Search Results (1,001)

Amyotrophic lateral sclerosis (ALS) is a rare but fatal neurodegenerative disease. Some occupational exposures are associated with ALS. This study evaluated ALS mortality rates in World Trade Center (WTC)-exposed and non-WTC-exposed rescue/recovery workers. Fire department workers who were 18–70 years old on 11 September 2001 (9/11) were included in the study (N = 33,122). Follow-up began on the later of 9/11 or on their hire date, and ended at the earliest death date or 31 December 2023. Cause of death data were obtained from the National Death Index; ALS (specifically motor neuron disease)-related mortality was the primary outcome. Demographic data were obtained from the fire departments’ databases. We estimated standardized mortality ratios (SMRs) and 95% CIs for ALS-related mortality in WTC-exposed and non-WTC-exposed workers using US population rates as a reference. Multivariable-adjusted Poisson regression models estimated relative rates (RRs) and 95% CIs for ALS-related mortality in the WTC-exposed vs. non-WTC-exposed groups. Between 9/11 and 31 December 2023, five WTC-exposed and sixteen non-WTC-exposed participants died of ALS. ALS mortality rates were lower in WTC-exposed than in non-WTC-exposed rescue/recovery workers (RR = 0.54, 95% CI = 0.49–0.60). ALS-related mortality was not elevated in WTC-exposed (SMR = 0.44, 95% CI = 0.14–1.03) or non-WTC-exposed rescue/recovery workers (SMR = 1.06, 95% CI = 0.60–1.72) compared with the US general population. This initial evaluation of ALS in WTC-exposed workers indicates that the risk of ALS death is not increased in this population. Full article

Haze significantly reduces visibility in critical applications such as autonomous driving, surveillance, and firefighting, making its removal essential for safety and reliability. Motivated by the limited robustness of the existing methods under non-uniform haze conditions, this study introduces a novel regression-based dehazing model that simultaneously incorporates the atmospheric light constant, transmission map, and scattering coefficient for improved restoration. Instead of relying on complex deep networks, the model leverages brightness–saturation cues and regression-driven scattering estimation with localized haze detection to reconstruct clearer images efficiently. Evaluated on the RESIDE dataset, the approach consistently surpasses state-of-the-art techniques including Dark Channel Prior, AOD-Net, FFA-Net, and Single U-Net, achieving SSIM = 0.99, PSNR = 22.25 dB, VIF = 1.08, and the lowest processing time of 0.038 s, demonstrating both accuracy and practicality for real-world deployment. Full article

Leadership is context-dependent in its influence on various employee attitudes and behaviors, particularly in high-risk environments. Despite this, few studies have explored the role of leadership in shaping safety-related outcomes within high-risk public sector settings. This study posits that leadership’s impact may differ in high-risk contexts such as firefighting, where safety is of utmost importance. Using survey data collected from firefighters in Gyeonggi-do, the largest province in South Korea, this study examines the relationship between transformational leadership, perceived accident likelihood, and three safety-related attitudes: safety motivation, safety compliance, and safety participation. With sample sizes for the three dependent variables ranging from 1502 to 1504, the ordinary least squares (OLS) regression results indicate that transformational leadership is positively associated with all three safety attitudes. However, perceived accident likelihood shows a positive relationship with only one of the safety-related attitudes: safety motivation. More importantly, perceived accident likelihood moderates the relationship between transformational leadership and safety attitudes; as perceived accident likelihood increases, the positive impact of transformational leadership on these attitudes diminishes. These findings underscore the contextual nature of leadership effectiveness in high-risk settings and highlight the importance of contextual factors in understanding leadership styles. Full article

Aircraft cargo compartment fires represent a major threat to aviation safety due to their rapid development, concealment, and the challenges associated with suppression in confined spaces. This study analyzes the 2019 A330 cargo compartment fire at Beijing Capital International Airport as a representative case. Based on flight crew statements, ECAM alerts, surveillance footage, and firefighting records, the event timeline was reconstructed and the emergency response process examined. The analysis identified four defining characteristics of cargo fires: rapid escalation, interacting hazards, restricted accessibility, and prolonged suppression duration. To address these challenges, a three-stage investigation framework—comprising timeline reconstruction, evidence analysis, and experimental verification—is proposed to systematically determine the causes of fires. In addition, a portable penetrating fire-suppression device was designed and experimentally validated. Results confirm its effectiveness in achieving rapid agent delivery, enhanced structural cooling, and prevention of re-ignition. The findings demonstrate that comprehensive cargo fire investigations require the integration of multi-source data and experimental validation, while tactical and equipment innovations are critical for improving suppression efficiency in confined environments. This research provides practical insights for optimizing cargo fire investigation methodologies and emergency response strategies, thereby contributing to the advancement of aviation safety management systems. Full article

This study examined the impact of a shift schedule change on firefighter sleep and health outcomes (n = 24). Firefighters from a U.S. department transitioned from a 24 h on, 48 h off (24/48) schedule to a 48 h on, 96 h off (48/96) schedule. Wrist actigraphy and self-reported health outcomes were assessed at three time points: baseline (24/48), 3 months post-transition, and 6 months post-transition. Objective sleep measures included total sleep time (TST), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO). Self-reported health outcomes included the Insomnia Severity Index (ISI), Beck Depression Inventory–II (BDI-II), Beck Anxiety Inventory (BAI), Multidimensional Assessment of Fatigue (MAF), and the Alcohol Use Disorders Identification Test (AUDIT). Linear mixed-effects models (LMMs) with random intercepts were used to evaluate changes over time, adjusting for age, years of service, and individual night-time call volume. Results showed significant improvements in TST, SE, SOL, and WASO at the 3-month follow-up, which were sustained but did not further increase at 6 months. ISI and BDI-II scores also improved, while BAI, MAF, and AUDIT remained stable. These findings suggest that the 48/96 schedule may provide short-term improvements in sleep and psychological health for firefighters in low call-volume settings. Additional research is needed in higher-volume departments and over longer timeframes. Full article

The accurate acquisition and real-time calculation of the attitude angle of precision firefighting extinguishing projectiles are essential for ensuring stable flight and precise extinguishing agent release. However, measuring the roll attitude angle in such projectiles is challenging due to their highly dynamic nature and environmental disturbances such as fire smoke, high temperature, and electromagnetic interference. Traditional methods for measuring attitude angles rely on multi-sensor fusion schemes, which suffer from complex structure and high cost. This paper proposes a single-gyro attitude calculation method based on micro-electromechanical inertial measurement units (MIMUs). This method integrates Fourier transform time-frequency analysis with a second-order Infinite Impulse Response (IIR) bandpass filtering algorithm optimized by dynamic coefficients. Unlike conventional fixed-coefficient filters, the proposed algorithm adaptively updates filter parameters according to instantaneous roll angular velocity, thereby maintaining tracking capability under time-varying conditions. This theoretical contribution provides a general framework for adaptive frequency-tracking filtering, beyond the specific engineering case of firefighting projectiles. Through joint time-frequency domain processing, it achieves high-precision dynamic decoupling of the roll angle, eliminating the dependency on external sensors (e.g., radar/GPS) inherent in conventional systems. This approach drastically reduces system complexity and provides key technical support for low-cost and high-reliability firefighting projectile attitude control. The research contributes to enhancing the effectiveness of urban firefighting, forest fire suppression, and public safety emergency response. Full article

This research highlights the issue that large amount of sweat generated by metabolism cannot be discharged from the internal environment of traditional fire suits when firefighters are intensively operating in high-temperature environments. This is highly prone to bacterial growth, which brings much harm to their health. Therefore, this study aims to present a new fire-retardant fabric with both antibacterial and high hygroscopic properties. Blended fibers were used including aramid 1313 fibers with excellent flame retardancy and flame-retardant viscose fibers. By uniformly embedding antibacterial nanofibers into the microfiber aggregates and controlling the adhesion behavior at the cross-scale interfaces of micro–nano fibers, the fire-retardant yarns were endowed with both antibacterial and moisture-transporting properties. The bacterial inhibition rate was calculated by comparing colonies cultured on EF fabric versus NF fabric. Additionally, the antibacterial and moisture-wicking properties of the fabrics were verified through tests such as placing the fabrics vertically in liquid to measure the height of absorbed moisture. This prepared functionally integrated fabric has excellent antibacterial properties even after 50 washing cycles. Its antibacterial rate against Escherichia coli and Staphylococcus aureus kept a preferred result of 99%. Its moisture-transporting performance has also been significantly improved. Based on the above, this study has not only successfully developed a flame-retardant fabric with high antibacterial and moisture-wicking properties, but more importantly, the method demonstrates a degree of universal applicability. Full article

Firefighters wear bunker gear for protection against thermal hazards during firefighting. Bunker gear are fabricated from superior-performance fibers and enhanced by chemical flame retardants to increase fire resistance. However, brominated flame retardants (BFRs), which are widely used, have been associated with health and environmental toxicity risks. Despite the concerns, toxic BFRs continue to find application in consumer products, including in firefighter bunker gear. This study investigated the possibility of volatilization of BFRs from firefighter bunker gear during thermal exposure. Five different bunker gear samples were subjected to 3–8 kW/m² thermal conditions in a cone calorimeter, and polyurethane foam disks were used to capture the volatilizing effluents. The samples were analyzed for brominated diphenyl ether (BDE) congeners (-28, -47, -99, -100, -154, and -209) using gas chromatography–mass spectrometry. BDE-28, -47, and -99 were detected in all five samples, with concentrations ranging from 0.02 to 0.1 ng/g, 0.03 to 0.34 ng/g and 0.18 to 0.86 ng/g, respectively. BDE-100 and -154 were detected in 80% and -209 was below the limit of detection. BDE-99 was the most abundant congener detected, followed by BDE-47. The results confirm the volatilization of BFRs from bunker gear during firefighting, which can expose firefighters to toxic flame retardants. Full article

In real-world fire scenarios, complex lighting conditions and smoke interference significantly challenge the accuracy and robustness of traditional fire detection systems. Fusion of complementary modalities, such as visible light (RGB) and infrared (IR), is essential to enhance detection robustness. However, spatial shifts and geometric distortions occur in multi-modal image pairs collected by multi-source sensors due to installation deviations and inconsistent intrinsic parameters. Existing multi-modal fire detection frameworks typically depend on pre-registered data, which struggles to handle modal misalignment in practical deployment. To overcome this limitation, we propose an end-to-end multi-modal Fire Salient Object Detection framework capable of dynamically fusing cross-modal features without pre-registration. Specifically, the Channel Cross-enhancement Module (CCM) facilitates semantic interaction across modalities in salient regions, suppressing noise from spatial misalignment. The Deformable Alignment Module (DAM) achieves adaptive correction of geometric deviations through cascaded deformation compensation and dynamic offset learning. For validation, we constructed an unregistered indoor fire dataset (Indoor-Fire) covering common fire scenarios. Generalizability was further evaluated on an outdoor dataset (RGB-T Wildfire). To fully validate the effectiveness of the method in complex building fire scenarios, we conducted experiments using the Fire in historic buildings (Fire in historic buildings) dataset. Experimental results demonstrate that the F1-score reaches 83% on both datasets, with the IoU maintained above 70%. Notably, while maintaining high accuracy, the number of parameters (91.91 M) is only 28.1% of the second-best SACNet (327 M). This method provides a robust solution for unaligned or weakly aligned modal fusion caused by sensor differences and is highly suitable for deployment in intelligent firefighting systems. Full article

Coal spontaneous combustion causes both human casualties and environmental pollution. Owing to special flow behaviors, foam materials used in fire-fighting technology can effectively bring water and solid non-combustible substances into the fire-fighting area, greatly preventing spontaneous combustion. This paper systematically elucidates three foam materials, three-phase foam, gel foam and curing foam, and analyzes their physical and chemical inhibition mechanisms on coal spontaneous combustion. In particular, the preparation, performance and latest chemical modification methods of the foam materials are summarized in detail. It is found that foam materials with environmental friendliness, economy and excellent anti-fire performance need to be consistently explored. The primary application areas for cement-based foamed materials remain the building materials and civil engineering industries, and their modification should be studied accordingly based on the specific application context. Furthermore, a new component of foam materials, coal gasification slag (a solid waste), is proposed. In addition, the seepage properties of fire-fighting foam in porous media should be fully studied to accurately grasp the dispersion of foam materials in mine goafs. This review provides new insights and guidance for the development of fire-fighting foam materials. Full article

Remote sensing of wildland fires has become an integral part of fire science. Airborne sensors provide high spatial resolution and can provide high temporal resolution, enabling fire behavior monitoring at fine scales. Fire agencies frequently use airborne long-wave infrared (LWIR) imagery for fire monitoring and to aid in operational decision-making. While tactical remote sensing systems may differ from scientific instruments, our objective is to illustrate that operational support data has the capacity to aid scientific fire behavior studies and to facilitate the data analysis. We present an image processing algorithm that automatically delineates active fire edges in tactical LWIR orthomosaics. Several thresholding and edge detection methodologies were investigated and combined into a new algorithm. Our proposed method was tested on tactical LWIR imagery acquired during several fires in California in 2020 and compared to manually annotated mosaics. Jaccard index values ranged from 0.725 to 0.928. The semi-automated algorithm successfully extracted active fire edges over a wide range of image complexity. These results contribute to the integration of infrared fire observations captured during firefighting operations into scientific studies of fire spread and support landscape-scale fire behavior modeling efforts. Full article

(1) Background: Firefighters, exposed to diverse and unpredictable occupational environments, face cumulatively increased physical health risks. The purpose of this study was to assess the standardized prevalence ratios (SPRs) of occupational and chronic diseases in firefighters and the general population, categorized into pre-disease and disease stages; (2) Methods: This study was a community-based, retrospective, cross-sectional study. Data sources included the occupational health examination of 7024 firefighters and the National Health and Nutrition Examination Survey of 1485 general populations in 2019. Statistical analyses were performed using SAS version 9.4 SAS Institute Inc., Cary, NC, USA. SPRs of chronic and occupational diseases were calculated for each pre-disease and disease stage, and chi-square tests were performed; (3) Results: Data were analyzed from a cohort of 7024 firefighters who consented to the access and use of their occupational health examination results, 91.9% (n = 6456) were male, the average age was 43 years, the average number of years of service was 15.3 years. Among the five classifications of the occupational health examination results, 26.7% (n = 1877) were A, 19.2% (n = 1352) were C1, 42.4% (n = 2980) were C2, 1.5% (n = 108) were D1, and 10% (n = 705) were D2. As a result of calculating the SPRs compared to the general population, in the pre-disease stage, obesity SPR = 1.29 (95% confidence interval [CI] 1.23 to 1.34), hypertension SPR = 1.52 (95% CI 1.47 to 1.57), diabetes mellitus SPR = 1.07 (95% CI 1.02 to 1.11), and metabolic syndrome SPR = 1.62 (95% CI 1.57 to 1.66) were all higher in the firefighter group. On the other hand, in the disease stage, metabolic syndrome and complex pulmonary ventilation impairment were higher in SPRs than in the general population, but not statistically significant. However, at the disease stage, SPRs for obesity, hypertension, diabetes, and noise-induced hearing loss were higher and statistically significant in the general population; (4) Conclusions: The SPRs for firefighters produced in this study clearly demonstrate the healthy worker effect. The SPRs, derived from a cross-sectional study, highlight the need for future cohort building of firefighters to track and monitor health outcomes, as well as systematic and thorough health management interventions to prevent progression from pre-disease to disease. Therefore, this study can be utilized in the development of mid-to-long-term firefighter health promotion programs and health and safety plans to minimize firefighters’ physical health and occupational exposures. Full article

This paper examines the state-of-the-art in fire suppression technologies based on computer vision applications in the subject areas of computer science and engineering. The study involves a two-stage analysis of publications using keywords. This paper presents a bibliographic analysis of scientific literature from the Scopus database using VOSviewer software and the author’s methodological approach. General keywords were used for the initial analysis of the dataset, followed by a more detailed study with additional criteria and specific keywords. The categories considered in the article are as follows: Firefighting Robots, Fire Detection, Fire Suppression, Aerial Vehicles, and Computer Vision. It is shown that the research includes technical aspects of fire robots and systems, as well as the improvement of their software and hardware. The subsequent review highlights the important role of computer vision in improving the efficiency and effectiveness of fire suppression systems. It is noted that key advances include the development of sophisticated fire detection algorithms and the implementation of automated fire suppression systems. The study also discusses the challenges and future directions in this field, emphasizing the need for continuous innovation and interdisciplinary collaboration. This review provides valuable information for researchers, engineers, and practitioners in the field of fire safety by offering a comprehensive overview of state-of-the-art technologies and their applications in fire suppression. Full article

This paper presents a method for functionally extending an IoT indoor air quality monitoring network by adding a cloud-level fire detection logic component. The proposed method does not aim to replace traditional fire detection systems at this stage of research, but to propose a solution for the development of fire detection capabilities and to improve the support provided to firefighting teams by providing a geospatial representation of the building in which a fire occurs. The proposed solution is based on a series of laboratory tests that demonstrated that air quality sensors can successfully detect the effects caused by an ignition event of common materials and can differentiate fire events from other events that can generate false-positive alarms by classic detection systems. The research involved five laboratory combustion tests based on the measurement of temperature, humidity, PM2.5 particle concentration, volatile organic compound index, and nitrogen oxide index. Following the tests, a warning mechanism and geospatial representation were designed using a system with ten IoT sensors to monitor the indoor air quality in a building on our university’s campus. Full article

With the enlargement of underground parking lots, the risk of massive smoke and toxic gases generated during a fire will be increased, resulting in significant casualties, property damage, and difficulties in firefighting operations. To address these issues, installation of ventilation fans and inducer fans together has been proposed to extract smoke and hazardous gases more efficiently to the outside. However, the disturbance of ventilation caused by simultaneous operation of inducer fans and ventilation fans limits smoke extraction efficiency. In some worst cases, smoke disturbance may even lead to further smoke spread. Therefore, this study aims to suggest an efficient smoke extraction strategy for underground parking lots equipped with ventilation and inducer fans by optimizing the orientation of ventilation fans in the event of vehicle fires. Computational fluid dynamics-based simulation results showed that installing ventilation fan intakes and exhausts perpendicularly (PE, 90° apart) was more effective in controlling smoke than installing them in parallel (PA, horizontally facing each other). In the case of PE, the smoke stagnation area around the intakes decreased markedly from 38.18% to 3.68%. Although the smoke area near the exhausts increased in the PE configuration (53.66%) compared with the PA configuration (26.13%), this indicates that smoke was being effectively transported from the intakes to the exhausts. Furthermore, the overall smoke distribution across the entire space decreased by 4.5% under the PE setup compared with the PA setup. As the intake and exhaust flow rates of the fans increased, the efficiency of smoke removal was enhanced under the PE configuration. Consequently, in environments equipped with both ventilation and inducer fans with given conditions, perpendicular installation of fan intakes and exhausts is more efficient. These results are expected to provide practical design guidelines for ensuring effective smoke extraction in underground parking facilities. Full article