Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques by Uwe Knauer, Sebastian Warnemünde, Patrick Menz, Bonito Thielert, Lauritz Klein, Katharina Holstein, Miriam Runne, Wolfgang Jarausch

Get full text

Role of metabolites in mediating the effect of triacylglycerol on aplastic anemia by Jingkui Zhu, Wen Li

“…The precise mechanism and potential implications of lipid metabolism disorder in AA remain unclear, necessitating further studies in this area.Method This study aimed to examine the causal relationship between 38 different subtypes of triacylglycerols and AA using two-sample Mendelian randomization (MR). Additionally, two-step MR analyses were conducted to investigate the mediating effects of vitamin A to oleoyl-linoleoyl-glycerol (18:1–18:2) ratio.Results MR analysis showed that triacylglycerol (53:3) levels were positively associated with the risk of AA [inverse variance weighting (IVW): odds ratio (OR) = 1.131,95% confidence interval (CI):1.029-1.243, P = 0.011; Bayesian weighted MR (BWMR): OR = 1.137,95% CI:1.031-1.254, P = 0.010]. …”
Get full text

Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning anal... by Abhijeet Das

“…The research aims to fill the gap by considering a total of 13 surface water samples, which were collected and analyzed using standard methods. …”
Get full text

Causal relationship between lipidome and acute respiratory distress syndrome by Ruoyi Shen, Zhijiang Qi, Xu Huang, Jingen Xia, Qingyuan Zhan

“…Using summary-level data from a genome-wide association study (GWAS), a two-sample Mendelian randomization (MR) analysis of 179 genetically predicted lipid species and ARDS (375 cases, 406,518 controls) was performed and validated in plasma and pulmonary edema fluid from 24 patients. …”
Get full text

Classification of Apples (<i>Malus × domestica</i> <span style="font-variant: small-caps">borkh.</span>) According to Geographical Origin, Variety and Production Method Using Liqui... by Jule Hansen, Iris Fransson, Robbin Schrieck, Christof Kunert, Stephan Seifert

“…In this study, ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-ToF-MS) is applied in combination with random forest to 193 apple samples for the analysis of various authentication issues. …”
Get full text

Exploring spatial machine learning techniques for improving land surface temperature prediction by Arunab K.S., Mathew A.

“…The purpose of this study is to investigate the effects of including spatial information into the Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) models for forecasting LST. …”
Get full text

Dominant Tree Species Mapping Using Machine Learning Based on Multi-Temporal and Multi-Source Data by Heyi Guo, Sornkitja Boonprong, Shaohua Wang, Zhidong Zhang, Wei Liang, Min Xu, Xinwei Yang, Kaimin Wang, Jingbo Li, Xiaotong Gao, Yujie Yang, Ruichen Hu, Yu Zhang, Chunxiang Cao

“…The optimal input variable combination was explored using 1519 field survey samples for training and testing datasets. Classification employed Random Forest, XGBoost, and deep learning models, with performance evaluated through out-of-bag estimation and cross-validation. …”
Get full text

Activity prediction of anti-cancer drug candidate ERα inhibitor by XIA Yulan, XIE Jiming, WANG Yajing, LU Mengyuan, WANG Jinrui, QIN Yaqin

“…A quantitative structure-activity relationship prediction model is proposed to predict the bioactivity of compounds that can be applied to anti-breast cancer drugs under small samples and multi-characteristic conditions. First, the descriptive statistics and multicollinearity diagnosis are performed on the information of 729 molecular descriptors of 1 974 compounds, and the random forest method is used to screen 20 significant variables with variable importance measure that is greater than 0.01. …”
Get full text

Real-Time State Evaluation System of Antenna Structures in Radio Telescopes Based on a Digital Twin by Hanwei Cui, Binbin Xiang, Shike Mo, Wei Wang, Shangmin Lin, Peiyuan Lian, Wei Wang, Congsi Wang

“…Secondly, the quadric error metrics (QEM) mesh-simplification algorithm and mesh-reconstruction technology are employed to obtain a lightweight twin model of the antenna. Furthermore, a random forest (RF) regression surrogate model is established using finite element point cloud data samples. …”
Get full text

Characteristics and Clinical Significance of Gut Microbiota in Patients with Invasive Pulmonary Aspergillosis by CAO JIAQI, HE QIAN, ZHANG MING, ZHOU RONG, FENG CHUNLAI

“…We also built a random forest model for diagnosing IPA based on the gut microbiota. …”
Get full text

The Fungal Microbiome in the Vineyard Ecosystem Plays a Key Role in Shaping the Regional Characteristics of Wine by Chunyan Bai, Yuan Yao, Hua Wang, Hua Li, Ruteng Wei

“…In this study, soil, grape must, and fermentation samples were collected from Cabernet Sauvignon vineyards in five regions of China. …”
Get full text

MODEL VOLATILITAS GARCH(1,1) DENGAN ERROR STUDENT-T UNTUK KURS BELI EUR DAN JPY TERHADAP IDR by F. C. Salim, D. B. Nugroho, B. Susanto

“…Specifically, the draws are sampled using adaptive random walk Metropolis and independence chain Metropolis–Hastings (IC-MH) methods that constructed in the MCMC algorithm. …”
Get full text

Assessment of geotechnical behavior of gypseous soil under leaching effect using machine learning by Saif M. Hassan Al-Riahi, Nur Irfah Mohd Pauzi, Mohammed Y. Fattah, Hasan Ali Abbas

“…A synthetic dataset of 1000 samples was statistically generated using MATLAB to capture realistic variability in geotechnical properties. …”
Get full text

Copper and iron as unique trace elements linked to fibromyalgia risk by Wenxing Zeng, Minhua Hu, Luyao Ma, Feng Huang, Ziwei Jiang

“…This study employed Mendelian randomization (MR) to assess potential causal relationships between 15 major trace elements and the risk of FM, focusing on the specific roles of elements that show significant associations. …”
Get full text

Unmanned Aerial Vehicles Applicability to Mapping Soil Properties Under Homogeneous Steppe Vegetation by Azamat Suleymanov, Mikhail Komissarov, Mikhail Aivazyan, Ruslan Suleymanov, Ilnur Bikbaev, Arseniy Garipov, Raphak Giniyatullin, Olesia Ishkinina, Iren Tuktarova, Larisa Belan

Get full text

Model Development for Estimating Sub-Daily Urban Air Temperature Patterns in China Using Land Surface Temperature and Auxiliary Data from 2013 to 2023 by Yuchen Guo, János Unger, Tamás Gál

“…Space-related variables were more important under cold conditions (or nighttime) compared with warm conditions (or daytime), while time-related variables exhibited the opposite trend and were key to improving model accuracy in summer. Finally, two samples of Tair patterns in Beijing and the Pearl River Delta region were effectively estimated. …”
Get full text

Long-term alterations in gut microbiota following mild COVID-19 recovery: bacterial and fungal community shifts by Da Li, Da-Ya Zhang, Shi-Ju Chen, Yan-Ting Lv, Shi-Mei Huang, Chen Chen, Fan Zeng, Run-Xiang Chen, Xiao-Dong Zhang, Jian-Xin Xiong, Fa-Di Chen, Yue-Hong Jiang, Zhai Chen, Cui-Yi Mo, Jia-Jia Chen, Xu-Li Zhu, Li-Jun Zhang, Fei-Hu Bai, Fei-Hu Bai

“…A random forest model evaluated the predictive capacity of key taxa.ResultsThe gut microbiota of COVID-19 recoverees differed significantly from that of healthy individuals. …”
Get full text

Urban growth simulation using cellular automata model and machine learning algorithms (case study: Tabriz metropolis) by Omid Ashkriz, Babak Mirbagheri, Ali Akbar Matkan, Alireza Shakiba

“…To prevent over-fitting of algorithms to training samples and to obtain optimistic results, in the process of extracting optimal parameters of machine learning algorithms, the spatial cross-validation method was used to reduce the spatial correlation between training and test data.Results and discussion: The results showed that the random forest algorithm with the area under the ROC curve of 0.9228 compared to the support vector machine and multilayer perceptron neural network algorithms with 0.8951 and 0.8726, respectively, had a better performance in estimating the change potential of non-urban to urban areas. …”
Get full text

Wastewater-based epidemiology of influenza A virus in Shenzhen: baseline values and implications for multi-pathogen surveillance by Xiuyuan Shi, Shisong Fang, Chen Du, Guixian Luo, Yanpeng Cheng, Zhen Zhang, Qiuying Lv, Xin Wang, Zhigao Chen, Bincai Wei, Ziqi Wu, Bingchan Guo, Panpan Yang, Miaomiao Luo, Weihua Wu, Liping Zhou, Ting Huang, Xuan Zou, Xiaolu Shi, Songzhe Fu, Zhanwei Du, Xinxin Han, Yinghui Li, Qinghua Hu

“…Real-time PCR was employed to quantify IAV concentrations in wastewater samples from 38 treatment plants in Shenzhen, China (n = 2,764), collected weekly from March 2023 to March 2024. …”
Get full text

Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study by Huiyu Yao, Zixin Cao, Liangfu Huang, Haojie Pan, Xiaomin Xu, Fucai Sun, Xi Ding, Wan Wu

“…Serum levels of immunoglobulins (IgG, IgA, IgM), complements (C3, C4), vitamin B (VB1, VB2, VB3, VB5), serum zinc (Serum Zn), serum iron (Serum Fe), unsaturated iron-binding capacity (UIBC), total iron-binding capacity (TIBC), and iron saturation (Iron Sat) were measured and compared among groups. A Random Forest model was applied to analyze a dataset comprising 319 samples with eight key biomarkers. …”
Get full text