Florida Fishing Guide Requirements Checklist by Betty Staugler, Ralph Allen, Edward Camp

“…Camp and published by the UF/IFAS School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences summarizes the relevant regulations and requirements. https://edis.ifas.ufl.edu/fa218 …”
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The Wayqecha Amazon Cloud Curtain Ecosystem Experiment: A new experimental method to manipulate fog water inputs in terrestrial systems by Daniel B. Metcalfe, Darcy F. Galiano Cabrera, Luis Miguel Alvarez Mayorga, Roxana Sacatuma Cruz, Daniela Corrales Alvarez, Blanca Rosa Espinoza Otazu, Walter Huaraca Huasco, Jimmy R. Chambi, Maria E. Ezquerra, Beisit L. Puma Vilca, Mark Mulligan, Matthew A. Vadeboncoeur, Heidi Asbjornsen, Paulo R. L. Bittencourt, Aline B. Horwath, David C. Bartholomew

“…The curtains divert and intercept airborne water droplets in fog moving upslope, thereby depriving a ~420 m2 patch of forest immediately behind the curtains of this water source. …”
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Ophiostomatoid fungi associated with pine bark beetles and infested pines in south-eastern Australia, including Graphilbum ipis-grandicollis sp. nov. by Conrad Trollip, Angus J. Carnegie, Quang Dinh, Jatinder Kaur, David Smith, Ross Mann, Brendan Rodoni, Jacqueline Edwards

“…These fungi are considered a significant threat to coniferous forests, which has resulted in numerous studies characterising the diversity of bark beetles and their ophiostomatoid associates globally. …”
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Advantageous Extraction, Cleanup, and UHPLC-MS/MS Detection of Patulin Mycotoxin in Dietary Supplements and Herbal Blends Containing Hawberry from Crataegus spp. by Anna Przybylska, Grzegorz Bazylak, Robert Kosicki, Iwona Altyn, Magdalena Twaruzek, Jan Grajewski, Anna Soltys-Lelek

“…., Crataegus laevigata (Poiret) DC, and Crataegus rhipidophylla Gand, growing in the recreational forest areas and in the law-protected state national forest park in Poland. …”
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Occurrence and Behavior Analysis of <i>Duponchelia fovealis</i> on Strawberry Plants: Insights for Integrated Pest Management by Rodrimar Barboza Gonçalves, Maria Aparecida Cassilha Zawadneak, Taciana Melissa de Azevedo Kuhn, Thales Fernando Moreno Gulinelli, Ida Chapaval Pimentel, Alex Sandro Poltronieri, Joatan Machado da Rosa, José Manuel Mirás-Avalos, Emily Silva Araujo

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Effectiveness of a Collaborative, Virtual Outreach Curriculum for 4th-Year EM-bound Students at a Medical School Affiliated with a Historically Black College and University by Cortlyn Brown, Richard Carter, Nicholas Hartman, Aaryn Hammond, Emily MacNeill, Lynne Holden, Ava Pierce, Linelle Campbell, Marquita Norman

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Narrow band based and broadband derived vegetation indices using Sentinel-2 Imagery to estimate vegetation biomass by A.B. Imran, K. Khan, N. Ali, N. Ahmad, A. Ali, K. Shah

“…Forest’s ecosystem is one of the most important carbon sink of the terrestrial ecosystem. …”
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Leveraging survival analysis and machine learning for accurate prediction of breast cancer recurrence and metastasis by Shahd M. Noman, Youssef M. Fadel, Mayar T. Henedak, Nada A. Attia, Malak Essam, Sarah Elmaasarawii, Fayrouz A. Fouad, Esraa G. Eltasawi, Walid Al-Atabany

“…LightGBM, XGBoost, and Random Forest models were employed and validated against data from the Baheya Foundation. …”
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Soil health of bananas cultivated in Ribeira River Valley – the major producing region of Brazil by Cavalieri-Polizeli Karina Maria Vieira, da Silva Anderson Lucas, Cremonesi Marcus, Lima Juliana Domingues, Cipriano Patriciani Estela, Cherubin Maurício Roberto, Rozane Danilo Eduardo

“…Compared with natural forests, in general, banana crop soil showed elevated values of the chemical indicators, mainly due to the frequent fertiliser applications. …”
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Own Experience in the Use of Artificial Intelligence Technologies in the Diagnosis of Esophageal Achalasia by O. A. Storonova, N. I. Kanevskii, A. S. Trukhmanov, V. T. Ivashkin

“…The model with the best results was integrated into a web application.Results. The RandomForestClassifier was chosen as the best performing model to compare. …”
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Mallard Hybridization With Domesticated Lineages Alters Spring Migration Behavior and Timing by Nicholas W. Bakner, Nicholas M. Masto, Philip Lavretsky, Cory J. Highway, Allison C. Keever, Abigail G. Blake‐Bradshaw, Ryan J. Askren, Heath M. Hagy, Jamie C. Feddersen, Douglas C. Osborne, Bradley S. Cohen

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ARTEMISIA SIEVERSIANA WILLD. IN TRANSBAIKALIA: FEATURES OF CENOFLORA AND INTRASPECIFIC VARIABILITY by A. B. Sakhyaeva, B. B. Namzalov

“…In Transbaikalia,  A. sieversiana is differentiated into three morphotypes. With this, the forest-steppe type, if compared with the adventive and fallow forms, is distinguished by a set of morphological traits in its vegetative and  generative spheres, which may lead to its recognition as a separate botanical variety.…”
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Expecting the Unexpected: Predicting Panic Attacks From Mood, Twitter, and Apple Watch Data by Ellen W. McGinnis, Bryn Loftness, Shania Lunna, Isabel Berman, Skylar Bagdon, Genevieve Lewis, Michael Arnold, Christopher M. Danforth, Peter S. Dodds, Matthew Price, William E. Copeland, Ryan S. McGinnis

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Divergent Responses of Grassland Productivity to Large-Scale Atmospheric Circulations Across Ecoregions on the Mongolian Plateau by Cuicui Jiao, Xiaobo Yi, Ji Luo, Ying Wang, Yuanjie Deng, Xiao Guo

“…When considering seasonal variances, winter TCs dominated ANPP variations in the Selenge–Orkhon forest steppe, Daurian forest steppe, and Khangai Mountains alpine meadow ecoregions. …”
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Geographic information system and process-based modeling of soil erosion and sediment yield in agricultural watershed by G.R. Puno, R.A. Marin, R.C.C. Puno, A.G. Toledo-Bruno

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Compositional Characteristics and Antioxidant Activity of Edible Rose Flowers and Their Effect on Phenolic Urinary Excretion by Andrea Devecchi, Sonia Demasi, Francesca Saba, Rosalba Rosato, Roberto Gambino, Valentina Ponzo, Antonella De Francesco, Paola Massarenti, Simona Bo, Valentina Scariot

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Utilizing bioinformatics and machine learning to identify CXCR4 gene-related therapeutic targets in diabetic foot ulcers by Hengyan Zhang, Ye Zhou, Heguo Yan, Changxing Huang, Licong Yang, Yangwen Liu

“…Feature selection methods such as LASSO, SVM-RFE and random forest algorithm were applied to localize possible therapeutic target genes. …”
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Association between normal saline infusion volume in the emergency department and acute kidney injury in heat stroke patients: a multicenter retrospective study by Lan Chen, Junlu Zhao, Liyun Lu, Zhumei Gong, Shuying Xu, Xiaoling Yang, Yuping Zhang, Xiuqin Feng

“…Multivariate regression models, random forest imputation, and genetic and propensity score matching were used to explore the relationship between NS infusion and outcomes.Results The mean volume of NS infusion in the emergency department (ED) was 3.02 ± 1.45 L. …”
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Predictive model of acute kidney injury in critically ill patients with acute pancreatitis: a machine learning approach using the MIMIC-IV database by Shengwei Lin, Wenbin Lu, Ting Wang, Ying Wang, Xueqian Leng, Lidan Chi, Peipei Jin, Jinjun Bian

“…We performed feature selection using the random forest method. Model construction involved an ensemble of ML, including random forest (RF), support vector machine (SVM), k-nearest neighbors (KNN), naive Bayes (NB), neural network (NNET), generalized linear model (GLM), and gradient boosting machine (GBM). …”
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Exploring the restorativeness of different hydrodynamic landscapes in world natural heritage sites by Ping Zhang, Tongyao Zhang, Zexuan Chen, Qianyi He, Ke Luo, Jinpeng Li, Yanbin Yang, Qingjie Zhang, Xuan Wang, Limin Han, Mingze Chen, Fupei Zhao, Xiaoqing He, Saixin Cao, Xiaoqing Xu, Guangyu Wang, Xi Li

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