Search Results (39,321)

The growing complexity of human systems and the increasing frequency of climate-driven hazards have transformed some disasters from isolated events into cascading phenomena which propagate through critical infrastructure networks, disrupting essential services and amplifying systemic risk. This work examines the impacts of extreme storms and subsequent flooding on critical entities as defined under the new EU Directive (Critical Entities Resilience, CER). This study introduces a structured Critical Entities Disruption Database—Greece (CEDD-GR), as a methodological framework for systematically recording and analysing disruptions to critical entities, and applies it to the case of Storm Daniel (2023), one of the most severe flood events recorded in Greece. The analysis identified direct impacts across eight of the eleven sectors defined in the CER Directive, namely, energy, transport, health, drinking water, wastewater, public administration, digital infrastructure and food production, processing and distribution. A total of 21 different types of critical entities were documented, revealing the mechanisms through which failures affected different subsectors. The results underscore the systemic fragility of critical entities when exposed to extreme storms, compound flooding, and mass wasting processes (landslides, ground subsidence) and highlight the need for integrated resilience planning in line with the CER framework. Full article

Rapid urbanization and agricultural expansion in arid regions have profoundly altered carbon cycles and landscape stability. Focusing on the Hexi Corridor, China, this study integrates multi-source geospatial data (1990–2020) to analyze the spatiotemporal evolution and driving factors of land-use carbon emissions (LUCE) and landscape ecological risks (LER). By integrating carbon accounting, LER assessment, bivariate spatial autocorrelation, and the Optimal Parameter Geographic Detector (OPGD), we quantify the intricate relationship between carbon dynamics and landscape integrity. Results indicate a transformative pattern of anthropogenic expansion and natural contraction, with a 2315.49 km² net loss of unused land. Net carbon emissions surged 4.6-fold, while forest and grassland sinks exhibited a significant “lock-in effect” due to fragile ecological foundations. Simultaneously, LER followed an “inverted U-shaped” trajectory; the refined 5 × 5 km grid scale revealed a significant drop in high-risk areas from 44.65% to 10.96% following ecological restoration. Spatial analysis reveals a significant “spatial mismatch” between LUCE and LER, with oases manifesting “high carbon–low risk” clustering. Driver detection confirms a driving asymmetry. LUCE is dominated by anthropogenic factors (nighttime light, q > 0.90), whereas LER is profoundly constrained by natural backgrounds. Future governance must shift toward a collaborative system centered on source-based emission control and precise regional management to synergize low-carbon transition with landscape security. Full article

Small ruminant lentiviruses are longstanding viral infections affecting sheep and goats worldwide, resulting in reduced efficiency and economic losses. In Portugal, updated epidemiological data are scarce. The aim of this study was to assess the seroprevalence and risk factors for SRLV in Portugal. The study was conducted in Portuguese flocks of ovine and caprine species. Flocks were randomly chosen, and producers were invited to answer a questionnaire. The indirect ELISA test, ID Screen^® MVV/CAEV Indirect, was made to detect infection. We collected samples from 59 flocks, of which 55.93% (CI 95%: 43.26–68.60%) had at least one positive animal. Of these flocks, 1302 individual samples presented a seroprevalence of 32.95% (CI 95%: 30.08–35.81%). Regarding the risk factor analysis, the multivariable mixed-effects logistic regression model at the individual level identified variables with increased odds of SRLV seropositivity. Caprine species (OR = 2.47; CI 95%: 1.01–6.03), non-autochthonous breed (OR = 2.95; CI 95%: 1.23–7.06), animals older than two years old (OR = 1.95; CI 95%: 1.29–2.94), dairy aptitude (OR = 8.15; CI 95%: 2.53–26.24), unknown serostatus of newly acquired animals (OR = 9.41; CI 95%: 2.93–30.23) and participation in livestock competitions (OR = 4.25; CI 95%: 1.42–12.73) were significantly associated with increased odds of seropositivity. SRLV has been confirmed in both regions of Portugal studied, with a significant regional disparity that is likely attributable to differences in management practices. The identification of risk factors specific to each production system is crucial for the development and implementation of voluntary control programs. Full article

Large-scale integration of photovoltaics (PV) introduces complex source-load temporal volatility and grid-connection/off-grid transitions. Traditional static reliability assessments fail to capture these dynamics, resulting in “considerable deviations” in system indices. This paper proposes a reliability evaluation framework that couples temporal source-load trajectories with a multi-stage fault recovery process. Unlike traditional methods that rely on a single static snapshot, the proposed model evaluates the system state across a continuous 5-h restoration window. The novelty lies in the unique integration of a Dynamic Time Warping (DTW)–Kmedoids method to preserve temporal phase-shifts and a multi-stage Mixed-Integer Linear Programming (MILP) model to simulate PV grid-connection transitions throughout this window. By capturing the intra-outage evolution of sources and loads, the framework fundamentally corrects the “considerable deviations” of static assessments. Case studies demonstrate high precision with an error of less than 0.71% and a 20-fold speedup. Crucially, the framework corrects the 22.31% risk underestimation bias inherent in static models by tracking real-time source-load evolution. This confirms that temporal coordination performance is the primary determinant of the reliability ceiling in active distribution networks. The findings reveal that the precise alignment of intermittent generation and fluctuating demand defines the actual operational safety margin, providing a superior quantitative foundation for grid resilience enhancement. Full article

Hearing loss is detrimental to human health, and currently, more than 1.5 billion people are affected by hearing loss. Active military personnel and construction workers are examples of individuals in the workplace who are exposed to loud noise and are at serious risk of hearing loss. While there is currently no therapy for hearing loss, evidence supports investigating the enhancement of the Medial Olivocochlear (MOC) System, an efferent pathway for hearing that serves as a gain-control for hearing loss protection. Selectively modulating the α9α10 nicotinic acetylcholine receptor (nAChRs) found within this pathway is promising for the development of a new drug class. In this review article, we present the most current findings related to the therapeutic targeting of α9α10 nAChRs for hearing loss. We discuss the loss- or gain-of-function of the receptor, evaluate the known modulators of the receptor, examine their clinical relevance, and discuss their chemical and physical properties. Investigation of this novel pathway may aid in the development of a therapeutic for hearing loss. Full article

Distributed generation (DG) exhibits inherent volatility and intermittency, and its grid-integration expansion presents formidable challenges to microgrid regulation and control. Conventional control strategies often neglect the uncertainties associated with renewable energy generation and the coordinated management of flexible resources. This paper proposes a multi-time-scale optimal control strategy for microgrids that explicitly accounts for uncertainty. The strategy integrates a collaborative scheduling framework for assets, including electric vehicles (EVs) and energy storage systems, alongside a stochastic optimization model for microgrids that comprehensively incorporates uncertainties from wind and solar power generation, EV operations, and load forecasting errors. The improved Archimedean chaotic adaptive whale optimization algorithm is utilized to solve the optimal scheduling model, while the Latin hypercube sampling (LHS) technique is employed to address uncertainty-related problems in the optimization process. Case study results demonstrate that, in comparison with traditional optimal scheduling strategies, the proposed approach more effectively mitigates uncertainties in real-world operations, reduces microgrid operational risks, achieves a significant reduction in scheduling costs, and concurrently fulfills the dual objectives of microgrid economic efficiency and operational security. Full article

While direct current (DC) ice-melting is currently adopted for some transmission lines, its application to 10 kV distribution transformers—often located in remote and rugged terrain—presents significant operational challenges. Disconnecting these transformers prior to ice-melting is a complex procedure that incurs substantial labor, material, and financial costs. Leaving transformers connected risks DC current flowing into idle windings, potentially causing damage. Furthermore, existing mobile DC ice-melting power supplies are bulky and impose stringent transportation requirements, rendering them unsuitable for use on mountain roads. To overcome these limitations, this paper proposes a compact, lightweight variable-frequency ice-melting device. The operating principle and output characteristics of the variable-frequency method are investigated in detail. Using Simulink, system modeling and simulation analyses are performed to obtain the voltage and current output characteristics, along with harmonic spectra. Simulation results demonstrate that the proposed device achieves significant miniaturization compared with conventional solutions: within the typical parameter range of conventional devices, the volume can be reduced by 44–58% and the weight by 43–52%. In addition, the selected LC filter parameters (L = 10.39 mH, C = 86.62 μF) represent an optimized compromise solution that effectively suppresses input harmonics while maintaining the output current total harmonic distortion (THD) within an acceptable limit of 3.6%. Experimental results further validate the feasibility of the variable-frequency ice-melting current. Based on a matrix converter topology, the proposed device enables flexible adjustment of the output melting voltage and frequency, exhibits excellent low-frequency performance and dynamic response, and maintains low output harmonic content—fully meeting the application requirements for variable-frequency ice-melting. The key novelty lies in a compact matrix-converter-based de-icing device with systematic low-frequency performance analysis, offering superior portability and adaptability over traditional DC solutions. Full article

Background/Objectives: Postoperative pulmonary complications (PPCs) following abdominal surgery are associated with prolonged hospitalization, delayed recovery, and increased mortality. Because nursing surveillance is essential for early detection and timely intervention, this study aimed to develop a holistic nursing surveillance decision support system integrating PPC risk prediction with structured nursing action recommendations. Methods: In this retrospective cohort study, electronic medical record (EMR) data from approximately 6900 adult patients who underwent abdominal surgery at a single institution between January 2015 and September 2023 were analyzed. The study protocol was approved by the Institutional Review Board, and the requirement for informed consent was waived because of the retrospective study design. PPC risk was predicted using a tabular multilayer perceptron (MLP) encoder with SHapley Additive exPlanations (SHAP)-based feature weighting and a random forest classification head optimized via Optuna. Class imbalance was addressed using weighted sampling, class weighting in BCE(Binary Cross Entropy) With Logits Loss, and decision-threshold optimization. For clinical decision support, a large language model generated structured nursing surveillance recommendations in an action–evidence–rationale JSON format and was aligned through supervised fine-tuning (SFT) using human-evaluated cases. Results: The prediction model achieved an AUROC of 0.810, with an accuracy of 0.811, precision of 0.547, and recall of 0.545. In expert evaluation, the SFT-aligned model improved recommendation quality, reducing incorrect nursing actions from 19.3% to 8.0%. Conclusions: The proposed system demonstrates the feasibility of an end-to-end nursing surveillance decision support framework linking PPC risk prediction with structured clinical recommendations. The findings suggest its potential to support more accurate risk prediction and more actionable nursing surveillance for patients undergoing abdominal surgery. Full article

Soil contamination in Sub-Saharan Africa (SSA) is increasingly driven by rapid industrialization, intensive agriculture, mining activities, and urban expansion, posing significant risks to food safety, ecosystem services, and human livelihoods. Despite the growing scale of the problem, low-cost, locally adaptable remediation technologies are widely available and technically feasible within the region. Organic waste and waste-derived products—such as compost, manure, biochar, vermicompost, digestate, and agro-industrial residues—have emerged as sustainable and cost-effective amendments for the remediation of contaminated soils. These materials can immobilize heavy metals, enhance the microbial degradation of organic pollutants, and improve soil health, making them especially suitable for resource-constrained settings. This review synthesizes the current knowledge on the use of organic waste-based remediation approaches in SSA, highlighting technologies already applied at the laboratory, pilot, and field scales, as well as their effectiveness across different contaminant types. However, despite their demonstrated potential, their widespread adoption remains limited. The primary challenge is not the absence of affordable solutions, but rather the systemic constraints characteristic of many SSA countries, including limited technical capacity, weak policy and regulatory frameworks, low stakeholder awareness, and insufficient financial and institutional support for large-scale implementation. To enable broader uptake, there is a need to strengthen waste segregation and treatment systems, standardize composting and pyrolysis processes, and develop robust regulatory guidelines and certification schemes. Investments in monitoring infrastructure, practitioner training, and knowledge transfer mechanisms will also be critical to translating scientific advances into scalable, field-ready solutions for sustainable soil remediation in SSA. Full article

Phospholipid transfer protein (PLTP) is a lipid transfer protein classically studied in the context of plasma lipoprotein metabolism, high-density lipoprotein (HDL) remodeling, and cardiovascular disease risk. PLTP facilitates phospholipid transfer between lipoproteins and regulates HDL particle size and composition through interactions with apolipoprotein A-I and apolipoprotein A-II. While its systemic roles in cholesterol handling, reverse cholesterol transport, and inflammatory signaling are well established, the cell-autonomous functions of PLTP within cardiomyocytes remain poorly defined, particularly in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Extensive experimental and clinical studies demonstrate that PLTP enhances ABCA1-dependent cholesterol efflux primarily by stabilizing ABCA1 at the plasma membrane and by promoting the generation of lipid-poor apolipoprotein A-I and pre-β HDL particles, which serve as efficient cholesterol acceptors; the magnitude of these effects depends on cellular context, PLTP expression levels, and the availability of lipid acceptors. PLTP expression is metabolically regulated and widely distributed across tissues, including macrophages and other non-hepatic cells, supporting roles beyond circulating lipoprotein remodeling. Altered PLTP activity has been linked to atherosclerosis, cardiovascular disease, and inflammatory pathways, underscoring its relevance to cardiac pathophysiology. Emerging evidence further suggests that intracellular cholesterol distribution, rather than total cholesterol content alone, critically influences mitochondrial membrane composition, bioenergetics, and stress signaling in cardiomyocytes. These observations raise the possibility that PLTP-regulated lipid flux may indirectly shape mitochondrial function by modulating cellular cholesterol homeostasis. This review synthesizes current knowledge of PLTP biology, cholesterol metabolism, and lipoprotein remodeling, and integrates these concepts with emerging frameworks in cardiomyocyte lipid metabolism and mitochondrial physiology. We highlight human iPSC-derived cardiomyocytes as a strategic and translationally relevant platform to investigate PLTP’s non-canonical, cell-intrinsic roles, identify critical knowledge gaps, and propose future directions for elucidating how PLTP may influence mitochondrial function in human cardiac cells. Full article

Recent advances in machine design, automation, and industrial digitalization have transformed Coordinate Measuring Machines (CMMs) from standalone inspection devices into fully integrated elements of automated manufacturing systems. In the automotive sector, CMMs increasingly operate in workshop, near-line, and in-line environments, interacting with production equipment and contributing directly to process control and zero-defect manufacturing strategies. This paper presents a structured methodology for the industrial deployment of automated CMMs in automotive mechanical manufacturing. The proposed approach is illustrated through an industrial use case involving the dimensional inspection of mechanically machined components under real production conditions. The methodology addresses machine design selection, sensor configuration, environmental constraints, and multi-axis architectures, as well as validation and acceptance procedures based on the ISO 10360 series. Particular attention is given to the integration of CMMs within automated manufacturing systems, including robustness against thermal variations, vibrations, and contamination, and the use of metrological data for feedback to machining processes. Rather than introducing new metrological principles, the proposed approach focuses on the structured integration of established engineering practices into a coherent lifecycle-based deployment framework. Based on industrial experience, the proposed methodology is illustrated through an industrial case study to support the reliable of automated dimensional inspection, reduce measurement-related risks, and support the integration of CMMs as active components of modern automated manufacturing systems. Full article

The Internet of Medical Things (IoMT) is becoming a vital part of modern healthcare, enabling ongoing patient monitoring and remote diagnosis. However, as more devices connect to the internet, healthcare systems become more vulnerable to serious security issues such as unauthorized access, patient data manipulation, and Man-in-the-Middle attacks. Conventional Intrusion Detection Systems (IDSs) often struggle with the unclear and uncertain characteristics of IoMT traffic, which leads to reduced detection accuracy and increased false alarms. To address these challenges, this paper proposes ML-FSID-FIS, a multi-level feature selection-based Intrusion Detection System that employs a fuzzy inference system (FIS) for classification in IoMT networks. The model combines multiple feature selection techniques into a three-stage multi-level feature selection strategy to improve detection efficiency and strengthen the security of IoMT networks. In the first stage, four feature selection techniques—Random Forest, XGBoost, ReliefF, and Mutual Information—are applied to identify the most relevant features. In the second stage, a frequency-based consensus strategy is utilized to extract consistently selected features from the four top-ranked sets. In the third stage, an ensemble refinement using bagging-based ranking is employed to rank the remaining features, resulting in the selection of the top five features. From these, three candidate 3-feature groups are formed and evaluated, and the best-performing group is selected as the final input set for the fuzzy logic classifier. The FIS produces a continuous risk score that is mapped to a binary decision using a validation-selected threshold. When the proposed method was tested on the WUSTL-EHMS-2020 dataset and compared with other recent work using the same dataset, it showed strong detection performance while maintaining a very low false positive rate of 0.3%. This study is distinguished by its integrated design, which combines a three-stage multi-level feature selection strategy with fuzzy logic-based intrusion classification to improve feature efficiency and support interpretable intrusion detection in IoMT. Full article

Background/Objectives: Stress experienced by families of individuals with illnesses or disabilities is shaped through the interaction of multiple complex influencing factors. This study aimed to elucidate the factors influencing stress in families of young/adult children with illnesses or disabilities, using Family System Unit Stress Theory (FSUST) as the guiding theoretical framework. Methods: Semi-structured interviews were conducted with 10 families of young/adult children with illnesses or disabilities. Data were analyzed using qualitative content analysis following the approach of Graneheim and Lundman. In line with FSUST, the identified influencing factors were categorized into negative factors (risk/causal/promoting) and positive factors (preventive/inhibitory/suppressive). Results: A total of six categories and 18 subcategories were extracted for the risk/causal/promoting factors, including “accumulation of unshared burdens within the family leading to role overload” and “concerns about the future of the young/adult child.” For the preventive/inhibitory/suppressive factors, five categories and 13 subcategories were extracted, including “receiving a diagnosis of the young/adult child’s illness or disability” and “family maintaining a positive attitude.” Conclusions: Family stress in families of young/adult children with illnesses or disabilities varies through the interaction of multilayered influencing factors, including persistent emotions carried over from the past, difficulties faced in the present, and anticipatory concerns regarding the future. Therefore, nursing practice requires a life course-oriented understanding of family stress and an integrated approach that concurrently reduces risk/causal/promoting factors while enhancing preventive/inhibitory/suppressive factors. Full article

Cadmium (Cd) contamination is widely recognized as a major risk factor affecting the security and quality of crop production. Watermelon (Citrullus lanatus) is a globally cultivated fruit that is susceptible to Cd stress. 24-Epibrassinolide (EBR), an active brassinosteroid, is essential for plant growth and abiotic stress responses. However, its protective role in watermelon under Cd stress remains unclear. This study elucidates the physiological and molecular processes underlying EBR-mediated alleviation of Cd toxicity in watermelon seedlings. The results showed that exogenous EBR application effectively mitigated Cd-induced growth inhibition through decreased Cd deposition, reduced the accumulation of reactive oxygen species (ROS), lowered membrane lipid peroxidation, and increased antioxidant capacity in watermelon leaves under Cd treatment. Transcriptome (RNA-Seq) analysis revealed that EBR triggered substantial reprogramming of gene expression patterns, identifying 530 differentially expressed genes (DEGs) in Cd + EBR co-treatment compared with Cd treatment alone, including 204 down-regulated genes and 326 up-regulated genes. These DEGs are vital for controlling several physiological processes, including phenylpropane metabolism, phenylpropanoid biosynthesis, endoplasmic reticulum’s protein production, cell wall organization, and others. Further physiological assays confirmed that EBR increased the activities of PAL and 4CL, the core enzymes driving phenylpropanoid biosynthesis, leading to a significant accumulation of total phenols and flavonoids. Together, the above results give concrete proof of the powerful functions of 24-EBR, acting as an enhancer of plant performance under Cd stress by enhancing the antioxidant system and by activating the phenylpropanoid pathway and its derived metabolic networks. Full article