NF-GAT: A Node Feature-Based Graph Attention Network for ASD Classification by Shuaiqi Liu, Beibei Liang, Siqi Wang, Bing Li, Lidong Pan, Shui-Hua Wang

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Systematic review of machine learning applications using nonoptical motion tracking in surgery by Teona Z. Carciumaru, Cadey M. Tang, Mohsen Farsi, Wichor M. Bramer, Jenny Dankelman, Chirag Raman, Clemens M. F. Dirven, Maryam Gholinejad, Dalibor Vasilic

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Towards pen‐holding hand pose recognition: A new benchmark and a coarse‐to‐fine PHHP recognition network by Pingping Wu, Lunke Fei, Shuyi Li, Shuping Zhao, Xiaozhao Fang, Shaohua Teng

“…Abstract Hand pose recognition has been one of the most fundamental tasks in computer vision and pattern recognition, and substantial effort has been devoted to this field. …”
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Passive Monitoring of Parkinson Tremor in Daily Life: A Prototypical Network Approach by Luc J. W. Evers, Yordan P. Raykov, Tom M. Heskes, Jesse H. Krijthe, Bastiaan R. Bloem, Max A. Little

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Gut Microbiome and Inflammation: A Study of Diabetic Inflammasome-Knockout Mice by Roma Pahwa, Miriam Balderas, Ishwarlal Jialal, Xinpu Chen, Ruth Ann Luna, Sridevi Devaraj

“…Diabetes is a proinflammatory state, evidenced by increased pattern recognition receptors and the inflammasome (NOD-like receptor family pyrin domain (NLRP)) complex. …”
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Effect of complexation with lanthanide metal ions on the photochromism of (1,3,3-trimethyl-<mml:math alttext="$5'$"> <mml:msup> <mml:mn>5</mml:mn> <mml:mo>&#x2032;</mml:mo...

“…Moreover, luminescence mappings for pattern recognition analysis have been obtained from which the nature of the solvent and/or the ligand is clearly identified.…”
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À la recherche des points-clefs de Gilbert Simondon autour d’un système d’information géographique by Stephan Kowal

“…In an effort to link digital cartography to architectural design, this article exemplifies the transition from representations based on the human eye, developed since the Renaissance, to the use of remote sensing devices and computer-generated imageries, pattern recognition, influencing decision-making and design, with the system’s capacity to generate new knowledge with the overlay and combination processes of point elements. …”
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Effects of Microbes on Insect Host Physiology and Behavior Mediated by the Host Immune System by Shan Zhang, Zhengyan Wang, Qiong Luo, Lizhen Zhou, Xin Du, Yonglin Ren

“…Insects recognize environmental pathogens through pattern recognition receptors, thus activating the innate immune system to eliminate pathogens. …”
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Regulating Immune Responses Induced by PEGylated Messenger RNA–Lipid Nanoparticle Vaccine by Hyein Jo, Jaewhoon Jeoung, Wonho Kim, Dooil Jeoung

“…After an mRNA-LNP vaccine enters a cell via an endosome, mRNA is translated into an antigen, which can activate adaptive immunity. mRNAs can bind to various pattern recognition receptors (PRRs), including toll-like receptors (TLRs), and increase the production of inflammatory cytokines. …”
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Comprehensive analysis of ionomic profiling in Chlorella exposed to chlorpyrifos by Qing-Qing Yu, Yulong Zhang, Shiyuan Zhao, Min Pang, Pei Jiang, Pei Qu

“…However, little is known about the toxicological mechanism of CPF on marine microalgae, which is the main primary producer in the marine ecosystem.MethodsThis study explored the ion changes of microalgae Chlorella vulgaris under the stress of CPF through Inductively Coupled Plasma Mass Spectrometry (ICP-MS).ResultsSignificant disparities in ionomics among control and treatment group were observed through pattern recognition analysis (principal component analysis, PCA; orthogonal partial least squares discriminant analysis, OPLS-DA), indicating that CPF may impede their growth by disrupting the homeostasis of crucial elements within algal cells.DiscussionThis study elucidated the inhibitory impact of CPF on green algae growth and its potential mechanism of toxicity through ICP-MS, providing crucial insights for a comprehensive understanding of the influence of organophosphorus pesticides on aquatic ecosystems.…”
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Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization by Guosheng Cui, Ye Li, Jianzhong Li, Jianping Fan

“…Nonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. It has been widely used and studied in the multi-view clustering tasks because of its effectiveness. …”
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A robust, deep learning-based analysis of time-domain signals for NMR spectroscopy by Kyungdoe Han, Eunhee Kim, Kyoung-Seok Ryu, Donghan Lee

“…However, recent advancements in artificial intelligence, particularly deep learning, have demonstrated superior pattern recognition capabilities compared to humans in complex scenarios. …”
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ECT Image Recognition of Pipe Plugging Flow Patterns Based on Broad Learning System in Mining Filling by Xuebin Qin, ChenChen Ji, Yutong Shen, Pai Wang, Mingqiao Li, Junle Zhang

“…This conclusion indicates the effectiveness of BLS to predict different two-phase flow patterns; it also provides a new solution for the pattern recognition of the flow pattern in the mining filling pipeline.…”
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Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. …”
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Evaluation of an Information Flow Gain Algorithm for Microsensor Information Flow in Limber Motor Rehabilitation by Naiqiao Ning, Yong Tang

“…After the noise is removed, the signal is extracted in the time domain and frequency domain, and the root mean square (RMS), absolute mean, median frequency in the time domain, and average power frequency in the frequency domain are selected and input to the classifier for pattern recognition. The support vector machine is used to classify the myoelectric signals and optimize the parameters in the support vector machine using the grid search method and particle swarm optimization algorithm and classify the test samples using the trained support vector machine. …”
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Toll-Like Receptor Signaling and Liver Fibrosis by Tomonori Aoyama, Yong-Han Paik, Ekihiro Seki

“…Toll-like receptors (TLRs) are pattern recognition receptors that sense pathogen-associated molecular patterns (PAMPs), which discriminate the products of microorganisms from the host. …”
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Combinations of TLR Ligands: A Promising Approach in Cancer Immunotherapy by Saskia Stier, Claudia Maletzki, Ulrike Klier, Michael Linnebacher

“…Toll-like receptors (TLRs), a family of pattern recognition receptors recognizing molecules expressed by pathogens, are typically expressed by immune cells. …”
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Serum and Brain Metabolomic Variations Reveal Perturbation of Sleep Deprivation on Rats and Ameliorate Effect of Total Ginsenoside Treatment by Xiao-jun Gou, Fang Cen, Zi-quan Fan, Ying Xu, Hong-yi Shen, Ming-mei Zhou

“…In this study, serum and brain metabolomic method based on gas chromatography coupled with mass spectrometry (GC/MS) was employed to evaluate the efficacy and study the mechanism of GS on a rat model of SD. With pattern recognition analysis of serum and brain tissue metabolite profile, a clear separation of the model group and control group was acquired for serum and brain tissue samples; the MGS (model + GS) group showed a tendency of recovering when compared to control group, which was consistent with behavioral and biochemical parameters. 39 and 40 potential biomarkers of brain tissues and serum samples, respectively, were identified and employed to explore the possible mechanism. …”
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Catastrophic and violent tornadoes: a detailed review of physical-mathematical models by Sergey A. Arsen’yev, Lev V. Eppelbaum

“…A method for nonstochastic long-term forecasting using the pattern recognition theory and Fourier analysis has recently been developed. …”
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The Walk of Guilt: Multimodal Deception Detection from Nonverbal Motion Behaviour by Sharifa Alghowinem, Sabrina Caldwell, Ibrahim Radwan, Michael Wagner, Tom Gedeon

“…From these baseline results, we can conclude that pattern recognition techniques could help in characterising deceptive behaviour, where future work will focus on exploring the tuning and enhancement of the results and techniques.…”
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