A Multifeature Fusion Short-Term Traffic Flow Prediction Model Based on Deep Learnings by Chunxu Chai, Chuanxiang Ren, Changchang Yin, Hui Xu, Qiu Meng, Juan Teng, Ge Gao

“…Moreover, a feature fusion layer in the model is used to fuse the features extracted by each module. And then, the number of neurons in the model, the loss function, and other parameters such as the optimization algorithm are discussed and set up through simulation experiments. …”
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RETRACTED: In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlying Mycobacterium bovis infection by Aliakbar Hasankhani, Abolfazl Bahrami, Abolfazl Bahrami, Shayan Mackie, Sairan Maghsoodi, Heba Saed Kariem Alawamleh, Negin Sheybani, Farhad Safarpoor Dehkordi, Farhad Safarpoor Dehkordi, Fatemeh Rajabi, Ghazaleh Javanmard, Hosein Khadem, Herman W. Barkema, Marcos De Donato

“…Additionally, functional enrichment analysis was used to investigate the biological behavior of the non-preserved modules and to identify bTB-specific non-preserved modules. …”
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A Two-Piece Derivative of a Group I Intron RNA as a Platform for Designing Self-Assembling RNA Templates to Promote Peptide Ligation by Takahiro Tanaka, Hiroyuki Furuta, Yoshiya Ikawa

“…Multicomponent RNA-peptide complexes are attractive from the viewpoint of artificial design of functional biomacromolecular systems. We have developed self-folding and self-assembling RNAs that serve as templates to assist chemical ligation between two reactive peptides with RNA-binding capabilities. …”
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Identification of Periodontal Disease Diagnostic Markers Via Data Cross-Validation by Juan Du, Yi Liu, Zhenhua Luo, Minfeng Wang, Yitong Liu

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Cluster-independent multiscale marker identification in single-cell RNA-seq data using localized marker detector (LMD) by Ruiqi Li, Rihao Qu, Fabio Parisi, Francesco Strino, Hainan Lam, Jay S. Stanley, Xiuyuan Cheng, Peggy Myung, Yuval Kluger

“…LMD’s candidate markers can be grouped into functional gene modules, which accurately reflect cell types, subtypes, and other sources of variation such as cell cycle status. …”
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Visualization of large-scale user association feature data based on a nonlinear dimensionality reduction method by Nong Linlin

“…Secondly, the nonlinear dimensionality reduction algorithm is integrated into the platform, and the functional modules and data dimensionality reduction modules of the platform are finally tested. …”
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DIFF: A dataset for indoor flexible furniture by Jia-Hong Liu, Shao-Kui Zhang, Shuran Sun, Zihao Wang, Song-Hai Zhang

“…Each module exhibits flexibility in shifting to multiple shapes and functionalities. …”
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Enhancing Real-Time Road Object Detection: The RD-YOLO Algorithm With Higher Precision and Efficiency by Weijian Wang, Wei Yu

“…Finally, we introduce MPDIoU as the new bounding box regression loss function, replacing the original loss function to accelerate algorithm convergence and improve target localization accuracy. …”
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DWS-YOLO: A Lightweight Detector for Blood Cell Detection by Yihai Mao, Hongyi Zhang, Wanqing Wu, Xingen Gao, Zhibin Lin, Juqiang Lin

“…Our model includes several improved modules, including the lightweight C3 module, the increased combined attention mechanism, the Scylla-IoU loss function, and the improved soft non-maximum suppression. …”
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Identification of signature genes and relationship with immune cell infiltration in intervertebral disc degeneration by Kun Mu, JingChao Geng, Yu Dong, Wei Guo, Wei Guo, Wei Guo

“…Weighted gene coexpression network analysis (WGCNA) and DEGs were employed to pinpoint the key modules and IVD degeneration genes. Functional enrichment analysis was performed for these IVD degeneration genes. …”
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Enhancing oxygen utilization and mitigating oxidative stress in Tibetan chickens for adaptation to high-altitude hypoxia by Ruidong Hao, Xianpei Ao, Yijing Xu, Mengyu Gao, Cunling Jia, Xianggui Dong, Cirenluobu, Peng Shang, Yourong Ye, Zehui Wei

“…Further investigation of the function of hub TFs indicated the involvement of ATF4, CEBPA, TCF7L1, and GFI1B in improving oxygen transport in TBCs. …”
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Design and Implementation of J2EE Application Service Middleware Monitoring System of Nanning Power Supply Bureau by Yiming Wu, Yongtao Tian

“…The object of study is Tomcat, using JMX technology to achieve the core function of monitoring system. A discussion was made in detail about the design, function modules and system implementation of J2EE application services middleware monitoring system. …”
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Design and Implementation of J2EE Application Service Middleware Monitoring System of Nanning Power Supply Bureau by Yiming Wu, Yongtao Tian

“…The object of study is Tomcat, using JMX technology to achieve the core function of monitoring system. A discussion was made in detail about the design, function modules and system implementation of J2EE application services middleware monitoring system. …”
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Structural Insights into the Protein Mannosyltransferase from Mycobacterium tuberculosis reveal a WW-Domain-Like Protein Motif in Bacteria by Nicolas Géraud, Chloé Rivière, Camille Falcou, Gianluca Cioci, Carine Froment, Virginie Gervais, Julien Marcoux, Martine Gilleron, Jérôme Nigou, Emeline Fabre, Michel Rivière

“…This first identification of a functional WW-like domain in a prokaryotic protein raises questions about its potential evolutionary linkage with eukaryotic WW modules and provides new insights into PMT’s acceptor-substrate recognition mechanism paving the way for the development selective inhibitors of MtPMT with potential therapeutic application against tuberculosis.…”
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Similarity of immune-associated markers in COVID-19 and Kawasaki disease: analyses from bioinformatics and machine learning by Wang Li, Wenjie Zhu, Xiangting Tang, Zhiting Peng, Jiaqi Ye, Shuping Nie

“…Results This analysis identified 26 shared DEGs in COVID-19 and KD. The results from functional annotation showed that the shared DEGs primarily functioned in immune responses, the formation of neutrophil extracellular traps, and NOD-like receptor signaling pathways. …”
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Identification and characterization of gene networks and key genes related to the high-yield production of milk in high-yield cows using meta-analysis of microarray data by Mahdi Rahmatzadeh, Reza Shokri-Gharelo, Morteza Derakhti-Dizaji, Asghar Bazzaz, Bizhan Mahmoudi

“…Moreover, we could reveal some gene modules and hub genes in each module which are biologically more meaningful.…”
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Intelligent assistance system for people with visual impairments by Олеся Барковська, Віталій Сердечний

“…Tasks: To achieve the set objective, the following tasks were accomplished: a generalized functional model of the proposed intelligent assistance system for people with visual impairments was created; the functional dependencies of the components of the developed model were substantiated; a review of the basic modules of the proposed system model was conducted. …”
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DNA-damage-associated protein co-expression network in cardiomyocytes informs on tolerance to genetic variation and disease by Omar Darrel Johnson, Sayan Paul, José Angel Gutiérrez, William Kent Russell, Michelle Claire Ward

“…A network constructed from 4,178 proteins reveals 12 co-expressed modules with 403 hub proteins. Five modules correlate with DOX and associate with RNA processing, chromatin regulation, and metabolism. …”
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The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma by Binyu Wang, Di Liu, Danfei Shi, Xinmin Li, Yong Li

“…Subsequently, Weighted Gene Co-expression Network Analysis (WGCNA) was conducted to classify DEGs into modules. Functional annotation of these modules was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. …”
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Comparing UNet configurations for anthropogenic geomorphic feature extraction from land surface parameters. by Sarah Farhadpour, Aaron E Maxwell

“…This study investigates a variety of architectural modifications to base UNet including replacing the rectified linear unit (ReLU) activation function with leaky ReLU or swish; incorporating residual connections within the encoder blocks, decoder blocks, and bottleneck; inserting squeeze and excitation modules into the encoder or attention gate modules along the skip connections; replacing the default bottleneck layer with one that incorporates dilated convolution; and using a MobileNetV2 architecture as an encoder backbone. …”
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