Evaluating the impact of concurrent sucrose availability on operant ethanol self-administration in male and female Long Evans rats by Olivia A. Ortelli, Jeffrey L. Weiner

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Community-based Environmental Communication for Disaster Mitigation on Peatlands in Bengkalis Regency, Indonesia by Yasir Yasir, Ibrahim Johan Afendi, Nurjanah Nurjanah, Samsir Samsir

“…Environmental communication based on Forest Farmer Groups (KTH) contributes to reducing the risk of land fires and can improve the community’s economy. …”
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Modeling the Impacts of Boreal Deforestation on the Near-Surface Temperature in European Russia by Zhihui Li, Xiangzheng Deng, Qingling Shi, Xinli Ke, Yingcheng Liu

“…The land cover change in European Russia boreal forest region, which will be characterized by the conversion from boreal forests to croplands (boreal deforestation) in the future 100 years, will lead to significant change of the near-surface temperature. …”
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Sharing soil knowledge of the Congolese coastal plains within international research partnerships by Lydie-Stella Koutika

“…This mini-review investigates forest and agroforestry systems, focusing on soil knowledge, especially regarding the introduction of nitrogen-fixing species (NFS). …”
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Effects of Weather, Time, and Pollution Level on the Amount of Particulate Matter Deposited on Leaves of Ligustrum lucidum by Huixia Wang, Hui Shi, Yanhui Wang

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Predicting Risk through Artificial Intelligence Based on Machine Learning Algorithms: A Case of Pakistani Nonfinancial Firms by Shamsa Khalid, Muhammad Anees Khan, M.S. Mazliham, Muhammad Mansoor Alam, Nida Aman, Muhammad Tanvir Taj, Rija Zaka, Muhammad Jehangir

“…Our results prove that AI techniques can accurately predict risk with minimum error values, and among all the techniques used, the random forest technique outperforms as compared to the rest of the techniques.…”
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Leaf Area and Structural Changes after Thinning in Even-Aged Picea rubens and Abies balsamea Stands in Maine, USA by R. Justin DeRose, Robert S. Seymour

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Machine learning-based prediction of soil organic matter via smartphone by Qingying Gao, Yi Chen, Hui Zhang, Jingjing Chen, Liang Wang

“…The aim of this study is to construct models to predict SOM for a range of colors using a smartphone as an image-capturing device. Random forest of classification (RFC), random forest of logical regression (RFLR), convolutional neural network (CNN) and MobileNet models are compared, which is better for SOM prediction. …”
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Butterfly Diversity from Farmlands of Central Uganda by M. B. Théodore Munyuli

“…The highest diversity and abundance of butterflies occurred in sites that contained forest remnants. Thus, forest reserves in the surrounding of fields increased the conservation values of coffee-banana agroforestry systems for butterflies. …”
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High survival promotes bunchgrass persistence in old‐growth savannas under different fire regimes by Jennifer M. Fill, Raelene M. Crandall

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Engineering Wood Products from Eucalyptus spp. by Lee Seng Hua, Lum Wei Chen, Petar Antov, Lubos Kristak, Paridah Md Tahir

“…Forest covers 4.06 billion hectares (ha) or 31% of the total land area worldwide, where 93% (3.75 billion ha) are natural regenerating forests and the remaining 7% (294 million ha) are planted forests. …”
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Chemical properties of Terminalia catappa wood by Richmond Acheampong, Kwaku Antwi, Mark Bright Donkoh, Michael Awotwe-Mensah, Frank Kofi Dorwu

“… Ghana’s forest is fast depleting as a result of over-dependency on the traditionally known timber species and high demand for wood products for structural works. …”
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Medicinal Potential of Pine Trees: A Brief Review Focusing on Three Species by Qinsong Li, Qiyu Li, Anping Wang, Wenxuan Quan

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Limited Effect of Future Land‐Use Changes on Human Heat Stress and Labor Capacity by Steven J. DeHertog, Anton Orlov, Felix Havermann, Suqi Guo, Iris Manola, Julia Pongratz, Quentin Lejeune, Carl‐Friedrich Schleussner, Inga Menke, Florian Humpenöder, Alexander Popp, Peter Lawrence, George C. Hurtt, Louise Chini, Inne Vanderkelen, Edouard L. Davin, Thomas Reerink, Sonia I. Seneviratne, Hans Verbeeck, Wim Thiery

“…Achieving a sustainable land‐use scenario with increasing global forest cover instead of an inequality scenario with decreasing forest cover in the Global South causes a global cooling ranging between 0.09°C and 0.35°C across the Earth System Models. …”
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Predictive Laboratory Markers for Gastrointestinal Complications in Children with Henoch-Schönlein Purpura by Guo Q, Xia S, Ding Y, Liu F

“…The use of machine learning models can enhance the early identification and management of high-risk patients, potentially improving clinical outcomes.Keywords: Henoch-Schönlein Purpura, gastrointestinal complications, laboratory markers, machine learning, random forest classifier…”
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Diagnosis of Malignant Endometrial Lesions from Ultrasound Radiomics Features and Clinical Variables Using Machine Learning Methods by Shanshan Li, Jiali Wang, Li Zhou, Hui Wang, Xiangyu Wang, Jian Hu, Qingxiu Ai

“…Six common machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression, Decision Tree, Random Forest, Gradient Boosting Tree, and k-Nearest Neighbors, were employed to identify benign and malignant changes in endometrial tissue. …”
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Symptoms of dwarf elm (Ulmus pumila L.) health condition in the Left-bank Ukraine by Valentyna L. Meshkova, Olena A. Kuznetsova, Volodymyr P. Turenko

“…In June – September 2023, the health condition of Ulmus sp. was examined in forest shelterbelts along the M 03 highway, passing through the territory of Kyiv, Poltava, and Kharkiv regions. …”
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Determination of the breeding value of collection chickpea (<i>Cicer arietinum</i> L.) accessions by cluster analysis by N. A. Vus, L. N. Kobyzeva, O. N. Bezuglaya

“…Assessment of the genetic resources of chickpea (Cicer arietinum L.) in a zone that is atypical for its cultivation (eastern forest-steppe of Ukraine) gives an opportunity to identify valuable starting material for priority breeding areas. …”
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Construction and Optimization of Integrated Yield Prediction Model Based on Phenotypic Characteristics of Rice Grown in Small–Scale Plantations by Jihong Sun, Peng Tian, Zhaowen Li, Xinrui Wang, Haokai Zhang, Jiangquan Chen, Ye Qian

“…Experimental results indicate that the random forest model performs best after individual machine learning modeling, with RMSE, R², and MAPE values of 0.2777, 0.9062, and 17.04%, respectively. …”
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Comprehensive approach to predictive analysis and anomaly detection for road crash fatalities by Chopparapu Gowthami, S. Kavitha

“…These factors include weather, road features, and geographic regions. A Random Forest Regression model is trained to estimate the number of deaths arising from traffic crashes after data preprocessing, which includes feature selection and encoding. …”
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