Geographical origin identification of dendrobium officinale based on NNRW-stacking ensembles by Yinsheng Zhang, Chen Chen, Fangjie Guo, Haiyan Wang

“…Considering its therapeutic effect and price vary among different geographical origins, this paper proposed an origin identification method based on Raman spectroscopy and NNRW (neural network with random weights)-stacking ensemble model. In a case study of dendrobium officinale samples from three different geographical origins, we compare both single estimators, i.e., KNN (k-nearest neighbors), MLP (multi-layer perceptron), DTC (decision tree classifier), and NNRW, and their stacking ensemble counterparts. …”
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Binary Quasi-differential Stochastic Process Keying Modulation Scheme for Covert Communications by Z. J. Xu, S. Zhang, Z. W. Liu, J. L. Lin, X. S. Huang, Y. Gong

“…A pseudo-random sequence is introduced to eliminate the transmitted sequences' correlation. …”
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Modeling of Characteristics of Complex Microstructure and Heterogeneity at the Core Scale by Yiwei Chen, Pingchuan Dong

“…A comparative study of the measured data of five limestone and dolomite samples reveals that the P-wave prediction error of the new model is less than 5%, whereas the Biot model is less than 10%, implying that the prediction accuracy of the new model is better.…”
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Machine learning models for predicting the risk of depressive symptoms in Chinese college students by Chengfu Yu, Xiangxuan Kong, Weijie Yu, Xingcan Ni, Jing Chen, Xiaoyan Liao

“…Future studies should improve generalizability by incorporating more diverse samples and physiological biomarkers.…”
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Land use and land cover classification and change analysis in the area surrounding the Manglares Churute Ecological Reserve (Ecuador) using Sentinel-1 time series by D.A. Vélez-Alvarado, J. Álvarez-Mozos

“…Sentinel-1 scenes were processed and ground-truth data were collected consisting of samples of the main land-use/land-cover classes in the region. …”
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Modeling and mapping spatial distribution of baseline soil organic carbon stock, a case of West Hararghe, Oromia Regional State, Eastern Ethiopia by Martha Kidemu Negassa, Mitiku Haile, Gudina Legesse Feyisa, Lemma Wogi, Feyera Merga

“…The objective of this study was to produce a 30m-resolution digital map of SOC stock for selected districts in West Hararghe Zone of Ethiopia. 148 soil samples(0-30cm) were collected for SOC analysis and BD estimation. …”
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Predictive modeling of oil rate for wells under gas lift using machine learning by Famin Ma, Farag M. A. Altalbawy, Pinank Patel, R. Manjunatha, Rishiv Kalia, Shoira Formanova, P. Raja Naveen, Kamal Kant Joshi, Aashna Sinha, Abdolali Yarahmadi Kandahari, Taqi Mohammed Khattab Al-Rubaye, Mohammad Mahtab Alam

“…The dataset, comprised of 169 rigorously validated samples, includes key features such as basic sediment and water content, choke size, pressures, gas injection characteristics, gas lift valve depth, oil density, and temperature. …”
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Assessing the declining trend in soil erodibility across China: A comparison of conventional and digital K-factor maps by Zhiyuan Tian, Yan Zhao, Longxi Cao, Yuan Zhao, Yin Liang

“…For update, an investigation of 4262 samples from the soil series survey in the 2010s and a random forest regression model were used to generate a new K-factor map for China. …”
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Nonlinear characteristics and prediction of gas and temperature in coal spontaneous combustion oxidation process by Ping ZHAN, Changkui LEI, Renhui CHENG

“…To investigate the gas and temperature variation laws during coal spontaneous combustion oxidation and achieve accurate prediction of high-temperature points in coal spontaneous combustion, coal samples from Dafosi Coal Mine were collected for experimental research on coal spontaneous combustion. …”
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Two-tier classification framework for mapping grassland types using multisource earth observation data by Min Zhang, Wenzheng Yu, Ang Chen, Cong Xu, Jian Guo, Xiaoyu Xing, Dong Yang, Zichao Wang, Xiuchun Yang

“…In this framework, LC samples were automatically generated using existing LC products combined with vegetation indices and phenological features. …”
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Modelling Salmo trutta Complex Spatial Distribution in Central Italy: A Random Forest Approach Revealing Underrepresented Lowland Populations Based on Spatially‐Explicit Predictors... by Lorenzo Talarico, Elena Catucci, Marco Martinoli, Michele Scardi, Lorenzo Tancioni

“…Moreover, the prediction values (iii) expresses a remarkable positive monotone relationship with abundance classes of brown trout computed during field sampling, despite such information was not included in the model development. …”
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Hybrid Deep Learning Models Using LSTM with Random Forest for Radio Frequency-Based Human Activity Recognition in Line-of-Sight and Non-Line-of-Sight Environments by Niko Andriano, Feddy Setio Pribadi

“…This study proposes a hybrid deep learning model combining long short-term memory (LSTM) networks with Random Forest classifiers for RF-based HAR, aiming to improve recognition accuracy across diverse environments. …”
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Soil Organic Carbon Mapping Through Remote Sensing and In Situ Data with Random Forest by Using Google Earth Engine: A Case Study in Southern Africa by Javier Bravo-García, Juan Mariano Camarillo-Naranjo, Francisco José Blanco-Velázquez, María Anaya-Romero

“…This study, conducted within the SteamBioAfrica project, assessed the potential of Digital Soil Mapping (DSM) to estimate Soil Organic Carbon (SOC) across key regions of southern Africa: Otjozondjupa and Omusati (Namibia), Chobe (Botswana), and KwaZulu-Natal (South Africa). Random Forest (RF) models were implemented in the Google Earth Engine (GEE) environment, integrating multi-source datasets including real-time Sentinel-2 imagery, topographic variables, climatic data, and regional soil samples. …”
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Analysis of factors influencing hookwire dislodgement in CT-guided hookwire localization: a retrospective study using variable importance analysis with a random forest model by Kiook Baek, Jin Young Kim, Jung Hee Hong

“…Variables were compared using chi-square tests or Mann-Whitney tests. A random forest model, enhanced with the Synthetic Minority Over-sampling Technique (SMOTE) for oversampling, was employed to determine the relative importance of each variable. …”
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Efficacy of an intervention to increase therapeutic adherence in patients with secondary prevention for cardiovascular disease: a study protocol for a randomized controlled trial by Francisco Manuel Lidón-Muñoz, José Antonio Quesada, José Antonio Quesada, José Antonio Quesada, Vicente Francisco Gil-Guillén, Vicente Francisco Gil-Guillén, Vicente Francisco Gil-Guillén, Domingo Orozco-Beltrán, Domingo Orozco-Beltrán, Domingo Orozco-Beltrán

“…Furthermore, non-adherence is more pronounced in primary care.ObjectiveBased on our hypothesis that in patients undergoing cardiovascular secondary prevention, an intervention grounded in the application of the Chronic Care Model improves adherence to the three preventive drugs, this study aims to evaluate the efficacy of a health education intervention, which implements this model, to increase adherence in patients with cardiovascular disease.MethodsAn open-label randomized controlled trial will be conducted, selecting patients who meet inclusion criteria through consecutive non-probability sampling. …”
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RETRACTED: Tolerable random interruption duration based reliability estimation of stand alone hybrid renewable energy system by network reduction and sequential Monte Carlo simulat... by Atul S. Koshti, Aanchal Verma, Rajesh Arya, Chandrima Roy, Liladhar Arya, Sharat Chandra Choube, Baseem Khan

“…A sample SAHRES has been considered for the study.…”
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Preventing gambling-related harm among adolescents (PRoGRAM-A): an embedded multi-modal process evaluation in a pilot cluster random control trial by Martine Miller, Freya Howell, James White, Dave Griffiths, Leon Noble, Christopher J. Weir, Angela Niven, Andrew Stoddart, Hanna Ensor, Heather Wardle, Richard Purves, Fiona Dobbie

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Elucidating the causal associations and mechanisms between circulating immune cells and idiopathic pulmonary fibrosis: new insights from Mendelian randomization and transcriptomics by Han Yang, Xuanyu Wu, Xiang Xiao, Jiajing Chen, Xiaomin Yu, Wen Zhao, Fei Wang

“…Although studies have attempted to elucidate the causal relationship between the two, further clarification of the specific mechanisms and causal linkages is warranted.ObjectiveWe aimed to conduct a two-sample Mendelian randomization (MR) analysis with transcriptomics data analysis to elucidate the causal relationship between circulating immune cells and IPF and to explore potential biomarkers.MethodsWe first explored the bidirectional causal association between IPF and immune cell phenotypes using two-sample MR analysis. …”
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Efficacy and safety of tadalafil in a pediatric population with pulmonary arterial hypertension: phase 3 randomized, double‐blind placebo‐controlled study by Dunbar Ivy, Damien Bonnet, Rolf Berger, Gisela M.B. Meyer, Simin Baygani, Baohui Li, the LVHV Study Group

“…Primary endpoint was change from baseline in six‐minute walk distance in patients aged ≥6 years at Week 24. Sample size was amended from 134 to ≥34 patients, due to serious recruitment challenges. …”
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The impact of a multimodal intervention on physical health factors and lifestyle in patients with affective disorders – results from a randomized controlled trial by Ida Schou Ipsen, Rasmus Schwarz, Lars Vedel Kessing, Kamilla W. Miskowiak, Maj Vinberg

“…Study limitations include a modest sample size and a relatively short intervention duration. …”
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