Identification of heat tolerant lentil genotypes through stress tolerance indices by Rohit Sarkar, Gyan Prakash Mishra, Premakumar, Ankita Singh, Jenia Roy, Kumbarahally Murthigowda Shivaprasad, Shashidhar B. Reddappa, Sudhir Kumar, Ruchi Bansal, Uttarayan Dasgupta, Soma Gupta, Susheel Kumar Sarkar, Sanjeev Gupta, Shiv Kumar, Harsh K. Dikshit, Prachi Sripathrao Yadav, Muraleedhar S. Aski

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Characteristics of Soil Profile Greenhouse Gas Concentrations and Fluxes of Alpine Grassland as Affected by Livestock Grazing by Mingyuan Yin, Xiaopeng Gao, Yanyan Li, Yufeng Wu, Wennong Kuang, Fanjiang Zeng

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Challenges of Engineering Skillsets Essential for Driving Circularity of Smart Cities by Benjamin Neale, Sakdirat Kaewunruen, Dan Li, Ayfer Donmez Cavdar, Rand Askar, Tatjana Tambovceva, Diana Bajare

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Ratio-dependent competitions between a Wolbachia-uninfected bisexual strain and Wolbachia-infected thelytokous strain of the egg parasitoid, Trichogramma dendrolimi Matsumura (Hyme... by Qian-Jin Dong, Yue He, Yu-Zhe Dong, Wu-Nan Che, Jin-Cheng Zhou, Hui Dong

“…Abstract Background Wolbachia-infected thelytokous Trichogramma wasps have been considered as potential effective biocontrol agents against lepidopteran pests in agriculture and forests. However, intra-specific competition may arise when Wolbachia-infected thelytokous Trichogramma coexist with their uninfected bisexual counterparts in fields or during mass-rearing procedures. …”
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HPLC Analysis and Antioxidant Evaluation of Acteoside-Rich Osmanthus fragrans Extracts by Sung-Ho Lee, Seong-Wook Seo, Seung-Yub Song, Deuk-Sil Oh, Jung-Hyun Shim, Goo Yoon, Ye-Yong Choi, Do-Kyung Kim, Jae-Sung Kim, In-Soo Yoon, Seung-Sik Cho

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Diversity of Picea omorika (Pančić) Purk. Populations Based on Morpho-anatomical Needle Traits and Bioclimatic Parameters by Biljana Nikolić, Nemanja Rajčević, Zorica Mitić, Sanja Jovanović, Nevena Čule, Katarina Mladenović, Marija Marković, Petar Marin

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The relationship between complete blood cell count-derived inflammatory biomarkers and erectile dysfunction in the United States by Yi Zhang, Tingzhen Li, Qixin Chen, Maobiao Shen, Xinyang Fu, Changjin Liu

“…The prognostic significance of these CBC-derived inflammatory indicators was evaluated using random survival forests(RSF) analysis. Our study encompassed a cohort of 3,639 individuals, among whom 1,031 were diagnosed with ED. …”
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Rapid detection of carbapenem-resistant Escherichia coli and carbapenem-resistant Klebsiella pneumoniae in positive blood cultures via MALDI-TOF MS and tree-based machine learning... by Xiaobo Xu, Zhaofeng Wang, Erjie Lu, Tao Lin, Hengchao Du, Zhongfei Li, Jiahong Ma

“…This study was based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), Decision Tree (DT), Random Forest (RF), Gradient Boosting Machine (GBM), eXtreme Gradient Boosting (XGBoost), and Extremely Randomized Trees (ERT) models were constructed to classify carbapenem-resistant Escherichia coli (CREC) and carbapenem-resistant Klebsiella pneumoniae (CRKP). …”
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Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach by Tianshu Gu, Wensen Pan, Jing Yu, Guang Ji, Xia Meng, Yongjun Wang, Minghui Li

“…Results Decision Tree (DT) and Random Forest (RF) models consistently showed improvements in accuracy, precision, and ROC-AUC scores for Non-Hispanic Black, Hispanic/Latino, and Asian populations. …”
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Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the China health and retirement lo... by Qing Huang, Zihao Jiang, Bo Shi, Jiaxu Meng, Li Shu, Fuyong Hu, Jing Mi

“…Data preprocessing included missing value imputation via random forest. Feature selection was performed using the Least Absolute Shrinkage and Selection Operator (Lasso CV) method with cross-validation prior to model training. …”
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Agricultural land use conflict identification and land degradation risk analysis from the perspective of spatial matching in the Ili River Valley by DONG Guanglong, WANG Jue, WANG Han, CHENG Weiya, LIU Zheng, ZHANG Wenxin

“…The moderately sensitive, highly sensitive, and extremely sensitive areas were 3811.25, 3692.74, and 2683.44 km², respectively, which are mainly distributed in the northern part of Khorgos City, the southern part of Zhaosu County, and the northern part of Nilek County. (4) The high land degradation risk area covered 4200.92 km², accounting for 20.95% of the agricultural land use conflict area and 7.63% of the Ili River Valley, mainly distributed in the north, middle, and south Tianshan Mountains with rugged terrain and harsh natural environment making it suitable for woodland or mixed forest and grass. However, it’s current used as artificial pasture coupled with overgrazing has increased the risk of land degradation. …”
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A retrospective cohort study: do patients with graves’ disease need to be euthyroid prior to surgery? by Abrar Al Jassim, Tim Wallace, Sarah Bouhabel, Agnieszka Majdan, Michael Hier, Veronique-Isabelle Forest, Richard Payne

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Combining a Risk Factor Score Designed From Electronic Health Records With a Digital Cytology Image Scoring System to Improve Bladder Cancer Detection: Proof-of-Concept Study by Sandie Cabon, Sarra Brihi, Riadh Fezzani, Morgane Pierre-Jean, Marc Cuggia, Guillaume Bouzillé

“…MethodsThe first step relied on designing a predictive model based on clinical data (ie, risk factors identified in the literature) extracted from the clinical data warehouse of the Rennes Hospital and machine learning algorithms (logistic regression, random forest, and support vector machine). It provides a score corresponding to the risk of developing bladder cancer based on the patient’s clinical profile. …”
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Genetic Rescue of the Dinaric Lynx Population: Insights for Conservation From Genetic Monitoring and Individual‐Based Modelling by Elena Pazhenkova, Matej Bartol, Barbara Boljte, Urša Fležar, Andrea Gazzola, Tomislav Gomerčić, Marjeta Konec, Ivan Kos, Miha Krofel, Jakub Kubala, Ladislav Paule, Mihai Pop, Hubert Potočnik, Barbara Promberger, Robin Rigg, Teodora Sin, Magda Sindičić, Vedran Slijepčević, Astrid Vik Stronen, Ira Topličanec, Tomaž Skrbinšek

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Evaluating novel approaches for estimating awake and sleep blood pressure: design of the Better BP Study – a randomised, crossover trial by Paul Muntner, Ligong Chen, Daichi Shimbo, Joseph E Schwartz, Maria Cepeda, Demetria Hubbard, Suzanne Oparil, Byron C Jaeger, Shakia T Hardy, Julia Medina

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Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings by Mosbeh R. Kaloop, Abidhan Bardhan, Pijush Samui, Jong Wan Hu, Mohamed Elsharawy

“…Two deep learning methods viz deep belief network (DBN) and deep neural network (DNN), and five machine learning methods namely feedforward neural network, extreme learning machine, weighted extreme learning machine, random forest, and gradient boosting machine were evaluated, and compared in predicting the design wind pressures on tall buildings. …”
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River-groundwater transformation and ecological effects in the Tuwei River watershed by Jinxuan WANG, Yi WANG, Fan GAO, Xuanming ZHANG, Zhitong MA, Fan YANG

“…Under the control of geological and geomorphological conditions and the three-water transformation, the watershed can be spatially divided into lakes-shrub-grass-tree wet environment ecosystem, grass-shrub-tree-sand dry environment ecosystem, dwarf sparse forest-grass dry environment ecosystem, farmland-tree wet environment ecosystem, and riparian wet environment ecosystem. …”
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Wind and rainfall erosion energy in large sediment generating and coarse sediment class areas of the middle Yellow river by Tao Yang, Jianzhi Niu, Dengxing Fan, Di Wang, Yubo Miao, Miao Wang, Chunguang Zhao, Linus Zhang, Xiongwen Chen, Ronny Berndtsson

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Rainwater harvesting in arid and semi-arid lands of Africa: challenges and opportunities by Etienne Umukiza, Romain Ntole, Sylvester R. Chikavumbwa, Erion Bwambale, Davis Sibale, Zechariah Jeremaih, Ciro Apollonio, Andrea Petroselli

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Widely Targeted Metabolomics Analysis Reveals Key Quality-Related Metabolites in Kernels of Sweet Corn by Ruichun Yang, Yunfeng Li, Yuanyuan Zhang, Jun Huang, Junjie Liu, Zimei Lin, Qinqin Yu, Aimin Wu, Bo Wang

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