Search Results (2,276)

Growing concern for environmental sustainability has resulted in the implementation of sanitization methods that respect ecological principles. This research evaluates a “green” sanitizing protocol that uses CAM (Minimum Environmental Criteria)-compliant products against a traditional protocol within two ASL Roma 1 facilities. The study performed a Life Cycle Assessment (LCA) following ISO 14040, ISO 14044, and ISO 14067 standards to measure greenhouse gases emissions. Microbiological sampling was conducted according to established protocols across three different risk zones utilizing contact plates and surface swabs. The Life Cycle Assessment showed that CO₂ emissions reduced by 49.6% to 53.3% at different sites due to reduced energy use together with concentrated detergents and improved washing cycles. Microbiological testing revealed notable decreases in contamination rates across both cleaning systems yet demonstrated the “green” system achieved superior results specifically within high-risk zones. The “green” protocol matched traditional cleaning methods hygienically but delivered significant environmental advantages which positions it as a sustainable hospital cleaning solution. Full article

In response to the instability fluctuations and erosion characteristic changes in pantograph-catenary system (PCS) arcs induced by humidity variations in an open environment, a single-variable controlled experimental approach based on multi-source data fusion is proposed. This study innovatively establishes a humidity-controlled reciprocating current-carrying arc initiation test platform, integrating digital image processing with the dynamic analysis of multi-physics sensor signals (current, voltage, temperature). The study quantitatively evaluates the arc motion characteristics and the erosion effects on the frictional contact pair under different relative humidity levels (30%, 50%, 70%, and 90%) with a DC power supply (120 V/25 A). The experimental data and analysis reveal that increasing humidity results in higher contact resistance and accumulated arc energy, with arc stability first improving and then decreasing. At low humidity, arc behavior is more intense, and the erosion rate is faster. As humidity increases, the electrode wear transitions from adhesive wear to electrochemical wear, accompanied by copper transfer. The results suggest that the arc stability is optimal at moderate humidity (50% RH), with a peak current-carrying efficiency of 66% and a minimum loss rate of 14.5%. This threshold offers a vital theoretical framework for the optimization and risk assessments of PCS design. Full article

Ice accretion on critical transportation infrastructure presents serious operational risks and economic challenges, highlighting the need for sustainable anti-icing solutions. This study develops a strong PDMS-based composite coating on aluminum by incorporating carbon nanotubes (CNTs) and carbon powder, effectively merging passive superhydrophobicity with photothermal capabilities. We systematically assess how different ratios of CNTs to carbon powder (3:1, 1:1, 1:3) influence surface morphology, wettability, anti-icing performance, mechanical durability, and corrosion resistance. The morphological analysis shows the formation of hierarchical micro/nano-structures, with the optimal 1:3 ratio (designated as P13) resulting in dense, porous agglomerates of intertwined CNTs and carbon powder. P13 demonstrates high-performing superhydrophobicity, with a contact angle of 139.7° and a sliding angle of 9.4°, alongside a significantly extended freezing delay of 180 s at −20 °C. This performance is attributed to reduced water–surface interaction and inhibited ice nucleation. Mechanical abrasion tests indicate remarkable durability, as P13 retains a contact angle of 132.5° and consistent anti-icing properties after enduring 100 abrasion cycles. Electrochemical analysis reveals exceptional corrosion resistance, particularly for P13, which achieves a notable 99.66% corrosion inhibition efficiency by creating a highly tortuous diffusion barrier that protects against corrosive agents. This multifunctional coating effectively utilizes the photothermal properties of CNTs, the affordability of carbon powder, the low surface energy of PDMS, and the thermal conductivity of aluminum, presenting a robust and high-performance solution for anti-icing applications in challenging environments. Full article

Although the ultimate drivers of bat fatalities at wind turbines are still not well understood, the foraging behavior of insectivorous bats puts them at increased risk of collision with rotating blades. Wind energy facilities are commonly located in agriculture fields where bats can exploit periodic superabundant insect emergence events in the late summer and early autumn. Thermal imaging, acoustic monitoring, and bat carcass stomach content analyses show that bats prey upon insects on and near wind turbine towers. Studies have shown a positive association between insect abundance and bat activity, including in agricultural systems. We conducted a systematic review of bat diets for four common bat species in the Midwest and northern Great Plains to synthesize existing knowledge across species, assess the extent to which these bat focal species consume crop pests, and evaluate the potential for crop pest emergence models to predict temporal and spatial patterns of bat fatalities in this region. Big brown bats and eastern red bats consumed a variety of crop pests, including some for which emergence models may be available. In contrast, there were few studies for hoary bats or silver-haired bats, and the dietary evidence available has insufficient taxonomic resolution to conclude that crop pests were consumed. To augment existing data and illuminate relationships, we recommend that genetic diet analyses for bats, specifically hoary and silver-haired, be conducted in the late summer and autumn in this region. The results of these studies may provide additional candidate insect models to evaluate for predicting bat fatalities at wind turbines and clarify if the superabundant insect emergence hypothesis warrants further investigation. Full article

The global rise in population, increased life expectancy, and heightened international mobility have escalated disease prevalence and pharmaceutical demand. This growth intensifies energy consumption and chemical waste production within the pharmaceutical industry, challenging environmental sustainability and operational efficiency. Chromatography, a vital analytical technique for ensuring product quality and regulatory compliance, can also contribute to material waste and energy inefficiencies if not properly maintained and optimized. This study applies Failure Mode and Effects Analysis (FMEA) to chromatographic equipment maintenance within Hovione’s Engineering and Maintenance Department, aiming to identify and mitigate failure risks. By integrating environmental metrics derived from Life Cycle Assessment (LCA) into the FMEA framework, a hybrid risk evaluation tool was developed that prioritizes both equipment reliability and sustainability performance. The findings demonstrate how this integrated approach reduces unplanned downtime, lowers solvent waste, and improves energy efficiency. Additionally, the study proposes a conceptual dashboard to support proactive, sustainability-driven asset management in pharmaceutical laboratories. By bridging reliability engineering and environmental sustainability, this research offers a strategic model for optimizing resource use, minimizing chemical waste, and enhancing long-term operational resilience in regulated pharmaceutical environments. Full article

This study investigates whether green assets can serve as safe havens for dirty assets in the context of carbon and energy futures markets. Using daily data from April 2021 to June 2025, the analysis focuses on four key instruments: carbon emissions futures and crude oil futures, EUA futures, and natural gas futures. The study applies two main approaches—a conditional value-at-risk (CVaR)-based relative risk ratio (RRR) analysis and dynamic conditional correlation (DCC-GARCH) modeling—to assess tail risk mitigation and time-varying correlations. The results show that while green assets do not consistently act as safe havens during extreme market downturns, they can reduce the portfolio tail risk beyond certain allocation thresholds. Natural gas futures demonstrate significant volatility but offer diversification benefits when their portfolio weight exceeds 40%. EUA futures, although highly correlated with carbon emissions futures, show limited safe haven behavior. The findings challenge the assumption that green assets inherently provide downside protection and highlight the importance of strategic allocation. This research contributes to the literature by extending safe haven theory to environmental futures and offering empirical insights into the risk dynamics between green and dirty assets. Full article

Background/Objectives: Poor nutritional status and cachexia have been well-documented as predictors of adverse outcomes in individuals with chronic heart failure (HF). However, despite obesity being a common observation in this patient population, a growing body of evidence indicates that these individuals may still suffer from nutrient deficiencies and malnutrition. This study aimed to characterize the food and nutrient intake of participants enrolled in the Pro-HEART clinical trial—a study evaluating dietary interventions in overweight and obese individuals with HF—and to compare their consumption patterns to national nutritional guidelines. Methods: A cohort of 92 overweight and obese individuals with chronic HF enrolled in the Pro-HEART trial. Baseline food consumption was assessed via a validated 3-day Food Record. The data were analyzed using descriptive statistics to evaluate adherence to recommended intake levels for energy, macronutrients (fat, carbohydrates, protein), and key micronutrients. Results: Among the 92 participants, 41% exceeded fat intake recommendations, 73% surpassed guidelines for saturated fat, and 95% consumed excessive sodium. Despite adequate caloric intake, many individuals failed to meet recommended levels for key micronutrients known to influence inflammation and metabolic regulation, including vitamin D, calcium, magnesium, and potassium. Conclusions: These findings suggest that overweight and obese individuals with HF, despite their excess body weight, exhibit dietary patterns that place them at risk of malnutrition. The results underscore the necessity of nutritional assessments and interventions in this population to address deficiencies that may contribute to the metabolic and inflammatory abnormalities associated with HF. Full article

Oil and gas pipelines represent critical infrastructure for energy transportation and are essential for ensurin g energy security. The seismic disaster risk assessment of these pipelines is of paramount importance for safeguarding energy supplies. Traditional assessment methodologies primarily focus on the structural integrity of the pipeline body, often neglecting the impact of auxiliary structures and site-specific disaster effects. This study proposes an enhanced risk assessment methodology to address these gaps. This research systematically compiles seismic damage case studies of pipelines from major seismic zones in China. By considering the interactions between auxiliary structure types, site conditions, and forms of disasters, 15 typical operating conditions are identified, and a seismic damage case database is constructed. We develop a failure probability model that integrates geotechnical parameters, structural responses, and ground motion characteristics to assess the impact of liquefaction, site amplification, fault activity, and collapse/landslide phenomena. Utilizing Particle Swarm Optimization (PSO) and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) algorithms, this model quantifies the influence weights and coefficients of these disasters on pipeline auxiliary structures, forming a vulnerability matrix centered around Peak Ground Acceleration (PGA). Additionally, a dual-vulnerability assessment framework is established, and a failure probability formula accounting for the superposition effects of multiple disasters is proposed. This study marks a significant advancement, transitioning from traditional single-pipeline evaluations to “structure-disaster-site” coupling analysis, and provides a scientific basis for pipeline seismic design, operation, and maintenance under specific environmental conditions. This work contributes to the development of quantitative and refined seismic risk assessments for oil and gas pipelines. Full article

Autonomous vehicle (AV) navigation in dynamic urban environments faces challenges such as unpredictable traffic conditions, varying road user behaviors, and complex road networks. This study proposes a novel reinforcement learning-based framework that enhances AV decision making through spatial-temporal context awareness. The framework integrates Proximal Policy Optimization (PPO) and Graph Neural Networks (GNNs) to effectively model urban features like intersections, traffic density, and pedestrian zones. A key innovation is the urban context-aware reward mechanism (UCARM), which dynamically adapts the reward structure based on traffic rules, congestion levels, and safety considerations. Additionally, the framework incorporates a Dynamic Risk Assessment Module (DRAM), which uses Bayesian inference combined with Markov Decision Processes (MDPs) to proactively evaluate collision risks and guide safer navigation. The framework’s performance was validated across three datasets—Argoverse, nuScenes, and CARLA. Results demonstrate significant improvements: An average travel time of 420 ± 20 s, a collision rate of 3.1%, and energy consumption of 11,833 ± 550 J in Argoverse; 410 ± 20 s, 2.5%, and 11,933 ± 450 J in nuScenes; and 450 ± 25 s, 3.6%, and 13,000 ± 600 J in CARLA. The proposed method achieved an average navigation success rate of 92.5%, consistently outperforming baseline models in safety, efficiency, and adaptability. These findings indicate the framework’s robustness and practical applicability for scalable AV deployment in real-world urban traffic conditions. Full article

As benthic filter feeders, bivalve mollusks serve as ideal biological indicators. Bisphenol A (BPA) and its substitutes (BPS, BPF, and BPAF) are endocrine disruptors with reproductive toxicity, targeting estrogen receptors (ERs). However, their binding sites and affinity for shellfish ERs remain unclear. This study aims to identify ER binding sites of BPA and its substitutes, compare toxicity via molecular docking, and validate results through exposure experiments. The full-length cDNA of Corbicula fluminea ER was cloned using the RACE technique for the first time, the sequence length is 2138bp. Homologous models of LBD sequences from Danio rerio, C. fluminea, Azumapecten farreri, and Ruditapes philippinarum ERs were constructed via homology modeling and screened for optimal fit. Hydrogen bonds were observed during the docking process, with interaction sites including Glu-66, Arg-177, and other amino acid residues. Exposure experiments (1, 10, and 100 μg/L) showed an enhancement in ER mRNA expression. Based on the docking energies and results of the exposure experiments, it was concluded that the toxicity of BPA and BPS is similar and greater than that of BPF and BPAF. This study provides data for a reproductive risk assessment and aquatic toxicological monitoring of bisphenols. Full article

The safe exploitation of marine natural gas hydrates, a promising cleaner energy resource, is hindered by reservoir instability during drilling. The inherent temperature–pressure sensitivity and cementation of hydrate-bearing sediments leads to severe operational risks, including borehole collapse, gas invasion, and even blowouts. This review synthesizes the complex instability mechanisms and evaluates the state of the art in inhibitive, wellbore-stabilizing drilling fluids. The analysis first deconstructs the multiphysics-coupled failure process, where drilling-induced disturbances trigger a cascade of thermodynamic decomposition, kinetic-driven gas release, and geomechanical strength degradation. Subsequently, current drilling fluid strategies are critically assessed. This includes evaluating the limitations of conventional thermodynamic inhibitors (salts, alcohols, and amines) and the advancing role of kinetic inhibitors and anti-agglomerants. Innovations in wellbore reinforcement using nanomaterials and functional polymers to counteract mechanical failure are also highlighted. Finally, a forward-looking perspective is proposed, emphasizing the need for multiscale predictive models that bridge molecular interactions with macroscopic behavior. Future research should prioritize the development of “smart”, multifunctional, and green drilling fluid materials, integrated with real-time monitoring and control systems. This integrated approach is essential for unlocking the potential of marine gas hydrates safely and efficiently. Full article

Hospital-acquired infections (HAIs) remain a major clinical and economic burden, with pathogens such as Escherichia coli contributing to high rates of morbidity and mortality. Traditional manual disinfection methods are often insufficient, particularly in high-risk hospital environments. In this study, we investigated innovative strategies to enhance surface decontamination and reduce infection risk. First, we assessed the efficacy of the SMEG BPW1260 bedpan washer-disinfector, a thermal disinfection system for human waste containers. Our results demonstrated a reduction in Clostridium difficile and Escherichia coli contamination by >99.9% (>3 log reduction), as measured by colony-forming units (CFU) before and after treatment. Molecular techniques, including spectrophotometry, cell counting, and quantitative PCR (qPCR) for DNA quantification, confirmed reduction in bacterial contamination. Specifically, Clostridium difficile showed a reduction of approximately 89% in both optical density (OD) and cell count (cells/mL). In the case of Escherichia coli, a reduction of around 82% in OD was observed, with an even more pronounced decrease in cell count, reaching approximately 99.3%. For both bacteria, DNA quantification by qPCR was below detectable limits. Furthermore, we optimized the energy efficiency of the disinfection cycle, achieving a 45% reduction in power consumption compared to standard protocols without compromising antimicrobial efficacy. Secondly, we developed a sustainable cleaning solution based on methyl ester sulfonate surfactants derived from waste cooking oil. The detergent’s antibacterial activity was tested on contaminated surfaces and further enhanced through the incorporation of nanoassemblies composed of silver, electrostatically bound either to biomimetic magnetic nanoparticles or to conventional magnetic nanoparticles. Washing with the detergent alone effectively eliminated detectable contamination, while the addition of nanoparticles inhibited bacterial regrowth. Antimicrobial testing against E. coli revealed that the nanoparticle-enriched formulations reduced the average MIC values by approximately 50%, with MIC₅₀ values around 0.03–0.06 mg/mL and MIC₉₀ values between 0.06 and 0.12 mg/mL, indicating improved inhibitory efficacy. Finally, recognizing the infection risks associated with intra-hospital transport, we tested the SAFE-HUG Wheelchair Cover, a disposable non-woven barrier designed to reduce patient exposure to contaminated wheelchair surfaces. Use of the cover resulted in a 3.3 log reduction in surface contamination, based on viable cell counts. Optical density and bacterial DNA were undetectable in all covered samples at both 1 and 24 h, confirming the strong barrier effect. Together, these approaches—thermal no-touch disinfection, eco-friendly detergent boosted with nanoparticles, and protective transport barriers—respond to the urgent need for effective, sustainable infection control methods in healthcare settings. Our findings demonstrate the potential of these systems to counteract microbial contamination while minimizing environmental impact, offering promising solutions for the future of infection prevention in healthcare settings. Full article

Per- and polyfluoroalkyl substances (PFASs) are widespread in the environment, bioaccumulate in humans, and lead to disease and organ injury, such as liver steatosis. However, we lack a clear understanding of how these chemicals cause organ-level toxicity. Here, we aimed to analyze PFAS-induced metabolic perturbations in male and female rat livers by combining a genome-scale metabolic model (GEM) and toxicogenomics. The combined approach overcomes the limitations of the individual methods by taking into account the interaction between multiple genes for metabolic reactions and using gene expression to constrain the predicted mechanistic possibilities. We obtained transcriptomic data from an acute exposure study, where male and female rats received a daily PFAS dose for five consecutive days, followed by liver transcriptome measurement. We integrated the transcriptome expression data with a rat GEM to computationally predict the metabolic activity in each rat’s liver, compare it between the control and PFAS-exposed rats, and predict the benchmark dose (BMD) at which each chemical induced metabolic changes. Overall, our results suggest that PFAS-induced metabolic changes occurred primarily within the lipid and amino acid pathways and were similar between the sexes but varied in the extent of change per dose based on sex and PFAS type. Specifically, we identified that PFASs affect fatty acid-related pathways (biosynthesis, oxidation, and sphingolipid metabolism), energy metabolism, protein metabolism, and inflammatory and inositol metabolite pools, which have been associated with fatty liver and/or insulin resistance. Based on these results, we hypothesize that PFAS exposure induces changes in liver metabolism and makes the organ sensitive to metabolic diseases in both sexes. Furthermore, we conclude that male rats are more sensitive to PFAS-induced metabolic aberrations in the liver than female rats. This combined approach using GEM-based predictions and BMD analysis can help develop mechanistic hypotheses regarding how toxicant exposure leads to metabolic disruptions and how these effects may differ between the sexes, thereby assisting in the metabolic risk assessment of toxicants. Full article

Exercise-induced muscle damage (EIMD) is the most common health risk in physical exercise. However, instant and non-invasive methods for EIMD prediction have not been reported. Urine is a promising tool for EIMD prediction. However, urinary metabolite variations after EIMD occurrence have not been revealed, and potential biomarkers have not been identified. In this study, eighteen young students without regular exercise habits were recruited to perform high-intensity rowing exercise. EIMD occurrence was determined using blood biochemical analyses and pain assessment. The changes in urinary metabolites were revealed by quasi-targeted metabolomics. Results demonstrated that high-intensity rowing exercise induced EIMD and obviously changed urinary metabolites, including 23 upregulated metabolites and 26 downregulated metabolites. These differential metabolites were related to energy metabolism, exercise performance, and antioxidant metabolism. Among these metabolites, potential urinary biomarkers were identified with high sensitivity and specificity. Full article

This study analyzes the dynamics of temperature and moisture in a cylindrical silo with a conical roof and floor used for storing corn in the Bajío region of Mexico, considering conditions both with and without aeration. The model incorporates external temperature fluctuations, solar radiation, grain moisture equilibrium with air humidity through the sorption isotherm (water activity), and grain respiration to simulate real storage conditions. The model is based on continuity, momentum, energy, and moisture conservation equations in porous media. This model was solved using the finite element method (FEM) to evaluate temperature and interstitial humidity variations during January and May, representing cold and warm environmental conditions, respectively. The simulations show that, without aeration, grain temperature progressively accumulates in the center and bottom region of the silo, reaching critical values for safe storage. In January, the low ambient temperature favors the natural dissipation of heat. In contrast, in May, the combination of high ambient temperatures and solar radiation intensifies thermal accumulation, increasing the risk of grain deterioration. However, implementing aeration periods allowed for a reduction in the silo’s internal temperature, achieving more homogeneous cooling and reducing the threats of mold and insect proliferation. For January, an airflow rate of 0.15 m³/(min·ton) was optimal for maintaining the temperature within the safe storage range (≤17 °C). In contrast, in May, neither this airflow rate nor the accumulation of 120 h of aeration was sufficient to achieve optimal storage temperatures. This indicates that, under warm conditions, the aeration strategy needs to be reconsidered, assessing whether a higher airflow rate, longer periods, or a combination of both could improve heat dissipation. The results also show that interstitial relative humidity remains stable with nocturnal aeration, minimizing moisture absorption in January and preventing excessive drying in May. However, it was identified that aeration period management must be adaptive, taking environmental conditions into account to avoid issues such as re-wetting or excessive grain drying. Full article