Quantification of Rear-End Crash Risk and Analysis of Its Influencing Factors Based on a New Surrogate Safety Measure by Qiangqiang Shangguan, Ting Fu, Junhua Wang, Rui Jiang, Shou’en Fang

“…This study provides a new surrogate safety measure that can better identify rear-end crash risks in a more reliable way and can be applied to real-time crash risk prediction in driver assistance systems. In addition, the results of this study can be used to provide a theoretical basis for the formulation of traffic management strategies to improve driving safety.…”
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Identification of Hydraulic Connection Points between Different Confined Aquifers in the Liyazhuang Coal Mine by Zhenghe Liu, Peiyun Zhao, Lusheng Yang, Jingui Zhao, Hailong Ye, Jun Yang, Rujun Mo

“…Determining the source of water inrush can facilitate its prediction and guide decisions regarding measures for prevention and control. …”
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Selective Ensemble Learning Method for Belief-Rule-Base Classification System Based on PAES by Wanling Liu, Weikun Wu, Yingming Wang, Yanggeng Fu, Yanqing Lin

“…This drastically decreases the prediction speed and increases the storage requirements for BRB systems. …”
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FEATURES OF THE MODEL OF A SPECIALIZED GEOSPATIAL DATABASE FOR VISUALIZING INDICATORS OF HUMAN SOCIO-ECONOMIC SECURITY IN WARTIME CONDITIONS by Zakharii S. Varnalii, Oleksii P. Fedchenko, Ihor V. Pampukha, Ihor V. Tolok

“…They enable the analysis of situations, the prediction of event developments, and the formulation of optimal action strategies. …”
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Psychological and Behavioral Insights From Social Media Users: Natural Language Processing–Based Quantitative Study on Mental Well-Being by Xingwei Yang, Guang Li

“…ConclusionsThe developed framework offers practical applications, such as accelerating hospital diagnoses, improving prediction accuracy, facilitating timely referrals, and providing actionable insights for early interventions in mental health treatment plans.…”
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Atom-Driven and Knowledge-Based Hydrolysis Metabolite Assessment for Environmental Organic Chemicals by Zhe Liu, Yufan Lin, Qi He, Lingjie Dai, Qinyan Tan, Binyan Jin, Philip W. Lee, Xiaoming Zhang, Li Zhang

“…For an external test set of 75 chemicals, the global hydrolysis site prediction model achieved an accuracy of 93%. Additionally, among 99 experimental hydrolysis products, our model successfully predicted 90, with a hit rate of 90%. …”
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Deteksi Cepat Kadar Alkohol Pada Minuman Kopi dengan Metode Dielektrik dan Jaringan Syaraf Tiruan by Sucipto Sucipto, Yuyun Rohmawati, Dyah Ayu Widyaningrum, Danang Triagus Setiyawan

“…The back propagation algorithm was used to connect the input of bioelectric properties and output of prediction of alcohol content and pH in liqueur coffee. …”
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Domestic water consumptions and associated factors in rural household of Harari region, Eastern Ethiopia; A cross sectional study by Bushra Yusuf Ahmed, Sina Temesgen Tolera, Liku Muche Temesgen, Abraham Geremew

“…Descriptive analysis was used to determine average total and per capita water consumption, while a multiple linear regression model allowed for the identification of associated factors and the prediction of water consumption with statistical significance.ResultDaily water consumption was found to be 103.3 L/hh/d and 17.6 L/c/d. …”
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Perceived costs and benefits of companion dog keeping based on a convenience sample of dog owners by Laura Gillet, Borbála Turcsán, Eniko Kubinyi

“…On average, positive statements were rated significantly higher (2.06) than negative ones (−0.66), supporting the prediction from social exchange theory that dog owners in a voluntary sample tend to perceive more advantages than disadvantages in dog ownership. …”
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Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction by Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L. Vincent, Garin N. Kessler, Boshu Ru, Mei Yang

“…An AUC of 0.861 was attained for prediction of 90-day readmission in patients aged 18-64. …”
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ERBB3-related gene PBX1 is associated with prognosis in patients with HER2-positive breast cancer by Shufen Mo, Haiming Zhong, Weiping Dai, Yuanyuan Li, Bin Qi, Taidong Li, Yongguang Cai

“…In addition, the risk model had better prognostic and predictive effects, and the immune infiltration analysis showed that IGHM, CXCL13 might affect the proliferation of BC cells through immune cells. …”
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Identification of the sex determination region and the development of a marker to distinguish males and females in megai abalone (Haliotis gigantea) by Taito Kina, Motoyuki Hara, Shotaro Hirase, Kiyoshi Kikuchi

“…Sex identification markers are of considerable value to aquaculture and fisheries as they enable pre-maturity prediction of the genotypic sex of individuals as well as of the sex ratio in offspring. …”
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Forecasting models for leprosy cases: a scoping review protocol by Bruna Oliveira Ascef, Gustavo Laine Araújo de Oliveira, Carmelita Ribeiro Filha Coriolano, Haliton Alves De Oliveira Junior

“…Various models for predicting leprosy cases have been reported in the literature, but they have different settings and distinct approaches to predicting the cases. …”
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Advanced NGS analysis of cell-free tumor DNA supports clonal relation to primary high-grade B-cell lymphoma lesion and CNS relapse despite MRI negativity by Veronika Navrkalova, Andrea Mareckova, Jakub Porc, Samuel Hricko, Viera Hrabcakova, Jarmila Kissova, Sona Kundova, Marie Jarosova, Sarka Pospisilova, Jana Kotaskova, Andrea Janikova

“…In clinical practice, such a minimally invasive approach provides a more sensitive tool than standard imaging and cell analyzing techniques, enabling more accurate disease monitoring and relapse prediction in particular cases.…”
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Estimation of Individual Tree Structure and Wood Density Parameters for <i>Ginkgo biloba</i> Using Terrestrial LiDAR and Resistance Drill Data by Ting Li, Xin Shen, Kai Zhou, Lin Cao

“…The feasibility of predicting the wood basic density based on wood resistance (R² = 0.51) and combined with DBH, tree height, and crown width (R² = 0.49) was relatively high. …”
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Computational Analysis of nsSNPs of ADA Gene in Severe Combined Immunodeficiency Using Molecular Modeling and Dynamics Simulation by Soukaina Essadssi, Al Mehdi Krami, Lamiae Elkhattabi, Zouhair Elkarhat, Ghita Amalou, Houria Abdelghaffar, Hassan Rouba, Abdelhamid Barakat

“…In this study, we performed a bioinformatics analysis of the human ADA gene to identify potentially harmful nonsynonymous SNPs and their effect on protein structure and stability. Using eleven prediction tools, we identified 15 nsSNPs (H15D, H15P, H17Q, H17Y, D19N, T26I, G140E, C153F, A183D, G216R, H258Y, C262Y, S291L, S291W, and K34OE) as harmful. …”
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A comprehensive review of the impacts of climate change on agriculture in Thailand by Muhammad Waqas, Adila Naseem, Usa Wannasingha Humphries, Phyo Thandar Hlaing, Muhammad Shoaib, Sarfraz Hashim

“…Climate forecasts indicate a significant increase in temperatures and more inconsistent, extreme rainfall, obfuscating the prediction of extreme weather events. The IPCC projects that by the end of the 21st century, temperatures in Thailand will rise by 0.95 ​°C–3.23 ​°C. …”
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Impact of the Westerly Jet on Rainfall/Runoff in the Source Region of the Yangtze River during the Flood Season by Xin Lai, Yuanfa Gong, Sixian Cen, Hui Tian, Heng Zhang

“…Based on runoff data collected at the Zhimenda station, reanalysis data from the National Centers of Environmental Prediction/National Centers of Atmospheric Research (NCEP/NCAR), and observation data from ground stations in China, this study analyzes the characteristics of changes in runoff in the source region of the Yangtze River (SRYR) during the flood season (from July to September), the relationship between runoff and antecedent rainfall, and the impact of the westerly jet (WJ) on rainfall in the coastal zone of the SRYR. …”
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Validating a novel measure for assessing patient openness and concerns about using artificial intelligence in healthcare by Bryan A. Sisk, Alison L. Antes, Sunny C. Lin, Paige Nong, James M. DuBois

“…The openness scale includes examples of AI‐driven tools for diagnosis, prediction, treatment selection, and medical guidance. …”
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A Review of the Modeling of Adsorption of Organic and Inorganic Pollutants from Water Using Artificial Neural Networks by Hilda Elizabeth Reynel-Ávila, Ismael Alejandro Aguayo-Villarreal, Lizbeth Liliana Diaz-Muñoz, Jaime Moreno-Pérez, Francisco Javier Sánchez-Ruiz, Cintia Karina Rojas-Mayorga, Didilia Ileana Mendoza-Castillo, Adrián Bonilla-Petriciolet

“…These artificial intelligence models have been utilized to correlate and predict kinetics, isotherms, and breakthrough curves of a wide spectrum of adsorbents and adsorbates in the context of water purification. …”
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