Addressing the emerging threat of Oropouche virus: implications and public health responses for healthcare systems by Olalekan John Okesanya, Blessing Olawumi Amisu, Olaniyi Abideen Adigun, Mohamed Mustaf Ahmed, Abdulmajeed Opeyemi Agboola, Tolga Kab, Gilbert Eshun, Bonaventure Michael Ukoaka, Tolutope Adebimpe Oso, Jerico Bautista Ogaya, Don Eliseo Lucero-Prisno

“…The ability of the virus to thrive in both forested and urban areas has raised concerns regarding its potential spread to new regions, particularly in the context of climate change. …”
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Exploring links between socio-ecological systems and psychological distress: a case study in rural Uganda by Thomas Pienkowski, Aidan Keane, Eugene Kinyanda, Birthe Loa Knizek, Caroline Asiimwe, Geoffrey Muhanguzi, E.J. Milner-Gulland

“…Households bordering a conservation area reported that crop losses from wildlife contributed to food insecurity. However, forest resources represented important safety nets for those facing poverty and food insecurity. …”
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When Three Trees Go to War by van Iersel, Leo, Jones, Mark, Weller, Mathias

“…The case of three trees is interesting since it is the easiest case that cannot be equivalently formulated in terms of agreement forests. Instead, we base the result on a surprising lower bound for multilabelled trees (MUL-trees) displaying the caterpillars. …”
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A Tractor Work Position Prediction Method Based on CNN-BiLSTM Under GNSS Signal Denial by Yangming Hu, Liyou Xu, Xianghai Yan, Ningjie Chang, Qigang Wan, Yiwei Wu

“…In farmland environments where GNSS signals are obstructed, such as forested areas or in adverse weather conditions, traditional GNSS/INS integrated navigation systems suffer from positioning errors and instability. …”
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Analysis of Germination Curves of Cinchona officinalis L. (Rubiaceae) Using Sigmoidal Mathematical Models by Lenin Quiñones-Huatangari, Annick Estefany Huaccha-Castillo, Franklin Hitler Fernandez-Zarate, Eli Morales-Rojas, Jenny Del Milagro Marrufo-Jiménez, Leslie Lizbeth Mejía-Córdova

“…Seed germination is the fundamental phenomenon that determines the successful growth and development of each plant species, even more so in Cinchona officinalis, which is a forest species that stands out for its medicinal importance. …”
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Intrusion Detection for Wireless Sensor Network Using Particle Swarm Optimization Based Explainable Ensemble Machine Learning Approach by Shaikh Afnan Birahim, Avijit Paul, Fahmida Rahman, Yamina Islam, Tonmoy Roy, Mohammad Asif Hasan, Fariha Haque, Muhammad E. H. Chowdhury

“…This paper proposes a novel Intrusion Detection System (IDS) leveraging Particle Swarm Optimization (PSO) and an ensemble machine learning approach combining Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbors (KNN) models to enhance the accuracy and reliability of intrusion detection in WSNs. …”
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Examining the landscape transformation and temperature dynamics in Pakistan by Awais Ali, Bilal Hussain, Riaz Ul Hissan, Khalid M. Al Aiban, Magdalena Radulescu, Cosimo Magazzino

“…Nevertheless, larger fluctuations in land surface temperature were found in the cover and protective forests of the study area, especially in the northwestern and southeastern parts of the system. …”
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Predicting Patients’ Revisit Intention Based on Satisfaction Scores: Combination of Penalized Regression and Neural Networks by Farshid Abdi, Shaghayegh Abolmakarem, Amir Karbassi Yazdi, Paul Leger, Yong Tan, Giuliani Coluccio

“…In addition to feature selection models such as Random Forest, Genetic Algorithm, and Lasso Regression, the study employs various methods, including Neural Networks, Support Vector Machines, Decision Trees, k-Nearest Neighbors, Rule-based systems, and Naive Bayes algorithms. …”
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LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification by Nimisha Ghosh, Sankar Kumar Mridha, Rourab Paul

“…To identify such biomarkers, initially LASSO in association with four machine learning models such as Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Naive Bayes (NB) are applied on the dataset to find the initial reduced set of genes as well as the best learning model based on classification accuracy; SVM in this case. …”
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A dataset of gridded precipitation intensity-duration-frequency curves in Qinghai-Tibet Plateau by Zhihui Ren, Yan-Fang Sang, Peng Cui, Fei Chen, Deliang Chen

“…The generalized extreme value distribution is chosen to fit the annual maximum precipitation samples at 203 weather stations, based on which the at-site IDF curves are estimated; then, principal component analysis is done to identify the southeast-northwest spatial pattern of at-site IDF curves, and its first principal component gives a 96% explained variance; finally, spatial interpolation is done to estimate gridded IDF curves by using the random forest model with geographical and climatic variables as predictors. …”
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Synergistic effects of high atmospheric and soil dryness on record-breaking decreases in vegetation productivity over Southwest China in 2023 by Zhikai Wang, Wen Chen, Jinling Piao, Qingyu Cai, Shangfeng Chen, Xu Xue, Tianjiao Ma

“…Our findings reveal that, during the 2023 extreme event in SWC, the decreases in forest productivity were primarily driven by low SM anomalies, while the decreases in the grassland and cropland productivity mainly resulted from abnormally high VPDs. …”
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Graph-based two-level indicator system construction method for smart city information security risk assessment by Li Yang, Kai Zou, Yuxuan Zou

“…In this study, we proposed a graph-based two-level indicator system construction method. First, a random forest was used to extract the indicators' dependency graph from missing data. …”
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Gaussian Process Regression and Machine Learning Methods for Carbon-Based Material Adsorption by Manar Ahmed Hamza, Maha M. Althobaiti, Fahd N. Al-Wesabi, Rana Alabdan, Hany Mahgoub, Anwer Mustafa Hilal, Abdelwahed Motwakel, Mesfer Al Duhayyim

“…In the existing system, random forest and ANN methods were used for TC and SMX for predicting the quantities of antibiotics in the CBMs. …”
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CryoProtect: A Web Server for Classifying Antifreeze Proteins from Nonantifreeze Proteins by Reny Pratiwi, Aijaz Ahmad Malik, Nalini Schaduangrat, Virapong Prachayasittikul, Jarl E. S. Wikberg, Chanin Nantasenamat, Watshara Shoombuatong

“…This study addresses this issue by predicting AFPs directly from sequence on a large set of 478 AFPs and 9,139 non-AFPs using machine learning (e.g., random forest) as a function of interpretable features (e.g., amino acid composition, dipeptide composition, and physicochemical properties). …”
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Cutting-Edge Intrusion Detection in IoT Networks: A Focus on Ensemble Models by Najm Us Sama, Saeed Ullah, S. M. Ahsan Kazmi, Manuel Mazzara

“…This paper provides a comprehensive performance comparison of various machine learning classifiers, including K-Nearest Neighbors, Gradient Boosting, XGBoost, Support Vector Machines, Random Forests, Decision Trees, and Extremely Randomized Trees, for intrusion detection in IoT networks. …”
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Recently Delisted Songbird Harbors Extensive Genomic Evidence of Inbreeding, Potentially Complicating Future Recovery by Anna María Calderón, Andrew W. Wood, Zachary A. Szpiech, David P. L. Toews

“…ABSTRACT The Kirtland's warbler (Setophaga kirtlandii) is a rare migratory passerine species and habitat specialist of the North American Jack Pine Forests. Their near extinction in the 1970s classified them as endangered and protected under the Endangered Species Act of 1973. …”
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A spatial accessibility framework for mapping the mismatch between wood supply and demand across Europe by Anita Poturalska, Ossi Kotavaara, Terhi Ala-Hulkko

“…Wood is one of the most important provisioning ecosystem services (ES) of forest, crucial for maintaining the welfare and wellbeing of the population. …”
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Developing an Intelligent System for Efficient Botnet Detection in IoT Environment by Ramesh Singh Rawat, Manoj Diwakar, Umang Garg, Prakash Srivastava

“…This paper focused on analyzing botnet traffic in an IoT environment using machine learning and deep learning classifiers: Decision tree classifier, Naïve Bayes, K nearest neighbor, Convolution neural network, Recurrent neural network, and Random Forest. We calculated each algorithm's Accuracy, True Positive, False Positive, False Negative, True Negative, Precision, and Recall. …”
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Insight into the phylogeny and antibiotic resistance of Pseudomonas spp. originating from soil of the Białowieża National Park in Northeastern Poland by Wioleta Lewandowska, Wioleta Lewandowska, Jacques Mahillon, Justyna Małgorzata Drewnowska, Izabela Swiecicka, Izabela Swiecicka

“…., we investigated 41 isolates from soil samples taken in the Białowieża National Park in Northeastern Poland. This unique forest without notable anthropogenic influence, provides excellent conditions for research of antibiotic resistance from the perspective of natural environments. …”
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Vibration Reliability Analysis of Aeroengine Rotor Based on Intelligent Neural Network Modeling Framework by Jia-Qi Liu, Yun-Wen Feng, Cheng Lu, Wei-Huang Pan, Da Teng

“…The comparison of INNMF, random forest (RF), and ANN shows that INNMF improves analysis accuracy and calculation efficiency. …”
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