Phylogeography and genetic diversity of Ulmus elongata (Ulmaceae), a Tertiary relict tree with extremely small populations (PSESP) by Yakun Wang, Xiankun Wang, Junyuan Wu, Jun Yang, Yanpei Liu, Peng Guo, Fude Shang, Nan Lin

“…Our findings also provide evidence for the important roles of East Asian monsoon system and climate oscillations in shaping the phylogeographic pattern in subtropical broad-leaved forests.…”
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Boron adsorption in semiarid Mediterranean soils under the influence of background electrolytes by S. Fatnassi, M.B. Almendro Candel, J. Navarro Pedreño, I. Gómez Lucas, M. Hachicha

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Effectiveness of canine‐assisted surveillance and human searches for early detection of invasive spotted lanternfly by Angela K. Fuller, Ben C. Augustine, Eric H. Clifton, Ann E. Hajek, Arden Blumenthal, Josh Beese, Aimee Hurt, Carrie J. Brown‐Lima

“…We modeled transect‐level occupancy of SLF as a function of infestation level, habitat type, topographic position index, and distance to forests. Occupancy probability of SLF was higher on vines within vineyards than in forests, and occupancy declined with increasing distance from forests, which is informative for future search efforts. …”
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Efficacy of Antimicrobial Photodynamic Therapy for Treating Moderate to Deep Periodontal Pockets in Individuals with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis by João Victor Soares Rodrigues, Mariella Boaretti Deroide, Wilton Mitsunari Takeshita, Valdir Gouveia Garcia, Rafael Scaf de Molon, Leticia Helena Theodoro

“…The principal periodontal parameters assessed included PPD, clinical attachment level (CAL), plaque index (PI), and bleeding on probing (BOP). Forest plots for PD, BOP, PI, and CAL at baseline, three months, and six months revealed no statistically significant differences between the SI+aPDT group and the SI-only group. …”
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Non-pharmacological interventions for the reduction and maintenance of blood pressure in people with prehypertension: a systematic review protocol by Paul Rutter, Andrew Clegg, Valerio Benedetto, Caroline Watkins, Nefyn Williams, Joseph Spencer, Lucy Hives, Emma P Bray, Cath Harris, Rachel F Georgiou, Nafisa Iqbal

“…Heterogeneity will be assessed through visual inspection of forest plots and the calculation of the χ2 and I2 statistics and causes of heterogeneity will be assessed where sufficient data are available. …”
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Pooled prevalence and associated factors of traditional uvulectom among children in Africa: A systematic review and meta-analysis. by Solomon Demis Kebede, Kindu Agmas, Demewoz Kefale, Amare Kassaw, Tigabu Munye Aytenew

“…Heterogeneity among the included studies was assessed using a forest plot, I2 statistics, and Egger's test, ensuring the robustness and reliability of the findings. …”
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Applying the Dempster–Shafer Fusion Theory to Combine Independent Land-Use Maps: A Case Study on the Mapping of Oil Palm Plantations in Sumatra, Indonesia by Carl Bethuel, Damien Arvor, Thomas Corpetti, Julia Hélie, Adrià Descals, David Gaveau, Cécile Chéron-Bessou, Jérémie Gignoux, Samuel Corgne

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EVALUATION OF THE ADAPTIVE PROPERTIES OF SPRING BARLEY VARIETIES ACCORDING TO THEIR YIELD CAPACITY IN THE ENVIRONMENTS OF THE NEAR-IRTYSH AREA IN OMSK PROVINCE by P. N. Nikolaev, P. V. Popolzukhin, N. I. Anisimov, O. A. Yusova, I. V. Safonova

“…The experimental part of the work was  carried out during 2011-2017, on the experimental fields of the  Siberian Research Institute of Agriculture, RAAS, located in the  southern forest-steppe in the vicinity of Omsk. The plot area was 10  m2, with 4 repetitions. …”
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Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia by Nani Cholianawati, Tiin Sinatra, Ginaldi Ari Nugroho, Didin Agustian Permadi, Asri Indrawati, Halimurrahman, Meta Kallista, Moch Syarif Romadhon, Ilma Fauziah Ma’ruf, Dipo Yudhatama, Tesalonika Angela Putri Madethen, Asif Awaludin

“…Meanwhile, the investigation on the extreme rise of PM2.5 in Pontianak due to peatland forest fires using HYSPLIT shows that emission from the surrounding area significantly raises the maximum half-hourly in Pontianak to 700 μg m−3.…”
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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study by Yunzhen Ye, Yu Xiong, Qiongjie Zhou, Jiangnan Wu, Xiaotian Li, Xirong Xiao

“…Eight common machine learning methods (GDBT, AdaBoost, LGB, Logistic, Vote, XGB, Decision Tree, and Random Forest) and two common regressions (stepwise logistic regression and logistic regression with RCS) were implemented to predict the occurrence of GDM. …”
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The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review by Ricardo Smits Serena, Florian Hinterwimmer, Rainer Burgkart, Rudiger von Eisenhart-Rothe, Daniel Rueckert

“…Furthermore, our analysis reveals the current dominance of machine learning models in 76% on the surveyed studies, suggesting a preference for traditional models like linear regression, support vector machine, and random forest, but also indicating significant growth potential for deep learning models in this area. …”
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Impact of #PCOSweightloss: A global X hashtag analysis study of weight loss narratives in the PCOS community by Munaza Afaq, Kumar Vashisht, Areen Al-Dhoon, Divya Abraham, Atanas G. Atanasov, Maima Matin, Zara Arshad, Rahul Kashyap, Faisal A. Nawaz

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Integrating machine learning and structure-based approaches for repurposing potent tyrosine protein kinase Src inhibitors to treat inflammatory disorders by Muhammad Waleed Iqbal, Muhammad Shahab, Zakir ullah, Guojun Zheng, Irfan Anjum, Gamal A. Shazly, Atrsaw Asrat Mengistie, Xinxiao Sun, Qipeng Yuan

“…Different machine learning models including random forest (RF), k-nearest neighbors (K-NN), decision tree, and support vector machine (SVM), were trained using already available bioactivity data of Src kinase targeting compounds. …”
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To Develop Biomarkers for Diabetic Nephropathy Based on Genes Related to Fibrosis and Propionate Metabolism and Their Functional Validation by Sha Li, Jingshan Chen, Wenjing Zhou, Yonglan Liu, Di Zhang, Qian Yang, Yuerong Feng, Chunli Cha, Li Li, Guoyong He, Jun Li

“…Second, the intersection of DN-DEGs, PM-DEGs, and FRGs was taken to yield intersected genes. Random forest (RF) and recursive feature elimination (RFE) analyses of the intersected genes were performed to sift out biomarkers. …”
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A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data by Nayoung Ro, Pilmo Sung, Mesfin Haile, Hyemyeong Yoon, Dong-Su Yu, Ho-Cheol Ko, Gyu-Taek Cho, Hee-Jong Woo, Nam-Jin Chung

“…This study addresses these limitations by employing an integrative approach combining hierarchical clustering, Principal Component Analysis–Linear Discriminant Analysis (PCA-LDA), and Random Forest (RF) to analyze the compiled morphological datasets. …”
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Variation characteristics and influencing mechanisms of CO2 flux from grassland ecosystem in the Central Tianshan Mountains, China by Kun Zhang, Yu Wang, Ali Mamtimin, Yongqiang Liu

“…Multiple environmental factors were integrated for an attribution analysis of CO2 flux using advanced systems, including random forest model, hyperbolic tangent model, future scenario simulation, and stepwise multiple regression model. …”
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Development of data-driven algal bloom alert models with low temporal resolution data and application to Hong Kong rivers by Shujie Xu, Zhongnan Ye, Shu-Chien Hsu, Xiaoyi Liu, Chunmiao Zheng

“…New hydrological insights for the region: Models that integrate data discretization outperformed those using numerical normalization, showing higher recall scores and greater stability across selected algorithms (linear regression, support vector machine, random forest, and decision tree). Permutation importance analysis identified nitrogen compounds and rising temperatures as key triggers of algal blooms, while false negative analysis highlighted total phosphorus and flow as critical factors. …”
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Specific shoot formation in Miscanthus sacchariflorus (Poaceae) under different environmental factors and DNA passportization using ISSR markers by O. V. Dorogina, N. S. Nuzhdina, G. A. Zueva, Yu. A. Gismatulina, O. Yu. Vasilyeva

“…., which has good prospects for growing under the conditions of the forest-steppe area in Western Siberia. The goals of our study were: (1) to determine the peculiarities of shoot formation, (2) to assess the cellulose and lignin accumulation in M. sacchariflorus populations under different lighting conditions and (3) to perform a DNA passportization of the Miscanthus population by ISSR marking. …”
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A CNN-RF Hybrid Approach for Rice Paddy Fields Mapping in Indramayu Using Sentinel-1 and Sentinel-2 Data by Dodi Sudiana, Mia Rizkinia, Rahmat Arief, Tiara De Arifani, Anugrah Indah Lestari, Dony Kushardono, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo

“…This study proposes the CNN-RF method, which combines a convolutional neural network (CNN) as a feature extractor and a random forest (RF) as a classifier. The experiment used combinations of input data, including variations of single and multisource data, to achieve optimal results. …”
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Long-Term Assessment of Soil Salinization Patterns in the Yellow River Delta Using Landsat Imagery from 2003 to 2021 by Yu Fu, Pengyu Wang, Wengeng Cao, Shiqian Fu, Juanjuan Zhang, Xiangzhi Li, Jiju Guo, Zhiquan Huang, Xidong Chen

“…In this study, we constructed and evaluated three soil salinization indices—NDSI, SI, and S5—using measured soil conductivity data and three machine learning methods: Random Forest, Support Vector Machine, and XGBoost. The results indicate that the Support Vector Machine achieved the best inversion effect on regional salinization levels, with an Area Under Curve (AUC) value of 0.88. …”
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