Annual Achievements Report
Available Now
 
 Find out more
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 

Recent Articles  

21 pages, 1090 KiB  
Article
Analyzing CO2 Emissions by CSI Categories: A Life Cycle Perspective
by Gulbin Ozcan-Deniz and Sarah Rodovalho
Sustainability 2025, 17(15), 6830; https://doi.org/10.3390/su17156830 (registering DOI) - 27 Jul 2025
Abstract
As the construction industry continues to evolve, energy consumption of buildings, particularly CO2 emissions, has become a critical focus for sustainable development. The need for effective design decisions regarding the selection of materials throughout the project life cycle is apparent, yet the [...] Read more.
As the construction industry continues to evolve, energy consumption of buildings, particularly CO2 emissions, has become a critical focus for sustainable development. The need for effective design decisions regarding the selection of materials throughout the project life cycle is apparent, yet the link between specifications and CO2 emissions has not been set yet. This study presents a comprehensive life cycle assessment (LCA) of CO2 emissions across various Construction Specifications Institute (CSI) categories, aiming to identify the carbon footprint of different building systems and materials. The methodology focuses on using 3D building model case studies to evaluate the design decisions versus their impact on global warming potential (GWP). The results of this study emphasize that within CSI categories, concrete divisions consistently emerge as the predominant contributors to GWP, exceeding 75% in several instances. Following closely, metals contribute approximately 50% in multiple projects. The study also explores sustainable design options across CSI divisions to provide insights into building components contributing most to a building’s overall carbon footprint. This deeper understanding of sustainable design principles regarding CSI divisions and their impact on carbon footprint reduction will help sustainable designers and construction managers to implement carbon-conscious material choices and design strategies early in the planning phase. Full article
(This article belongs to the Special Issue Green Building: CO2 Emissions in the Construction Industry)
►▼ Show Figures

Figure 1

20 pages, 1084 KiB  
Article
A Class of Perimeter Defense Strategies Based on Priority Path Planning
by Shuang Zhang, Chengqian Yang, Shiwei Lin and Bomin Huang
Mathematics 2025, 13(15), 2420; https://doi.org/10.3390/math13152420 (registering DOI) - 27 Jul 2025
Abstract
This paper investigates perimeter defense strategies for multi-agent systems. Considering the complex scenario with multiple obstacles in the mission environment, a defense strategy based on prioritized path planning is proposed in this paper. The strategy employs a minimum weight matching method to solve [...] Read more.
This paper investigates perimeter defense strategies for multi-agent systems. Considering the complex scenario with multiple obstacles in the mission environment, a defense strategy based on prioritized path planning is proposed in this paper. The strategy employs a minimum weight matching method to solve the optimal task assignment for interception and determines the task priority based on the relative time window. Meanwhile, the swarm path planning is realized using particle swarm optimization with a designed cost function. Compared with the existing literature, the proposed method can handle large-scale agent-based perimeter defense while accounting for inter-defender collision avoidance and obstacle avoidance. The effectiveness of the strategy is verified through simulation in the mission scenario. Full article
14 pages, 2524 KiB  
Article
Precise Cruise Control for Fixed-Wing Aircraft Based on Proximal Policy Optimization with Nonlinear Attitude Constraints
by Haotian Wu, Yan Guo, Juliang Cao, Zhiming Xiong and Junda Chen
Aerospace 2025, 12(8), 670; https://doi.org/10.3390/aerospace12080670 (registering DOI) - 27 Jul 2025
Abstract
In response to the issues of severe pitch oscillation and unstable roll attitude present in existing reinforcement learning-based aircraft cruise control methods during dynamic maneuvers, this paper proposes a precise control method for aircraft cruising based on proximal policy optimization (PPO) with nonlinear [...] Read more.
In response to the issues of severe pitch oscillation and unstable roll attitude present in existing reinforcement learning-based aircraft cruise control methods during dynamic maneuvers, this paper proposes a precise control method for aircraft cruising based on proximal policy optimization (PPO) with nonlinear attitude constraints. This method first introduces a combination of long short-term memory (LSTM) and a fully connected layer (FC) to form the policy network of the PPO method, improving the algorithm’s learning efficiency for sequential data while avoiding feature compression. Secondly, it transforms cruise control into tracking target heading, altitude, and speed, achieving a mapping from motion states to optimal control actions within the policy network, and designs nonlinear constraints as the maximum reward intervals for pitch and roll to mitigate abnormal attitudes during maneuvers. Finally, a JSBSim simulation platform is established to train the network parameters, obtaining the optimal strategy for cruise control and achieving precise end-to-end control of the aircraft. Experimental results show that, compared to the cruise control method without dynamic constraints, the improved method reduces heading deviation by approximately 1.6° during ascent and 4.4° during descent, provides smoother pitch control, decreases steady-state altitude error by more than 1.5 m, and achieves higher accuracy in overlapping with the target trajectory during hexagonal trajectory tracking. Full article
(This article belongs to the Section Aeronautics)
16 pages, 2370 KiB  
Article
SemABC: Semantic-Guided Adaptive Bias Calibration for Generative Zero-Shot Point Cloud Segmentation
by Yuyun Wei and Meng Qi
Appl. Sci. 2025, 15(15), 8359; https://doi.org/10.3390/app15158359 (registering DOI) - 27 Jul 2025
Abstract
Due to the limited quantity and high cost of high-quality three-dimensional annotations, generalized zero-shot point cloud segmentation aims to transfer the knowledge of seen to unseen classes by leveraging semantic correlations to achieve generalization purposes. Existing generative point cloud semantic segmentation approaches rely [...] Read more.
Due to the limited quantity and high cost of high-quality three-dimensional annotations, generalized zero-shot point cloud segmentation aims to transfer the knowledge of seen to unseen classes by leveraging semantic correlations to achieve generalization purposes. Existing generative point cloud semantic segmentation approaches rely on generators trained on seen classes to synthesize visual features for unseen classes in order to help the segmentation model gain the ability of generalization, but this often leads to a bias toward seen classes. To address this issue, we propose a semantic-guided adaptive bias calibration approach with a dual-branch network architecture. This network consists of a novel visual–semantic fusion branch alongside the primary segmentation branch to suppress the bias toward seen classes. Specifically, the visual–semantic branch exploits the visual–semantic relevance of the synthetic features of unseen classes to provide auxiliary predictions. Furthermore, we introduce an adaptive bias calibration module that dynamically integrates the predictions from both the main and auxiliary branches to achieve unbiased segmentation results. Extensive experiments conducted on standard benchmarks demonstrate that our approach significantly outperforms state-of-the-art methods on both seen and unseen classes, thereby validating the effectiveness of our approach. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Industrial Engineering)
►▼ Show Figures

Figure 1

25 pages, 8335 KiB  
Article
Integrative In Silico and In Vivo Analysis of Banhasasim-Tang for Irritable Bowel Syndrome: Mechanistic Insights into Inflammation-Related Pathways
by Woo-Gyun Choi, Seok-Jae Ko, Jung-Ha Shim, Chang-Hwan Bae, Seungtae Kim, Jae-Woo Park and Byung-Joo Kim
Pharmaceuticals 2025, 18(8), 1123; https://doi.org/10.3390/ph18081123 (registering DOI) - 27 Jul 2025
Abstract
Background/Objectives: Banhasasim-tang (BHSST) is a traditional herbal formula commonly used to treat gastrointestinal (GI) disorders and has been considered a potential therapeutic option for irritable bowel syndrome (IBS). This study aimed to explore the molecular targets and underlying mechanisms of BHSST in IBS [...] Read more.
Background/Objectives: Banhasasim-tang (BHSST) is a traditional herbal formula commonly used to treat gastrointestinal (GI) disorders and has been considered a potential therapeutic option for irritable bowel syndrome (IBS). This study aimed to explore the molecular targets and underlying mechanisms of BHSST in IBS using a combination of network pharmacology, molecular docking, molecular dynamics simulations, and in vivo validation. Methods: Active compounds in BHSST were screened based on drug-likeness and oral bioavailability. Potential targets were predicted using ChEMBL, and IBS-related targets were obtained from GeneCards and DisGeNET. A compound–target–disease network was constructed and analyzed via Gene Ontology and KEGG pathway enrichment. Compound–target interactions were further assessed using molecular docking and molecular dynamics simulations. The in vivo effects of eudesm-4(14)-en-11-ol, elemol, and BHSST were evaluated in a zymosan-induced IBS mouse model. Results: Twelve BHSST-related targets were associated with IBS, with enrichment analysis identifying TNF signaling and apoptosis as key pathways. In silico simulations suggested stable binding of eudesm-4(14)-en-11-ol to TNF-α and kanzonol T to PIK3CD, whereas elemol showed weak interaction with PRKCD. In vivo, eudesm-4(14)-en-11-ol improved colon length, weight, stool consistency, TNF-α levels, and pain-related behaviors—effects comparable to those of BHSST. Elemol, however, showed no therapeutic benefit. Conclusions: These findings provide preliminary mechanistic insight into the anti-inflammatory potential of BHSST in IBS. The integrated in silico and in vivo approaches support the contribution of specific components, such as eudesm-4(14)-en-11-ol, to its observed effects, warranting further investigation. Full article
(This article belongs to the Special Issue Network Pharmacology of Natural Products, 2nd Edition)
►▼ Show Figures

Figure 1

18 pages, 4456 KiB  
Article
Study on the Filling and Plugging Mechanism of Oil-Soluble Resin Particles on Channeling Cracks Based on Rapid Filtration Mechanism
by Bangyan Xiao, Jianxin Liu, Feng Xu, Liqin Fu, Xuehao Li, Xianhao Yi, Chunyu Gao and Kefan Qian
Processes 2025, 13(8), 2383; https://doi.org/10.3390/pr13082383 (registering DOI) - 27 Jul 2025
Abstract
Channeling in cementing causes interlayer interference, severely restricting oilfield recovery. Existing channeling plugging agents, such as cement and gels, often lead to reservoir damage or insufficient strength. Oil-soluble resin (OSR) particles show great potential in selective plugging of channeling fractures due to their [...] Read more.
Channeling in cementing causes interlayer interference, severely restricting oilfield recovery. Existing channeling plugging agents, such as cement and gels, often lead to reservoir damage or insufficient strength. Oil-soluble resin (OSR) particles show great potential in selective plugging of channeling fractures due to their excellent oil solubility, temperature/salt resistance, and high strength. However, their application is limited by the efficient filling and retention in deep fractures. This study innovatively combines the OSR particle plugging system with the mature rapid filtration loss plugging mechanism in drilling, systematically exploring the influence of particle size and sorting on their filtration, packing behavior, and plugging performance in channeling fractures. Through API filtration tests, visual fracture models, and high-temperature/high-pressure (100 °C, salinity 3.0 × 105 mg/L) core flow experiments, it was found that well-sorted large particles preferentially bridge in fractures to form a high-porosity filter cake, enabling rapid water filtration from the resin plugging agent. This promotes efficient accumulation of OSR particles to form a long filter cake slug with a water content <20% while minimizing the invasion of fine particles into matrix pores. The slug thermally coalesces and solidifies into an integral body at reservoir temperature, achieving a plugging strength of 5–6 MPa for fractures. In contrast, poorly sorted particles or undersized particles form filter cakes with low porosity, resulting in slow water filtration, high water content (>50%) in the filter cake, insufficient fracture filling, and significantly reduced plugging strength (<1 MPa). Finally, a double-slug strategy is adopted: small-sized OSR for temporary plugging of the oil layer injection face combined with well-sorted large-sized OSR for main plugging of channeling fractures. This strategy achieves fluid diversion under low injection pressure (0.9 MPa), effectively protects reservoir permeability (recovery rate > 95% after backflow), and establishes high-strength selective plugging. This study clarifies the core role of particle size and sorting in regulating the OSR plugging effect based on rapid filtration loss, providing key insights for developing low-damage, high-performance channeling plugging agents and scientific gradation of particle-based plugging agents. Full article
(This article belongs to the Section Chemical Processes and Systems)
►▼ Show Figures

Figure 1

22 pages, 6926 KiB  
Article
Exploring Heavy Metals Exposure in Urban Green Zones of Thessaloniki (Northern Greece): Risks to Soil and People’s Health
by Ioannis Papadopoulos, Evangelia E. Golia, Ourania-Despoina Kantzou, Sotiria G. Papadimou and Anna Bourliva
Toxics 2025, 13(8), 632; https://doi.org/10.3390/toxics13080632 (registering DOI) - 27 Jul 2025
Abstract
This study investigates the heavy metal contamination in urban and peri-urban soils of Thessaloniki, Greece, over a two-year period (2023–2024). A total of 208 composite soil samples were systematically collected from 52 sites representing diverse land uses, including high-traffic roadsides, industrial zones, residential [...] Read more.
This study investigates the heavy metal contamination in urban and peri-urban soils of Thessaloniki, Greece, over a two-year period (2023–2024). A total of 208 composite soil samples were systematically collected from 52 sites representing diverse land uses, including high-traffic roadsides, industrial zones, residential neighborhoods, parks, and mixed-use areas, with sampling conducted both after the wet (winter) and dry (summer) seasons. Soil physicochemical properties (pH, electrical conductivity, texture, organic matter, and calcium carbonate content) were analyzed alongside the concentrations of heavy metals such as Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn. A pollution assessment employed the Geoaccumulation Index (Igeo), Contamination Factor (Cf), Pollution Load Index (PLI), and Potential Ecological Risk Index (RI), revealing variable contamination levels across the city, with certain hotspots exhibiting a considerable to very high ecological risk. Multivariate statistical analyses (PCA and HCA) identified distinct anthropogenic and geogenic sources of heavy metals. Health risk assessments, based on USEPA models, evaluated non-carcinogenic and carcinogenic risks for both adults and children via ingestion and dermal contact pathways. The results indicate that while most sites present low to moderate health risks, specific locations, particularly near major transport and industrial areas, pose elevated risks, especially for children. The findings underscore the need for targeted monitoring and remediation strategies to mitigate the ecological and human health risks associated with urban soil pollution in Thessaloniki. Full article
(This article belongs to the Special Issue Distribution and Behavior of Trace Metals in the Environment)
►▼ Show Figures

Figure 1

26 pages, 3121 KiB  
Article
Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion
by Siming Deng, Jiale Zhu, Yang Hu, Mingfang He and Yonglin Xia
Plants 2025, 14(15), 2329; https://doi.org/10.3390/plants14152329 (registering DOI) - 27 Jul 2025
Abstract
Precisely recognizing diseases in tomato leaves plays a crucial role in enhancing the health, productivity, and quality of tomato crops. However, disease identification methods that rely on single-mode information often face the problems of insufficient accuracy and weak generalization ability. Therefore, this paper [...] Read more.
Precisely recognizing diseases in tomato leaves plays a crucial role in enhancing the health, productivity, and quality of tomato crops. However, disease identification methods that rely on single-mode information often face the problems of insufficient accuracy and weak generalization ability. Therefore, this paper proposes a tomato leaf disease recognition framework FCMNet based on multimodal fusion, which combines tomato leaf disease image and text description to enhance the ability to capture disease characteristics. In this paper, the Fourier-guided Attention Mechanism (FGAM) is designed, which systematically embeds the Fourier frequency-domain information into the spatial-channel attention structure for the first time, enhances the stability and noise resistance of feature expression through spectral transform, and realizes more accurate lesion location by means of multi-scale fusion of local and global features. In order to realize the deep semantic interaction between image and text modality, a Cross Vision–Language Alignment module (CVLA) is further proposed. This module generates visual representations compatible with Bert embeddings by utilizing block segmentation and feature mapping techniques. Additionally, it incorporates a probability-based weighting mechanism to achieve enhanced multimodal fusion, significantly strengthening the model’s comprehension of semantic relationships across different modalities. Furthermore, to enhance both training efficiency and parameter optimization capabilities of the model, we introduce a Multi-strategy Improved Coati Optimization Algorithm (MSCOA). This algorithm integrates Good Point Set initialization with a Golden Sine search strategy, thereby boosting global exploration, accelerating convergence, and effectively preventing entrapment in local optima. Consequently, it exhibits robust adaptability and stable performance within high-dimensional search spaces. The experimental results show that the FCMNet model has increased the accuracy and precision by 2.61% and 2.85%, respectively, compared with the baseline model on the self-built dataset of tomato leaf diseases, and the recall and F1 score have increased by 3.03% and 3.06%, respectively, which is significantly superior to the existing methods. This research provides a new solution for the identification of tomato leaf diseases and has broad potential for agricultural applications. Full article
(This article belongs to the Special Issue Advances in Artificial Intelligence for Plant Research)
►▼ Show Figures

Figure 1

29 pages, 8251 KiB  
Article
Research on the Diaphragm Movement Characteristics and Cavity Profile Optimization of a Dual-Stage Diaphragm Compressor for Hydrogen Refueling Applications
by Chongzhou Sun, Zhilong He, Dantong Li, Xiaoqian Chen, Jie Tang, Manguo Yan and Xiangjie Kang
Appl. Sci. 2025, 15(15), 8353; https://doi.org/10.3390/app15158353 (registering DOI) - 27 Jul 2025
Abstract
The large-scale utilization of hydrogen energy is currently hindered by challenges in low-cost production, storage, and transportation. This study focused on investigating the impact of the diaphragm cavity profile on the movement behavior and stress distribution of a dual-stage diaphragm compressor. Firstly, an [...] Read more.
The large-scale utilization of hydrogen energy is currently hindered by challenges in low-cost production, storage, and transportation. This study focused on investigating the impact of the diaphragm cavity profile on the movement behavior and stress distribution of a dual-stage diaphragm compressor. Firstly, an experimental platform was established to test the gas mass flowrate and fluid pressures under various preset conditions. Secondly, a simulation path integrating the finite element method simulation, theoretical stress model, and movement model was developed and experimentally validated to analyze the diaphragm stress distribution and deformation characteristics. Finally, comparative optimization analyses were conducted on different types of diaphragm cavity profiles. The results indicated that the driving pressure differences at the top dead center position reached 85.58 kPa for the first-stage diaphragm and 75.49 kPa for the second-stage diaphragm. Under experimental conditions of 1.6 MPa suction pressure, 8 MPa second-stage discharge pressure, and 200 rpm rotational speed, the first-stage and second-stage diaphragms reached the maximum center deflections of 4.14 mm and 2.53 mm, respectively, at the bottom dead center position. Moreover, the cavity profile optimization analysis indicated that the double-arc profile (DAP) achieved better cavity volume and diaphragm stress characteristics. The first-stage diaphragm within the optimized DAP-type cavity exhibited 173.95 MPa maximum principal stress with a swept volume of 0.001129 m3, whereas the second-stage optimized configuration reached 172.57 MPa stress with a swept volume of 0.0003835 m3. This research offers valuable insights for enhancing the reliability and performance of diaphragm compressors. Full article
(This article belongs to the Section Mechanical Engineering)
►▼ Show Figures

Figure 1

25 pages, 1797 KiB  
Article
Zoning of “Protected Designation of Origin La Mancha Saffron” According to the Quality of the Flower
by Jorge F. Escobar-Talavera, María Esther Martínez-Navarro, Sandra Bravo, Gonzalo L. Alonso and Rosario Sánchez-Gómez
Agronomy 2025, 15(8), 1819; https://doi.org/10.3390/agronomy15081819 (registering DOI) - 27 Jul 2025
Abstract
The quality of Crocus sativus L. flowers, beyond their stigmas, is influenced by the presence of bioactive metabolites also in their floral bio-residues. Given the effect of climatic and soil variables on these bioactive compounds, the aim of this research was to develop [...] Read more.
The quality of Crocus sativus L. flowers, beyond their stigmas, is influenced by the presence of bioactive metabolites also in their floral bio-residues. Given the effect of climatic and soil variables on these bioactive compounds, the aim of this research was to develop an agroecological zoning of saffron crop areas within the Protected Designation of Origin (PDO) La Mancha region (Castilla-La Mancha, Spain) by integrating the floral metabolite content with climatic and soil variables. To achieve this, a total of 173 samples were collected during the 2022 and 2023 harvests and analyzed via RP-HPLC-DAD to determine crocins, picrocrocin, kaempferols, and anthocyanins. Two new indices, Cropi (crocins + picrocrocin) and Kaeman (kaempferols + anthocyanins), were defined to classify flowers into four quality categories (A–D). High-quality classifications (A and B) were consistently associated with plots grouped in the meteorological stations of Ontur, El Sanchón, and Bolaños, indicating favorable edaphoclimatic conditions and climatic parameters, such as moderate temperatures and reduced humidity, for metabolite biosynthesis. In contrast, plots included in the meteorological stations of Tarazona and Pedernoso were mostly assigned to lower categories (C and D). Spatial analysis using thematic maps revealed that areas with an intermediate carbonate content, less calcareous soils, and higher organic matter levels were linked to higher flower quality. These findings highlight the influence of soil characteristics and climate, with distinct seasonal contrasts, that positively influence metabolite synthesis and flower quality. Full article
(This article belongs to the Special Issue Agricultural Aspects of Medicinal, Aromatic and Spice Plants' Cultivation, Harvest, Processing and Conservation)
40 pages, 3124 KiB  
Review
Structural Diversity and Bioactivities of Marine Fungal Terpenoids (2020–2024)
by Minghua Jiang, Senhua Chen, Zhibin Zhang, Yiwen Xiao, Du Zhu and Lan Liu
Mar. Drugs 2025, 23(8), 300; https://doi.org/10.3390/md23080300 (registering DOI) - 27 Jul 2025
Abstract
Marine-derived fungi have proven to be a rich source of structurally diverse terpenoids with significant pharmacological potential. This systematic review of 119 studies (2020–2024) identifies 512 novel terpenoids, accounting for 87% of the total discoveries to 2020, from five major classes (monoterpenes, sesquiterpenes, [...] Read more.
Marine-derived fungi have proven to be a rich source of structurally diverse terpenoids with significant pharmacological potential. This systematic review of 119 studies (2020–2024) identifies 512 novel terpenoids, accounting for 87% of the total discoveries to 2020, from five major classes (monoterpenes, sesquiterpenes, diterpenes, sesterterpenes, and triterpenes) isolated from 104 fungal strains across 33 genera. Sesquiterpenoids and diterpenoids constitute the predominant chemical classes, with Trichoderma, Aspergillus, Eutypella, and Penicillium being the most productive genera. These fungi were primarily sourced from distinct marine niches, including deep sea sediments, algal associations, mangrove ecosystems, and invertebrate symbioses. Notably, 57% of the 266 tested compounds exhibited diverse biological activities, encompassing anti-inflammatory, antibacterial, antimicroalgal, antifungal, cytotoxic effects, etc. The chemical diversity and biological activities of these marine fungal terpenoids underscore their value as promising lead compounds for pharmaceutical development. Full article
(This article belongs to the Special Issue Diversity of Marine Fungi as a Source of Bioactive Natural Products, 3rd Edition)
►▼ Show Figures

Figure 1

20 pages, 4727 KiB  
Article
Developing a Novel Fermented Milk with Anti-Aging and Anti-Oxidative Properties Using Lactobacillus kefiranofaciens HL1 and Lactococcus lactis APL015
by Sheng-Yao Wang, Wei-Chen Yen, Yen-Po Chen, Jia-Shian Shiu and Ming-Ju Chen
Nutrients 2025, 17(15), 2447; https://doi.org/10.3390/nu17152447 (registering DOI) - 27 Jul 2025
Abstract
Background/Objectives: Lactobacillus kefiranofaciens HL1, isolated from kefir, exhibits antioxidant and anti-aging activities, defined here as improved cognitive function and reductions in oxidative stress and inflammatory markers. However, its poor milk viability limits application. This study developed a novel fermented milk by co-culturing [...] Read more.
Background/Objectives: Lactobacillus kefiranofaciens HL1, isolated from kefir, exhibits antioxidant and anti-aging activities, defined here as improved cognitive function and reductions in oxidative stress and inflammatory markers. However, its poor milk viability limits application. This study developed a novel fermented milk by co-culturing HL1 with Lactococcus lactis subsp. cremoris APL015 (APL15) to enhance fermentation and health benefits. Methods: HL1 and APL15 were co-cultured to produce fermented milk (FM), and fermentation performance, microbial viability, texture, and syneresis were evaluated. A D-galactose-induced aging BALB/c mouse model was used to assess cognitive function, oxidative stress, inflammation, antioxidant enzyme activity, and gut microbiota after 8 weeks of oral administration. Results: FM reached pH 4.6 within 16 h, with high viable counts (~109 CFU/mL) for both strains. HL1 viability and texture were maintained, with smooth consistency and low syneresis. In vivo, FM improved cognitive behavior (Y-maze, Morris water maze), reduced oxidative damage (MDA), lowered IL-1β and TNF-α, and enhanced brain SOD levels. FM-fed mice exhibited increased short-chain fatty acid producers, higher cecal butyrate, and reduced Clostridium perfringens. Conclusions: The co-cultured fermented milk effectively delivers HL1 and provides antioxidant, anti-inflammatory, and anti-aging effects in vivo, likely via gut–brain axis modulation. It shows promise as a functional food for healthy aging. Full article
(This article belongs to the Section Prebiotics and Probiotics)
►▼ Show Figures

Figure 1

23 pages, 7095 KiB  
Article
Development of a Dual-Input Hybrid Wave–Current Ocean Energy System: Design, Fabrication, and Performance Evaluation
by Farooq Saeed, Tanvir M. Sayeed, Mohammed Abdul Hannan, Abdullah A. Baslamah, Aedh M. Alhassan, Turki K. Alarawi, Osama A. Alsaadi, Muhanad Y. Alharees and Sultan A. Alshehri
J. Mar. Sci. Eng. 2025, 13(8), 1435; https://doi.org/10.3390/jmse13081435 (registering DOI) - 27 Jul 2025
Abstract
This study presents the design, fabrication, and performance assessment of a novel, small-scale (30–70 W), hybrid ocean energy system that captures energy from wave-induced heave motion using a point-absorber buoy and from ocean currents via a vertical axis water turbine (VAWT). Key innovations [...] Read more.
This study presents the design, fabrication, and performance assessment of a novel, small-scale (30–70 W), hybrid ocean energy system that captures energy from wave-induced heave motion using a point-absorber buoy and from ocean currents via a vertical axis water turbine (VAWT). Key innovations include a custom designed and built dual-rotor generator that accepts independent mechanical input from both subsystems without requiring complex mechanical coupling and a bi-directional mechanical motion rectifier with an overdrive. Numerical simulations using ANSYS AQWA (2024R2) and QBLADE(2.0.4) guided the design optimization of the buoy and turbine, respectively. Wave resource assessment for the Khobar coastline, Saudi Arabia, was conducted using both historical data and field measurements. The prototype was designed and built using readily available 3D-printed components, ensuring cost-effective construction. This mechanically simple system was tested in both laboratory and outdoor conditions. Results showed reliable operation and stable power generation under simultaneous wave and current input. The performance is comparable to that of existing hybrid ocean wave–current energy converters that employ more complex flywheel or dual degree-of-freedom systems. This work provides a validated pathway for low-cost, compact, and modular hybrid ocean energy systems suited for remote coastal applications or distributed marine sensing platforms. Full article
(This article belongs to the Section Marine Energy)
►▼ Show Figures

Figure 1

18 pages, 1022 KiB  
Article
A Novel Variable Stiffness Torque Sensor with Adjustable Resolution
by Zhongyuan Mao, Yuanchang Zhong, Xuehui Zhao, Tengfei He and Sike Duan
Micromachines 2025, 16(8), 868; https://doi.org/10.3390/mi16080868 (registering DOI) - 27 Jul 2025
Abstract
In rotating machinery, the demands for torque sensor resolution and range in various torque measurements are becoming increasingly stringent. This paper presents a novel variable stiffness torque sensor designed to meet the demands for high resolution or a large range under varying measurement [...] Read more.
In rotating machinery, the demands for torque sensor resolution and range in various torque measurements are becoming increasingly stringent. This paper presents a novel variable stiffness torque sensor designed to meet the demands for high resolution or a large range under varying measurement conditions. Unlike traditional strain gauge-based torque sensors, this sensor combines the advantages of torsion springs and magnetorheological fluid (MRF) to achieve dynamic adjustments in both resolution and range. Specifically, the stiffness of the elastic element is adjusted by altering the shear stress of the MRF via an applied magnetic field while simultaneously harnessing the high sensitivity of the torsion spring. The stiffness model is established and validated for accuracy through finite element analysis. A screw modulation-based angle measurement method is proposed for the first time, offering high non-contact angle measurement accuracy and resolving eccentricity issues. The performance of the sensor prototype is evaluated using a self-developed power-closed torque test bench. The experimental results demonstrate that the sensor exhibits excellent linearity, hysteresis, and repeatability while effectively achieving dynamic continuous adjustment of resolution and range. Full article
17 pages, 1525 KiB  
Article
Clonidine Protects Endothelial Cells from Angiotensin II-Induced Injury via Anti-Inflammatory and Antioxidant Mechanisms
by Bekir Sıtkı Said Ulusoy, Mehmet Cudi Tuncer and İlhan Özdemir
Life 2025, 15(8), 1193; https://doi.org/10.3390/life15081193 (registering DOI) - 27 Jul 2025
Abstract
Background: Cerebral aneurysm (CA) is a focal or diffuse pathological dilation of the cerebral arterial wall that arises due to various etiological factors. It represents a serious vascular condition, particularly affecting the elderly, and carries a high risk of rupture and neurological morbidity. [...] Read more.
Background: Cerebral aneurysm (CA) is a focal or diffuse pathological dilation of the cerebral arterial wall that arises due to various etiological factors. It represents a serious vascular condition, particularly affecting the elderly, and carries a high risk of rupture and neurological morbidity. Clonidine (CL), an α2-adrenergic receptor agonist, has been reported to suppress aneurysm progression; however, its underlying molecular mechanisms, especially in relation to cerebral endothelial dysfunction, remain unclear. This study aimed to investigate the potential of CL to mitigate CA development by modulating apoptosis, inflammation, and oxidative stress in an Angiotensin II (Ang II)-induced endothelial injury model. Methods: Human brain microvascular endothelial cells (HBMECs) were used to establish an in vitro model of endothelial dysfunction by treating cells with 1 µM Ang II for 48 h. CL was administered 2 h prior to Ang II exposure at concentrations of 0.1, 1, and 10 µM. Cell viability was assessed using the MTT assay. Oxidative stress markers, including reactive oxygen species (ROS) and Nitric Oxide (NO), were measured using 2′,7′–dichlorofluorescin diacetate (DCFDA). Gene expression levels of vascular endothelial growth factor (VEGF), matrix metalloproteinases (MMP-2 and MMP-9), high mobility group box 1 (HMGB1), and nuclear factor kappa B (NF-κB) were quantified using RT-qPCR. Levels of proinflammatory cytokines; tumor necrosis factor-alpha (TNF-α), Interleukin-6 (IL-6), and interferon-gamma (IFN-γ); were measured using commercial ELISA kits. Results: Ang II significantly increased ROS production and reduced NO levels, accompanied by heightened proinflammatory cytokine release and endothelial dysfunction. MTT assay revealed a marked decrease in cell viability following Ang II treatment (34.18%), whereas CL preserved cell viability in a concentration-dependent manner: 44.24% at 0.1 µM, 66.56% at 1 µM, and 81.74% at 10 µM. CL treatment also significantly attenuated ROS generation and inflammatory cytokine levels (p < 0.05). Furthermore, the expression of VEGF, HMGB1, NF-κB, MMP-2, and MMP-9 was significantly downregulated in response to CL. Conclusions: CL exerts a protective effect on endothelial cells by reducing oxidative stress and suppressing proinflammatory signaling pathways in Ang II-induced injury. These results support the potential of CL to mitigate endothelial injury in vitro, though further in vivo studies are required to confirm its translational relevance. Full article
(This article belongs to the Section Pharmaceutical Science)
►▼ Show Figures

Figure 1

25 pages, 4296 KiB  
Article
StripSurface-YOLO: An Enhanced Yolov8n-Based Framework for Detecting Surface Defects on Strip Steel in Industrial Environments
by Haomin Li, Huanzun Zhang and Wenke Zang
Electronics 2025, 14(15), 2994; https://doi.org/10.3390/electronics14152994 (registering DOI) - 27 Jul 2025
Abstract
Recent advances in precision manufacturing and high-end equipment technologies have imposed ever more stringent requirements on the accuracy, real-time performance, and lightweight design of online steel strip surface defect detection systems. To reconcile the persistent trade-off between detection precision and inference efficiency in [...] Read more.
Recent advances in precision manufacturing and high-end equipment technologies have imposed ever more stringent requirements on the accuracy, real-time performance, and lightweight design of online steel strip surface defect detection systems. To reconcile the persistent trade-off between detection precision and inference efficiency in complex industrial environments, this study proposes StripSurface–YOLO, a novel real-time defect detection framework built upon YOLOv8n. The core architecture integrates an Efficient Cross-Stage Local Perception module (ResGSCSP), which synergistically combines GSConv lightweight convolutions with a one-shot aggregation strategy, thereby markedly reducing both model parameters and computational complexity. To further enhance multi-scale feature representation, this study introduces an Efficient Multi-Scale Attention (EMA) mechanism at the feature-fusion stage, enabling the network to more effectively attend to critical defect regions. Moreover, conventional nearest-neighbor upsampling is replaced by DySample, which produces deeper, high-resolution feature maps enriched with semantic content, improving both inference speed and fusion quality. To heighten sensitivity to small-scale and low-contrast defects, the model adopts Focal Loss, dynamically adjusting to sample difficulty. Extensive evaluations on the NEU-DET dataset demonstrate that StripSurface–YOLO reduces FLOPs by 11.6% and parameter count by 7.4% relative to the baseline YOLOv8n, while achieving respective improvements of 1.4%, 3.1%, 4.1%, and 3.0% in precision, recall, mAP50, and mAP50:95. Under adverse conditions—including contrast variations, brightness fluctuations, and Gaussian noise—SteelSurface-YOLO outperforms the baseline model, delivering improvements of 5.0% in mAP50 and 4.7% in mAP50:95, attesting to the model’s robust interference resistance. These findings underscore the potential of StripSurface–YOLO to meet the rigorous performance demands of real-time surface defect detection in the metal forging industry. Full article
►▼ Show Figures

Figure 1

12 pages, 277 KiB  
Article
Risk Factors for Latent Tuberculosis Identified Using Epidemiological Investigation in Congregate Settings of Gyeongsan City, Republic of Korea (2014–2023)
by Seonyeong Park and Kwan Lee
Pathogens 2025, 14(8), 740; https://doi.org/10.3390/pathogens14080740 (registering DOI) - 27 Jul 2025
Abstract
Latent tuberculosis infection (LTBI) remains an important public health issue, as individuals can harbor Mycobacterium tuberculosis without symptoms and later develop active disease. This study aimed to assess the prevalence and risk factors associated with LTBI positivity among tuberculosis (TB) contacts in congregate [...] Read more.
Latent tuberculosis infection (LTBI) remains an important public health issue, as individuals can harbor Mycobacterium tuberculosis without symptoms and later develop active disease. This study aimed to assess the prevalence and risk factors associated with LTBI positivity among tuberculosis (TB) contacts in congregate settings in Gyeongsan City, the Republic of Korea (ROK), from 2014 to 2023. A total of 213 index cases and 3666 contacts were analyzed using data from the Korea Tuberculosis Infection Control System (KTB-NET). Overall, 20.7% of contacts tested positive for LTBI, with the highest rates observed among contacts aged ≥65 years (50.4%) and in healthcare facilities (34.8%). Binary logistic regression analyses revealed that age ≥65 years (OR: 2.93; 95% CI: 1.95–4.39; p < 0.001), social welfare facilities (OR: 2.75; 95% CI: 2.10–3.58; p < 0.001), workplaces (OR: 2.42; 95% CI: 1.88–3.10; p < 0.001), and healthcare facilities (OR: 3.42; 95% CI: 2.63–4.43; p < 0.001) were significantly associated with increased LTBI risk. These findings highlight the importance of targeted interventions and prevention strategies focused on older adults and high-risk groups to prevent future TB outbreaks by reducing the burden of LTBI. Full article
(This article belongs to the Special Issue Feature Papers on the Epidemiology of Infectious Diseases)
►▼ Show Figures

Figure 1

18 pages, 1636 KiB  
Article
Green Synthesis of Copper Oxide Nanoparticles Using Camellia sinensis: Anticancer Potential and Apoptotic Mechanism in HT-29 and MCF-7 Cells
by Devanthiran Letchumanan, Suriani Ibrahim, Noor Hasima Nagoor and Norhafiza Mohd Arshad
Int. J. Mol. Sci. 2025, 26(15), 7267; https://doi.org/10.3390/ijms26157267 (registering DOI) - 27 Jul 2025
Abstract
The increasing prevalence of cancer necessitates the development of novel and effective therapeutic agents. This study evaluates the anticancer potential of biosynthesized copper oxide nanoparticles (CuO NPs) using Camellia sinensis extract against human colon and breast cancer cells. The CuO NPs were characterized [...] Read more.
The increasing prevalence of cancer necessitates the development of novel and effective therapeutic agents. This study evaluates the anticancer potential of biosynthesized copper oxide nanoparticles (CuO NPs) using Camellia sinensis extract against human colon and breast cancer cells. The CuO NPs were characterized using various techniques to confirm their structure, size, morphology, and functional groups. The average size of CuO NPs synthesized was 20–60 nm, with spherical shape. The cytotoxic effects of these CuO NPs reveal a dose-dependent reduction in cell viability with 50% inhibitory concentration (IC50) at 58.53 ± 0.13 and 53.95 ± 1.1 μg/mL, respectively. Further investigation into the mechanism of action was conducted using flow cytometry and apoptosis assays, which indicated that CuO NPs induced cell cycle arrest and apoptosis in cancer cells. Reactive oxygen species (ROS) generation, caspase activity assay, and comet assay were also performed to elucidate the underlying pathways, suggesting that oxidative stress and DNA damage play pivotal roles in the cytotoxicity observed. Overall, our findings demonstrate that biosynthesized CuO NPs exhibit notable anticancer activity against colon and breast cancer cells, with moderate selectivity over normal cells, highlighting their potential as a therapeutic agent due to their biocompatibility. However, further studies are required to validate their selectivity and safety profile. Full article
(This article belongs to the Special Issue The Application of Nanoparticles in Biomedicine)
27 pages, 42290 KiB  
Article
Study on the Dynamic Changes in Land Cover and Their Impact on Carbon Stocks in Karst Mountain Areas: A Case Study of Guiyang City
by Rui Li, Zhongfa Zhou, Jie Kong, Cui Wang, Yanbi Wang, Rukai Xie, Caixia Ding and Xinyue Zhang
Remote Sens. 2025, 17(15), 2608; https://doi.org/10.3390/rs17152608 (registering DOI) - 27 Jul 2025
Abstract
Investigating land cover patterns, changes in carbon stocks, and forecasting future conditions are essential for formulating regional sustainable development strategies and enhancing ecological and environmental quality. This study centers on Guiyang, a mountainous urban area in southwestern China, to analyze the dynamic changes [...] Read more.
Investigating land cover patterns, changes in carbon stocks, and forecasting future conditions are essential for formulating regional sustainable development strategies and enhancing ecological and environmental quality. This study centers on Guiyang, a mountainous urban area in southwestern China, to analyze the dynamic changes in land cover and their effects on carbon stocks from 2000 to 2035. A carbon stocks assessment framework was developed using a cellular automaton-based artificial neural network model (CA-ANN), the InVEST model, and the geographical detector model to predict future land cover changes and identify the primary drivers of variations in carbon stocks. The results indicate that (1) from 2000 to 2020, impervious surfaces expanded significantly, increasing by 199.73 km2. Compared to 2020, impervious surfaces are projected to increase by 1.06 km2, 13.54 km2, and 34.97 km2 in 2025, 2030, and 2035, respectively, leading to further reductions in grassland and forest areas. (2) Over time, carbon stocks in Guiyang exhibited a general decreasing trend; spatially, carbon stocks were higher in the western and northern regions and lower in the central and southern regions. (3) The level of greenness, measured by the normalized vegetation index (NDVI), significantly influenced the spatial variation of carbon stocks in Guiyang. Changes in carbon stocks resulted from the combined effects of multiple factors, with the annual average temperature and NDVI being the most influential. These findings provide a scientific basis for advancing low-carbon development and constructing an ecological civilization in Guiyang. Full article
(This article belongs to the Special Issue Smart Monitoring of Urban Environment Using Remote Sensing)
►▼ Show Figures

Figure 1

14 pages, 10838 KiB  
Article
Transcription Factor LjWRKY50 Affects Jasmonate-Regulated Floral Bud Duration in Lonicera japonica
by Yanfei Li, Yutong Gan, Guihong Qi, Wenjie Xu, Tianyi Xin, Yuanhao Huang, Lianguo Fu, Lijun Hao, Qian Lou, Xiao Fu, Xiangyun Wei, Lijun Liu, Chengming Liu and Jingyuan Song
Plants 2025, 14(15), 2328; https://doi.org/10.3390/plants14152328 (registering DOI) - 27 Jul 2025
Abstract
Lonicera japonica Thunb. is a traditional Chinese medicinal herb whose floral buds are the primary source of pharmacological compounds that require manual harvesting. As a result, its floral bud duration, determined by the opening time, is a key determinant of both quality and [...] Read more.
Lonicera japonica Thunb. is a traditional Chinese medicinal herb whose floral buds are the primary source of pharmacological compounds that require manual harvesting. As a result, its floral bud duration, determined by the opening time, is a key determinant of both quality and economic value. However, the genetic mechanisms controlling floral bud duration remain poorly understood. In this study, we employed population structure analysis and molecular experiments to identify candidate genes associated with this trait. The improved cultivar Beihua No. 1 (BH1) opens its floral buds significantly later than the landrace Damaohua (DMH). Exogenous application of methyl jasmonate (MeJA) to BH1 indicated that jasmonate acts as a negative regulator of floral bud duration by accelerating floral bud opening. A genome-wide selection scan across 35 germplasms with varying floral bud durations identified the transcription factor LjWRKY50 as the causative gene influencing this trait. The dual-luciferase reporter assay and qRT-PCR experiments showed that LjWRKY50 activates the expression of the jasmonate biosynthesis gene, LjAOS. A functional variant within LjWRKY50 (Chr7:24636061) was further developed into a derived cleaved amplified polymorphic sequence (dCAPS) marker. These findings provide valuable insights into the jasmonate-mediated regulation of floral bud duration, offering genetic and marker resources for molecular breeding in L. japonica. Full article
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
►▼ Show Figures

Figure 1

20 pages, 1676 KiB  
Article
Data-Driven Distributionally Robust Optimization for Solar-Powered EV Charging Under Spatiotemporal Uncertainty in Urban Distribution Networks
by Tianhao Wang, Xuejiao Zhang, Xiaolin Zheng, Jian Wang, Shiqian Ma, Jian Chen, Mengyu Liu and Wei Wei
Energies 2025, 18(15), 4001; https://doi.org/10.3390/en18154001 (registering DOI) - 27 Jul 2025
Abstract
The rapid electrification of transportation and the proliferation of rooftop solar photovoltaics (PVs) in urban environments are reshaping the operational dynamics of power distribution networks. However, the inherent uncertainty in electric vehicle (EV) behavior—including arrival times, charging preferences, and state-of-charge—as well as spatially [...] Read more.
The rapid electrification of transportation and the proliferation of rooftop solar photovoltaics (PVs) in urban environments are reshaping the operational dynamics of power distribution networks. However, the inherent uncertainty in electric vehicle (EV) behavior—including arrival times, charging preferences, and state-of-charge—as well as spatially and temporally variable solar generation, presents a profound challenge to existing scheduling frameworks. This paper proposes a novel data-driven distributionally robust optimization (DDRO) framework for solar-powered EV charging coordination under spatiotemporal uncertainty. Leveraging empirical datasets of EV usage and solar irradiance from a smart city deployment, the framework constructs Wasserstein ambiguity sets around historical distributions, enabling worst-case-aware decision-making without requiring the assumption of probability laws. The problem is formulated as a two-stage optimization model. The first stage determines day-ahead charging schedules, solar utilization levels, and grid allocations across an urban-scale distribution feeder. The second stage models real-time recourse actions—such as dynamic curtailment or demand reshaping—after uncertainties are realized. Physical grid constraints are modeled using convexified LinDistFlow equations, while EV behavior is segmented into user classes with individualized uncertainty structures. The model is evaluated on a modified IEEE 123-bus feeder with 52 EV-PV nodes, using 15 min resolution over a 24 h horizon and 12 months of real-world data. Comparative results demonstrate that the proposed DDRO method reduces total operational costs by up to 15%, eliminates voltage violations entirely, and improves EV service satisfaction by more than 30% relative to deterministic and stochastic baselines. This work makes three primary contributions: it introduces a robust, tractable optimization architecture that captures spatiotemporal uncertainty using empirical Wasserstein sets; it integrates behavioral and physical modeling within a unified dispatch framework for urban energy-mobility systems; and it demonstrates the value of robust coordination in simultaneously improving grid resilience, renewable utilization, and EV user satisfaction. The results offer practical insights for city-scale planners seeking to enable the reliable and efficient electrification of mobility infrastructure under uncertainty. Full article
(This article belongs to the Topic Intelligent, Flexible, and Effective Operation of Smart Grids with Novel Energy Technologies and Equipment)
►▼ Show Figures

Figure 1

19 pages, 1059 KiB  
Review
Shear Strength of Lightweight Concrete Structural Elements Reinforced with FRP Bars: Experimental Studies vs. Code Predictions
by Agnieszka Wiater and Tomasz Wojciech Siwowski
Materials 2025, 18(15), 3525; https://doi.org/10.3390/ma18153525 (registering DOI) - 27 Jul 2025
Abstract
Using lightweight concrete (LWC) reduces the dead weight of the concrete structure by 25–30% compared to ordinary concrete. However, harmful and corrosive substances penetrate the lightweight concrete matrix due to its high permeability, resulting in higher maintenance costs and a reduced structure service [...] Read more.
Using lightweight concrete (LWC) reduces the dead weight of the concrete structure by 25–30% compared to ordinary concrete. However, harmful and corrosive substances penetrate the lightweight concrete matrix due to its high permeability, resulting in higher maintenance costs and a reduced structure service life. Therefore, in harsh environments where conventional steel bars are susceptible to corrosion, fibre-reinforced polymer (FRP) bars should be used for reinforcement. However, there is a paucity of experimental studies regarding LWC structural elements reinforced with FRP bars. Shear strength is a critical limit state that typically determines the proper design of such elements, ensuring the required safety margin and an appropriate level of reliability. The research work was conducted to compare the experimentally determined shear strengths (Vexp) of 50 structural elements (beams, slabs) made of LWC/FRP with code predictions (Vcode) made according to eight codes used for design. Based on this comparison, the so-called conformity coefficient (Vexp/Vcode) was calculated and used to assess which provision documents are the best, considering the entire population of test results. The work demonstrated that the recent Eurocode best predicts the shear strength of LWC/FRP elements. Full article
(This article belongs to the Special Issue Computational and Experimental Methodologies for Advanced and Sustainable Structural Materials)
►▼ Show Figures

Figure 1

22 pages, 4495 KiB  
Article
Physiological and Transcriptomic Analyses Reveal Regulatory Mechanisms of Adventitious Root Formation in In Vitro Culture of Cinnamomum camphora
by Yuntong Zhang, Ting Zhang, Yongjie Zheng, Jun Wang, Chenglin Luo, Yuhua Li and Xinliang Liu
Int. J. Mol. Sci. 2025, 26(15), 7264; https://doi.org/10.3390/ijms26157264 (registering DOI) - 27 Jul 2025
Abstract
Cinnamomum camphora is an ecologically and economically significant species, highly valued for its essential oil production and environmental benefits. Although a tissue culture system has been established for C. camphora, large-scale propagation remains limited due to the inconsistent formation of adventitious roots [...] Read more.
Cinnamomum camphora is an ecologically and economically significant species, highly valued for its essential oil production and environmental benefits. Although a tissue culture system has been established for C. camphora, large-scale propagation remains limited due to the inconsistent formation of adventitious roots (ARs). This study investigated AR formation from callus tissue, focusing on associated physiological changes and gene expression dynamics. During AR induction, contents of soluble sugars and proteins decreased, alongside reduced activities of antioxidant enzymes, including superoxide dismutase (SOD), peroxidase (POD), and polyphenol oxidase (PPO). Levels of indole-3-acetic acid (IAA) and abscisic acid (ABA) decreased significantly throughout AR formation. Zeatin riboside (ZR) levels initially declined and then rose, whereas gibberellic acid (GA) levels displayed the opposite trend. Comparative transcriptomic and temporal expression analyses identified differentially expressed genes (DEGs), which were grouped into four distinct expression patterns. KEGG pathway enrichment indicated that 67 DEGs are involved in plant hormone signaling pathways and that 38 DEGs are involved in the starch and sucrose metabolism pathway. Additionally, protein–protein interaction network (PPI) analysis revealed ten key regulatory genes, which are mainly involved in auxin, cytokinin, GA, ABA, and ethylene signaling pathways. The reliability of the transcriptome data was further validated by quantitative real-time PCR. Overall, this study provides new insights into the physiological and molecular mechanisms underlying AR formation in C. camphora and offers valuable guidance for optimizing tissue culture systems. Full article
(This article belongs to the Special Issue Emerging Insights into Phytohormone Signaling in Plants)
►▼ Show Figures

Figure 1

31 pages, 8327 KiB  
Review
Performance of Asphalt Materials Based on Molecular Dynamics Simulation: A Review
by Chengwei Xing, Zhihang Xiong, Tong Lu, Haozongyang Li, Weichao Zhou and Chen Li
Polymers 2025, 17(15), 2051; https://doi.org/10.3390/polym17152051 (registering DOI) - 27 Jul 2025
Abstract
With the rising performance demands in road engineering, traditional experiments often fail to reveal the microscopic mechanisms behind asphalt behavior. Molecular dynamics (MD) simulation has emerged as a valuable complement, enabling molecular-level insights into asphalt’s composition, structure, and aging mechanisms. This review summarizes [...] Read more.
With the rising performance demands in road engineering, traditional experiments often fail to reveal the microscopic mechanisms behind asphalt behavior. Molecular dynamics (MD) simulation has emerged as a valuable complement, enabling molecular-level insights into asphalt’s composition, structure, and aging mechanisms. This review summarizes the recent advances in applying MD to asphalt research. It first outlines molecular model construction approaches, including average models, three- and four-component systems, and modified models incorporating SBS, SBR, PU, PE, and asphalt–aggregate interfaces. It then analyzes how MD reveals the key performance aspects—such as high-temperature stability, low-temperature flexibility, self-healing behavior, aging processes, and interfacial adhesion—by capturing the molecular interactions. While MD offers significant advantages, challenges remain: idealized modeling, high computational demands, limited chemical reaction simulation, and difficulties in multi-scale coupling. This paper aims to provide theoretical insights and methodological support for future studies on asphalt performance and highlights MD simulation as a promising tool in pavement material science. Full article
(This article belongs to the Section Polymer Applications)
►▼ Show Figures

Figure 1

20 pages, 1160 KiB  
Article
Analysis of the Limiting Values of Thermodynamic Parameters for Jouguet Detonation
by Andriy A. Avramenko, Igor V. Shevchuk, Margarita M. Kovetskaya, Yulia Y. Kovetska and Dmytro V. Anastasiev
Mathematics 2025, 13(15), 2419; https://doi.org/10.3390/math13152419 (registering DOI) - 27 Jul 2025
Abstract
An analytical study of the interaction of an ideal gas flow with a detonation wave was performed with account for the activation energy of chemical processes. Based on the modified Rankine-Hugoniot conditions, the effect of heat release on the limiting characteristics of detonation [...] Read more.
An analytical study of the interaction of an ideal gas flow with a detonation wave was performed with account for the activation energy of chemical processes. Based on the modified Rankine-Hugoniot conditions, the effect of heat release on the limiting characteristics of detonation was analyzed. A dependence of the limiting value of the exponent Arrhenius number on the Mach number before the shock wave has been obtained. As the Mach number increases, the limiting value of the Arrhenius number decreases. An equation has been derived for determining the limiting value of the compression ratio in the shock wave. The effect of heat release intensity on the limiting compression ratio in a shock wave was elucidated. Also studied were effects of the Mach number and the Arrhenius number on the limiting compression ratio in a detonation wave. A condition for determining the critical value of the Arrhenius number necessary for the onset of detonation was obtained. Effects of the Mach number and the exponent of the Arrhenius number ArE on the critical value of the amplitude Arrhenius number ArА were discussed. The symmetry analysis of the gas flow parameters when passing through a detonation wave was performed. Full article
(This article belongs to the Special Issue Computational Fluid Dynamics with Applications)
23 pages, 614 KiB  
Article
Air Pollution, Credit Ratings, and Corporate Credit Costs: Evidence from China
by Haoran Wang and Jincheng Wang
Sustainability 2025, 17(15), 6829; https://doi.org/10.3390/su17156829 (registering DOI) - 27 Jul 2025
Abstract
From the perspective of credit ratings, this paper studies the impact of air pollution on corporate credit costs and the impact mechanism. Based on 2007–2022 data on A-share listed companies in the Chinese capital market, this paper uses a two-way fixed effects model [...] Read more.
From the perspective of credit ratings, this paper studies the impact of air pollution on corporate credit costs and the impact mechanism. Based on 2007–2022 data on A-share listed companies in the Chinese capital market, this paper uses a two-way fixed effects model to examine the impact of air pollution on corporate credit costs and the impact mechanism. The results show that air pollution increases the credit costs for enterprises because air pollution affects the sentiment of rating analysts, leading them to give more pessimistic credit ratings to enterprises located in areas with severe air pollution. The moderating effect analysis reveals that the effect of air pollution on the increase in corporate credit costs is more pronounced for high-polluting industries, manufacturing industries, and regions with weaker bank competition. Further analysis reveals that in the face of rising credit costs caused by air pollution, enterprises tend to adopt a combination strategy of increasing commercial credit financing and reducing the commercial credit supply to cope. Although this response behavior alleviates corporations’ own financial pressure, it may have a negative effect on supply chain stability. This paper provides new evidence that reveals that air pollution is an implicit cost in the capital market, enriching research in the fields of environmental governance and capital markets. Full article
►▼ Show Figures

Figure 1

More Articles...

Open Access Journals

► Browse by Indexing ► Browse by Subject ► Selected Journals
Explore All Journals...

Highly Accessed Articles

Latest Books

More Books and Reprints...

News

19 July 2025
MDPI Canada | MDPI Montreal Editors Salon
16 July 2025
JAMS is a Sponsor for the ISMTE Annual North American Conference, 5–8 August 2025, in Montreal, Canada
15 July 2025
Meet Us at the 21st European Burns Association Congress, 3–6 September 2025, Berlin, Germany
More News & Announcements...

Blog Posts

More From Our Blog...

Topics

More Topics...
loading...

Selected Special Issues

Selected Collections

Back to TopTop