A Study of the Soil–Wall–Indoor Air Thermal Environment in a Solar Greenhouse by Zhi Zhang, Yu Li, Liqiang Wang, Weiwei Cheng, Zhonghua Liu

“…The CFD model and LSTM prediction model have been shown to be superior, and the findings of this study offer a theoretical basis for the optimization of thermal environment control in solar greenhouses.…”
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Forecasting Urban Sprawl Dynamics in Islamabad: A Neural Network Approach by Saddam Sarwar, Hafiz Usman Ahmed Khan, Falin Wu, Sarah Hasan, Muhammad Zohaib, Mahzabin Abbasi, Tianyang Hu

“…Utilizing a land change modeler (LCM), forecasts of the future conditions in 2025, 2030, and 2035 are predicted. The artificial neural network (ANN) model embedded in IDRISI software 18.0v based on a well-defined backpropagation (BP) algorithm was used to simulate future urban sprawl considering the historical pattern for 2015–2020. …”
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A Coupled Least Absolute Shrinkage and Selection Operator–Backpropagation Model for Estimating Evapotranspiration in Xizang Plateau Irrigation Districts with Reduced Meteorological... by Qiang Meng, Jingxia Liu, Fengrui Li, Peng Chen, Junzeng Xu, Yawei Li, Tangzhe Nie, Yu Han

“…Short-term ET_O predictions for the three districts were also conducted using the mean-generating function optimal subset regression algorithm. …”
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Single-cell and bulk transcriptome analyses reveal elevated amino acid metabolism promoting tumor-directed immune evasion in colorectal cancer by Tianyue Sun, Yan Chen, Ying-Xuan Chen

“…Additionally, LASSO and Cox regression analyses were conducted to construct an AA metabolism-related risk score for predicting prognosis and drug sensitivity across multiple bulk transcriptome cohorts.ResultsThis study identified a link between elevated amino acid metabolism in CRC epithelial cells and resistance to PD-1 blockade therapy. …”
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Assessment of the Maize Crop Water Stress Index (CWSI) Using Drone-Acquired Data Across Different Phenological Stages by Mpho Kapari, Mbulisi Sibanda, James Magidi, Tafadzwanashe Mabhaudhi, Sylvester Mpandeli, Luxon Nhamo

“…This study used a unmanned aerial vehicle (UAV) to remotely collect data, to use in combination with the random forest regression algorithm to detect the maize CWSI in smallholder croplands. …”
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Relationship of transforming growth factor β1 with diabetic retinopathy in type 2 diabetes by A.S. Hudz, V.A. Serhiyenko, I.V. Kudryl, V.G. Guryanov, M.I. Kovtun, S.V. Ziablitsev

“…A three-factor classification model was created on the identified features, which included a system of equations that predicted PDR with 100% accuracy. The overall prediction accuracy of the model was 88.2 % (95% CI 80.4–93.8 %). …”
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H-NMR metabolomics identifies three distinct metabolic profiles differentially associated with cardiometabolic risk in patients with obesity in the Di@bet.es cohort by Enrique Ozcariz, Montse Guardiola, Núria Amigó, Sergio Valdés, Wasima Oualla-Bachiri, Pere Rehues, Gemma Rojo-Martinez, Josep Ribalta

“…In addition, H-NMR metabolomics improved the prediction of future cardiometabolic disease in comparison with models relying on just anthropometric measures. …”
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Simulation and Modelling of C+L+S Multiband Optical Transmission for the OCATA Time Domain Digital Twin by Prasunika Khare, Nelson Costa, Marc Ruiz, Antonio Napoli, Jaume Comellas, Joao Pedro, Luis Velasco

“…Being able to predict the optical signal in the time domain, as it will be received after propagation, opens opportunities for automating network operation, including connection provisioning and failure management. …”
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Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients by Jacob C. Jentzer, Eunjung Lee, Zachi Attia, Dustin Hillerson, Garvan C. Kane, Francisco Lopez‐Jimenez, Peter A. Noseworthy, Paul A. Friedman, Jae K. Oh

“…An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been examined in cardiac intensive care units. …”
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Market and cadastral data comparison for the real estate market value forecasting by M. B. Laskin, P. A. Cherkesova

“…The theoretical significance of the work is the proposed algorithm for estimating the most probable trajectory of the market value of the investigated object, based on the conditional multivariate log-normal distribution for a given value of the cadastral value. …”
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Stepwise autonomous orbit determination of large LEO constellations by GNSS observations with partial inter-satellite ranging by Yuanxi Yang, Xiaoyong Song

“…The difference of the adaptive stepwise OD algorithm is that the covariance matrix of the predicted orbit parameters based on the dynamic model is modified by an adaptive factor. …”
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Research on Non-Random Vibration Analysis of Concrete Pump Truck Boom Based on Dynamic Excitation by Weixin Zhou, Wubin Xu, Bing Li, Yuanbin Xiao, Xianyu Liu, Hanwen Zhang, Bo Xu

“…The technique can reliably predict the dynamic displacement boundary and control the casting position deviation within a predefined range by accurately predicting the dynamic displacement range of the pump truck’s boom end and efficiently constructing the displacement envelope under uncertain dynamic excitation. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Thus, scientifically assessing and predicting geological disasters and formulating disaster prevention and mitigation policies are of critical importance for promoting regional sustainable development. …”
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Multi-objective optimization of sustainable cement-zeolite improved sand based on life cycle assessment and artificial intelligence [version 1; peer review: 1 approved, 2 approved... by Hossein MolaAbasi, Satinder Kaur Brar, Amin Tanhadoust, Sepideh Nasrollahpour, Omolbanin Ataee, Moncef L. Nehdi

“…This study proposes a multi-objective optimization approach using back-propagation neural network (BPNN) to predict the mechanical strength, along with an adaptive geometry estimation-based multi-objective evolutionary algorithm (AGE-MOEA) to identify the best parameters for cement-zeolite-improved sand, filling a long-lasting research gap. …”
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Increasing Systemic Resilience to Socioeconomic Challenges: Modeling the Dynamics of Liquidity Flows and Systemic Risks Using Navier–Stokes Equations by Davit Gondauri, Nino Chedia, Vakhtang Tsintsadze

“…The methodology is based on a mixed approach: econometric testing, Fourier analysis, stochastic simulations, and AI-algorithm tuning, which together provide dynamic testing, calibration, and forecasting capabilities of the model. …”
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Cer(d18:1/16:0) as a biomarkers for acute coronary syndrome in Chinese populations by Liang Zhang, Yang Zhang, YaoDong Ding, Tong Jin, Yi Song, Lin Li, XiaoFang Wang, Yong Zeng

“…Diagnostic performance assessments showed that Cer(d18:1/16:0) had superior accuracy in detecting ACS compared to other ceramides tested. The Boruta algorithm identified 8 significant variables related to ACS. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…These findings, supported by the FLOW-AF trial, underscore the usefulness of clinical outcome-based machine learning to improve the efficacy of algorithm based medical diagnostics.…”
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Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets by Lechen Yang, Weifeng Shang, Dongjie Chen, Hang Qian, Sheng Zhang, Xiaojun Pan, Sisi Huang, Jiao Liu, Dechang Chen

“…Differentially expressed genes (DEGs) analysis, pathway enrichment, transcription factor (TF) prediction, intercellular communication, and trajectory inference were used to explore the role of propionate metabolism in sepsis. …”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…Constructing an intelligent and precise disaster management system for coal mines helps improve the accuracy of accident prediction and early warning, enabling intelligent risk assessment. …”
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Peningkatan Performa Ensemble Learning pada Segmentasi Semantik Gambar dengan Teknik Oversampling untuk Class Imbalance by Arie Nugroho, M. Arief Soeleman, Ricardus Anggi Pramunendar, Affandy Affandy, Aris Nurhindarto

“…The use of synthetic oversampling techniques can improve the level of accuracy in minority classes. The random forest algorithm experienced an increase in accuracy by 37% while the LGBM algorithm increased by 41%. …”
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