Search Results (275)

During large-scale pavement construction, the preparation of SBS-modified asphalt typically produces large amounts of harmful fumes. The emergence of deodorants can effectively alleviate the problem of smoke emissions during the asphalt manufacturing process. On the basis of ensuring the original road performance, exploring more suitable dosages and types of deodorant is urgently needed. Five commercial deodorants were evaluated using an asphalt smoke collection system, and UV-visible spectrophotometry (UV) was employed to screen the deodorants based on smoke concentration. Gas chromatography–mass spectrometry (GC-MS) was used to quantitatively analyze changes in harmful smoke components before and after adding two deodorants. Subsequently, the mechanisms of action of the two different types of deodorants were analyzed microscopically using fluorescence microscopy. Finally, the performance of bitumen and asphalt mixtures after adding deodorants was evaluated. The results showed that deodorant A (reactive type) and D (adsorption type) exhibited the best smoke suppression effects, with optimal addition rates of 0.6% and 0.5%, respectively. Deodorant A reduced benzene homologues by nearly 50% and esters by approximately 40%, while deodorant D reduced benzene homologues by approximately 70% and esters by approximately 60%, without producing new toxic gases. Both deodorants had a minimal impact on the basic properties of bitumen and the road performance of asphalt mixtures, with all indicators meeting technical specifications. This research provides a theoretical basis for the effective application of deodorants in the future, truly enabling a transition from laboratory research to large-scale engineering applications in the construction of environmentally friendly roads. Full article

There are significant scale and morphological differences between fire and smoke features in forest fire detection. This paper proposes a detection method based on dual-branch multi-scale adaptive feature fusion network (DMAFNet). In this method, convolutional neural network (CNN) and transformer are used to form a dual-branch backbone network to extract local texture and global context information, respectively. In order to overcome the difference in feature distribution and response scale between the two branches, a feature correction module (FCM) is designed. Through space and channel correction mechanisms, the adaptive alignment of two branch features is realized. The Fusion Feature Module (FFM) is further introduced to fully integrate dual-branch features based on the two-way cross-attention mechanism and effectively suppress redundant information. Finally, the Multi-Scale Fusion Attention Unit (MSFAU) is designed to enhance the multi-scale detection capability of fire targets. Experimental results show that the proposed DMAFNet has significantly improved in mAP (mean average precision) indicators compared with existing mainstream detection methods. Full article

Smoke appears earlier than flames, so image-based fire monitoring techniques mainly focus on the detection of smoke, which is regarded as one of the effective strategies for preventing the spread of initial fires that eventually evolve into serious fires. Smoke monitoring in mine fires faces serious challenges: the underground environment is complex, with smoke and backgrounds being highly integrated and visual features being blurred, which makes it difficult for existing image-based monitoring techniques to meet the actual needs in terms of accuracy and robustness. The conventional ground-based methods are directly used in the underground with a high rate of missed detection and false detection. Aiming at the core problems of mixed target and background information and high boundary uncertainty in smoke images, this paper, inspired by the principle of information entropy, proposes a method for recognizing smoke from mine fires by integrating entropy-enhanced image processing and improved YOLOv8. Firstly, according to the entropy change characteristics of spatio-temporal information brought by smoke diffusion movement, based on spatio-temporal entropy separation, an equidistant frame image differential fusion method is proposed, which effectively suppresses the low entropy background noise, enhances the detail clarity of the high entropy smoke region, and significantly improves the image signal-to-noise ratio. Further, in order to cope with the variable scale and complex texture (high information entropy) of the smoke target, an improvement mechanism based on entropy-constrained feature focusing is introduced on the basis of the YOLOv8m model, so as to more effectively capture and distinguish the rich detailed features and uncertain information of the smoke region, realizing the balanced and accurate detection of large and small smoke targets. The experiments show that the comprehensive performance of the proposed method is significantly better than the baseline model and similar algorithms, and it can meet the demand of real-time detection. Compared with YOLOv9m, YOLOv10n, and YOLOv11n, although there is a decrease in inference speed, the accuracy, recall, average detection accuracy mAP (50), and mAP (50–95) performance metrics are all substantially improved. The precision and robustness of smoke recognition in complex mine scenarios are effectively improved. Full article

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide, primarily driven by chronic airway inflammation due to cigarette smoke exposure. Despite its burden, however, current anti-inflammatory therapies offer limited efficacy in preventing disease progression. Plasminogen activator inhibitor-1 (PAI-1), as a key regulator of fibrinolysis, has recently been implicated in structural airway changes and persistent inflammation in patients with COPD. This study aimed to investigate the ability of the PAI-1 inhibitor TM5441 to attenuate airway inflammation and structural lung damage induced by a cigarette smoke extract (CSE) in a mouse model. Mice received intratracheal CSE or vehicle on days 1, 8, and 15, and were sacrificed on day 22. TM5441 (20 mg/kg) was administered orally from days 1 to 22. The CSE significantly increased the mean linear intercept, destructive index, airway resistance, and reductions in dynamic compliance. The CSE also increased the numbers of neutrophils and macrophages in the bronchoalveolar lavage fluid, systemic PAI-1 activity, and neutrophil elastase mRNA and protein expression in the lungs. TM5441 treatment significantly suppressed these changes without affecting coagulation time. These findings suggest that TM5441 may be a novel therapeutic agent for COPD by targeting PAI-1-mediated airway inflammation and emphysema. Full article

This study presents the design and validation of an integrated fire safety system that leverages edge AI, hybrid sensing, and precision suppression to overcome the latency and collateral limitations of conventional smoke detection and sprinkler systems. The proposed platform features a dual-mode sensor array for early fire recognition, motorized ventilation units for rapid smoke extraction, and a 360° directional nozzle for targeted agent discharge using a residue-free clean extinguishing agent. Experimental trials demonstrated an average fire detection time of 5.8 s and complete flame suppression within 13.2 s, with 90% smoke clearance achieved in under 95 s. No false positives were recorded during non-fire simulations, and the system remained fully functional under simulated cloud communication failure, confirming its edge-resilient architecture. A probabilistic risk analysis based on ISO 31000 and NFPA 551 frameworks showed risk reductions of 75.6% in life safety, 58.0% in property damage, and 67.1% in business disruption. The system achieved a composite risk reduction of approximately 73%, shifting the operational risk level into the ALARP region. These findings demonstrate the system’s capacity to provide proactive, energy-efficient, and spatially targeted fire response suitable for high-value infrastructure. The modular design and SmartThings Edge integration further support scalable deployment and real-time system intelligence, establishing a strong foundation for future adaptive fire protection frameworks. Full article

Fire refers to a disaster caused by combustion that is uncontrolled in the temporal and spatial dimensions, occurring in diverse complex scenarios where timely and effective detection is crucial. However, existing fire detection methods are often challenged by the deformation of smoke and flames, resulting in missed detections. It is difficult to accurately extract fire features in complex backgrounds, and there are also significant difficulties in detecting small targets, such as small flames. To address this, this paper proposes a YOLO-Multi-scenario Fire Detector (YOLO-MFD) for multi-scenario fire detection. Firstly, to resolve missed detection caused by deformation of smoke and flames, a Scale Adaptive Perception Module (SAPM) is proposed. Secondly, aiming at the suppression of significant fire features by complex backgrounds, a Feature Adaptive Weighting Module (FAWM) is introduced to enhance the feature representation of fire. Finally, considering the difficulty in detecting small flames, a fine-grained Small Object Feature Extraction Module (SOFEM) is developed. Additionally, given the scarcity of multi-scenario fire datasets, this paper constructs a Multi-scenario Fire Dataset (MFDB). Experimental results on MFDB demonstrate that the proposed YOLO-MFD achieves a good balance between effectiveness and efficiency, achieving good effective fire detection performance across various scenarios. Full article

Researchers have tended to blend isopropanol (IPA) with other fuels in diesel engines to reduce emissions and improve performance. However, low-reactivity controlled compression ignition via port injection at a low cetane number results in a well-mixed charge of low-reactivity fuel, air, and recirculated exhaust gas (EGR). This study’s novel approach combines critical elements, such as the mass fraction of port-injected IPA, EGR ratio, and charge temperature, to improve combustion characteristics and lessen emissions from a diesel engine. The results demonstrated that the injection of IPA and the installation of EGR at the inlet reduced NO_x, smoke, and PM_2.5. On the contrary, HC and CO increased with the port-injection of IPA and EGR. Preheating air at the inlet can suppress the emissions of HC and CO. Under 1500 rpm and 60% load, when compared to diesel at the same EGR ratio and charge temperature, the maximum smoke decrease rate (26%) and PM_2.5 decrease rate (21%) occur at 35% IPA, 45 °C, and 10% EGR, while the maximum NO_x decrease rate (24%) occurs at 35% IPA, 60 °C, and 20% EGR. These findings support the novelty of the research. Conversely, it modestly increased CO and HC emissions. However, port-injecting IPA increased thermal efficiency by up to 24% at 60 °C, 1500 rpm, and 60% load with EGR. Full article

Polyamide 6,6 (PA6,6) fabrics are widely used in textiles due to their high mechanical strength and chemical stability. However, their inherent flammability and melting behavior under fire pose significant safety challenges. In this study, a dual-layer flame-retardant system was developed by integrating atomic layer deposition (ALD) of ZnO with a phosphorus–silane-based flame retardant (DOPO-ETES). ALD allowed precise control of ZnO layer thickness (50, 84, and 199 nm), ensuring uniform coating. Thermal analysis (TGA) and microscale combustion calorimetry (MCC) revealed that ZnO altered the degradation pathway of PA6,6 through catalytic effects, promoting char formation and reducing heat release. The combination of ZnO and DOPO-ETES resulted in further reductions in heat release rates. However, direct flame tests showed that self-extinguishing behavior was not achieved, emphasizing the limitations related to the melting of PA6,6. TG-IR and cone calorimetry confirmed that ZnO coatings suppressed the release of smoke-related volatiles and incomplete combustion products. These findings highlight the potential of combining metal-based catalytic flame retardants like ZnO with phosphorus-based coatings to improve flame retardancy while addressing the specific challenges of polyamide textiles. This approach may also be adapted to other fabric types and integrated with additional flame retardants, broadening its relevance for textile applications. Full article

Forest fire detection is vital for ecological conservation and disaster management. Existing visual detection methods exhibit instability in smoke-obscured or illumination-variable environments. Although multimodal fusion has demonstrated potential, effectively resolving inconsistencies in smoke features across diverse modalities remains a significant challenge. This issue stems from the inherent ambiguity between regions characterized by high temperatures in infrared imagery and those with elevated brightness levels in visible-light imaging systems. In this paper, we propose MCDet, an RGB-T forest fire detection framework incorporating target-aware fusion. To alleviate feature cross-modal ambiguity, we design a Multidimensional Representation Collaborative Fusion module (MRCF), which constructs global feature interactions via a state-space model and enhances local detail perception through deformable convolution. Then, a content-guided attention network (CGAN) is introduced to aggregate multidimensional features by dynamic gating mechanism. Building upon this foundation, the integration of WIoU further suppresses vegetation occlusion and illumination interference on a holistic level, thereby reducing the false detection rate. Evaluated on three forest fire datasets and one pedestrian dataset, MCDet achieves a mean detection accuracy of 77.5%, surpassing advanced methods. This performance makes MCDet a practical solution to enhance early warning system reliability. Full article

Fire-resistant coatings have emerged as crucial materials for reducing fire hazards in various industries, including construction, textiles, electronics, and aerospace. This review provides a comprehensive account of recent advances in fire-resistant coatings, emphasizing environmentally friendly and high-performance systems. Beginning with a classification of traditional halogenated and non-halogenated flame retardants (FRs), this article progresses to cover nitrogen-, phosphorus-, and hybrid-based systems. The synthesis methods, structure–property relationships, and fire suppression mechanisms are critically discussed. A particular focus is placed on bio-based and waterborne formulations that align with green chemistry principles, such as tannic acid (TA), phytic acid (PA), lignin, and deep eutectic solvents (DESs). Furthermore, the integration of nanomaterials and smart functionalities into fire-resistant coatings has demonstrated promising improvements in thermal stability, char formation, and smoke suppression. Applications in real-world contexts, ranging from wood and textiles to electronics and automotive interiors, highlight the commercial relevance of these developments. This review also addresses current challenges such as long-term durability, environmental impacts, and the standardization of performance testing. Ultimately, this article offers a roadmap for developing safer, sustainable, and multifunctional fire-resistant coatings for future materials engineering. Full article

Background: Breast cancer (BC) is the second most common cancer among women in the United States. It has been estimated that one in eight women will be diagnosed with breast cancer in her lifetime. Various BC risk factors, such as age, physical inactivity, and smoking, play a substantial role in BC occurrence and development. Early life dietary intervention with plant-based bioactive compounds has been studied for its potential role in BC prevention. Sulforaphane (SFN), an isothiocyanate, is an antioxidant and anti-inflammatory agent extracted from broccoli sprouts (BSp) and other plants. Dietary supplementation of SFN suppresses tumor growth by inducing protective epigenetic changes and inhibiting cancer cell proliferation. Inulin, as a dietary fiber, has been studied for alleviating GI discomfort and weight loss by promoting the growth of beneficial bacteria in the gut. Objective: Early-life combinatorial treatment with both phytochemical SFN and potential prebiotic agent inulin at lower and safer dosages may confer more efficacious and beneficial effects in BC prevention. Methods: Transgenic mice representing estrogen receptor-negative BC were fed 26% (w/w) BSp and 2% (w/v) inulin supplemented in food and water, respectively. Results: The combinatorial treatment inhibited tumor growth, increased tumor onset latency, and synergistically reduced tumor weight. Gut microbial composition was analyzed between groups, where Ruminococcus, Muribaculaceae, and Faecalibaculum significantly increased, while Blautia, Turicibacter, and Clostridium sensu stricto 1 significantly decreased in the combinatorial group compared with the control group. Furthermore, combinatorial treatment induced a protective epigenetic effect by inhibiting histone deacetylases (HDACs) and DNA methyltransferases (DNMTs). Intermediates in the AKT/PI3K/MTOR pathway were significantly suppressed by the combinatorial treatment, including PI3K p85, p-AKT, p-PI3K p55, MTOR, and NF-κB. Cell cycle arrest and programmed cell death were induced by the combinatorial treatment via elevating the expression of cleaved-caspase 3 and 7 and inhibiting the expressions of CDK2 and CDK4, respectively. Orally administering F. rodentium attenuated tumor growth and induced apoptosis in a syngeneic triple-negative breast cancer (TNBC) mouse model. Conclusions: Overall, the findings suggest that early-life dietary combinatorial treatment contributed to BC prevention and may be a potential epigenetic therapy that serves as an adjunct to other traditional neoadjuvant therapies. Full article

Epoxy resins are limited by their flammability and brittleness. In this study, a phosphorus- and silicon-based additive was synthesized to improve fire resistance and mechanical performance. The incorporation of just 1 wt% phosphorus from this additive into epoxy resin achieved a limiting oxygen index of 33% and a V-0 fire rating. The modified epoxy exhibited a 52.43% reduction in the peak heat release rate and a 35.70% decrease in total smoke production compared to the unmodified resin, demonstrating enhanced heat resistance and smoke suppression. Notably, the modified epoxy thermoset displayed superior mechanical properties, with tensile and impact strengths increasing by 48.41% and 130%, respectively. This research presents a promising approach for developing high-performance epoxy resins with improved flame retardancy, smoke suppression, and mechanical strength. Full article

This study investigates the spread patterns of tunnel fires and examines issues related to emergency response. It focuses on the temperature characteristics, spread patterns, conditions leading to multi-source fires, and the efficacy of water mist suppression methods in heavy-haul railway tunnel fires. The research employs theoretical derivations and numerical simulations to achieve its objectives. It was discovered that, during a fire in a heavy-haul railway tunnel, the temperature inside the tunnel can exceed 500 °C. Furthermore, depending on the nature of the goods transported by the train and under specific wind speed conditions, the fire source has the potential to spread to other carriages, resulting in a multi-source fire. Using the numerical simulation software Pyrosim 2022, various wind speed conditions were simulated. The results revealed that at lower wind speeds, the smoke demonstrates a reverse flow phenomenon. Concurrently, when the adjacent carriage on the leeward side of the fire is ignited, the high-temperature reverse flow smoke, along with the thermal radiation from the flames, ignites combustible materials in the adjacent carriage on the windward side of the burning carriage. Through theoretical derivation and numerical simulation, the critical wind speed for the working conditions was determined to be 2.14 m/s. It was found that while a higher wind speed can lead to a decrease in temperature, it also increases the flame deflection angle. When the wind speed exceeds 2.4 m/s, although the temperature significantly drops in a short period, the proximity of combustible materials on the leeward side of the carriage becomes a concern. At this wind speed, the flame deflection angle causes heat radiation on the leeward side, specifically between 0.5 m and 3 m, to ignite the combustible materials on the carriage surface, resulting in fire spread and multiple fire incidents. The relationship between wind speed and the angle of deflection from the fire source was determined using relevant physics principles. Additionally, the relationship between wind speed and the trajectory of water mist spraying was established. It was proposed to optimize the position of the water mist based on its deviation, and the results indicated that under critical wind speed conditions, when the water mist spraying is offset approximately 5 m towards the upwind side of the fire source, it can act more directly on the surface of the fire source. Numerical simulation results show a significant reduction in the maximum temperature and effective control of fire spread. Under critical wind speed conditions, the localized average temperature of the fire decreased by approximately 140 °C when spraying was applied, compared to the conditions without spraying, and the peak temperature decreased by about 190 °C. This modification scheme can effectively suppress the threat of fire to personnel evacuation under simulated working conditions, reflecting effective control over fires. Additionally, it provides theoretical support for the study of fire patterns in tunnels and emergency response measures. Full article

Background: Previously, we found that an uncharacterized protein CXorf38 is significantly downregulated in human ZIP8-knockout (KO) cells. Given that ZIP8 regulates essential micronutrients linked to diseases including cancer, this study aims to characterize CXorf38 and evaluate its role in lung adenocarcinoma. Methods: iTRAQ-based proteomics was previously used to identify the abundance of proteins in ZIP8-KO cells. Cell proliferation and colony formation assays were used to examine the function of CXorf38 by overexpressing the gene in lung adenocarcinoma cell lines. Kaplan–Meier survival analysis was used to assess the prognostic value of CXorf38, while TCGA clinical database analysis was used to evaluate its expression in lung cancer tissues, particularly in smokers. Bioinformatics analyses (GO, KEGG, PPI, and ICI) were performed on CXorf38-coexpressed genes derived from patients with lung cancer. Results: CXorf38 overexpression suppressed lung cancer cell proliferation and colony formation, suggesting a tumor-suppressive role. Higher CXorf38 expression correlated with improved survival in patients with lung adenocarcinoma, but not in lung squamous cell carcinoma. Clinical data showed CXorf38 downregulation with lung cancer tissues of smokers, indicating a potential role in smoking-induced cancer progression and treatment. Functional analysis using bioinformatics linked CXorf38 to immune response regulation, suggesting involvement in the tumor immune microenvironment. Conclusions: Our study reveals for the first time that CXorf38 is a potential tumor suppressor, prognostic biomarker, and/or tumor immune regulator in lung adenocarcinoma—further research is warranted to explore its role in tumor immunity and its therapeutic potential. Full article

Marine diesel engines face persistent challenges in balancing transient black smoke emissions and maneuverability under low-speed conditions due to inherent limitations of single turbocharger systems, such as high inertia and delayed intake response, compounded by control strategies prioritizing steady-state efficiency. To address this gap, this study proposes a dual -turbocharger dynamic matching framework integrated with a speed–pitch synergistic control strategy—the first mechanical-control co-design solution for transient emission suppression. By establishing a λ-opacity correlation model and a multi-physics ship–engine–propeller simulation platform, we demonstrate that the Type-C dual turbocharger reduces rotational inertia by 80%, shortens intake pressure buildup time to 25.8 s (54.7% faster than single turbochargers), and eliminates high-risk black smoke regions (maintaining λ > 1.5). The optimized system reduces the fuel consumption rate by 12.9 g·(kW·h)⁻¹ under extreme loading conditions and decreases the duration of high-risk zones by 74.4–100%. This study provides theoretical and practical support for resolving the trade-off between transient emissions and maneuverability in marine power systems through synergistic innovations in mechanical design and control strategies. Full article