Diversity and abundance of butterflies in urban areas of Bankura district, Bankura, West Bengal, India by Avisek Patra, Anirban Patra, Biplab Mandal, Anupam Ghosh

“…Abstract Objective During the present study, the biodiversity profile of butterflies was assessed on the Bankura Christian College campus, a large area with a huge amount of trees, bushes, rain forest, and undisturbed areas within the urban areas of Bankura district of West Bengal, India. …”
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Advancing biomonitoring of eDNA studies with the Anaconda R package: Integrating soil and One Health perspectives in the face of evolving traditional agriculture practices. by Pierre-Louis Stenger, Audrey Léopold, Kelly Dinh, Pierre Mournet, Nadia Robert, Julien Drouin, Jacques Wamejonengo, Sylvie Russet, Thomas Ibanez, Laurent Maggia, Fabian Carriconde

“…This study applied the Anaconda package to examine the impact of two types of duration fire-fallow cropping systems, using natural forests as a reference, on soil fungal and bacterial communities in Maré Island (New Caledonia). …”
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Analysis of Internet Financial Risk Control Model Based on Machine Learning Algorithms by Mingjin Liu, Ruijie Gao, Wei Fu

“…The accuracy of classification and early warning results of the random forest algorithm is relatively high, and the detection rate of the decision tree model is relatively high, but the cost is also the highest. …”
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Bursting Phenomenon and Chaos Phase Control in Plant Dynamics by Makenne Yemeli Lola, Kengne Romanic, Pelap Francois Beceau

“…It also helps to understand the impact of wind on the plant dynamics, in particular, and in forest in general, which is very crucial for understanding several plant communities. …”
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Breast Cancer Prediction: A Fusion of Genetic Algorithm, Chemical Reaction Optimization, and Machine Learning Techniques by Md. Rafiqul Islam, Md. Shahidul Islam, Saikat Majumder

“…In our study, we employed two metaheuristic algorithms, namely, genetic algorithm (GA) and chemical reaction optimization (CRO) with machine learning techniques, including support vector machine (SVM), decision tree, random forest, and XGBoost. GA and CRO are used to optimize the feature selection process. …”
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Modeling Equatorial to Mid‐Latitudinal Global Night Time Ionospheric Plasma Irregularities Using Machine Learning by Ephrem Beshir Seba, Giovanni Lapenta

“…Abstract This study focuses on modeling the characteristics of nighttime topside Ionospheric Plasma Irregularities (PI) on a global scale. We utilize Random Forest (RF) and a one‐dimensional Convolutional Neural Network (1D‐CNN) model, incorporating data from the Swarm A, B, and C satellites, space weather data from the OMNIWeb data center, as well as zonal and meridional wind model data. …”
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A Data Mining Approach Identified Salivary Biomarkers That Discriminate between Two Obesity Measures by Ping Shi, J. Max Goodson

“…For a random cohort of over 700 subjects from 8137 Kuwait children (10.00 ± 0.67 years), four data mining methods were applied to identify important variables associated with obesity, including logistic regression by lasso regularization (Lasso), multivariate adaptive regression spline (MARS), random forests (RF), and boosting classification trees (BT). …”
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Comparative Microstructural Evaluation of Wood in Three Dominant Ziziphus Species of Desert Ecosystem (Cholistan), Pakistan by Muhammad Bilal, Zaheer-ud-din Khan, Sohaib Muhammad, Uzma Hanif, Khalid Hussain, Muhammad Tayyab, Andleeb Anwar Sardar, Hassan Nawaz, Muhammad Jawad Tariq Khan, null Mahrukh, Aneela Rasool, Summiya Faisal, Muhammad Zahid

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Ion channel classification through machine learning and protein language model embeddings by Ghazikhani Hamed, Butler Gregory

“…We employ a comprehensive array of machine learning algorithms, including k-Nearest Neighbors, Random Forest, Support Vector Machines, and Feed-Forward Neural Networks, alongside a novel Convolutional Neural Network (CNN) approach. …”
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Characteristic of stem rot diseases caused by Ceratocystis sp. on Acacia decurrens and its status in Gunung Merapi National Park, Yogyakarta by Sri Rahayu, Handojo Hadi Nurjanto, Rahman Gilang Pratama

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Next-generation diabetes diagnosis and personalized diet-activity management: A hybrid ensemble paradigm. by Muhammad Sajid, Kaleem Razzaq Malik, Ali Haider Khan, Sajid Iqbal, Abdullah A Alaulamie, Qazi Mudassar Ilyas

“…This research proposes an optimized approach by harnessing machine learning classifiers, including Random Forest, Support Vector Machine, and XGBoost, to develop a robust framework for accurate diabetes prediction. …”
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Effect of PVA-co-MMA Copolymer on the Physical, Mechanical, and Thermal Properties of Tropical Wood Materials by Md. Saiful Islam, Sinin Hamdan, Mansor B. Ahmad, Mahbub Hasan, Azman Hassan, M. K. Mohamad Haafiz, M. Jawaid

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Eucalyptus globulus en el sudeste de la provincia de Buenos Aires: edades, procedencias y densidad de la madera by K. MORENO, D. IGARTÚA

“…Los objetivos del presente trabajo fueron describir el recurso forestal de Eucalyptus globulus Labill. (Eucalipto blanco) implantado en el sudeste de la provincia de Buenos Aires, Argentina, en términos de edad, procedencias y suelos; determinar la densidad básica de la madera y analizar su variabilidad. …”
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Ensemble Deep Learning Technique for Detecting MRI Brain Tumor by Rasool Fakhir Jader, Shahab Wahhab Kareem, Hoshang Qasim Awla

“…These results significantly surpass the accuracy of other methods such as Naive Bayes, decision tree classifier, random forest, and DNN models.…”
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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

“…Conventional ML techniques like random forest (RF) and decision tree (DT) were also employed for comparison. …”
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Breeding properties and cytological characteristics of interspecific hybrids between the Ussuri plum and bullace by D. S. Garapov, O. V. Mochalova

“…The research was conducted in 2004–2023 in the forest-steppe zone of the Ob river region in Altai. …”
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Integrated Bioinformatics Identifies FREM1 as a Diagnostic Gene Signature for Heart Failure by Chenyang Jiang, Weidong Jiang

“…Integrating three machine learning methods, the least absolute shrinkage and selection operator (LASSO) algorithm, random forest (RF) algorithm, and support vector machine recursive feature elimination (SVM-RFE) are used to determine candidate diagnostic gene signals. …”
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Soil Quality Assessment Strategies for Evaluating Soil Degradation in Northern Ethiopia by Gebreyesus Brhane Tesfahunegn

“…Eight LUSMS selected for soil sampling and analysis included (i) natural forest (LS1), (ii) plantation of protected area, (iii) grazed land, (iv) teff (Eragrostis tef)-faba bean (Vicia faba) rotation, (v) teff-wheat (Triticum vulgare)/barley (Hordeum vulgare) rotation, (vi) teff monocropping, (vii) maize (Zea mays) monocropping, and (viii) uncultivated marginal land (LS8). …”
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The Impacts of Blue Stain Degradation on the Industrial Processing Properties of logs by Osman Komut, Atakan Öztürk

“…This study aims to determine the effects of blue stain degradation on manufacturing process of forest industry managements processing log and the losses caused by this. …”
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Identifying RBBP7 as a Promising Diagnostic Biomarker for BK Virus-Associated Nephropathy by Yicun Wang, Yuxuan Wang, Di Zhang, Hao Zhang, Wei Wang, Xiaopeng Hu

“…We collected gene expression profiles of 169 kidney biopsies taken from BKVN, rejection, and stable functioning allografts, based on single sample gene set enrichment analysis and random forest algorithm, and three hallmark activities associated with DNA damage and proliferation were found to be relatively specific in BKVN. …”
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