Phage therapy in antibiotic resistant pneumonia: immunomodulation or redistribution? by S. S. Bochkareva, I. M. Fedorova, O. N. Ershova, S. I. Koteleva, I. V. Kapustin, M. S. Blyakher, L. I. Novikova, A. V. Aleshkin, А. М. Vorobev

“…Statistical processing of the results was carried out using the Statistica 6 program according to the nonparametric Mann-Whitney U-test. …”
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Inventory of Galilean Transformation of uniform linear motion in position-time graphs by E. B. Merki, S. I. Hofer, A. Vaterlaus, A. Lichtenberger

“…Moreover, existing tests that explore differences in reference frame typically focus on the equivalence principle through written answers, interviews, or simple calculations and vector addition; however, none of these tests evaluate position-time graphs. …”
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ExAutoGP: Enhancing Genomic Prediction Stability and Interpretability with Automated Machine Learning and SHAP by Yao Rao, Lilian Zhang, Lutao Gao, Shuran Wang, Linnan Yang

“…For each dataset, we applied ExAutoGP and five baseline models—Genomic Best Linear Unbiased Prediction (GBLUP), BayesB, Support Vector Regression (SVR), Kernel Ridge Regression (KRR), and Random Forest (RF). …”
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Prediction Model for the Chloride Ion Permeability Resistance of Recycled Aggregate Concrete Based on Machine Learning by Pengfei Gao, Yuanyuan Song, Jian Wang, Zhiyong Yang, Kai Wang, Yongyu Yuan

“…Based on the experimental data, four algorithms, including artificial neural network (ANN), support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBoost), were adopted to establish the machine learning prediction models and study the relationships between the electric flux of RAC and the IFs. …”
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Machine learning with label-free Raman microscopy to investigate ferroptosis in comparison with apoptosis and necroptosis by Joost Verduijn, Eva Degroote, André G. Skirtach

“…Abstract Human and animal health rely on balancing cell division and cell death to maintain normal homeostasis. This process is accomplished by regulated cell death (RCD), whose imbalance can lead to disease. …”
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The role of cytokines in the pathogenesis of infectious complications in surgical treatment of obstructive jaundice of gallstone origin by O. V. Smirnova, N. G. Elmanova

“…In the pathogenesis of obstructive jaundice, a local inflammatory process plays an essential role. This is confirmed by statistically significant changes in the studied cytokines. …”
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Body surface gastric mapping to determine gastric motility patterns associated with delayed gastric emptying after pancreaticoduodenectomy. Gastric Electric Mapping after Pancreato... by Mike Jones, Sanjay Pandanaboyana, Keno Mentor, Jade Lembo, Samantha Carswell

“…Key parameters of BSGM measurement, including wave amplitude, frequency and directional vector, will be measured at each timepoint and compared between different patient subgroups. …”
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Sentiment Analysis of Product Reviews Using Machine Learning and Pre-Trained LLM by Pawanjit Singh Ghatora, Seyed Ebrahim Hosseini, Shahbaz Pervez, Muhammad Javed Iqbal, Nabil Shaukat

“…., Random Forest, Naive Bayes, and Support Vector Machine, alongside the GPT-4 model to benchmark their effectiveness for sentiment analysis. …”
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AI‐Based Digital Rocks Augmentation and Assessment Metrics by Lei Liu, Bernard Chang, Maša Prodanović, Michael J. Pyrcz

“…Compared to most traditional dimensionality reduction methods that process images into a flattened vector, we propose topological image analysis for dimensionality reduction while preserving the essential geometric and topological features of the high‐dimensional data. …”
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A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…For estimating SoH, prevalent data-driven techniques include support vector regression (SVR) and Gaussian process regression (GPR), alongside hybrid models merging machine learning with conventional estimation techniques to heighten predictive accuracy. …”
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Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…As expected, the results showed rather poor values of the coefficient of determination (R2) of the artificial neural network (ANN), support vector machine (SVM), and random forest (RF) with pre-adjusted values for their hyperparameters. …”
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Positive effects of bFGF modified rat amniotic epithelial cells transplantation on transected rat optic nerve. by Jia-Xin Xie, Yu Feng, Jian-Min Yuan, Zhen-Dong You, Hai-Yan Lin, Chang-Lin Lu, Jia-Jun Xu

“…<h4>Methods</h4>A human bFGF gene segment was delivered into rat AECs (AECs/hbFGF) by lentiviral vector, and the gene expression was examined by RT-PCR and ELISA. …”
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The role of the Republic of Kazakhstan in geopolitical transformation in the framework of the «Eurasian project» by M. M. Nurtazin

“…The Russian example shows that Moscow’s foreign policy vector was initially perceived by the EEU as a global project connecting Europe with the Asia-Pacific region. …”
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4 Pattern Recognition for Healing Burns to Compute Evidence: Space Syntax and Machine Learning Analysis of Burns Center Karachi by Javaria Manzoor Shaikh, JaeSeung Park

“…Our findings support the hypothesis that the windowed wall is most healing wall, here fundamental suggestion is support vector machines: which is most advantageous hyper plane for linearly divisible patterns for the burns depth as well as the depth map is used. …”
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19~21 GHz GaAs high linearity power amplifier MMIC by Liu Xiaoyu, Han Chenghao, Ruan Wenwu, Guo Runnan, Liu Ling, Xu Xindong, Hou Zewen, Zhuang Yuan, Yu Xuming, Tao Hongqi

“…For a 64-QAM orthogonal frequency division multiplexing signal with 6 dB peak-to-average power ratio and 100 MHz bandwidth，the PA exhibits an adjacent channel power ratio of -31.9 dBc、-33.2 dBc and -31.2 dBc when the error vector magnitude are 4.32%、4.13% and 5.3%.…”
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Machine learning and microfluidic integration for oocyte quality prediction by Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi

“…Supervised learning models (Random Forest, Decision Tree, K-Nearest Neighbors, eXtreme Gradient Boosting, Logistic Regression, Naive Bayes, Support Vector Machines, and Light Gradient Boosting Machine were evaluated. …”
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Estimated ultimate recovery prediction of shale gas wells based on stacked integrated learning algorithm by Min Pang, Zheyuan Zhang, Zhaoming Zhou, Wendi Zhou, Qiong Li

“…The method employs Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) as base learners, with Logistic Regression (LR) as the meta-learner. …”
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Pesticide Residue Detection in Broccoli Based on Hyperspectral Technology and Convolutional Neural Network by Dan WANG, Yuqing LUAN, Zuojun TAN, Wei WEI

“…The results indicated that the combination of hyperspectral imaging technology and deep learning algorithms as 1D-CNN not only simplified the recognition process of pesticide residues in broccoli, but also improved recognition efficiency and accuracy.…”
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NNG-Based Secure Approximate k-Nearest Neighbor Query for Large Language Models by Heng Zhou, Yuchao Wang, Yi Qiao, Jin Huang

“…Furthermore, we construct a secure index table that enables complete candidate set retrieval through a single query, ensuring our solution completes the search process in one interaction while minimizing communication costs. …”
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Infrared Small Target Detection Using Directional Derivative Correlation Filtering and a Relative Intensity Contrast Measure by Feng Xie, Dongsheng Yang, Yao Yang, Tao Wang, Kai Zhang

“…This approach involves converting the original infrared image into an infrared gradient vector field (IGVF) using a facet model. Exploiting the distinctive characteristics of small targets in second-order derivative computations, four directional filters are designed to emphasize target features while suppressing edge clutter. …”
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