Research on load reduction and rockburst prevention technology in areas with square composite structures of extra-thick coal seams under strong impact by JIAO Biao, MA Hongyuan, HAO Baoli, YANG Huadong, SHI Xingxing, ZHANG Huaizhong, DONG Zhe

“…To reveal the impact risk when mining advances into special areas of strong-impact extra-thick coal seams and to enhance rockburst prevention safety during the mining process, the square composite structure area of the 401106 working face at Hujiahe Mine was taken as the engineering background. …”
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Genetic analysis of grain yield and related traits of extra-early orange maize inbred lines and their hybrids under drought and rain-fed conditions by Tégawendé Odette Bonkoungou, Tégawendé Odette Bonkoungou, Baffour Badu-Apraku, Victor Olawale Adetimirin, Kiswendsida Romaric Nanema, Idris Ishola Adejumobi

“…The 41 inbred lines were classified into three heterotic groups under both growing conditions. …”
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Plasma biomarkers for afatinib monotherapy in EGFR-mutated non-small cell lung cancer: Novel insights from companion genomics analysis of the EXTRA study by Tomonori Makiguchi, Hisashi Tanaka, Kei Morikawa, Aya Hirata, Hidetoshi Itani, Shigeru Tanzawa, Kageaki Watanabe, Hiroyuki Yasuda, Kazuya Horiuchi, Hideyuki Nakagawa, Yoshitaka Seki, Yoshiro Nakahara, Kentaro Hayashi, Nobumasa Takahashi, Takeo Endo, Akihiro Bessho, Tetsuya Okano, Kiyoshi Takeyama, Akikazu Kawase, Makoto Endo, Toshiya Maekura, Kenji Nemoto, Nagio Takigawa, Kazuma Kishi, Kenzo Soejima, Yusuke Okuma, Akira Togashi, Noriyuki Matsutani, Hiroki Shinchi, Koji Ueda, Nobuhiko Seki

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In Silico Detection of Virulence Genes in Whole-Genome Sequences of Extra-Intestinal Pathogenic <i>Escherichia coli</i> (ExPEC) Documented in Countries of the Andean Community by Nabila Aldaz, Karen Loaiza, César Marcelo Larrea-Álvarez, Miroslava Anna Šefcová, Marco Larrea-Álvarez

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Effect of Cefotaxime Administration on the kidney, liver and Lung of Swiss white Mice (mus musculus) by Asraa Abed Jazaa

“…The experiment was designed by using 30 Swiss white mice from both sexes. • Mice were classified randomly into three groups: Group A: Control Group, injected intramuscularly with 0.5ml distilled water daily for 6 days. …”
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Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil with lower-grade olive oils and hazeln... by Derick Malavi, Katleen Raes, Sam Van Haute

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Integration of Multiple Biosensors for Emotion Classification with Artificial Intelligence by Cintia Ricaele Ferreira da Silva, Marcus Vinicius Costa Alves, Maria José Nunes Gadelha, Edgard Morya

“…After preprocessing, the data were input into LazyPredict, where the Extra Trees model consistently demonstrated the best performance for binary emotion classification. …”
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Could the quality characteristics of virgin olive oil influence its geographical classification using untargeted infrared spectroscopy and chemometrics? by Davide De Angelis, Michela Pia Totaro, Francesco Caponio, Michele Faccia, Giacomo Squeo

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Enhancing Power Grid Reliability With Machine Learning and Auxiliary Classifier Generative Adversarial Networks: A Study on Fault Detection Using the Georgia Electric System Load D... by Hafeez Ur Rehman Siddiqui, Robert Brown, Adil Ali Saleem, Muhammad Amjad Raza, Sandra Dudley

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Spinal Cord Tumors—Our 5-Year Experience by Manpreet S. Banga, B.V. Sandeep, Anantha Kishan, M.A. Arun, Arjun H. Dev, Rajesh B. Devabhakthuni

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General, high-tech, and mid-tech regional trade introversion indexes as measures of trade integration within RTAs by Czarny Elżbieta, Folfas Paweł, Szarek-Piaskowska Aleksandra

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Differential Early Secreted Antigen Target (ESAT) 6 kDa–induced IFN-γ and SOCS1 expression distinguishes latent and active tuberculosis by Kiran Iqbal Masood, Rabia Hussain, Nisar Rao, Martin E Rottenberg, Naseem Salahuddin, Muhammad Irfan, Zahra Hasan

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Identifying Human Factors in Aviation Accidents with Natural Language Processing and Machine Learning Models by Flávio L. Lázaro, Tomás Madeira, Rui Melicio, Duarte Valério, Luís F. F. M. Santos

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Three Machine Learning Techniques for Melanoma Cancer Detection by Hadi Naghavipour, GholamReza Zandi, Abdulaziz Al-Nahari

“…After using a threshold, a binary-classified version of image was obtained, and the boundary of the lesion was determined. …”
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Mediterranean Diet and Olive Oil Redox Interactions on Lactate Dehydrogenase Mediated by Gut <i>Oscillibacter</i> in Patients with Long-COVID-19 Syndrome by Amanda Cuevas-Sierra, Victor de la O, Andrea Higuera-Gómez, Lourdes Chero-Sandoval, Begoña de Cuevillas, María Martínez-Urbistondo, Victor Moreno-Torres, Ilduara Pintos-Pascual, Raquel Castejón, J. Alfredo Martínez

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Tree-Based Algorithms and Incremental Feature Optimization for Fault Detection and Diagnosis in Photovoltaic Systems by Khaled Chahine

“…An ensemble of six tree-based classifiers, including decision trees, random forest, Stochastic Gradient Boosting, LightGBM, CatBoost, and Extra Trees, is trained in both phases. …”
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Feature engineering for fault detection and diagnosis in Power Transmission Lines using a tree-based approach by Hassan N. Noura, Zaid Allal, Ola Salman, Khaled Chahine

“…In the second phase, the ExtraTrees classifier dominated, exhibiting a 99.8% accuracy and 100% classification precision in diagnosing four of the five fault types studied. …”
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Fault Classification of 3D-Printing Operations Using Different Types of Machine and Deep Learning Techniques by Satish Kumar, Sameer Sayyad, Arunkumar Bongale

“…The collected data are used to train the machine learning (ML) and deep learning (DL) classification models to classify the variation in printing parameters. The ML models such as k-nearest neighbor (KNN), decision tree (DT), extra trees (ET), and random forest (RF) with convolutional neural network (CNN) as a DL model are used to classify the variable operation printing parameters. …”
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The implementation of take-home naloxone: Lessons learned from a 3-year take-home naloxone project in Germany by Simon Fleißner, Larissa Steimle, Dirk Schäffer, Bernd Werse, Daniel Deimel, Maria Kuban, Heino Stöver

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Area-based face curve characteristic analysis to recognize Multimodal 2D/3D monozygotic twins using Simpson’s rule and Machine Learning by Gangothri Sanil, Krishna Prakasha, Srikanth Prabhu, Vinod C. Nayak

“…To more accurately identify and analyze the facial differences and compare the twin faces, the resulting area-based score is then used as input to various machine learning algorithms such as Extreme gradient boosting (XGBoost), Adaptive Boosting (AdaBoost) classifiers, Random Forest (RF) classifiers, Light Gradient Boosting Model(LGBM), and Extra Tree Classifier(ETC) classifiers, etc. …”
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