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Search Results (178,183)

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29 pages, 12889 KiB  
Article
Development of a Multi-Robot System for Autonomous Inspection of Nuclear Waste Tank Pits
by Pengcheng Cao, Edward Kaleb Houck, Anthony D'Andrea, Robert Kinoshita, Kristan B. Egan, Porter J. Zohner and Yidong Xia
Appl. Sci. 2025, 15(17), 9307; https://doi.org/10.3390/app15179307 - 24 Aug 2025
Abstract
This paper introduces the overall design plan, development timeline, and preliminary progress of the Autonomous Pit Exploration System project. This project aims to develop an advanced multi-robot system for the efficient inspection of nuclear waste-storage tank pits. The project is structured into three [...] Read more.
This paper introduces the overall design plan, development timeline, and preliminary progress of the Autonomous Pit Exploration System project. This project aims to develop an advanced multi-robot system for the efficient inspection of nuclear waste-storage tank pits. The project is structured into three phases: Phase 1 involves data collection and interface definition in collaboration with Hanford Site experts and university partners, focusing on tank riser geometry and hardware solutions. Phase 2 includes the selection of sensors and robot components, detailed mechanical design, and prototyping. Phase 3 integrates all components into a cohesive system managed by a master control package which also incorporates digital twin and surrogate models, and culminates in comprehensive testing and validation at a simulated tank pit at the Idaho National Laboratory. Additionally, the system’s communication design ensures coordinated operation through shared data, power, and control signals. For transportation and deployment, an electric vehicle (EV) is chosen to support the system for a full 10 h shift with better regulatory compliance for field deployment. A telescopic arm design is selected for its simple configuration and superior reach capability and controllability. Preliminary testing utilizes an educational robot to demonstrate the feasibility of splitting computational tasks between edge and cloud computers. Successful simultaneous localization and mapping (SLAM) tasks validate our distributed computing approach. More design considerations are also discussed, including radiation hardness assurance, SLAM performance, software transferability, and digital twinning strategies. Full article
(This article belongs to the Special Issue Mechatronic Systems Design and Optimization)
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25 pages, 732 KiB  
Article
Long-Term Variability of Ice Phenomena in Selected Rivers of the Central Vistula River Catchment
by Agnieszka Hejduk and Michał Szalkowski
Water 2025, 17(17), 2523; https://doi.org/10.3390/w17172523 - 24 Aug 2025
Abstract
The phenomenon of surface freezing in lakes, rivers, and reservoirs, has been an essential part of Poland’s winter landscape for centuries. It plays critical ecological roles, such as regulating heat balance and influencing the state of biocenoses. Due to progressive climate warming, we [...] Read more.
The phenomenon of surface freezing in lakes, rivers, and reservoirs, has been an essential part of Poland’s winter landscape for centuries. It plays critical ecological roles, such as regulating heat balance and influencing the state of biocenoses. Due to progressive climate warming, we have observed significant changes in ice cover duration, thickness, and timing in recent decades. Ice phenomena on rivers are temporary. They strongly depend on air temperature, which has recently been increasing worldwide. This paper analyzes the variability of ice phenomena formation in selected river profiles of the central Vistula River catchment, central Poland. The research period covers the years 1968–2016. The data come from the Institute of Meteorology and Water Management-State Research Institute (IMGW-PIB). The duration (including the dates of occurrence and disappearance of the phenomenon) and the frequency of occurrence of ice phenomena over the long-term were determined with particular attention to ice cover. The long-term occurrence of ice phenomena shows a decreasing trend (shorter duration, later onset dates) with a simultaneous increase in the average air temperature during the winter half of the hydrological year. Full article
(This article belongs to the Section Hydrology)
27 pages, 3909 KiB  
Review
Identifying Root Causes and Sustainable Solutions for Reducing Construction Waste Using Social Network Analysis
by Mona Salah, Emad Elbeltagi, Meshal Almoshaogeh, Fawaz Alharbi and Mohamed T. Elnabwy
Sustainability 2025, 17(17), 7638; https://doi.org/10.3390/su17177638 - 24 Aug 2025
Abstract
The construction industry is a major contributor to environmental degradation, primarily due to the substantial volumes of construction waste (CW) generated on-site. As sustainability becomes a global imperative aligned with the UN 2030 Agenda, identifying and mitigating the root causes of CW is [...] Read more.
The construction industry is a major contributor to environmental degradation, primarily due to the substantial volumes of construction waste (CW) generated on-site. As sustainability becomes a global imperative aligned with the UN 2030 Agenda, identifying and mitigating the root causes of CW is essential. This study adopts a cross-disciplinary approach to explore the drivers of CW and support more effective, sustainable waste reduction strategies. A systematic literature review was conducted to extract 25 key CW source factors from academic publications. These were analyzed using Social Network Analysis (SNA) to reveal their structural relationships and relative influence. The results indicate that the lack of structured on-site waste management planning, accumulation of residual materials, and insufficient worker training are among the most influential CW drivers. Comparative analysis with industry data highlights theoretical–practical gaps and the need for improved alignment between research insights and site implementation. This paper recommends the adoption of tiered waste management protocols as part of contractual documentation, integrating Building Information Modeling (BIM)-based residual material traceability systems, and increasing attention to workforce training programs focused on material handling efficiency. Future research should extend SNA frameworks to sector-specific waste patterns (e.g., pavement or demolition projects) and explore the intersection between digital technologies and circular economy practices. The study contributes to enhancing waste governance, promoting resource efficiency, and advancing circularity in the built environment by offering data-driven prioritization of CW sources and actionable mitigation strategies. Full article
(This article belongs to the Section Waste and Recycling)
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28 pages, 10321 KiB  
Article
Influence of Spill Pressure and Saturation on the Migration and Distribution of Diesel Oil Contaminant in Unconfined Aquifers Using Three-Dimensional Numerical Simulations
by Alessandra Feo and Fulvio Celico
Appl. Sci. 2025, 15(17), 9303; https://doi.org/10.3390/app15179303 - 24 Aug 2025
Abstract
Spilled hydrocarbons released from oil pipeline accidents can result in long-term environmental contamination and significant damage to habitats. In this regard, evaluating actions in response to vulnerability scenarios is fundamental to emergency management and groundwater integrity. To this end, understanding the trajectories and [...] Read more.
Spilled hydrocarbons released from oil pipeline accidents can result in long-term environmental contamination and significant damage to habitats. In this regard, evaluating actions in response to vulnerability scenarios is fundamental to emergency management and groundwater integrity. To this end, understanding the trajectories and their influence on the various parameters and characteristics of the contaminant’s fate through accurate numerical simulations can aid in developing a rapid remediation strategy. This paper develops a numerical model using the CactusHydro code, which is based on a high-resolution shock-capturing (HRSC) conservative method that accurately follows sharp discontinuities and temporal dynamics for a three-phase fluid flow. We analyze nine different emergency scenarios that represent the breaking of a diesel oil onshore pipeline in a porous medium. These scenarios encompass conditions such as dry season rupture, rainfall-induced saturation, and varying pipeline failure pressures. The influence of the spilled oil pressure and water saturation in the unsaturated zone is analyzed by following the saturation contour profiles of the three-phase fluid flow. We follow with the high-accuracy formation of shock fronts of the advective part of the migration. Additionally, the mass distribution of the expelled contaminant along the porous medium during the emergency is analyzed and quantified for the various scenarios. The results obtained indicate that the aquifer contamination strongly depends on the pressure outflow in the vertical flow. For a fixed pressure value, as water saturation increases, the mass of contaminant decreases, while the contamination speed increases, allowing the contaminant to reach extended areas. This study suggests that, even for LNAPLs, the distribution of leaked oil depends strongly on the spill pressure. If the pressure reaches 20 atm at the time of pipeline failure, then contamination may extend as deep as two meters below the water table. Additionally, different seasonal conditions can influence the spread of contaminants. This insight could directly inform guidelines and remediation measures for spill accidents. The CactusHydro code is a valuable tool for such applications. Full article
(This article belongs to the Section Environmental Sciences)
27 pages, 3693 KiB  
Article
Energy Management Strategy for Hybrid Electric Vehicles Based on Experience-Pool-Optimized Deep Reinforcement Learning
by Jihui Zhuang, Pei Li, Ling Liu, Hongjie Ma and Xiaoming Cheng
Appl. Sci. 2025, 15(17), 9302; https://doi.org/10.3390/app15179302 - 24 Aug 2025
Abstract
The energy management strategy of Hybrid Electric Vehicles (HEVs) plays a key role in improving fuel economy and reducing battery energy consumption. This paper proposes a Deep Reinforcement Learning-based energy management strategy optimized by the experience pool (P-HER-DDPG), aimed at improving the fuel [...] Read more.
The energy management strategy of Hybrid Electric Vehicles (HEVs) plays a key role in improving fuel economy and reducing battery energy consumption. This paper proposes a Deep Reinforcement Learning-based energy management strategy optimized by the experience pool (P-HER-DDPG), aimed at improving the fuel efficiency of HEVs while accelerating the training speed. The method integrates the mechanisms of Prioritized Experience Replay (PER) and Hindsight Experience Replay (HER) to address the reward sparsity and slow convergence issues faced by the traditional Deep Deterministic Policy Gradient (DDPG) algorithm when handling continuous action spaces. Under various standard driving cycles, the P-HER-DDPG strategy outperforms the traditional DDPG strategy, achieving an average fuel economy improvement of 5.85%, with a maximum increase of 8.69%. Compared to the DQN strategy, it achieves an average improvement of 12.84%. In terms of training convergence, the P-HER-DDPG strategy converges in 140 episodes, 17.65% faster than DDPG and 24.32% faster than DQN. Additionally, the strategy demonstrates more stable State of Charge (SOC) control, effectively mitigating the risks of battery overcharging and deep discharging. Simulation results show that P-HER-DDPG can enhance fuel economy and training efficiency, offering an extended solution in the field of energy management strategies. Full article
29 pages, 2209 KiB  
Review
Pulmonary Aspergillosis in Immunocompromised Critically Ill Patients: Prevalence, Risk Factors, Clinical Features and Diagnosis—A Narrative Review
by Maria Grazia Bocci, Laura Cascarano, Giulia Capecchi, Antonio Lesci, Valerio Sabatini, Dorotea Rubino, Giulia Valeria Stazi, Gabriele Garotto, Stefania Carrara, Antonella Vulcano, Chiara Gori, Franca Del Nonno, Daniele Colombo, Laura Falasca, Emanuela Caraffa, Stefania Cicalini and Carla Fontana
J. Fungi 2025, 11(9), 617; https://doi.org/10.3390/jof11090617 - 24 Aug 2025
Abstract
Aspergillosis in immunocompromised individuals is a serious and potentially life-threatening infection, as the weakened immune system cannot effectively fight the Aspergillus fungus. This review provides an in-depth examination of aspergillosis in patients with various conditions that compromise immunity, including hematological disorders, HIV, SARS-CoV-2 [...] Read more.
Aspergillosis in immunocompromised individuals is a serious and potentially life-threatening infection, as the weakened immune system cannot effectively fight the Aspergillus fungus. This review provides an in-depth examination of aspergillosis in patients with various conditions that compromise immunity, including hematological disorders, HIV, SARS-CoV-2 pneumonia, influenza, and those who have undergone solid organ transplants. The clinical manifestations of aspergillosis are influenced by factors such as the host’s underlying comorbidities, immune response, and immune suppression due to medications or treatments. The review delves into the epidemiology of aspergillosis, exploring various risk factors that predispose individuals to infection. It also discusses the wide range of clinical symptoms, highlighting the challenges in diagnosis and the importance of early detection. The review contrasts traditional diagnostic approaches with emerging molecular techniques, emphasizing the role of advanced diagnostics in improving outcomes. A proposed clinical decision-making flowchart is provided to assist healthcare professionals in managing suspected cases of aspergillosis. In addition to diagnostic challenges, the review addresses antifungal prophylaxis, pre-emptive therapy, and the growing concern of pharmacological resistance to antifungal agents. It concludes with a discussion of future research directions, underscoring the need for improved therapeutic strategies and preventative measures in immunocompromised patients to reduce the burden of this severe fungal infection. Full article
(This article belongs to the Special Issue Fungal Infections in Intensive Care Medicine)
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21 pages, 2000 KiB  
Review
Diabetic Kidney Disease: From Pathophysiology to Regression of Albuminuria and Kidney Damage: Is It Possible?
by Georgia Doumani, Panagiotis Theofilis, Aikaterini Vordoni, Vasileios Thymis, George Liapis, Despina Smirloglou and Rigas G. Kalaitzidis
Int. J. Mol. Sci. 2025, 26(17), 8224; https://doi.org/10.3390/ijms26178224 - 24 Aug 2025
Abstract
Diabetes mellitus (DM) poses an increasingly high global health burden nowadays, while in adults, chronic kidney disease (CKD) associated with DM impacts 20–40% of those with the condition. Effective management of CKD in patients with diabetes necessitates a comprehensive, multidisciplinary approach. Numerous factors, [...] Read more.
Diabetes mellitus (DM) poses an increasingly high global health burden nowadays, while in adults, chronic kidney disease (CKD) associated with DM impacts 20–40% of those with the condition. Effective management of CKD in patients with diabetes necessitates a comprehensive, multidisciplinary approach. Numerous factors, including glomerular hyperfiltration, oxidative stress, inflammation, and hypoxia are linked to the advancement of diabetic kidney disease (DKD). Currently, no specific treatment for DKD has been established, prompting extensive exploration of new approaches. Renin-angiotensin-aldosterone system inhibitors and sodium-glucose cotransporter 2 inhibitors have demonstrated renoprotective effects in various human clinical trials. Additionally, glucagon-like peptide 1 receptor agonists and mineralocorticoid receptor antagonists have been reported as effective in managing DKD, while new therapeutic candidates are also under investigation, such as soluble guanylate cyclase activators and aldosterone synthase inhibitors. Recent evidence has shown that treating diabetic nephropathy by reducing albuminuria levels and retarding its progression is a complex skill. The purpose of this review is to support the impressive results that appear in reducing albuminuria and the progression of diabetic nephropathy with early and intensive combination treatment compared to the recently emerged conventional monotherapy, with agents that act on different pathophysiological mechanisms. Full article
(This article belongs to the Collection Latest Review Papers in Endocrinology and Metabolism)
23 pages, 7301 KiB  
Article
A Study on the Associative Regulation Mechanism Based on the Water Environmental Carrying Capacity and Its Impact Indicators in the Songhua River Basin in Harbin City, China
by Zhongbao Yao, Xuebing Wang, Nan Sun, Tianyi Wang and Hao Yan
Sustainability 2025, 17(17), 7636; https://doi.org/10.3390/su17177636 - 24 Aug 2025
Abstract
With intensifying watershed pollution pressures and growing ecological vulnerability, scientifically revealing and enhancing the water environmental carrying capacity is crucial for ensuring the long-term health of the basin and the sustainable socioeconomic development of the region. However, the dynamic regulatory mechanisms linking narrow-sense [...] Read more.
With intensifying watershed pollution pressures and growing ecological vulnerability, scientifically revealing and enhancing the water environmental carrying capacity is crucial for ensuring the long-term health of the basin and the sustainable socioeconomic development of the region. However, the dynamic regulatory mechanisms linking narrow-sense and broad-sense water environmental carrying capacity remain poorly understood, limiting the development of integrated management strategies. This study systematically investigated the changing trends of both the narrow-sense and broad-sense water environmental carrying capacity in the Harbin section of the Songhua River basin through model calculations, along with the regulatory mechanisms of its key influence indicators. The results of the study on the carrying capacity of the water environment in the narrow sense show that permanganate, total phosphorus, and ammonia nitrogen exhibited partial carrying capacity across water periods, while dissolved oxygen decreased during flat and dry periods, with only limited capacity remaining at the Ash River estuary and in the Hulan River. The biochemical oxygen demand in the Ash River was consistently overloaded, and total nitrogen showed insufficient capacity except during the abundant water period. Broad-sense analysis indicated that improving urbanization quality, water supply infrastructure, and drinking water safety could effectively reduce future overload risks, with projections suggesting a transition from critical to loadable levels by 2030, though latent threats persist. Correlation analysis between narrow- and broad-sense indicators informed targeted control strategies, including stricter regulation of nitrogen- and phosphorus-rich industrial discharges, restoration of aquatic vegetation, and periodic dredging of riverbed sediments. This work is the first to dynamically integrate pollutant and socio-economic indicators through a hybrid modelling framework, providing a scientific basis and actionable strategies for improving water quality and achieving sustainable management in the Songhua River Basin. Full article
20 pages, 6878 KiB  
Article
EMR-YOLO: A Multi-Scale Benthic Organism Detection Algorithm for Degraded Underwater Visual Features and Computationally Constrained Environments
by Dehua Zou, Songhao Zhao, Jingchun Zhou, Guangqiang Liu, Zhiying Jiang, Minyi Xu, Xianping Fu and Siyuan Liu
J. Mar. Sci. Eng. 2025, 13(9), 1617; https://doi.org/10.3390/jmse13091617 - 24 Aug 2025
Abstract
Marine benthic organism detection (BOD) is essential for underwater robotics and seabed resource management but suffers from motion blur, perspective distortion, and background clutter in dynamic underwater environments. To address visual feature degradation and computational constraints, we, in this paper, introduce EMR-YOLO, a [...] Read more.
Marine benthic organism detection (BOD) is essential for underwater robotics and seabed resource management but suffers from motion blur, perspective distortion, and background clutter in dynamic underwater environments. To address visual feature degradation and computational constraints, we, in this paper, introduce EMR-YOLO, a deep learning based multi-scale BOD method. To handle the diverse sizes and morphologies of benthic organisms, we propose an Efficient Detection Sparse Head (EDSHead), which combines a unified attention mechanism and dynamic sparse operators to enhance spatial modeling. For robust feature extraction under resource limitations, we design a lightweight Multi-Branch Fusion Downsampling (MBFDown) module that utilizes cross-stage feature fusion and multi-branch architecture to capture rich gradient information. Additionally, a Regional Two-Level Routing Attention (RTRA) mechanism is developed to mitigate background noise and sharpen focus on target regions. The experimental results demonstrate that EMR-YOLO achieves improvements of 2.33%, 1.50%, and 4.12% in AP, AP50, and AP75, respectively, outperforming state-of-the-art methods while maintaining efficiency. Full article
40 pages, 4344 KiB  
Review
Digital Cardiovascular Twins, AI Agents, and Sensor Data: A Narrative Review from System Architecture to Proactive Heart Health
by Nurdaulet Tasmurzayev, Bibars Amangeldy, Baglan Imanbek, Zhanel Baigarayeva, Timur Imankulov, Gulmira Dikhanbayeva, Inzhu Amangeldi and Symbat Sharipova
Sensors 2025, 25(17), 5272; https://doi.org/10.3390/s25175272 - 24 Aug 2025
Abstract
Cardiovascular disease remains the world’s leading cause of mortality, yet everyday care still relies on episodic, symptom-driven interventions that detect ischemia, arrhythmias, and remodeling only after tissue damage has begun, limiting the effectiveness of therapy. A narrative review synthesized 183 studies published between [...] Read more.
Cardiovascular disease remains the world’s leading cause of mortality, yet everyday care still relies on episodic, symptom-driven interventions that detect ischemia, arrhythmias, and remodeling only after tissue damage has begun, limiting the effectiveness of therapy. A narrative review synthesized 183 studies published between 2016 and 2025 that were located through PubMed, MDPI, Scopus, IEEE Xplore, and Web of Science. This review examines CVD diagnostics using innovative technologies such as digital cardiovascular twins, which involve the collection of data from wearable IoT devices (electrocardiography (ECG), photoplethysmography (PPG), and mechanocardiography), clinical records, laboratory biomarkers, and genetic markers, as well as their integration with artificial intelligence (AI), including machine learning and deep learning, graph and transformer networks for interpreting multi-dimensional data streams and creating prognostic models, as well as generative AI, medical large language models (LLMs), and autonomous agents for decision support, personalized alerts, and treatment scenario modeling, and with cloud and edge computing for data processing. This multi-layered architecture enables the detection of silent pathologies long before clinical manifestations, transforming continuous observations into actionable recommendations and shifting cardiology from reactive treatment to predictive and preventive care. Evidence converges on four layers: sensors streaming multimodal clinical and environmental data; hybrid analytics that integrate hemodynamic models with deep-, graph- and transformer learning while Bayesian and Kalman filters manage uncertainty; decision support delivered by domain-tuned medical LLMs and autonomous agents; and prospective simulations that trial pacing or pharmacotherapy before bedside use, closing the prediction-intervention loop. This stack flags silent pathology weeks in advance and steers proactive personalized prevention. It also lays the groundwork for software-as-a-medical-device ecosystems and new regulatory guidance for trustworthy AI-enabled cardiovascular care. Full article
(This article belongs to the Section Biomedical Sensors)
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13 pages, 1701 KiB  
Article
Modeling the Impact of Tele-Health on Accessibility and Equity of Medical Resources in Metropolitan Cities in China
by Qing Wang, Leqi Weng and Jingshan Li
Healthcare 2025, 13(17), 2105; https://doi.org/10.3390/healthcare13172105 - 24 Aug 2025
Abstract
Background: Although the expansion of medical resources has largely alleviated challenges of “more diseases but fewer medicines”, the growing urbanization and rapid aging in China have led to increasing demands of healthcare services in metropolitan cities. The uneven distribution of medical facilities makes [...] Read more.
Background: Although the expansion of medical resources has largely alleviated challenges of “more diseases but fewer medicines”, the growing urbanization and rapid aging in China have led to increasing demands of healthcare services in metropolitan cities. The uneven distribution of medical facilities makes services unequal for residents in the city. To achieve fair and rapid access to medical services, healthcare accessibility and equity have become key concerns. The introduction of tele-health, i.e., online visits or digital health, can help balance the distribution of medical resources to improve accessibility and equity, particularly for elderly patients with chronic diseases. Methods: To quantitatively assess the spatial accessibility of healthcare facilities, an improved two-step floating catchment area method with tele-health (i2SFCA-TH) is proposed to study the demand–supply ratio by considering traveling time, chronic diseases, and online visits based on services provided by community and tertiary hospitals. An optimization model using mixed-integer programming to maximize average accessibility under resource constraints could help improve overall accessibility and reduce differences in access among all residential divisions to achieve better equity in the region. Results: By applying the method in a metropolitan city in China, it is observed that the overall spatial accessibility of residential divisions in the city is 0.72, but the gap between the highest and the lowest reaches 2.36; i.e., significant differences exhibit due to uneven allocation of medical resources. By introducing tele-health, the gaps of access among different divisions can be decreased, with the largest gap reduced to 1.49, and the accessibility in divisions with poor medical resource allocation can be increased. Finally, the mean healthcare accessibility and equity in the study region can be improved to 0.75. In addition, it is shown that proper management of medical resources and patients’ willingness to accept online visits could help improve accessibility and equity, which can provide insights for hospital management and urban planning. Conclusions: An integrated framework to quantitatively assess and optimally improve healthcare accessibility and equity of medical resource allocation through tele-health is presented in this paper. An i2SFCA-TH method and an optimization model are used in the framework, which provides hospital management and urban planners a quantitative tool to improve accessibility and equity in metropolitan cities in China and other countries. Full article
(This article belongs to the Section TeleHealth and Digital Healthcare)
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24 pages, 7258 KiB  
Article
Experimental Validation of a Rule-Based Energy Management Strategy for Low-Altitude Hybrid Power Aircraft
by Yunfeng She, Kunkun Fu, Bo Diao and Maosheng Sun
Aerospace 2025, 12(9), 758; https://doi.org/10.3390/aerospace12090758 - 24 Aug 2025
Abstract
In the electrification of low-altitude aircraft, aviation hybrid power systems have become one of the core research areas in this field due to their significant advantages of low emissions and long endurance. The energy management strategy is an important part of the design [...] Read more.
In the electrification of low-altitude aircraft, aviation hybrid power systems have become one of the core research areas in this field due to their significant advantages of low emissions and long endurance. The energy management strategy is an important part of the design of aviation hybrid power systems and has a significant impact on the performance and safety.This paper first develops a 200 kW dual DC-bus series hybrid power system prototype for low-altitude aircraft and its Simulink simulation model; then, it proposes a rule-based energy management strategy that uses the smoothness of the state of charge (SOC) of energy storage batteries as a coordination criterion. The strategy is validated via ground tests, where the battery SOC remains above 30%, the system response time is within 5 s, and the DC-bus voltage fluctuation is within 1%. These results demonstrate the strategy’s feasibility, providing a reference for designing and implementing series hybrid power systems. Full article
(This article belongs to the Section Aeronautics)
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22 pages, 912 KiB  
Review
Integration of “Omics”-Based Approaches in Environmental Risk Assessment to Establish Cause and Effect Relationships: A Review
by Kirsty F. Smith, Xavier Pochon, Steven D. Melvin, Thomas T. Wheeler and Louis A. Tremblay
Toxics 2025, 13(9), 714; https://doi.org/10.3390/toxics13090714 - 24 Aug 2025
Abstract
Marine and freshwater environments are under increasing pressure from anthropogenic stressors. The resulting impacts on exposed ecosystems are complex and challenging to characterise. The effects may be subtle and exhibited over long time periods. Effective and robust approaches are required to characterise the [...] Read more.
Marine and freshwater environments are under increasing pressure from anthropogenic stressors. The resulting impacts on exposed ecosystems are complex and challenging to characterise. The effects may be subtle and exhibited over long time periods. Effective and robust approaches are required to characterise the physiological and genetic processes that are impacted by pollutants to assess how populations and ecosystems may be adversely affected and at risk. The objective of the review is to provide an overview of “omics” methodologies used to assess the risk of stressors on exposed biota. This review covers the development of key omics approaches and how they have been used to contribute towards improved knowledge about the effects of environmental stressors, from molecular to whole-organism and community levels of biological organisation. We provide insights into how ecotoxicogenomics approaches can be used for various aspects of environmental risk assessment by characterising toxicological mechanisms of action. This information can be used to confirm cause-and-effect relationships required to better manage risks and protect the integrity and functionality of ecosystems. Full article
(This article belongs to the Special Issue Ecotoxicological Monitoring of Aquatic Systems)
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24 pages, 5949 KiB  
Article
Green Smart Museums Driven by AI and Digital Twin: Concepts, System Architecture, and Case Studies
by Ran Bi, Chenchen Song and Yue Zhang
Smart Cities 2025, 8(5), 140; https://doi.org/10.3390/smartcities8050140 - 24 Aug 2025
Abstract
In response to the urgent global call for “dual carbon” targets, the sustainable transformation of public museums has become a focal issue in both academic research and engineering practice. This study proposes and empirically validates an integrated management framework that unites digital twin [...] Read more.
In response to the urgent global call for “dual carbon” targets, the sustainable transformation of public museums has become a focal issue in both academic research and engineering practice. This study proposes and empirically validates an integrated management framework that unites digital twin modeling, artificial intelligence, and green energy systems for next-generation green smart museums. A unified, closed-loop platform for data-driven, adaptive management is implemented and statistically validated across distinct deployment scenarios. Empirical evaluation is conducted through the comparative analysis of three representative museum cases in China, each characterized by a distinct integration pathway: (A) advanced digital twin and AI management with moderate green energy adoption; (B) large-scale renewable energy integration with basic AI and digitalization; and (C) the comprehensive integration of all three dimensions. Multi-dimensional data on energy consumption, carbon emissions, equipment reliability, and visitor satisfaction are collected and analyzed using quantitative statistical techniques and performance indicator benchmarking. The results reveal that the holistic “triple synergy” approach in Case C delivers the most balanced and significant gains, achieving up to 36.7% reductions in energy use and 41.5% in carbon emissions, alongside the highest improvements in operational reliability and visitor satisfaction. In contrast, single-focus strategies show domain-specific advantages but also trade-offs—for example, Case B achieved high energy and carbon savings but relatively limited visitor satisfaction gains. These findings highlight that only coordinated, multi-technology integration can optimize performance across both environmental and experiential dimensions. The proposed framework provides both a theoretical foundation and practical roadmap for advancing the digital and green transformation of public cultural buildings, supporting broader carbon neutrality and sustainable development objectives. Full article
(This article belongs to the Special Issue Big Data and AI Services for Sustainable Smart Cities)
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11 pages, 442 KiB  
Article
Virological Effectiveness of Dolutegravir Plus Darunavir in People with Multi-Drug-Resistant HIV: Data from the PRESTIGIO Registry
by Filippo Lagi, Michele Bellomo, Riccardo Lolatto, Filippo Ducci, Seble Tekle Kiros, Vincenzo Spagnuolo, Rebecka Papaioannu Borjesson, Tommaso Clemente, Leonardo Calza, Marcello Feasi, Emanuele Focà, Andrea Giacomelli, Roberto Gulminetti, Barbara Menzaghi, Antonella Castagna and on behalf of the PRESTIGIO Study Group
Viruses 2025, 17(9), 1158; https://doi.org/10.3390/v17091158 - 24 Aug 2025
Abstract
Background: Data on the use of dolutegravir (DTG) plus boosted darunavir (DRV/b) in people with 4-class drug-resistant HIV (4DR-PWH) are limited. This study assessed the virological effectiveness of DTG + DRV/b in this population using real-world data from the PRESTIGIO Registry. Methods: We [...] Read more.
Background: Data on the use of dolutegravir (DTG) plus boosted darunavir (DRV/b) in people with 4-class drug-resistant HIV (4DR-PWH) are limited. This study assessed the virological effectiveness of DTG + DRV/b in this population using real-world data from the PRESTIGIO Registry. Methods: We compared three regimen groups: dual DTG + DRV/b (DODA), DTG + DRV/b plus an additional antiretroviral drug (DODA + Other), and regimens excluding DTG + DRV/b (NO-DODA). Virological failure (VF) was defined as ≥2 HIV-RNA values ≥ 50 copies/mL or 1 ≥ 1000 copies/mL. Mixed-effects logistic regression was used to assess VF, adjusting for antiretroviral therapy (ART) duration, age, number of fully active drugs, sex at birth, and nadir CD4+. Individuals could switch regimens during follow-up. Results: Among 249 4DR-PWH (median follow-up: 8.7 years), 844 ART regimens were analyzed: 72 (8.5%) DODA, 264 (31.3%) DODA + Other, and 508 (60.2%) NO-DODA. Compared to NO-DODA, the odds of VF were 77% and 35.9% lower with DODA and DODA + Other, respectively. Notably, in the DODA group, DTG and DRV/b were fully active in only 63.9% and 47.2% of the cases, respectively. Conclusions: DTG + DRV/b regimens were associated with a significantly lower risk of virological failure, even when drug activity was partial. This strategy remains a valuable option for managing multi-drug-resistant HIV. Full article
(This article belongs to the Special Issue Viral Resistance)
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