Deep-Learning-Driven Insights into Nitrogen Leaching for Sustainable Land Use and Agricultural Practices by Caixia Hu, Jie Li, Yaxu Pang, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

“…A machine learning (ML) model for predicting nitrate leaching was then developed, with the random forest (RF) model outperforming the support vector machine (SVM), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) models, achieving an R² of 0.75. …”
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Bioâdigestion and postâtreatment of effluents by bioâfermentation, an opportunity for energy uses and generation of organic fertilizers from bovine manure... by Luis Antonio Barzallo-Bravo, David Carrera-Villacrés, Rafael Eduardo Vargas-Verdesoto, Lourdes Karina Ponce-Loaiza, Modesto Correoso, Ãlvaro Petronio Gavilanes-Quishpi

“…The project was located at the tropical zone into the Choco forest, at an average altitude of 1110 m above sea level and an average temperature annual of 21â22 °C.…”
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Genetic methods in honey bee breeding by M. D. Kaskinova, A. M. Salikhova, L. R. Gaifullina, E. S. Saltykova

“…A method based on the analysis of polymorphisms of the tRNAleu-COII locus and microsatellite nuclear DNA loci has been developed to identify the dark forest bee A. m. mellifera and does not allow one to differentiate subspecies from C (A. m. carnica and A. m. ligustica) and O (A. m. caucasica) evolutionary lineages from each other. …”
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The Efficacy of Lubiprostone in Patients of Constipation: An Updated Systematic Review and Meta‐Analysis by Umar Akram, Obaid Ur Rehman, Eeshal Fatima, Zain Ali Nadeem, Omer Usman, Waqas Rasheed, Ramsha Ali, Khawaja Abdul Rehman, Abdulqadir J. Nashwan

“…A meta‐analysis was performed and findings were presented using forest plots. Results A total of 14 studies, comprising 4550 patients, were included in the review. …”
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Application of multi-indexing approach within a GIS framework to investigate the quality and contamination of ground water in Barisal sadar, Bangladesh by Md. Numan Hossain, M. Farhad Howladar, Sohag Ahammed, Md Rezwanul Haque, Majedul Islam Khan, Muyeed Hasan, Tayabur Rashid Chowdhury, Alamgir Hosain

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Study on influencing factors of age-adjusted Charlson comorbidity index in patients with Alzheimer's disease based on machine learning model by Jian Ding, Jian Ding, Zheng Long, Yiming Liu, Min Wang

“…Multiple logistic regression, LASSO regression, random forest, Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) models were used to screen for feature factors significantly correlated with aCCI. …”
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A pipeline for processing hyperspectral images, with a case of melanin-containing barley grains as an example by I. D. Busov, M. A. Genaev, E. G. Komyshev, V. S. Koval, T. E. Zykova, A. Y. Glagoleva, D. A. Afonnikov

“…The current version of the package implements the following methods: construction of a confidence interval of an arbitrary level for the difference of sample averages; verification of the similarity of intensity distributions of spectral lines for two sets of hyperspectral images on the basis of the Mann–Whitney U-criterion and Pearson’s criterion of agreement; visualization in two-dimensional space using dimensionality reduction methods PCA, ISOMAP and UMAP; classification using linear or ridge regression, random forest and catboost; clustering of samples using the EM-algorithm. …”
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Physical Activity, Obesity, and Hypertension among Adults in a Rapidly Urbanised City by Qianqian Dun, Wanglin Xu, Maozhen Fu, Nengjian Wu, Justin B. Moore, Ting Yu, Xin Li, Yating Du, Biao Zhang, Qiaomai Wang, Yiting Duan, Ziqi Meng, Shuangshuang Tian, Yuliang Zou

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Evaluation of synthetic wheat lines (Triticum durum/Aegilops tausсhii) for vegetative period and resistance to diseases by V. P. Shamanin, I. V. Pototskaya, S. S. Shepelev, V. E. Pozherukova, A. Yu. Truschenko, A. S. Chursin, A. I. Morgunov

“…Research was performed on the experimental field of Omsk SAU under conditions of southern forest-steppe of West Siberia in 2016. Between synthetics, there was revealed a genotypic difference in the vegetative period duration and resistance to diseases. …”
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Resource availability and competition shape pollinator trophic specialization in longleaf pine savannas by Pablo Moreno-García, Johanna E. Freeman, Benjamin Baiser, Joshua W. Campbell, Daijiang Li

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Meta-analysis of nifedipine and enalapril combination therapy for hypertensive patients with coronary heart disease: A systematic review and meta-analysis by Kun Wang, Wenchao Ma, Leina Sun, Fangcheng Su

“…Heterogeneity in the studies was evaluated based on the results of the Q test (P value), and the OR value of the combined effect was calculated using either the model with fixed effects or the one with random effects, with the results presented in a forest plot. Furthermore, a sensitivity analysis was conducted by excluding articles with the highest impact, and potential bias in publication was assessed through the utilization of a funnel plot. …”
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Exploring the significance of medical humanities in shaping internship performance: insights from curriculum categories by Chao Ting Chen, Anna Y.Q. Huang, Po-Hsun Hou, Ji-Yang Lin, His-Han Chen, Shiau-Shian Huang, Stephen J. H. Yang

“…Ten-fold cross-validation machine learning models (support vector machines, logistic regression, random forest) were performed to predict the internship grades. …”
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Machine learning based predictive model and genetic mutation landscape for high-grade colorectal neuroendocrine carcinoma: a SEER database analysis with external validation by Ruixin Wu, Ruixin Wu, Sihao Chen, Sihao Chen, Yi He, Yi He, Ya Li, Song Mu, Aishun Jin, Aishun Jin

“…Independent factors influencing both overall survival (OS) and cancer-specific survival (CSS) were identified using LASSO, Random Forest, and XGBoost regression techniques. Molecular data with the most common mutations in CNEC were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database.ResultsIn this prognostic analysis, the data from 714 participants with HCNEC were evaluated. …”
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Chemical Composition, Antioxidant Potential, and Antibacterial Activity of Essential Oil Cones of Tunisian Cupressus sempervirens by Aicha Ben Nouri, Wissal Dhifi, Sana Bellili, Hanene Ghazghazi, Chedia Aouadhi, Ameur Chérif, Mohamed Hammami, Wissem Mnif

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Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases by Yuji Miyamoto, Takeshi Nakaura, Mayuko Ohuchi, Katsuhiro Ogawa, Rikako Kato, Yuto Maeda, Kojiro Eto, Masaaki Iwatsuki, Yoshifumi Baba, Toshinori Hirai, Hideo Baba

“…Treatment response was classified as responder (complete or partial response) or non-responder (stable or progressive disease), based on the best overall response according to RECIST criteria, version 1.1. Employing Random Forest and Boruta algorithms, we identified significant features for responder-non-responder differentiation. …”
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Chemical Fingerprint Analysis for Discovering Markers and Identifying Saussurea involucrata by HPLC Coupled with OPLS-DA by Qingdong Ma, Xiaoxiang Chen, Ke Zhang, Dahong Yao, Lu Yang, Hangyu Wang, Santai Bulemasi, Jian Huang, Jinhui Wang

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Design a Robust DDoS Attack Detection and Mitigation Scheme in SDN-Edge-IoT by Leveraging Machine Learning by Habtamu Molla Belachew, Mulatu Yirga Beyene, Abinet Bizuayehu Desta, Behaylu Tadele Alemu, Salahadin Seid Musa, Alemu Jorgi Muhammed

“…We evaluated four popular classifiers (K-Nearest Neighbor (K-NN), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and FeedForward Neural Network (FFNN)) on benchmark datasets CICIDS2017 and Edge-IIoTset, conducting both binary and multi-class classifications. …”
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Sub-seasonal Patterns of PM10 and Black Carbon in a Coastal City: A Case Study of Salé, Morocco by Anas Otmani, Abdeslam Lachhab, Abdelfettah Benchrif, Mounia Tahri, Mohamed Azougagh, Mohammed El Bouch, El Mahjoub Chakir

“…The study centered on the repercussions of fossil fuel combustion (BCFF specifically, emissions from traffic) and biomass burning (BCBB Consisting of forest fires and agricultural burning) on BC2.5 levels. …”
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Estimation of daily groundwater evapotranspiration from diurnal variations of lysimeter experiments data in an arid zone by Peng Yao, Fengzhi Shi, Yuehui Wang, Ningze Dai, Chengyi Zhao

“…Principal component analysis and a random forest model were used to assess meteorological influences. …”
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Validation of In-field Calibration for Low-Cost Sensors Measuring Ambient Particulate Matter in Kolkata, India by Siddharth Nobell, Arnab Majumdar, Shovon Mukherjee, Sukumar Chakraborty, Sanjoy Chatterjee, Soumitra Bose, Anindita Dutta, Sandhya Sethuraman, Daniel M. Westervelt, Shairik Sengupta, Rakhi Basu, V. Faye McNeill

“…Data from the co-locations were used to calibrate the LCS network using random forest regression and multiple linear regression approaches. …”
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