Search Results (985)

Background/Objectives: Alcohol-associated hepatitis (AH) is an acute inflammatory condition of alcohol-associated liver disease (ALD) with rapid progression and high mortality. The Age-Bilirubin-INR-Creatinine (ABIC) score is a static algorithm that predicts survivability in AH. The roles of alcohol drinking patterns and nutritional status in AH progression and risk of death are understudied. This study evaluates the impact of alcohol drinking patterns and nutrition on AH progression and mortality. Methods: Sixty-one adult patients diagnosed with AH were stratified by the Model for End-Stage Liver Disease (MELD) as non-severe (MELD < 20, n = 26, Gr.1) and severe (MELD ≥ 20, n = 35, Gr.2). Each group was further subdivided by ABIC: low- (<6.71), intermediate- (6.71–9), and high- (>9) risk categories. We assessed different demographics: nutrition using the Controlling Nutritional Status (CONUT) score; lifetime drinking history (LTDH); recent alcohol use (AUDIT); laboratory measures (complete metabolic panel, complete blood count, and coagulation), and clinical measures (Maddrey DF, Child–Turcotte–Pugh, and Lille). Results: All patients showed a significant and positive correlation between ABIC and LTDH (r = 0.538, p = 0.004), particularly in Gr.2 (r = 0.554, p = 0.011). The low-risk Gr.2 exhibited the highest AST:ALTs. AST:ALTs were significantly associated with LTDH, AUDIT, and CONUT (R² = 0.539, p = 0.031). In all AH patients with intermediate mortality risk, AST:ALTs were strongly linked to CONUT and LTDH (R² = 0.657, p = 0.017). Conclusions: Severe AH demonstrates rapid liver injury progression even when the mortality risk is low. Chronic and recent heavy alcohol consumption and poor nutrition adversely impact AH severity and mortality risk. Alcohol intake and nutritional assessments in routine clinicals could identify high-risk patients, thereby improving treatment and a favorable prognosis. Full article

The aim of this study was to analyse the relationship between sustainability and customer lifetime value (CLV) through the mediation–moderation effect of search engine optimization (SEO) metrics of websites. We obtained a data sample of 296 European sustainable firms from both industrial and technological industries. Based on the theory of source credibility, the firm’s official website, where SEO techniques are applied, is more credible regarding its sustainability activities than other sources such as social media, paid advertising, etc. As a result, we show that sustainability is a precursor of financial performance over time in sustainable firms, represented by CLV. Furthermore, we found that the value of the moderating variable, website traffic, alters the indirect effects produced by the mediating variable called website relevance (domain authority), thereby demonstrating a moderated mediation effect. The contribution of this research to the body of literature is twofold. First, it deepens the understanding of how sustainability predicts marketing outcomes based on both digital and customer metrics over time. Second, we rely on recent literature on prediction-oriented modelling (PLS-SEM) to support that it is not suitable for estimation by reflective measurement models due to the woozle effect. Full article

Objective: We aimed to investigate the relationship between camouflaging and lifetime depression among autistic people, along with the role of sex in this relationship. Methods: Sixty-five autistic subjects with no intellectual or language disability (34 females, 31 males), presenting to an outpatient service for the treatment of concurrent mental disorders, were administered module A of the Structured Clinical Interview for DSM-5 Disorders, the Autism Spectrum Quotient (AQ), and the Camouflaging Autistic Traits Questionnaire (CAT-Q). Results: No differences were found in CAT-Q total or domain scores across sexes. Subjects with lifetime depression reported significantly higher scores than those without for all CAT-Q scores, with depressed women often reporting the highest scores among the groups. The difference between depressed and non-depressed women was significant for all but the CAT-Q assimilation score. The CAT-Q total score significantly predicted lifetime depression (B = 0.053, p = 0.003) when controlling for age, sex, and the AQ total score. Conclusions: Our study expands the extant knowledge about the role of camouflaging in the mental wellbeing of autistic people by showing a correlation between camouflaging and depressive disorders throughout the lifetime among both males and females. Full article

In modern shock absorber development, the fatigue durability of shim-based clamped valve systems remains a critical factor influencing both performance and operational safety. In this study, the authors extend their previous research achievements by developing a fatigue life prediction methodology that integrates an established finite element framework with a strength-based fatigue model incorporating experimentally derived and validated Wöhler characteristics of the metal alloy used in the valve shims. The focus of this work is the validation of the proposed methodology for hydraulic shock absorbers equipped with shim stack valve systems, supporting the virtual pre-selection of valve configurations during the OEM design process. This approach enables substantial reductions in experimental testing and facilitates cost-effective development under realistic operating conditions. To address random-amplitude loading scenarios, the rainflow-counting algorithm was employed to convert complex load histories into equivalent constant-amplitude cycles, thereby accurately capturing material memory effects associated with stress–strain hysteresis. Experimental validation was conducted using a high-performance servo-hydraulic load frame tester. The validated model demonstrated a prediction uncertainty of 46% for random-amplitude lifetime estimation. Full article

Background: BAP1 mutation carriers are predisposed to the development of mesothelioma. In mice, there is limited data and controversy about whether germline Bap1 heterozygous mutations alone cause mesothelioma. However, a marked increase in mesothelioma incidence is observed in Bap1-mutant mice upon even minimal asbestos exposures. Methods: To address this issue, we investigated spontaneous mesothelioma development over the lifetime of a large cohort of Bap1-mutant and wild-type (WT) mice across several genetic backgrounds. To determine if the incidence of mesotheliomas in Bap1-mutant mice is significantly increased compared to WT mice, we performed statistical analyses using frequentist and Bayesian frameworks. In the Bayesian framework, to model the probability of disease occurrence, a non-informative prior was used for Bap1-mutant mice, whereas an informative prior for the WT group was derived from historical data spanning the animals’ lifetimes. Multiple strategies were employed to incorporate historical data and infer the informative prior, including a meta-analysis, assuming a consistent probability of mesothelioma across historical datasets, and applying Bayesian meta-analytic predictive priors derived from historical data. Posterior distribution was used, and a comparison was made using odds ratio, risk difference, and risk ratio. Results: Spontaneous mesotheliomas were detected in 2/329 Bap1-mutant and 0/227 WT mice from various genetic backgrounds. Using four statistical approaches, the results did not detect a significant difference in the probabilities of mesothelioma occurrence between Bap1-mutant and WT mice.  Conclusions: Based on these analyses, we cannot conclude that germline Bap1-mutant mice have a significantly increased risk of mesothelioma in the absence of asbestos exposure. Full article

Electronic devices (EDs) exhibit complex failure patterns throughout their lifetime, with failure modes (FaM) can be monotonic, non-monotonic, or a combination of both. This complexity is increased by using advanced semiconductors and flexible electronics, which introduce variability in degradation mechanisms. Although multiple reliability models exist, many lack flexibility or practical applicability in this context. This work proposes a novel competing risk (CR) model that combines the Fréchet and Chen distributions, called Fréchet-Chen Competitive Risk (FCCR). This model allows for modeling the minimum time to failure between two relevant FaMs. Its key mathematical properties and applicability to real-life scenarios are analyzed. Parameter estimation is performed using maximum likelihood (MLE) and Bayesian inference (BEM) using Hamiltonian Monte Carlo (HMC), which provides a robust basis for analysis. Two case studies with real-life ED data validate the model, demonstrating its superior fit and predictive capability compared to classical models. Furthermore, the effect of FCCR parameters on system behavior is explored, highlighting its usefulness in accurately modeling complex failure patterns in EDs. Full article

To address the issue of key component degradation in hybrid electric commercial vehicles under complex driving cycles negatively impacting system economy and durability, this paper proposes a model predictive control (MPC)-based energy management co-optimization strategy. Firstly, dynamic degradation models for the key components are established, enabling high-fidelity characterization of component health status. Secondly, a system-level model incorporating vehicle dynamics, power battery, and electric drive motor is developed, with the degradation feedback mechanism deeply integrated. Building on this foundation, an MPC-based energy management strategy for multi-objective optimization is designed. Its core functionality lies in the cooperative allocation of power sources within a rolling horizon framework: by integrating component degradation status as critical feedback into the control loop, the strategy proactively coordinates the optimization objectives between operational economy (minimization of equivalent energy consumption) and key component durability (degradation mitigation). Simulation results demonstrate that, compared to traditional energy management strategies, the proposed strategy significantly enhances system performance while ensuring vehicle drivability: equivalent energy efficiency improves by approximately 3.5%, component degradation is reduced by up to 87%, and superior state of charge (SOC) regulation capability for the battery is achieved. This strategy provides an effective control method for achieving intelligent, long-life, and high-efficiency operation of hybrid electric commercial vehicles. Full article

Although vacuum insulated panels (VIPs) are known for their exceptional thermal insulation capabilities, their service life is limited due to an increase in internal gas pressure and material aging. In this study, an innovative monitoring system incorporating embedded sensors was developed to estimate the lifespan of VIPs in real time. A test panel was specifically selected to degrade its thermal conductivity over a shortened timeframe to facilitate validation and optimize the experimental duration. Hourly pressure and temperature data collected from the sensors embedded within the panel were analyzed using established pressure–thermal conductivity (λ) relationships from the literature. Based on the time-dependent λ values, a machine learning model employing a random forest regressor was trained to predict the panel’s lifetime. The model demonstrated high accuracy with R² = 0.9999 and RMSE = 0.0017 mW/mK. During the test period, the panel maintained acceptable performance, and the model projected that the critical thermal conductivity threshold of 8.0 mW/mK would be reached at day 66.9. This approach enables continuous, in situ field monitoring of VIP service life without the need for laboratory infrastructure and offers a scalable and practical solution for assessing long-term energy efficiency. Full article

The direct relationship between aerosols and clouds strongly influences the effects of clouds on the global climate. Aerosol particles act as cloud condensation nuclei (CCN) and ice nuclei (IN), affecting cloud formation, microphysics, and precipitation, as well as increasing the reflection of solar radiation at the cloud tops. Processes such as gas-to-particle conversion and new particle formation (NPF) control aerosol properties that, together with meteorological conditions, regulate cloud droplet nucleation through Köhler theory and related effects. The indirect aerosol effects described by Twomey and Albrecht demonstrate how changes in aerosols impact droplet number, cloud lifetime, and precipitation efficiency. Cloud microphysical processes, including droplet growth, collision-coalescence, and solid-phase mechanisms such as riming, vapor diffusion, and aggregation, shape precipitation development in warm, cold, and mixed-phase clouds. Ice nucleation remains a significant uncertainty due to the diversity of aerosol types and nucleation modes. This work synthesizes these physical interactions to better understand how the chemical and physical properties of aerosols influence cloud and precipitation processes, supporting improvements in weather and climate prediction models despite numerical challenges arising from the complexity of aerosol–cloud interactions. Full article

LGBTQ+ individuals face substance use disparities linked to minority stress. While community belongingness may buffer stress, its role is complex. This study examined divergent associations between belongingness within the LGBTQ+ community and lifetime illicit drug use versus past-year alcohol frequency among LGBTQ+ adults in Kentucky (n = 2953), a region with notably high rates of substance use. Methods: Cross-sectional online survey data were analyzed. We measured LGBTQ+ belongingness, lifetime use of cocaine/crack/heroin/methamphetamine, and past-year alcohol frequency. Logistic and linear regressions controlled for age, education, gender identity, and income. Results: Greater belongingness predicted significantly higher odds of lifetime illicit drug use (OR = 1.24) but lower past-year alcohol consumption frequency (B = −0.094). Transgender and gender expansive identity predicted significantly higher illicit drug use odds and higher alcohol frequency. Conclusions: In this Kentucky sample, LGBTQ+ belongingness showed divergent substance use associations: it was protective against frequent alcohol use but, unexpectedly, was associated with higher odds of lifetime illicit drug use. Findings highlight belongingness’s complex, context-dependent nature and the need for nuanced research and interventions considering substance type and specific vulnerabilities, particularly for TGE individuals. Full article

Electromigration (EM) is a critical reliability concern in electronic solder joints due to increasing current densities in modern electronic packaging. EM-induced failures often manifest as void formation and microstructural degradation, particularly at the cathode interface. To address this issue, composite solder joints with elemental additions have been explored to enhance performance under high current stress. This study investigates the effect of Zn addition on the electromigration behavior and mechanical performance of eutectic Sn-Bi solder joints on copper (Cu) and nickel-coated copper (Ni/Cu) substrates. The solder alloys 58Sn-42Bi and Zn-modified Sn-Bi were prepared and reflowed onto the substrates. Electromigration testing was performed under a constant current of 1000 mA at room temperature, with applied voltages of 5 V, 12 V, and 24 V over a 10-day period per sample. Shear tests were conducted at a crosshead speed of 0.1 mm/min to evaluate joint strength. The results revealed that Zn addition influenced the distribution of Bi within the solder matrix, reducing Bi depletion at the cathode and mitigating accumulation at the anode, suggesting improved EM resistance. Zn-containing solder joints also demonstrated enhanced shear strength compared to unmodified Sn-Bi joints. These findings highlight the potential of Zn as a beneficial alloying element for improving the reliability of lead-free solder joints and form a foundation for future studies incorporating phase analysis and predictive EM lifetime modelling. Full article

Against the backdrop of an urgent energy crisis, solar energy has attracted sufficient attention as one of the most inexhaustible and friendly types of environmental energy. Faced with long service and harsh environment, the poor performance ratios of photovoltaic arrays and safety hazards are frequently boosted worldwide. In particular, the hot spot effect plays a vital role in weakening the power generation performance and reduces the lifetime of photovoltaic (PV) modules. Here, our research reports a spatial–temporal hot spot management system integrated with fiber Bragg grating (FBG) temperature sensor arrays and cooling hydrogels. Through finite element simulations and indoor experiments in laboratory conditions, a superior cooling effect of hydrogels and photoelectric conversion efficiency improvement have been demonstrated. On this basis, field tests were carried out in which the FBG arrays detected the surface temperature of the PV module first, and then a classifier based on an optimized artificial neural network (ANN) recognized hot spots with an accuracy of 99.1%. The implementation of cooling hydrogels as a feedback mechanism achieved a 7.7 °C reduction in temperature, resulting in a 5.6% enhancement in power generation efficiency. The proposed strategy offers valuable insights for conducting predictive maintenance of PV power plants in the case of hot spots. Full article

This paper presents a new methodical procedure to monitor in real time the junction temperature of SiC Power MOSFET modules of parallel-connected chips utilized in machine drive systems to develop their reliability modelling and predict their lifetime. The paper implements the on-line measurements of temperature-sensitive electrical parameters (TSEP) approach, particularly the quasi-threshold voltage and the on-state drain to source voltage, to estimate the junction temperature in real time. The proposed procedure firstly applied computational fluid dynamics analysis on the module under study to determine the chip which undergoes the maximum junction temperature during typical operation of the module. Then, a calibration phase, using double-pulse tests on the selected chip, is used to generate look-up tables to relate the TSEPs under study to the junction temperature. Next, the real-time estimation of junction temperature was accomplished during the on-line operation of the three-phase inverter, taking into account the induced distortion/noises due to operation of the parallel-connected chips in the module. After that, a comparison between the two TSEPs under study was provided to demonstrate their advantages/drawbacks. Finally, reliability modelling was developed to predict the lifetime of the studied module based on the estimated junction temperature under a predetermined mission profile. Full article

This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (R_ds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, addressing key limitations in current state-of-the-art (SOTA) methods. Traditional approaches rely on expensive data acquisition systems under controlled laboratory conditions, making them unsuitable for real-world applications due to component variability, time delay, and noise sensitivity. Furthermore, these methods lack cloud interfacing for real-time data analysis and fail to provide comprehensive reliability metrics such as Remaining Useful Life (RUL). Additionally, the proposed CM method benefits from noise mitigation during switching transitions by utilizing delay circuits to ensure stable and accurate data capture. Moreover, collected data are transmitted to the cloud for long-term health assessment and damage evaluation. In this paper, experimental validation follows a structured design involving signal acquisition, filtering, cloud transmission, and temperature and thermal degradation tracking. Experimental testing has been conducted at different temperatures and operating conditions, considering coolant temperature variations (40 °C to 80 °C), and an output power of 7 kW. Results have demonstrated a clear correlation between temperature rise and R_ds,on variations, validating the ability of the proposed method to predict device degradation. Finally, by leveraging cloud computing, this work provides a practical solution for real-world Wide Band Gap (WBG)-based PEC reliability and lifetime assessment. Full article

While IPV is often studied as a predictor of housing insecurity, few U.S. studies explore how different forms of housing instability may contribute to intimate partner violence (IPV) risk. Using a mixed-methods approach and a cross-sectional design, this study examined the association between four housing instability domains and IPV among a sample of tenants that had either experienced eviction or were at high risk for eviction. Tenants in Harris and Travis counties (Texas, USA) completed an online survey (n = 1085; March–July 2024). Housing instability was assessed across four domains: homelessness, lease violations, utility hardship, and poor housing quality. IPV was measured using the Hurt, Insult, Threaten, Scream Screener. Covariate-adjusted logistic regression models suggest indicators within the four housing instability domains were associated with IPV risk. Within the homelessness domain, experiences with lifetime homelessness (AOR = 1.92, 95%CI 1.61–2.28), in the past 12 months living in unconventional spaces (AOR = 2.10, 95%CI 1.92–2.29), and moving in with others (AOR = 1.20, 95%CI 1.06–1.36) were associated with IPV. Within the lease violations domain, missed rent payments (AOR = 1.69, 95%CI 1.68–1.71) and non-payment lease violations (AOR = 2.50, 95%CI 2.29–2.73) in the past 12 months were associated with IPV. Utility shutoffs (AOR = 1.62, 95%CI 1.37–1.91) and unsafe housing (AOR = 1.65, 95%CI 1.31–2.09) in the past 12 months were associated with IPV. Homelessness, housing-related economic hardships and substandard living conditions predict an elevated risk of IPV. Full article