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33 pages, 1114 KB

Open AccessArticle

Bangladesh’s Ship Recycling Industry in the Global South: Readiness, Regional Competition, and Reform Imperatives

by Khandakar Akhter Hossain

Sustainability 2025, 17(24), 10998; https://doi.org/10.3390/su172410998 (registering DOI) - 9 Dec 2025

The ship recycling industry in Bangladesh has transformed from informal, beaching-based operations into a globally significant sector, representing over 45% of global recycling tonnage and providing essential raw materials and employment opportunities. This study adopts a mixed-methods design, combining secondary data analysis (2014–2024 [...] Read more.

The ship recycling industry in Bangladesh has transformed from informal, beaching-based operations into a globally significant sector, representing over 45% of global recycling tonnage and providing essential raw materials and employment opportunities. This study adopts a mixed-methods design, combining secondary data analysis (2014–2024 gross tonnage records), over 500 stakeholder interviews, and ARIMA-based scenario forecasting up to 2050. The findings indicate that the sector contributes approximately USD 2.1 billion annually to the national economy and supports more than 250,000 direct and indirect jobs. Despite its economic significance, major compliance gaps persist with the Hong Kong International Convention (HKC): only about 52% of yards are certified or in the process of certification. Workplace accident rates remain roughly 30% higher than regional averages, while environmental assessments reveal elevated heavy metal concentrations in soil and water, underscoring weak regulatory enforcement and environmental management. Comparative analysis shows that India has successfully modernized over 120 HKC-compliant yards through targeted policy and financial incentives, whereas Pakistan is rapidly upgrading its Gadani facilities through major investment programs. Forecasting results identify three trajectories: a baseline of ~2.7 million GT annually to 2050, an optimistic expansion to ~5 million GT with green reforms, and a pessimistic decline below 2 million GT if progress stagnates. To ensure sustainable advancement, five strategic policy pillars are proposed, offering an evidence-based roadmap for Bangladesh to achieve safe, environmentally sound, and globally competitive ship recycling. Full article

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21 pages, 2246 KB

Open AccessArticle

Robotic Bricklaying Adoption in Post-Pandemic Jordan: A Resilience Framework for Construction Automation

by Rola AlShawabkeh and Khaled Al Omari

Buildings 2025, 15(24), 4438; https://doi.org/10.3390/buildings15244438 (registering DOI) - 9 Dec 2025

Abstract

The COVID-19 pandemic intensified labor shortages and safety challenges in Jordan’s construction sector, revealing systemic vulnerabilities in its reliance on migrant workers. This study evaluates an advanced robotic bricklaying system through simulation of 10 residential buildings (80 units) under Jordanian building codes (JSBC [...] Read more.

The COVID-19 pandemic intensified labor shortages and safety challenges in Jordan’s construction sector, revealing systemic vulnerabilities in its reliance on migrant workers. This study evaluates an advanced robotic bricklaying system through simulation of 10 residential buildings (80 units) under Jordanian building codes (JSBC 2020) and strict pandemic constraints, including workforce absenteeism rates of 30% based on ILO data and Ministry of Health density protocols. The simulation-based analysis, which focuses specifically on standardized housing designs, demonstrates 84% faster bricklaying (6.75 vs. 43.2 days/unit), 94% productivity retention during absenteeism, 15% mortar waste reduction (advancing SDG 9), and 60% lower transmission risk versus manual methods. Despite higher rental costs (15,168 JD vs. 12,946 JD/unit), accelerated construction timelines substantially reduced overhead expenses, yielding a rapid <5-month payback period. Policy recommendations target vocational training programs and financial subsidies for small contractors, aligning with Jordan’s Economic Modernization Vision (2022–2024). Limitations involve architectural irregularities and supply chain dependencies; future work requires field validation to complement these simulation findings. Full article

(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)

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Graphical abstract

27 pages, 2899 KB

Open AccessArticle

Adaptive Fuzzy Finite-Time Synchronization Control of Fractional-Order Chaotic Systems with Uncertain Dynamics, Unknown Parameters and Input Nonlinearities

by Xiyu Zhang, Chun Feng, Youjun Zhou and Xiongfeng Deng

Fractal Fract. 2025, 9(12), 805; https://doi.org/10.3390/fractalfract9120805 (registering DOI) - 9 Dec 2025

Abstract

This work focuses on the finite-time synchronization control (FTSC) for fractional-order chaotic systems (FOCSs) subject to uncertain dynamics, unknown parameters and input nonlinearities. In the control law design, the uncertain dynamics of the FOCSs are addressed by using fuzzy logic systems (FLSs), while [...] Read more.

This work focuses on the finite-time synchronization control (FTSC) for fractional-order chaotic systems (FOCSs) subject to uncertain dynamics, unknown parameters and input nonlinearities. In the control law design, the uncertain dynamics of the FOCSs are addressed by using fuzzy logic systems (FLSs), while the unknown control direction caused by unknown input nonlinearity is handled through applying the Nussbaum gain function (NGF) method. Parameter adaptive laws are derived to estimate the unknown parameters of the given FOCSs, the parameter vectors of the FLSs, and unknown bounded constants, respectively. By integrating these parameter-adaptive laws with the FT backstepping control framework and FO Lyapunov direct method, an adaptive fuzzy FTSC strategy is developed. This strategy ensures that the synchronization error (SE) can converge to a small neighborhood of zero (SNoZ) within a FT and all signals of the closed-loop system (CLS) remain ultimately bounded. In the end, three simulation cases are utilized to demonstrate the efficiency of the proposed control method. Full article

(This article belongs to the Special Issue Advances in Dynamics and Control of Fractional-Order Systems)

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14 pages, 1400 KB

Open AccessArticle

Adaptive Optimization of Diffuse Spot Intensities and Locations for Enhanced Performance in Indoor Visible-Light Optical Wireless Communications

by Michael David, Abdullahi. B. Babadoko, Suleiman Zubair, Abraham U. Usman, Abraham. D. Morakinyo, Stephen S. Oyewobi and Topside E. Mathonsi

Computers 2025, 14(12), 537; https://doi.org/10.3390/computers14120537 (registering DOI) - 9 Dec 2025

Abstract

This study explores the application of JAYA optimization algorithms to significantly enhance the performance of indoor optical wireless communication (OWC) systems. By strategically optimizing photo-signal parameters, the system was able to improve signal distribution and reception within a confined space using circular and [...] Read more.

This study explores the application of JAYA optimization algorithms to significantly enhance the performance of indoor optical wireless communication (OWC) systems. By strategically optimizing photo-signal parameters, the system was able to improve signal distribution and reception within a confined space using circular and randomly positioned diffuse spots. The primary objective was to maximize signal-to-noise ratio (SNR) and minimize delay spread (DS), two critical factors that affect transmission quality in OWC systems. Given the challenges posed by background noise and multipath dispersion, an effective optimization strategy was essential to ensure robust signal integrity at the receiver end. Key achievements of JAYA optimization include significant performance gains, such as a 29% improvement in SNR, enhancing signal clarity and reception, and a 23.3% reduction in delay spread, ensuring stable and efficient transmission. System stability also improved, with the standard deviation of SNR improving by up to 5%, leading to a more consistent performance, while the standard deviation of delay spread improved by up to 9.9%, minimizing variations across receivers. Resilience against environmental challenges: Optimization proved effective even in the presence of ambient light noise and complex multipath dispersion effects, reinforcing its adaptability in real-world applications. The findings of this study confirm that JAYA optimization algorithms offer a powerful solution for overcoming noise and dispersion issues in indoor OWC systems, leading to more reliable and high-quality optical wireless communications. These results underscore the importance of algorithmic precision in enhancing system performance, paving the way for further advancements in indoor optical networking technologies. Full article

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19 pages, 1814 KB

Open AccessArticle

Effect of Treated Wastewater Quality on Agronomic Performance, Yield, and Nutritional Composition of Tomato (Solanum lycopersicum L.)

by Noura Benlemlih, Monica Brienza, Vincenzo Trotta, Ali Hammani, Ehssan Elmeknassi Youssoufi, Fatima El Bahja, Rania Brital, Safae El Aammouri, Essaïd Ait Barka and Mohammed Ibriz

Agronomy 2025, 15(12), 2824; https://doi.org/10.3390/agronomy15122824 (registering DOI) - 9 Dec 2025

Abstract

Water scarcity in Mediterranean regions such as Morocco makes treated wastewater a strategic alternative for irrigation. This field study evaluated the effects of two treated wastewater sources, membrane bioreactor T2 and activated sludge T3, compared with groundwater (T1, control) on growth, yield, and [...] Read more.

Water scarcity in Mediterranean regions such as Morocco makes treated wastewater a strategic alternative for irrigation. This field study evaluated the effects of two treated wastewater sources, membrane bioreactor T2 and activated sludge T3, compared with groundwater (T1, control) on growth, yield, and fruit quality of two tomato cultivars (Solanum lycopersicum L., Bobcat and Galilia). Irrigation with activated sludge effluent T3 significantly improved agronomic performance relative to both MBR-treated water and groundwater. Under T3, plant height reached 158 ± 3.5 cm in Galilia and 150 ± 3.2 cm in Bobcat, while fruit yield increased to 9.93 ± 0.38 kg plant⁻¹ in Bobcat and 7.12 ± 0.25 kg plant⁻¹ in Galilia, more than double the yield recorded under T2. Physiological parameters such as chlorophyll a, proline, and soluble sugars increased markedly under T3, indicating enhanced photosynthetic activity and improved stress tolerance. Fruit quality was enhanced under T3, with higher soluble sugar and protein levels, while lycopene and acidity were greatest under groundwater irrigation. Overall, the results demonstrate that secondary treated wastewater, particularly from activated sludge processes, can sustainably improve tomato yield and quality while conserving freshwater resources in arid regions. These findings demonstrate the potential of treated wastewater as a sustainable irrigation source for water-scarce Mediterranean agriculture. Full article

(This article belongs to the Special Issue Smart Strategies and Technologies for Sustainability and Biodiversity in Herbaceous and Horticultural Crops—3rd Edition)

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20 pages, 2261 KB

Open AccessArticle

Design, Synthesis, and Biological Evaluation of 6″-Modified Apramycin Derivatives to Overcome Aminoglycoside Resistance

by Kseniya S. Shapovalova, Georgy V. Zatonsky, Elizaveta A. Razumova, Nikolai D. Dagaev, Dmitrii A. Lukianov, Natalia E. Grammatikova, Alexander S. Tikhomirov and Andrey E. Shchekotikhin

Pharmaceutics 2025, 17(12), 1583; https://doi.org/10.3390/pharmaceutics17121583 (registering DOI) - 8 Dec 2025

Abstract

Background/Objectives: Despite their long history of clinical use, aminoglycosides remain important broad-spectrum antibiotics, exhibiting potent activity against Gram-positive, Gram-negative, and mycobacterial pathogens. However, the growing prevalence of antimicrobial resistance, along with the well-documented nephrotoxicity and ototoxicity associated with this class, underscores the [...] Read more.

Background/Objectives: Despite their long history of clinical use, aminoglycosides remain important broad-spectrum antibiotics, exhibiting potent activity against Gram-positive, Gram-negative, and mycobacterial pathogens. However, the growing prevalence of antimicrobial resistance, along with the well-documented nephrotoxicity and ototoxicity associated with this class, underscores the urgent need for novel derivatives with enhanced pharmacological and safety profiles. Methods: In this study, we developed a synthetic approach for the synthesis of new apramycin derivatives featuring structural modifications at the 6″-position of 4-amino-4-deoxy-D-glucose residue, specifically through the introduction of aminoalkylamine and guanidinoalkylamine substituents. The synthesized compounds were evaluated for their antimicrobial activity against a broad panel of bacterial strains, including multidrug-resistant clinical isolates. Results: The obtained derivatives of apramycin demonstrated significant antibacterial activity, retaining potency against strains resistant to conventional aminoglycosides. Moreover, the new compounds exhibited the ability to circumvent aminoglycoside resistance mediated by enzymatic modification and showed reduced cytotoxicity in mammalian cell assays. Conclusions: The distinctive pharmacological properties of apramycin and its newly synthesized derivatives, particularly their resilience to common resistance mechanisms and low cytotoxicity, highlight apramycin as a valuable structural scaffold for the development of next-generation aminoglycoside antibiotics with improved efficacy and safety. Full article

(This article belongs to the Special Issue Novel Approaches in the Search for Active Compounds in Drug Discovery and Development)

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26 pages, 3521 KB

Open AccessArticle

Optimizing Robotic Arm Obstacle Avoidance via Improved Random Tree Star (RRT)* and Deep Reinforcement Learning Coordination

by Tingyu Fu and Xing Tang

Symmetry 2025, 17(12), 2112; https://doi.org/10.3390/sym17122112 (registering DOI) - 8 Dec 2025

Abstract

Driven by Industry 5.0, efficient obstacle avoidance of robotic arms in dynamic environments is a key bottleneck for human–robot collaboration in smart manufacturing. Traditional path planning methods such as Rapidly-exploring Random Tree and artificial potential field work stably in static settings but exhibit [...] Read more.

Driven by Industry 5.0, efficient obstacle avoidance of robotic arms in dynamic environments is a key bottleneck for human–robot collaboration in smart manufacturing. Traditional path planning methods such as Rapidly-exploring Random Tree and artificial potential field work stably in static settings but exhibit flaws including path oscillation and poor real-time performance under dynamic obstacles. Deep reinforcement learning adapts to environmental changes but is limited by low sample efficiency and high computational costs, failing industrial demands. This study proposes a collaborative framework integrating improved Rapidly-exploring Random Tree Star and Deep reinforcement learning. It uses Rapidly-exploring Random Tree Star to guide Deep reinforcement learning’s strategy exploration, reducing invalid sampling by 62%, and leverages Deep reinforcement learning’s global optimization to enhance dynamic obstacle prediction. The framework achieves a task success rate of 93.8%, surpassing traditional Rapidly-exploring Random Tree Star by 21.5%, with an average path length of 1.97 m and system energy consumption of 12.6 kWh. Experiments demonstrate superior performance in extreme dynamic scenarios, including a 94.7% success rate in multi-robot collaboration. Industrial cases confirm improvements in automobile manufacturing assembly cycle time to 8.4 s per task, yield rate to 98.7%, and reductions in energy consumption by 34% and human intervention by 85.6%, providing a reliable dynamic obstacle avoidance solution for Industry 5.0 applications. Full article

(This article belongs to the Section Engineering and Materials)

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20 pages, 1285 KB

Open AccessSystematic Review

Treatment and Prevention of Cardiogenic Arterial Thromboembolism in the Cat: A Systematic Review

by Giulia Arcuri, Pietro Bresolin and Carlo Guglielmini

Animals 2025, 15(24), 3539; https://doi.org/10.3390/ani15243539 (registering DOI) - 8 Dec 2025

Abstract

Feline cardiogenic arterial thromboembolism (ATE) is a severe complication of cardiac disease in cats, often causing severe clinical signs and poor prognosis. Despite its importance, standardized guidelines for prevention and treatment are lacking. This systematic review evaluated available evidence on preventive, acute, and [...] Read more.

Feline cardiogenic arterial thromboembolism (ATE) is a severe complication of cardiac disease in cats, often causing severe clinical signs and poor prognosis. Despite its importance, standardized guidelines for prevention and treatment are lacking. This systematic review evaluated available evidence on preventive, acute, and chronic management strategies for feline cardiogenic ATE. A comprehensive search using PubMed, Scopus and Web of Science was performed, following PRISMA 2020 guidelines. Peer-reviewed studies investigating therapeutic interventions for ATE were included. Risk of bias was assessed using the SYRCLE tool. Nineteen studies involving 909 cats were included. Preventive therapy with clopidogrel and rivaroxaban improved survival. Acute multimodal treatment combining anticoagulant and antiplatelet drugs improved survival compared to monotherapy. Thrombolytic therapy showed some efficacy but had frequent severe complications. Long-term management with clopidogrel and rivaroxaban achieved the longest survival and lowest recurrence, while acetylsalicylic acid provided inconsistent benefits and more adverse effects. Eleven of the nineteen (58%) studies had high risk of bias due to small sample size and heterogeneous protocols. Current evidence supports dual therapy, particularly clopidogrel with rivaroxaban or enoxaparin, as the most effective and well-tolerated approach for prevention and treatment. Larger, standardized prospective trials are urgently needed to strengthen the evidence. Full article

(This article belongs to the Section Veterinary Clinical Studies)

33 pages, 3256 KB

Open AccessArticle

DMF-Net: A Dynamic Fusion Attention Mechanism-Based Model for Coronary Artery Segmentation

by GuangKun Ma, Linghui Kong, Mo Guan, Yanhong Meng and Deyan Chen

Symmetry 2025, 17(12), 2111; https://doi.org/10.3390/sym17122111 (registering DOI) - 8 Dec 2025

Abstract

Coronary artery segmentation in CTA images remains challenging due to blurred vessel boundaries, unclear structural details, and sparse vascular distributions. To address these limitations, we propose DMF-Net (Dual-path Multi-scale Fusion Network), a novel multi-scale feature fusion architecture based on UNet++. The network incorporates [...] Read more.

Coronary artery segmentation in CTA images remains challenging due to blurred vessel boundaries, unclear structural details, and sparse vascular distributions. To address these limitations, we propose DMF-Net (Dual-path Multi-scale Fusion Network), a novel multi-scale feature fusion architecture based on UNet++. The network incorporates three key innovations: First, a Dynamic Buffer–Bottleneck–Buffer Layer (DBBLayer) in shallow encoding stages enhances the extraction and preservation of fine vascular structures. Second, an Axial Local–global Hybrid Attention Module (ALHA) in deep encoding stages employs a dual-path mechanism to simultaneously capture vessel trajectories and small branches through integrated global and local pathways. Third, a 2.5D slice strategy improves trajectory capture by leveraging contextual information from adjacent slices. Additionally, a composite loss function combining Dice loss and binary cross-entropy jointly optimizes vascular connectivity and boundary precision. Validated on the ImageCAS dataset, DMF-Net achieves superior performance compared to state-of-the-art methods: 89.45% Dice Similarity Coefficient (DSC) (+3.67% vs. UNet++), 3.85 mm Hausdorff Distance (HD, 49.1% reduction), and 0.95 mm Average Surface Distance (ASD, 42.4% improvement). Subgroup analysis reveals particularly strong performance in clinically challenging scenarios. For small vessels (<2 mm diameter), DMF-Net achieves 85.23 ± 1.34% DSC versus 78.67 ± 1.89% for UNet++ (+6.56%, p < 0.001). At complex bifurcations, HD improves from 9.34 ± 2.15 mm to 4.67 ± 1.28 mm (50.0% reduction, p < 0.001). In low-contrast regions (HU difference < 100), boundary precision (ASD) improves from 2.15 ± 0.54 mm to 1.08 ± 0.32 mm (49.8% improvement, p < 0.001). All improvements are statistically significant (p < 0.001). Full article

(This article belongs to the Section Computer)

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22 pages, 8773 KB

Open AccessArticle

Reconfigurable Multispectral Imaging System Design and Implementation with FPGA Control

by Shuyang Chen, Min Huang, Wenbin Ge, Guangming Wang, Xiangning Lu, Yixin Zhao, Jinlin Chen, Lulu Qian and Zhanchao Wang

Appl. Sci. 2025, 15(24), 12951; https://doi.org/10.3390/app152412951 (registering DOI) - 8 Dec 2025

Abstract

Multispectral imaging plays an important role in fields such as environmental monitoring and industrial inspection. To meet the demands for high spatial resolution, portability, and multi-scenario use, this study presents a reconfigurable 2 × 3 multispectral camera-array imaging system. The system features a [...] Read more.

Multispectral imaging plays an important role in fields such as environmental monitoring and industrial inspection. To meet the demands for high spatial resolution, portability, and multi-scenario use, this study presents a reconfigurable 2 × 3 multispectral camera-array imaging system. The system features a modular architecture, allowing for the flexible exchange of lenses and narrowband filters. Each camera node is equipped with an FPGA that performs real-time sensor control and data preprocessing. A companion host program, based on the GigE Vision protocol, was developed for synchronous control, multi-channel real-time visualization, and unified parameter configuration. End-to-end performance verification confirmed stable, lossless, and synchronous acquisition from all six 3072 × 2048-pixel resolution channels. Following field alignment, the 16 mm lens achieves an effective 4.7 MP spatial resolution. Spectral profile measurements further confirm that the system exhibits favorable spectral response characteristics. The proposed framework provides a high-resolution and flexible solution for portable multispectral imaging. Full article

(This article belongs to the Section Optics and Lasers)

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17 pages, 464 KB

Open AccessArticle

Sustainable Fashion in China: Consumers’ Second-Hand Clothing Intentions and Market Evolution

by Zhiyi Zhang

Sustainability 2025, 17(24), 10997; https://doi.org/10.3390/su172410997 (registering DOI) - 8 Dec 2025

Abstract

As global attention on environmental sustainability grows, the fashion industry is shifting towards circular models, with the second-hand clothing market emerging as a key pathway to sustainable development. In China, this market is rapidly evolving, with millennials and Generation Z showing strong interest [...] Read more.

As global attention on environmental sustainability grows, the fashion industry is shifting towards circular models, with the second-hand clothing market emerging as a key pathway to sustainable development. In China, this market is rapidly evolving, with millennials and Generation Z showing strong interest in environmentally friendly and personalized fashion. This study investigates Chinese consumers’ motivations and barriers to purchasing second-hand clothing and examines the diversity of China’s sustainable fashion ecosystem. Using a mixed-methods approach of semi-structured interviews and surveys, the findings reveal that environmental awareness, economic affordability, and social influence drive purchase intentions, while hygiene concerns, societal perceptions, and trust in platforms act as barriers. The study also compares the roles of online platforms, offline vintage stores, and upcycling fashion brands, highlighting their complementarity across economic, cultural, and social dimensions. Online platforms offer efficiency and convenience, vintage stores build brand loyalty through cultural narratives, and upcycling brands merge creativity with sustainability. It also reflects on the cultural context shaping second-hand fashion adoption in China. The study suggests enhancing trust in platforms, promoting education, and leveraging social media campaigns to support future market development. Full article

(This article belongs to the Special Issue Sustainability in Fashion and Textiles: Can Environmental Impact Assessments Inform a Circular Fashion Future?)

22 pages, 23544 KB

Open AccessArticle

Investigation of Coral Reefs for Coastal Protection: Hydrodynamic Insights and Sustainable Flow Energy Reduction

by Faisal Karim, Napayalage A. K. Nandasena, James P. Terry, Mohamed M. Mohamed and Zhonghou Xu

Sustainability 2025, 17(24), 10996; https://doi.org/10.3390/su172410996 - 8 Dec 2025

Abstract

Coral reefs are integral components of tropical coastal marine ecosystems that have considerable capacity to mitigate extreme flows and marine floods caused by storms and tsunamis. However, limited studies on coral reef efficacy in reducing such flows, coupled with variable roughness coefficient characteristics, [...] Read more.

Coral reefs are integral components of tropical coastal marine ecosystems that have considerable capacity to mitigate extreme flows and marine floods caused by storms and tsunamis. However, limited studies on coral reef efficacy in reducing such flows, coupled with variable roughness coefficient characteristics, hinder their broader utilization in sustainable engineering applications for societal benefit. In this study, we conducted comprehensive experimental investigations to examine flow–coral interactions and the flow energy reduction capabilities of coral reefs. Three-dimensional-printed coral reefs were used to simulate actual coral reefs, providing a scalable and environmentally responsible approach for studying nature-based coastal protection systems. Flow characteristics within the coral reef were investigated through flow depth and velocity measurements taken at the front of, over, and behind the reef. Analysis was performed considering nondimensional parameters, i.e., the Froude number (Fr), the depth effect (DE; ratio of flow depth to coral height), and the size effect (SE; ratio of coral length to coral height), to assess the flow energy reduction under different coral combinations and flow conditions. Spatial variations in flow depth over the reef showed that fast and shallow flows exhibited a reduction gradient toward the back of the reef. The findings revealed a substantial reduction in flow depth and velocity, reaching up to 27.5% and 25%, respectively, at the back boundary of the coral. Two-layered velocity analyses showed that the velocity over the top of corals could be six times higher than that through the coral reef structure for deep flows. Manning’s roughness coefficient varied considerably from 0.03 to 0.26. Overall, this study contributes to sustainable coastal engineering by demonstrating how bio-inspired coral reef structures can be applied to reduce flow energy and enhance coastal resilience in an environmentally adaptive manner. Full article

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24 pages, 2648 KB

Open AccessArticle

Optimizing Ridge–Furrow Configuration and Nitrogen Rate to Enhance Wheat Nitrogen Use Efficiency Under Diverse Climate and Soil Conditions

by Ting Pan, Zeyu Liu, Liuyang Yan, Fu Chen, Juanling Wang, Xuefang Huang and Yueyue Xu

Agriculture 2025, 15(24), 2543; https://doi.org/10.3390/agriculture15242543 - 8 Dec 2025

Abstract

Optimizing field cropping practices to improve nitrogen use efficiency is imperative to promote intensive and sustainable wheat production. As a cultivation method commonly adopted in arid and semi-arid regions globally, the ridge–furrow mulching system (RFMS) is capable of efficiently harvesting rainfall, reduce evaporation [...] Read more.

Optimizing field cropping practices to improve nitrogen use efficiency is imperative to promote intensive and sustainable wheat production. As a cultivation method commonly adopted in arid and semi-arid regions globally, the ridge–furrow mulching system (RFMS) is capable of efficiently harvesting rainfall, reduce evaporation losses, enhancing soil moisture levels in the root zone, and boosting crop productivity. However, the combined effects of varying ridge–furrow ratios (RD), ridge heights (RH), and nitrogen application rates (RN) on nitrogen fertilizer bias productivity (PFPN) under the influence of climatic conditions, soil types, and field management practices remain poorly understood due to a lack of systematic evaluation. This study conducted a meta-analysis of 462 comparative datasets from 98 research projects to reveal the interactive effects of RFMS and nitrogen fertilizer across climatic gradients. The results showed that RH, RD, and RN increased by 23.78%, 22.37%, and 23.07% respectively (p < 0.05), with the most significant enhancement of PFPN being demonstrated by RH. The most significant improvement in PFPN was observed when RD = 1:1, R < 10 cm, and RN > 200 kg∙hm⁻², with PFPN increasing by 27.7%, 29.50%, and 29.32% respectively (p < 0.05). Climatic and soil physico-chemical factors and field management practices are the key factors influencing the RFMS. When average annual evapotranspiration (AE) < 1000, RN > 200 has the best effect on nitrogen utilization efficiency, while under the condition of AE > 1500, RN < 100 is more effective. In terms of mulching strategy, full mulching of ridges and furrows is recommended in areas with severe drought and low temperatures, while mulching only ridges or furrows is more appropriate in areas with relatively mild climate. The present study provides a scientific basis for the optimal design of ridge–furrow mulching configuration and nitrogen application level. This is achieved by considering climatic conditions, soil fertility, and field management in agro-ecosystems in arid and semi-arid areas. Full article

(This article belongs to the Section Agricultural Soils)

18 pages, 407 KB

Open AccessReview

Low-Coverage Whole-Genome Sequencing (lcWGS) in Cattle: Analysis of Potential and Prospects for Application

by Olga Kostyunina, Nikita Koldichev, Gleb Nemkovskiy, Alexey Traspov, Anton Ermilov, Faridun Bakoev, Dmitriy Chesnokov, Anna Panova, Kseniia Antonovskaia, Alexander Kusnetzov and Vladimir Belyakov

Animals 2025, 15(24), 3538; https://doi.org/10.3390/ani15243538 - 8 Dec 2025

Abstract

Whole-genome studies in cattle play a key role in exploring both individual and population-level genetic variability. Recently, low-coverage whole-genome sequencing (0.5–2×) has been considered as an alternative to traditional approaches. Low-coverage whole-genome sequencing (lcWGS), which provides uniform coverage of the entire genome at [...] Read more.

Whole-genome studies in cattle play a key role in exploring both individual and population-level genetic variability. Recently, low-coverage whole-genome sequencing (0.5–2×) has been considered as an alternative to traditional approaches. Low-coverage whole-genome sequencing (lcWGS), which provides uniform coverage of the entire genome at relatively low cost, combined with subsequent imputation, enables the reconstruction of genotypes with high accuracy and density. lcWGS enables detection of rare and functionally important variants and provides exploratory potential for structural variation analysis; however, accurate SV imputation still presents significant challenges. The aim of this review is to analyze the potential and prospects of lcWGS as a tool for genomic selection and genetic studies in cattle. The review systematizes current advances in the application of lcWGS in cattle, focusing on imputation accuracy, factors affecting it, and the comparative efficiency of different software solutions. A literature survey was conducted using PubMed and Google Scholar databases, with preference given to original studies, systematic reviews, and large-scale projects addressing imputation accuracy, reference panel composition and size, cost-effectiveness, and practical applications of lcWGS in cattle genomics. Key factors influencing efficiency include sequencing depth, reference panel size and composition, as well as the choice of imputation algorithm. lcWGS represents a cost-effective and powerful alternative to traditional genome-wide approaches, capable of capturing rare and breed-specific variants; however, its application to structural variation still requires methodological improvement and integration with high-resolution reference pangenomes or long-read sequencing. Despite significant progress and the high potential of lcWGS in cattle genomics, several challenges and limitations remain, requiring further investigation and resolution to fully realize the advantages of this technology. Addressing these challenges will enable more efficient use of lcWGS for genetic research and accelerate genetic progress in cattle breeding. Full article

(This article belongs to the Special Issue Advances in Cattle Genetics and Breeding)

26 pages, 1622 KB

Open AccessArticle

Does Understanding Water Footprint and Virtual Water Concepts Promote Water Conservation?

by Shengqian Zhang, Mengyang Wu, Raffaele Albano and Xinchun Cao

Water 2025, 17(24), 3480; https://doi.org/10.3390/w17243480 - 8 Dec 2025

Abstract

Amid escalating global water scarcity and growing emphasis on demand-side interventions for sustainable resource use, understanding how consumers’ virtual water cognition can drive food–water resource conservation is critical for strengthening sustainable resource governance. Through a questionnaire survey, this study constructed a Food–Water Behavior [...] Read more.

Amid escalating global water scarcity and growing emphasis on demand-side interventions for sustainable resource use, understanding how consumers’ virtual water cognition can drive food–water resource conservation is critical for strengthening sustainable resource governance. Through a questionnaire survey, this study constructed a Food–Water Behavior Synergy Model to explore the relationship among consumers’ virtual water cognition and food-conservation behavior, water-conservation behavior, and food–water synergistic cognition in China. Results show that virtual water cognition significantly increased food-conservation behavior (β = 0.158, p < 0.001) and WCB (β = 0.064, p < 0.001). Food–water synergistic cognition also positively affected food-conservation behavior (β = 0.099, p < 0.001) and water-conservation behavior (β = 0.035, p < 0.01), consistent with the knowledge–action framework. The magnitudes of these effects differed across subgroups (gender, education level, major, region, and urban–rural residence). Virtual water cognition did not significantly enhance food–water synergistic cognition (β = 0.006, p = 0.758), providing empirical evidence of a knowledge–action gap. There was a strong direct effect of food-conservation behavior on water-conservation behavior (β = 0.498, p < 0.001), and there was evidence that food-conservation behavior mediated the indirect paths from both virtual water cognition and food–water synergistic cognition to water-conservation behavior. Implementing consumer-oriented contextual interventions—such as differentiated educational guidance and water-footprint labeling—would be conducive to translating theoretical knowledge into practical action. Full article

(This article belongs to the Special Issue Advanced Perspectives on the Water–Energy–Food Nexus)

16 pages, 290 KB

Open AccessSystematic Review

Reconstructive Surgery of the Female Genital, Urethral, and Anal Tract: A Multidisciplinary Review and Future Perspectives

by Vivian Del Sorbo, Paola Pentangelo, Paolo Verrazzo, Ritapia Papa and Carmine Alfano

J. Pers. Med. 2025, 15(12), 613; https://doi.org/10.3390/jpm15120613 - 8 Dec 2025

Abstract

Background: Pelvic floor dysfunctions, congenital anomalies, and acquired defects of the female genital, urethral, and anal tract represent complex conditions requiring multidisciplinary management. This review synthesizes current evidence and aims to evaluate reconstructive surgical techniques, prosthetic use, and cosmetic approaches with a focus [...] Read more.

Background: Pelvic floor dysfunctions, congenital anomalies, and acquired defects of the female genital, urethral, and anal tract represent complex conditions requiring multidisciplinary management. This review synthesizes current evidence and aims to evaluate reconstructive surgical techniques, prosthetic use, and cosmetic approaches with a focus on functional and aesthetic outcomes. Methods: A structured literature search of PubMed, Embase, and the Cochrane Library was performed for the period from January 2000 to May 2025 (last search: 31 May 2025). Eligible studies included randomized controlled trials, prospective or retrospective clinical studies, and case series in English or Italian, enrolling women aged ≥18 years with a minimum follow-up of 6 months. Primary outcomes were anatomical restoration, continence, sexual function, and quality of life; secondary outcomes included patient satisfaction, wound complications, donor-site morbidity, and recurrence. Recent high-quality studies published after 2018 were prioritized to ensure an updated and evidence-based synthesis. Results: Out of 532 records, 94 full texts were assessed and 41 studies met the eligibility criteria, comprising a total of 1862 women. Flap-based reconstruction (gluteus maximus, VRAM, gracilis, ALT) remained the cornerstone for large or irradiated defects, while prosthetic meshes improved anatomical outcomes but raised concerns of erosion and chronic pain, leading to a shift toward autologous tissue. Cosmetic gynecology procedures (labiaplasty, vaginoplasty, perineoplasty) showed high patient satisfaction, although the evidence was limited and heterogeneous. Across studies, improvements were observed in continence, sexual function, quality of life, and self-image when reconstructive and aesthetic principles were integrated. Conclusions: Reconstructive and cosmetic pelvic surgery significantly impacts functional recovery and psychological well-being. Standardized outcome reporting, prospective multicenter trials, and the integration of plastic surgery, physiotherapy, and psychological support are needed to optimize patient-centered care. The findings highlight the growing role of personalized surgical planning, with reconstructive decisions increasingly guided by patient-specific anatomy, functional goals, and validated patient-reported outcome measures. Full article

(This article belongs to the Section Personalized Therapy in Clinical Medicine)

27 pages, 722 KB

Open AccessReview

Artificial Intelligence in Medical Education: A Narrative Review

by Mateusz Michalczak, Wiktoria Zgoda, Jakub Michalczak, Anna Żądło, Ameen Nasser and Tomasz Tokarek

AI 2025, 6(12), 322; https://doi.org/10.3390/ai6120322 - 8 Dec 2025

Abstract

Background: Artificial intelligence (AI) is increasingly shaping medical education through adaptive learning systems, simulations, and large language models. These tools can enhance knowledge retention, clinical reasoning, and feedback, while raising concerns related to equity, bias, and institutional readiness. Methods: This narrative review examined [...] Read more.

Background: Artificial intelligence (AI) is increasingly shaping medical education through adaptive learning systems, simulations, and large language models. These tools can enhance knowledge retention, clinical reasoning, and feedback, while raising concerns related to equity, bias, and institutional readiness. Methods: This narrative review examined AI applications in medical and health-profession education. A structured search of PubMed, Scopus, and Web of Science (2010–October 2025), supplemented by grey literature, identified empirical studies, reviews, and policy documents addressing AI-supported instruction, simulation, communication, procedural skills, assessment, or faculty development. Non-educational clinical AI studies were excluded. Results: AI facilitates personalized and interactive learning, improving clinical reasoning, communication practice, and simulation-based training. However, linguistic bias in Natural language processing (NLP) tools may disadvantage non-native English speakers, and limited digital infrastructure hinders adoption in rural or low-resource settings. When designed inclusively, AI can amplify accessibility for learners with disabilities. Faculty and students commonly report low confidence and infrequent use of AI tools, yet most support structured training to build competence. Conclusions: AI can shift medical education toward more adaptive, learner-centered models. Effective adoption requires addressing bias, ensuring equitable access, strengthening infrastructure, and supporting faculty development. Clear governance policies are essential for safe and ethical integration. Full article

(This article belongs to the Special Issue Development of Artificial Intelligence and Computational Thinking: Future Directions, Opportunities, and Challenges)

32 pages, 1495 KB

Open AccessArticle

YOLO-HRNet with Attention Mechanism: For Automated Ergonomic Risk Assessment in Garment Manufacturing

by Yichen Tan, Ziqian Yang and Zhihui Wu

Appl. Sci. 2025, 15(24), 12950; https://doi.org/10.3390/app152412950 - 8 Dec 2025

Abstract

For garment manufacturing, an efficient and precise assessment of ergonomics is vital to prevent work-related musculoskeletal disorders. This study creates a computer vision-based algorithm for fast and accurate risk analysis. Specifically, we introduced SE and CBAM attention mechanisms into the YOLO network and [...] Read more.

For garment manufacturing, an efficient and precise assessment of ergonomics is vital to prevent work-related musculoskeletal disorders. This study creates a computer vision-based algorithm for fast and accurate risk analysis. Specifically, we introduced SE and CBAM attention mechanisms into the YOLO network and integrated the optimized modules into the HRNet architecture to improve the accuracy of human pose recognition. This approach effectively addresses common interferences in garment production environments, such as fabric accumulation, equipment occlusion, and complex hand movements, while significantly enhancing the accuracy of human detection. On the COCO dataset, it increased mAP and recall by 4.43% and 5.99%, respectively, over YOLOv8. Furthermore, by analyzing key postural features from worker videos of cutting, sewing, and pressing, we achieved a quantified ergonomic risk assessment. Experimental results indicate that the RULA scores calculated using this algorithm are highly consistent and stable with expert evaluations and accurately reflect the dynamic changes in ergonomic risk levels across different processes. It is important to note that the validation was based on a pilot study involving a limited number of workers and task types, meaning that the findings primarily demonstrate feasibility rather than full-scale generalizability. Even so, the algorithm outperforms existing lightweight solutions and can be deployed in real-time on edge devices within factories, providing a low-cost ergonomic monitoring tool for the garment manufacturing industry. This helps prevent and reduce musculoskeletal injuries among workers. Full article

23 pages, 6694 KB

Open AccessCommunication

Bismuth–Titanium–Silicate–Oxide Glass Ceramics for Various Dielectric Applications

by Stanislav Slavov and Veselin Stankov

Materials 2025, 18(24), 5519; https://doi.org/10.3390/ma18245519 - 8 Dec 2025

Abstract

Ceramics based on bismuth titanate with added SiO₂ and Nd₂O₃ were synthesized from the Bi₂O₃–TiO₂–SiO₂–Nd₂O₃ system through rapid melt quenching followed by controlled cooling. By adjusting the initial [...] Read more.

Ceramics based on bismuth titanate with added SiO₂ and Nd₂O₃ were synthesized from the Bi₂O₃–TiO₂–SiO₂–Nd₂O₃ system through rapid melt quenching followed by controlled cooling. By adjusting the initial compositions and applying heat treatments between 1450 °C and 1100 °C, either homogeneous crystalline products or multiphase glass–ceramics were obtained. The identified crystalline phases included Bi₁₂TiO₂₀ and Bi₄Ti₃O₁₂, coexisting with amorphous networks enriched in silicon, bismuth, titanium, and aluminum oxides. In previous investigations, the materials were characterized using X-ray diffraction, scanning electron microscopy, and Fourier-transform infrared spectroscopy, which collectively confirmed the presence of both ordered and disordered structural domains within the bulk samples. Electrical properties were evaluated through measurements of conductivity (4 × 10⁻⁹ S/m to 30 S/m), dielectric constant (real part from 10 to 5 × 10³ and imaginary part from 5 to 5 × 10⁴), and dielectric loss (0.02 to ~100) over the frequency range 1 Hz–1 MHz. These results provide a foundation for rational control of phase evolution in this quaternary oxide system and highlight strategies for tailoring the functional properties of glass–ceramic materials for dielectric applications. The aim of the present study is to investigate the relationship between phase composition, structural features, and dielectric behavior in cast Bi–Ti–Si–Nd glass–ceramics. Particular attention is given to the influence of the amorphous network containing SiO₂ as a traditional glass former, as well as the formation of amorphous crosslinking Si–O–Ti structures acting as non-traditional glass formers. Full article

(This article belongs to the Special Issue New Generation Materials for Advanced Electronic and Biomedical Applications)

32 pages, 3523 KB

Open AccessArticle

Empowering Service Designers with Integrated Modelling Tools: A Model-Driven Approach

by Francisco Javier Pérez-Blanco, Juan Manuel Vara, Cristian Gómez-Macías, David Granada and Carlos Villarrubia

Systems 2025, 13(12), 1107; https://doi.org/10.3390/systems13121107 - 8 Dec 2025

Abstract

Service design often involves using diverse business and process modelling notations to represent strategic and operational aspects of services. Although complementary, no modelling environment currently enables integrated use of these notations. This paper addresses this gap by proposing a model-driven solution that supports [...] Read more.

Service design often involves using diverse business and process modelling notations to represent strategic and operational aspects of services. Although complementary, no modelling environment currently enables integrated use of these notations. This paper addresses this gap by proposing a model-driven solution that supports multiple modelling notations within a unified environment. The research is guided by the following question: To what extent can a modelling environment that integrates multiple business and process modelling notations benefit service designers? To answer it, the study adopts Design Science Research (DSR) methodology and develops a prototype integrating several graphical Domain-Specific Languages (DSLs), along with mechanisms for model transformation, traceability, and validation. The prototype was evaluated through a two-phase process: (1) a laboratory case study applying the double diamond model of service design to a real-world scenario, and (2) an empirical study involving nine service design professionals who assessed the usability of the tool, efficiency, and completeness of generated models. Results show that integrating heterogeneous modelling notations through Model-Driven Engineering (MDE) can reduce modelling effort by up to 36.4% and generate models with up to 97.7% completeness, demonstrating not only technical benefits but also contributions to the well-being of designers by reducing cognitive load, fostering consistency, and improving communication among the stakeholders involved in the designing process. Full article

(This article belongs to the Section Systems Practice in Social Science)

20 pages, 1030 KB

Open AccessArticle

VISTA: A Multi-View, Hierarchical, and Interpretable Framework for Robust Topic Modelling

by Tvrtko Glunčić, Domjan Barić and Matko Glunčić

Mach. Learn. Knowl. Extr. 2025, 7(4), 162; https://doi.org/10.3390/make7040162 - 8 Dec 2025

Abstract

Topic modeling is a fundamental technique in natural language processing used to uncover latent themes in large text corpora, yet existing approaches struggle to jointly achieve interpretability, semantic coherence, and scalability. Classical probabilistic models such as LDA and NMF rely on bag-of-words assumptions [...] Read more.

Topic modeling is a fundamental technique in natural language processing used to uncover latent themes in large text corpora, yet existing approaches struggle to jointly achieve interpretability, semantic coherence, and scalability. Classical probabilistic models such as LDA and NMF rely on bag-of-words assumptions that obscure contextual meaning, while embedding-based methods (e.g., BERTopic, Top2Vec) improve coherence at the expense of diversity and stability. Prompt-based frameworks (e.g., TopicGPT) enhance interpretability but remain sensitive to prompt design and are computationally costly on large datasets. This study introduces VISTA (Vector-Similarity Topic Analysis), a multi-view, hierarchical, and interpretable framework that integrates complementary document embeddings, mutual-nearest-neighbor hierarchical clustering with selective dimension analysis, and large language model (LLM)-based topic labeling enforcing hierarchical coherence. Experiments on three heterogeneous corpora—BBC News, BillSum, and a mixed U.S. Government agency news + Twitter dataset—show that VISTA consistently ranks among the top-performing models, achieving the highest C_UCI coherence and a strong balance between topic diversity and semantic consistency. Qualitative analyses confirm that VISTA identifies domain-relevant themes overlooked by probabilistic or prompt-based models. Overall, VISTA provides a scalable, semantically robust, and interpretable framework for topic discovery, bridging probabilistic, embedding-based, and LLM-driven paradigms in a unified and reproducible design. Full article

(This article belongs to the Section Visualization)

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20 pages, 2850 KB

Open AccessArticle

Influence of Sandblasting Particle Size on the Shear Bond Strength of Orthodontic Brackets to Milled and 3D-Printed Provisional Crowns or Materials After Artificial Aging

by Khurshid Mattoo, Mohammed E. Sayed, Marwan Someli, Ahmed Alhazmi, Mohammed Khawajy, Shroog A. Almasoudi, Ebrahim Fihaid Alsubaiy, Saeed M. Alqahtani, Mohammed A. Alfaifi and Raghdah M. Alshaibani

J. Funct. Biomater. 2025, 16(12), 457; https://doi.org/10.3390/jfb16120457 - 8 Dec 2025

Abstract

Purpose: This in vitro study ascertained the impact of three distinct alumina particle sizes on the shear bond strength (SBS) between two distinct provisional crowns (milled and 3D-printed) and stainless-steel orthodontic brackets following artificial aging. Materials and methods: Eighty specimens [disc 10 mm [...] Read more.

Purpose: This in vitro study ascertained the impact of three distinct alumina particle sizes on the shear bond strength (SBS) between two distinct provisional crowns (milled and 3D-printed) and stainless-steel orthodontic brackets following artificial aging. Materials and methods: Eighty specimens [disc 10 mm diameter/15 mm height] were fabricated with two provisional crown materials, milled (CopraTemp) [group (GP) M] and three-dimensionally printed (Asiga DentaTooth) (GP P), and divided into eight subgroups based on alumina oxide (sandblasting) particle size surface treatments of 25 μm [P25, M25], 50 μm [P50, M50], and 100 μm [P100, M100], with no surface treatment specimens serving as control [PC, MC]. After thermocycling (2200 cycles), the SBS and Adhesive Remnant Index (ARI) were calculated. Statistical tests included one-way analysis of variance (ANOVA) (Kruskal–Wallis), followed by post hoc tests [Tukey HSD, Dunn’s], with the probability ‘p’ value being significant at 0.05 (p ≤ 0.05). Results: Without surface treatment, the 3D-printed provisional crown had the lowest SBS [median (IQR); 12.8 (2.74)]. The highest SBS was found in both milled and 3D-printed PMs with 50-micron particle sizes [Milled = 23.10 (2.3); Printed = 20.72 (2.31)], followed by 100-micron [Milled = 20 (2.36); Printed = 17.99 (3.45)] and 25-micron [Milled = 16.13 (2.71); Printed = 15.08 (1.55)]. The majority of cohesive failures were seen in the milled subgroups, while all subgroups of 3D-printed provisional material had adhesive bond failures. Conclusions: Sandblasting, irrespective of particle size, enhances SBS in both milled and 3D-printed provisional restorations; however, 50-micron alumina particles are recommended since they enhance SBS substantially. Full article

(This article belongs to the Section Dental Biomaterials)

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21 pages, 2992 KB

Open AccessArticle

Effect of Temperature on Germination and Distribution of Pinus ayacahuite Ehrenb. ex Schltdl. Under Climate Change Scenarios in Mexico

by Luis V. Pedrero-López, Salvador Sampayo-Maldonado, Mixtli Y. Nabor-Vazquez, María E. Sánchez-Coronado, Alma Orozco-Segovia, Patricia Dávila Aranda, Daniel Cabrera-Santos, Isela Rodríguez-Arévalo, Diana C. Acosta-Rojas and Cesar M. Flores-Ortíz

Forests 2025, 16(12), 1833; https://doi.org/10.3390/f16121833 - 8 Dec 2025

Abstract

Pinus ayacahuite is an important species for reforestation in Mexico, as it is a pioneer species in open areas. Its regeneration could be threatened by rising temperatures. The effect of a temperature gradient on germination was analyzed, and potential distribution projections of climate [...] Read more.

Pinus ayacahuite is an important species for reforestation in Mexico, as it is a pioneer species in open areas. Its regeneration could be threatened by rising temperatures. The effect of a temperature gradient on germination was analyzed, and potential distribution projections of climate change scenarios were modeled at various time scales. Seeds were collected in Huayacocotla, Veracruz; these were germinated under nine constant temperatures (5–45 °C). Germination parameters, cardinal temperatures, and thermal time were estimated using a Gaussian model. Germination occurred between 10 and 40 °C, with optimal, base, and ceiling temperatures of 27 °C, 10 °C, and 42 °C, respectively, and a thermal time (Tt₅₀) of 118.5 °C d⁻¹. Based on climate change projections (SSP1-2.6 and SSP5-8.5), NASA’s GISS-E2-1-G model predicts temperature increases from 1.1 to 2.3 °C by 2050 and from 1.7 to 3.6 °C by 2090, which would accelerate germination by 12.9–25 days. However, the species’ potential distribution is projected to decline by 15%–22%, primarily in southern states such as Chiapas, Oaxaca, and Puebla, although it could shift to new suitable areas in Tamaulipas and Nuevo León. These results suggest that while higher temperatures may favor earlier germination, water availability will remain the main limiting factor for successful establishment. Integrating physiological parameters into distribution models offers a stronger foundation for seed storage, conservation, and reforestation strategies in the face of changing climatic conditions. Full article

(This article belongs to the Special Issue Climate and Land-Use Change Effects on the Biogeography of Woody Plant Species and Biodiversity Conservation)

12 pages, 451 KB

Open AccessArticle

Surgical Site Infection After Breast Surgery—A Bicentric Retrospective Case–Control Study in Saudi Arabia

by Moteb AlSaadi, Salem Alghamdi, Fayyaz Mazari, Sabah Alshuhri, Rustom Bashtawi, Raghad Aljehani, Basmah Alwuqaisi, Rawan Almohammadi, Mahmoud Alfirikh, Sameer Desai and Ebrahim Mahmoud

Clin. Pract. 2025, 15(12), 231; https://doi.org/10.3390/clinpract15120231 - 8 Dec 2025

Abstract

Background: Surgical site infections (SSIs) are common postoperative complications. Data on SSIs following breast surgery in Saudi Arabia are limited because these procedures are not included in the national SSI surveillance system. This study determined the SSI incidence rate, identified associated risk factors, [...] Read more.

Background: Surgical site infections (SSIs) are common postoperative complications. Data on SSIs following breast surgery in Saudi Arabia are limited because these procedures are not included in the national SSI surveillance system. This study determined the SSI incidence rate, identified associated risk factors, and described the microbiological profiles of patients undergoing breast surgery at two tertiary hospitals in Saudi Arabia. Methods: This bicentric retrospective case–control study analyzed 1841 breast surgeries performed at two tertiary hospitals between July 2021 and July 2024. Demographic, surgical, and microbiological data were extracted from electronic medical records. SSIs were defined according to National Healthcare Safety Network criteria. Descriptive statistics summarized patient and surgical characteristics and SSI rates. A matched case–control analysis (1:4 ratio based on age and hospital site) included 172 patients. Multivariable logistic regression was used to identify predictors of SSI. Results: The cumulative SSI incidence was 2.4%, and most infections occurred within 30 days of surgery (69%). Gram-negative organisms were predominant in microbiologically positive cases (53.6%), mainly Klebsiella pneumoniae and Pseudomonas aeruginosa, whereas Staphylococcus aureus (including MRSA) accounted for 25%. Immunocompromised status (OR 3.32, 95% CI 1.35–8.14) and surgical drain use (OR 4.07, 95% CI 1.68–9.87) were independently associated with SSI. Conclusions: The incidence of SSIs after breast surgery in Saudi Arabia was relatively low. The predominance of Gram-negative pathogens and the identification of immunocompromised status and surgical drain use as major risk factors highlight opportunities for targeted infection prevention strategies. Further studies should validate these findings in larger and more diverse populations and healthcare settings. Full article

19 pages, 746 KB

Open AccessArticle

The Impact of Flow on University EFL Learners’ Psychological Capital: Insights from Positive Psychology

by Fan Jia, Xihong Wang, Chunjie Ding, Shujun Wang, Xiaorong Wang and Yanhui Mao

Behav. Sci. 2025, 15(12), 1703; https://doi.org/10.3390/bs15121703 - 8 Dec 2025

Abstract

Many studies have shown that flow, psychological capital (PsyCap), anxiety, and academic efficacy play significant roles in EFL learning, yet little attention has been paid to how these positive and negative states jointly shape learners’ PsyCap. Grounded in the broaden-and-build theory, this study [...] Read more.

Many studies have shown that flow, psychological capital (PsyCap), anxiety, and academic efficacy play significant roles in EFL learning, yet little attention has been paid to how these positive and negative states jointly shape learners’ PsyCap. Grounded in the broaden-and-build theory, this study investigated how flow, a state of deep engagement and enjoyment in learning, affected EFL learners’ PsyCap. A total of 1611 EFL learners at the CEFR B1–B2 levels from six universities in China participated in the study. Data were collected using validated questionnaires developed for this study that measured flow, foreign language classroom anxiety (FLCA), academic efficacy, and PsyCap, and analyzed using structural equation modeling (SEM) in AMOS. The results revealed that flow had a significant direct positive effect on PsyCap (β = 0.648, p < 0.001). Academic efficacy significantly mediated this relationship (β = 0.059, p < 0.001), and a significant chain-mediated path was observed through FLCA and academic efficacy (β = 0.023, p < 0.001). The total effect of flow on PsyCap was 0.729 (p < 0.001). These findings provide new insights into educational practices that can effectively enhance EFL learners’ PsyCap and academic achievement by facilitating flow and reducing anxiety. Full article

27 pages, 4695 KB

Open AccessArticle

A Multi-Layered Analytical Pipeline Combining Informatics, UHPLC–MS/MS, Network Pharmacology, and Bioassays for Elucidating the Skin Anti-Aging Activity of Melampyrum roseum

by Min Hyung Cho, JangHo Ha, Haiyan Jin, SoHee An and SungJune Chu

Int. J. Mol. Sci. 2025, 26(24), 11853; https://doi.org/10.3390/ijms262411853 - 8 Dec 2025

Abstract

Oxidative stress, UV exposure, inflammation, and extracellular matrix degradation collectively drive skin aging, underscoring the need for safe, multi-target therapeutic options. We developed and applied an integrated analytical pipeline combining UHPLC–MS/MS metabolomics, computational analyses (network pharmacology, molecular docking, and molecular dynamics simulation), and [...] Read more.

Oxidative stress, UV exposure, inflammation, and extracellular matrix degradation collectively drive skin aging, underscoring the need for safe, multi-target therapeutic options. We developed and applied an integrated analytical pipeline combining UHPLC–MS/MS metabolomics, computational analyses (network pharmacology, molecular docking, and molecular dynamics simulation), and experimental bioassays to efficiently identify and characterize novel natural products with anti-aging potential. This workflow was applied to Melampyrum roseum Maxim., a previously unassessed hemiparasitic plant of the Orobanchaceae family, to elucidate its bioactive potential against skin aging. UHPLC–MS/MS profiling annotated 13 secondary metabolites, predominantly flavone aglycones, iridoid glycosides, and phenylpropanoid derivatives. Network pharmacology analysis linked these metabolites to 172 potential skin-aging-associated targets, mainly within inflammatory, ECM, and oxidative-stress pathways. Molecular docking and 100-ns molecular dynamics simulations confirmed stable ligand-target interactions with favorable binding energies, particularly with AKT1, EGFR, PTGS2 and XDH. Validating these predictions, the M. roseum extract demonstrated significant antioxidant activity and effectively suppressed key inflammatory mediators (IL-6, TNF-α, COX-2) and MMP-1 levels in UVB-exposed fibroblasts, notably without significant cytotoxicity. Collectively, these findings demonstrate that M. roseum harbors multifunctional metabolites that modulate key inflammatory and matrix-regulatory pathways, providing preliminary mechanistic evidence for its potential as a promising candidate for natural anti-aging applications. Full article

(This article belongs to the Special Issue Bioactives from Natural Products)

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