fault recovery performance. It provides a reliable and engineering-feasible protection solution for related systems and technical references for similar flexible DC system protection design. Full article

Tidal flats play a vital role in coastal ecosystems by supporting biodiversity, mitigating natural hazards, and functioning as blue carbon reservoirs. However, monitoring their geomorphological changes remains challenging due to high turbidity, shallow depths, and tidal variability. Conventional approaches—such as satellite remote sensing, acoustic sounding, and topographic LiDAR—face limitations in resolution, accessibility, or coverage of submerged areas. Airborne bathymetric LiDAR (ABL), which uses green laser pulses to detect reflections from both the water surface and seabed, has emerged as a promising alternative. Unlike traditional discrete-return data, full waveform analysis offers greater accuracy, resolution, and reliability, enabling more flexible point cloud generation and extraction of additional signal parameters. A critical step in ABL processing is waveform decomposition, which separates complex returns into individual components. Conventional methods typically assume fixed models with three returns (water surface, water column, bottom), which perform adequately in clear waters but deteriorate under shallow and turbid conditions. To address these limitations, we propose an adaptive progressive Gaussian decomposition (APGD) tailored to tidal flat environments. APGD introduces adaptive signal range selection and termination criteria to suppress noise, better accommodate asymmetric echoes, and incorporates a water-layer classification module. Validation with datasets from Korea’s west coast tidal flats acquired by the Seahawk ABL system demonstrates that APGD outperforms both the vendor software and the conventional PGD, yielding higher reliability in bottom detection and improved bathymetric completeness. At the two test sites with different turbidity conditions, APGD achieved seabed coverage ratios of 66.7–70.4% and bottom-classification accuracies of 97.3% and 96.7%. Depth accuracy assessments further confirmed that APGD reduced mean depth errors compared with PGD, effectively minimizing systematic bias in bathymetric estimation. These results demonstrate APGD as a practical and effective tool for enhancing tidal flat monitoring and management. Full article

A novel architectural design is proposed to optimize the thermal management of lithium-ion batteries (LiBs) through a software-enabled switching mechanism. This approach addresses critical challenges such as hot-spot generation, peak temperature rise, and uneven thermal distribution—issues commonly observed in conventional single-terminal battery modules (STBMs). The proposed dual-terminal configuration integrates an enhanced battery pack structure with a software-enabled switching algorithm that identifies the 50% depth of discharge (DoD) and toggles the current path between two terminals to supply the load. Correspondingly, the module also incorporates the division of four thermal zones and four regions concept in the battery module (BM). Experiments were conducted to evaluate the performance of the proposed model at five different C-rates: 0.5C, 0.75C, 1C, 1.25C, and 1.5C. The results demonstrate that the software-enabled dual-terminal switching (Se-DTS) consistently outperforms the STBM across three key aspects. First, in terms of peak temperature, Se-DTS achieved reductions of 19.33%, 17.83%, and 12.72% at C-rates of 1C, 1.25C, and 1.5C, respectively. Second, in thermal distribution, Se-DTS improved performance, with an 86.1% reduction at 1.25C. Third, regarding hot-spot reduction, improvements of 100% (regional level) and 72.22% (zonal level) were observed at 1.25C, while at 1.5C, an 80% improvement was achieved at the zonal level, without using a cooling system. Full article

Plants grow, develop, and reproduce within a rhythmic environment. Environmental cues—such as light, temperature, nutrition, water—initiate, sustain, or terminate basic physiological processes within the plant, such as photosynthesis, respiration, nutrient uptake, water management, transpiration, growth, and hormone regulation. Simultaneously, inside the plant, internal “living clocks” are ticking and helping plants to synchronize internal processes with environmental cues and defend themselves against stressful conditions. These clock-regulated processes underlie a variety of plant traits, such as germination capability, growth and development rate, time of flowering, fruiting and yielding, development of plant shape, and size and biomass production. Most of these physiological traits are important attributes of crop plants. In recent years, the growing understanding of environmental rhythms as environmental cues and the mechanisms underlying plant internal clocks has begun to play an increasingly important role in agricultural practices. This is an emerging area of research that integrates insights from chronobiology with practices in plant agriculture. In this review, this new research area is studied and mapped using Scopus, Web of Science, Google Scholar, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA protocol), and VOSviewer1.6.20 software. The analyses were carried out on 18 July–27 August 2025. For the VOSviewer author keywords co-occurrence analysis, all 1022 documents covering the time range of the last 7.5–2.5 years (2018–July 2025) were included and three maps were generated. Additionally, 59 review documents covering the last 27 years (1988–July 2025) were extracted by relevance using Google Scholar. In this review, recent advances and topics in plant chronobiology were examined. The issue of how these advances respond to key challenges in plant agriculture was explored. The bidirectional influence between chronobiology and practices in plant agriculture were also considered. Full article

Transmission lines are constantly exposed to changes in climatic conditions and aging which affect the parameters and change the characteristics of the three-terminal circuit over time. In this paper we propose a fault location algorithm for three-terminal transmission lines to solve this problem. The algorithm utilizes the positive components of the voltage and current signals measured synchronously from the terminals. In this work no prior knowledge of the line parameters was required when calculating the fault location and the use of fault classification algorithms was not necessary. In addition, the proposed method determines the parameters of the line segment and fault location based on a solid mathematical basis and has been verified through simulation results using SIMULINK/MATLAB R2018a software. The fault location results demonstrate the high accuracy and efficiency of the algorithm. Moreover, this method can estimate the characteristic impedance and propagation constants of the transmission lines and determine the location of the fault, which is not affected by different fault parameters including fault location, and fault resistance. Full article

Onboard Vehicle-to-Everything (V2X) communication technology is being widely implemented in domains such as intelligent driving, vehicle–road cooperation, and smart transportation. Nevertheless, time synchronization in V2X systems suffers from instability due to the random loss of Global Navigation Satellite System (GNSS) Pulse-Per-Second (PPS) signals. To address this challenge, a model-driven local clock correction approach is proposed. Leveraging probability theory and mathematical statistics, models for the randomly lost GNSS PPS signals are developed. High-order polynomials are used to model local clocks. An optimized Kalman-filter-based time compensation algorithm is then devised to compensate for time errors during PPS signal loss. A software-based task-scheduling solution for precision-time synchronization is developed. An experimental testbed was then built to measure both terminal clocks and PPS signals. The proposed algorithm was integrated into the V2X terminals. Results show that the full-value PPS signals follow an exponential distribution. The onboard clock correction algorithm operates stably across three V2X terminals and accurately predicts clock variations. Furthermore, the virtual clocks achieve an average absolute error of 1.1 μs and a standard deviation of 16 μs, meeting the time synchronization requirements for V2X communication in intelligent connected vehicles. Full article

Focusing on the power consumption of a regional multi-energy system with the characteristics of energy congestion in students’ dormitory buildings in the hot summer and warm winter regions of southern China, a practical regional multi-energy system consisting of three subsystems, namely an integrated screw chiller (ISC), a screw ground-source heat pump (SGSHP), and an air-source heat pump (ASHP), was optimised by the operation control strategy. The system’s power consumption and cooling/heating load characteristics during operation were analysed, and changes in the terminal air-conditioning load were simulated. Based on the dynamic cooling and heating load of the building, a two-stage loading strategy was proposed for optimising the system operation. Taking the load demand matching requirement of the system output and the terminal load demand as constraints, a simulation model of the system was developed using TRNSYS 16 software, and the changes in power consumption and the cooling/heating capacity before and after optimisation were analysed. The results show that the optimised system reduced annual power consumption by approximately 19% and increased condensation heat recovery by about 2.3%. The optimised operation control strategy was aligned well with the terminal cooling and heating demands. Full article

Background/Objectives: Cone-beam computed tomography (CBCT)-guided online adaptive radiotherapy (oART) represents a significant advancement in radiation oncology, enabling on-couch plan adaptation to account for daily anatomical changes. While this automation improves precision and workflow efficiency, it also introduces new failure modes (FMs) and workflow irregularities. This study aimed to systematically evaluate the clinical and technical challenges associated with CBCT-guided oART implementation. Methods: We retrospectively analyzed over 1000 CBCT-guided oART sessions for pelvic malignancies performed at our institution. A multidisciplinary team conducted a comprehensive review to identify and classify FMs, followed by root cause analysis (RCA) to evaluate their impact on treatment safety, efficacy, and workflow robustness. Results: In addition to session-terminating FMs, we identified recurring failure modes across three major domains: (1) system-driven issues, such as rigid target localization and software-driven irregularities; (2) patient-driven challenges, including interfractional and intrafractional anatomical variations; and (3) treatment planning and execution failures, including excessive dose hotspots from field-of-view limitations. The system’s closed-loop automation, while streamlining processes, introduced rigid constraints in plan adaptation and fallback plan execution, occasionally leading to unintended dose discrepancies. Conclusions: This study provides a comprehensive clinical practice-based evaluation of CBCT-guided oART, highlighting system-specific failure modes and their implications. Addressing these challenges requires structured quality assurance processes, multidisciplinary collaboration, and continuous workflow refinement. Our findings contribute to the development of safer and more robust adaptive radiotherapy platforms and clinical workflows. Full article

In this paper, we first introduced asymmetric coupled lines (ACLs) into both the transmission path and isolation path in traditional in-phase Gysel power dividers and proposed the single-resistor asymmetric coupled line in-phase Gysel power dividers (ACPDs). Utilizing the decoupled branch-line model of ACLs, a generalized design approach for ACPDs with arbitrary terminal real impedances and arbitrary power division ratio was innovatively proposed. Design formulas relating terminal real impedances, power division ratio, and image impedances of ACLs, for simultaneously satisfying the perfect port isolation and match conditions, are presented. ACPDs achieved a large in-phase power division ratio of 100:1 (20 dB) and offered significant advantages, including impedance transformation, high design freedom, and miniaturization. To automatically determine accurate initial values of geometric parameters for ACLs, a solution software based on MATLAB-HFSS co-simulation and multi-layer perception neural networks was developed, significantly reducing subsequent optimization iterations. To verify the proposed analysis theory and design approach, three ACPDs with different power division ratios of 1:1 (3 dB), 10:1 (10 dB), and 100:1 (20 dB) were implemented. Comparisons of the measured and simulated results showed great accordance, and the three ACPDs achieved good frequency bandwidth, high isolation, excellent port match, and compact size. Full article

This paper introduces a simulation model designed as a decision-making tool to assess and analyze various crowd management strategies with a focus on enhancing sustainability in airport operations. This model specifically addresses the challenges and risks associated with managing passenger flows within airport terminals. By simulating different scenarios, the model aims to provide valuable insights into how to effectively handle crowd dynamics and enhance overall terminal efficiency, safety, and sustainability. This case study was conducted at Henri Coanda International Airport, ARENA 12 simulation software being used in order to model the passenger flows within the airport terminal. Two scenarios were considered: The first one involves maintaining a fixed number of security and check-in desks for the two airline groups. In contrast, the second scenario allows for a variable number of security and check-in desks for the same airline groups. By optimizing resource allocation and minimizing waiting time, this model contributes to more sustainable airport management operations. Three measures of performance (MOPs) were selected to assess the system activity: the average passenger waiting time, the average passenger number queue length, and the average utilization rate. Comparing the results, we concluded that the second scenario shows a relative improvement in almost all performance measures when compared to the first scenario. Full article