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Given the basic data anomalies and significant redundancy in line loss management within distribution networks， a technique for identifying and correcting abnormal line loss data based on segmented regions is proposed. In view of the redundancy of terminal data， a Kalman filter algorithm is employed to fuse terminal redundant data. Then， by traversing the distribution transformers of various line nodes in the distribution network and using local outlier factor （LOF） algorithm， the operational data are detected. Based on the topological relationship of the distribution networks， the Girvan-Newman （GN） algorithm is used to segment the abnormal nodes. By analyzing the neighboring node measurement data and the imbalance index of the segmented regions， the boundary of the regions is dynamically adjusted until the segmented regions meet the estimated observability conditions. The final division result of segmented regions is obtained， and abnormal data are solved using the measurement model， constraint model， and estimation model within the regions. Finally， an example of the 10 kV Shixin line and Shijin line in a province in Northwest China is used to validate the proposed method. The results demonstrate that the proposed method can identify and correct abnormal line loss data within distribution networks.

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is diagnosed increasingly in children and adolescents. We aimed to investigate the prevalence and related influencing factors of NAFLD in school-aged children and adolescents in Shenyang, Liaoning Province. Furthermore, we analyzed the relationship between lifestyle and fatty liver. Methods We conducted aprospective cohort study of 1309 school-aged children and adolescents between the ages of 7 and 18 years who underwent physical examination from November to December 2019. In addition, they were collected age, gender, learning stage, height, weight, BMI, waist circumference, hip circumference, and waist-hip ratio. Finally, a portion of the population was selected to complete a questionnaire survey to explore the impact of lifestyle habits on fatty liver disease. Results NAFLD was present in 23.83% of subjects. The prevalence of children and adolescents was 22.73% and 24.43%, respectively. Fatty liver prevalence differs significantly by gender and learning stages. The highest rate of fatty liver was seen in obese children (71.68%). Moreover, exercise, diet, and parental factors can affect children with fatty liver. Conclusions NAFLD is very prevalent in children and adolescents in Shenyang city. Due to the close relationship between NAFLD and obesity, lifestyle plays a major role in the occurrence of NAFLD. Trial registration The First Affiliated Hospital of China Medical University, [2020] 2020–258-2. Registered 6 June 2020—Retrospectively registered.

This cohort study investigates the cumulative contribution of environmental and lifestyle (exposome) factors to risk of suicide attempt among youth. Key Points: Question: What is the cumulative contribution of environmental and lifestyle (exposome) factors to risk of suicide attempt among youth? Findings: In this cohort study including 40 364 youth, aggregate exposomic scores of risk and protective factors consistently explained substantial variance in suicide attempt over and above clinical risk benchmarks in diverse clinical and population youth cohorts from the US and the UK. Meaning: Results of this cohort study suggest that exposomic scores of suicide attempt provide a generalizable method for risk classification that can be applied in clinical or population settings and can advance reproducibility in suicide research. Importance: Suicide is the third-leading cause of death among US adolescents. Environmental and lifestyle factors influence suicidal behavior and can inform risk classification, yet quantifying and incorporating them in risk assessment presents a significant challenge for reproducibility and clinical translation. Objective: To quantify the aggregate contribution of environmental and lifestyle factors to youth suicide attempt risk classification. Design, Setting, and Participants: This was a cohort study in 3 youth samples: 2 national longitudinal cohorts from the US and the UK and 1 clinical cohort from a tertiary pediatric US hospital. An exposome-wide association study (ExWAS) approach was used to identify risk and protective factors and compute aggregate exposomic scores. Logistic regression models were applied to test associations and model fit of exposomic scores with suicide attempts in independent data. Youth from the Adolescent Brain Cognitive Development (ABCD) study, the UK Millennium Cohort Study (MCS), and the Children's Hospital of Philadelphia emergency department (CHOP-ED) were included in the study. Exposures: A single-weighted exposomic score that sums significant risk and protective environmental/lifestyle factors. Main Outcome and Measure: Self-reported suicide attempt. Results: A total of 40 364 youth were included in this analysis: 11 564 from the ABCD study (3 waves of assessment; mean [SD] age, 12.0 [0.7] years; 6034 male [52.2%]; 344 attempted suicide [3.0%]; 1154 environmental/lifestyle factors were included in the ABCD study), 9000 from the MCS cohort (mean [SD] age, 17.2 [0.3] years; 4593 female [51.0%]; 661 attempted suicide [7.3%]; 2864 environmental/lifestyle factors were included in the MCS cohort), and 19 800 from the CHOP-ED cohort (mean [SD] age, 15.3 [1.5] years; 12 937 female [65.3%]; 2051 attempted suicide [10.4%]; 36 environmental/lifestyle factors were included in the CHOP-ED cohort). In the ABCD discovery subsample, ExWAS identified 99 risk and protective exposures significantly associated with suicide attempt. A single weighted exposomic score that sums significant risk and protective exposures was associated with suicide attempt in an independent ABCD testing subsample (odds ratio [OR], 2.2; 95% CI, 2.0-2.6; P <.001) and explained 17.6% of the variance (based on regression pseudo-R2) in suicide attempt over and above that explained by age, sex, race, and ethnicity (2.8%) and by family history of suicide (6.3%). Findings were consistent in the MCS and CHOP-ED cohorts (explaining 22.6% and 19.3% of the variance in suicide attempt, respectively) despite clinical, demographic, and exposure differences. In all cohorts, compared with youth at the median quintile of the exposomic score, youth at the top fifth quintile were substantially more likely to have made a suicide attempt (OR, 4.3; 95% CI, 2.6-7.2 in the ABCD study; OR, 3.8; 95% CI, 2.7-5.3 in the MCS cohort; OR, 5.8; 95% CI, 4.7-7.1 in the CHOP-ED cohort). Conclusions and Relevance: Results suggest that exposomic scores of suicide attempt provided a generalizable method for risk classification that can be applied in diverse samples from clinical or population settings. [ABSTRACT FROM AUTHOR]

Abstract. This study aimed to explore aberrantly methylated-differentially expressed genes and related pathways in cholangiocarcinoma (CCA). The mRNA expression data (GSE26566) and methylation profiling data (GSE44965) were collected from the Gene Expression Omnibus (GEO) Datasets. Differentially expressed genes and differentially methylated genes were identified using GEO2R. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using clusterprofiler in R. MCODE clustering tool was used to screen modules of the protein–protein interaction network in Cytoscape. Related pathways of hub gene by using gene set enrichment analysis. Eighty-one hypermethylated, lowly expressed genes (Hyper-LGs) and 76 hypomethylated, highly expressed genes (Hypo-HGs) were identified in this study. Hyper-LGs were enriched in ion channel binding and transcription factor activity, which was associated with Mineral absorption and Cell adhesion molecules. Hypo-HGs were enriched in cysteine-type endopeptidase activity, which was associated with Sphingolipid signaling pathway and T cell receptor signaling pathway. Based on protein–protein interaction networks, MYC and VWF were identified as hub genes for Hyper-LGs, and no hub genes for Hypo-HGs. This study found methylated-differentially expressed genes and signaling pathways that are connected with the CCA by using a series of bioinformatics databases and tools. MYC and VWF act as hub genes of CCA, which can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of CCA.

Aluminum profiles are widely used in various manufacturing sectors due to their flexibility and chemical properties. However, these profiles are susceptible to defects during manufacturing and transportation. Detecting these defects is crucial, but existing object detection models like Mask R-CNN and YOLOv8-seg are not optimized for this task. These models are large and computationally intensive, making them unsuitable for edge devices used in industrial inspections. To address this issue, this study proposes a novel lightweight instance segmentation model called AL-damage-seg, inspired by the YOLOv8n-seg architecture. This model utilizes MobileNetV3 as the backbone. In YOLOv8n-seg, the role of C2f is to enhance the nonlinear representation of the model to capture complex image features more efficiently. We upgraded and improved it to form multilayer feature extraction module (MFEM) and integrates a large separable kernel attention (LSKA) mechanism in the C2f module, resulting in C2f_LSKA, to further optimize the performance of the model. Additionally, depth-wise separable convolutions are employed in the feature fusion process. The ALdamage-seg's weight on the Alibaba Tian-chi aluminum profile dataset constitutes 43.9% of that of YOLOv8n-seg, with its GFLOPs reduced to 53% relative to YOLOv8-seg, all the while achieving an average precision ( m A P ) of 99% relative to YOLOv8-seg. With its compact size and lower computational requirements, this model is well-suited for deployment on edge devices with limited processing capabilities. [ABSTRACT FROM AUTHOR]

[Purpose/significance] This paper investigates the status quo of public innovation participation and information demands, it is conducive to modifying social information provision strategy and promoting mass innovation. [Method/process] Based on the literature review and the user interview, this paper designed a questionnaire to acquire Xi 'an public perception of innovation, current situation of innovation practice, factors that influence participation in innovation, innovation information demands and other relevant information. [Result/conclusion] According to the investigation outcome and actual situation, this paper put forward the following proposals: publicizing innovation information, fostering innovative atmosphere, building maker spaces and strengthening the building of innovation centers. These proposals facilitate the distribution of innovation information and promote the innovation capacity of the society.

Given the mixed evidence that having both women and men in the top management team (TMT) or in the board of directors (BOD) has a significant influence on organizational innovation, we resolve this issue by conceptualizing TMT–BOD gender diversity as part of a multiteam system, that has joint effects which impact organizational innovation. Evidence from the study of both Chinese firms and UK firms confirm our conceptualization by showing an interaction effect between TMT gender diversity and BOD gender diversity such that innovation is greatest when both are high. The positive TMT–BOD gender diversity interaction effect on innovation improves subsequent firm performance particularly in dynamic environments. The findings refine current thinking by going beyond research that tests intra‐team TMT or BOD diversity independently and instead considers inter‐team diversity across both leadership teams within the strategic leadership upper echelons. In sum, findings show that high levels of TMT and BOD gender diversity result in more organizational innovation, which ultimately improves firm performance. We offer implications for women's inclusion in leadership as well as for research on the upper echelons. [ABSTRACT FROM AUTHOR]

A novel synergistic extractant consisting of a deep eutectic solvent (DES) and tri‐n‐butyl phosphate (TBP) is proposed for selective extraction of valuable metals from waste lithium‐ion batteries (LIBs). The extraction efficiencies of Ni2+, Co2+, and Mn2+ were 99.8%, 99.1%, and 95.9%, respectively, and high‐purity Li+ was enriched in the raffinate after the single‐stage extraction. Valuable metal salts, lithium carbonate (92.3 wt%) and cobalt oxalate (94.9 wt%), were obtained. The DES + TBP extractant retained its high extraction performance even after multiple regeneration cycles. The extraction process followed the so‐called "cation exchange mechanism" with thermodynamic properties of ΔH < 0, ΔG < 0, and ΔS < 0. The molecular‐level extraction mechanism demonstrated that the extraction process was dominated by both electrostatic and coordination interactions between the metal ions and DES/TBP, based on quantum chemical calculations. This study aims to provide a new strategy for recycling valuable metals from waste LIBs. [ABSTRACT FROM AUTHOR]