Impacts of Land Use and Land Cover Change on Soil Erosion and Hydrological Responses in Ethiopia by Ajanaw Negese

“…From the past researches reviewed in this paper, the expansion of cultivated land at the expense of forest land, shrubland, and grassland in Ethiopia has increased the mean rate of soil erosion, sediment yield, surface runoff, mean wet monthly flow, and mean annual stream flow in the last four decades. …”
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Risk Assessment of Biological Asset Mortgage Loans of China’s New Agricultural Business Entities by Shuzhen Zhu, Yutao Chen, Wenwen Wang

“…Based on 1249 production and operation data samples of new agricultural entities in Zhejiang, Henan, and Shandong provinces, this study constructs an XGBoost model for empirical analysis and compares it with logical regression, support vector machine, and random forest algorithms to obtain the optimal model and feature importance value. …”
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Le régime alimentaire des Gorilles de plaine de l’Est, Gorilla beringei graueri et la pharmacopée humaine : Alimentation ou automédication ? by Dalley-Divin Kambale Saa-Sita, Shelly Masi, Aimée Lorela Katungu Sawa-Sawa, Jean-Claude Kyungu Kasolene, Jean Malekani Mukulire

“…Given both the phylogenetic proximity of great apes and humans and the small proportion of wild plant species known by humans in the tropical forest, the observation of the diet of a species of great apes still very less known, such as the gorillas of the East, could lead to the discovery of new plants that may be useful for human health.…”
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School Gardens in Poland – Rediscovered Places by Joanna Ziemkowska

“…Vogt-Kostecka notes that the fear of dirt, wind and ticks limits children's free play in a meadow and in a forest. Limited access to nature is particularly visible among urban children (Vogt-Kostecka 2017, 11). …”
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Mathematical and computational modeling for organic and insect frass fertilizer production: A systematic review. by Malontema Katchali, Edward Richard, Henri E Z Tonnang, Chrysantus M Tanga, Dennis Beesigamukama, Kennedy Senagi

“…Mathematical models such as simulation, regression, dynamics, and kinetics have been applied while computational data driven machine learning models such as random forest, support vector machines, gradient boosting, and artificial neural networks have also been applied as well. …”
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Under the bridge: marking sites prove the presence of Eurasian otter Lutra lutra in the Poljanska Sora River valley, Slovenia by Rudi Kraševec, Aleksander Trajbarič, Urša Fležar

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Humus and Humic Acids of Luvisol and Cambisol of Jiguli Ridges, Samara Region, Russia by Evgeny Abakumov, Nobihudu Fujitake, Takashi Kosaki

“…Essential differences in humus composition and humic acids properties confirm that local humid climate in continental forest-steppe leads to formation of Cambisols instead of zonal Luvisols.…”
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Morphological Variation and Ecological Structure of Iroko (Milicia excelsa Welw. C.C. Berg) Populations across Different Biogeographical Zones in Benin by Christine Ouinsavi, Nestor Sokpon

“…Apart from strong climate oscillation during the Pleistocene, human caused habitat fragmentation through continuous land clearing for agriculture, extensive forests exploitation and urbanization induced the occurrence of many isolated forest plots and trees species among which Milicia excelsa trees. …”
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Glena bipennaria bipennaria and Apatelodes pandara (Lepidoptera): new defoliating insects associated with Khaya in Brazil by Luana de Souza Covre, Robert A. Haack, Carlos Alberto Hector Flechtmann

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A Revisit to the Impacts of Land Use Changes on the Human Wellbeing via Altering the Ecosystem Provisioning Services by Xiangzheng Deng, Zhihui Li, Jikun Huang, Qingling Shi, Yanfei Li

“…First, the explorations on the influences of LUC on ecosystem provisioning services were reviewed, including the researches on the influences of LUC on agroecosystem services and forest and/or grassland ecosystem services. Then the quantitative identification of the impacts of LUC on ecosystem provisioning services was commented on. …”
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AutoPVPrimer: A comprehensive AI-Enhanced pipeline for efficient plant virus primer design and assessment. by Abozar Ghorbani, Mahsa Rostami, Elham Ashrafi-Dehkordi, Pietro Hiram Guzzi

“…The design_primers_with_tuning module uses a random forest classifier that optimizes parameters and provides flexibility for different experimental conditions. …”
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Merging Nitrogen Management and Renewable Energy Needs by Elizabeth Wilson, Pippa J. Chapman, Adrian McDonald

“…The plant is fueled by a mix of wood from short rotation coppice (SRC) and forest residues. Where feasible, composted/conditioned sewage sludge is applied to coppice sites to increase yields and improve soil structure. …”
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A hybrid machine learning model for intrusion detection in wireless sensor networks leveraging data balancing and dimensionality reduction by Md. Alamin Talukder, Majdi Khalid, Nasrin Sultana

“…The model employs classifiers such as Decision Tree Classifier, Random Forest Classifier (RFC), and gradient boosting techniques like XGBoost (XGBC) to enhance detection accuracy and efficiency. …”
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An eastern Congolian endemic, or widespread but secretive? New data on the recently described Afrixalus lacustris (Anura, Hyperoliidae) from the Democratic Republic of the Congo by Tadeáš Nečas, Gabriel Badjedjea, Janis Czurda, Václav Gvoždík

“…The Great Lakes spiny reed frog (Afrixalus lacustris) was recently described from transitional (submontane) forests at mid-elevations of the Albertine Rift mountains in the eastern Congolian region. …”
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Prediction the Choice of Financing for Start-ups using Machine Learning Algorithms and Behavioral Biases by Naimeh Niazi, Hamideh Razavi

“…Based on 70 responses received and using algorithms including binary matching, classification chains, label power set, K-nearest neighbors, extreme gradient boosting, cluster boosting algorithm and random forest, the financing methods chosen by startups were predicted. …”
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DNAPred_Prot: Identification of DNA-Binding Proteins Using Composition- and Position-Based Features by Omar Barukab, Yaser Daanial Khan, Sher Afzal Khan, Kuo-Chen Chou

“…The results of SVM and ANN were also compared with those of a random forest classifier. The robustness of the proposed model was evaluated by using the independent dataset PDB186, and an accuracy of 91.47% was achieved by it. …”
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PENGGUNAAN BAP DAN TDZ UNTUK PERBANYAKAN TANAMAN GAHARU (Aquilaria malaccensis Lamk.) by Azwin Azwin

“… Agarwood (A. malaccensis Lamk.) is one of the important tropical forest trees, which produces a high economically valuable fragrant resinous wood. …”
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Integrating Machine Learning and Material Feeding Systems for Competitive Advantage in Manufacturing by Müge Sinem Çağlayan, Aslı Aksoy

“…The research employs six machine learning (ML) algorithms—logistic regression (LR), decision trees (DT), random forest (RF), support vector machines (SVM), K-nearest neighbors (K-NN), and artificial neural networks (ANN)—to develop a multi-class classification model for material feeding system selection. …”
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Classification of Animal Behaviour Using Deep Learning Models by M. Sowmya, M. Balasubramanian, K. Vaidehi

“…People who stay near forest areas face a major issue with animals. The most significant task in deep learning is animal behaviour classification. …”
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Machine Learning for Predicting Distant Metastasis of Medullary Thyroid Carcinoma Using the SEER Database by Zhen-Tian Guo, Kun Tian, Xi-Yuan Xie, Yu-Hang Zhang, De-Bao Fang

“…Among the six ML models, the random forest (RF) had the best predictability in assessing the risk of DM in MTC, with an accuracy, precision, recall rate, F1-score, and AUC higher than those of the traditional binary LR model. …”
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