The implications of model formulation when transitioning from spatial to landscape ecology by Robert Stephen Cantrell, Chris Cosner, William F. Fagan

“…In this article we compare and contrast the predictions of some spatially explicit and implicit models in the context of a thought problem at the interface of spatial and landscape ecology. …”
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Advanced machine learning approach with dynamic kernel weighting for accurate electrical load forecasting by C. Jeevakarunya, V. Manikandan

“…Next, we compare these predictions’ performance measures, which has demonstrated the ability to generate highly ranked accuracy metrics.…”
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Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…Abstract Multiple linear regression models were trained to predict the degree of substitution (DS) of cellulose acetate based on raw infrared (IR) spectroscopic data. …”
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Infarct volume as a predictor and therapeutic target in post-stroke cognitive impairment by Lingjia Xu, Dan Shan, Danling Wu

“…In particular, infarct volume has been proposed as a potential target and may play a critical role in predicting and managing PISCI. We advocate for improved and timely predictions of PISCI to enhance the quality of life for patients and reduce the economic and emotional burden on caregivers.…”
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Geopolitical Risk and Stock Market Volatility in Emerging Economies: Evidence from GARCH-MIDAS Model by Menglong Yang, Qiang Zhang, Adan Yi, Peng Peng

“…However, the studies on whether and how these influences can explain and predict the volatility of stock returns in emerging markets are scant and emerging. …”
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Tsunami modelling over global oceans by Siva Srinivas Kolukula, P. L. N. Murty, T. Srinivasa Kumar, E. Pattabhi Ramarao, Ramana Murthy M. V

“…Computed results are compared with the observations, and it is found that the model’s predictions align well with the observations. The simulation results demonstrate that ADCIRC can be applied to real-time tsunami predictions due to its computational efficiency and accuracy.…”
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Modeling Compressive Strength of Self-Compacting Concrete (SCC) Using Novel Optimization Algorithm of AOA by Francisca Blanco, Ye Woo

“…The developed models were evaluated using several performance metrics, with results showing a strong correlation between predicted and actual values, achieving an R² of 97.3%. …”
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Detection of mental disorders other than depression with the Edinburgh Postnatal Depression Scale in a sample of pregnant women in northern Mexico by Cosme Alvarado-Esquivel, Antonio Sifuentes-Alvarez, Carlos Salas-Martinez

“…This threshold showed a sensitivity of 52.4%, a specificity of 67.0%, a positive predictive value of 11.5%, a negative predictive value of 95.4%, and an area under the curve of 0.643 (95% confidence interval: 0.52-0.76). …”
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Exploring ways to respond to rising obesity and diabetes in the Caribbean using a system dynamics model. by Leonor Guariguata, Leandro Garcia, Natasha Sobers, Trevor S Ferguson, James Woodcock, T Alafia Samuels, Cornelia Guell, Nigel Unwin

“…For obesity, it predicts prevalence to rise from 28.6% in 2018 to 32.1% by 2030 and 39.2% by 2050. …”
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Investigating the Compressibility of Sandy-Clay Soil in the Laboratory Soil Bin Caused by Agricultural Tire Traffic and Analyzed by the Adaptive Neuro–Fuzzy Inference System by Davood Kalantari, Mohammad Askari, Seyed Reza Mousavi-Seyedi, Nezamedin Asadi

“…Next, soil compaction was predicted under the influence of investigated parameters using ANFIS. …”
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Prognostic Factors and Nomograms for Overall and Cancer-Specific Survival of Patients with Uveal Melanoma without Metastases: A SEER Analysis of 4119 Cases by Xin Liu, Chang Liu, Yue Shang, Lin Yang, Fengling Tan, Yong Lv

“…To determine prognostic factors for patients with uveal melanoma without metastases and to construct nomograms to predict their 3- and 5-year overall survival (OS) and cancer-specific survival (CSS). …”
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An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks by Shun Zeng, Hongyu Chen, Rui Jing, Wenzhuo Yang, Ligong He, Tianle Zou, Peng Liu, Bo Liang, Dan Shi, Wenhao Wu, Qiusheng Lin, Zhenyu Ma, Jinhui Zha, Yonghao Zhong, Xianbin Zhang, Guangrui Shao, Peng Gong

“…In this study, a deep learning model (CBAM ResNet-18) was developed to predict the expression of these three receptors on mammography without manual segmentation of masses. …”
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Jinbei oral liquid for idiopathic pulmonary fibrosis: a randomized placebo-controlled trial by Aijun Zhang, Kangkang Han, Fangfang Chen, Xiao Chen, Jun Wang, Yikai Niu, Zhaoqiu Hu, Chunyan Zheng, Liping Han, Zhaoqing Meng, Liangzong Zhang, Qingcui Xu, Cuixiang Yu, Wei Zhang, Quanguo Li, Ningning Tao, Weixiang Kong, Fei Liu, Min Wang, Juanjuan Jiang, Honglin Li, LongBin Pang, Huaichen Li

“…To assess efficacy, over the duration of the trial, we measured serial changes in a composite indicator encompassing time to first acute exacerbation of IPF (first hospitalization or death due to respiratory cause), total lung capacity (TLC) (mL), predicted forced vital capacity (FVC%), forced vital capacity (FVC) (mL), predicted diffusing capacity of the lungs for carbon monoxide (predicted DLco%), 6-minute walk distance (6MWD), St. …”
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The Monocyte-to-Lymphocyte Ratio at Hospital Admission Is a Novel Predictor for Acute Traumatic Intraparenchymal Hemorrhage Expansion after Cerebral Contusion by Jiangtao Sheng, Tian Li, Dongzhou Zhuang, Shirong Cai, Jinhua Yang, Faxiu Ding, Xiaoxuan Chen, Fei Tian, Mindong Huang, Lianjie Li, Kangsheng Li, Weiqiang Chen

“…To explore the potential of monocyte-to-lymphocyte ratio (MLR) at hospital admission for predicting acute traumatic intraparenchymal hematoma (tICH) expansion in patients with cerebral contusion. …”
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Monetary policy shocks and multi-scale positive and negative bubbles in an emerging country: the case of India by Oguzhan Cepni, Rangan Gupta, Jacobus Nel, Joshua Nielsen

“…We use a nonparametric causality-in-quantiles approach to analyze the predictive impact of monetary policy shocks on bubble indicators. …”
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Investigation and Improvement of Bursting Force Equations in Posttensioned Anchorage Zone by Young Hak Lee, Min Sook Kim

“…Therefore, it is very important to predict the bursting force to determine appropriate reinforcement details. …”
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Evaluation of Production Line Modelling in Qualified Cardboard Production with Reliability Analysis by Aykut Güleryüz, Mehmet Yılmaz, Hüseyin Ünözkan

“…By calculating transition probabilities and employing Markov Chain and reliability analysis, it predicts long-term production capacity for the production line.Findings: It can predict long-term production expectations with high accuracy for a business with six production lines.Originality: The proposed model and method in this current study are capable of effectively addressing any production line problem where regular data is maintained.…”
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Social network information diffusion model based on user’s influence and interesting by Rui WANG, Yong LIU, Jing-hua ZHU, Ping XUAN, Jin-bao LI

“…A new non-topological information diffusion model of social network was proposed,called non-topological influence-interest diffusion model (NT-II).Representation learning was exploited to construct two hidden spaces for NT-II，called the user-influence space and the user-interest space,each user and each propagation item was mapped into a vector in space.The model predicted the probability of a user receiving a propagated item,considering not only the degree of influence from other users,but also the user's preference for propagated item.The experimental results show that the model can simulate the propagation process and predict the propagation results more accurately.…”
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Integrins identified as potential prognostic markers in osteosarcoma through multi-omics and multi-dataset analysis by Lei Cui, Shuai Zhao, Hai long Teng, Biao Yang, Qian Liu, An Qin

“…A novel machine learning framework combining 10 algorithms was developed to construct an Integrin-related Signature (IRS), which demonstrated robust predictive power across multiple datasets. The IRS’s utility in predicting overall survival was confirmed using data from The Cancer Genome Atlas, underscoring its potential in personalized cancer management.…”
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Dynamics Simulation Analysis for the Escapement Mechanism of the Mechanical Watch Movement by Chen Shijia, Chen Lin, Gong Xiang

“…Compared with the experimental data,the simulated results are able to predict the trend of the instantaneous daily rates in different driving torques in a moderate precision level. …”
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