Search Results (89)

Introduction: Sexual minority men (SMM) are at increased risk for psychosocial stressor exposure, substance use, and poor mental health relative to heterosexual men. While the burden of mental health is growing in the United States, among SMM these trends are increasing at a greater rate, driving health disparities. Methods: Framed within a minority stress framework, these analyses examine how stressors explain substance use and poorer mental health over time. Participants were asked questions on stressor exposure (stigma, discrimination, internalized homophobia, perceived stress), mental health (anxiety, depression, PTSD), and substance use (alcohol to intoxication, club drugs, poly club drugs) over 36 months among 528 SMM in NYC. Results: Perceived stress increased frequency of all substance use, whereas discrimination decreased days of club and poly club drug use. Depression severity predicted increased days of club drug and poly club drug use. PTSD severity predicted increased days of club drug and poly club drug use. Conclusion: We are able to expand on the literature with granular substance use data to highlight associations with stressors and mental health. These findings support an increased need for systematic policy solutions and public health interventions to address drivers of substance use disparities among young SMM. Full article

Macrophages are a heterogenous population of cells that adopt specific phenotypes in response to signals from their dynamic microenvironment. Apart from being key players in innate immunity and in the maintenance of tissue homeostasis, macrophages are also important drivers of low-grade inflammation, which is associated with different chronic conditions including stress and cancer. The activation of macrophages during chronic stress and cancer results in their multifaceted pathogenic roles. Macrophages residing in the tumor microenvironment are commonly known as tumor-associated macrophages and favor or inhibit tumor growth depending on the microenvironmental cues and their activation state. Activated macrophages display a continuum of properties rather than a distinct proinflammatory or anti-inflammatory dichotomy. Emerging evidence suggests that prolonged tissue residency restricts the plasticity of macrophages, while recruited monocytes are more plastic and their differentiation into tumor-associated macrophages during stress can result in a dual imprinting from both the existing stress-induced inflammation and the tumor microenvironment. In addition, the immunomodulation of the tumor microenvironment and reprogramming of tumor-associated macrophages toward the anti-tumor phenotypes have emerged as promising therapeutic approaches. In this review, we will focus on how the persistent inflammatory state underlying chronic stress affects macrophages as well as the macrophages’ contribution to various aspects of tumor growth and progression, highlighting a therapeutic potential of modulation of the macrophage-mediated immunosuppressive tumor microenvironment. Full article

This study investigates the mechanical properties of LiCoO₂ (LCO) cathode materials under varying states of charge (SOCs) using both an empirical Buckingham potential model and a machine learning-based Deep Potential (DP) model. The results reveal a substantial decrease in Young’s modulus with decreasing SOC. Analysis of stress factors identified pairwise interactions, particularly those involving Co³⁺ and Co⁴⁺, as key drivers of this mechanical evolution. The DP model demonstrated superior performance by providing consistent and reliable predictions reflected in a smooth and monotonic stiffness decrease with SOC, in contrast to the large fluctuations observed in the classical Buckingham potential results. The study further identifies the increasing dominance of Co⁴⁺ interactions at low SOCs as a contributor to localized stress concentrations, which may accelerate crack initiation and mechanical degradation. These findings underscore the DP model’s capability to capture SOC-dependent mechanical behavior accurately, establishing it as a robust tool for modeling battery materials. Moreover, the calculated SOC-dependent mechanical properties can serve as critical input for continuum-scale models, improving their predictive capability for chemo-mechanical behavior and degradation processes. This integrated multiscale modeling approach can offer valuable insights for developing strategies to enhance the durability and performance of lithium-ion battery materials. Full article

Bronchopulmonary dysplasia (BPD) remains a significant complication of premature birth and neonatal intensive care. While much is known about the drivers of lung injury, few studies have addressed the interrelationships between oxidative stress, inflammation, and downstream events, such as endoplasmic reticulum (ER) stress. In this review, we explore the concept of a “destructive cycle” in which these drivers self-amplify to push the lung into a state of maladaptive repair. Animal models, primarily the hyperoxic rat pup model, support a sequential progression from the generation of reactive oxygen species (ROS) and inflammation to endoplasmic reticulum (ER) stress and mitochondrial injury. We highlight how these intersecting pathways offer not just therapeutic targets but also opportunities for interventions that reprogram system-wide responses. Accordingly, we explore the potential of systems pharmacology therapeutics (SPTs) to address the multifactorial nature of BPD. As a prototype SPT, we describe the development of N-acetyl-L-lysyl-L-tyrosyl-L-cysteine amide (KYC), a systems chemico-pharmacology drug (SCPD), which is selectively activated in inflamed tissues and modulates key nodal targets such as high-mobility group box-1 (HMGB1) and Kelch-like ECH-associated protein-1 (Keap1). Collectively, the data suggest that future therapies may require a coordinated, network-level approach to break the destructive cycle and enable proper regeneration rather than partial repair. Full article

Under service conditions, randomly distributed cracks in the top coat (TC) layer of thermal barrier coatings (TBCs) lead to local stress concentrations, which serve as the primary drivers of crack propagation and coating delamination. This study systematically analyzes the influence of crack defects on the thermal stress distribution in TBCs, based on their microstructural characteristics, using a multi-physics-coupled finite element model. Numerical analysis of crack characteristics reveals that crack length significantly influences the stress distribution in the coatings, with the maximum tensile stress at the crack tip increasing from 104.02 to 238.51 MPa as the crack half-length extends from 400 to 1000 μm. Shorter cracks induce lower tensile stresses, thereby retarding crack propagation and delaying coating delamination. Crack depth also influences the stress distribution, with the maximum tensile stress decreasing from 205.88 to 101.65 MPa as the crack is buried deeper, from 50 to 200 μm, indicating a more stable stress state less prone to propagation in deeper cracks. For inclined cracks, increasing the inclination angle induces a shift in stress from tensile to compressive, with larger inclination angles exhibiting greater stability. Accordingly, this study proposes a laser scribing strategy to mitigate crack-tip stress concentration, which is validated through comparison with two-dimensional crack models. Laser scribing shortens crack length by interrupting crack continuity, relieves localized thermal expansion strain, effectively suppresses crack growth, and significantly enhances the crack resistance and thermal shock stability of the coating. Full article

LED lighting plays a pivotal role in the illumination landscape owing to its substantial energy efficiency, prolonged operational lifespan, environmental advantages, superior light quality, and its capacity for advanced lighting control. Flicker in led lighting systems has emerged as a substantial concern and is appropriate to its potential opposing impacts on human health and visual comfort. Hence, this paper presents a comprehensive analysis, design, and mitigation strategy for flicker in a DC-DC led driver that incorporates a valley fill circuit. The initial stage of this investigation involves an analysis of a conventional cuk converter. However, it is noted that this converter produces an inverting output and experiences high current stress on the semiconductor switch. Consequently, to address these limitations, a non-inverting cuk converter (NICC) is introduced, resulting in a positive output, reduced voltage and current ripple and increased efficiency. To surmount these challenges, the implementation of a valley fill circuit is proposed. This addition facilitates the rapid attainment of a steady state, increases efficiency, and substantially reduces the output voltage and current ripple. An in-depth analysis of the stress imposed on the switch is conducted, leading to the development of a circuit designed to extend the operational life of the LED driver. Therefore, this paper compares the topologies of three different DC-DC cuk power converters. These converters include conventional cuk, non-inverting cuk (NICC), and non-inverting cuk with valley-fill. The performance metrics are examined and compared for all three topologies. The findings of this study affirm that the proposed driver circuit is highly effective in mitigating flicker, thereby enhancing the user experience and elevating the quality of led lighting, all while maintaining energy efficiency. The MATLAB simulations of these converters are performed to validate the theoretical results. Full article

Water resources are a key constraint on sustainable development in arid regions, especially for agricultural production where water use is intensive. To assess the sustainability of agricultural water use in such environments, this study utilizes 2010–2020 agricultural data from the Turpan–Hami Basin and is among the first to integrate the water footprint (WF) theory with the DPSIR (driver–pressure–state–impact–response) model into a comprehensive framework for evaluating water resource sustainability in arid agricultural systems. The agricultural blue, green, and grey WF in the Turpan–Hami Basin were quantified for 2010–2020, followed by a sustainability assessment under the DPSIR framework using a comprehensive weighting method. The results showed a continuous increase in the WF, dominated by the blue WF (>60%), largely due to crops like cotton and grapes, intensifying regional water stress. Turpan experienced prolonged resource overload, while Hami exhibited slightly higher sustainability. DPSIR analysis revealed stronger policy responses in Turpan and significant ecological investments in Hami. Key influencing factors included the crop yield, WF modulus, per capita WF, and water quality shortage index. Overall, sustainability in the basin fluctuated between “Basically Sustainable (Level III)” and “Insufficiently Sustainable (Level IV)”, with slight improvement in 2020. The findings highlight the need for region-specific agricultural optimization, strengthened ecological governance, and improved water-saving strategies to enhance water use efficiency and sustainability in arid regions. Full article

The Southwest Region (SWR) is one of Nigeria’s six geo-political zones and comprises six distinct states. It holds considerable significance due to its unique geographical features, economic vibrancy, pastoral heritage, and fragile natural ecosystems. These ecosystems are becoming increasingly susceptible to human activities and the adverse impacts of climate change. This study analyzed the temporal and spatial variations of the Normalized Difference Vegetation Index (NDVI) in relation to key influencing factors in the SWR from 2001 to 2020. The analytical methods included Sen’s slope estimator, the Mann–Kendall trend test, and the Geographical Detector Model (GDM). The analysis revealed significant spatial variability in vegetation cover, with dense vegetation concentrated in the eastern part of the region and low vegetation coverage overall, reflected by an average NDVI value of 0.45, indicating persistent vegetation stress. Human activities, particularly land use and land cover (LULC) changes, were identified as major drivers of vegetation loss in some states such as Ekiti, Lagos, Ogun, and Ondo. Conversely, Osun and Oyo exhibited signs of vegetation recovery, suggesting the potential for restoration. The study found that topographic factors, including slope and elevation, as well as climatic variables like precipitation, influenced vegetation patterns. However, the impact of these factors was secondary to LULC dynamics. The interaction detection analysis further highlighted the cumulative effect of combined anthropogenic and environmental factors on vegetation distribution, with the interaction between LULC and topography being particularly significant. These findings provide essential insights into the biological condition of the SWR and contribute to advancing the understanding of vegetation patterns with critical implications for the sustainable management and conservation of tropical forest ecosystems. Full article

Oxidative stress serves as both a driver and result of redox metabolism across diverse physiological and pathological states, including cancer. Head and neck squamous cell carcinoma (HNSCC), the sixth most prevalent malignancy worldwide, is no exception. HNSCC is strongly linked to modifiable external risk factors such as tobacco smoking, alcohol consumption, and high-risk human papilloma (HR-HPV) infection. These risk factors are associated with elevated oxidative stress, which contributes to carcinogenesis through DNA damage, chronic inflammation, and dysregulation of cell signaling pathways. Current treatment options for HNSCC have limitations and burden of side effects. Studies have been conducted on potent dietary antioxidants for the prevention and adjunctive treatment of HNSCC. This review aims to explore the contribution of oxidative stress to carcinogenesis in general and the three major risk factors for HNSCC. We evaluate latest evidence for nine dietary antioxidants such as vitamin C, vitamin E, carotenoids, epigallocatechin-3-gallate (EGCG), and curcumin, that have shown promise in preclinical and clinical studies. We discuss how these compounds mitigate ROS, influence cancer-related signaling pathways, and modulate tumor microenvironment. Despite encouraging findings, current clinical data remain limited and inconclusive, highlighting the need for further research on possible dietary antioxidants for HNSCC. Full article

The economic assessment of CO₂ emissions from fossil fuels is gaining importance in the context of sustainable development. Climate change, driven by excessive greenhouse gas emissions, poses a significant threat to humanity, requiring an integrated approach that considers both environmental and economic factors. The European Union (EU) plays a key role in global efforts to reduce CO₂ emissions and promote sustainability. This study explores economic approaches to analyzing CO₂ emissions in Europe, focusing on trends in fossil fuel use and their economic drivers. The research highlights the connection between economic activity, energy consumption, and emissions, contributing to a better understanding of climate change mitigation strategies. The findings emphasize the strong influence of demographic factors on carbon emissions, stressing the need for targeted policies to address the environmental impact of population growth. This study presents a literature-based assessment of CO₂ emissions from fossil fuel consumption in the context of sustainable development, with a focus on Europe. Recognizing the urgent threat posed by climate change, the paper explores how economic and demographic factors influence emissions trends and energy consumption. Through the synthesis of recent research and statistical data, it examines the relationship between economic activity and CO₂ emissions across EU countries. Special attention is given to national policy frameworks, particularly Germany’s “Energiewende”, as a successful example of emission reduction through building-sector reform. The study highlights that while economic growth remains a driver of emissions, strategic investments in renewable energy, energy efficiency, and sectoral transformation can decouple growth from environmental degradation. The findings support the need for country-specific mitigation strategies, emphasizing that uniform approaches may not address the diverse challenges faced by EU member states. This work contributes to the broader understanding of climate policy design by linking empirical evidence with policy implications in the transition to a low-carbon economy. Full article

As the primary driver of energy transfer between atmospheric and oceanic systems, the air–sea momentum flux fundamentally governs coupled model dynamics through its regulation of wind stress partitioning. Given the complexity of the physical processes involved, simplified representations of these interactions are widely adopted to balance computational efficiency and physical fidelity. This systematic evaluation of five wind stress parameterizations reveals scheme-dependent variability in momentum partitioning efficiency, particularly under typhoon conditions. Our results quantify how the wind stress drag coefficient’s formulation alters atmosphere–ocean feedback, with wave-state aware schemes exhibiting superior surge prediction accuracy compared to wind-speed-dependent approaches. Specifically, a larger wind stress drag coefficient leads to increased atmospheric bottom stress and sea surface stress, resulting in weaker winds and larger sea surface currents and storm surges. These findings provide actionable guidelines into the performance and sensitivity of various air–sea coupled models and offer useful suggestions for improving operational marine forecasting systems. Full article

Flash droughts are rapidly evolving drought events, primarily affecting agriculture, with an onset ranging from 5 days to 8 weeks. Previous research has highlighted the significant impact of flash droughts on agriculture and ecosystems, posing unique challenges for drought monitoring and mitigation. Various indicators have been used to identify the regions and occurrences of flash droughts. However, studies indicate that a single unique indicator does not serve the purpose of identifying/monitoring flash droughts in the United States. This study aims to identify flash droughts using indicators, including the Evaporative Stress Index (ESI), Soil Moisture (SM), and Normalized Difference Vegetation Index (NDVI), complemented by data from the United States Drought Monitor (USDM), which is used as a reference. The research examines flash droughts across Florida, Georgia, and Louisiana from 2000 to 2023, incorporating case studies of recent events. The findings indicate that the SM indicator demonstrates the highest consistency (91%) with the USDM, followed by SESI (64%) and NDVI (52%). Seasonally, flash droughts were most frequent in Florida and Georgia during May and October, whereas Louisiana experienced the highest occurrences between June and October. These indicators effectively reflect flash drought impacts, as documented by crop progress and condition reports from the United States Department of Agriculture (USDA). Finally, to enhance understanding and management of flash droughts, the study proposes a Driver-Impact-Response (DRI) conceptual framework is proposed to connect the drivers, impacts, and responses. The DRI framework identifies the drivers initiating flash droughts, evaluates their impacts, and develops mitigation strategies. The DRI framework is specifically of support and management use for planners to summarize the information for decision-making. Full article

Reprogramming energy metabolism is pivotal to tumor development. Ketone bodies (KBs), which are generated during lipid metabolism, are fundamental bioactive molecules that can be modulated to satisfy the escalating metabolic needs of cancer cells. At present, a burgeoning body of research is concentrating on the metabolism of KBs within tumors, investigating their roles as signaling mediators, drivers of post-translational modifications, and regulators of inflammation and oxidative stress. The ketogenic diet (KD) may enhance the sensitivity of various cancers to standard therapies, such as chemotherapy and radiotherapy, by exploiting the reprogrammed metabolism of cancer cells and shifting the metabolic state from glucose reliance to KB utilization, rendering it a promising candidate for adjunct cancer therapy. Nonetheless, numerous questions remain regarding the expression of key metabolic genes across different tumors, the regulation of their activities, and the impact of individual KBs on various tumor types. Further investigation is imperative to resolve the conflicting data concerning KB synthesis and functionality within tumors. This review aims to encapsulate the intricate roles of KBs in cancer metabolism, elucidating a comprehensive grasp of their mechanisms and highlighting emerging clinical applications, thereby setting the stage for future investigations into their therapeutic potential. Full article

Green innovation provides powerful incentives to achieve sustained social progress. However, the available research examines the financial drivers of green innovation, overlooking the impact of digital government development and the institutional environment. The integration of digital government construction with the institutional environment, and the coupling of the two with green innovation, will paint a picture of the future that promotes sustainable social progress and the modernization of governance. This research utilizes data from 31 provinces in China from 2018 to 2022 to study the impact of digital government construction and the institutional environment on the provincial green innovation efficiency. An empirical analysis is conducted on the basis of analyzing the spatiotemporal evolution and pattern of digital government construction, the institutional environment and the provincial green innovation efficiency. Firstly, digital government construction emphasizes data openness and sharing, and data become a key link between those inside and outside the government. The digital platform becomes an important carrier connecting the government and multiple subjects in collaborative innovation to continuously shape a new digital governance ecology. The netting of digital ecology is conducive to the institutional environment, serving to break the path dependence and create a more open, inclusive and synergistic institutional environment. Based on this, we consider that digital government construction positively affects the institutional environment, and this is verified. Secondly, a good government–market relationship, mature market development, a large market service scale, a complete property rights system and a fair legal system brought about by the improved institutional environment provide macro-external environmental support for enhanced innovation dynamics. Based on this, it is proposed that the institutional environment positively affects the provincial green innovation efficiency. Meanwhile, building on embeddedness theory, the industrial embeddedness of the institutional environment for green innovation highlights the scattered distribution of innovation components. Geographical embeddedness stresses indigenous resource distribution grounded in space vicinity and clustering. The better the institutional environment, the greater the forces of disempowerment at the industrial tier and the easier it is for resources to flow out. This may potentially have a detrimental role in improving the local green innovation efficiency. In view of this, it is proposed that the institutional environment negatively affects the provincial green innovation efficiency, and this is verified. Thirdly, digital government construction, as an important aspect of constructing a digital governance system and implementing the strategy of a strong network state, can effectively release the multiplier effect of digital technology in ecological environment governance and green innovation, continuously enhancing the provincial green innovation efficiency. In view of this, it is proposed that digital government construction positively affects the provincial green innovation efficiency, and this is verified. When the institutional environment is used as a mediating variable, digital government construction will have a certain non-linear impact in terms of provincial green innovation efficiency improvement. Building on the evidence-based analysis results, it is found that the institutional environment plays a competitive mediating role. This study integrates digital government construction, the institutional environment and the provincial green innovation efficiency under a unified analytical structure, offering theoretical inspiration and operational directions to enhance the provincial green innovation efficiency. Full article

Driving is integral to many people’s daily existence, but aggressive driving behavior increases the risk of road traffic collisions. Young drivers are more prone to aggressive driving and danger perception impairments. A driver’s physiological state (e.g., fatigue, anger, or stress) can negatively affect their driving performance. This is especially true for young drivers who have limited driving experience. This research focuses on examining the connection between emotional arousal and aggressive driving behavior in young drivers, using predictive analysis based on electrodermal activity (EDA) data through neural networks. The study involved 20 participants aged 18 to 30, who completed 84 driving sessions. During these sessions, their EDA signals and driving behaviors, including acceleration and braking, were monitored using an Empatica E4 wristband and a telematics device. This study conducted two key analyses using neural networks. The first analysis used a comprehensive set of EDA features to predict emotional arousal, achieving an accuracy of 65%. The second analysis concentrated on predicting aggressive driving behaviors by leveraging the top 10 most significant EDA features identified from the arousal prediction model. Initially, the arousal prediction was performed using the complete set of EDA features, from which feature importance was assessed. The top 10 features with the highest importance were then selected to predict aggressive driving behaviors. Another aggressive driving behavior prediction with a refined set of difference features, representing the changes from baseline EDA values, was also utilized in this analysis to enhance the prediction of aggressive driving events. Despite moderate accuracy, these findings suggest that EDA data, particularly difference features, can be valuable in predicting emotional states and aggressive driving, with future research needed to incorporate additional physiological measures for enhanced predictive performance. Full article