Computational insights into the anti-diabetic potential of Albizia antunesiana (Mimosaceae) metabolites: A molecular docking, drug-likeness and ADMET analysis by Bitwell Chibuye, Indra Sen Singh, Luke Chimuka, Mokgaetji Monyai, Maseka Kenneth Kakoma

“…This study evaluates the antidiabetic potential of seven metabolites from the root of Albizia antunesiana (Mimosaceae) using molecular docking, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis. …”
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Precise Apple Yield Prediction Utilizing Differential Fusion of UAV and Satellite Multispectral Images by Meixuan Li, Xicun Zhu, Xinyang Yu, Cheng Li, Dongyun Xu, Ling Wang, Dong Lv, Yuyang Ma

“…This study provides a technical reference for multisource remote-sensing-based yield prediction in orchards.…”
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Study on the Structural Instability Characteristics of Interlayer Rock Strata During Mining Under Interval Goaf in Shallow Coal Seams by Bin Wang, Jie Zhang, Haifei Lin, Dong Liu, Tao Yang

“…Analysis suggests that the cutting instability of the IRS was the root cause of the increased AP in the working face of the lower coal seam. …”
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Establishment of predictive models for head loss and filtration efficiency of pontoon mesh rotary filter based on dimension analysis by Zhen Jin, Lingwei Chen, Qiao Li, Mahemujiang Aihemaiti, Youwei Jiang, Hongfei Tao

“…Predictive models for head loss and filtration efficiency were developed, with coefficients of determination R2 of 0.969 and 0.954, and root mean square error (RMSE) values of 0.1041 and 0.0183. …”
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Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults by Pathima Fairoosa, Pulani Lanerolle, Maduka De Lanerolle-Dias, V. Pujitha Wickramasinghe, Indu Waidyatilaka

“…Independent variables of the prediction equation were able to predict 88.5% of the variance. Root mean square error (RMSE) of the prediction equation in validation and cross-validation was 88.11 kcal/day and 79.03 kcal/day, respectively. …”
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Scaffold-level genome assembly of Fusarium neocosmosporiellum strain CA18-1 by Le Wang, Ruifang Jia, Jianjun Hao, Zhengqiang Chen, Xiaoluo Zhang, Na Wang, Shengze Wang, Yuanyuan Zhang, Kejian Lin

“…To explore the genetics of F. neocosmosporiellum, strain CA18-1 was isolated from infected alfalfa roots and subjected to whole-genome analysis. A scaffold-level reference genome of strain CA18-1 was assembled using both Nanopore long-read and Illumina short-read sequencing technologies. …”
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In silico analysis of Triphala-derived polyphenols as inhibitors of TIR–TIR homodimerization in the inflammatory pathway by Durgadevi Rajendran, Nalini Easwaran

“…The MD trajectory revealed that polyphenol binding enhanced the stability of the target protein, as indicated by lower root-mean-square deviation (RMSD) (∼0.25 nm), solvent accessible surface area (SASA) (∼96.848–100.666 nm2), and stabilized radius of gyration (Rg) (∼1.50–1.53 nm) values for punicalagin and chebulagic acid complexes compared to the reference complex. …”
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Comparison of Essential Oil Components and <i>In Vitro</i> Antioxidant Activity of <i>Zanthoxylum nitidum</i> from Different Parts by Yang Yang, Yanqun Li, Hanjun He, Leilei Yang, Jiaxin Zeng, Mei Bai, Hong Wu

“…The leaf essential oil has the highest <i>in vitro</i> antioxidant activity, followed by the root, pericarp, and stem. This study aims to provide a scientific reference for the rational development and utilization of different parts of <i>Z. nitidum</i>, especially the leaf essential oil.…”
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A rolling bearing life prediction method based on multi-task gated networks by Liuyang SONG, Chuanhao ZHENG, Ye JIN, Tianjiao LIN, Changkun HAN, Huaqing WANG

“…ConclusionThe proposed method can achieve the prediction of the remaining life of bearings and has certain reference value for the health management and intelligent operations and maintenance (O&M) of ship mechanical equipment.…”
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Comparing the accuracy of 3D-printed casts versus plaster casts for tooth-supported and implant-supported restorations by Hedie Derakhshi, Mohammad Alihemmati, Seyed Mohammad Reza Hakimaneh, Mohammad Amin Bafandeh, Maryam Jahangiri, Sayed Shojaedin Shayegh

“…As a result, the Kruskal–Wallis H test, a nonparametric method, was employed to compare root mean square (1 RMS = 100 μm) values across three groups. …”
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An Empirical Comparison of Urban Road Travel Time Prediction Methods—Deep Learning, Ensemble Strategies and Performance Evaluation by Yizhe Wang, Yangdong Liu, Xiaoguang Yang

“…The research results provide empirical reference for method selection in urban road travel time prediction, while also revealing the limitations of single data sources and the differences in model performance under different evaluation metrics, offering directions for future research.…”
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Probabilistic Site Adaptation for High-Accuracy Solar Radiation Datasets in the Western Sichuan Plateau by Lianlian Ye, Mengqi Liu, Disong Fu, Hao Wu, Hongrong Shi, Chunlin Huang

“…Systematic quantification reveals inherent errors with root mean square errors (RMSEs) > 200 W/m² across all datasets. …”
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HEVERL – Viewport Estimation Using Reinforcement Learning for 360-degree Video Streaming by Nguyen Viet Hung, Pham Tien Dat, Nguyen Tan, Nguyen Anh Quan, Le Thi Huyen Trang, Le Mai Nam

“…Additionally, it reduces the Root Mean Square Error (RMSE) by 0.008 to 0.013, the Mean Absolute Error (MAE) by 0.012 to 0.018 and the F1-score by 0.017 to 0.028. …”
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Performance analysis of ultra-wideband positioning for measuring tree positions in boreal forest plots by Zuoya Liu, Harri Kaartinen, Teemu Hakala, Heikki Hyyti, Juha Hyyppä, Antero Kukko, Ruizhi Chen

“…The experimental results show that UWB data-driven method is able to map individual tree locations accurately with total root-mean-squared-errors (RMSEs) of 0.17 m, 0.2 m, and 0.26 m for “Easy”, “Medium” and “Difficult” forest plots, respectively, providing a strong reference for forest surveys.…”
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China Earth Observation Data Cube: The 30-m Seamless Annual Leaf-On Landsat Composites from 1985 to 2023 by Yaotong Cai, Xing Li, Peng Zhu, Sheng Nie, Cheng Wang, Xiaoping Liu, Yuhe Chen

“…To address this, we applied segmented linear interpolation to generate proxies, which we validated for stability, achieving high consistency with actual Landsat references for both stable and dynamic pixel sequences (r = 0.77 to 0.99, root mean square error [RMSE] = 0.0043 to 0.0232). …”
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Improving large-scale snow albedo modeling using a climatology of light-absorbing particle deposition by M. Gaillard, M. Gaillard, V. Vionnet, M. Lafaysse, M. Dumont, P. Ginoux

“…Optimized values for multi-year snow albedo simulations with Crocus were generated at 10 reference experimental sites spanning a large variety of climates across the world. …”
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Positive Role of <i>Trichoderma harzianum</i> in Increasing Plant Tolerance to Abiotic Stresses: A Review by Yueyao Geng, Shuying Chen, Pinke Lv, Yankai Li, Jingxuan Li, Fangling Jiang, Zhen Wu, Qirong Shen, Rong Zhou

“…<i>T. harzianum</i> can also improve plant nutrient uptake and root development, secondary metabolism, soil environment and structure, and expression of related genes. …”
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Development of the Maladaptive Eating Behavior Questionnaire after Bariatric Metabolic Surgery and test of its reliability and validity by YANG Ningli, HUA Hongxia, LIANG Hui

“…Objective To develop a scientifically sound and standardized Maladaptive Eating Behavior Questionnaire after Bariatric Metabolic Surgery （MEBQBS）， and to test its reliability and validity， providing a reference for early identification of maladaptive eating behaviors in post-bariatric patients. …”
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Shipborne comparison of infrared and passive microwave radiometers for sea surface temperature observations by G. Gacitúa, J. Lorentsen Høyer, S. Schmidl Søbjærg, H. Shi, S. Skarpalezos, I. Karagali, E. Alerskans, C. Donlon

“…A linear regression algorithm was developed using IR SST data as a reference to derive PMW SST from brightness temperature. …”
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Large-Scale Completion of Ionospheric TEC Maps Using Machine Learning Models With Constraints Conditions by Qingfeng Li, Hanxian Fang, Chao Xiao, Die Duan, Hongtao Huang, Ganming Ren

“…Results show that the CGVAE-label model excels in TEC completion, achieving a mean structural similarity of 93.80% and a root mean square error of 2.20 TECU. It outperforms the baseline CGVAE model, particularly in reconstructing peak ionospheric structures. …”
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