A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…This increases the prediction accuracy by 10% and boosts the F1 score for low-yield area identification by 5%. …”
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Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models by Youzhi Lian, Yinyu Shi, Haibin Shang, Hongsheng Zhan

“…These key genes were then used to train 45 machine learning models by combining nine different algorithms: Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosting Machine, Multilayer Perceptron, Naive Bayes, and Linear Discriminant Analysis. …”
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Risk Index Model of Property and Cargo Insurance Claims Based on Precipitation in Hunan by Peng Weiying, Li Yueyong, Tan Shiqi, Li Hao, Guan Jianwen, Liao Chunhua, Zhou Wei, Xie Ruiheng

“…Such proactive measures are customized for different types of property and cargo insurance, thereby boosting the region's ability to reduce potential property and casualty insurance risks linked to precipitation events. …”
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Synergistic antimicrobial activity of essential oils mixture of Moringa oleifera, Cinnamomum verum and Nigella sativa against Staphylococcus aureus using L-optimal mixture design by Samah H. Abu-Hussien, Antony R. Nasry, Ziad Samy, Salwa M. El-Sayed, Ashraf Bakry, Naglaa Ebeed, Hesham Elhariry, Thanaa ElNoby

“…Synergistic interactions between oils further boosted efficacy, with moringa-cinnamon and cinnamon-black seed pairings exhibiting the strongest synergies. …”
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Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach by Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani

“…Machine learning classifiers, including support vector machine, random forest, adaptive boosting, and k-nearest neighbors, were trained using weak supervision and minority oversampling to handle sparse and imbalanced pain labels. …”
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Ethnobotanical studies on rice landraces under on-farm conservation in Xishuangbanna of Yunnan Province, China by Fei Wang, Tao Sun, Shuai Yu, Chunhui Liu, Zhuo Cheng, Jianxin Xia, Longzhi Han

“…The Xishuangbanna region stands out as a hub for the genetic diversity of landraces, boasting rich genetic resources. Despite the diverse rice resources in this region, a comprehensive and systematic study has not been undertaken. …”
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The impact of teacher emotional support on learning engagement among college students mediated by academic self-efficacy and academic resilience by Wenjing Guo, Juan Wang, Na Li, Luxin Wang

“…Additionally, teachers’ emotional support enhances students’ learning engagement by boosting their academic self-efficacy and reinforcing their academic resilience. …”
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Insights into a Renowned Fishery: Distinct Spatial Patterns, Environmental Predictors and Species Associations of Trophy-Class Spotted Seatrout (<i>Cynoscion nebulosus</i> [Cuvier... by Catherine Eckert, Elliot Briell, Ethan Getz

“…Kernel density distribution estimates, hot spot analyses, and space–time pattern mining methods were used to compare the distribution of the two size classes of trout spatially and temporally. Boosted regression trees (BRTs) were used to determine the environmental drivers of abundance, and multivariate analyses were utilized to compare the species associated with each size class. …”
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Meta-synthesizing of Practices of Corporate Social Responsibility: External Stake-holders Approach by Maryam Khalatbari Moazam, Hamidreza Yazdani, Naser Asgari

“…Objective In the context of today's intensely competitive environments, the ability of organizations to meet and exceed the expectations of their key stakeholders has become increasingly crucial for their survival, as well as for boosting their overall competitiveness and productivity. …”
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Human Primary Monocytes as a Model for in vitro Immunotoxicity Testing: Evaluation of the Regulatory Properties of TiO2 Nanoparticles by Svadlakova T, Kolackova M, Kulich P, Kotoucek J, Rosecka M, Krejsek J, Fiala Z, Andrýs C

“…While co-exposure of monocytes to MDP and TiO2 boosted NLRP3 activity, co-exposure to LPS and TiO2 inhibited NLRP3 by enhancing IL-10 release. …”
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Optimizing Growth and Yield in Mulched Cotton Through Aerated Subsurface Drip Irrigation in Southern Xinjiang by Yuxi Zhang, Baolin Yao, Peining Niu, Zhu Zhu, Yan Mo, Fayong Li, Sanmin Sun

“…Furthermore, aerating combined with increased irrigation quotas resulted in higher seed cotton yields, with aerated irrigation boosting yields by 1.79% in 2021 and 4.43% in 2022 compared to non-aerated irrigation. …”
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Increasing vulnerability of an endemic Mediterranean-climate conifer to changing climate and fire regime by Frank W. Davis, Anne-Marie Parkinson, Max A. Moritz, Max A. Moritz, Isaac W. Park, Carla M. D’Antonio

“…Ensembles of MAXENT and General Boosted Models were produced for a 2.1 million ha model domain encompassing BDF’s 672,000 ha range for the period 1981–2010, and were projected to 2040–2069 and 2070–2099 using three climate models (warmer-wetter, warmer, and hotter-drier) under a high emission scenario (IPCC 5th Assessment, RCP 8.5). …”
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DERECHO Y LITERATURA: HACIA LA HUMANIZACIÓN DEL DERECHO by Elvis Cotrado Cahui

“…Para tal propósito, se ha empleado el método inferencial y el método socio-jurídico con el fin de llegar a conclusiones sobre este fenómeno jurídico y concluyendo, entre otras cosas, que la tendencia romántica aporta contenido al obiter dicta de una sentencia sin perjudicar su contenido esencial, es decir, el decisum y la ratio decidendi de una sentencia. …”
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Evaluation of linear, nonlinear and ensemble machine learning models for landslide susceptibility assessment in southwest China by Bingwei Wang, Qigen Lin, Tong Jiang, Huaxiang Yin, Jian Zhou, Jinhao Sun, Dongfang Wang, Ran Dai

“…Linear models represented by logistic regression (LR), nonlinear models represented by support vector machine (SVM), artificial neural network (ANN) and classification 5.0 decision tree (C5.0 DT), and ensemble models represented by random forest (RF) and categorical boosting (Catboost) were selected. The correlation coefficient, variance inflation factor (VIF), and relative important analysis were used to select the dominate landslide conditioning factors. …”
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Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques by Mohammad Shakiul Islam, Padmanava Dash, Abduselam M. Nur, Hafez Ahmad, Rajendra M. Panda, Jessica S. Wolfe, Gray Turnage, Lee Hathcock, Gary D. Chesser, Jr, Robert J. Moorhead

“…Among the 10 ML algorithms tested, the extreme gradient boosting (XGB) algorithm demonstrated superior performance, achieving the highest R2 score of 0.848. …”
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Impact of microwave processing on phytochemicals, antioxidant status, anti-nutritional factors and metabolite profile of maize flour by Alla Yaswanth Naveen Kumar, Alonkrita Chowdhury, Rajesh Kumar, Vivek Kumar Maurya, Subhasis Batabyal, Mayukh Ghosh

“…The 600-watt, 2-minute microwave treatment was identified as optimal, boosting phytochemicals and antioxidants in maize flour while minimally impacting the main metabolite profile. …”
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Predictive modelling and identification of critical variables of mortality risk in COVID-19 patients by Olawande Daramola, Tatenda Duncan Kavu, Maritha J. Kotze, Jeanine L. Marnewick, Oluwafemi A. Sarumi, Boniface Kabaso, Thomas Moser, Karl Stroetmann, Isaac Fwemba, Fisayo Daramola, Martha Nyirenda, Susan J. van Rensburg, Peter S. Nyasulu

“…This study aimed to investigate the performance and interpretability of several ML algorithms, including deep multilayer perceptron (Deep MLP), support vector machine (SVM) and Extreme gradient boosting trees (XGBoost) for predicting COVID-19 mortality risk with an emphasis on the effect of cross-validation (CV) and principal component analysis (PCA) on the results. …”
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Immunoregulatory programs in anti‐N‐methyl‐D‐aspartate receptor encephalitis identified by single‐cell multi‐omics analysis by Xinhui Li, Yicong Xu, Weixing Zhang, Zihao Chen, Dongjie Peng, Wenxu Ren, Zhongjie Tang, Huilu Li, Jin Xu, Yaqing Shu

“…IFN‐I pathway activation in plasma cells boosts their antibody production and potentially exacerbates immune dysregulation. …”
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DNGR-1 limits Flt3L-mediated antitumor immunity by restraining tumor-infiltrating type I conventional dendritic cells by Ignacio Melero, Ruth Conde-Garrosa, David Sancho, Santos Mañes, Alfonso R Sanchez-Paulete, Francisco J Cueto, Carlos del Fresno, Paola Brandi, Alexis J. Combes, Elena Hernández-García, Michel Enamorado, Christian P Bromley, Manuel J Gomez, Santiago Zelenay, Salvador Iborra, Matthew F. Krummel

“…Mechanistically, the deficiency in DNGR-1 boosted an Flt3L-induced specific inflammatory gene signature in cDC1s, including Ccl5 expression. …”
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Microenvironmental G protein‐coupled estrogen receptor‐mediated glutamine metabolic coupling between cancer‐associated fibroblasts and triple‐negative breast cancer cells governs t... by Chongwu He, Meixi Peng, Xiaoqiang Zeng, Hanzhi Dong, Zhengkui Sun, Jiawei Xu, Manran Liu, Liyan Liu, Yanxiao Huang, Zhiqiang Peng, Yu‐An Qiu, Chunling Jiang, Bin Xu, Tenghua Yu

“…Microenvironmental GPER‐induced glutamine serves as a crucial mediator of metabolic coupling between CAFs and TNBC cells, boosting tumour progression by enhancing mitochondrial function. …”
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