Service capability evaluation of electric vehicle charging and battery swapping stations: A game theory‐based combination weighting method

The rapid development of electric vehicles (EVs) has made the construction and service capability evaluation of EV charging and battery swapping stations (CBSSs) more important. A comprehensive evaluation indicator system for the service capability evaluation of EV‐CBSSs is established, meticulously outlining the critical aspects of operational efficiency, economy, convenience, and reliability, each with multiple indicators for thorough assessment. To address the shortcomings of individual evaluation methods in evaluating the service capability of EV‐CBSSs, the game theory‐based combination weighting (GTCW) method is adopted, which integrates the advantages of the analytic hierarchy process method, entropy weight method, and grey relation analysis method. Specifically, the weights for each indicator are obtained separately using these three evaluation methods, and then combined using the GTCW method to calculate the final weights. In case studies, the service capability for each EV‐CBSS is calculated and compared between these three individual methods and the proposed GTCW method. Simulation results validate that the proposed evaluation indicator system and GTCW method can offer a more comprehensive evaluation of the service capability for EV‐CBSSs, providing guiding suggestions for future construction plans

Aloperine Suppresses Cancer Progression by Interacting with VPS4A to Inhibit Autophagosome-lysosome Fusion in NSCLC.

Aloperine (ALO), a quinolizidine-type alkaloid isolated from a natural Chinese herb, has shown promising antitumor effects. Nevertheless, its common mechanism of action and specific target remain elusive. Here, it is demonstrated that ALO inhibits the proliferation and migration of non-small cell lung cancer cell lines in vitro and the tumor development in several mouse tumor models in vivo. Mechanistically, ALO inhibits the fusion of autophagosomes with lysosomes and the autophagic flux, leading to the accumulation of sequestosome-1 (SQSTM1) and production of reactive oxygen species (ROS), thereby inducing tumor cell apoptosis and preventing tumor growth. Knockdown of SQSTM1 in cells inhibits ROS production and reverses ALO-induced cell apoptosis. Furthermore, VPS4A is identified as a direct target of ALO, and the amino acids F153 and D263 of VPS4A are confirmed as the binding sites for ALO. Knockout of VPS4A in H1299 cells demonstrates a similar biological effect as ALO treatment. Additionally, ALO enhances the efficacy of the anti-PD-L1/TGF-β bispecific antibody in inhibiting LLC-derived subcutaneous tumor models. Thus, ALO is first identified as a novel late-stage autophagy inhibitor that triggers tumor cell death by targeting VPS4A

Effects of Aging Stereotype Threat on Working Self-Concepts: An Event-Related Potentials Approach

Although the influence of stereotype threat (ST) on working self-concepts has been highlighted in recent years, its neural underpinnings are unclear. Notably, the aging ST, which largely influences older adults’ cognitive ability, mental and physical health, did not receive much attention. In order to investigate these issues, electroencephalogram (EEG) data were obtained from older adults during a modified Stroop task using neutral words, positive and negative self-concept words in aging ST vs. neutral control conditions. Results showed longer reaction times (RTs) for identifying colors of words under the aging ST compared to the neutral condition. More importantly, the negative self-concept elicited more positive late P300 amplitudes and enhanced theta band activities compared to the positive self-concept or neutral words under the aging ST condition, whereas no difference was found between these self-concepts and neutral words in the control condition. Furthermore, the aging ST induced smaller theta band synchronization and enhanced alpha band synchronization compared to the control condition. Moreover, we also observed valence differences in self-concepts where the negative self-concept words reduced early P150/N170 complex relative to neutral words. These findings suggest that priming ST could activate negative self-concepts as current working self-concept, and that this influence occurred during a late neural time course

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Drug sensitivity prediction with high-dimensional mixture regression.

This paper proposes a mixture regression model-based method for drug sensitivity prediction. The proposed method explicitly addresses two fundamental issues in drug sensitivity prediction, namely, population heterogeneity and feature selection pertaining to each of the subpopulations. The mixture regression model is estimated using the imputation-conditional consistency algorithm, and the resulting estimator is consistent. This paper also proposes an average-BIC criterion for determining the number of components for the mixture regression model. The proposed method is applied to the CCLE dataset, and the numerical results indicate that the proposed method can make a drastic improvement over the existing ones, such as random forest, support vector regression, and regularized linear regression, in both drug sensitivity prediction and feature selection. The p-values for the comparisons in drug sensitivity prediction can reach the order O(10-8) or lower for the drugs with heterogeneous populations

An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity

Acting as a virtual sensor network for household appliance energy use monitoring, non-intrusive load monitoring is emerging as the technical basis for refined electricity analysis as well as home energy management. Aiming for robust and reliable monitoring, the ensemble approach has been expected in load disaggregation, but the obstacles of design difficulty and computational inefficiency still exist. To address this, an ensemble design integrated with multi-heterogeneity is proposed for non-intrusive energy use disaggregation in this paper. Firstly, the idea of utilizing a heterogeneous design is presented, and the corresponding ensemble framework for load disaggregation is established. Then, a sparse coding model is allocated for individual classifiers, and the combined classifier is diversified by introducing different distance and similarity measures without consideration of sparsity, forming mutually heterogeneous classifiers. Lastly, a multiple-evaluations-based decision process is fine-tuned following the interactions of multi-heterogeneous committees, and finally deployed as the decision maker. Through verifications on both a low-voltage network simulator and a field measurement dataset, the proposed approach is demonstrated to be effective in enhancing load disaggregation performance robustly. By appropriately introducing the heterogeneous design into the ensemble approach, load monitoring improvements are observed with reduced computational burden, which stimulates research enthusiasm in investigating valid ensemble strategies for practical non-intrusive load monitoring implementations

Effect of providing free glasses on children's educational outcomes in China: cluster randomized controlled trial

Development and application of statistical models for medical scientific researc

CircEZH2 Regulates Milk Fat Metabolism through miR-378b Sponge Activity

In this study, we evaluated the roles of heat-induced circEZH2 in the regulation of milk fat metabolism. CircEZH2 overexpression increased HC11 cell proliferation and decreased apoptosis. These changes were accompanied by increased expression of proliferation marker proteins (PCNA, Cyclin D, and Cyclin E) and the anti-apoptotic protein Bcl2, while expression of the pro-apoptotic proteins Bax and cleaved-caspase was reduced. SiRNA-mediated silencing of EZH2 in HC11 cells had the opposite effects. CircEZH2 overexpression promoted the uptake of a fluorescent fatty acid (Bodipy) as well as expression of the fatty acid transport-related protein CD36, lipolysis-related protein LPL, and unsaturated fatty acid metabolism-related proteins FADS1 and SCD1. Dual luciferase reporter assays verified the targeting relationship of the two ceRNA networks, circEZH2-miR378b-LPL and circEZH2-miR378b-CD36. This information provides further clarification of the role of circRNAs in milk fat regulation in addition to a theoretical basis for alleviating the effects of heat stress on milk production by dairy cows

A two-dimensional correlation spectroscopy analysis-based approach for asymptomatic rot detection in stored potatoes using hyperspectral imaging

Fusarium dry rot (FDR), which is caused by several Fusarium species, is a major disease affecting potatoes during storage. The study aimed to identify the gleyic stage and monitor rot progression in stored potatoes using a hyperspectral imaging (HSI) system. We evaluated the susceptibility parameters and quality attributes during the infection process and monitored starch, soluble protein, malondialdehyde, and aerobic bacterial contents in all samples. To further characterize the infection process, we collected spectral data on different storage days and then mapped these data using two-dimensional correlation spectroscopy. The results revealed 20 peaks related to these component contents. Then, the quantitative analysis models of these indicators were established based on the 2D correlation synchronization spectrum. The optimal correlation coefficients of the validation set were 0.9273, 0.9634, 0.9470, and 0.9487 for these indicators. Visual analysis was implemented to these indicators, and the content distribution can be effectively observed on hyperspectral images

Infection Heterogeneity and Microbiota Differences in Chicks Infected by Salmonella enteritidis

This study was conducted to compare the infection heterogeneity and cecal microbiota in chicks infected by S. enteritidis. Forty-eight 8-d-old female Arbor Acres chicks were challenged with S. enteritidis and euthanized 24 h later. The eight chicks with the highest Salmonella tissue loads were assigned to group S (S. enteritidis-susceptible), and the eight chicks with the lowest Salmonella tissue loads were assigned to group R (S. enteritidis-resistant). Chicks in group S showed a higher liver index (p &lt; 0.05), obvious liver lesions, and an decreasing trend for the villus height-to-crypt depth ratio (p &lt; 0.10), compared with those in group R. Gene expression of occludin, MUC2, and IL10 was higher, whereas that of iNOS and IL6 was lower (p &lt; 0.05), in chicks of group R relative to those in group S. Separation of the cecal microbial community structure has been found between the two groups. The S. enteritidis-susceptible chicks showed higher abundance of pathogenic bacteria (Fusobacterium and Helicobacter) in their cecal, while Desulfovibrio_piger was enriched in the cecal of S. enteritidis-resistant chicks. In summary, chicks showed heterogeneous responses to S. enteritidis infection. Enhanced intestinal barrier function and cecal microbiota structure, especially a higher abundance of Desulfovibrio_piger, may help chicks resist S. enteritidis invasion