Investigation of Metoprolol Concentrations in Plasma Using Automated Sample Preparation and LC-MS/MS Detection by Ionel-Bogdan Cioroiu, Mona-Elisabeta Dobrin, Marius Niculaua, Constantin-Bogdan Nechita, Valeriu V. Cotea

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Psychometrics properties of the Team Interaction Scale and influencing factors of team interaction of tertiary hospital physicians in China: a cross-sectional study by Ning Ding, Deliang Wen, Wenwen Song, Honghe Li, Weiyue Zhao, Lin Shi

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A Meta-Analysis of Studies on Quality Assessment of Public Libraries Using the LibQUAL Model by Reza Karimi, Mohammad Asadzadehbaghi

“…Additionally, given the substantial sample size and low error rate in studies on these three variables according to Cohen's d index, the findings of research on public libraries using the LibQUAL tool can be considered highly reliable. …”
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Engineering Safety-Oriented Blasting-Induced Seismic Wave Signal Processing: An EMD Endpoint Suppression Method Based on Multi-Scale Feature by Miao Sun, Jing Wu, Yani Lu, Fangda Yu, Hang Zhou

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The Impact of Flow Channel Structural Parameters on Both the Hydraulic Performance and Anticlogging Abilities of Variable Flow Emitters by Peining Niu, Yan Mo, Baolin Yao, Zongze Yang, Yanqun Zhang, Dequan Zhang

“…The <i>nRMSE</i> between the measured (<i>q</i>_m) and simulated (<i>q</i>) values of the flow rate is 11.23%, and the <i>relative error</i> between the measured (<i>x</i>_m) and simulated (<i>x</i>) values of the flow index is 4.66%, which gives a high simulation accuracy. …”
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Changes in Brain Activity and Functional Connectivity During Spinal Nerve Stimulation in a Rat Model of Overactive Bladder by Haoyu Sun, Yongheng Zhou, Qinggang Liu, Xing Li, Limin Liao

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Debriefing Methodologies in Nursing Simulation: An Exploratory Study of the Italian Settings by Sonia Lomuscio, Emanuele Capogna, Stefano Sironi, Marco Sguanci, Sara Morales Palomares, Giovanni Cangelosi, Gaetano Ferrara, Stefano Mancin, Antonio Amodeo, Anne Destrebecq, Mauro Parozzi, Susy Dal Bello

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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…The outcomes of our study are particularly noteworthy, with the model demonstrating remarkably low Mean Squared Error (MSE) values across all data clusters, ranging from 0.011 to 0.072. …”
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Blackberry Growth Monitoring and Feature Quantification with Unmanned Aerial Vehicle (UAV) Remote Sensing by Akwasi Tagoe, Alexander Silva, Cengiz Koparan, Aurelie Poncet, Dongyi Wang, Donald Johnson, Margaret Worthington

“…The objective of the research was to develop a methodology for accurate measurement of blackberry flowers and vegetation coverage using UAV remote sensing and image analysis. …”
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Forestry and economic growth in Ghana: evaluating the dynamics using the environmental Kuznets curve and adjusted net savings by Joseph Antwi Baafi, Kwame Acheampong, Michael Kwame Asiedu, Pearl Seyram Kumah

“…It applied quantitative techniques, including regression, vector error correction model and multiple Granger causality to examine the impact of GDP growth, adjusted net savings (ANS) and other control variables on Ghana’s deforestation rate. …”
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Advancements in predicting soil liquefaction susceptibility: a comprehensive analysis of ensemble and deep learning approaches by Divesh Ranjan Kumar, Warit Wipulanusat

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<monospace>TWIRLD</monospace>: Transformer Generated Terahertz Waveform for Improved Radio Link Distance by Shuvam Chakraborty, Claire Parisi, Dola Saha, Ngwe Thawdar

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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…The experimental outcomes highlight significant advancements in convergence rates and error reduction, particularly in complex models like 3-layer-wrapped Bidirectional Long Short-Term Memory (3wBiLSTM). …”
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Downscaling Satellite Night-Time Light Imagery While Addressing the Blooming Effect by Nikolaos Tziokas, Ce Zhang, Alexandros Tziokas, Qunming Wang, Peter M. Atkinson

“…Nevertheless, the full potential of NTL data for urban research is constrained by a relatively coarse spatial resolution and the blooming effect. …”
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Cervical cancer demystified: exploring epidemiology, risk factors, screening, treatment modalities, preventive measures, and the role of artificial intelligence by N. Mohammad, M. Khan, M. Maqsood, A. H. K. Naseeb

“…These innovations have the potential to enhance diagnostic accuracy, reduce human error, and improve patient outcomes, particularly in resource-limited settings. …”
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Integrated Energy System Load Forecasting Based on Multi-energy Demand Response and Improved BiLSTM by ZHANG Xiaojia, WANG Can, ZHANG Jiaheng, WANG Zhen, LI Zhiwei, ZHANG Zhaoyang, GAN Youchun

“…[Results] Compared with the multiload forecasting method without considering the demand response， the mean absolute percentage error of the electricity， heat， and cooling loads was reduced by 6.59%， 13.04%， and 24.86%， respectively. …”
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Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression by Raphael Uwamahoro, Raphael Uwamahoro, Kenneth Sundaraj, Farah Shahnaz Feroz

“…Yet, the lack of direct muscle strength measurement techniques has prompted previous research to deploy joint torque estimation using machine learning models. …”
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Enhancing building energy efficiency with thermal mass optimization by Yichen Han, Zhengyu He, Shuangdui Wu, Yuqiu Liu, Yingkai Lian, Chaohong Wang, Jiajia Feng, Zhengnan Zhou

“…These strategies were then validated in cold regions using conduction transfer function models (error margin of 3.6 %), which confirmed their year-round effectiveness for both individual buildings with distinct occupancy patterns and groups of buildings. …”
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WRF-Based Wind Assimilated With SAR Measurements: With Application of Wave Simulation by WW3 During Tropical Cyclone by Weizeng Shao, Lingdong Zhang, Yuyi Hu, Yashi Zhou, Qingjun Zhang

“…Wind speeds from WRF model are compared with SFMR measurements yields a root mean squared-error (RMSE) of 3.48 m&#x002F;s and a correlation (Cor) of 0.89. …”
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Machine learning for automated cause-of-death classification from 2021 to 2022 in Korea: development and validation of an ICD-10 prediction model by Seokmin Lee, Gyeongmin Im

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