Targeting SPATS2 in lung adenocarcinoma: implications for prognosis and immune-based therapy by Maorong Teng, Fangtao Yan, Jingping Shang, Xiaohua Sun, Yahui Wang, Jian Shen

“…Abstract Background Lung adenocarcinoma (LUAD) is a major contributor to cancer mortality and exhibits high intratumoral heterogeneity. The functional role of SPATS2 in LUAD remains poorly defined. …”
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Few-Shot Object Detection via Sample Processing by Honghui Xu, Xinqing Wang, Faming Shao, Baoguo Duan, Peng Zhang

“…For the fine-tuning phase, we modify the classification loss function to increase the punishment for hard samples. …”
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Dynamic Risk Assessment System for Power System Based on Multi-source Information of the Ubiquitous Power Internet of Things by Shenhua WANG, Xiangwei HE, Xiaofang FANG, Bingsong CHEN, Chuangxin GUO

“…The data source, data platform and main function modules of the system are also described. …”
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Network insights into childhood obesity: unveiling methylated-differentially expressed genes and pathways through integrative bioinformatics analysis by Felipe Mateus Pellenz, Guilherme Coutinho Kullmann Duarte, Giovanna Câmara Giudicelli, Thayne Woycinck Kowalski, Taís Silveira Assmann, Daisy Crispim

“…The PPI network highlighted three hub-bottleneck genes (CCL5, STAT1, and GATA3) and two functional modules. Overall, the 70 MeDEGs were associated with KEGG pathways related to cellular differentiation, inflammation, chemokine signaling, lipid and glucose metabolism, insulin resistance, and apoptosis. …”
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Brain CT image classification based on mask RCNN and attention mechanism by Shoulin Yin, Hang Li, Lin Teng, Asif Ali Laghari, Ahmad Almadhor, Michal Gregus, Gabriel Avelino Sampedro

“…The deformable convolution is embedded to the two modules to extract global features. Finally, the loss function is improved to further optimize the precision of target edge segmentation in the Mask RCNN branch. …”
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Reconfigurable Hardware-based Embedded Control System Development using LabView Environment by SZÁSZ Csaba

“…Usually embedded systems are optimized for a particular task and function. They express many advantages in terms of performance, cost-effectiveness, reliability, size-weight, or interfacing versatility over other computing solutions. …”
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Residual Vision Transformer and Adaptive Fusion Autoencoders for Monocular Depth Estimation by Wei-Jong Yang, Chih-Chen Wu, Jar-Ferr Yang

“…Lastly, the model is trained using a loss function that aligns with human perception to enable it to focus on the depth values of foreground objects. …”
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Multi-Sensor Information Fusion Positioning of AUKF Maglev Trains Based on Self-Corrected Weighting by Qian Hu, Hong Tang, Kuangang Fan, Wenlong Cai

“…It combines the Sage–Husa algorithm with the unscented Kalman filter (UKF) to form the AUKF algorithm using the data collected by the cross-sensor lines, INS, Doppler radar, and GNSS, which adaptively updates the statistical feature estimation of the measurement noise and eliminates the single-function and low-integration shortcomings of the various modules to achieve the precise positioning of maglev trains. …”
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Improved IEC performance via emotional stimuli-aware captioning by Zibo Zhou, Zhengjun Zhai, Xin Gao, Jiaqi Zhu

“…We also introduce a variable-weight loss function to emphasize hard-to-classify samples. Extensive validation experiments using multiple public datasets demonstrated that our approach outperformed state-of-the-art models. …”
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Online ECG Biometrics for Streaming Data with Prototypes Learning and Memory Enhancement by Kuikui Wang, Na Wang

“…Furthermore, we design a novel and efficient online optimization algorithm to minimize the overall loss function. Extensive experiments conducted on two widely used datasets demonstrate the effectiveness of our proposed method.…”
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Expression of cell-wall related genes is highly variable and correlates with sepal morphology by Hartasánchez, Diego A., Kiss, Annamaria, Battu, Virginie, Soraru, Charline, Delgado-Vaquera, Abigail, Massinon, Florian, Brasó-Vives, Marina, Mollier, Corentin, Martin-Magniette, Marie-Laure, Boudaoud, Arezki, Monéger, Françoise

“…Although causality between gene expression and sepal morphology has not been established, our approach opens the way to informed analysis for mutant characterization and functional studies. …”
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Novel Insights from Comprehensive Bioinformatics Analysis Utilizing Large-Scale Human Transcriptomes and Experimental Validation: The Role of Autophagy in Periodontitis by Liu F, Zhu Z, Zou H, Huang Z, Xiao S, Li Z

“…This investigation involved transcriptomic analysis of a broad range of human samples and complemented by in vitro experimentation.Materials and Methods: We analyzed the transcriptomes of human gingival tissues from individuals with periodontitis and health controls to identify the differential expression of autophagy-related genes (DEARGs) and to investigate their potential interactions and functional pathways. Additionally, protein-protein interaction (PPI) networks were constructed to identify key functional modules and hub genes. …”
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Identification of biomarkers and target drugs for melanoma: a topological and deep learning approach by Xiwei Cui, Xiwei Cui, Jipeng Song, Qingfeng Li, Jieyi Ren

“…Advanced network analysis tools were employed to identify structural disparities and functional module shifts. Key driver genes were validated through topological centrality metrics. …”
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Bioinformatics analysis identifies dysregulation of MiR-548F-3p and its hub gene in triple-negative breast cancer by Samira Behroozi, Mahdieh Salimi, Najaf Allahyari Fard

“…Functional enrichment and protein-protein interaction (PPI) network analyses were conducted. …”
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Iron metabolism and preeclampsia: new insights from bioinformatics analysis by Xijiao Guo, Sha Li, Guoping Xiong

“…Subsequently, WGCNA was used to screen for genes associated with PE. Functional annotations were performed for the intersection of differentially expressed genes (DEGs), two key modules, and iron metabolism-related genes. …”
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Identification of EXPA4 as a key gene in cotton salt stress adaptation through transcriptomic and coexpression network analysis of root tip protoplasts by Qiankun Liu, Pengtao Li, Muhammad Jawad Umer, Mubashir Abbas, Yongqing Zhao, Yu Chen, Yanfang Li, Aiming Zhang, Yuling Liu, Yangyang Wei, Quanwei Lu, Mengying Yang, Yiman Liu, Xiaoyan Cai, Zhongli Zhou, Shuxun Yu, Fang Liu, Renhai Peng

“…Conclusion These findings underscore the functional significance of GaEXPA4 in the salt stress response. …”
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DynExp—Highly flexible laboratory automation for dynamically changing classical and quantum experiments by Julian M. Bopp, Tim Schröder

“…It enables to assign physical devices to measurement modules at runtime and provides networking functionality. …”
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Design of a Wearable Exoskeleton Piano Practice Aid Based on Multi-Domain Mapping and Top-Down Process Model by Qiujian Xu, Meihui Li, Guoqiang Chen, Xiubo Ren, Dan Yang, Junrui Li, Xinran Yuan, Siqi Liu, Miaomiao Yang, Mufan Chen, Bo Wang, Peng Zhang, Huiguo Ma

“…This method integrates the functional domain, structural domain, and user needs domain, and explores the principles and methods for creating functional construction modules, overcoming the limitations of traditional top-down approaches in design flexibility. …”
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Dual associations of gut and oral microbial networks with kidney transplantation by Siming Qu, Yuzheng Gu, Xiaoxue Hou, Min Wei, Mengmeng Wang, Yuya Su, Yinglei Miao, Jinlong Yang, Yang Sun, Zhong Zeng

“…Through shotgun metagenomic sequencing of fecal and saliva samples, we found that for both gut and oral microbiome, the initial loss of species diversity after kidney transplantation led to a reduction in network nodes and interactions, but strengthened the connections among the remaining species, which started to get a recovery approximately 7–14 days later. Different network modules tended to exhibit unique functions and showed different responses to transplantation. …”
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Frequency experimental identification approach for single-phase induction motor common-mode parameters by Y. Hakmi, H. Miloudi, M. Miloudi, A. Gourbi, M. H. Bermaki

“…The motor impedance analysis is based on the measurement of variations in motor characteristics as a function of frequency in the CM setup. Originality. …”
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