Search Results (2,036)

As a typical enclosed engineering microenvironment, tunnel construction sites exert a profound influence on workers’ unsafe behaviors. This impact is particularly significant in cold regions, where extreme environmental conditions are more likely to trigger unsafe behavior among construction workers. This study utilized two exemplary tunnels in cold regions of China as case studies. During the construction period, microenvironmental data were systematically collected, encompassing temperature, humidity, noise, and dust concentration. In parallel, data on workers’ unsafe behaviors were integrated to construct a nonlinear relationship model, and the importance of each microenvironmental variable was assessed using the random forest algorithm. The results indicate that various microenvironmental factors exhibit significant nonlinear effects on unsafe behavior. Among them, dust concentration had the strongest impact (22.56%), followed by noise (17.40%), humidity (15.02%), and temperature (9.21%). Specifically, the maintenance of temperature control close to 0 °C, humidity levels maintained at 60% to 65%, noise levels not exceeding 82 dB, and dust concentrations below 12 mg/m³ contributed to a significant reduction in unsafe behavior scores. The present study investigates the mechanism of the microenvironment of cold-region tunnel construction on personnel behavioral risk. The study’s findings provide a threshold reference and strategy support for safety optimization and engineering site management of cold-region tunnel construction environments. Full article

In recent decades, pollutant emissions from the combustion of fossil fuels have become increasingly serious for the environment. The present paper reports experimental results for research carried out under laboratory conditions for a Selective Catalytic Reduction (SCR) system, implemented in different configurations on an ISUZU 4JB1 diesel engine. The obtained results allow for a comparative analysis of NOx formation as a function of diesel engine load (χ = 25–100%), at 1350, 2100, 2850, and 3600 rpm, with the engine operating under either cold (T < 343 K) or warm (T > 343 K) regimes. A preheating system for AdBlue droplets, in the form of a metal honeycomb that uses electromagnetic induction and incorporates a high-frequency generator, was introduced in the flow path of the combustion gases and tested to compare the experimental results. This system enabled temperatures of up to 643 K. A magneto-strictive system was also introduced in the SCR structure to atomize the AdBlue droplets to a minimum diameter of 3.5 μm. Using this principle, combined with preheating, the effect of calefaction was compared with the classical case of the internal heating of the SCR catalyst. For experimental purposes, piezoelectric cells dedicated to the transformation of the AdBlue solution into micro- or nano-droplets, which were entrained into the SCR by an ejector, were also used. Experimental results are presented in graphical form and reveal that the use of preheating, heating, or piezoelectric cells leads to improved NOx conversion. The tested solutions showed reductions in NOx emissions of up to eight times depending on the diesel engine load, demonstrating their strong impact on NOx reduction. Full article

Structural parameters, such as strain or deflection, were collected by sensors and analyzed to assess the bridge’s structural condition and obtain a reliable reference for bridge maintenance. In the data acquisition and transmission process, sensor data inevitably contains noise and interference, resulting in anomalies, especially data distortion during wireless transmission. These anomalies significantly impact data analysis and structural evaluation. To mitigate the effects of these abnormalities, we conducted the cause analysis. The Sanxia Viaduct was used to design a strain monitoring method as a bridge model. We analyzed vibrating string sensor data collected in the cold environment using the Nair method to eliminate outlier data. The analysis results of strain and temperature trends showed that the data fusion method developed in this study showed high precision and stability and effectively reduced the impact of noise and data anomalies. By monitoring actual bridges, the effectiveness and practicality of the method were validated. The model provides significant information on the development and application of bridge health monitoring technology. Full article

E-commerce platforms offering regional fresh produce often face a trade-off between logistics costs and product quality. Due to limited use of cold chain logistics, consumers frequently receive damaged goods, resulting in negative post-purchase experiences. This study examines how logistics service encounters, as reflected in consumer reviews, influence subsequent purchase behaviour, and how the alignment between review images and text moderates this relationship. We analyse sales and review data from 694 fruit products on Tmall between February and April 2024. Latent Dirichlet Allocation (LDA) is applied to extract logistics-related review content. At the same time, image–text similarity is assessed using the Chinese-CLIP model. Regression analysis reveals that positive logistics service encounters significantly enhance purchase intention. However, high image–text similarity weakens this positive effect, suggesting that overly repetitive content may reduce informational value for prospective buyers. These findings advance understanding of consumer behaviour in online fresh produce markets by highlighting the interactive effects of logistics experiences and user-generated content. The results offer practical implications for improving logistics services, enhancing content diversity in review systems, and increasing consumer trust in e-commerce environments. Full article

Low-temperature environments in cold regions pose a significant threat to cattle farming. Bovine mammary epithelial cells (BMECs) are highly sensitive to cold stress, and acute cold stress can induce apoptosis, adversely affecting lactation performance and health. To explore the mechanism of acute cold stress-induced apoptosis in BMECs, we established an in vitro acute cold stress model. Results showed that mRNA levels of HSP90 increased significantly in a time-dependent manner after 2 h of cold stress, confirming successful model establishment. Following 4 h of cold stress, pro-apoptotic genes (Caspase-3, Bax) exhibited significantly elevated mRNA levels, while the anti-apoptotic gene (BCL-2) showed significantly reduced mRNA levels. Concurrently, the apoptosis rate increased significantly, indicating that acute cold stress induces apoptosis and suggesting the 4 h mark may represent a critical transition point. Integrated transcriptomic and functional analyses identified ENO1 as a core metabolic regulator counteracting acute cold stress-induced apoptosis in BMECs. As a multifunctional protein, ENO1 (alpha-enolase) acts as a central enzyme in glycolysis while exerting additional roles in cellular signaling and apoptotic processes, thereby participating in various pathophysiological regulations. Both mRNA and protein levels of ENO1 were significantly elevated in cold-stressed cells compared to untreated controls. Importantly, interference with ENO1 expression aggravated the extent of cold stress-induced apoptosis, demonstrating the regulatory role of ENO1 in this process. To our knowledge, this is the first report elucidating the core regulatory function of ENO1 in acute cold stress-induced apoptosis in BMECs. These findings provide a theoretical basis for understanding apoptotic mechanisms under stress. Full article

Although numerous observational and theoretical studies have examined the mean and turbulent structure of the tropical cyclone boundary layer (TCBL) over the open ocean, there have been comparatively fewer studies that have examined the kinematic and thermal structure of the TCBL across the land–ocean interface. This study examines the impact of different continental environments on the thermodynamic evolution of the TCBL during the landfall transition using high-resolution, full-physics numerical simulations. During landfall, the changes in the wind field within the TCBL due to the development of the internal boundary layer (IBL), combined with the formation of a surface cold pool, generates a pronounced thermal asymmetry in the boundary layer. As a result, the maximum thermodynamic boundary layer height occurs in the rear-right quadrant of the storm relative to its motion. In addition, azimuthal and vertical advection by the mean flow lead to enhanced turbulent kinetic energy (TKE) in front of the vortex (enhancing dissipative heating immediately onshore) and onshore precipitation to the left of the storm track (stabilizing the environment). The strength and depth of thermal asymmetry in the boundary layer depend on the contrast in temperature and moisture between the continental and storm environments. Dry air intrusion enhances cold pool formation and stabilizes the onshore boundary layer, reducing mechanical mixing and accelerating the decay of the vortex. The temperature contrast between the continental and storm environments establishes a coastal baroclinic zone, producing stronger baroclinicity and inflow on the left of the track and weaker baroclinicity on the right. The resulting gradient imbalance in the front-right quadrant triggers radial outflow through a gradient adjustment process that redistributes momentum and mass to restore dynamical balance. Therefore, the surface thermodynamic conditions over land play a critical role in shaping the evolution of the TCBL during landfall, with the strongest asymmetries in thermodynamic boundary layer height emerging when there are large thermal contrasts between the hurricane and the continental environment. Full article

The cold-chain supply of perishable fruits continues to face challenges such as fuel wastage, fragmented stakeholder coordination, and limited real-time adaptability. Traditional solutions, based on static routing and centralized control, fall short in addressing the dynamic, distributed, and secure demands of modern food supply chains. This study presents a novel end-to-end architecture that integrates multi-agent reinforcement learning (MARL), blockchain technology, and generative artificial intelligence. The system features large language model (LLM)-mediated negotiation for inter-enterprise coordination, Pareto-based reward optimization balancing spoilage, energy consumption, delivery time, and climate and emission impact. Smart contracts and Non-Fungible Token (NFT)-based traceability are deployed over a private Ethereum blockchain to ensure compliance, trust, and decentralized governance. Modular agents—trained using centralized training with decentralized execution (CTDE)—handle routing, temperature regulation, spoilage prediction, inventory, and delivery scheduling. Generative AI simulates demand variability and disruption scenarios to strengthen resilient infrastructure. Experiments demonstrate up to 50% reduction in spoilage, 35% energy savings, and 25% lower emissions. The system also cuts travel time by 30% and improves delivery reliability and fruit quality. This work offers a scalable, intelligent, and sustainable supply chain framework, especially suitable for resource-constrained or intermittently connected environments, laying the foundation for future-ready food logistics systems. Full article

Climate change poses significant challenges to agriculture in Türkiye, where diverse climatic conditions demand resilient forage crops to meet rising roughage demands. This study evaluates the performance of Hungarian vetch (Vicia pannonica Crantz), a cold- and drought-tolerant legume, to enhance sustainable forage production. Eight genotypes (Line-5, Line-16, Line-23, Line-28, Tarm White, Aegean White, Budak, and Oguz) were tested in Bilecik and Bingol during the 2015–2016 and 2016–2017 growing seasons using a randomized complete block design with three replications. Key traits such as pods per plant, thousand-seed weight, biological yield, seed yield, straw yield, and harvest index were analyzed using Genotype plus Genotype-by-Environment (GGE) biplot analysis based on Principal Component Analysis (PCA). The distribution of these traits was also examined using box plots. Results showed significant variations: pods per plant ranged from 17.5 to 21.7, thousand-seed weight from 26.8 to 42.6 g, biological yield from 5710 to 8780 kg ha⁻¹, seed yield from 826 to 1132 kg ha⁻¹, straw yield from 4997 to 7643 kg ha⁻¹, and harvest index (HI) from 13.9% to 21.0%. Aegean White excelled in seed yield, while Line-16 showed the highest harvest index. GGE biplot analysis highlighted harvest index as the primary variance contributor, emphasizing genotype-environment interactions for selecting adaptable cultivars for sustainable agriculture. Full article

Geopolymer binders are a promising low-carbon substitute for Portland cement, but their behavior in cold climates remains underexplored. This study investigates the influence of sodium nitrite (NaNO₂) on geopolymer properties cured at −10 °C for 28 days. The binders were formulated from bauxite residue, fly ash, and waste glass, and NaNO₂ was added in various dosages as a chemical admixture. The geopolymer was tested for its setting time, compressive strength, and chemical and morphological characterizations. The addition of the 3 wt% NaNO₂ significantly improved the strength retention in the cold environment, with a compressive strength of 40.7 MPa, compared to a geopolymer without an admixture (26.1 MPa). The X-ray diffraction (XRD) analysis confirmed the presence of gismondine, quartz, and FeSiO₃, with NaNO₂ remaining largely unreacted within the matrix. Fourier Transform Infrared Spectroscopy (FTIR) indicated the presence of Si–O–T bonds in the NaNO₂-modified samples, which showed continued geopolymerization at low temperatures. Scanning electron microscopy (SEM) revealed reduced cracking and a denser microstructure with increasing concentrations of NaNO₂. The results indicate that NaNO₂ not only mitigates the adverse effects of subzero curing but also promotes structure development, and hence it is a viable admixture for enhancing the cold weather durability of geopolymer materials. Full article

Polytetrafluoroethylene (PTFE) is one of the alternative materials suitable for seawater-lubricated bearings, favored for its excellent corrosion resistance and good self-lubricating properties. As marine equipment develops towards higher load, higher reliability, and longer service life, more stringent requirements are imposed on the wear resistance of bearing materials. However, traditional PTFE materials struggle to meet the performance requirements for long-term stable operation in modern marine environments. To improve the wear resistance of PTFE, this study used alumina (Al₂O₃) particles with three different particle sizes (50 nm, 3 μm, and 80 μm) as fillers and prepared Al₂O₃/PTFE composites via the cold pressing and sintering process. Tribological performance tests were conducted using a ball-on-disk reciprocating friction and wear tester, with Cr12 steel balls as counterparts, under an artificial seawater lubrication environment, applying a normal load of 10 N for 40 min. The microstructure and wear scar morphology were characterized by scanning electron microscopy (SEM), and mechanical properties were measured using a Shore hardness tester. A systematic study was carried out on the microstructure, mechanical properties, friction coefficient, wear rate, and limiting PV value of the composites. The results show that the particle size of Al₂O₃ particles significantly affects the mechanical properties, friction coefficient, wear rate, and limiting PV value of the composites. The 50 nm Al₂O₃/PTFE formed a uniformly spread friction film and transfer film during the friction process, which has better friction and wear reduction performance and load bearing capacity. The 80 μm Al₂O₃ group exhibited poor friction properties despite higher hardness. The nanoscale Al₂O₃ filler was superior in improving the wear resistance, stabilizing the coefficient of friction, and prolonging the service life of the material, and demonstrated good seawater lubrication bearing suitability. This study provides theoretical support and an experimental basis for the design optimization and engineering application of PTFE-based composites in harsh marine environments. Full article

Several decades after the development of FEM in computer-based form, which is a milestone in the evaluation of mechanical systems, the method has been adopted to analyze the biomechanical response of human skeletal structures. This innovative technique has generated new questions, but also new results, and, at the same time, competitive environments with explosive development, in the recent period. This research is focused on analyzing, using FEM, the extreme thermal variations produced at the level of two oro-facial systems (one control and one subjected to orthodontic therapy using a fixed metallic orthodontic appliance). The objective of the study was to determine the temperature evolution in different dental structures subjected to extreme temperatures given by variations between very cold and very hot foods. Each system was exposed to a succession of extreme thermal regimes (70…−18…70… °C and −18…70…−18… °C). In order to conduct this research, we used the case of a 14-year-old female patient. Following an orthodontic evaluation, we discovered that the patient had dento-alveolar disharmony with crowding. The straight-wire method of applying a fixed metallic orthodontic appliance was chosen. As complementary examinations, the patient was subjected to a bimaxillary CBCT. Using a series of programs (InVesalius, Geomagic, SolidWorks, and AnsysWorkbench), a three-dimensional model was obtained. This model contained jaws and teeth. Also, brackets, tubes, and orthodontic wires can be incorporated into the model. Following the simulations carried out in this study, it was found that thermal variations from the dental pulp are more severe for the oro-facial system with a fixed metallic orthodontic appliance (regardless of the type of thermal stimulus used). Thus, even today, with all the facilities available in the dental materials industry, metallic orthodontic devices present significant thermal conductivity, generating harmful effects on the dental structures. The reading of the results was performed on the virtual model, more precisely, on the internal dental structures (enamel, dentin, and pulp). A statistical study was not performed because it was considered that, in other patients, the results would be similar. Full article

Elevated chloride (Cl⁻) concentrations in surface water and groundwater are an increasing concern in cold region urban environments, largely due to long-term road salt application. This study investigates the Cl⁻ distribution across southern Ontario, Canada, using geospatial methods to identify contamination hot spots and assess groundwater vulnerability at both regional and watershed scales. Chloride data from 2001 to 2010 and 2011 to 2020 were compiled from public sources and interpolated using inverse distance weighting. A regional-scale vulnerability index was developed using slope (SL), surficial geology (SG), and land use (LU) (SL-SG-LU), and compared it to a more detailed DRASTIC-LU index within the Credit River watershed. Results show that Cl⁻ hot spots are concentrated in urbanized areas, including the Greater Toronto Area and Golden Horseshoe, with some rural zones also exhibiting elevated concentrations. Vulnerability mapping corresponded well with the observed Cl⁻ patterns and highlighted areas at risk for groundwater discharge to surface waters. While the DRASTIC-LU method offered finer resolution, the simplified SL-SG-LU index effectively captured broad vulnerability trends and is suitable for data-limited regions. This work provides a transferable framework for identifying Cl⁻ risk areas and supports long-term monitoring and management strategies in cold climate watersheds. Full article

This paper presents a numerical analysis of cold-formed thin-walled columns reinforced with sectional transverse stiffeners (STSs) based on the recent part of EC3 concerning the finite element analysis. Columns that are 1 m tall with various arrangements of STSs were modeled in the AxisVM environment. Numerical design calculations were completed using an analysis requiring a subsequent design check. This included a geometrically nonlinear analysis considering imperfections (GNIA) along with linear analysis (LBA) to assess the columns’ susceptibility to second-order effects. Reinforcing columns with STSs did not show a significant effect on the local buckling behavior of the elements. However, the results indicated that increasing the number of STSs positively influenced the columns’ resistance. This modification reduced the magnitudes of distortional, global flexural, and torsional buckling. Additionally, adding more than three STSs increased the critical loads related to distortional, flexural, and torsional buckling by 58–90%, 52–119%, and 19–154%, respectively. For the GNIA, two combinations of imperfections were analyzed: global flexural imperfection paired with either local or distortional imperfection. LBA was used to apply the imperfect geometry of the columns with the appropriate magnitudes of imperfections. The results between LBA and GNIA for the single-branched columns varied by 8–24%, while for the double-branched columns, the differences were less than 3%. Full article

Veterinary vaccines are essential tools for controlling infectious and zoonotic diseases, safeguarding animal welfare, and ensuring global food security. However, conventional vaccines are hindered by cold-chain dependence, thermal instability, and logistical challenges, particularly in low- and middle-income countries (LMICs). This review explores next-generation veterinary vaccines, emphasizing innovations in thermostability and delivery platforms to overcome these barriers. Recent advances in vaccine drying technologies, such as lyophilization and spray drying, have improved antigen stability and storage resilience, facilitating effective immunization in remote settings. Additionally, novel delivery systems, including nanoparticle-based formulations, microneedles, and mucosal routes (intranasal, aerosol, and oral), enhance vaccine efficacy, targeting immune responses at mucosal surfaces while minimizing invasiveness and cost. These approaches reduce reliance on cold-chain logistics, improve vaccine uptake, and enable large-scale deployment in field conditions. The integration of thermostable formulations with innovative delivery technologies offers scalable solutions to immunize livestock and aquatic species against major pathogens. Moreover, these strategies contribute significantly to One Health objectives by mitigating zoonotic spillovers, reducing antibiotic reliance, and supporting sustainable development through improved animal productivity. The emerging role of artificial intelligence (AI) in vaccine design—facilitating epitope prediction, formulation optimization, and rapid diagnostics—further accelerates vaccine innovation, particularly in resource-constrained environments. Collectively, the convergence of thermostability, advanced delivery systems, and AI-driven tools represents a transformative shift in veterinary vaccinology, with profound implications for public health, food systems, and global pandemic preparedness. Full article

Atmospheric aerosols are recognized as a major air pollutant with significant impacts on human health, air quality, and climate. Yet, the chemical composition and seasonal variability of aerosols remain underexplored in several Western Mediterranean regions. This study presents a year-long investigation of PM_2.5 and PM₁₀ in Tetouan, Northern Morocco, where both local emissions and regional transport influence air quality. PM_2.5 and PM₁₀ samples were collected and analysed for total mass and comprehensive chemical characterization, including organic carbon (OC), elemental carbon (EC), water-soluble ions (WSIs), and sugar tracers (levoglucosan, arabitol, and glucose). Concentration-weighted trajectory (CWT) modelling and air mass back-trajectory analyses were used to assess potential source regions and transport pathways. PM_2.5 concentrations ranged from 4.2 to 41.8 µg m⁻³ (annual mean: 18.0 ± 6.4 µg m⁻³), while PM₁₀ ranged from 11.9 to 66.3 µg m⁻³ (annual mean: 30.8 ± 9.7 µg m⁻³), with peaks in winter and minima in spring. The PM_2.5-to-PM₁₀ ratio averaged 0.59, indicating a substantial accumulation of particle mass within the fine fraction, especially during the cold season. Carbonaceous aerosols dominated the fine fraction, with total carbonaceous aerosol (TCA) contributing ~52% to PM_2.5 and ~34% to PM₁₀. Secondary organic carbon (SOC) accounted for up to 90% of OC in PM_2.5, reaching 7.3 ± 3.4 µg m⁻³ in winter. WSIs comprised ~39% of PM_2.5 mass, with sulfate, nitrate, and ammonium as major components, peaking in summer. Sugar tracers exhibited coarse-mode dominance, reflecting biomass burning and biogenic activity. Concentration-weighted trajectory and back-trajectory analyses identified the Mediterranean Basin and Iberian Peninsula as dominant source regions, in addition to local urban emissions. Overall, this study attempts to fill a critical knowledge gap in Southwestern Mediterranean aerosol research by providing a comprehensive characterization of PM_2.5 and PM₁₀ chemical composition and their seasonal dynamics in Tetouan. It further offers new insights into how a combination of local emissions and regional transport shapes the aerosol composition in this North African urban environment. Full article