Search Results (356)

The efficacy of oil spill response depends on the speed of detecting the oil. Detecting submerged oil is more difficult than oil on the water surface, because most conventional sensors are not effective. Oil Detection Canines (ODCs) have been reliably used to detect oil during shoreline spill surveys, and preliminary laboratory studies also showed promising results for detecting oil submerged under water. To confirm their potential, a field study was conducted in a boreal freshwater lake in Northwestern Ontario, Canada to investigate the capability of an ODC to detect submerged weathered oils at depths of 1 to 5 m. Triplicate targets at each depth used weathered diluted bitumen (dilbit), Bunker C residual fuel oil, and Maya crude oil burn residue and both the ODC and handler blinded to the location of each target. Boat-based searches were conducted and the handler identified “alerts” based on ODC behaviour changes that were compared to georeferenced oil target locations. The ODC positively identified seven (7) of the eight (8) dilbit targets at 1 to 5 m, five (5) of the six (6) Bunker C targets at 1 and 3 m, and none of the burn residue targets at 1-m depth. The ability of ODCs to detect submerged or sunken oil in shallow water was clearly demonstrated, adding another technique for submerged and sunken oil surveys with the advantages of real-time data returns, the ability to detect small oil deposits, and an operational capability in shallow waters with potential for detection in deeper water. Full article

Accurate documentation of burn wounds is essential for evaluating treatment outcomes and monitoring healing progression. Traditional two-dimensional (2D) photography remains the clinical standard but lacks depth and volumetric accuracy. Three-dimensional (3D) scanning offers enhanced visualization of wound morphology and tissue vitality, potentially improving objectivity in burn assessment. This study compares two handheld 3D scanning systems—Artec Eva and Revopoint Miraco—in documenting acute and healing burn wounds, using standard clinical photography as the reference. Fifteen patients with second-degree and third-degree burns were prospectively examined at the Burn Unit of AGEL Hospital Košice-Šaca, with five representative cases selected for detailed analysis. For each patient, clinical photographs and paired 3D scans were obtained under standardized conditions and evaluated for color fidelity, wound margin clarity, representation of epithelialisation islands, necrotic tissue, and correlation with clinical findings. Across all cases, Artec Eva demonstrated superior color accuracy, clearer wound delineation, and more realistic visualization of tissue vitality and re-epithelialisation. Revopoint Miraco reliably captured wound shape but produced darker tones and exaggerated surface relief, occasionally distorting depth perception. Overall, both systems successfully identified key healing features; however, Artec Eva provided more clinically accurate and visually consistent results. Three-dimensional scanning represents a valuable adjunct to conventional burn documentation. Full article

Objective: To identify key predictors of clinical outcomes in burn survivors and clarify the role of mixed-depth burns and confounding by indication in observational rehabilitation research. Design: Retrospective cohort study using data from a burn rehabilitation registry (January 2024 to July 2025). Setting: Burn rehabilitation center. Participants: 120 adult patients (age ≥ 18 years) with burns affecting ≥1% total body surface area (TBSA) and complete baseline data. Interventions: Not applicable. Main Outcome Measures: Primary outcome was functional improvement (ΔFIM). Secondary outcomes included pain reduction (ΔPain), scar severity (Vancouver Scar Scale; VSS), Activities of Daily Living (ADL) improvement, and Range of Motion (ROM) recovery. Multivariable linear and logistic regression models were used to identify predictors. Results: Patients achieved significant improvements in function (mean ΔFIM = 11.3 ± 8.9 points) and pain (mean ΔPain = 1.28 ± 0.81). Having a mixed-depth burn was the strongest predictor of worse scar outcomes (β = 2.52, 95% CI: 0.93 to 4.12, p = 0.002) and failure to achieve full ROM (OR = 0.089, 95% CI: 0.008 to 0.930, p = 0.043). An apparent association between inpatient ward care and better scar outcomes (β = −1.30, p = 0.020) was determined to be an artifact of confounding by indication, as the outpatient group had a higher proportion of high-risk mixed-depth burns (6.2% vs. 3.5%). Longer therapy duration was the only significant predictor of achieving ADL goals (OR = 1.014, 95% CI: 1.002 to 1.026, p = 0.025). Conclusions: Injury characteristics, particularly the presence of a mixed-depth burn, emerged as the dominant predictors of long-term scar and functional outcomes. This study identifies mixed-depth burns as a potentially high-risk clinical phenotype requiring targeted therapeutic strategies and demonstrates the critical importance of accounting for confounding by indication when evaluating rehabilitation outcomes in observational burn research. Full article

Maintaining adequate root-zone temperature in solar greenhouses during extreme cold is crucial for crop production. This study investigated the optimization of an auxiliary biomass heating system in a solar greenhouse. The heating performance was evaluated using an integrated methodology that combined orthogonal experimental design, Computational Fluid Dynamics (CFD) simulation, and Machine Learning (ML) surrogate modeling. First, a reliable CFD model, validated against experimental data (Index of Agreement, IA = 0.954), was used to generate high-fidelity temperature field data for nine layout schemes. Parameter sensitivity analysis revealed that the burning cave Diameter is the dominant factor (R = 6.01), followed by burial Depth (R = 2.00), with inter-pool Spacing having the least impact (R = 0.89). Subsequently, six ML algorithms were compared for use as a predictive surrogate model, with Lasso Regression demonstrating superior performance (R² = 0.934). Comprehensive optimization focused on maximizing the Suitable Area Ratio (R_s) in the critical 0.2 m depth root zone. The analysis conclusively identified the 2.5 m diameter group as optimal, achieving a maximum R_s of 90% and the lowest temperature standard deviation. The final recommended optimal design (2.5 m diameter, 0.7 m depth, 10 m spacing) significantly improves heating uniformity and efficiency. This integrated CFD-ML approach provides a scientific basis and a rapid assessment tool for the design and structural optimization of similar underground thermal systems in cold-climate agriculture. Full article

Background: Burns cause about 180,000 deaths annually and lead to substantial morbidity, especially in low- and middle-income countries. Clinical assessment of burn depth and TBSA relies on visual and bedside examination and remains subjective. Convolutional neural networks (CNNs) have been proposed to improve objectivity in image-based burn assessment, but clinical generalizability and acceptance remain uncertain. Aims: To map current evidence on CNN performance for burn TBSA, burn depth and treatment-related tasks and to explore whether a large language model (LLM) can organize extracted findings into a transparent, literature-derived orientation decision tree. Methods: We performed a scoping review following PRISMA-ScR. PubMed, Web of Science and Cochrane were searched on 5 April 2025. Eligible studies reported CNN analysis of 2D burn images and quantitative performance metrics. We summarized reported values descriptively. We then provided a structured summary of extracted findings to ChatGPT to draft a one-page orientation decision tree. Two consultant burn surgeons reviewed the figure for clarity and plausibility. Results: Of 659 records, 24 studies were included. Across studies, reported performance for TBSA and depth assessment was often high, but study designs, datasets, labels, imaging modalities and validation strategies varied substantially. High reported performance does not necessarily imply clinical robustness or real-world accuracy. A single study reported high test-set accuracy for graft versus non-graft using heavily expanded data. This value should not be generalized. Conclusions: CNNs show promise for image-based burn TBSA and depth assessment, but heterogeneity, dataset limitations and limited external validation restrict interpretation and clinical transfer. The LLM-derived decision tree is a literature-synthesis orientation figure, not a clinical decision-support tool. Full article

The utilization of metal roofing as natural air terminals is a standard practice in lightning protection; however, the risk of thermal perforation and subsequent ignition of internal hazardous atmospheres remains a critical safety concern. While current standards (e.g., IEC 62305) primarily focus on material thickness and total charge (Q), this study demonstrates that these parameters alone are insufficient for predicting burn-through failure. We present a comprehensive electrothermal analysis based on the method of images to simulate three-dimensional heat diffusion in finite-thickness plates (0.5–7 mm) made of aluminum, copper, and steel. Unlike simplified 1D models, our approach considers the spatial distribution of the heat source and the varying depth of the thermal penetration. The results confirm that the continuing current component ($Q_{long}\approx 200$ C) is the primary driver of volumetric melting. Crucially, the sensitivity analysis reveals that the lightning channel radius ($r_{mbo}$) acts as a governing factor for perforation risk; a reduction in the lightning channel radius from 5 mm to 2 mm can shift the outcome from minor surface heating to complete perforation for thin sheets ($0.5$ mm), even under identical charge conditions. This paper identifies a “safety gap” in current engineering practices, demonstrating that neglecting this parameter constriction effect results in an underestimation of the thermal threat. The proposed analytical model provides a precise tool for determining the safety margins of natural air terminals, offering direct applicability for designing lightning protection systems in high-risk industrial facilities. Full article

This study investigates the fire behaviour of building-integrated photovoltaic (PV) claddings, focusing on the progression from glass failure to ignition under different cavity conditions. Experimental tests were conducted on two common PV cladding types: bifacial dual-glass (GG) and monofacial glass–plastic (GP) modules. Results revealed that GP modules exhibited faster burning and higher peak heat release rates (HRR), reaching up to 600 kW, while GG modules burned more slowly with peak HRR between 50 and 100 kW. Cavity conditions, including depth, ventilation, and operational energization, were found to be vital in determining glass breakage, occurring between 400 and 550 °C, and cavity ignition and subsequent flame spread. The relationship between cavity fire dynamics and glass breakage suggests the importance of system design, particularly regarding cavity ventilation and flame barriers, for mitigating upward fire propagation. These results establish a basis for advancing numerical fire models through integration of critical parameters such as material properties, glass breakage, cavity ignition, and cavity configuration. This approach supports comprehensive real-scale analysis to guide the development of effective design recommendations, ultimately improving fire safety in PV-integrated construction. Full article

Post-harvest forest residue management and liming practices can significantly affect soil quality. This study evaluated the impacts of burnt pine harvest residues and lime application methods (surface-applied vs. incorporated) on the chemical and physical properties of a Dystric Cambisol in Southern Brazil. Soil samples were collected at two depths (0–10 cm and 10–20 cm) and analyzed for pH, exchangeable acidity, organic carbon, cation exchange capacity, macroporosity, microporosity, and bulk density. The results showed that changes were more pronounced in the 0–10 cm layer and mainly affected chemical attributes. Incorporated lime increased pH from 4.7 to 5.1, increased base saturation from 17% to 36%, and reduced Al saturation from 45% to 13% in the 0–10 cm layer. Burnt residues alone did not significantly alter soil properties, whereas lime incorporation led to improved chemical conditions and enhanced soil structure, especially in the surface layer. The treatments that maintained pine residues on the surface favored biological processes in the topsoil, while the burning of these residues had variable impacts on soil structure and nutrient availability. These findings highlight the importance of incorporating lime to optimize soil rehabilitation following pine harvesting in subtropical forest systems. Full article

Hyperspectral imaging (HSI) is a swiftly developing intraoperative and diagnostic technique in several clinical specialties. By monitoring oxygenation and biochemical markers, it helps with tissue viability, burn depth measurement, wound healing, and tumor detection. HSI facilitates real-time, harmless diagnosis throughout surgeries or outpatient settings, and allows for the detection of tumor boundaries with over 90% accuracy, according to clinical studies. Originally developed for remote sensing and aerospace applications, HSI has rapidly evolved and found increasing relevance across diverse sectors, including agriculture, environmental monitoring, food safety, pharmaceuticals, defense, and especially medical diagnostics. This review explores the origins, development, and expanding applications of HSI, with a particular emphasis on its role in healthcare. It discusses the operational principles and unique features of hyperspectral systems, such as their ability to produce spectral data cubes, perform non-destructive analysis, and integrate with emerging technologies like artificial intelligence and drone-based platforms. By comparing hyperspectral imaging to traditional and multispectral techniques, the review highlights its superior spectral resolution and versatility. Key challenges, including data volume, sensor calibration, and real-time processing, are also addressed. Finally, emerging trends such as miniaturization, integration with the Internet of Things, and sustainable system designs are examined, offering insights into the future directions and interdisciplinary potentials of HSI in both scientific research and practical applications. Full article

Atmospheric aerosols are known to alter the Earth’s radiative balance and influence climate. However, accurately quantifying the magnitude of aerosol-induced radiative forcing remains challenging. We characterize optical properties of biomass-burning (BB) and non-biomass-burning (NB) aerosols and quantify BB aerosol radiative forcing at two AERONET (AErosol RObotic NETwork) sites in Huancayo (Peru) and La Paz (Bolivia) during 2015–2021. From AERONET data, we derive aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo (SSA), and asymmetry parameter (ASY). We then employ the SBDART model to calculate aerosol radiative forcing (ARF) on monthly and multiannual timescales. BB aerosols peak in September (AOD: 0.230 at Huancayo; 0.235 at La Paz), while NB aerosols reach maxima in September at Huancayo (0.109) and November at La Paz (0.104). AE values exceeding unity for BB aerosols indicate fine-mode dominance. Huancayo exhibited the highest BB ARF in November: +16.4 W m⁻² at the top of the atmosphere (TOA), –18.6 W m⁻² at the surface (BOA), and +35.1 W m⁻² within the atmospheric column (ATM). This was driven by elevated AOD and high scattering efficiency. At La Paz, where SSA data was only available for September, BBARF values were also significant (+15.16 at TOA, –17.52 at BOA, and +32.73 W m⁻² within the ATM). This result underscores the importance of quantifying the ARF, particularly over South America where data is scarce. Full article

This study aims to understand the effects of wildfires in sagebrush ecosystem on soil properties by examining connections between Soil Water Repellency (SWR), reflectance, and chemistry. Ash and burned soil samples were collected after performing laboratory burns of three common sagebrush plants: sagebrush, rabbitbrush, and bitterbrush. The collected samples were analyzed for their physical properties, including SWR measured by Water Drop Penetration Time (WDPT) and Apparent Contact Angle (ACA), and solar spectral reflectance in the wavelength range of 350 to 2500 nm. Chemical functional groups of the samples were analyzed using Fourier-Transform Infrared (FTIR) spectroscopy. WDPT and ACA values were in the range of 1 to 600 s and ~10° to 88°, respectively, for all three tested fuels. The FTIR analysis showed a decrease (~2 to 4 times) in the ratio of COO⁻/C=C signals for the burned soil samples compared to the unburned soil samples. Overall, increase in temperature and ACA levels for the samples of burned and burned soil from a 2 cm depth led to increased formation of non-polar compounds with C=C functional groups, and decarboxylation. Full article

Forests play a crucial role in climate regulation through atmospheric CO₂ sequestration. However, disturbances like wildfires can severely compromise this function. This study assesses the ecological and economic consequences of a 2018 wildfire in The Roaches Nature Reserve, UK, focusing on post-fire carbon dynamics. A mixed woodland dominated by Pinus sylvestris L. and Larix decidua Mill. was evaluated via satellite imagery (remote sensing indices), dendrochronological analysis (wood cores sampling), and soil properties analyses. Remote sensing revealed areas of high fire severity and progressive vegetation decline. Tree-ring data indicated near-total mortality of L. decidua, while P. sylvestris showed greater post-fire resilience. Soil properties (e.g., soil organic carbon, biomass and microbial indices, etc.) assessed at a depth of 0–5 cm showed no significant changes. The analysis of CO₂ sequestration trends revealed a marked decline in burned areas, with post-fire sequestration reduced by approximately 70% in P. sylvestris and nearly 100% in L. decidua, in contrast to the stable patterns observed in the control stands during the same period. To estimate this important ecosystem service, we developed a novel CO₂ Sequestration Loss (CSL) index, which quantified the reduction in forest carbon uptake and underscored the impaired sequestration capacity of burned area. The decrease in CO₂ sequestration also resulted in a loss of regulating ecosystem service value, with burned areas showing a marked reduction compared to pre-fire conditions. Finally, a carbon loss of ~208 Mg ha⁻¹ was estimated in the burnt area compared to the control, mainly due to tree mortality rather than shallow soil carbon stock. Overall, our findings demonstrate that wildfire can substantially compromise the climate mitigation potential of temperate forests, highlighting the urgency of proactive management and restoration strategies. Full article

Background: Optical Coherence Tomography (OCT) is a high-resolution imaging technique capable of quantifying Blood Flow at Depth (BD) and the Attenuation Coefficient (AC). However, the clinical relevance of these parameters in burn assessment remains unclear. This study investigated whether OCT-derived metrics can differentiate between superficial and deep pediatric hand burns. Method: This prospective, single-center study analyzed 73 OCT scans from 37 children with thermal hand injuries. A structured algorithm was used to evaluate AC and BD. Results: The mean AC was 1.61 mm⁻¹ (SD ± 0.48), with significantly higher values in deep burns (2.11 mm⁻¹ ± 0.53) compared to superficial burns (1.49 mm⁻¹ ± 0.38; p < 0.001), reflecting increased optical density in more severe burns. BD did not differ significantly between burn depths, although superficial burns more often showed visible capillary networks. Conclusions: This is the first study to assess both AC and BD using OCT in pediatric hand burns. AC demonstrated potential as a diagnostic marker for burn depth, whereas BD had limited utility. Image quality limitations highlight the need for technical improvements to enhance OCT’s clinical application. Full article

Burns represent a significant medical challenge, and the development of theoretical models has the potential to contribute to the advancement of new diagnostic tools. This study aimed to perform numerical simulations of the Pennes bioheat transfer equation, incorporating heat generation terms due to the body’s immunological response to thermal injury, as well as changes in skin thermal parameters and blood perfusion for each burn type. We propose the incorporation of specific parameters and boundary conditions related to multilayer perfusion into the Pennes bioheat model. Using the proposed layered skin model, we evaluate temperature differences to establish correlations for determining burn depth. In this investigation, 1D and 3D algorithms based on the finite volume method were applied to capture transient and spatial thermal variations, with the resulting temperature distributions demonstrating the ability of the proposed models to describe the expected thermal variations in healthy and burned tissue. This work demonstrates the potential of the finite volume method to approximate the solution of the Pennes biothermal equation. Overall, this study provides a computational framework for analyzing heat transfer in burn injuries and highlights the relevance of mathematical simulations as a tool for future research on infrared thermography in medicine. Full article

Biomass burning in the Amazon region, especially during the dry season, generates aerosol dispersion events across the southern part of the continent, with impacts observable thousands of kilometers from the emission source. This study presents a long-range aerosol transport case from September 2024, in which smoke aerosols from forest fires in the central Amazon reached southeastern and southern Brazil, affecting the air quality in distant areas such as São Paulo and São Martinho. The event was simulated using the Weather Research and Forecasting model with Chemistry (WRF-Chem), configured with the MOZCART chemical mechanism, combined with MERRA-2 reanalysis data and by using the 3BEM biomass burning emission inventory. Satellite datasets from MODIS and MERRA-2 reanalysis were used to evaluate the model’s performance. The results indicate that the South American Low-Level Jet (SALLJ) played a key role in transporting carbonaceous aerosols over long distances. The model successfully captured the spatial and temporal evolution of the aerosol plume and its impacts, although it tended to underestimate aerosol optical depth (AOD) values compared with satellite observations. This study highlights the WRF-Chem’s capability to simulate extreme smoke transport events in South America and supports its potential application in forecasting and air quality assessments. Full article