Feeding Patterns and Xenomonitoring of Trypanosomes among Tsetse Flies around the Gashaka-Gumti National Park in Nigeria by Solomon Ngutor Karshima, Idris A. Lawal, Oluseyi Oluyinka Okubanjo

“…We identified 10 T. brucei, 3 T. congolense savannah, 2 T. congolense forest, and 2 mixed infections among the 13 pools made from the 27 flies positive for trypanosomes with light microscopy. …”
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Environmental influences on chorusing patterns in an Australian tropical savanna frog community by Sheryn Brodie, Slade Allen‐Ankins, Lin Schwarzkopf

“…We described the chorusing patterns of each species over two wet seasons at three breeding sites, and used conditional random forest analysis to investigate the influence of various environmental factors. …”
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Three-Rooted Permanent Mandibular First Molars: A Meta-Analysis of Prevalence by Nyan M. Aung, Kyaw K. Myint

“…The proportions of the prevalence of three-rooted permanent mandibular first molars were presented in the forest plots by random effect model. The calculation was performed with MetaXL version 5.3. …”
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Comparison of Different Machine Learning Methodologies for Predicting the Non‐Specific Treatment Response in Placebo Controlled Major Depressive Disorder Clinical Trials by Roberto Gomeni, Françoise Bressolle‐Gomeni

“…At this purpose, six machine learning methodologies (gradient boosting machine, lasso regression, logistic regression, support vector machines, k‐nearest neighbors, and random forests) were compared to the multilayer perceptrons artificial neural network (ANN) methodology for predicting the probability of individual non‐specific treatment response. …”
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Breaking the Barriers for Women Participation in Agroforestry in the Context of AfCFTA by Patrick Opoku, Awonlimali Kenneth Ali, Peter Ampadu-Daaduam, Dorothy Asare Akoto

“…The study found out that Taungya farming, home garden, and forest farming were the types of agroforestry systems carried out by women in the study area. …”
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Singleton-based species names and fungal rarity: Does the number really matter? by Jonathan Cazabonne, Allison K. Walker, Jonathan Lesven, Danny Haelewaters

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ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease by Tripti Tripathi, Rakesh Kumar

“…The characteristics are subsequently used to educate five machine learning algorithms, namely k-nearest neighbors (KNN), decision tree (DT), support vector machine (SVM), XGBoost, and random forest (RF). The effectiveness of every algorithm is assessed through a 10-fold cross-validation. …”
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Bird diversity in different vegetation types in the Pacific coastal plain of Guatemala by Sofia Aguilar-Jocol, Michelle Bustamante-Castillo, Marco Tax

“…The avian community consisted predominantly of species adapted to open habitats, with generalist bird species prevailing and only a limited representation of species typical of the understory in subtropical wet forests. Additionally, the observed species turnover value suggests a moderate level of species replacement among different vegetation types at the study site. …”
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Municipios “libres de eucaliptos”: análisis de los actores políticos locales en Galicia by Diego Cidrás

“… La conflictividad vinculada a la gestión del eucalipto trasciende en Galicia su política forestal y abarca nuevos ámbitos sociales y políticos poco explorados en la academia. …”
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A machine learning approach for wind turbine power forecasting for maintenance planning by Hariom Dhungana

“…The interpretable ML includes Linear Regression (LR), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Random Forest (RF); the explainable ML consists of graphical Neural network (GNN); and the blackbox model includes Multi-layer Perceptron (MLP), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM). …”
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Les bonobos se rappellent-ils la voix de leurs anciens partenaires ? by Florence Levréro, Sumir Keenan, Nicolas Mathevon, Jeroen MG Stevens, Jean Pascal Guéry, Klaus Zuberbühler

“…For non-human primates who live in dense forest environments, visual access to one another is often limited, and recognition of social partners over distances largely depends on vocal communication. …”
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Advanced machine learning approach with dynamic kernel weighting for accurate electrical load forecasting by C. Jeevakarunya, V. Manikandan

“…In terms of performance, the study assesses the effectiveness of EDW-MKSVR models against those of boosted tree, random forest regression, K-nearest neighbor, support vector regression, and long short term memory. …”
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NATURAL RESOURCE ENDOWMENT AND ECONOMIC GROWTH: EVIDENCE FROM SOME SELECTED SUB-SAHARAN AFRICAN COUNTRIES by Felix Gbenga Olaifa, Ebenezar Adesoji Olubiyi, Oluwasegun Olawale Benjamin Benjamin, Philip Olugbenga Adebayo Adebayo

“…Data on economic growth, arable land, forest land rent, tertiary education enrolment, and labour force growth obtained from World Development Indictors of the World Bank were used. …”
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Effect of Roasting on the Proximate Composition, Antioxidant Activity, and Functional Properties of Afrostyrax lepidophyllus (Country Onion) Seeds by Wiyeh Claudette Bakisu Muala, Tonfack Djikeng Fabrice, Noumo Ngangmou Thierry, Ngangoum Eric Serge

“…Afrostyrax lepidophyllus seed is a nontimber forest product which has a strongly ferocious smell of garlic or onion. …”
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Effect of active faults in the groundwater level of Shaharchay basin in Urmia by Tayebeh Kiani, Zahra Yousefi

“…But the center of the basin zoning was very high with very low permeability, high slope, average precipitation and mixture of garden, forest and grassland usages. basin center located on high seismic intensity zone and density Quaternary faults. only because of the high level in the basin center of Silvaneh are active faults and a high intensity tectonic seismic.…”
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Monitoring Volcanic Eruptions with Geographical Information Systems and Remote Sensing Methods: The Case Study of Cumbre Vieja Volcano (Spain) by Özer Akyürek

“…As a result of the GIS and UA analyzes, it was determined that various agricultural areas and forest areas, as well as residential areas and the ocean, were also damaged. …”
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Wae Bobok Tourism Potential: Mapping a Destination in West Manggarai, East Nusa Tenggara by L. K. Herindiyah Kartika Yuni, I Wayan Kartimin

“…Many tourism potentials in West Manggarai have been known, widely praised, and researched but Wae Bobok and its potential have not yet been published. Wae Bobok is a forest area located in the Tanjung Boleng Tourism Village area. …”
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Analyzing the influence of urban vegetation cover on land surface temperature in Southwestern Nigeria by Aladesanmi Daniel Agbelade

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Paddy Crop and Weed Discrimination: A Multiple Classifier System Approach by Radhika Kamath, Mamatha Balachandra, Srikanth Prabhu

“…This paper investigates the multiple classifier systems built using support vector machines and random forest classifiers for plant classification in classifying paddy crops and weeds from digital images. …”
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Relationship of Meteorological Variables with the Concentration of Various Tree Pollen Types in Madrid (Spain) by Javier Chico-Fernández, Esperanza Ayuga-Téllez

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