DeepQR: single-molecule QR codes for optical gene-expression analysis by Jeffet Jonathan, Hadad Barak, Froim Sahar, Kaboub Kawsar, Rabinowitz Keren M., Deek Jasline, Margalit Sapir, Dotan Iris, Bahabad Alon, Ebenstein Yuval

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Exploring the Acceptance and Application of a Humanoid Robot: Insights from Three Field Studies

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Development and validation of a multiple myeloma diagnostic model based on systemic lupus erythematosus-associated genes and identification of specific genes by Yuepei Liu, Songshan Liu

“…Furthermore, we used the STRING database to build a PPI network for the intersecting genes and the cytoHubba plugin in Cytoscape software to identify important genes with biological significance. …”
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AbstractTrace: The Use of Execution Traces to Cluster, Classify, Prioritize, and Optimize a Bloated Test Suite by Ziad A. Al-Sharif, Clinton L. Jeffery

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Cword2vec: a novel morphological rule-based word embedding approach for Urdu text sentiment analysis by Saquib Khushhal, Abdul Majid, Syed Ali Abass, Rabia Riaz, Mohammad Babar, Shafiq Ahmad

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Computational analysis of DEHP’s oncogenic role in colorectal cancer by Zhou Zhu, Jian Qin, Chungang He, Shuangyou Wang, Yaolin Lu, Shuai Wang, Xiaogang Zhong

“…We predicted DEHP molecular targets via SwissTargetPrediction and ChEMBL databases and constructed a protein–protein interaction (PPI) network using STRING. Machine learning methods, including LASSO regression, SVM, and Random Forest, identified key genes. …”
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Exploring the complex interplay between oral Fusobacterium nucleatum infection, periodontitis, and robust microRNA induction, including multiple known oncogenic miRNAs by Syam Jeepipalli, Aravindraja C, William Duncan, V. M. Krishna, Bikash Sahay, Edward K. L. Chan, L. Kesavalu

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Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers by Wentong Li, Yiyi Zhang, Chuanhong Li, Mingyang Jiang, Dong Wang, Luomeng Chao, Luomeng Chao, Luomeng Chao, Yuxia Yang

“…Protein-protein interaction (PPI) networks were constructed using the STRING database. Biomarker validation was performed through cross-validation using LASSO, SVM-RFE, and Random Forest algorithms. …”
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Usage of hypercomplex numbers in a cryptographic key agreement protocol based on neural networks by Павел Павлович Урбанович, Надежда Павловна Шутько

“…A hash size of 512 bits are generated by transforming the string representation of the current input vector of neuron weights. …”
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Plagiarism types and detection methods: a systematic survey of algorithms in text analysis by Altynbek Amirzhanov, Cemil Turan, Alfira Makhmutova

“…This survey critically evaluates existing literature, contrasting traditional methods like string-matching with advanced machine learning, natural language processing, and deep learning approaches. …”
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Critical Evaluation of SQL Injection Security Measures in Web Applications by Haneen mohammed adhab Al salmawi

“…The VIWeb vulnerability scanner is introduced in the study, which evaluates three machine learning models—Decision Trees, Support Vector Machines (SVMs), and Artificial Neural Networks (ANNs)—for malware detection. …”
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Rack1 and Pon1 as predictive hub genes in WNT-based oral cancer: an interactomic approach by Yadalam Pradeep Kumar, Ramadoss Ramya, Anegundi Raghavendra Vamsi, Arumuganainar Deepavalli, Brahmbhatt Nilam, Mathew Asok, Ardila Carlos M

“…Protein–protein interaction (PPI) networks were constructed using the STRING database and visualised in Cytoscape. Machine learning models, including naïve Bayes and neural networks, were applied to predict interactomic hub genes based on differentially expressed gene (DEG) data. …”
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Integrative in Silico modeling for mTOR inhibition: From ridge classifiers to descriptor-free deep neural networks by Seyed Alireza Khanghahi, Hadi Kamkar, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Parviz Abdolmaleki

“…Using a variety of quantitative structure-activity relationship (QSAR) models, we present a comprehensive comparison of deep learning (DL) and classical machine learning (ML) techniques for modeling mTOR inhibitor activity. …”
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Real-time prediction of the rate of penetration via computational intelligence: a comparative study on complex lithology in Southwest Iran by Mohammad Najafi, Yousef Shiri

“…Following preprocessing and outlier removal, six features, namely, the flow rate (Q), weight on bit (WOB), standpipe pressure (SPP), depth, torque (T), and drill string rotation (DSR), were utilized as inputs for estimating the ROP. …”
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An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control by Caixia Huang, Wu Tang, Jiande Wang, Zhiyong Zhang

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Error monitoring and correction in violin performance: An EEG study by Ángel David Blanco, Jordi Costa-Faidella, Alfonso Pérez Carrillo, David Dalmazzo, Rafael Ramirez-Melendez, Iria SanMiguel

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基于神经网络和遗传算法的多齿轮并联传动优化设计 by 杜子学, 赵大毅

“…Based on neural network and genetic algorithm,the optimal designed mathematical model of multi-gear parallel drive and transmission for a certain giant overload operation machine is established.In this optimized gear design,some vague string diagrams of input-output relationship as well as the neural networks fitting methods of discrete data are given,and then the optimizing calculation by applying genetic algorithm is conducted.The result shows that through the utilization of this method,not only the working efficiency could be promoted,but the result could also be reasonable and credible.…”
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RANDOM FORCE MODELING AND VIBRATION ANALYSIS OF FIXED ABRASIVE WIRE SAW by JI LeiLei, TANG AoFei, GUO XiaoLing, CUI FangYuan

“…The main vibration patterns include the incentive of abrasive grains to the wire saw and vibrations transmitted by the machine itself. For the sake of investigating the effect of abrasive grains on the vibration of wire saws during cutting process, based on the oscillation theory of the string, the vibration equations of the wire saw in the case of a damped axially uniform motion were constructed and together with an analysis of the force in the wire saw during the process of cutting. …”
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Euclidean Distance-Based Tree Algorithm for Fault Detection and Diagnosis in Photovoltaic Systems by Youssouf Mouleloued, Kamel Kara, Aissa Chouder, Abdelhadi Aouaichia, Santiago Silvestre

“…The developed procedure for fault detection and diagnosis is implemented and applied to classify a dataset comprising seven distinct classes: normal operation, string disconnection, short circuit of three modules, short circuit of ten modules, and three cases of string disconnection, with 25%, 50%, and 75% of partial shading. …”
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QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals by Veysel Yusuf Cambay, Irem Tasci, Gulay Tasci, Rena Hajiyeva, Sengul Dogan, Turker Tuncer

“…The proposed XFE model generates a DLob string, and the explainable results were obtained using this string. …”
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