Search Results (1,017)

African swine fever (ASF) is a highly contagious viral disease with significant impacts on domestic pigs and wild boar populations. This study applies GIS-based spatial analysis to monitor ASF outbreaks in northwestern Italy (Piedmont and Liguria) and identify areas at increased risk. Key factors considered include pig density, wildlife proximity, and environmental conditions. The spatial analysis revealed that central–western municipalities exhibited higher risk due to favorable environmental conditions and dense wild boar populations, while peripheral areas showed a temporal delay in outbreak emergence. Mapping the spreading rate and habitat interfaces allowed the development of a spatial risk model, which was further analyzed using geostatistical techniques to understand disease dynamics. The results demonstrate the effectiveness of geospatial modeling in identifying high-risk zones, characterizing spatio-temporal patterns, and supporting targeted prevention and surveillance strategies. These findings provide actionable insights for ASF management and resource allocation. Future studies may refine these models by integrating additional datasets and environmental variables, enhancing predictive capacity and applicability across different regions. Full article

The lung is increasingly recognized as an organ with dual endocrine and respiratory roles, participating in a complex bidirectional crosstalk with systemic hormones and local/paracrine activity. Endocrine and paracrine pathways regulate lung development, ventilation, immunity, and repair, while pulmonary cells express hormone receptors and secrete mediators with both local and systemic effects, defining the concept of the “endocrine lung”. This narrative review summarizes current evidence on the endocrine–pulmonary axis. Thyroid hormones, glucocorticoids, sex steroids, and metabolic hormones (e.g., insulin, leptin, adiponectin) critically influence alveologenesis, surfactant production, ventilatory drive, airway mechanics, and immune responses. Conversely, the lung produces mediators such as serotonin, calcitonin gene-related peptide, endothelin-1, leptin, and keratinocyte growth factor, which regulate vascular tone, alveolar homeostasis, and immune modulation. We also describe the respiratory manifestations of major endocrine diseases, including obstructive sleep apnea and lung volume alterations in acromegaly, immunosuppression and myopathy in Cushing’s syndrome, hypoventilation in hypothyroidism, restrictive “diabetic lung”, and obesity-related phenotypes. In parallel, chronic pulmonary diseases such as chronic obstructive pulmonary disease, interstitial lung disease, and sleep apnea profoundly affect endocrine axes, promoting insulin resistance, hypogonadism, GH/IGF-1 suppression, and bone metabolism alterations. Pulmonary neuroendocrine tumors further highlight the interface, frequently presenting with paraneoplastic endocrine syndromes. Finally, therapeutic interactions are discussed, including the risks of hypothalamic–pituitary–adrenal axis suppression with inhaled corticosteroids, immunotherapy-induced endocrinopathies, and inhaled insulin. Future perspectives emphasize mapping pulmonary hormone networks, endocrine phenotyping of chronic respiratory diseases, and developing hormone-based interventions. Full article

This study aimed to evaluate how different insertion angles of titanium orthodontic miniscrews (30°, 45°, and 90°) influence stress distribution and displacement in surrounding alveolar bone using three-dimensional finite element analysis (FEA), with a focus on biomechanical outcomes at the titanium–bone interface. The 90° insertion angle generated the highest stress in cortical bone (58.2 MPa) but the lowest displacement (0.023 mm), while the 30° angle produced lower stress (36.4 MPa) but greater displacement (0.052 mm). The 45° angle represented a compromise, combining moderate stress (42.7 MPa) and displacement (0.035 mm). This simulation-based study was conducted between January and April 2025 at the Department of Orthodontics, Kocaeli Health and Technology University. A standardized 3D mandibular bone model (2 mm cortical and 13 mm cancellous layers) was constructed, and Ti-6Al-4V miniscrews (1.6 mm × 8 mm) were virtually inserted at 30°, 45°, and 90°. A horizontal orthodontic load of 2 N was applied, and von Mises stress and displacement values were calculated in ANSYS Workbench. Stress patterns were visualized using color-coded maps. The 90° insertion angle generated the highest von Mises stress in cortical bone (50.6 MPa), with a total maximum stress of 58.2 MPa, followed by 45° (42.7 MPa) and 30° (36.4 MPa) insertions (p < 0.001). Stress was predominantly concentrated at the cortical entry point, especially in the 90° model. In terms of displacement, the 90° group exhibited the lowest mean displacement (0.023 ± 0.002 mm), followed by 45° (0.035 ± 0.003 mm) and 30° (0.052 ± 0.004 mm), with statistically significant differences among all groups (p < 0.001). The 45° angle showed a balanced biomechanical profile, combining moderate stress and displacement values, as confirmed by post hoc analysis. From a biomimetics perspective, understanding how insertion angle affects bone response provides insights for designing bio-inspired anchorage systems. By simulating natural stress dissipation, this study demonstrates that insertion angle strongly modulates miniscrew performance. Vertical placement (90°) ensures rigidity but concentrates cortical stress, whereas oblique placement, particularly at 45°, offers a balanced compromise with adequate stability and reduced stress. These results emphasize that beyond material properties, surgical parameters such as insertion angle are critical for clinical success. Full article

To investigate hydraulic fracture propagation in multi-layered porous media such as sand–coal interbedded formations, we present a new phase-field-based model. In this formulation, a diffuse fracture is activated only when the local element strain exceeds the rock’s critical strain, and the fracture width is represented by orthogonal components in the x and y directions. Unlike common PFM approaches that map the permeability directly from the damage field, our scheme triggers fractures only beyond a critical strain. It then builds anisotropy via a width-to-element-size weighting with parallel mixing along and series mixing across the fracture. At the element scale, the permeability is constructed as a weighted sum of the initial rock permeability and the fracture permeability, with the weighting coefficients defined as functions of the local width and the element size. Using this model, we examined how the in situ stress contrast, interface strength, Young’s modulus, Poisson’s ratio, and injection rate influence the hydraulic fracture growth in sand–coal interbedded formations. The results indicate that a larger stress contrast, stronger interfaces, a greater stiffness, and higher injection rates increase the likelihood that a hydraulic fracture will cross the interface and penetrate the barrier layer. When propagation is constrained to the interface, the width within the interface segment is markedly smaller than that within the coal-seam segment, and interface-guided growth elevates the fluid pressure inside the fracture. Full article

Discrimination between normal (fresh/non-frozen) and frozen-thawed beef is crucial for ensuring food safety. This paper proposed a novel, non-destructive and real-time you only look once for normal and frozen-thawed beef discrimination (YOLO-NF) model using deep learning techniques. The simple, parameter-free attention module (SimAM) and the squeeze and excitation (SE) attention mechanism were introduced to enhance the model’s performance. A total of 1200 beef samples were used, with their images captured by a charge-coupled device (CCD) camera. In the model development, specifically, the training set comprised 3888 images after data augmentation, while the validation set and test set each included 216 original images. Experimental results on the test set showed that the YOLO-NF model achieved precision, recall, F1-Score and mean average precision (mAP) of 95.5%, 95.2%, 95.3% and 98.6%, respectively, significantly outperforming YOLOv7, YOLOv5 and YOLOv8 models. Additionally, gradient-weighted class activation mapping (Grad-CAM) was adopted to interpret the model’s decision basis. Moreover, the model was deployed on the web interface for user convenience, and the discrimination time on the local server was 0.94 s per image, satisfying the requirements for real-time processing. This study provides a promising technique for high-performance and rapid meat quality assessment in food safety monitoring systems. Full article

Conventional wildfire assessment products emphasize regional-scale ignition likelihood and potential spread derived from fuels and weather. While useful for broad planning, they do not directly support boundary-aware, scenario-specific decision-making for localized threats to communities in the Wildland–Urban Interface (WUI). This limitation constrains the ability of fire managers to effectively prioritize mitigation efforts and response strategies for ignition events that may lead to severe local impacts. This paper introduces WUI-BTI—a scenario-based, simulation-driven boundary-threat index for the Wildland–Urban Interface that quantifies consequences conditional on an ignition under standardized meteorology, rather than estimating risk. WUI-BTI evaluates ignition locations—referred to as Fire Amplification Sites (FAS)—based on their potential to compromise the defined boundary of a community. For each ignition location, a high-resolution fire spread simulation is conducted. The resulting fire perimeter dynamics are analyzed to extract three key metrics: (1) the minimum distance of fire approach to the community boundary ($D_{min}$) for non-breaching fires; and for breaching fires, (2) the time required for the fire to reach the boundary ($T_p$), and (3) the total length of the community boundary affected by the fire ($L_c$). These raw outputs are mapped through monotone, sigmoid-based transformations to yield a single, interpretable score: breaching fires are scored by the product of an inverse-time urgency term and an extent term, whereas non-breaching fires are scored by proximity alone. The result is a continuous boundary-threat surface that ranks ignition sites by their potential to rapidly and substantially compromise a community boundary. By converting complex simulation outputs into scenario-specific, boundary-aware intelligence, WUI-BTI provides a transparent, quantitative basis for prioritizing fuel treatments, pre-positioning suppression resources, and guiding protective strategies in the WUI for fire managers, land use planners, and emergency response agencies. The framework complements regional hazard layers (e.g., severity classifications) by resolving fine-scale, consequence-focused priorities for specific communities. Full article

Surface water resources are under growing pressure from urbanization, industrial activity, and agriculture, making effective monitoring essential for safeguarding ecological integrity and human use. Conventional monitoring methods, which rely on manual sampling and rigid Water Quality Index (WQI) categories, often provide delayed feedback and oversimplify conditions near classification thresholds, limiting their usefulness for timely management. To overcome these shortcomings, we have developed an interactive fuzzy logic-based water quality monitoring interface or dashboard that integrates the WQI developed by Malaysia’s Department of Environment with the National Water Quality Standards (NWQS) Class I–V framework. The interface combines conventional WQI computation with advanced visualization tools such as dynamic gauges, parameter tables, fuzzy membership graphs, scatter plots, heatmaps, and bar charts. Then, triangular membership functions map six key parameters to NWQS classes, providing smoother and more nuanced interpretation compared to rigid thresholds. In addition to that, the dashboard enables clearer communication of trends, supports timely decision-making, and demonstrates adaptability for broader applications since it is implemented on the Replit platform. Finally, evaluation results show that the fuzzy interface improves interpretability by resolving ambiguities in over 15% of cases near class boundaries and facilitates faster assessment of pollution trends compared to conventional reporting. Thus, these contributions highlight the necessity and value of the research on advancing Malaysia’s national water quality monitoring and providing a scalable framework for international contexts. Full article

Background: This article presents an international comparative review of involuntary psychiatric care, Community Treatment Orders (CTOs), and forensic mental health services, with operational implications for Italy. Italy has a community-based model inspired by the “Basaglia Law” (Law No. 180/1978), emphasizing deinstitutionalization and continuity of care. Nevertheless, risk governance gaps persist for high-complexity patients, imposing a disproportionate legal and clinical burden on mental health professionals. This group includes individuals who refuse treatment despite meeting criteria for compulsory admission, patients at elevated risk with substantial management complexity, and offenders with a current or suspected psychiatric disorder. Methods: We conducted a comparative legal and policy review across seven jurisdictions (Italy, England and Wales (UK), France, Germany, Spain, the United States, and Canada) to map frameworks for involuntary treatment, forensic services, CTOs (or equivalents), and community-based risk management. We also extracted procedural safeguards, duration and renewal limits, and interfaces with forensic services. Results: CTOs are available in five of the seven jurisdictions (England and Wales, France, Spain, the United States, and Canada) but are absent in Italy and Germany. We propose a three-pillar framework: (1) enforceable outpatient measures, including CTOs; (2) Forensic Psychiatry Units within Local Health Authorities; and (3) oversight boards with judicial, clinical, and social representatives. These components aim to redistribute responsibility, ensure continuity of care, and provide proportional oversight within a least restrictive, graduated system. Conclusions: When narrowly targeted, time limited, and paired with robust safeguards and service-quality standards, CTOs can support adherence and continuity for patients who repeatedly disengage from care. For Italy, integrating this instrument within the three-pillar framework and under independent oversight could strengthen patient rights and public safety, reduce revolving-door admissions, and improve outcomes. Full article

The tumour suppressor protein p53 plays a central role in safeguarding genomic integrity through the regulation of DNA repair, cell cycle arrest, and apoptosis. Mutations in TP53, particularly within its DNA-binding domain, are among the most frequent genetic alterations in human cancers and are strongly associated with chemoresistance and poor prognosis. In this study, all TP53 mutations reported in the COSMIC database were systematically mapped onto all experimentally resolved TP53 three-dimensional structures available in the Protein Data Bank, supplemented with AlphaFold-predicted models to achieve full structural coverage. Mutations were classified according to their structural context—protein core, interface regions, ligand- and zinc-binding sites, and intrinsically disordered regions—and evaluated using complementary sequence- and structure-based predictive tools. The analysis revealed distinct mutational hotspots, differential distribution across structural regions, and context-dependent effects on stability and DNA-binding capacity. Notably, a subset of mutations exhibited consistent predictions of high destabilisation across all structural contexts, underscoring their potential as drivers of functional inactivation. By providing a comprehensive structural map of TP53 alterations, this work offers a valuable resource for understanding mutation-specific mechanisms of p53 dysfunction and for guiding the development of precision therapeutic strategies aimed at restoring its tumour-suppressive functions. Full article

Multi-camera systems (MCSs) are pivotal in aviation surveillance and autonomous navigation due to their wide coverage and high-resolution sensing. However, challenges such as complex setup, time-consuming data acquisition, and costly testing hinder research progress. To address these, we introduce MCS-Sim, a photo-realistic MCSsimulator for UAV visual perception research. MCS-Sim integrates vision sensor configurations, vehicle dynamics, and dynamic scenes, enabling rapid virtual prototyping and multi-task dataset generation. It supports dense flow estimation, 3D reconstruction, visual simultaneous localization and mapping, object detection, and tracking. With a hardware-in-loop interface, MCS-Sim facilitates closed-loop simulation for system validation. Experiments demonstrate its effectiveness in synthetic dataset generation, visual perception algorithm testing, and closed-loop simulation. Here we show that MCS-Sim significantly advances multi-camera UAV visual perception research, offering a versatile platform for future innovations. Full article

Governments increasingly integrate artificial intelligence (AI) into digital public services, and understanding how citizens perceive and respond to these technologies has become essential. This systematic review analyzes 30 empirical studies published from early January 2019 to mid-April 2025, following PRISMA guidelines, to map the current landscape of citizen attitudes toward AI-enabled e-government services. Guided by four research questions, the study examines: (1) the forms of AI implementation most commonly investigated, (2) the attitudinal variables used to assess user perception, (3) key factors influencing attitudes, and (4) concerns and challenges reported by users. The findings reveal that chatbots dominate current implementations, with behavioral intentions and satisfaction serving as the main outcome measures. Perceived usefulness, ease of use, trust, and perceived risk emerge as recurring determinants of positive attitudes. However, widespread concerns related to privacy and interface usability highlight persistent barriers. Overall, the review underscores the need for transparent, citizen-centered AI design and ethical safeguards to enhance acceptance and trust. It concludes that future research should address understudied applications, include vulnerable populations, and explore perceptions across diverse public sector domains. Full article

Coastal public spaces in large Euro-Mediterranean cities represent critical zones of negotiation between land and sea, where ecological fragilities, infrastructural pressures and social demands intersect. Grounded in the concept of the urban amphibious, this study explores the spatial-functional complexity of city-sea interfaces through the development of CITI4SEA (City-Sea Interface Typological Indicators for Spatial-Ecological Assessment), an original multidimensional framework for the evaluation of coastal public spaces. The methodology builds on a geo-database of 149 coastal municipalities in eight EU Member States and applies a set of indicators to seven major cities (with populations over 500,000 and comprehensive port infrastructure). Through a structured evaluation grid applied to 23 coastal public spaces, the framework enables a cross-comparative analysis of spatial configurations, ecological qualities, and patterns of public use. Results reveal the emergence of transnational clusters based on shared planning logics and degrees of socio-environmental integration, rather than geographic proximity. The study also identifies asymmetries in accessibility, environmental performance and equipment provision. Beyond mapping spatial disparities, the contribution offers a replicable tool for assessing littoral transformations within the broader framework of Integrated Coastal Zone Management (ICZM) and Maritime Spatial Planning (MSP), supporting context-specific strategies for resilient and inclusive coastal governance. Full article

Coastal vegetated ecosystems, including tidal marshes, vegetated dunes, and shrub- and forest-dominated wetlands, can mitigate hurricane impacts such as coastal flooding and erosion by increasing surface roughness and reducing wave energy. Land cover maps can be used as input to improve simulations of surface roughness in advanced hydro-morphological models. Consequently, there is a need for efficient tools to develop up-to-date land cover maps that include the accurate distribution of vegetation types prior to an extreme storm. In response, we developed the RUSH tool (Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models). RUSH delivers high-resolution maps of coastal vegetation for near-real-time or historical conditions via a Jupyter Notebook application and a graphical user interface (GUI). The application generates 3 m spatial resolution land cover maps with classes relevant to coastal settings, especially along mainland beaches, headlands, and barrier islands, as follows: (1) open water; (2) emergent wetlands; (3) dune grass; (4) woody wetlands; and (5) bare ground. These maps are developed by applying one of two seasonal random-forest machine learning models to Planet Labs SuperDove multispectral imagery. Cool Season and Warm Season Models were trained on 665 and 594 reference points, respectively, located across study regions in the North Carolina Outer Banks, the Mississippi Delta in Louisiana, and a portion of the Florida Gulf Coast near Apalachicola. Cool Season and Warm Season Models were tested with 666 and 595 independent points, with an overall accuracy of 93% and 94%, respectively. The Jupyter Notebook application provides users with a flexible platform for customization for advanced users, whereas the GUI, designed with user-experience feedback, provides non-experts access to remote sensing capabilities. This application can also be used for long-term coastal geomorphic and ecosystem change assessments. Full article

This paper presents ALMODES, a discrete-time modeling approach for social systems that uses matrix algebra and directed graphs. The method bridges the gap between static network analysis and continuous System Dynamics, offering a transparent framework that reduces data requirements. The method enables clear causal mapping, rapid simulation, straightforward sensitivity analysis, and natural hybridization with agent-based or discrete-event models. Two case studies illustrate its utility for sustainable-development strategy: in an urban public-health setting, modernization and sanitation policies drive sustained declines in disease despite growth, whereas reversing the population-to-modernization link triggers a morbidity rebound that can be prevented by strengthening the modernization-to-sanitation pathway; in a high-tech services Balanced Scorecard model, a baseline backlog spike depresses customer satisfaction, aggressive hiring shortens the spike but erodes income, and coordinated boosts to training and incentives (about twelve percent productivity gain) remove the backlog early, stabilize customers, and improve income, highlighting human-capital policy as a robust lever. ALMODES thus supports pragmatic policy design under limited, expert-elicited parameters. Future research will address uncertainty quantification, time-varying structures and shocks, automated calibration and empirical validation at scale, optimization and control design, richer integration with hybrid simulation, participatory interfaces for stakeholders, and standardized benchmarks across domains. Full article

Arch structure is a crucial interface between the human body and the ground during landing tasks, but the biomechanical effects of arch support stiffness remain insufficiently explored. This study examines the effects of arch supports with different stiffnesses on lower-limb biomechanics during landing. Twelve male participants (six normal arches, six flat feet) performed a single-leg drop landing from a 45 cm height under four arch support conditions: no arch support pad (NAP), soft-stiffness arch support pad (SAP), medium-stiffness arch support pad (MAP), and high-stiffness arch support pad (HAP). Dominant lower-limb joint angles and moments in the sagittal plane and vertical ground reaction force (vGRF)-related parameters—time to peak vGRF, peak vGRF, and max loading rate—were recorded using a motion capture system and force plate. Data were analyzed using one-way repeated measures analysis of variance (ANOVA). Arch pad stiffness significantly affected ankle and knee kinematics. The NAP condition exhibited significantly higher ankle plantarflexion at initial contact (p ≤ 0.01), as well as larger range of motion (ROM) of the knee (p = 0.03) and hip (p < 0.01), compared to the use of a SAP or MAP. The use of a HAP resulted in a significantly lower peak ankle dorsiflexion moment and larger peak knee flexion angle than the other conditions (p ≤ 0.04). The peak knee extension moment was the highest when using a NAP, and was significantly higher than that shown with the use of a MAP or HAP (p ≤ 0.02). No significant differences were observed in hip joint moments or vGRF-related parameters across conditions (p ≥ 0.52). These results indicate that hard-stiffness arch support pads modulate lower-limb mechanics during landing, potentially enhancing shock absorption and reducing knee loading. Full article