Teach Aquaculture Curriculum: Chlorine--Friend or Foe? by Carlos V. Martinez, Cortney L. Ohs, Brian E. Myers, Elisa J. Livengood, Craig S. Kasper, Amber L. Garr, R. Leroy Creswell, Frank A. Chapman

“…Published by the UF School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences, May 2010. …”
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Mapping Your World with Community Analyst: An Easy to Use Tool to Map the Characteristics of U.S. Communities by Robert Swett, Lisa Krimsky

“…This 9-page fact sheet was written by Robert Swett and Lisa Krimsky, and published by the UF Department of School of Forest Resources and Conservation, October 2013. …”
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Butterfly fauna (Lepidoptera: Rhopalocera) of Donji Emovci, Požega, Croatia by Toni Koren, Goran Letić

“…The surveyed area consists mostly of a mosaic of different kinds of monocultures, scattered grasslands and forest fragments. Seventy-nine butterfly species could have been reliably identified from the photographs, several of which are rare or interesting records for Croatia (e.g. …”
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Mobile stance-taking in nature: an exploration of gaze patterns during assessments of objects in nature by Barbara Laner

“…The analysis is based on a corpus of 10 hiking pairs who walked through the Black Forest National Park while wearing mobile eye-tracking glasses to record their gaze behavior and verbal practices. …”
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A surface model of nonlinear, non-steady-state phloem transport by Youcef Mammeri, Damien Sellier

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Urban Tree Selection for Diversity by Deborah R. Hilbert, Andrew K. Koeser, Robert J. Northrop

“… Urban tree diversity is important when attempting to create a healthy, beneficial, and resilient urban forest. Having a variety of trees can increase the aesthetic value for residents and create habitats for plants and animals. …”
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Tetraploid Induction and Establishment of Breeding Stocks for All-Triploid Seed Production by Huiping Yang, Ximing Guo, John Scarpa

“…This 8-page fact sheet written by Huiping Yang, Ximing Guo, and John Scarpa and published by the UF/IFAS School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences, conveys basic knowledge about tetraploid induction and breeding to commercial shellfish culturists and the general public. …”
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Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models by Youzhi Lian, Yinyu Shi, Haibin Shang, Hongsheng Zhan

“…Key genes were selected using five machine learning models, including Lasso, Elastic Net, Random Forest, SVM, and GBM. These key genes were then used to train 45 machine learning models by combining nine different algorithms: Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosting Machine, Multilayer Perceptron, Naive Bayes, and Linear Discriminant Analysis. …”
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Effects of urbanization on the ephemeral lake flood risks under subtropical humid monsoon climate by Biqing Tian, Chaojun Gu, Hao Jia, Peng Gao, Liping Guo, Xingmin Mu

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Accurate estimation of Jujube leaf chlorophyll content using optimized spectral indices and machine learning methods integrating geospatial information by Nigela Tuerxun, Sulei Naibi, Jianghua Zheng, Renjun Wang, Lei Wang, Binbin Lu, Danlin Yu

“…To test this hypothesis, a framework was developed that first uses elastic net (EN) and the successive projection algorithm (SPA) for wavelength selection, followed by spectral index creation with OBC and ranking with random forest (RF). Support vector regression (SVR), random forest regression (RFR), and geographically weighted least squares support vector regression (GWLS-SVR) were then used to assess the prediction accuracy. …”
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An intelligent lithology identification method for sandstone and mudstone strata and its applications: A case study of the Jurassic strata in the Lunnan area, Xinjiang, China by Ming CAI, Qingwen ZHOU, Cong YANG, Feng CHEN, Dong WU, Wang LIN, Chengguang ZHANG, Yuanjun ZHANG, Yuxin MIAO

“…The optimized model was employed to deal with actual logging data for lithology identification, and its performance was evaluated using accuracy, precision, and recall and was then compared with the lithology identification results of the random forest (RF) and k-nearest neighbors (KNN) algorithms. …”
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An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer by Subrata Das, Vatsal Patel, Shouvik Chakravarty, Arnab Ghosh, Anirban Mukhopadhyay, Nidhan K. Biswas

“…Three machine learning algorithms—logistic regression, random forest, and support vector machine—along with recursive feature elimination, were used to rank these PCSAs. …”
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Machine Learning–Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study by Qian Xu, Xue Cai, Ruicong Yu, Yueyue Zheng, Guanjie Chen, Hui Sun, Tianyun Gao, Cuirong Xu, Jing Sun

“…Principal component analysis and random forest (RF) were used as feature selection techniques. …”
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Exploring cement Production's role in GDP using explainable AI and sustainability analysis in Nepal by Ramhari Poudyal, Biplov Paneru, Bishwash Paneru, Tilak Giri, Bibek Paneru, Tim Reynolds, Khem Narayan Poudyal, Mohan B. Dangi

“…On evaluation, the Extra Trees Regressor showed strong performance, along with the SET (Stacking) model, which was further validated using a nested cross-validation technique. Random Forest, on the other hand, had trouble; it displayed the greatest RMSE (15617.85) and the lowest testing (0.8117), suggesting poorer generalization. …”
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Evaluasi Usability pada Website Monitoring Kebakaran Hutan Menggunakan Metode Webuse by Helen Sasty Pratiwi, Haried Novriando

“…The importance of the two applications in monitoring forests is the reason for the need for a review of the measurement of both applications. …”
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Reflections by a member of the Editorial Board by Kevin T. Smith

“…These tree responses affect forest health, the economic value of wood for art and industry, the tree-ring record of environmental conditions, and the performance of trees in urban and community environments. …”
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Effects of different types of ginseng on intercellular wireless communication networks and central carbon metabolism pathways by Yujiao Liu, Dingqiang Lu, Jiayi Qiang, Lianjie Xu, Ming Li, Xinqian Wang, Yixuan Liu, Yifei Zhang, Wei Xu, Chenyu Xu, Qingwei Song, Wenling Wu, Yimeng Bi, Ruijuan Ren, Guangchang Pang

“…Therefore, the intake of 500 mg/person of forest ginseng or 100 mg/person of wild ginseng was beneficial to health. …”
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Bio-ecological characteristics of Malus genus species in the context of prospective directions in horticulture and landscape forestry by Tetiana Moskalets, Oleksandr Kratiuk, Mariana Ivankiv, Sergii Shevchenko, Nataliia Shevchuk

“…Borkh. are wellsuited for use in the creation of forest-park landscapes. Under the conditions of the Northern Forest-Steppe of Ukraine, Malus species were differentiated by their resistance to the scab pathogen (Venturia inaequalis Cooke). …”
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Influence of Arbuscular Mycorrhizal Fungi on Nitrogen Dynamics During <i>Cinnamomum camphora</i> Litter Decomposition by Yuehong Gao, Xiaoyu Long, Yiqi Liao, Yonghui Lin, Zaihua He, Qin Kong, Xiangshi Kong, Xingbing He

“…Both pathways will contribute to C sequestration in forest ecosystems, which advances our understanding of AMF’s contribution to nutrient cycling and ecosystem processes in subtropical forests.…”
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Are neurasthenia and depression the same disease entity? An electroencephalography study by Ge Dang, Lin Zhu, Chongyuan Lian, Silin Zeng, Xue Shi, Zian Pei, Xiaoyong Lan, Jian Qing Shi, Nan Yan, Yi Guo, Xiaolin Su

“…Among the classification models, random forest performed best with an accuracy of 0.93, area under the receiver operating characteristic curve of 0.97, and area under the precision-recall curve of 0.96. …”
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