SOURCE MATERIAL TO CREATE OF HIGH-PROTEIN VARIETIES OF OATS IN A ZONE OF NORTHERN TRANS-URAL by Ju. S. Ivanova, M. N. Fomina, I. G. Loskutov

“…The research performed in the southern forest-steppe of West Siberia resulted in identifying chickpea accessions with a shorter growing season, high plant productivity, good processability, and high symbiotic activity. …”
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The Mushroom Agaricus blazei Murill Elicits Medicinal Effects on Tumor, Infection, Allergy, and Inflammation through Its Modulation of Innate Immunity and Amelioration of Th1/Th2 I... by Geir Hetland, Egil Johnson, Torstein Lyberg, Gunnar Kvalheim

“…The medicinal mushroom Agaricus blazei Murill from the Brazilian rain forest has been used in traditional medicine and as health food for the prevention of a range of diseases, including infection, allergy, and cancer. …”
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Deep Learning- and Word Embedding-Based Heterogeneous Classifier Ensembles for Text Classification by Zeynep H. Kilimci, Selim Akyokus

“…The ensemble of base classifiers includes traditional machine learning algorithms such as naïve Bayes, support vector machine, and random forest and a deep learning-based conventional network classifier. …”
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Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…Subsequently, the paper provides an in-depth analysis of image classification methods based on machine learning, including traditional algorithms such as Support Vector Machine (SVM), Random Forest, and Decision Tree. These methods achieve image classification through two stages: feature extraction and classification, but they encounter limitations when confronted with large-scale datasets and complicated tasks. …”
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Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms by Chandan Kumar Roy

“…Additionally, the predictive accuracy of the OLS model was compared with several machine learning algorithms, including decision tree, random forest, support vector, and gradient boosting, using a 75-25 training-testing split and k-fold cross-validation. …”
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Abundance of Sesamia nonagrioides (Lef.) (Lepidoptera: Noctuidae) on the Edges of the Mediterranean Basin by Matilde Eizaguirre, Argyro A. Fantinou

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Terrestrial isopods (Isopoda: Oniscidea) in the Upper Mežica valley by Petra Štern, Primož Zidar

“…The most frequently found isopod was Trachelipus ratzeburgii as the researched area is mainly forest covered. However, the highest diversity of species was recorded in urban and semiurban areas. …”
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Comparative Study on Heart Disease Prediction Using Feature Selection Techniques on Classification Algorithms by Kaushalya Dissanayake, Md Gapar Md Johar

“…., decision tree, random forest, support vector machine, K-nearest neighbor, logistic regression, and Gaussian naive Bayes, have been applied to Cleveland heart disease dataset. …”
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Gestion en métapopulation de Propithecus coronatus: une approche originale et multidisciplinaire pour la conservation d’une espèce en danger à Madagascar by Josia Razafindramanana, Delphine Roullet

“…This project will serve as a model for the implementation of metapopulation management for endangered species in isolated forest fragments of Madagascar.…”
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Kelayakan Modul Submateri Tumbuhan Paku Kelas X SMA dari Hasil Inventarisasi Pteridophyta Kabupaten Sanggau by Patrisia Vika, Syamswisna Syamswisna, Hayatul Fajri

“…The module of  the fern sub-material has been made based on the results of the Pteridophyta inventory in the Gunung Belungai Protected Forest, Sanggau Regency, in March-April 2021. The validity of the module teaching materials is calculated based on the Lawshe method. …”
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Making the most of grasslands and heathlands by Doyle McKey

“…Compared to traditional (pre-industrial) forest-based agricultural systems, traditional agriculture as practiced in grasslands and heathlands has been neglected, both by agronomists and by ethnoecologists. …”
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Evaluation of machine learning models for the prediction of Alzheimer's: In search of the best performance by Michael Cabanillas-Carbonell, Joselyn Zapata-Paulini

“…The models used were Random Forest (RF), Adaptive Boosting (AdaBoost), Support Vector Machine (SVM), K-nearest Neighbors (KNN), and Logistic Regression (LR). …”
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Machine learning-based analyzing earthquake-induced slope displacement. by Jiyu Wang, Niaz Muhammad Shahani, Xigui Zheng, Jiang Hongwei, Xin Wei

“…This study evaluates the capabilities of various machine learning models, including artificial neural network (ANN), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) in analyzing earthquake-induced slope displacement. …”
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Morphological and phylogenetic analyses reveal four novel species of Distoseptispora (Distoseptisporaceae, Distoseptisporales) from southern China by Ming-Gen Liao, Xing-Xing Luo, Ya-Fen Hu, Rafael F. Castañeda-Ruíz, Zhao-Huan Xu, Jian Ma

“…During our mycological surveys in southern China, numerous strains were isolated from dead branches of unidentified plants in the forest of Jiangxi and Fujian provinces, China. Phylogenetic analyses of ITS, LSU, RPB2, and TEF1 sequence data using maximum-likelihood (ML) and Bayesian inference (BI) methods revealed the systematic placement of several Sporidesmium-like species within Distoseptispora. …”
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Comparisons of Machine Learning Models for Prediction of Susceptibility to Diabetes by Jiao Yutian

“…This study compares the predictive performance of machine learning models such as Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM). …”
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UPAYA KONSERVASI EKS-SITU FAMILI BEGONIACEAE DARI TAMAN NASIONAL BUKIT BARISAN SELATAN DI KEBUN RAYA LIWA, KABUPATEN LAMPUNG BARAT, PROVINSI LAMPUNG by Esti Munawaroh

“…Conservation efforts need to be done, due to the destruction of continuous forest areas that lead to reduced biodiversity of Begonia plant species. …”
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Machine Learning–Based Predictive Farmland Optimization and Crop Monitoring System by Marion Olubunmi Adebiyi, Roseline Oluwaseun Ogundokun, Aneoghena Amarachi Abokhai

“…This study provided a machine learning–aided mobile system for farmland optimization, using various inputs such as location, crop type, soil type, soil pH, and spacing. Random forest algorithm and BigML were employed to analyze and classify datasets containing crop features that generated subclasses based on random crop feature parameters. …”
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Woodworking industry in Russia: analysis of the industry structure and development prospects by Sh. A. Sultanakhmedov

“…The issue of waste utilization in wood processing industries due to low utilization of waste wood has been separately highlighted, and the importance of reasonable use of forest resources has been emphasized. The author concludes that, in general, the real contribution of the woodworking industry to the country’s economic development is still lagging behind the potential, but the main prospects for overcoming this condition have been highlighted, such as exports development, transportation costs reduction, state support strengthening in the industry, and improvement of waste disposal in woodworking industries.…”
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Physicochemical, antioxidant, and antimicrobial study in Nepalese honey by Amrita Adhikari, Nabin Kumar Thapa, Anita Gurung, Niranjan Parajuli

“…The IC50 values were calculated of which Forest honey was found to have the lowest IC50 value i.e. 7.735 ± 0.008 mg/mL. …”
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Indigenous Identity in the Global Sustainable Project by Yusril Ihza Mahendra, Eduardus Andhika Kurniawan, Balya Arung Segara

“…Developing countries can secure funding from developed countries to preserve their forests. However, despite the ideal goals set, the project's achievements varied due to differences in responses among local communities in several areas. …”
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