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Identifying daily-living features related to loneliness: A causal machine learning approach
Background Loneliness is a distressing feeling that influences well-being. Immigrants’ experience of acculturation to a new dominant culture places them at risk for maladaptive behaviors and daily rhythms leading to loneliness. Identifying daily-living features that causally influence loneliness is essential for developing effective preventive mental health screening. Objective To identify the important daily living-features related to loneliness for the development of robust screening solutions using causal machine learning for health providers working with first-generation immigrants. Methods We monitored 39 immigrants in Finland for 28 days using mobile devices and wearables under free-living conditions. Data included ecological momentary assessments of loneliness, social interactions, physical activity, sleep, and cardiac features. We estimated the average treatment effect (ATE) of each daily-living feature (treatment variable) on loneliness scores (outcome) and validated the robustness of causal estimates using three refutation techniques. Results Our results reveal the ATE of various daily-living features on loneliness. Features such as longer outgoing call durations (ATE = 0.197, p < 0.001), higher LF/HF ratio (ATE = 0.129, p < 0.0001), higher respiratory rate (ATE = 0.144, p < 0.001), and increased inactivity (ATE = 0.130, p < 0.001) causally increased loneliness. Conversely, certain features exhibit negative ATEs, such as higher activity calories (ATE = −0.174, p < 0.001), sleep RMSSD (ATE = −0.128, p < 0.001), longer home duration (ATE = −0.107, p < 0.001), and more sleep time (ATE = −0.103, p < 0.001) mitigated loneliness. Conclusions Daily-living features, including social interactions, activity, sleep, and cardiac features, causally influence loneliness. Our findings provide a basis for loneliness screening targeting immigrant populations. Future work should refine the measurement and incorporate contextual information to establish more reliable causal links in real life.
Phase-Rearrangement-Induced Atomic Replacement toward Customizing Noble-Metal Intermetallics
Digital governance, anti-corruption and political stability: An empirical study using cross-national panel data
Digital governance has emerged as a critical domain for national development and international cooperation. This study investigates the impact of digital governance on political stability through both theoretical and empirical analyses. First, we establish a theoretical framework to examine the effects of digital governance on political stability and the role that anti-corruption plays in it. Using panel data from 112 countries during 2014–2023, we then examined the quantitative relationship between digital governance and political stability. The results show that digital governance significantly enhances political stability, mediated by anti-corruption efforts. Additionally, the impact of digital governance exhibits heterogeneity across different levels of economic development. Based on these insights, we provide policy recommendations and future research directions to leverage digital governance for enhancing political stability.
Electrocatalytic Proton Borrowing N-Alkylation of Pure Alcohols and Amines
Concentration-dependent effects of fermented spent coffee grounds and contrasting effects of earthworms on growth and phytochemicals in medicinal plant Glechoma longituba
Fermented spent coffee grounds (FSCG) serve as a valuable soil amendment to improve soil structure and fertility, while earthworms play a well-established role in enhancing soil processes and plant growth. However, their combined effects on bioactive compound accumulation in medicinal plants remain unclear. This study investigated the individual and interactive effects of FSCG (0%, 10%, and 20%, v/v) and earthworms (with and without Pheretima guillelmi ) on the growth and phytochemical content of Glechoma longituba , a common medicinal herb, under greenhouse conditions. Results showed that 10% FSCG generally promoted plant growth, whereas 20% FSCG generally enhanced the accumulation of total flavonoids, chlorogenic acid, and soluble protein. Earthworms enhanced aboveground biomass and node number but significantly reduced chlorogenic acid content. These findings highlight the potential of FSCG as a sustainable soil amendment in medicinal plant cultivation and underscore the need to consider earthworm activity when optimizing both plant biomass and phytochemical quality.
Flexible Aliphatic Carboxylates for Colossal Thermal Expansion Engineering: From Local and Extended Structure Analysis to Thermomechanical Devices
Biological age threshold is associated with symptomatic knee osteoarthritis risk in chinese adults: Insights from machine learning analysis of a national cohort
Background Symptomatic knee osteoarthritis (KOA) imposes a substantial global health and economic burden. Although chronological age (CA) is a key risk factor, it poorly reflects interindividual aging heterogeneity. Biological age (BA), which is quantified using blood biomarkers that reflect systemic physiological integrity, is a superior measure of functional decline and molecular aging. Mechanistically, BA may be linked to KOA pathogenesis via cellular senescence and senescence-associated secretory phenotype (SASP). Objective This study aimed to explore the association between BA and symptomatic KOA in a nationally representative Chinese cohort and to evaluate BA’s utility of BA in enhancing KOA risk assessment. Methods We conducted a cross-sectional analysis using the 2011/2015 China Health and Retirement Longitudinal Study (CHARLS) data of 1,000 participants (≥45 years old) with complete BA and symptomatic KOA data (defined as self-reported physician-diagnosed osteoarthritis with concurrent knee pain). BA was calculated using the Klemera-Doubal method (KDM) and eight serum biomarkers. Associations were assessed using multivariable-adjusted logistic regression, restricted cubic splines (RCS), and subgroup analyses. Six machine learning models (including XGBoost and LightGBM) were used to distinguish cases of symptomatic KOA, with SHAP interpreting the optimal model. Results Participants with symptomatic KOA had a significantly higher mean BA than those without (59.97 vs. 58.76 years, p < 0.001). After multivariable adjustment, each 1-year BA increase was associated with 1.23% higher symptomatic KOA odds ( OR =1.0123, 95% CI :1.0049–1.0197, p = 0.0010). Compared with the lowest BA quartile (Q1), the highest quartiles (Q3 and Q4) showed a significantly elevated symptomatic KOA risk (Q3: OR =1.4655, 95% CI :1.1989–1.7940, p = 0.0002; Q4: OR =1.4519, 95% CI :1.1755–1.7956, p = 0.0001). RCS analysis revealed a non-linear relationship, with symptomatic KOA risk accelerating beyond approximately 66.7 years ( p for non-linearity = 0.013). Subgroup analyses demonstrated consistent results. The XGBoost model demonstrated the highest discriminative performance (AUROC = 0.9078), with SHAP identifying BA as the most influential feature. Conclusion BA is strongly and non-linearly associated with symptomatic KOA risk in Chinese adults, accelerating beyond a critical threshold. BA assessment may enhance KOA risk stratification and could inform future interventional studies. However, the cross-sectional design of this study precludes causal inferences. Longitudinal studies are required to establish temporal relationships and explore potential causal associations.
Pressure-Induced Unexpected Stabilization of the High-Spin State of Iron(II) in a Metal–Organic Framework
Retraction: miR-150-5p inhibits hepatoma cell migration and invasion by targeting MMP14
Fast Oxide Ion Conduction in Ba <sub>3</sub> MoNbO <sub>8.5</sub> Enhanced by Acceptor Substitution and Dehydration
Fabrication of p-type ZnO thin films with high mobility using reactive gases N2 and Ar by RF sputtering
Co-doping with AlN via RF sputtering is necessary since it is still very difficult to create high conductivity p-type zinc oxide (ZnO) thin films. At room temperature, RF sputtering was used with Ar (20%) and N2 (80%) at a range of target powers (150, 175, 200, 225, and 250 W). All of the produced films displayed the ZnO (002) peak of the wurzite structure. Using the PL approach, the recombination of free excitons was detected. The ZnO:AlN and ZnO:N Raman peaks were observed at 578.58 cm -1 and 276 cm -1 , respectively.With hole concentrations of 3.06 × 10 +16 cm -3 and 1.83 × 10 +18 cm -3 , respectively, and corresponding mobilities of 117 cm 2 V -1 s -1 and 19.1 cm 2 V -1 s -1 , the AZO23 and AZO25 samples demonstrated p-type conductivity behavior. The N-Al-N complex, which forms as a shallow acceptor when Zn +2 ions are substituted by Al +3 ions, is the cause of the p-type behavior of the ZnO sample (AZO23).However, the production of (N) O acceptors due to the substitution of the bigger N -3 ions (radius of 0.146 nm) for the O -2 ions (radius of 0.140 nm), may be the cause of the p-type behavior of AZO25 sample. AZO23 sample has a greater mobility (117 cm 2 V -1 s -1 ) which can be explained by the higher mean free path/crystallite size (̖Ɩ/D) ratio.
Lignin-Directed Construction of Vertical Ru/RuO <sub>2</sub> Electron–Bridge Interfaces for Low-Input Self-Powered Hydrazine-Water Splitting
The prevalence, spatial distribution and geographic weighted regression of open defecation practice in sub-Saharan Africa using demographic and health survey (DHS) data
Background Open defecation is a harmful and unsafe practice that contributes to environmental pollution and disproportionately affects developing nations, particularly those in Sub-Saharan Africa. According to the World Health Organization (WHO) and the United Nations International Children’s Emergency Fund (UNICEF) Joint Monitoring Programme (JMP), Sub-Saharan Africa is home to 46% of the global population still practising open defecation. Socio-economic factors, cultural norms, and individual attitudes play crucial roles in shaping sanitation behaviours and influencing open defecation practices. Therefore, this study aims to determine the prevalence, spatial distribution, and geographic inequalities of open defecation in Sub-Saharan Africa. Methods A community-based cross-sectional survey was conducted, including 20,130 clusters and 496,957 households from 34 Sub-Saharan African countries. The Demographic and Health Survey (DHS) data were weighted, cleaned, and analyzed using Microsoft Excel, Stata version 17, ArcGIS version 10.7, and SaTScan™ version 10.1. Spatial analyses were performed using ArcGIS version 10.7 and Kulldorff’s SaTScan™ version 10.1, while Geographically Weighted Regression (GWR) analyses were conducted using ArcGIS version 10.7. Results The prevalence of open defecation among households in Sub-Saharan Africa was 23.24% (95% CI: 23.12–23.35). The practice was clustered across enumeration areas (Global Moran’s I = 0.25, Z-score = 366.12, P-value ≤ 0.001). The Getis-Ord Gi* statistic identified hotspots of open defecation primarily in East Africa, Central Africa, and West Africa. Anselin Local Moran’s I detected both high and low clusters of open defecation, while SaTScan cluster analysis identified 146 windows containing significant clusters of households practising open defecation across Sub-Saharan Africa. Geographically Weighted Regression (GWR) analysis revealed that several factors were positively associated with open defecation, including lack of educational attainment, unimproved drinking water sources, lack of basic access to water, younger household heads, and extreme poverty. Additionally, household size greater than four, the richest households and urban and rural residency were negatively associated with open defecation practices. Conclusion This study reveals a high prevalence of open defecation (23.24%) in Sub-Saharan Africa with significant geographic clustering, particularly in East, Central, and West Africa. This estimate is higher than the 18% reported by the 2021 WHO/UNICEF Joint Monitoring Programme (JMP). Novel spatial and GWR analyses uncovered associations with poverty, lack of education, water access, age of household heads, and wealth status. These findings underscore the need for geographically targeted, multi-sectoral sanitation interventions that address underlying socio-demographic disparities. Future research should explore the effectiveness of spatially tailored programs and integrate behavioral insights to accelerate progress toward Sustainable Development Goal 6.