Search Results (708)

The neutral point of a 10 kV distribution network often adopts an arc suppression coil or high resistance grounding mode to ensure the reliability of the power supply. The single-phase grounding fault current is below 10 A, and the distribution network can continue to operate with the fault for up to 2 h. However, long-time arc faults may ignite cables and cause electrical fires, causing further damage to adjacent cables and seriously affecting the safety of the power grid. To study the combustion characteristics of a single-phase grounding fault of a distribution network cable under the action of a long-term small current arc, the cable fault ignition test was carried out by using the arc ignition method of welding tin wire fuses. Then, the temperature distribution of the cable channel in an electrical fire was simulated, based on an FDS simulation, and the damage of adjacent cables under typical layout was further analyzed. The results show that the 10 kV cable was quickly ignited by the high temperature arc within 0.04 s after the breakdown and damage of the cable. Flammable XLPE insulation melted or even dripped off at a high temperature in fire. Thus, the fire spread to both ends when burning. Under the condition of 4–10 A, the maximum flame temperatures above the arc fault point reached 725 °C, 792 °C, 812 °C and 907 °C, respectively. According to the network structure, some protection, such as fireproof tape, needs to be applied directly above the faulty cable when the fault current exceeds 6 A. Full article

Laboratories are complex and dynamic environments where diverse hazards—including toxic gas leakage, volatile solvent combustion, and unexpected fire ignition—pose serious threats to personnel safety and property. Traditional monitoring systems relying on single-type sensors or manual inspections often fail to provide timely warnings or comprehensive hazard perception, resulting in delayed response and potential escalation of incidents. To address these limitations, this study proposes a multi-node laboratory safety monitoring and early warning system integrating multi-source sensing, heterogeneous communication, and cloud–edge collaboration. The system employs a LoRa-based star-topology network to connect distributed sensing and actuation nodes, ensuring long-range, low-power communication. A Raspberry Pi-based module performs real-time facial recognition for intelligent access control, while an OpenMV module conducts lightweight flame detection using color-space blob analysis for early fire identification. These edge-intelligent components are optimized for embedded operation under resource constraints. The cloud–edge–app collaborative architecture supports real-time data visualization, remote control, and adaptive threshold configuration, forming a closed-loop safety management cycle from perception to decision and execution. Experimental results show that the facial recognition module achieves 95.2% accuracy at the optimal threshold, and the flame detection algorithm attains the best balance of precision, recall, and F1-score at an area threshold of around 60. The LoRa network maintains stable communication up to 0.8 km, and the system’s emergency actuation latency ranges from 0.3 s to 5.5 s, meeting real-time safety requirements. Overall, the proposed system significantly enhances early fire warning, multi-source environmental monitoring, and rapid hazard response, demonstrating strong applicability and scalability in modern laboratory safety management. Full article

In light of the global energy shortage, the development of renewable energy has become increasingly vital. With China’s commitment to achieving “carbon peak and carbon neutrality,” photovoltaic power generation has emerged as a focal point in new energy development. However, DC arc faults in photovoltaic systems pose significant safety hazards, potentially leading to electrical fires. While new detection technologies for DC arc faults in photovoltaic power generation systems have advanced rapidly, the diversity of international standards—such as UL 1699 B, GB/T 39750, IEC 63027, and CGC/GF 175—limits both the construction of experimental platforms and the universality of detection technologies. Current research often relies on a single standard to establish experimental platforms, resulting in detection methods with limited applicability and an inability to validate technological effectiveness fully. To address this issue, this paper conducts an in-depth study of four international and national standards (IEC 63027; UL 1699 B, GB/T 39750, and CGC/GF 175), focusing on the discrepancies in decoupling methods, impedance parameter settings, and experimental circuit topologies, including series and parallel arc scenarios. Through comprehensive comparative analysis of multiple standards, this study integrates major international and domestic specifications to develop a multi-standard compatible experimental platform. The platform is designed to accommodate diverse topologies and parameter requirements, enabling efficient collection of arc test data and performance evaluation of arc fault detection devices. It also provides a standardized foundation for the performance testing and classification of DC arc circuit breakers in photovoltaic power generation systems. Through a comprehensive multi-standard comparative analysis, we systematically analyze the technical differences in photovoltaic DC arc detection. We construct a multi-standard compatible experimental platform by integrating mainstream international and domestic standards. This platform is designed to accommodate various topological structures and parameter requirements, facilitating the collection of arcing experimental data and assessment of the performance of arc fault detection devices. The findings from this research provide both theoretical and experimental foundations for developing unified technical guidelines for photovoltaic DC arc protection. This will aid in standardizing the development of detection devices and enhancing the electrical safety of photovoltaic systems. Ultimately, this work is significant for promoting the safe utilization of new energy within the framework of the dual carbon goals. Moving forward, it is crucial to enhance the generalization abilities of detection algorithms further and foster the integration of standards and industrial applications. Full article

This article presents the study of an architectural-constructive type located in Valencia: ribless brick vaults built with the “catalan” technique (one single brick plement approximately 5 cm thick). This is a very specific variant of the star-shaped vault, from the late 15th and early 16th centuries, of which we will examine a representative example: the vault that covers the entrance to the Mas Palace in Valencia. The methodology used is dual in nature: on the one hand, a historical study has been carried out to contextualize the typology, and on the other, a metric analysis of the Mas Palace vault has been carried out using laser scanning technology as a prominent tool. These two parts have finally been put into relationship, determining the formal correspondences that define the type, as well as the particularities of the built work. The main finding of the research is the consideration of this star-shaped vaults, not as a set of particular cases, but as a well-defined typology, which was widespread and successful in its context. We have also determined that its formal characteristics are not only due to aesthetic but also functional (stability and fire resistance) issues. This research, therefore, has allowed us to ponder the importance of a constructive solution that usually goes unnoticed and whose originality does not lie in the techniques used but in their original combination. Full article

This single high-impact case study investigates the impact of planetary boundary layer (PBL) representation on long-range transport of Amazon fire smoke that reached the Metropolitan Area of São Paulo (MASP) from 15 to 20 August 2019, using the WRF model to compare three PBL schemes (MYNN 2.5, YSU, and BouLac) and three source-tagged tracers. The simulations are evaluated against MODIS-derived aerosol optical depth (AOD), the Light Detection and Ranging (LiDAR) time–height curtain over MASP, and HYSPLIT forward trajectories. Transport is diagnosed along the source-to-MASP pathway using six-hourly cross-sections and two integrative metrics: the projected mean wind in the 700–600 hPa layer and the vertical moment of tracer mass above the boundary layer. Outflow and downwind impact are strongest when a persistent reservoir between 2 and 4 km coexists with projected winds for several hours. In this episode, MYNN maintains an elevated 2–5 km transport layer and matches the observed arrival time and altitude, YSU yields a denser but delayed column, and BouLac produces discontinuous pulses with reduced coherence over the city. A negatively tilted trough, jet coupling, and a nearly stationary front establish a northwest-to-southeast corridor consistent across model fields, trajectories, and satellite signal. Seasonal robustness should be assessed with multi-event, multi-model analyses. Full article

Coal spontaneous combustion in arid regions poses severe threats to both ecological security and resource sustainability. Focusing on the detection challenges in Fire Zone No. 1 of the Miaoergou Coalfield, Xinjiang, this study proposes an Integrated Geophysical Collaborative Detection Framework that combines high-precision magnetic surveys, spontaneous potential (SP) measurements, and transient electromagnetic (TEM) methods. This innovative framework effectively overcomes the limitations of traditional single-method detection approaches, enabling the precise delineation of fire zone boundaries and the accurate characterization of spatial dynamics of coal fires. The key findings of the study are as follows: (1) High-magnetic anomalies (with a maximum ΔT of 1886.3 nT) exhibit a strong correlation with magnetite-enriched burnt rocks and dense fracture networks (density > 15 fractures/m), with a correlation coefficient (R²) of 0.89; (2) Negative SP anomalies (with a minimum SP of −38.17 mV) can effectively reflect redox interfaces and water-saturated zones (moisture content > 18%), forming a “positive–negative–positive” annular spatial structure where the boundary gradient exceeds 3 mV/m; (3) TEM measurements identify high-resistivity anomalies (resistivity ρ = 260–320 Ω·m), which correspond to non-waterlogged goaf collapse areas. Spatial integration analysis of the three sets of geophysical data shows an anomaly overlap rate of over 85%, and this result is further validated by borehole data with an error margin of less than 10%. This study demonstrates that multi-parameter geophysical coupling can effectively characterize the thermo-hydro-chemical processes associated with coal fires, thereby providing critical technical support for the accurate identification of fire boundaries and the implementation of disaster mitigation measures in arid regions. Full article

The increasing frequency and intensity of wildfires pose severe risks to ecosystems, infrastructure, and human safety. In wildland–urban interface (WUI) areas, nearby vegetation strongly influences building ignition risk through flame contact and radiant heat exposure. However, limited research has leveraged Unmanned Aerial Systems (UAS) remote sensing (RS) to capture species-specific vegetation geometry and predict thermal responses during ignition events This study proposes a two-stage framework integrating UAS-based multispectral (MS) imagery, LiDAR data, and Fire Dynamics Simulator (FDS) modeling to estimate the maximum temperature (T) and heat flux (HF) of outdoor vegetation, focusing on Syzygium smithii (Lilly Pilly). The study data was collected at a plant nursery at Queensland, Australia. A total of 72 commercially available outdoor vegetation samples were classified into 11 classes based on pixel counts. In the first stage, ensemble learning and watershed segmentation were employed to segment target vegetation patches. Vegetation UAS-LiDAR point cloud delineation was performed using Raycloudtools, then projected onto a 2D raster to generate instance ID maps. The delineated point clouds associated with the target vegetation were filtered using georeferenced vegetation patches. In the second stage, cone-shaped synthetic models of Lilly Pilly were simulated in FDS, and the resulting data from the sensor grid placed near the vegetation in the simulation environment were used to train an XGBoost model to predict T and HF based on vegetation height (H) and crown diameter (D). The point cloud delineation successfully extracted all Lilly Pilly vegetation within the test region. The thermal response prediction model demonstrated high accuracy, achieving an RMSE of 0.0547 °C and R² of 0.9971 for T, and an RMSE of 0.1372 kW/m² with an R² of 0.9933 for HF. This study demonstrates the framework’s feasibility using a single vegetation species under controlled ignition simulation conditions and establishes a scalable foundation for extending its applicability to diverse vegetation types and environmental conditions. Full article

Structural collapses are a major threat to urban safety and infrastructure resilience and as such there is growing research interest in understanding the causes and improving the prediction of risk to prevent human and material losses. Whether caused by fires, earthquakes or progressive failures due to overloads and displacements, these events have been the focus of investigation over the past 15 years. This systematic literature review looks at the use of formal risk analysis models in structural failures between 2010 and 2025 to map methodological trends, assess model effectiveness and identify future research pathways. From an initial database of 139 documented collapse incidents, only 42 were investigated using structured risk analysis frameworks. A systematic screening of 417 related publications yielded 101 peer-reviewed studies that met our inclusion criteria—specifically, the application of a formal analytical model. This discrepancy highlights a significant gap between the occurrence of structural failures and the use of rigorous, model-based investigation methods. The review shows a clear shift from single-method approaches (e.g., Fault Tree Analysis (FTA) or Finite Element Analysis (FEA)) to hybrid, integrated models that combine computational, qualitative and data-driven techniques. This reflects the growing recognition of structural failures as socio-technical phenomena that require multi-methodological analysis. A key contribution is the development of a strategic framework that classifies models by complexity, data requirements and cost based on patterns observed across the reviewed papers. This framework can be used as a practical decision support tool for researchers and practitioners to select the right model for the context and highlight the strengths and limitations of the existing approaches. The findings show that the future of structural safety is not about one single “best” model but about intelligent integration of complementary context-specific methods. This review will inform future practice by showing how different models can be combined to improve the depth, accuracy and applicability of structural failure investigations. Full article

The demand for energy-efficient construction in agriculture calls for a reassessment of materials used in livestock buildings. This study evaluated the use of timber as an alternative to traditional materials, with a focus on embodied energy (EE) and carbon footprint (CFP) Eight EU countries (Germany, Poland, Spain, Italy, Denmark, France, Sweden, and Finland), were analyzed considering both forest resources and livestock populations. The forest area varied from more than 310,000 km² in Sweden to just 6464 km² in Denmark. Meanwhile, livestock populations varied significantly, with Germany reporting over 8.2 million LSU (livestock unit, 500 kg) in cattle alone. The number of livestock buildings was estimated assuming 100 LSU per building, allowing for a comparison between timber and conventional designs. Timber-based cowsheds were found to lower embodied carbon by up to 10,433 kg CO₂e per barn compared with 17,450 kg CO₂e for conventional structures. Embodied energy for a single wooden cowshed was around 151 GJ versus more than 246 GJ for a traditional counterpart. Scaled up to the national level, this represents a 35–40% reduction in total embodied energy. In addition to environmental outcomes, the analysis considered economic, technical, and regulatory aspects influencing adoption. The results suggest that substituting conventional materials with timber can contribute to emission reductions in agricultural construction, while further research is needed on fire safety, prefabrication, and policy harmonizations. Full article

Post-fire soil and vegetation changes can intensify erosion and sediment yield by altering the factors controlling the runoff–infiltration balance. Erosion barriers (EBs) are widely used in hydrological and forest restoration to mitigate erosion, reduce sediment transport, and promote vegetation recovery. However, precise spatial assessments of their effectiveness remain scarce, requiring validation through operational methodologies. This study evaluates the impact of EB on post-fire vegetation recovery at two temporal and spatial scales: (1) Remotely Piloted Aircraft System (RPAS) imagery, acquired at high spatial resolution but limited to a single acquisition date coinciding with the field flight. These data were captured using a MicaSense RedEdge-MX multispectral camera and an RGB optical sensor (SODA), from which NDVI and vegetation height were derived through aerial photogrammetry and digital surface models (DSMs). (2) Sentinel-2 satellite imagery, offering coarser spatial resolution but enabling multi-temporal analysis, through NDVI time series spanning four consecutive years. The study was conducted in the area of the Luna Fire (northern Spain), which burned in July 2015. A paired sampling design compared upstream and downstream areas of burned wood stacks and control sites using NDVI values and vegetation height. Results showed slightly higher NDVI values (0.45) upstream of the EB (p < 0.05), while vegetation height was, on average, ~8 cm lower than in control sites (p > 0.05). Sentinel-2 analysis revealed significant differences in NDVI distributions between treatments (p < 0.05), although mean values were similar (~0.32), both showing positive trends over four years. This study offers indirect insight into the functioning and effectiveness of EB in post-fire recovery. The findings highlight the need for continued monitoring of treated areas to better understand environmental responses over time and to inform more effective land management strategies. Full article

Background. MiR-218 is a micro-RNA expressed in two isoforms (miR-218-1 and miR-218-2) in the brain and, within the mesencephalic area, it represents a specific regulator of differentiation and functional maturation of the dopamine-releasing neurons (DAn). Deletion of miR-218 isoforms within the midbrain alters the expression of synaptic mRNAs, the neuronal excitability of DAn of the substantia nigra pars compacta (SNpc), and their ability to release dopamine (DA) within the dorsal striatum. Objectives. Here we have investigated if miR-218 impacts the function of the DAn population adjacent to SNpc, the mesencephalic ventral tegmental area (VTA) innervating the nucleus accumbens (NAcc), and the medial prefrontal cortex. Methods. With the use of miR-218-1, miR-218-2, and double conditional knock-out mice (KO1, c-KO2, c-dKO), we performed electrophysiological recordings in VTA DAn to investigate firing activity, measurements of DA release in NAcc slices by constant potential amperometry (CPA), and in vivo behavioral analysis. Results. We find that KO1 VTA neurons display hyperexcitability in comparison with c-KO2, c-dKO, and wild type (WT) neurons. DA efflux in the NAcc core and shell is reduced in all single- and double-conditional KO striatal slices in comparison with controls. The KO1 mice display a tendency toward an anxiety-like trait, as revealed by the elevated plus maze test. Conclusions. Our data indicate that miR-218-1 is the isoform that mainly regulates VTA DA neuron excitability whereas both miR-218-1 and miR-218-2 impair DA release in the mesoaccumbens pathway. Full article

This study evaluates the competency-based performance of Initial Incident Commander (IIC) candidates—fire officers who serve as first-arriving, on-scene incident commanders—in South Korea and identifies sub-competency deficits to inform training improvements. Using evaluation data from 92 candidates tested between 2022 and 2024—of whom 67 achieved certification and 25 did not—we analyzed counts and mean scores for each sub-competency and integrated transcribed radio communications to contextualize deficiencies. Results show that while a majority (72.8%) passed, a significant proportion (27.2%) failed, with recurrent weaknesses in crisis response, progress management, and decision-making. For example, “Responding to Unexpected or Crisis Situations 3-3” recorded 27 unsuccessful cases with a mean score of 68.8. Candidates also struggled with resource allocation, situational awareness and radio communications. The study extends recognition-primed decision-making theory by operationalizing behavioral marker frameworks and underscores the need for predetermined internal alignment, scalability and teamwork synergy. Practical implications recommend incorporating high-fidelity simulation and VR scenarios, competency frameworks and reflective debriefs in training programs. Limitations include the single-country sample, reliance on predetermined scoring rubrics and absence of team-level analysis. Future research is indispensable to adopt multi-jurisdictional longitudinal designs, evaluate varied training interventions, assess skill retention and explore the interplay between physical and cognitive training over time. Full article

This study focused on the Wugong coal fire area in the Zhunnan coalfield of Xinjiang, analyzing 41 soil samples extending from the fire center outward. The key parameters included pH, soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), available potassium (AK), various ions (Ca²⁺, Na⁺, Mg²⁺, SO₄²⁻, CO₃²⁻, HCO₃⁻, and Cl⁻), and heavy metal concentrations (As, Cr, Hg, Ni, Cd, Cu, Zn, and Pb). The primary objectives were to evaluate heavy metal pollution levels and potential ecological risks using the single factor pollution index (P_i), the Geo-accumulation index (I_Geo), Nemero’s pollution index (P_n), the pollution load index (PLI), and the ecological risk factor (E_rⁱ) and risk index (RI). Spatial distribution analysis indicated higher heavy metal concentrations in the southwestern and central regions. The heavy metals Cr, Ni, Cd, Cu, and Zn reached mild pollution levels, while Hg exhibited high pollution, with P_i, I_Geo, and P_n values of 3.27, 0.61, and 9.68, respectively. Hg (E_rⁱ = 111.07) and Cd (E_rⁱ = 45.91) emerged as the primary ecological risk factors. The overall ecological risk index (RI) of 184.98 indicated a moderate ecological risk. The results demonstrate that soils surrounding the coal fire zone are significantly impacted by coal fire, characterized by severe heavy metal contamination and nutrient deficiency. Full article

A gypsum karst sinkhole at Westeregeln (north-central Germany) was filled during the Late Pleistocene, first by fluvial flooding, then by solifluctation, and finally with wind-transported loess. Pleistocene mollusks and bones of snakes, birds, micro- and macromammals, and hyena coprolites were accumulated, often mixed in gravel or sand layers with Middle Paleolithic artifacts, whereas ice wedges reach deep into the sinkhole. The high amount of small flint debris prove on-site tool production by using 99% local Saalian transported brownish-to-dark Upper Cretaceous flint, which could have been collected from the Bode River gravels near-site. Only a single quartzite and one jasper flake prove other local gravel sources or importation. A large bifacial flaked knife of layer 4 dates to the early/middle Weichselian/Wuermian (MIS 5-4), similar to two triangular handaxes in the MTA tradition and an absolutely dated woolly rhinoceros bone (50,310 + 1580/−1320 BP). A cold period of Late Pleistocene glacial mammoth steppe megafauna is represented, but the material is mostly strongly fragmented and smashed by humans. Neanderthal camp use on the gypsum hill is indicated also by small charcoal pieces, burned bone fragments, and fire-dehydrated flint fragments. Crocuta crocuta spelaea (Goldfuss) hyenas are well known from Westeregeln, with an open-air commuting den site, which was marked with feces. Full article

Accurate and timely 3D vegetation structure information is essential for ecological modeling and land management. However, these needs often cannot be met with existing airborne LiDAR surveys, whose broad-area coverage comes with trade-offs in point density and update frequency. To address these limitations, this study introduces a deep learning framework built on attention mechanisms, the fundamental building block of modern large language models. The framework upsamples sparse (<22 pt/m²) airborne LiDAR point clouds by fusing them with stacks of multi-temporal optical (NAIP) and L-band quad-polarized Synthetic Aperture Radar (UAVSAR) imagery. Utilizing a novel Local–Global Point Attention Block (LG-PAB), our model directly enhances 3D point-cloud density and accuracy in vegetated landscapes by learning structure directly from the point cloud itself. Results in fire-prone Southern California foothill and montane ecosystems demonstrate that fusing both optical and radar imagery reduces reconstruction error (measured by Chamfer distance) compared to using LiDAR alone or with a single image modality. Notably, the fused model substantially mitigates errors arising from vegetation changes over time, particularly in areas of canopy loss, thereby increasing the utility of historical LiDAR archives. This research presents a novel approach for direct 3D point-cloud enhancement, moving beyond traditional raster-based methods and offering a pathway to more accurate and up-to-date vegetation structure assessments. Full article