Search Results (967)

Agricultural drought, increasingly intensified by climate change, poses a significant threat to food security and water resources in semi-arid regions, including Türkiye’s Konya Closed Basin. This study evaluates six satellite-derived indices—Vegetation Health Index (VHI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI), Evapotranspiration Condition Index (ETCI), and Soil Moisture Condition Index (SMCI)—to monitor agricultural drought (2001–2024) and proposes a drought vulnerability map using a novel Drought Vulnerability Index (DVI). Integrating Moderate Resolution Imaging Spectroradiometer (MODIS), Climate Hazards Center InfraRed Precipitation with Station (CHIRPS), and Land Data Assimilation System (FLDAS) datasets, the DVI combines these indices with weighted contributions (VHI: 0.27, ETCI: 0.25, SMCI: 0.22, PCI: 0.26) to spatially classify vulnerability. The results highlight severe drought episodes in 2001, 2007, 2008, 2014, 2016, and 2020, with extreme vulnerability concentrated in the southern and central basin, driven by prolonged vegetation stress and soil moisture deficits. The DVI reveals that 38% of the agricultural area in the basin is classified as moderately vulnerable, while 29% is critically vulnerable—comprising 22% under high vulnerability and 7% under extreme vulnerability. The proposed drought vulnerability map offers an actionable framework to support targeted water management strategies and policy interventions in drought-prone agricultural systems. Full article

Integrating human–robot collaboration (HRC) into construction sites has significantly enhanced efficiency and quality. However, it also introduces new or intensifies existing risks as it brings in new entities, relationships, and construction activities. Safety remains the top priority and a persistent concern in HRC systems. However, the current literature on human–robot collaboration safety (HRCS) is vast yet fragmented, and a systematic exploration of its status and research trends in the construction context is still lacking. This paper explores advances in HRCS over the past two decades through a mixed quantitative and qualitative analysis method. Initially, 287 related articles were identified by keyword-searching in Scopus, followed by bibliometric analysis using CiteSpace to uncover the knowledge structure and track emerging research trends. Subsequently, a qualitative discussion highlights achievements in HRCS across five dimensions: (1) optimization of remote intelligent machinery; (2) hazard analysis and risk assessment in HRCS; (3) digital twin for safety monitoring; (4) cognitive and psychological impacts; (5) organizational management perspective. This study quantitatively maps the scientific landscape of HRCS at a macro level and qualitatively identifies key research areas. It provides a comprehensive foundation for understanding the evolution of HRCS and exploring future research directions and applications. Full article

Background and Aim: Food hygiene is fundamental to public health, ensuring safe and nutritious food free from contaminants, and is vital for economic development and sustainability. The Hazard Analysis and Critical Control Points (HACCP) system is a crucial tool for managing risks in food production. Despite global recognition of food safety’s importance, significant disparities exist, especially in Southern Italy, where diverse food production, tourism, and economic factors pose challenges to enforcing hygiene standards. This study evaluates non-compliance with food hygiene regulations within a Local Health Authority (LHA) in Calabria, Southern Italy, to inform effective public health strategies. Materials and Methods Authorized by the Food Hygiene and Nutrition Service (FHNS) of the LHA, the study covers January 2022 to December 2024, analyzing 579 enterprises with 1469 production activities. Inspections followed EC Regulation No. 852/2004, verifying the correct application of procedures based on the Hazard Analysis and Critical Control Points (HACCP) principles, including the operator’s monitoring of Critical Control Points (CCPs), and adherence to Good Hygiene Practices (GHPs). Non-compliances were classified by severity, and corrective and punitive actions were applied. Data were analyzed annually and across the full period using descriptive statistics and chi-squared tests to assess trends. Results: Inspection coverage increased markedly from 29.8% of production activities in 2022 to 62.5% in 2023, sustaining 62.0% in early 2024, exceeding the growth of new activities. Inspections were mainly triggered by RASFF alerts (22.4%), routine controls (20.0%), and verification of previous prescriptions (14.3%). The most frequent corrective measures were long-term prescriptions (28.6%), violation reports (22.9%), and short-term prescriptions (20.0%). Enterprises averaged 4.61 production activities, highlighting operational complexity. Conclusions: This study provides a granular analysis of food hygiene non-compliance within a Local Health Authority (LHA) in Southern Italy, to inform effective public health strategies. While official control data may be publicly available in some contexts, our research offers a unique, in-depth view of inspection triggers, non-compliance patterns, and corrective measures, which is crucial for understanding specific regional challenges. The analysis reveals that the prevalence of long-term prescriptions and reliance on RASFF alerts indicate systemic challenges requiring sustained interventions. Full article

Medicinal plants remain central to traditional healthcare, yet their increasing integration into modern pharmacology necessitates robust toxicological evaluation. Origanum majorana L. (sweet marjoram), widely used in culinary and folk medicine, contains diverse secondary metabolites with both therapeutic and potential genotoxic activities. Despite its popularity, systematic in vivo and in vitro safety assessments remain limited. This study aimed to comprehensively evaluate the acute oral toxicity, cytotoxicity, and genotoxicity of O. majorana methanolic extract, providing baseline toxicological data to support its safe traditional use and potential pharmaceutical applications. The methanol extract of O. majorana leaves was tested in NIH-3T3 fibroblasts for cytotoxicity and genotoxicity. In vivo acute oral toxicity was assessed in rats according to OECD Guideline 420, with animals monitored over 14 days for clinical signs, hematological and biochemical alterations, and histopathological changes. The extract preserved fibroblast viability above 90% across all tested concentrations (10–200 µg/mL), indicating absence of cytotoxicity. However, comet and micronucleus assays revealed dose-dependent DNA damage, suggesting genotoxic potential at higher exposures. In vivo, no mortality or overt systemic toxicity was observed at doses up to 2000 mg/kg. Hematological analyses showed immunomodulatory shifts (increased neutrophils and monocytes, reduced eosinophils), while biochemical profiles indicated hepatoprotective and cardioprotective effects, with reduced ALT, AST, and LDH levels. Histopathological evaluation revealed only mild, focal changes consistent with adaptive rather than irreversible responses. O. majorana extract demonstrates a favorable acute safety profile with preserved hepatic and renal function, hematological modulation, and absence of in vitro cytotoxicity. Nevertheless, dose-dependent genotoxicity warrants caution for concentrated formulations. According to GHS classification, the extract aligns with Category 5 (acute oral toxicity, lowest hazard) and Category 2 (germ cell mutagenicity). These findings underscore the importance of dose management and further long-term genotoxicity studies before translational applications in nutraceutical or biomedical fields. Full article

Despite the widespread use of dithiocarbamate fungicides such as maneb, mancozeb, metiram, propineb, thiram, and ziram detected, according to EU legislation, via common degradation product carbon disulfide (CS₂), recent and comprehensive reviews on analytical methods for their determination in plant-based foods are lacking. Given the well-documented toxicity shown by the experimental model for these pesticides, including neurotoxicity and endocrine disruption, harmonized and reliable analytical protocols are crucial for food safety monitoring and regulatory compliance. Dithiocarbamates, beyond CS₂ release, have been associated with immunotoxicity, thyroid dysfunction, and potential carcinogenicity, raising further concern regarding chronic dietary exposure. Their metabolites may disrupt enzymatic activity and oxidative balance, enhancing systemic toxicity. Early methods, had limited sensitivity, poor reproducibility, and relied on hazardous solvents, reducing practical value. Although later advancements improved detection limits, modern procedures, including those proposed by the European Union Reference Laboratory (EURL), still show limitations. The EURL-recommended protocol involves acid hydrolysis using concentrated HCl, extraction with isooctane, heating to 85 °C, and rapid ice-bath cooling, which poses environmental concerns. Recovery efficiency remains inconsistent in some cases, and reproducibility within commodity groups is poor. This review discusses the status of methods for determining dithiocarbamates as individual compounds and via CS₂ moiety. Full article

Real-time driving monitoring systems can use self-powered sensors based on artificial intelligence (AI) and triboelectric nanogenerators (TENGs). Here, we created a TENG-based self-powered intelligent steering wheel that can detect hand gripping. The TENG serves as the steering wheel’s smart surface. In addition to monitoring the steering wheel in real time, the intelligent steering wheel reacts quickly. The TENG sensor can detect hazardous conditions and lower processing demands while retaining excellent identification accuracy when used in conjunction with machine learning. Additionally, the TENG sensor may now offer an accurate and affordable monitoring solution for smart driving thanks to the integration of AI. Full article

Insulation degradation in photovoltaic (PV) cables can cause electrical faults and fire hazards, thereby compromising system reliability and safety. Early detection of precursor signals is crucial for preventive maintenance. However, conventional diagnostic techniques are limited to static assessments and fail to capture early-stage electrical anomalies in real-time. This study investigates the time-series behavior of voltage, current, and temperature in PV cables under thermal stress conditions. Experiments were conducted using TFR-CV cables installed in a vertically stacked and tight-contact configuration. A gas torch was applied for localized heating to induce insulation degradation. A grid-connected testbed with six series-connected PV modules was constructed. Each module was instrumented with PV-M sensors, temperature sensors, and an infrared camera. Data were acquired at 1 Hz intervals. Results showed that cable surface temperature exceeded 280 °C during degradation. The output voltage exhibited transient surges of up to +13.3% and drops of −68%, while the output current decreased by over 20%, particularly in the PV-M3 module. These anomalies, such as thermal imbalance, voltage spikes/dips, and current drops, were closely associated with critical degradation points and are interpreted as precursor signals. This work confirms the feasibility of identifying fire-related precursors through real-time monitoring of PV cable electrical characteristics. The observed correlation between electrical responses and thermal expansion behaviors suggests a strong link to the stages of insulation degradation. Future work will focus on quantifying the relationship between degradation and electrical behavior under controlled environmental conditions. Full article

The area encompassing the Campi Flegrei and Vesuvio volcanoes, situated approximately 25 km apart and bisected by the city of Naples, Italy, is recognised as one of the most hazardous regions globally. In recent decades, the Campi Flegrei caldera has undergone significant changes in its monitored geophysical, geochemical and geodetical signals. The most recent, ongoing unrest began in 2005, resulting in an uplift of over 150 centimetres in the area of maximum uplift. Previous analyses of deformation data from ERS/ENVISAT (available up to 2010) and Sentinel-1 (available since 2015) Synthetic Aperture Radar (SAR) imagery, as well as global navigation satellite system data, have suggested that the shape of the deformation field at Campi Flegrei has remained constant and that the area around Vesuvio experienced a slight subsidence in the early 2000s, concurrently with a change in the sign of the ground deformation (from subsidence to uplift) at Campi Flegrei. This study presents and provides the ground displacement time series obtained from RADARSAT-2 images of the entire volcanic area from 2010 to 2015, thus filling the temporal gap between the ERS/ENVISAT and Sentinel-1 missions. The time series were generated using a bespoke procedure, based on the Sentinel Application Platform and the GMTSAR software. The validity of the displacement time series has been confirmed through comparison with continuous Global Positioning System data from the Neapolitan Volcanoes Continuous GPS network. Analysis of RADARSAT-2 ground displacements indicates that velocities in the vicinity of Vesuvio were no greater than a few millimetres per year, and no discernible deformation pattern is evident. Consequently, given the uncertainty in Differential Interferometry Synthetic Aperture Radar (DInSAR) measurements, there is no evidence to suggest deformation activity close to Vesuvio between 2010 and 2015. In contrast to Vesuvio, significant deformation is evident in the Campi Flegrei area. The shape of the ground displacement field remained constant between 2010 and 2015, within the uncertainty of DInSAR measurements. The mean upward velocity reaches a maximum of approximately 5 cm y⁻¹, while the mean eastward velocity reaches 2.4 cm y⁻¹. Full article

Welding is an essential process across various industries; however, it exposes workers to dangerous fumes, extreme heat and physical stress, which pose considerable health and safety hazards. To tackle these issues, this article introduces the creation of a remote-controlled human–robot welding system aimed at safeguarding workers while ensuring the quality of the welds. The system monitors a welder’s torch movements through a stereoscopic sensor and accurately reproduces them with a robotic arm, facilitating real-time remote welding. Operated by a student, it effectively welded standardized sheet metals in overhead positions while adhering to critical quality standards. The weld geometry met ISO 5817 requirements, tensile strength surpassed the base material specifications, and bending and hardness assessments verified the durability and integrity of the welds. When utilized in hazardous settings, the system showcases its capability to produce high-quality welds while significantly enhancing worker safety, underscoring its potential for real-world industrial applications. Full article

Large woody debris (LWD) in river systems serves beneficial ecological functions and poses potential hazards during flood events. Managing LWD requires a balanced understanding of its dynamics. This study employed unmanned aerial vehicles (UAVs) for high-resolution, spatiotemporal monitoring of LWD distribution and mobility along the Oshirarika River in northern Japan. UAV imagery enabled efficient LWD recruitment and transport assessments. The spatial distribution analysis revealed that >90% of LWD was deposited on bar surfaces, underscoring the role of geomorphic features in controlling LWD accumulation. Generalized linear mixed models revealed that the maximum water level and the frequency of its rise above 0.8 m were the most influential predictors of the number of recruited and transported LWD. Additionally, the topographic position—channel, lower bar, or higher bar—exhibited a significant negative association, indicating greater LWD mobility and deposition in lower elevation zones. This trend may be attributed to infrequent high-magnitude flood events, which likely result in relatively limited LWD dynamics in higher bar areas. These findings demonstrate the utility of UAV-based monitoring coupled with GLMMs for capturing the spatial and temporal dynamics of LWD. The ability to link hydrological fluctuations and LWD behavior provides a valuable framework for management and ecological restoration in steep, forested watersheds. Full article

Co- and post-seismic earthquake-induced hydrogeological anomalies (EQHAs) in Greece are mainly associated with moderate to strong earthquakes (M_w = 6.0–7.0), particularly when seismic intensities reach IX or above. The highest frequencies are observed in the Peloponnese and Ionian Islands, followed by Central Greece and the North Aegean, characterized by dense faulting and frequent strong earthquakes. EQHAs are classified into six main types, with hydraulic variations being the most common. About 77% of earthquakes produced only one or two types of EQHA, suggesting localized hydrogeological effects, while only a few induced multiple types. Strong events (M_w = 6.0–7.0), often historic, generated the broadest variety, highlighting the influence of local geological, hydrological, and tectonic conditions on magnitude alone. Springs and wells, representing 81% of the cases, dominate the affected systems, while lakes and rivers respond less often but significantly. Most EQHAs occur in Greece’s second seismic hazard zone (74%) due to its larger geographic area. EQHAs primarily develop in karstic and porous formations but also appear in impermeable rocks due to fracturing or karst. Larger earthquakes trigger anomalies at greater distances (>100 km). Though rarely fatal, EQHAs can damage water infrastructure, contaminate supplies, and cause shortages, underscoring the need for systematic monitoring and post-earthquake water resource management. Full article

Asphalt fume emissions cause significant environmental hazards during the preparation of hot-mix asphalt. In this study, experimental investigations were conducted employing a reactor vessel to simulate asphalt fumes under controlled conditions. Asphalt fumes were obtained through an integrated system comprising glass fiber filter cartridges and an impinger absorption bottle. Quantitative analysis was then conducted using gravimetric analysis and UV-Vis spectrophotometry. Through systematic monitoring of compositional changes in asphalt binder fractions, the fume emission characteristics during in-plant mixing operations were quantitatively correlated with the following processing parameters: temperature, airflow rate, and mixing duration. Comparative evaluation revealed optimal performance from a ternary compound inhibitor containing cuprous chloride, ditert-butylhydroquinone, and ferric chloride in mass proportions of 4:4:2. At a critical dosage of 0.6 wt%, this compound inhibitor demonstrated significant reduction in total particulate matter emissions without compromising asphalt binder properties. In addition, comprehensive performance characterization through rheological testing and thin-film oven aging (TFOT) showed that the modified low-fume asphalt binder maintained equivalent or improved performances compared to a conventional asphalt binder. Full article

The emergence of microplastics (MPs) in drinking water supply systems has become a significant environmental challenge. Although the potential impacts of MPs in drinking water on human health remain incompletely understood, the ingestion of MPs through drinking water has raised substantial public concern regarding health risks. This review synthesizes contemporary scientific advances focusing on the following: I. the sources and fate of MPs in drinking water supply chains; II. comparative assessment of removal at treatment; III. detection techniques based on microscopy, spectroscopic, and thermal methods; and IV. the potential hazards of MPs to human health. This study aims to provide novel insights into understanding the threats posed by MPs in drinking water and to facilitate the development of effective monitoring strategies. Full article

Traffic accidents caused by black ice have become a serious public safety concern due to their high fatality rates and the limitations of conventional detection systems under low visibility. Millimeter-wave (mmWave) radar, capable of operating reliably in adverse weather and lighting conditions, offers a promising alternative for road surface monitoring. In this study, six representative road surface conditions—dry, wet, thin-ice, ice, snow, and sludge—were experimentally implemented on asphalt and concrete specimens using a temperature and humidity-controlled chamber. mmWave radar data were repeatedly collected to analyze the temporal variations in reflected signals. The acquired signals were transformed into range-based spectra using Range-Fast Fourier Transform (Range-FFT) and converted into statistical features and graphical representations. These features were used to train and evaluate classification models, including Extreme Gradient Boost (XGBoost), Light Gradient-Boosting Machine (LightGBM), Convolutional Neural Networks (CNN), and Vision Transformer (ViT). While machine learning models performed well under dry and wet conditions, their accuracy declined in hazardous states. Both CNN and ViT demonstrated superior performance across all conditions, with CNN showing consistent stability and ViT exhibiting competitive accuracy with enhanced global pattern-recognition capabilities. Comprehensive robustness evaluation under various noise and blur conditions revealed distinct characteristics of each model architecture. This study demonstrates the feasibility of mmWave radar for reliable road surface condition recognition and suggests potential for improvement through multimodal sensor fusion and time-series analysis. Full article

Railway service interruptions and electrical hazards often arise due to bird nests concealed within the intricate, highly symmetric overhead catenary networks of high-speed lines. These nests are difficult to pinpoint automatically, not only because they are diminutive and often merge visually with the surroundings but also due to occlusions and the persistent lack of substantial labeled datasets. To address this bottleneck, this work presents the High-Speed Railway Catenary Nest Dataset (HRC-Nest), merging 800 authentic images and 1000 synthetic samples to capture a spectrum of scenarios. Building on the symmetry of catenary structures—where nests appear as localized asymmetries—the Symmetry-Aware Railway Nest Detection Framework (RNDF) is proposed, an enhanced YOLOv12 system for accurate and robust nest detection in symmetric high-speed railway catenary environments. With the A2C2f_HRAMi design, the RNDF learns from multi-level features by unifying residual and hierarchical attention strategies. The SCSA component boosts the recognition in visually cluttered or obstructed settings further by jointly processing spatial and channel-wise signals. To sharpen the detection accuracy, particularly for subtle, hidden nests, the Focaler-GIoU loss guides bounding box optimization. Comparative studies show that the RNDF consistently outperforms recent detectors, surpassing the YOLOv12 baseline by 5.95% mAP@0.5 and 26.16% mAP@0.5:0.95, underscoring its suitability for symmetry-aware, real-world catenary anomaly monitoring. Full article