River-groundwater transformation and ecological effects in the Tuwei River watershed by Jinxuan WANG, Yi WANG, Fan GAO, Xuanming ZHANG, Zhitong MA, Fan YANG

“…Under the control of geological and geomorphological conditions and the three-water transformation, the watershed can be spatially divided into lakes-shrub-grass-tree wet environment ecosystem, grass-shrub-tree-sand dry environment ecosystem, dwarf sparse forest-grass dry environment ecosystem, farmland-tree wet environment ecosystem, and riparian wet environment ecosystem. …”
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Rainwater harvesting in arid and semi-arid lands of Africa: challenges and opportunities by Etienne Umukiza, Romain Ntole, Sylvester R. Chikavumbwa, Erion Bwambale, Davis Sibale, Zechariah Jeremaih, Ciro Apollonio, Andrea Petroselli

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Widely Targeted Metabolomics Analysis Reveals Key Quality-Related Metabolites in Kernels of Sweet Corn by Ruichun Yang, Yunfeng Li, Yuanyuan Zhang, Jun Huang, Junjie Liu, Zimei Lin, Qinqin Yu, Aimin Wu, Bo Wang

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Risk of myocardial infarction and heart failure in gout patients: a systematic review and meta-analysis by Panpan Wang, Huanhuan Yang

“…Relevant data were extracted from the final screened literature, and a forest map was drawn using RevMan 5.3 software for meta-analysis. …”
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Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

“…Leveraging the Coxboost and random survival forest combination algorithm, we filtered out six DC-related genes on which a prognostic prediction model, DCRGS, was established. …”
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Role of Aging in Ulcerative Colitis Pathogenesis: A Focus on ETS1 as a Promising Biomarker by Ni M, Peng W, Wang X, Li J

“…Next, core module genes were screened using WGCNA and then the hub genes were characterized using LASSO and random forest methods. Besides, the associations between hub genes, immune cells, and key pathways were explored. …”
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Boron adsorption in semiarid Mediterranean soils under the influence of background electrolytes by S. Fatnassi, M.B. Almendro Candel, J. Navarro Pedreño, I. Gómez Lucas, M. Hachicha

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Pooled prevalence and associated factors of traditional uvulectom among children in Africa: A systematic review and meta-analysis. by Solomon Demis Kebede, Kindu Agmas, Demewoz Kefale, Amare Kassaw, Tigabu Munye Aytenew

“…Heterogeneity among the included studies was assessed using a forest plot, I2 statistics, and Egger's test, ensuring the robustness and reliability of the findings. …”
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The Status of Wild Grapevine (<i>Vitis vinifera</i> L. subsp. <i>sylvestris</i> (C.C. Gmel.) Hegi) Populations in Georgia (South Caucasus) by Gabriele Cola, Gabriella De Lorenzis, Osvaldo Failla, Nikoloz Kvaliashvili, Shengeli Kikilashvili, Maia Kikvadze, Londa Mamasakhlisashvili, Irma Mdinaradze, Ramaz Chipashvili, David Maghradze

“…Their main natural vegetations are forests and open woodlands, with some individuals in the Southeast found in steppes. …”
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Applying the Dempster–Shafer Fusion Theory to Combine Independent Land-Use Maps: A Case Study on the Mapping of Oil Palm Plantations in Sumatra, Indonesia by Carl Bethuel, Damien Arvor, Thomas Corpetti, Julia Hélie, Adrià Descals, David Gaveau, Cécile Chéron-Bessou, Jérémie Gignoux, Samuel Corgne

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EVALUATION OF THE ADAPTIVE PROPERTIES OF SPRING BARLEY VARIETIES ACCORDING TO THEIR YIELD CAPACITY IN THE ENVIRONMENTS OF THE NEAR-IRTYSH AREA IN OMSK PROVINCE by P. N. Nikolaev, P. V. Popolzukhin, N. I. Anisimov, O. A. Yusova, I. V. Safonova

“…The experimental part of the work was  carried out during 2011-2017, on the experimental fields of the  Siberian Research Institute of Agriculture, RAAS, located in the  southern forest-steppe in the vicinity of Omsk. The plot area was 10  m2, with 4 repetitions. …”
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Impacto sobre el cambio climático del ciclo de vida de las tarimas de madera elaboradas en la región Huetar Norte de Costa Rica by John Solano Salmerón, William Fonseca González, Sebastián Ugalde Alfaro, Federico Alice Guier

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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study by Yunzhen Ye, Yu Xiong, Qiongjie Zhou, Jiangnan Wu, Xiaotian Li, Xirong Xiao

“…Eight common machine learning methods (GDBT, AdaBoost, LGB, Logistic, Vote, XGB, Decision Tree, and Random Forest) and two common regressions (stepwise logistic regression and logistic regression with RCS) were implemented to predict the occurrence of GDM. …”
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The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review by Ricardo Smits Serena, Florian Hinterwimmer, Rainer Burgkart, Rudiger von Eisenhart-Rothe, Daniel Rueckert

“…Furthermore, our analysis reveals the current dominance of machine learning models in 76% on the surveyed studies, suggesting a preference for traditional models like linear regression, support vector machine, and random forest, but also indicating significant growth potential for deep learning models in this area. …”
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Impact of #PCOSweightloss: A global X hashtag analysis study of weight loss narratives in the PCOS community by Munaza Afaq, Kumar Vashisht, Areen Al-Dhoon, Divya Abraham, Atanas G. Atanasov, Maima Matin, Zara Arshad, Rahul Kashyap, Faisal A. Nawaz

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To Develop Biomarkers for Diabetic Nephropathy Based on Genes Related to Fibrosis and Propionate Metabolism and Their Functional Validation by Sha Li, Jingshan Chen, Wenjing Zhou, Yonglan Liu, Di Zhang, Qian Yang, Yuerong Feng, Chunli Cha, Li Li, Guoyong He, Jun Li

“…Second, the intersection of DN-DEGs, PM-DEGs, and FRGs was taken to yield intersected genes. Random forest (RF) and recursive feature elimination (RFE) analyses of the intersected genes were performed to sift out biomarkers. …”
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Specific shoot formation in Miscanthus sacchariflorus (Poaceae) under different environmental factors and DNA passportization using ISSR markers by O. V. Dorogina, N. S. Nuzhdina, G. A. Zueva, Yu. A. Gismatulina, O. Yu. Vasilyeva

“…., which has good prospects for growing under the conditions of the forest-steppe area in Western Siberia. The goals of our study were: (1) to determine the peculiarities of shoot formation, (2) to assess the cellulose and lignin accumulation in M. sacchariflorus populations under different lighting conditions and (3) to perform a DNA passportization of the Miscanthus population by ISSR marking. …”
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The probability of detecting host-specific microbial source tracking markers in surface waters was strongly associated with method and season by Claire M. Murphy, Daniel L. Weller, Tanzy M. T. Love, Michelle D. Danyluk, Laura K. Strawn

“…Variance partitioning analysis was used to quantify the variance in host-specific MST marker detection attributable to non-methodological and methodological factors. Conditional forest and regression analysis were utilized to assess the association between detection and select non-methodological and methodological factors. …”
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Variabilidad intraespecífica en la calidad de semillas de especies forestales nativas en bosques montanos en el sur del Ecuador: Implicaciones para la restauración de bosques... by Ximena Palomeque, Andrea Maza, Juan Pablo Iñamagua, Sven Günter, Patrick Hildebrandt, Michael Weber, Bernd Stimm

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Construction of a prognostic prediction model for colorectal cancer based on 5-year clinical follow-up data by Boao Xiao, Min Yang, Yao Meng, Weimin Wang, Yuan Chen, Chenglong Yu, Longlong Bai, Lishun Xiao, Yansu Chen

“…Decision tree, random forest, support vector machine, and extreme gradient boosting (XGBoost) models were selected for modeling based on the features identified through recursive feature elimination (RFE). …”
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