A Next-generation Exoplanet Atmospheric Retrieval Framework for Transmission Spectroscopy (NEXOTRANS): Comparative Characterization for WASP-39 b Using JWST NIRISS, NIRSpec PRISM,... by Tonmoy Deka, Tasneem Basra Khan, Swastik Dewan, Priyankush Ghosh, Debayan Das, Liton Majumdar

“…We present NEXOTRANS , an atmospheric retrieval framework that integrates Bayesian inference using UltraNest / PyMultiNest with four machine learning algorithms: Random Forest , Gradient Boosting , K-Nearest Neighbor , and Stacking Regressor . …”
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STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG by Raquel Fernández-Martín, Alfonso Gijón, Odile Feys, Elodie Juvené, Alec Aeby, Charline Urbain, Xavier De Tiège, Vincent Wens

“…Clinical MEG analysis in epileptic patients traditionally relies on the visual identification of IEDs, which is time consuming and partially subjective. Automatic, data-driven detection methods exist but show limited performance. …”
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Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned by Marketa Ciharova, Khadicha Amarti, Ward van Breda, Ward van Breda, Martin J. Gevonden, Sina Ghassemi, Annet Kleiboer, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Sophia Trofimova, Alexander C. Cooper, Xianhua Peng, Xianhua Peng, Mieke Schulte, Mieke Schulte, Eirini Karyotaki, Eirini Karyotaki, Eirini Karyotaki, Pim Cuijpers, Pim Cuijpers, Pim Cuijpers, Heleen Riper, Heleen Riper

“…We aimed to detect laboratory-induced stress using multimodal data and identify challenges researchers may encounter when conducting a similar study.MethodsWe conducted a preliminary exploration of performance of a machine-learning algorithm trained on multimodal data, namely visual, acoustic, verbal, and physiological features, in its ability to detect stress severity following a partially automated online version of the Trier Social Stress Test. …”
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Cardiac Magnetic Resonance Imaging with Myocardial Strain Assessment Correlates with Cardiopulmonary Exercise Testing in Patients with Pectus Excavatum by André Lollert, Tariq Abu-Tair, Tilman Emrich, Karl-Friedrich Kreitner, Alexander Sterlin, Christoph Kampmann, Gundula Staatz

“…In addition to cardiac volumetry, we assessed the strain rates of both ventricles using a feature-tracking algorithm of a piece of commercially available post-processing software. …”
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Bioinformatics analysis and experimental studies reveal KPNA2 as a novel biomarker of hepatocellular carcinoma progression and telomere maintenance by Ke Ding, Lei Liu, Wang Yong, Beicheng Sun, Wenjie Zhang

“…Telomerase inhibition partially alleviated the inhibitory effect of KPNA2 overexpression on cell proliferation and migration. …”
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Research on short-term power load forecasting based on deep reinforcement learning with multiple intelligences by Tianyun Luo, Dunlin Zhu, Jinming Liu, Sheng Yang, Jinglong He, Yuan Fu

“…In this paper, we analyze the multi-intelligence application architecture in power load forecasting, and analyze the function of each intelligent unit applied to short-term power load forecasting; based on clarifying the interaction relationship of each intelligent unit in short-term power load forecasting, we model short-term power load forecasting as a distributed and partially observable Markov decision-making process, which is suitable for multi-intelligence deep reinforcement learning; based on the MATD3 algorithm, a centralized training-distributed execution framework is used to train multiple intelligences within the model to achieve short-term power load forecasting. …”
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The risk factors of cardiovascular disorders in children with chronic bronchopulmonary diseases by O. Ye. Pashkova, G. O. Lezhenko

“…We examined 144 patients aged 3–16 years (mean age was 11.3 ± 1.2 years) with chronic bronchopulmonary pathology (60 patients with cystic fibrosis with pancreatic insufficiency and 84 patients with heavily treated or partially treated persistent bronchial asthma) and 68 conditionally healthy children who made up the control group. …”
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Optimization of treatment for patients with combined unstable pelvic and thoracic injuries by О.А. Бур’янов, В.П. Кваша, В.М. Дьомін, Д.В. Мясніков, В.М. Лянскорунський

“…For type B pelvic injuries, which are characterized by anterior, rotational and partially posterior instability, stabilization of the anterior part is sufficient. …”
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Low-Carbon Slag Concrete Design Optimization Method Considering the Coupled Effects of Formwork Stripping, Strength Progress, and Carbonation Durability by Li-Na Zhang, Seung-Jun Kwon, Xiao-Yong Wang

“…Partially substituting cement with slag is an efficient approach to lowering the carbon footprint of concrete. …”
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Submeridional boundary zone in Asia: seismicity, lithosphere structure, and the distribution of convective flows in the upper mantle by N. A. Bushenkova, O. A. Kuchay, V. V. Chervov

“…A similar approach was applied in [Koulakov, Bushenkova, 2010 for the territory of Siberia; however, that model only partially covered the submeridional transregional boundary zone and was based on fewer ISC data (until 2001). …”
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Results of parallel independent visual evaluation of projective cover of the bottom during macrophyte assesment survey by A. A. Dulenin

“…For successful implementation of visual surveys, its algorithm for various environmental conditions is developed and supplemented with necessary instructions.…”
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Integrative single-cell and metagenomic analysis dissects SARS-CoV-2 shedding modes in human respiratory tract by Xiangxing Jin, Lili Ren, Xianwen Ren, Jianwei Wang

“…In this study, we integrated published human metagenomic data of SARS-CoV-2 and developed a novel algorithm named RedeCoronaVS to systematically dissect SARS-CoV-2 shedding modes with single-cell data as reference. …”
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Prediction of canopy mean traits in herbaceous plants by the UAV multispectral data: The quest for a better leaf-to-canopy upscaling method by Yuanqi Shan, Yunlong Yao, Lei Wang, Zhihui Wang, Huaihu Yi, Yi Fu, Weineng Li, Xuguang Zhang, Wenji Wang, Zhongwei Jing

“…This study proposed a novel approach for calculating canopy mean traits using the geometric mean method and compared its performance to that of the CWM methods in combination with three modeling algorithms Partial Least Squares Regression (PLSR), Random Forest regression (RF), and Support Vector Machine regression (SVM). …”
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Association between age and lung cancer risk: evidence from lung lobar radiomics by Yuwei Li, Chengting Lin, Lei Cui, Chao Huang, Liting Shi, Shiyang Huang, Yue Yu, Xianglan Zhou, Qian Zhou, Kun Chen, Lei Shi

“…The minimum redundancy maximum relevance algorithm was applied to identify the top 10 age-related radiomic features among 13,137 never smokers. …”
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Data-driven thrust prediction in applied-field magnetoplasmadynamic thrusters for space missions using artificial intelligence-based models by Tarik Pinaffo Almeida, Shahin Alipour Bonab, Mohammad Yazdani-Asrami

“…As an alternative to analytical/empirical formulas that approximate the true physics only partially, this paper demonstrates the potential of artificial intelligence (AI) techniques to predict thrust in AF-MPDTs. …”
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Predicting reticuloruminal pH and subacute ruminal acidosis of individual cows using machine learning and Fourier-transform infrared spectroscopy milk analysis by T. Touil, F. Huot, S. Claveau, A. Bunel, D. Warner, D.E. Santschi, R. Gervais, É.R. Paquet

“…Additionally, different ML algorithms, including partial least squares, random forest, and gradient boosting, were used to predict rpH and SARA. …”
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A systematic review of Leptospira in water and soil environments. by Emilie Bierque, Roman Thibeaux, Dominique Girault, Marie-Estelle Soupé-Gilbert, Cyrille Goarant

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Interaction between the assembly of the ribosomal subunits: Disruption of 40S ribosomal assembly causes accumulation of extra-ribosomal 60S ribosomal protein uL18/L5. by Nusrat Rahman, Md Shamsuzzaman, Lasse Lindahl

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Predicting regional tau accumulation with machine learning‐based tau‐PET and advanced radiomics by Saima Rathore, Ixavier A. Higgins, Jian Wang, Ian A. Kennedy, Leonardo Iaccarino, Samantha C. Burnham, Michael J. Pontecorvo, Sergey Shcherbinin

“…Abstract INTRODUCTION Alzheimer's disease is partially characterized by the progressive accumulation of aggregated tau‐containing neurofibrillary tangles. …”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…As many as 12 machine learning (ML) algorithms, namely, logistic regression (LR), decision tree (DT), random forest (RF), gradient boosting (GB), AdaBoost, XGBoost, Naive Bayes (NB), support vector machine (SVM), light gradient-boosting machine (LightGBM), K-nearest neighbors (KNN), extremely randomized trees (ET), and voting classifier (VC), were performed. …”
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