Evaluation of Sustainable Land Management Practices in Kaharo Subcounty Kabale District. by Nasaasira, Blair

“…The major findings of the study revealed that mixed farming, terracing, tree planting, mulching, crop rotation, fertilizer application and minimum tillage was the most land management practices identified in the study area. …”
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Derivation of allometric equations and carbon content estimation in mangrove forests of Malaysia by Waseem Razzaq Khan, Michele Giani, Stanislao Bevilacqua, Shoaib Ahmad Anees, Kaleem Mehmood, M. Nazre, Abdul Aziz Bin Abdul Haddy, Abang Norizan Bin Abang Median, Japanie Bin Bujang, Fatin-Norliyana Mohamad-Ismail, Johar Mohamed, Zaiton Samdin, Rambod Abiri, Tuan-Marina Tuan-Ibrahim, Lydia-Suzieana Mohammad, Hamid-Reza Naji, Seemab Akram, Hazandy Abdul-Hamid, Timothy Dube

“…Using diameter at breast height (DBH) and tree height, we developed site species-specific allometric equations to estimate aboveground biomass. …”
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Carbon stock dynamics of forest to oil palm plantation conversion for ecosystem rehabilitation planning by D. Frianto, E. Sutrisno, A. Wahyudi, E. Novriyanti, W.C. Adinugroho, A.S. Yunianto, H. Kurniawan, H. Khotimah, A. Windyoningrum, I.W.S. Dharmawan, H.L. Tata, S. Suharti, H.H. Rachmat, E.M. Lim

“…Data analysis was carried out using Classification and Regression Tree, a decision tree algorithm used in machine learning for guided classification. …”
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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials by Simin Nazari, Amira Abdelrasoul

“…A comparative analysis of linear regression, K-nearest neighbors regression, decision tree regression, random forest regression, XGBoost regression, lasso regression, and support vector regression is conducted to predict affinity energy. …”
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Familial Aggregation and Risk Factors for Prostate Cancer in Affected Individuals by Julio Armando Sánchez Delgado, Nailé Edita Sánchez Lara

“…The variables were operationalized: age, degree of consanguinity, and risk factors. The family tree was obtained.<br /> <strong>Results:</strong> first- and second-degree relatives of consanguinity showed the highest incidence of disease for both groups. …”
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Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…This study employs machine learning models, including Linear Regression, Ridge Regression, Lasso Regression, Bayesian Ridge, Decision Tree, Gradient Boosting, XGBoost, and CatBoost, to forecast future trends in under-5 mortality. …”
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Maximizing the neuroprotection from Citrus aurantium leaves: Optimization of a blended extract from a sequential extraction process with compressed fluids and NADES by Victor M. Amador-Luna, Miguel Herrero, Marta Jiménez de la Parra, Ángel Gómez Arribas, Elena Ibáñez, Lidia Montero

“…In particular, leaves from the tree pruning and from fruits harvesting are considered an agrifood-related waste with high valorization potential. …”
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Multi-Criteria Assessment of Flood Risk on Railroads Using a Machine Learning Approach: A Case Study of Railroads in Minas Gerais by Fernanda Oliveira de Sousa, Victor Andre Ariza Flores, Christhian Santana Cunha, Sandra Oda, Hostilio Xavier Ratton Neto

“…The models evaluated included linear regression, random forest, decision tree, and support vector machines. Among the evaluated models, Linear Regression emerged as the best-performing model with an R² value of 0.999998, a mean squared error (MSE) of 0.018672, and a low tendency to overfitting (0.000011).…”
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Fault Diagnosis of Planetary Gearbox Based on Motor Current Signal Analysis by Ziyuan Jiang, Qinkai Han, Xueping Xu

“…Subsequently, four classical machine learning models, including the support vector machine (SVM), decision tree (DT), random forest (RF), and AdaBoost, are used for fault classifications based on the features extracted via principal component analysis (PCA). …”
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Monitoring Soil Salinity in Arid Areas of Northern Xinjiang Using Multi-Source Satellite Data: A Trusted Deep Learning Framework by Mengli Zhang, Xianglong Fan, Pan Gao, Li Guo, Xuanrong Huang, Xiuwen Gao, Jinpeng Pang, Fei Tan

“…These variables are then integrated into various machine learning models—such as Ensemble Tree (ETree), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and LightBoost—as well as deep learning models, including Convolutional Neural Networks (CNN), Residual Networks (ResNet), Multilayer Perceptrons (MLP), and Kolmogorov–Arnold Networks (KAN), for modeling. …”
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Clinico¬pathological features and phylogenetic analysis of rabies infection in local Iraqi breed cattle by M. H. Hussain, Kh. A. Mansour, S. A. A. Al-Redah, A. J. Abid

“…Furthermore, when building the phylogenetic tree, the current study isolates (Iraqi isolates) were mostly similar to Nigerian isolates. …”

Patient with Jaundice, Dyspnea and Hyperferritinemia after COVID-19 by V. R. Grechishnikova, P. E. Tkachenko, M. S. Zharkova, T. P. Nekrasova, V. T. Ivashkin

“…Upon instrumental examination no signs of hepatosplenomegaly, biliary tree changes, intra- and extrahepatic obstruction were found. …”
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Natural Hybridization Between <i>Quercus crassipes</i> and <i>Q. crassifolia</i> (Fagaceae) Is a Key Process to Ensure the Biodiversity of Their Associated Lichen Community by Leticia Valencia-Cuevas, Jennie Melhado-Carboney, Efraín Tovar-Sánchez

“…Lichens are organisms whose dynamics take place on terrestrial substrates such as rock, dead wood, living plants, and soil. Living trees are used for lichens as structural support to access light. …”
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Path Planning for Autonomous Vehicle Based on a Two-Layered Planning Model in Complex Environment by Jiajia Chen, Rui Zhang, Wei Han, Wuhua Jiang, Jinfang Hu, Xiaoshan Lu, Xingtao Liu, Pan Zhao

“…In the high-level model, the improved Bidirectional Rapidly-exploring Random Tree (Bi-RRT) based on the steering constraint is used to generate an obstacle-free path while satisfying the nonholonomic constraints of vehicle. …”
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Effects of Water Deficit on Growth, Biomass Allocation and Photosynthesis of <i>A. senegal</i> Seedlings from Nguru and Gujba Provinces of Yobe State, North Eastern Nigeria by A.U. Jibo, M.G. Barker

“… Acacia senegal (L) Willd is a multipurpose tree species that occurs  throughout semi-arid Africa. …”
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Cost-effectiveness of Ruxolitinib vs Best Available Therapy in the Treatment of Myelofibrosis in Spain by María Teresa Gómez-Casares, Juan Carlos Hernández-Boluda, Antonio Jiménez-Velasco, Joaquin Martínez-López, María Giovanna Ferrario, Irmina Gozalbo, Joana Gostkorzewicz, Rudi Subirá

“…**Methods:** A decision-tree and Markov model were adapted to the Spanish setting to assess the cost-effectiveness of ruxolitinib vs. …”
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Study of Mitogenomes Provides Implications for the Phylogenetics and Evolution of the Infraorder Muscomorpha in Diptera by Huan Yuan, Wenbo Fu, Shulin He, Tingjing Li, Bin Chen

“…The ancestral area of origin and geographic range of Muscomorpha was deduced to be the Palaearctic region with 56.9% probability using the RASP software based on a dated tree.…”
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Chronic nitrogen legacy in the aquifers of China by Xin Liu, Fu-Jun Yue, Li Li, Feng Zhou, Hang Wen, Zhifeng Yan, Lichun Wang, Wei Wen Wong, Cong-Qiang Liu, Si-Liang Li

“…Here we used machine learning and decision tree-heatmap analysis by compiling nitrate concentrations and isotope data from 4047 groundwater sites across China to understand their dynamics and drivers across gradients of geographical, climate, and human factors. …”
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Internet of things-driven approach integrated with explainable machine learning models for ship fuel consumption prediction by Van Nhanh Nguyen, Nghia Chung, G.N. Balaji, Krzysztof Rudzki, Anh Tuan Hoang

“…Indeed, five different MLs were employed including linear regression, decision tree, random forest, XGBoost, and Gradient Boosting Regression. …”
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Grazing regime rather than grazing intensity affect the foraging behavior of cattle by You Wang, Rui Yu, Xin Li, Ronghao Chen, Jiahui Liu

“…Five machine learning models—XGBoost, Random Forest, Decision Tree, Extra Trees, and CatBoost—were employed to classify cattle's behavior and to assess the impact of grazing strategies on these behaviors. …”
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