A Multilevel Inverter Bridge Control Structure with Energy Storage Using Model Predictive Control for Flat Systems by Paolo Mercorelli

“…The technique uses a “cascade model predictive control (MPC),” which consists of two MPCs. …”
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Predicting the risk of bone metastases in patients with newly diagnosed prostate cancer - Development and validation of a nomogram model. by Wei Xu, Guoyu Zhu, Xiaoxiang Wang, Xuebing Yan, Fujun Wang, Shanyi Li, Wenji Li

“…<h4>Objectives</h4>The aim of this study was to develop and validate a nomogram model that predicts the risk of bone metastasis (BM) in a prostate cancer (PCa) population.…”
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Fatigue life prediction of asphalt binders under variable loading levels based on dissipated pseudo-strain energy by Chenze Fang, Hui Li, Zhenxia Li, Yuanzhao Chen, Tengteng Guo

“…Miner’s criterion is popularized to develop the conventional fatigue life prediction model for estimating the service life corresponding to fixed loading level. …”
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A nomogram for predicting mortality risk in geriatric patients with hip fractures complicated by pneumonia: A multicenter study by Kaiming Zhang, Xiangwei Li, Yujia Xiao, Cheng Zhou, Yu Liu, Fan Zhen, Hao Zhang, Mao Nie

“…Multiple logistic regression was then used to identify independent risk factors for inpatient mortality in the P group and a nomogram was constructed to predict inpatient mortality. The predictive performance of the nomogram was assessed using receiver operating characteristic curves, decision curve analysis, and calibration curves. …”
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Comparative analysis of Sentinel-2 and PlanetScope imagery for chlorophyll-a prediction using machine learning models by Eden T. Wasehun, Leila Hashemi Beni, Courtney A. Di Vittorio, Christopher M. Zarzar, Kyana R.L. Young

“…On the other hand, the SVR model demonstrated better predictive performance for Chl-a concentration retrieval using PlanetScope (PS) data (R2 = 0.71, RMSE = 8.15 μg/l, bias = 0.46). …”
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Construction and Optimization of Integrated Yield Prediction Model Based on Phenotypic Characteristics of Rice Grown in Small–Scale Plantations by Jihong Sun, Peng Tian, Zhaowen Li, Xinrui Wang, Haokai Zhang, Jiangquan Chen, Ye Qian

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Application of GA-BP Neural Network Optimized by Grey Verhulst Model around Settlement Prediction of Foundation Pit by C. Y. Liu, Y. Wang, X. M. Hu, Y. L. Han, X. P. Zhang, L. Z. Du

“…Due to the limitation in the prediction of the foundation pit settlement, this paper proposed a new methodology which takes advantage of the grey Verhulst model and a genetic algorithm. …”
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Prediction of Adaptive Self-Regulatory Responses to Arthritis Pain Anxiety in Exercising Adults: Does Pain Acceptance Matter? by Miranda A Cary, Nancy C Gyurcsik, Lawrence R Brawley

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Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction by Xiaojie Huang, Jiajia Chen, Peineng Liu

“…This study introduces an explainable machine learning model to predict the risk of chemical transfer through human milk. …”
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Predictive model of positive attitudes in Spanish health care students towards older people: assessment and associated factors by Jesús González-Moreno, Ana Isabel Agustí, Javier Guillem-Saiz, María Antonia Parra-Rizo, María Antonia Parra-Rizo, María Cantero-García

“…However, this work aims to not only quantify these attitudes but to study other associated variables and develop a predictive model of positive attitudes toward the older people in a sample of Spanish university students of health care careers.MethodsA total of 338 students were surveyed using a sociodemographic questionnaire and two validated scales: the Spanish versions of the Kogan Scale of Attitudes toward Older People (KAOP) and the Global Assessment of Character Strengths-24 (GACS-24). …”
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Short‐Term Prediction of the Dst Index and Estimation of Efficient Uncertainty Using a Hybrid Deep Learning Network by Ruyao Wang, Jianhui Wang, Tuo Liang, Huixiong Zhang

“…Abstract In this study, we developed a novel deep learning model to predict the disturbance storm time (Dst) index 1–4 hr ahead. …”
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Online Traffic Accident Spatial-Temporal Post-Impact Prediction Model on Highways Based on Spiking Neural Networks by Duowei Li, Jianping Wu, Depin Peng

“…Traffic accident management as an approach to improve public security and reduce economic losses has received public attention for a long time, among which traffic accidents post-impact prediction (TAPIP) is one of the most important procedures. …”
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Methods for Predicting Speed of Sound in Fatty Acid Ethyl Esters and Ethylic Biodiesels Using Gibbs Energy Additivity by Natakron Sirimongkolgal, Mana Amornkitbamrung, Suriya Phankosol

“…This study presents Gibbs energy additivity methods for predicting the speed of sound in saturated or unsaturated fatty acids, ethyl ester, or an ethylic biodiesel based on either (1) the number of carbon atoms (z) and number of double bonds (nd) of the fatty acid or (2) the saponification number (SN) and iodine value (IV) of the fatty acid. …”
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Forecasting Uranium Resource Price Prediction by Extreme Learning Machine with Empirical Mode Decomposition and Phase Space Reconstruction by Qisheng Yan, Shitong Wang, Bingqing Li

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Can Clinical Measures of Postoperative Binocular Function Predict the Long-Term Stability of Postoperative Alignment in Intermittent Exotropia? by Yidong Wu, Meiping Xu, Junxiao Zhang, Jinjing Zhou, Minghui Wan, Zhiyue Dai, Tingting Peng, Seung Hyun Min, Fang Hou, Jiawei Zhou, Xinping Yu

“…To evaluate whether clinical measures of postoperative binocular functions could predict the long-term stability of postoperative ocular alignment in children with intermittent exotropia. …”
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Study on Fatigue Test and Life Prediction of Polyurethane Cement Composite (PUC) under High or Low Temperature Conditions by Hongshuai Gao, Quansheng Sun

“…Under temperature and external force coupling condition, a method for predicting fatigue life of PUC is proposed by the combination of theoretical deduction and experimental research. …”
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Twenty-Four-Hour Urinary Aldosterone Predicts Inappropriate Left Ventricular Mass Index in Patients with Primary Aldosteronism by Chi-Sheng Hung, Yi-Lwun Ho, Yi-Yao Chang, Vin-Cent Wu, Xue-Ming Wu, Jen-Kuang Lee, Shih-Chieh Chueh, Yen-Hung Lin, Yuan-Shian Changh, Shao-Yu Yang, Ya-Hui Hu, Ming-Jai Sui, Ming-Fong Chen, Kwan-Dun Wu

“…There is no ideal parameter to predict the presence of LVH or inappropriate LVH in patients with PA. …”
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Drug-Drug interactions prediction calculations between cardiovascular drugs and antidepressants for discovering the potential co-medication risks. by Tie Hua Zhou, Tian Yu Jin, Xi Wei Wang, Ling Wang

“…Predicting Drug-Drug Interactions (DDIs) enables cost reduction and time savings in the drug discovery process, while effectively screening and optimizing drugs. …”
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The potential of MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations: a systematic review and meta-analysis by Linyong Wu, Dayou Wei, Songhua Li, Shaofeng Wu, Yan Lin, Lifei Chen

“…Results Thirteen studies were ultimately included, with 2369 cases of metastatic NSCLC, including five studies predicting EGFR mutations in primary NSCLC, eight studies predicting EGFR mutations in metastatic NSCL. …”
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Use of data mining algorithms in prediction of eggshell thickness from egg quality traits of Potchefstroom Koekoek layers by Kagisho Madikadike Molabe, Thobela Louis Tyasi, Vusi Gordon Mbazima

“…MARS with R2(0.86) revealed yolk ratio, shell weight, egg shape index, yolk ratio, shell ratio, albumen weight and albumen ratio as explanatory variables predicting eggshell thickness. MARS had high r (0.925), R2 (0.856) and lower RMSE (0.129) and AIC (-975.331) compared to CHAID, Ex-CHAID and CART leading MARS to be the best data mining algorithm when predicting the eggshell thickness using egg quality traits.…”
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