Classification of Physiology Indicators for the Automatic Detection of Potentially Hazardous Physiological States by I. G. Damousis, S. Argyropoulos, A. Muzet

“…In order to maximize the obtained information and the benefits from the use of obtrusive, physiological sensors, the collected data are processed to also detect abnormal physiology states that may endanger the subjects and those around them during critical operations. …”
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Detection of offensive content in the Kazakh language using machine learning and deep learning approaches by Milana Bolatbek, Moldir Sagynay, Shynar Mussiraliyeva, Zhastay Yeltay

“…Given the agglutinative structure and rich morphology of Kazakh, standard natural language processing (NLP) models require significant adaptation. …”
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TradeWise: Towards Context-Aware Stock Market Predictions with Sentiment and Political Insights by Andreas Marpaung, David Masterson

“…Our novel approach suggests that sentiment and political insights, when processed and integrated effectively, offer substantial predictive value that could refine the accuracy of financial prediction models. …”
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Identification of Formaldehyde under Different Interfering Gas Conditions with Nanostructured Semiconductor Gas Sensors by Lin Zhao, Jing Wang, Xiaogan Li

“…Sensor array with pattern recognition method is often used for gas detection and classification. Processing time and accuracy have become matters of widespread concern in using data analysis with semiconductor gas sensor array for volatile organic compound gas mixture classification. …”
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Identification of cellular signatures associated with chinese hamster ovary cell adaptation for secretion of antibodies by Ying Bai, Ivan Domenech Mercadé, Ramy Elgendy, Giulia Lambiase, Sew Peak-Chew, Catarina Franco, Steven W. Wingett, Tim J. Stevens, Luigi Grassi, Noah Hitchcock, Cristina Sayago Ferreira, Diane Hatton, Elizabeth A. Miller, Rajesh K. Mistry

“…Unconventional biological drugs with complex structures and processing requirements are particularly problematic. …”
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LncMPEG1/miR-2c regulates exoskeleton biocalcification via engrailed in bivalve by Minxin Liang, Caixia Cai, Ziqi Ren, Zhiqing Li, Ronglian Huang, Qingheng Wang, Yongshan Liao, Chuangye Yang, Zhe Zheng

“…This research elucidates the molecular interplay between long noncoding RNA LncMPEG1 and miRNA miR-2c in the biocalcification process of shell formation. The study establishes LncMPEG1 as a molecular sponge for miR-2c, modulating the expression of key biomineralization genes, including homeobox protein engrailed and matrix metalloproteases (MMPs). …”
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Myoelectric signal and machine learning computing in gait pattern recognition for flat fall prediction by Shuo Zhang, Biao Chen, Chaoyang Chen, Maximillian Hovorka, Jin Qi, Jie Hu, Gui Yin, Marie Acosta, Ruby Bautista, Hussein F. Darwiche, Bryan E. Little, Carlos Palacio, John Hovorka

“…Four basic ML algorithms including support vector machine (SVM), K-nearest neighbor (kNN), decision tree (DT), and naive Bayes (NB), and five deep learning models including convolutional neural network (CNN), long-short term memory (LSTM), bidirectional long short-term memory (BiLSTM), and CNN-BiLSTM were used to process the EMG signals recorded under different gaits. …”
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Predicting the Risk of Loneliness in Children and Adolescents: A Machine Learning Study by Jie Zhang, Xinyi Feng, Wenhe Wang, Shudan Liu, Qin Zhang, Di Wu, Qin Liu

“…A total of 39 indicators were collected and 28 predictors were finally included for prediction after data pre-processing, including demographic, parental relationship, mental health, pubertal development, behaviors, and environmental factors. …”
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Epizootic hemorrhagic disease virus oral infection affects midge reproduction and is vertically transmitted to offspring in Culicoides sonorensis by Dinesh Erram, Bethany McGregor, Carolina Acevedo, Barry W. Alto, Nathan Burkett-Cadena

“…In addition, the progeny (eggs and F1 generation adults) of EHDV-2 fed females were processed for viral detection through RT-qPCR and plaque assays. …”
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FAP-CAR-T cells reduce dystrophic muscle fibrosis, improving adeno-associated virus gene transfer efficacy by Maxime Ferrand, Céline J. Rocca, Guillaume Corre, Valentina Buffa, Sophie Frin, Francine Garnache-Ottou, Elodie Bôle-Richard, Sonia Albini, Isabelle Richard, Anne Galy

“…Single cell transcriptomics revealed that FAP-CAR-T cells triggered cellular interactions with otherwise inactive muscle resident macrophages and depleted specific subsets of FAP-highly-expressing fibro-adipogenic progenitor cells, pointing to their importance in the fibrosis process. Reducing fibrosis with FAP-CAR-T cells enhanced adeno-associated virus (AAV) microdystrophin gene transfer in the model by increasing vector copies, demonstrating that fibrosis is a restriction factor for AAV gene delivery in skeletal muscle. …”
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Research Progress in the Screening of Antimicrobial Substances Based on Machine Learning by HOU Jiangxia, JIANG Jinhui, WANG Chenxin, WANG Lan, SHI Liu, WU Wenjin, GUO Xiaojia, CHEN Sheng, CHEN Lang, CAO Feng, SUN Li, ZHOU Zhi

“…As a branch of artificial intelligence, machine learning algorithms have demonstrated exceptional capabilities in processing large-scale data, feature extraction, and model optimization, leading to their increasing application in the screening of antimicrobial substances. …”
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Equivalent method for DFIG wind farms based on modified LightGBM considering voltage deep drop faults by Xuecheng Liu, Peixiao Fan, Jun Yang, Song Ke, Binyu Ma, Yangzhou Pei, Jian Xu

“…First, the low voltage ride through process of wind turbines is analysed, with particular consideration given to the scenario of partial wind turbines tripping off due to voltage deep drop faults in the wind farm. …”
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SECURE METRIC DIMENSION OF ALTERNATE SNAKE GRAPHS by Basma Mohamed, Iqbal M. Batiha, Nidal Anakira, Mohammad Odeh, Mohammad Shehab, Huda Odetatllah

“…A resolving set uniquely identifies each vertex by its distance vector to the set; the smallest is the metric basis, and its size is the metric dimension. …”
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AI-Driven predicting and optimizing lignocellulosic sisal fiber-reinforced lightweight foamed concrete: A machine learning and metaheuristic approach for sustainable construction by Mohamed Sahraoui, Aissa Laouissi, Yacine Karmi, Abderazek Hammoudi, Mostefa Hani, Yazid Chetbani, Ahmed Belaadi, Ibrahim M.H. Alshaikh, Djamel Ghernaout

“…DNN-IGWO demonstrated enhanced predictive performance, significantly exceeding that of traditional machine learning models. The optimization process directed by the metaheuristic approach utilizing SMA demonstrated swift convergence in 216 iterations, identifying the optimal mix proportions of cement, water-to-cement ratio, sand, and sisal fiber content. …”
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Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat by Zhikai Cheng, Xiaobo Gu, Yadan Du, Zhihui Zhou, Wenlong Li, Xiaobo Zheng, Wenjing Cai, Tian Chang

“…Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV. …”
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NATIONAL AND CULTURAL PECULIARITIES OF THE LOVE CONCEPT IN THE PHRASEOLOGICAL PICTURE OF THE WORLD by G. Marinina, M. Pisklova

“…The analysis rests on linguo-cultural and hermeneutic approaches to studying the processes of formation and dynamics of lexical expression of certain components representing the cogitological spheres. …”
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A temperature-responsive PLA-based nanosponge as a novel nanoadjuvant and efficient delivery carrier of Ag85B for effective vaccine against Mycobacterium tuberculosis by Jin-Seung Yun, Soo-Min Kim, Jin Sil Lee, Su Hyun Jeong, Hyeryeon Oh, Panmo Son, Sunghyun Kim, Young-Ran Lee, Eunkyung Shin, Sang-Jun Ha, Yong-Woo Jung, Dokeun Kim, Hye-Sook Jeong, Won Il Choi

“…Methods Ag85B was produced using an EZtag fusion tag vector, achieving high product yield and purity. It was then loaded into aPNS, a nanoparticle system with a PLA core and Pluronic shell, through a temperature-responsive process at 4 °C that preserved protein bioactivity. …”
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A GIS Approach to Modeling the Ecological Niche of an Ecotype of <i>Bouteloua curtipendula</i> (Michx.) Torr. in Mexican Grasslands by Alma Delia Baez-Gonzalez, Jose Miguel Prieto-Rivero, Alan Alvarez-Holguin, Alicia Melgoza-Castillo, Mario Humberto Royo-Marquez, Jesus Manuel Ochoa-Rivero

“…A field work methodology was developed for the validation process using a georeferenced digital mesh and the nested sampling method modified by Whittaker. …”
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A novel machine learning models for meteorological drought forecasting in the semi-arid climate  region by Chaitanya Baliram Pande, Dinesh Kumar Vishwakarma, Aman Srivastava, Kanak N. Moharir, Fahad Alshehri, Norashidah Md Din, Lariyah Mohd Sidek, Bojan Đurin, Abebe Debele Tolche

“…Given the limited studies on ensemble and Machine Learning (ML) models for drought forecasting, this research compares five ML models [Robust Linear Regression, Bagged Trees, Boosted Trees, Support Vector Machine (SVM), and Matern Gaussian Process Regression (GPR)] to determine superior accuracy in the regional context. …”
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Effects of urban sprawl on land use change in the peripheral villages of Tehran metropolis (case study: Tehran-Damavand axis) by ِAshkan Mohammadi, Naser Shafiei Sabet, Alireza Shakiba

“…In this method, after collecting data contains Land sat satellite images with TM, ETM and OLI sensors and after visual interpretation of satellite images due to the absence of stroke errors, cloud spots by using remote sensing techniques and spatial information systems, the land use change process began in 1986, 2002, 2018, and divided into four residential and non-residential construction, vegetation, rangelands and roads. …”
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