Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
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Clinical significance of plasma-free amino acids and tryptophan metabolites in patients with non-small cell lung cancer receiving PD-1 inhibitor: a pilot cohort study for developin... by Akihiko Kawahara, Tetsuro Sasada, Koichi Azuma, Hidenobu Ishii, Norikazu Matsuo, Takaaki Tokito, Tomoaki Hoshino, Yohei Miyagi, Huihui Xiang, Tomoyuki Tagami, Rika Kasajima, Yumiko Kato, Sachise Karakawa, Shinya Kikuchi, Akira Imaizumi, Kenta Murotani

“…Using Cox hazard analysis with these variables, a multivariate model was established to stratify patient overall survival (OS). …”
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不同种群元宝枫种仁含油率及脂肪酸组成分析与评价Analysis and evaluation of oil content in seed kernel and fatty acid composition of Acer truncatum from different populations... by 韩旻昊1，2，燕丽萍1，王因花1，任飞1，梁燕1，仲伟国1，孙超1，吴德军1 HAN Minhao1,2, YAN Liping1, WANG Yinhua1, REN Fei1, LIANG Yan1, ZHONG Weiguo1, SUN Chao1, WU Dejun1

“…The average coefficients of variation of oil content in seed kernel and various main fatty acid from Haiyang, Shandong(12.59%), Tai′an, Shandong(11.22%) and Jinan, Shandong(10.36%) were higher. …”
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Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

“…Based on this insight, the CRESO is formulated to estimate both state variables and total internal/external disturbances. …”
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International Natural Uranium Price Prediction Based on TF-CNN-BiLSTM Model by YANG Jingzhe, XUE Xiaogang

“…The study meticulously constructed and trained the TF-CNN-BiLSTM model using TensorFlow with the Adam optimizer and mean squared error loss function. The training process was optimized with learning rate reduction and early stopping callbacks to prevent overfitting. …”

Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…In this method, the number of membership functions is 5 functions representing very low, low, medium, high and very high. …”
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On a Solution of a Third Kind Mixed Integro-Differential Equation with Singular Kernel Using Orthogonal Polynomial Method by Ahmad Alalyani, M. A. Abdou, M. Basseem

“…The singular kernel is modified to take a logarithmic form, while the kernels of time are continuous and positive functions. Using the separation of variables technique, we have a system of Fredholm integral equations (FIEs) that can be transformed into an algebraic system after using orthogonal polynomials. …”
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Good Governance and Seigniorage in a Selected OPEC Countries and Iran by ALI Rashid Shamkhal, Kambiz Paykarjou, beitollah Akbari Moghaddam

“…Therefore, based on the results obtained from the analysis of responce functions in empirical analysis, it is essential to pay attention to changing and improving the methods of governance and administration of the country. …”
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Vibration Analysis of Rotating Tapered Timoshenko Beams by a New Finite Element Model by Bulent Yardimoglu

“…A new finite element model is developed and subsequently used for transverse vibrations of tapered Timoshenko beams with rectangular cross-section. The displacement functions of the finite element are derived from the coupled displacement field (the polynomial coefficients of transverse displacement and cross-sectional rotation are coupled through consideration of the differential equations of equilibrium) approach by considering the tapering functions of breadth and depth of the beam. …”
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Enhancing access to specialist appointments in tertiary healthcare in Shanghai, China: a structured reservation pathway using digital health technologies by Li Li, Tao Zheng, Enhong Dong, Minjie Chen, Xiaojing Zhao, Binyuan Zhang, Xuji Zhao, Weijun Shao, Yiling Fan

“…Objective The aim of this study is to develop, implement the precise reservation path (PRP) and investigate its prediction function for scheduling shunting patients for specialist appointment registration in Shanghai, China.Design The PRP system was built on the hospital’s existing information system, integrated with WeChat (WeCom) for user convenience. …”
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Changes in white matter predict efficacy of repetitive transcranial magnetic stimulation in Parkinson's disease by Jinying Han, Lingling Lv, Xin Chen, Mengqi Wang, Lili Hu, Fengbo Xing, Pingping Liu, Liuzhenxiong Yu, Ziye Zhao, Jinmei Sun, Tingting Liu, Jingjing Cheng, Minhao Zhu, Manman Gao, Gongjun Ji, Rong Ye, Kai Wang, Panpan Hu

“…Conclusion: Baseline WM function may serve as a biomarker for predicting motor response to cTBS.…”
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Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations by LIU Xiaolian, LI Zhenrong, WANG Xue-ni, ZHAI Yu, ZHANG Lei-ke, GUO Weiwei, TIAN Yu

“…Additionally, a Tent boundary mapping strategy was employed to regenerate the boundary value, resulting in improved the optimization efficiency of RUN. Six benchmark functions, including unimodal, multimodal and fixed dimension, were used to verify the performance and improvement strategies of TRUN. …”
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Peroral endoscopic myotomy for complex achalasia and the POEM difficulty score: An update by Carmen Ching Hui Yee, Michael Youssef, Matthew Woo, Robert Bechara

“…PDS correlates moderately with procedural efficiency with a correlation coefficient of 0.595 (Spearman's p < 0.001). …”
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Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model by E. Fatima, E. Fatima, R. Kumar, S. Attinger, S. Attinger, M. Kaluza, O. Rakovec, O. Rakovec, C. Rebmann, C. Rebmann, R. Rosolem, R. Rosolem, S. E. Oswald, L. Samaniego, L. Samaniego, S. Zacharias, M. Schrön

“…<p>Profound knowledge of soil moisture and its variability plays a crucial role in hydrological modelling to support agricultural management, flood and drought monitoring and forecasting, and groundwater recharge estimation. …”
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Clinical Outcome Prediction Model in Tetralogy of Fallot Without Pulmonary Valve Replacement Using Contraction Fraction From the SCOUT‐TOF Registry by Mark A. Fogel, Jennifer A. Faerber, Abdullah Mahmood, Keerthi Reddy, Xuemei Zhang, Elizabeth Goldmuntz, Matthew A. Harris, David Biko, Sara Partington, Stephen Paridon, Michael Mcbride, Victor Ferrari, Kevin K. Whitehead, Laura Mercer‐Rosa

“…An elastic net was used to identify significant variables to enter a best subsets logistic regression. …”
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Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model. by Rui Meng, Kristofer E Bouchard

“…The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. …”
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Low-frequency rTMS modulates small-world network properties in an AVH-related brain network in schizophrenia by Lin Zhang, Li Guo, Xiaohui Liu, Jing Han, Yuanqiang Zhu, Chaozong Ma, Ye Li, Weiliang Ye

“…Resting-state fMRI data were collected before and after treatment to assess functional connectivity within the predefined 35-region AVH-related network. small-worldness (σ), normalized clustering coefficient (γ), and normalized characteristic path length (λ), as well as functional segregation (clustering coefficient [Cp], local efficiency [El]) and functional integration (global efficiency [Eg], characteristic path length [Lp])—were analyzed before and after rTMS. …”
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Fuzzy System for the Quality Assessment of Educational Multimedia Edition Design by Vsevolod Senkivskyy, Liubomyr Sikora, Nataliia Lysa, Alona Kudriashova, Iryna Pikh

“…A multilevel model of fuzzy logical inference is constructed, representing the dependency between quality factors. Membership functions for linguistic variables are formed and their weight coefficients are determined using pairwise comparison matrices. …”
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Panoramic spatial enhanced resolution proteomics (PSERP) reveals tumor architecture and heterogeneity in gliomas by Ziyan Xu, Yunzhi Wang, Tao Xie, Rongkui Luo, Heng-Li Ni, Hang Xiang, Shaoshuai Tang, Subei Tan, Rundong Fang, Peng Ran, Qiao Zhang, Xiaomeng Xu, Sha Tian, Fuchu He, Wenjun Yang, Chen Ding

“…Abstract The spatial proteomic profiling of complex tissues is essential for investigating cellular function in physiological and pathological states. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…To further enhance model inputs, Variational Mode Decomposition (VMD) is applied to extract informative Intrinsic Mode Functions (IMFs) from the selected features. A comparative evaluation of the models indicates that recurrent neural networks, particularly GRU and LSTM, deliver superior performance across various metrics, including RMSE, MAE, nRMSE, nMAE, R², and the correlation coefficient. …”
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