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45 pages, 827 KB

Open AccessArticle

Real-Time Visual Anomaly Detection in High-Speed Motorsport: An Entropy-Driven Hybrid Retrieval- and Cache-Augmented Architecture

by Rubén Juárez Cádiz and Fernando Rodríguez-Sela

J. Imaging 2026, 12(2), 60; https://doi.org/10.3390/jimaging12020060 (registering DOI) - 28 Jan 2026

Abstract

At 300 km/h, an end-to-end vision delay of 100 ms corresponds to 8.3 m of unobserved travel; therefore, real-time anomaly monitoring must balance sensitivity with strict tail-latency constraints at the edge. We propose a hybrid cache–retrieval inference architecture for visual anomaly detection in [...] Read more.

At 300 km/h, an end-to-end vision delay of 100 ms corresponds to 8.3 m of unobserved travel; therefore, real-time anomaly monitoring must balance sensitivity with strict tail-latency constraints at the edge. We propose a hybrid cache–retrieval inference architecture for visual anomaly detection in high-speed motorsport that exploits lap-to-lap spatiotemporal redundancy while reserving local similarity retrieval for genuinely uncertain events. The system combines a hierarchical visual encoder (a lightweight backbone with selective refinement via a Nested U-Net for texture-level cues) and an uncertainty-driven router that selects between two memory pathways: (i) a static cache of precomputed scene embeddings for track/background context and (ii) local similarity retrieval over historical telemetry–vision patterns to ground ambiguous frames, improve interpretability, and stabilize decisions under high uncertainty. Routing is governed by an entropy signal computed from prediction and embedding uncertainty: low-entropy frames follow a cache-first path, whereas high-entropy frames trigger retrieval and refinement to preserve decision stability without sacrificing latency. On a high-fidelity closed-circuit benchmark with synchronized onboard video and telemetry and controlled anomaly injections (tire degradation, suspension chatter, and illumination shifts), the proposed approach reduces mean end-to-end latency to 21.7 ms versus 48.6 ms for a retrieval-only baseline (55.3% reduction) while achieving Macro-F1 = 0.89 at safety-oriented operating points. The framework is designed for passive monitoring and decision support, producing advisory outputs without actuating ECU control strategies. Full article

(This article belongs to the Special Issue AI-Driven Image and Video Understanding)

21 pages, 5003 KB

Open AccessArticle

Design and Implementation of a Wave Measurement System Based on Millimeter-Wave Radar Array

by Zhijin Qiu, Yunfei Jiang, Bo Wang, Chen Fan, Yushang Wu, Zhiqian Li, Jing Zou and Bin Wang

Sensors 2026, 26(3), 859; https://doi.org/10.3390/s26030859 (registering DOI) - 28 Jan 2026

Abstract

Ocean waves are created by energy passing through water, causing it to move in a circular motion and have a crucial impact on the safety of ship navigation, offshore engineering construction, and marine disaster early warning. Therefore, developing high-precision, real-time wave observation technology [...] Read more.

Ocean waves are created by energy passing through water, causing it to move in a circular motion and have a crucial impact on the safety of ship navigation, offshore engineering construction, and marine disaster early warning. Therefore, developing high-precision, real-time wave observation technology to accurately obtain wave parameters is very important. This study employs a One-Vertical-Two-Inclined Millimeter-Wave Radar Array (1V2I-MMWRA) to observe wave parameters in the South China Sea. Based on the measured displacement time series, significant wave height, mean wave height, significant wave period, and mean wave period were estimated using both the zero-crossing method and spectral estimation. The system performance was validated against an air–sea interface flux buoy. Experimental results demonstrate that the zero-crossing method exhibits superior precision. The Root-Mean-Square Errors (RMSEs) for the aforementioned parameters were 0.13 m, 0.11 m, 0.81 s, and 0.46 s, respectively. In contrast, spectral estimation yielded higher RMSEs of 0.20 m, 0.16 m, 1.07 s, and 0.74 s, primarily attributed to increased deviations during typhoon passage. Furthermore, directional spectrum analysis reveals that peak frequency and Power Spectral Density (PSD) intensify with the strengthening of the typhoon, while estimated wave directions align closely with in situ measurements. These findings confirm the high reliability of the 1V2I-MMWRA under extreme conditions, highlighting its distinct advantages of lower power consumption and ease of deployment. Full article

(This article belongs to the Section Environmental Sensing)

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26 pages, 3600 KB

Open AccessReview

Integrated On-Board Charger, Wireless Charging and Auxiliary Power Topologies for EVs: A Survey

by Dorathi Christine D. R. Singh, Narayanamoorthi R, Jamal Aldahmashi and Amr Yousef

Energies 2026, 19(3), 689; https://doi.org/10.3390/en19030689 (registering DOI) - 28 Jan 2026

Abstract

Deploying independent plug-in chargers, wireless chargers and auxiliary power modules within a single Electric Vehicle (EV) leads to an increased system complexity, higher component count and reduced power density. Integrated charger architectures address these limitations by unifying multiple charging and power conversion functions [...] Read more.

Deploying independent plug-in chargers, wireless chargers and auxiliary power modules within a single Electric Vehicle (EV) leads to an increased system complexity, higher component count and reduced power density. Integrated charger architectures address these limitations by unifying multiple charging and power conversion functions within a common hardware framework. Such integration reduces hardware redundancy, improves volumetric efficiency and enables more compact and cost-effective EV designs. Recent studies have explored a wide range of integrated charger topologies, targeting improvements in power density, cost and charging flexibility, often involving trade-offs such as reduced efficiency in exchange for smaller size or lower complexity. This paper presents a review of recent integrated charging topologies for EV applications, emphasizing system-level insights, design trade-offs, emerging trends and key technical challenges with the objective of guiding the development of efficient and scalable next-generation EV charging systems. Full article

(This article belongs to the Collection "Electric Vehicles" Section: Review Papers)

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25 pages, 876 KB

Open AccessArticle

Multi-Scale Digital Twin Framework with Physics-Informed Neural Networks for Real-Time Optimization and Predictive Control of Amine-Based Carbon Capture: Development, Experimental Validation, and Techno-Economic Assessment

by Mansour Almuwallad

Processes 2026, 14(3), 462; https://doi.org/10.3390/pr14030462 (registering DOI) - 28 Jan 2026

Abstract

Carbon capture and storage (CCS) is essential for achieving net-zero emissions, yet amine-based capture systems face significant challenges including high energy penalties (20–30% of power plant output) and operational costs ($50–120/tonne CO

_{2}

). This study develops and validates a novel multi-scale Digital [...] Read more.

Carbon capture and storage (CCS) is essential for achieving net-zero emissions, yet amine-based capture systems face significant challenges including high energy penalties (20–30% of power plant output) and operational costs ($50–120/tonne CO

_{2}

). This study develops and validates a novel multi-scale Digital Twin (DT) framework integrating Physics-Informed Neural Networks (PINNs) to address these challenges through real-time optimization. The framework combines molecular dynamics, process simulation, computational fluid dynamics, and deep learning to enable real-time predictive control. A key innovation is the sequential training algorithm with domain decomposition, specifically designed to handle the nonlinear transport equations governing CO

_{2}

absorption with enhanced convergence properties.The algorithm achieves prediction errors below 1% for key process variables (R

^{2}

> 0.98) when validated against CFD simulations across 500 test cases. Experimental validation against pilot-scale absorber data (12 m packing, 30 wt% MEA) confirms good agreement with measured profiles, including temperature (RMSE = 1.2 K), CO

_{2}

loading (RMSE = 0.015 mol/mol), and capture efficiency (RMSE = 0.6%). The trained surrogate enables computational speedups of up to four orders of magnitude, supporting real-time inference with response times below 100 ms suitable for closed-loop control. Under the conditions studied, the framework demonstrates reboiler duty reductions of 18.5% and operational cost reductions of approximately 31%. Sensitivity analysis identifies liquid-to-gas ratio and MEA concentration as the most influential parameters, with mechanistic explanations linking these to mass transfer enhancement and reaction kinetics. Techno-economic assessment indicates favorable investment metrics, though results depend on site-specific factors. The framework architecture is designed for extensibility to alternative solvent systems, with future work planned for industrial-scale validation and uncertainty quantification through Bayesian approaches. Full article

(This article belongs to the Section Petroleum and Low-Carbon Energy Process Engineering)

14 pages, 1317 KB

Open AccessArticle

Micro-Stress Support-Enhanced Two-Plate Shearing Absolute Testing for Φ800 mm Interferometers

by Zijia Zhao, Zhiliang Zhao, Yuegang Fu, Jiake Wang, Zhihua Zhang and Yehao Zhao

Sensors 2026, 26(3), 858; https://doi.org/10.3390/s26030858 (registering DOI) - 28 Jan 2026

Abstract

Large-aperture optical elements are increasingly in demand for applications in astronomy, high-power lasers, and aerospace technology, but their manufacturing and testing processes pose significant challenges. In this paper, we propose an ultra-large-aperture digital laser plane interferometric testing technique that combines the two-plate shearing [...] Read more.

Large-aperture optical elements are increasingly in demand for applications in astronomy, high-power lasers, and aerospace technology, but their manufacturing and testing processes pose significant challenges. In this paper, we propose an ultra-large-aperture digital laser plane interferometric testing technique that combines the two-plate shearing absolute mutual testing method with micro-stress support technology. This method enables high-precision testing of Φ800 mm planar elements and offers advantages such as fast testing speed, high resolution, and precise alignment. Simulation results and comparisons with measurements from a ZYGO interferometer validate the effectiveness of the proposed method. Experimental testing of an Φ800 mm planar element yielded a PV value of 0.0923 Full article

(This article belongs to the Section Optical Sensors)

30 pages, 2818 KB

Open AccessArticle

From Farm to Retail: Decoding the Elemental Landscape of Milk and Dairy Products Across Organic and Conventional Production Systems Using ICP–MS

by Ovidiu Iliuță Marcus, Alexandra Tabaran, Oana Lucia Crișan Reget, Sorin Daniel Dan, Luciana-Catalina Panait, Caroline-Maria Lăcătuș, Maria Popescu, Andrei Răzvan Codea, Robert Cristian Purdoiu, Radu Lăcătuș, Ioan Valentin Petrescu-Mag, Alexandru Nicolescu and Florin-Dumitru Bora

Toxics 2026, 14(2), 124; https://doi.org/10.3390/toxics14020124 (registering DOI) - 28 Jan 2026

Abstract

The presence of trace and toxic elements in milk and dairy products is an important food safety issue, as contamination can occur along the dairy supply chain and may be influenced by animal species, production system, and processing conditions. This study aimed to [...] Read more.

The presence of trace and toxic elements in milk and dairy products is an important food safety issue, as contamination can occur along the dairy supply chain and may be influenced by animal species, production system, and processing conditions. This study aimed to investigate and compare the multi-elemental composition of milk and selected dairy products obtained from organic, conventional, and commercial production systems in north-western Romania. A total of 307 samples, including raw milk from different animal species (cow, goat, buffalo, donkey) as well as yogurt, cheese, and mozzarella, were collected from farms and retail outlets. Samples were subjected to standardized microwave-assisted acid digestion and analyzed for toxic and essential elements (Pb, Cd, Hg, As, Cr, Ni, Al, Sn, Cu, and Zn) using inductively coupled plasma mass spectrometry (ICP–MS), with quality assurance ensured through certified reference materials and proficiency testing. The results indicated low concentrations of toxic metals across all dairy matrices, with Pb ranging from 0.0047 to 0.0117 mg/kg, Cd from 0.0008 to 0.0011 mg/kg, and As from 0.0007 to 0.0664 mg/kg, depending on animal species and production system. Mercury was consistently below the limit of detection in all datasets (LCD = 100%). Essential and transition elements were systematically quantified, occurring within expected ranges (Al: 0.021–0.264 mg/kg; Cu: 0.078–0.270 mg/kg; Zn: 3.245–7.963 mg/kg; Sn ≈ 0.0030–0.0035 mg/kg). All toxic element concentrations were below the maximum limits established by European Union legislation. Variations in elemental profiles were observed between animal species and production systems, with organic cow milk showing the most homogeneous composition. All toxic element concentrations were below the maximum limits established by European Union legislation. Overall, the findings confirm the safety of the analyzed dairy products and emphasize the relevance of multi-elemental monitoring as a practical tool for dairy supply chain surveillance and risk assessment. Full article

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17 pages, 10981 KB

Open AccessArticle

NeuroGator: A Low-Power Gating System for Asynchronous BCI Based on LFP Brain State Estimation

by Benyuan He, Chunxiu Liu, Zhimei Qi, Ning Xue and Lei Yao

Brain Sci. 2026, 16(2), 141; https://doi.org/10.3390/brainsci16020141 (registering DOI) - 28 Jan 2026

Abstract

The continuous handling of the large amount of raw data generated by implantable brain–computer interface (BCI) devices requires a large amount of hardware resources and is becoming a bottleneck for implantable BCI systems, particularly for power-constrained wireless systems. To overcome this bottleneck, we [...] Read more.

The continuous handling of the large amount of raw data generated by implantable brain–computer interface (BCI) devices requires a large amount of hardware resources and is becoming a bottleneck for implantable BCI systems, particularly for power-constrained wireless systems. To overcome this bottleneck, we present NeuroGator, an asynchronous gating system using Local Field Potential (LFP) for the implantable BCI system. Unlike a conventional continuous data decoding approach, NeuroGator uses hierarchical state classification to efficiently allocate hardware resources to reduce the data size before handling or transmission. The proposed NeuroGator operates in two stages: Firstly, a low-power hardware silence detector filters out background noise and non-active signals, effectively reducing the data size by approximately

69.4 %

. Secondly, a Dual-Resolution Gate Recurrent Unit (GRU) model controls the main data processing procedure on the edge side, using a first-level model to scan low-precision LFP data for potential activity and a second-level model to analyze high-precision LFP data for confirmation of an active state. The experiment shows that NeuroGator reduces overall data throughput by 82% while maintaining an F1-Score of 0.95. This architecture allows the Implantable BCI system to stay in an ultra-low-power state for over 85% of its entire operation period. The proposed NeuroGator has been implemented in an Application-Specific Integrated Circuit (ASIC) with a standard 180 nm Complementary Metal Oxide Semiconductor (CMOS) process, occupying a silicon area of

0.006 {mm}^{2}

and consuming 51 nW power. NeuroGator effectively resolves the resource efficiency dilemma for implantable BCI devices, offering a robust paradigm for next-generation asynchronous implantable BCI systems. Full article

(This article belongs to the Special Issue Trends and Challenges in Neuroengineering)

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28 pages, 3235 KB

Open AccessArticle

Re-Examination: No True Tabidia Snellen, 1880 (Lepidoptera: Crambidae) in China, with Descriptions of Two New Genera and Three New Species

by Jia-Xin Wang, Jun Wu, Wan-Lu Liu and Yun-Li Xiao

Insects 2026, 17(2), 149; https://doi.org/10.3390/insects17020149 (registering DOI) - 28 Jan 2026

Abstract

Many species within the genus Tabidia Snellen, 1880 exhibit significant differences in wing pattern and genital morphology, which are inconsistent with the definition of Tabidia, indicating that the genus is not monophyletic. To address this, the present study revises the taxonomy of [...] Read more.

Many species within the genus Tabidia Snellen, 1880 exhibit significant differences in wing pattern and genital morphology, which are inconsistent with the definition of Tabidia, indicating that the genus is not monophyletic. To address this, the present study revises the taxonomy of the Chinese species previously placed in Tabidia based on wing morphological characteristics, differences in male and female genitalia, and phylogenetic relationships inferred from the mitochondrial COI gene and mitochondrial genomes. As a result, two new genera are established: Melanoleucagen. nov. and Scintillagen. nov. These new genera are confirmed to belong to the tribe Agroterini Acloque, 1897. Furthermore, three cryptic new species are discovered: Melanoleuca luteamacula sp. nov., Melanoleuca qianshanensis sp. nov., and Melanoleuca yingshanensis sp. nov. Based on the morphological characteristics of adult appearance and genitalia, an identification key to the species of these two new genera is provided. Illustrations of adult specimens and their genital structures are provided, along with a world catalog of the species for the three relevant genera: Tabidia, Melanoleuca, and Scintilla. Full article

(This article belongs to the Section Insect Systematics, Phylogeny and Evolution)

34 pages, 2492 KB

Open AccessArticle

The Positive Impact of the Digital Economy on the Coordinated Development of the Rural Economy–Environment: Evidence from China

by Shiou Liao, Chunfang Yang and Yifeng Zhang

Agriculture 2026, 16(3), 322; https://doi.org/10.3390/agriculture16030322 (registering DOI) - 28 Jan 2026

Abstract

The coordinated development of the rural economy and the ecological environment remains a central challenge in China’s rural revitalization agenda. Against this backdrop, the rapid expansion of the digital economy (DE) has the potential to reshape traditional development pathways and ease the longstanding [...] Read more.

The coordinated development of the rural economy and the ecological environment remains a central challenge in China’s rural revitalization agenda. Against this backdrop, the rapid expansion of the digital economy (DE) has the potential to reshape traditional development pathways and ease the longstanding tension between economic growth and environmental sustainability. However, existing studies have predominantly examined the economic or environmental effects of digitalization in isolation, leaving its role in fostering their coordinated development largely unexplored. Using balanced panel data for 30 Chinese provinces from 2011 to 2021, this paper constructs an index of the coupling coordinated development of the rural economy–environment (CREE) and employs a two-way fixed-effects framework, complemented by mediation analysis, panel threshold regression, and a spatial Durbin model, to examine the impact of the DE on CREE and its transmission mechanisms. The results show that the DE significantly enhances CREE on average. This positive effect, however, is non-linear and conditional: it emerges only after rural educational attainment exceeds a critical threshold, and its marginal contribution diminishes as the level of digital development increases. Mechanism analyses indicate that the DE promotes CREE primarily by stimulating technological innovation and advancing urbanization, while improvements in the structure of human capital further strengthen this relationship. Spatial econometric evidence reveals pronounced spillover effects of the DE on CREE across regions, with spillovers based on economic distance outweighing those associated with geographic proximity. By adopting a coupling perspective that integrates economic and environmental dimensions, this paper clarifies the non-linear dynamics, transmission channels, and spatial diffusion processes through which the DE contributes to rural green development. The findings underscore the importance of strengthening rural education foundations, deepening the application of digital technologies, and enhancing regional coordination to fully harness the DE’s role in promoting coordinated economy–environment development. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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30 pages, 5022 KB

Open AccessReview

Fibroblast-Targeted Nanodelivery Systems: Mechanisms of Collagen Remodeling Regulation and Novel Strategies for Scar Repair

by Junshan Lan, Zhipeng Teng, Qian Huang, Fang Qin, Yibin Zheng, Yuting Liu, Yilin Chang, Xing Zhou, Xiaohui Li, Wenwu Wan, Lu Wang and Jie Lou

Pharmaceutics 2026, 18(2), 172; https://doi.org/10.3390/pharmaceutics18020172 (registering DOI) - 28 Jan 2026

Abstract

Scar formation is a common outcome of post-injury repair and can compromise both esthetic appearance and physiological function. Fibroblasts are central mediators of this process; their aberrant activation or differentiation into myofibroblasts drives fibrosis and excessive scar tissue accumulation. Nanodrug delivery systems (NDDSs) [...] Read more.

Scar formation is a common outcome of post-injury repair and can compromise both esthetic appearance and physiological function. Fibroblasts are central mediators of this process; their aberrant activation or differentiation into myofibroblasts drives fibrosis and excessive scar tissue accumulation. Nanodrug delivery systems (NDDSs) offer unique opportunities to modulate fibroblast behavior through cell-/microenvironment-guided targeting, controlled release, and stimuli-adaptive designs. Here, we summarize fibroblast biology across scar repair and delineate the mechanistic underpinnings of scar pathogenesis. We then synthesize recent progress in NDDS-enabled interventions for pathological scarring, with an emphasis on how materials design can be matched to fibroblast states and wound-stage cues. By connecting mechanisms to delivery strategies, this review provides a framework to guide the development of scar-minimizing therapies and functional tissue regeneration. Full article

(This article belongs to the Special Issue Novel Drug Delivery Systems for the Treatment of Skin Disorders)

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24 pages, 1668 KB

Open AccessArticle

Experimental and Analytical Investigation of the Flexural Performance of UHPC Beams Reinforced with Hybrid GFRP and Steel Bars

by Tianyu Shi, Kangsheng Huang, Ruochen Wang, Changming Dai and Kun Wang

Buildings 2026, 16(3), 535; https://doi.org/10.3390/buildings16030535 (registering DOI) - 28 Jan 2026

Abstract

To investigate the bending response of ultra-high-performance concrete (UHPC) beams reinforced with hybrid glass-fiber-reinforced polymer (GFRP) and steel bars, five specimens were tested in four-point bending in the present experimental study. The effect of varying reinforcement ratios on the flexural behavior was evaluated. [...] Read more.

To investigate the bending response of ultra-high-performance concrete (UHPC) beams reinforced with hybrid glass-fiber-reinforced polymer (GFRP) and steel bars, five specimens were tested in four-point bending in the present experimental study. The effect of varying reinforcement ratios on the flexural behavior was evaluated. It was observed that all tested beams failed due to reinforcement yielding while maintaining satisfactory ductility; the failure mode was characterized by yielding of the bottom tensile reinforcement followed by crushing of the UHPC in the compression zone. When the steel reinforcement ratio increased from 2.03% to 2.42% and 3.08%, the beam load-carrying capacity increased by 6.27% and 14.34%, respectively. When the GFRP reinforcement ratio increased from 0.91% to 1.19% and 1.51%, the peak load-carrying capacity increased by 9.58% and 15.55%, respectively. Based on reasonable assumptions, analytical formulas were proposed to predict the cracking moment and the flexural capacity of the UHPC beams reinforced with hybrid GFRP and steel bars, with errors within ±5%. By fully accounting for the bridging effect of steel fibers, modified coefficients were introduced to estimate beam deformation and crack width, along with corresponding calculation methods. The proposed formulas accurately predicted cracking moment, ultimate moment, deflection and crack width for the beam. The findings propose a theoretical basis for the design and application of UHPC beams reinforced with hybrid GFRP and steel bars. Full article

(This article belongs to the Section Building Structures)

34 pages, 1040 KB

Open AccessArticle

Digital Infrastructure, SME E-Commerce, and Economic Growth: Evidence from China’s Platform Economy

by Tengyue Hao, Rajah Rasiah and Sohaib Mustafa

Economies 2026, 14(2), 40; https://doi.org/10.3390/economies14020040 (registering DOI) - 28 Jan 2026

Abstract

Digitalization is increasingly central to economic growth strategies, yet robust macro-level evidence on the role of SME-led e-commerce remains limited. Drawing on the Resource-Based View, this study examines how SME digitalization, internet finance, and platform-based activities influence regional economic growth in China, and [...] Read more.

Digitalization is increasingly central to economic growth strategies, yet robust macro-level evidence on the role of SME-led e-commerce remains limited. Drawing on the Resource-Based View, this study examines how SME digitalization, internet finance, and platform-based activities influence regional economic growth in China, and how these effects depend on digital infrastructure readiness (DIR). We construct an annual panel of 30 provincial-level regions in China over 2015–2024 and estimate dynamic relationships using two-step system GMM to address endogeneity and growth persistence. The results show that SME digitalization, supply-chain efficiency, mobile payment penetration, tech-driven employment growth, platform-economy contribution, and DIR all exert statistically significant positive effects on GDP growth. Quantitatively, a 10-percentage-point increase in SME digitalization is associated with approximately 0.3-percentage-point higher regional GDP growth, while a 10-point increase in DIR corresponds to about 0.4-percentage-point higher growth. Moderation analyses reveal that DIR significantly amplifies the growth effects of e-commerce expansion, mobile payments, and digital marketing, whereas its moderating role is weaker or insignificant for cross-border payments and supply-chain efficiency. These findings reconceptualize digitalization as a coordinated bundle of complementary resources and position DIR as a critical enabling capability for translating SME digital transformation into macroeconomic growth. The study offers policy-relevant evidence for targeting infrastructure investment and digital-economy strategies in emerging platform economies. Full article

(This article belongs to the Section Economic Development)

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75 pages, 5082 KB

Open AccessReview

Phytochemical Insights and Biological Potential of the Helianthus Genus

by Aldana Malen Corlatti, Hernán Bach, Ignacio Jorge Aguelo, Orlando Germán Elso, Rafael Ricco, Laura Cecilia Laurella and Valeria Patricia Sülsen

Plants 2026, 15(3), 401; https://doi.org/10.3390/plants15030401 (registering DOI) - 28 Jan 2026

Abstract

The Helianthus genus comprises more than 60 species distributed throughout North and Central America, with a few extending into South America. Among these, H. annuus and H. tuberosus represent the most widely utilized and extensively investigated species. The aim of this paper is [...] Read more.

The Helianthus genus comprises more than 60 species distributed throughout North and Central America, with a few extending into South America. Among these, H. annuus and H. tuberosus represent the most widely utilized and extensively investigated species. The aim of this paper is to provide an overview of the current knowledge regarding the phytochemical composition and biological activities of Helianthus species. Phytochemical studies of Helianthus taxa have demonstrated that terpenoid constituents, including sesquiterpene lactones, diterpenes, and triterpenes, together with phenolic compounds, constitute the principal classes of secondary metabolites. Pharmacological investigations on Helianthus extracts have revealed a broad spectrum of biological activities. More than twenty distinct bioactivities have been reported for H. annuus, with the majority supported by in vitro assays (≈26 reports), reflecting multiple experimental evaluations per activity using different plant parts, extracts, and models; followed by a substantial number of in vivo studies in animal models (≈21 reports), and very limited clinical evidence. In comparison, five bioactivities have been described for H. tuberosus, mainly in vitro with a few in vivo reports, whereas only single in vitro bioactivities have been described for H. salicifolius and H. angustifolius. Among these, antidiabetic, antioxidant, antimicrobial, and anticancer properties are the most frequently documented. Full article

(This article belongs to the Special Issue Bioactive Metabolites from Plants as Potential Treatments for Global Diseases)

16 pages, 10848 KB

Open AccessArticle

LLM4ATS: Applying Large Language Models for Auto-Testing Scripts in Automobiles

by Zeyuan Li, Wei Li, Yuezhao Liu, Wenhao Li and Min Chen

Big Data Cogn. Comput. 2026, 10(2), 41; https://doi.org/10.3390/bdcc10020041 (registering DOI) - 28 Jan 2026

Abstract

This paper introduces LLM4ATS , a framework integrating large language models, RAG, and closed-loop verification to automatically generate highly reliable automotive automated test scripts from natural language descriptions. Addressing the complex linguistic structure, strict rules, and strong dependency on the in-vehicle communication database [...] Read more.

This paper introduces LLM4ATS , a framework integrating large language models, RAG, and closed-loop verification to automatically generate highly reliable automotive automated test scripts from natural language descriptions. Addressing the complex linguistic structure, strict rules, and strong dependency on the in-vehicle communication database inherent in ATS scripts, LLM4ATS innovatively employs fine-grained line-level generation and a rule-guided iterative refinement mechanism. The framework first enhances prompt context by retrieving relevant information from constructed syntax and case knowledge bases via RAG. Subsequently, each generated script line undergoes rigorous verification through a two-stage validator: initial syntax validation followed by semantic compliance checks against the communication database for signal paths and value domains. Any errors trigger structured feedback, driving iterative refinement by the large language model until fully compliant scripts are produced. This paper evaluated the framework’s effectiveness on real ATS datasets, testing models including GPT-3.5, GPT-4, Qwen2.5-7B, and Qwen2.5-72B-Instruct. Experimental results demonstrate that compared to zero-shot and few-shot baseline methods, the LLM4ATS framework significantly improves generation quality and pass rates across all models. Notably, the strongest GPT-4 model achieved a script pass rate of 91% with LLM4ATS, up from 42% in zero-shot mode, and validated functional effectiveness on a specified in-vehicle hardware platform (Chery Fengyun T28 dashboard). At the same time, expert manual evaluations confirmed the superior performance of the generated scripts in correctness, readability, and compliance with industry standards. Full article

36 pages, 2846 KB

Open AccessReview

Protection in Inverter-Dominated Grids: Fault Behavior of Grid-Following vs. Grid-Forming Inverters and Mixed Architectures—A Review

by Md Nurunnabi and Shuhui Li

Energies 2026, 19(3), 684; https://doi.org/10.3390/en19030684 (registering DOI) - 28 Jan 2026

Abstract

The rapid rise of inverter-based resources (IBRs) such as solar, wind, and battery energy storage is transforming power grids and creating new challenges for protection. Unlike synchronous generators, many IBRs are interfaced through grid-following (GFL) inverters that operate as controlled current sources and [...] Read more.

The rapid rise of inverter-based resources (IBRs) such as solar, wind, and battery energy storage is transforming power grids and creating new challenges for protection. Unlike synchronous generators, many IBRs are interfaced through grid-following (GFL) inverters that operate as controlled current sources and rely on an external voltage reference, resulting in fault responses that are current-limited and controller-shaped. These characteristics reduce fault current magnitude and can undermine conventional protection schemes. In contrast, emerging grid-forming (GFM) inverters behave as voltage sources that establish local voltage and frequency, offering improved disturbance support but still transitioning to current-limited operation under severe faults. This review summarizes GFL versus GFM operating principles and deployments, compares their behavior under balanced and unbalanced faults, and evaluates protection impacts using a protection-relevant taxonomy supported by illustrative electromagnetic transient (EMT) case studies. Key challenges, including underreach/overreach of impedance-based elements, reduced overcurrent sensitivity, and directional misoperation, are identified. Mitigation options are discussed, spanning adaptive/supervised relaying, communication-assisted and differential protection, and inverter-side fault current shaping and GFM integration. The implications of IEEE 1547-2018 and IEEE 2800-2022 are reviewed to clarify ride-through and support requirements that constrain protection design in high-IBR systems. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Power Converters and Microgrids)

28 pages, 3721 KB

Open AccessArticle

A Fuzzy Bayesian-Based Integrated Framework for Risk Analysis of a Dual-Cycle Liquefied Natural Gas Cold Energy Power Generation System

by Yulin Zhou, Yungen He, Guojin Qin, Yihuan Wang, Chuanqi Guo, Chen Fang, Rongsheng Lin and Bohong Wang

Energies 2026, 19(3), 688; https://doi.org/10.3390/en19030688 (registering DOI) - 28 Jan 2026

Abstract

LNG serves as a pivotal element within integrated energy systems, especially in coastal regions where the implementation of a stable and reliable LNG cold energy power generation system significantly elevates energy efficiency. This system can effectively meet concurrent demands for cold energy utilization [...] Read more.

LNG serves as a pivotal element within integrated energy systems, especially in coastal regions where the implementation of a stable and reliable LNG cold energy power generation system significantly elevates energy efficiency. This system can effectively meet concurrent demands for cold energy utilization and electricity supply while contributing to the mitigation of carbon emissions. However, the inherent complexity of the system coupled with the scarcity of historical operational data for the novel dual-Rankine cycle process renders conventional reliability assessment methodologies inadequate. This study proposes an integrated framework utilizing fuzzy Bayesian methods to address data scarcity during the early stages of equipment deployment. A hierarchical risk factor model, incorporating process decomposition, expert evaluations, and triangular fuzzy numbers, is developed to quantify uncertainties in failure probabilities. The Bayesian network models the causal relationships among equipment failure factors, allowing for the inference of overall system reliability from individual equipment performance. Through a case study of a LNG terminal in Zhoushan, this approach integrates sensitivity analysis with forward-backward reasoning methodologies to rigorously evaluate and quantify system reliability under operational conditions. The results show that under high load conditions within the 1000 h prior to overhaul, following long-term accumulated operation, the probability of complete system shutdown in the power generation system is 3.30%, while the probability of the LNG cold energy power generation system failing to operate fully due to aging-related faults is 8.24%, demonstrating the system’s strong reliability under extreme conditions. Critical risks identified through backward inference include the seawater pump SWP1, with a posterior failure probability of 59.92% during complete shutdown, and the propane-side pump SWP3, with a posterior failure probability of 32.29% when the cold energy power generation system can only operate in a single-cycle mode. This study provides an advanced methodological framework for risk management in newly constructed LNG cold energy power generation systems, playing a crucial role in promoting sustainable, low-carbon technologies in the energy sector. Full article

(This article belongs to the Special Issue Advanced Research on Heat Exchanger Networks and Heat Recovery: 2nd Edition)

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13 pages, 440 KB

Open AccessArticle

The Effects of Fire on California Sage Scrub Germination Assemblages

by Bailey Parkhouse, Hannah Chan and Wallace Martin Meyer III

Seeds 2026, 5(1), 9; https://doi.org/10.3390/seeds5010009 (registering DOI) - 28 Jan 2026

Abstract

California sage scrub is an endangered, shrub-dominated, southern California ecosystem threatened by increasing fire frequencies and type-conversion to non-native grasslands. Once non-native grasses become established, their presence promotes more frequent fires, perpetuating grass dominance. To better understand how fire influences soil seed bank [...] Read more.

California sage scrub is an endangered, shrub-dominated, southern California ecosystem threatened by increasing fire frequencies and type-conversion to non-native grasslands. Once non-native grasses become established, their presence promotes more frequent fires, perpetuating grass dominance. To better understand how fire influences soil seed bank assemblages, we examined soil seed banks in burned and adjacent unburned sage scrub at the Robert J. Bernard Field Station (BFS) in two areas that burned in September 2013 and May 2017. In contrast to a previous soil seed bank study in California sage scrub, we found that unburned soil seed banks in sage scrub at the BFS were primarily composed of native seeds (88% of sprouts in unburned areas were native), highlighting that soil seed bank dynamics differ among California sage scrub sites. Despite burned areas supporting elevated densities of non-native seeds (the majority of which included Festuca myuros, a non-native grass), soil seed banks in our burned areas retained native seeds (21% of sprouts in burned areas were native), including native shrub species, suggesting that not all sage scrub habitats are primed to transition to non-native grasslands following disturbances. However, elevated densities on non-native seedlings in burned areas highlight the vulnerability of sage scrub to fire disturbances and the subsequent establishment of non-native grasses. Full article

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38 pages, 3428 KB

Open AccessReview

Superparamagnetic Nanoparticles Targeting Brain Cancer: Innovations in Carbohydrate-Based Coatings and Magnetic Field Guidance

by Ahmed Mahdi Abed Alobaidi and Vadim V. Kumeiko

Cancers 2026, 18(3), 419; https://doi.org/10.3390/cancers18030419 (registering DOI) - 28 Jan 2026

Abstract

The effective treatment of aggressive brain tumors, such as glioblastoma, is critically hindered by the blood-brain barrier (BBB) and the non-specific clearance of therapeutic agents by the immune system. Superparamagnetic iron oxide nanoparticles (SPMNPs) offer a powerful theranostic platform, combining magnetic resonance imaging [...] Read more.

The effective treatment of aggressive brain tumors, such as glioblastoma, is critically hindered by the blood-brain barrier (BBB) and the non-specific clearance of therapeutic agents by the immune system. Superparamagnetic iron oxide nanoparticles (SPMNPs) offer a powerful theranostic platform, combining magnetic resonance imaging (MRI)-based diagnostics with therapeutic delivery and hyperthermia. However, their clinical translation requires sophisticated strategies to ensure precise delivery to the tumor site. This review examines innovative functionalization strategies to enhance the targeting and efficacy of SPMNPs. Specifically, it addresses the various strategies for coating magnetic nanoparticles with carbohydrates, including both covalent and non-covalent methods, and the subsequent functionalization of these glycoconjugates to exploit the unique biological environment of brain tumors. The use of glycoconjugates on the nanoparticle surface is a key strategy, leveraging the altered glycosylation patterns and overexpression of specific lectins on glioma cell surfaces to achieve highly selective cellular targeting. The review details the synergistic effect achieved by combining these functionalized nanoparticles with external magnetic field guidance. This combination provides a dual-action mechanism: the magnetic field actively guides the nanoparticles across the BBB and concentrates them within the tumor mass, while the carbohydrate coating ensures specific cellular uptake, thereby significantly improving local therapeutic concentration and minimizing systemic toxicity. The scope of this review includes the development and evaluation of carbohydrate-coated SPMNPs, outlining their optimized physicochemical properties for both in vitro and in vivo imaging and treatment of cancerous brain tissues. This comprehensive evaluation represents a critical advancement in biomedicine, aiming to improve the prognosis for patients with brain cancer through more precise and effective therapeutic interventions. Full article

(This article belongs to the Special Issue Nanocarriers as an Emerging Platform for Cancer Therapy)

27 pages, 6483 KB

Open AccessArticle

Neighboring Alkali Cations as an Efficient Strategy for N₂ Activation: A DFT Analysis

by Jean C. Villa-Arpi, Romel Guañuna, Juan P. Saucedo-Vazquez and Thibault Terencio

Int. J. Mol. Sci. 2026, 27(3), 1311; https://doi.org/10.3390/ijms27031311 (registering DOI) - 28 Jan 2026

Abstract

Nitrogen gas is one of the most abundant resources on Earth, serving as a fundamental component in both biological and industrial processes. Nevertheless, this simple molecule can only be activated by a limited group of microorganisms in nature. Significant efforts have been devoted [...] Read more.

Nitrogen gas is one of the most abundant resources on Earth, serving as a fundamental component in both biological and industrial processes. Nevertheless, this simple molecule can only be activated by a limited group of microorganisms in nature. Significant efforts have been devoted to replicating this biological activity using metalorganic approaches. However, it is becoming increasingly evident that non-covalent interactions, particularly ionic interactions, can further enhance catalytic reactions. In this work, the effect of alkali and alkaline-earth cations on dinitrogen activation was assessed using Density Functional Theory (DFT) at distances ranging from 2 to 10 Å. This analysis revealed three distinct activity regimes. In Case I, the polarization of the N₂ molecule is the primary driving force; in Case II, the polarization effect is less pronounced; and in Case III, electrostatic interactions dominate, enhancing electron delocalization within the N₂–Mⁿ⁺ system. Among the various cations, those belonging to group II-A are particularly noteworthy due to their high ionic potential and polarizing power, with Mg²⁺ standing out for its superior activity at an N₂–Mg²⁺ distance of 2.7 Å. Consequently, these theoretical insights can serve as a guiding strategy for designing efficient N₂-activating complexes that integrate covalent and non-covalent interactions synergistically. Full article

(This article belongs to the Special Issue Noncovalent Interactions and Applications in Materials and Catalysis)

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16 pages, 438 KB

Open AccessReview

Advances in Adjuvanted Rabies Vaccines

by Yutian Wang, Hongliang Sun and Yehong Wu

Vaccines 2026, 14(2), 132; https://doi.org/10.3390/vaccines14020132 (registering DOI) - 28 Jan 2026

Abstract

Rabies is an acute and fatal zoonotic disease caused by the rabies virus, responsible for approximately 59,000 deaths worldwide each year. Once clinical symptoms manifest, the case fatality rate approaches 100%. Vaccination remains the only effective strategy for prevention and control. Currently, human [...] Read more.

Rabies is an acute and fatal zoonotic disease caused by the rabies virus, responsible for approximately 59,000 deaths worldwide each year. Once clinical symptoms manifest, the case fatality rate approaches 100%. Vaccination remains the only effective strategy for prevention and control. Currently, human rabies vaccines approved by regulatory authorities such as the U.S. Food and Drug Administration (FDA), and the China National Medical Products Administration (NMPA) are all inactivated, adjuvant-free formulations. These vaccines are associated with several limitations, including weak immunogenicity, delayed induction of neutralizing antibodies, complex immunization schedules, and poor patient compliance. Adjuvants, as nonspecific immunoenhancers, can potentiate the immune response even at low antigen doses and reduce the number of required doses, offering a promising approach to overcome the aforementioned challenges. This article reviews recent advances in adjuvants suitable for rabies vaccines and discusses the key challenges currently faced in the development of adjuvanted rabies vaccines. Full article

(This article belongs to the Section Vaccine Advancement, Efficacy and Safety)

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17 pages, 1369 KB

Open AccessReview

Challenges of Applying the RANO-BM Criteria for Characterization of Brain Metastases Treatment Response

by Tatiana Kashtanova and Naren Ramakrishna

Curr. Oncol. 2026, 33(2), 77; https://doi.org/10.3390/curroncol33020077 (registering DOI) - 28 Jan 2026

Abstract

The goal of brain metastasis therapy is to reduce the risk of intracranial disease progression and to minimize treatment-related adverse effects and loss of neurologic function without compromising extracranial disease control. A response assessment system plays a critical role in the comparative evaluation [...] Read more.

The goal of brain metastasis therapy is to reduce the risk of intracranial disease progression and to minimize treatment-related adverse effects and loss of neurologic function without compromising extracranial disease control. A response assessment system plays a critical role in the comparative evaluation of therapeutic strategies in clinical trials and in routine patient care. Since 2015, the RANO-BM criteria have become a standard schema for evaluating brain metastases treatment response, providing uniform definitions and methodology particularly practical in prospective clinical trials of systemic therapy. There have been a variety of modifications and additions to the original guidelines proposed to improve their utility for brain metastases response assessment, including lowering the measurable disease size threshold, optimizing disease progression metrics, and employing tumor volumetric analysis using automated measurement tools. However, despite these enhancements, the criteria display limitations in selected clinical scenarios. This article provides a detailed overview of these limitations and their corresponding clinical contexts and concludes with a discussion of approaches which may aid in the development of a more comprehensive brain metastases response assessment system. Full article

(This article belongs to the Section Neuro-Oncology)

24 pages, 2167 KB

Open AccessReview

Evolution from Composome to RNA Replicase

by Shaojie Deng, Doron Lancet and Roy Yaniv

Life 2026, 16(2), 219; https://doi.org/10.3390/life16020219 (registering DOI) - 28 Jan 2026

Abstract

This paper proposes a novel scheme for the origin of RNA replicase based on the replication-first stable complex evolution (SCE) model, also known as the stable complex encoding (SCE) model, and attempts to derive this scheme from the metabolism-first graded autocatalysis replication domain [...] Read more.

This paper proposes a novel scheme for the origin of RNA replicase based on the replication-first stable complex evolution (SCE) model, also known as the stable complex encoding (SCE) model, and attempts to derive this scheme from the metabolism-first graded autocatalysis replication domain (GARD) model, thereby theoretically integrating the two hypotheses of the origin of life: replication-first and metabolism-first. Currently, although the replication-first model has made some progress in the artificial selection of RNA replicase, it has yet to achieve a true breakthrough. Meanwhile, metabolism-first models such as the CAS (Collectively Autocatalytic Set) and its graph version RAF (Reflexively Autocatalytic and Food-generated) models, have conducted in-depth research into the origin of metabolic networks but have failed to address the critical transformation issue from metabolism to RNA replication. This paper argues that these two hypotheses should mutually support each other. By introducing oligonucleotide assemblies and expanding the concept of composomes in the GARD model, this paper attempts to understand the general evolutionary mechanism of enzymes, thereby addressing the long-standing neglect of enzymatic catalysis in metabolism-first theories. This integrated scheme not only provides new theoretical support for the evolution of RNA replicase but also offers important insights into solving the key transition problem from chemical evolution to biological evolution. Full article

(This article belongs to the Special Issue The 15th Anniversary of Life—Alternatives to RNA World)

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18 pages, 6947 KB

Open AccessArticle

Introducing Gregorian Chant to a Malaysian Methodist Congregation: A Case Study

by Cecilia Ting, Eleanor J. Giraud and Helen Phelan

Religions 2026, 17(2), 151; https://doi.org/10.3390/rel17020151 (registering DOI) - 28 Jan 2026

Abstract

This study explores the feasibility of introducing Gregorian chant into contemporary Chinese Methodist worship in Malaysia. Using ethnographic methods including participant observation, interviews, and focus groups, this article documents a pilot study conducted at Sing Ang Tong Methodist Church in Sibu, Sarawak, where [...] Read more.

This study explores the feasibility of introducing Gregorian chant into contemporary Chinese Methodist worship in Malaysia. Using ethnographic methods including participant observation, interviews, and focus groups, this article documents a pilot study conducted at Sing Ang Tong Methodist Church in Sibu, Sarawak, where seven singers learned and performed the communion chant Gustate et videte. Three different transcription editions were created to bridge the gap between medieval square notation and modern Western notation, which is more familiar to the participants. The chant was translated into Chinese alongside the original Latin text. The majority preferred the quaver-crotchet notation edition and supported performing the chant in both Latin and Chinese to balance authenticity with accessibility. Participants found the modal melodic structure and free rhythm challenging initially but developed appreciation for the chant’s meditative qualities. The performance during Holy Communion services in October 2022 received mixed congregational responses, with many describing it as creating a “calm and prayerful atmosphere” while some expressed discomfort with the unfamiliar musical style. The study demonstrates that Gregorian chant can be successfully integrated into Chinese Methodist worship contexts, particularly during solemn liturgical occasions, when approached with appropriate liturgical sensitivity and cultural adaptation. Full article

(This article belongs to the Special Issue Sacred Music: Creation, Interpretation, Experience)

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23 pages, 51673 KB

Open AccessArticle

HD-BSNet: A Plug-and-Play Dual-Mechanism Synergistic Enhancement Framework for Small Object Detection

by Jianwei Wen, Xiangyue Zheng, Nian Pan, Dan Jia, Haiying Wu, Tao Chen and Jin Zhou

Remote Sens. 2026, 18(3), 423; https://doi.org/10.3390/rs18030423 (registering DOI) - 28 Jan 2026

Abstract

In remote sensing and low-altitude unmanned aerial vehicle(UAV) detection scenarios, small target detection is extremely challenging due to the low pixel proportion, sparse features, and complex backgrounds of targets. The reliability of low-altitude security, in particular, is directly dependent on the accuracy of [...] Read more.

In remote sensing and low-altitude unmanned aerial vehicle(UAV) detection scenarios, small target detection is extremely challenging due to the low pixel proportion, sparse features, and complex backgrounds of targets. The reliability of low-altitude security, in particular, is directly dependent on the accuracy of small target detection. However, current methods still face three major limitations: insufficient detection accuracy for targets smaller than 20 pixels; artifacts and false textures introduced by Generative Adversarial Network-based enhancement, which lead to increased false detection rates; and the reliance of existing approaches on specialized architectures, resulting in weak generalization capability and difficulty in adapting to multi-scenario deployment requirements. To address these issues, this paper proposes a plug-and-play dual-mechanism collaborative enhancement framework named HD-BSNet. Firstly, a High-Frequency Differential Perception mechanism is designed to enhance the detailed feature representation of small targets. Secondly, a Background Semantic Modeling mechanism is introduced to learn key features that distinguish targets from the background. Additionally, a Parallel Multi-Scale Focus Module is constructed to further reinforce target features. Extensive experiments on three small target datasets demonstrate that the proposed method effectively improves the accuracy and generalization ability of small target detection. Full article

15 pages, 928 KB

Open AccessArticle

Mild to Virulent: Coat Protein Mutations Restore Mosaic Symptom Induction in a Korean PepMV Isolate

by Thuy T. B Vo, Marjia Tabassum, Ika Agus Rini, Bupi Nattanong, Hyo-Jin Im, Minkwan Kim, Hee-Seong Byun, Hae-Ryun Kwak and Sukchan Lee

Viruses 2026, 18(2), 175; https://doi.org/10.3390/v18020175 (registering DOI) - 28 Jan 2026

Abstract

Pepino mosaic virus (PepMV) is a significant threat to global tomato production, with symptom severity varying widely among strains and often leading to significant economic losses. Despite extensive studies on aggressive variants, the molecular determinants of mild symptomatology in field isolates, particularly from [...] Read more.

Pepino mosaic virus (PepMV) is a significant threat to global tomato production, with symptom severity varying widely among strains and often leading to significant economic losses. Despite extensive studies on aggressive variants, the molecular determinants of mild symptomatology in field isolates, particularly from Korea, remain underexplored. In this study, we characterized a mildly infecting PepMV isolate from asymptomatic tomato plants during a field survey in Jeonju, South Korea. The full-length genome sequence and phylogenetic analysis classified it as a CH2 strain. A full-length cDNA infectious clone of this isolate was constructed and confirmed to induce no mosaic symptoms in tomato plants. To identify symptom determinants, targeted mutagenesis was performed in the coat protein (CP) open reading frame. Substitution mutations at CP position 236 or combined 6/155 substitutions converted the mild isolate into a severe variant, inducing strong mosaic symptoms and significantly higher viral accumulation (up to tenfold). These results demonstrated that specific CP residues act as key regulators of symptom severity in PepMV CH2 strains and provide defined severe mutants as useful tools for screening resistance in tomatoes. Although the mechanism underlying symptom modulation remains unclear, this work advanced our understanding of molecular differences between mild and severe strains and supported targeted strategies for managing this economically important virus. Full article

(This article belongs to the Special Issue Emerging and Reemerging Plant Viruses in a Changing World: 2nd Edition)

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18 pages, 2351 KB

Open AccessArticle

Elevator Travelling Cable’s Diagnostics Based on Deep Learning Fitting and Channel Attention

by Zuen He, Jianguo Chen, Yao Lin, Renhui Yu, Zhenhua Li and Nan Xie

Electronics 2026, 15(3), 562; https://doi.org/10.3390/electronics15030562 (registering DOI) - 28 Jan 2026

Abstract

The ageing of elevator travelling cables results in the breakage of inner copper strands, leading to communication and control faults in the elevator system. In this paper, a travelling cable state evaluation method based on time-frequency transformation and a deep learning fitting method [...] Read more.

The ageing of elevator travelling cables results in the breakage of inner copper strands, leading to communication and control faults in the elevator system. In this paper, a travelling cable state evaluation method based on time-frequency transformation and a deep learning fitting method is proposed. The cable diagnosis is based on the transmission line theory and finite element simulation results, which indicate that the number of broken strands of copper wires in twisted cables is positively related to the amplitude of fluctuation in the cable’s transmission spectrum. To evaluate this fluctuation with low cost and high accuracy, we acquired the 500 Msps time-domain signal after a square wave with different periods was transmitted through the detected cable; the transmission in base frequency and harmonics is calculated and combined into the total transmission spectrum. A deep learning model with a two-layer 1-D CNN and squeeze-excitation channel attention is utilized to fit the spectrum data, and cross-entropy is applied to estimate the departure between the fitting results and the experimental data, which serves as the cable’s broken-state index. Experiments demonstrate that the proposed method is able to detect minor cable faults such as one or two copper strands broken and could distinguish different broken states with a sensitivity of 16.42 ± 1.39 per break strand. Full article

(This article belongs to the Section Industrial Electronics)

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