Bile acids in follicular fluid: potential new therapeutic targets and predictive markers for women with diminished ovarian reserve by Shu Ding, Wenyan Li, Xianglei Xiong, Manfei Si, Chuyu Yun, Yuqian Wang, Lixuan Huang, Sen Yan, Xiumei Zhen, Jie Qiao, Xinyu Qi

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Groundwater Level Forecasting Using Machine Learning: A Case Study of the Baekje Weir in Four Major Rivers Project, South Korea by Sooyeon Yi, G. Mathias Kondolf, Samuel Sandoval Solis, Larry Dale

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Comparison of Satellite-based PM2.5 Estimation from Aerosol Optical Depth and Top-of-atmosphere Reflectance by Heming Bai, Zhi Zheng, Yuanpeng Zhang, He Huang, Li Wang

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House Price Prediction of Real Time Data (DHA Defence) Karachi Using Machine Learning by Lata Bai Gokalani, Bhagwan Das, Dilip Kumar Ramnani, Mahender Kumar, Mazhar Ali Shah

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Joint modelling of longitudinal data: a scoping review of methodology and applications for non-time to event data by Rehema K. Ouko, Mavuto Mukaka, Eric O. Ohuma

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4SQR-Code: A 4-state QR code generation model for increasing data storing capacity in the Digital Twin framework by Ababil Islam Udoy, Muhammad Aminur Rahaman, Md. Jahidul Islam, Anichur Rahman, Zulfiqar Ali, Ghulam Muhammad

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AI in Medical Questionnaires: Innovations, Diagnosis, and Implications by Xuexing Luo, Yiyuan Li, Jing Xu, Zhong Zheng, Fangtian Ying, Guanghui Huang

“… This systematic review aimed to explore the current applications, potential benefits, and issues of artificial intelligence (AI) in medical questionnaires, focusing on its role in 3 main functions: assessment, development, and prediction. …”
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Integrated Single-Cell and Spatial Transcriptomic Analysis Identifies ISR-Related Genes Driving Immune Regulation in Parkinson’s Disease by Jiang H, Zhang X, Feng S, Feng W

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Causal Unit Selection using Tractable Arithmetic Circuits by Haiying Huang, Adnan Darwiche

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Interpersonal counselling for adolescent depression delivered by youth mental health workers without core professional training: the ICALM feasibility RCT by Jon Wilson, Viktoria Cestaro, Eirini Charami-Roupa, Timothy Clarke, Aoife Dunne, Brioney Gee, Sharon Jarrett, Thando Katangwe-Chigamba, Andrew Laphan, Susie McIvor, Richard Meiser-Stedman, Jamie Murdoch, Thomas Rhodes, Carys Seeley, Lee Shepstone, David Turner, Paul Wilkinson

“…Progression criteria The primary intended output of the research was the design of a subsequent trial. The following criteria were set out at the beginning of the study to make recommendations regarding the suitability of the proposed design for the full-scale trial: (1) recruitment rate is at least 80% of target, (2) at least 70% of those randomised to receive the intervention attended at least three therapy sessions within the 10-week treatment window, (3) follow-up assessments are completed by at least 80% of participants at 10 weeks and 70% of participants at 23 weeks, (4) at least 80% of IPC treatment sessions reviewed meet treatment fidelity criteria, (5) contamination of the control arm can be sufficiently limited for individual randomisation to be justified and (6) the mean Revised Children’s Anxiety and Depression Scale (RCADS) depression scores of the IPC-A and TAU groups at 10 weeks are indicative of a clinically significant difference in depression (3 points). …”
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Determining the Number of Measurements and Bootstrap Samples Required to Estimate of Long-Term Noise Indicators by Bartłomiej STĘPIEŃ

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High-precision positioning of robotic systems on programme trajectories using satellite navigation measurements by S. V. Sokolov, A. I. Okhotnikov, D. V. Marshakov, I. V. Reshetnikova

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A Multi-Mode Recognition Method for Broadband Oscillation Based on Compressed Sensing and EEMD by Jinggeng Gao, Honglei Xu, Yong Yang, Haoming Niu, Jinping Liang, Haiying Dong

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Machine Learning-Based Objective Evaluation Model of CTPA Image Quality: A Multi-Center Study by Sun Q, Liu Z, Ding T, Shi C, Hou N, Sun C

“…Feature selection was performed using the Lasso algorithm and Pearson correlation coefficient, and a random forest regression model was constructed. …”
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Development of a machine learning-based prediction model for extremely rapid decline in estimated glomerular filtration rate in patients with chronic kidney disease: a retrospectiv... by Shingo Fukuma, Yukio Yuzawa, Daijo Inaguma, Hiroki Hayashi, Ryosuke Yanagiya, Akira Koseki, Toshiya Iwamori, Michiharu Kudo

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Improved mapping of highland bamboo forests using Sentinel-2 time series and machine learning in Google Earth Engine by Dagnew Yebeyen, Binyam Tesfaw Hailu, Worku Zewdie, Temesgen Abera, Gudeta W. Sileshi, Melaku Getachew, Sileshi Nemomissa

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Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study by Mostafa A. Arafa, Karim H. Farhat, Sherin F. Aly, Farrukh K. Khan, Alaa Mokhtar, Abdulaziz M. Althunayan, Waleed Al-Taweel, Sultan S. Al-Khateeb, Sami Azhari, Danny M. Rabah

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Assessment of environmental impacts of armed conflict in Mozambique using remotely sensed data by Focas Francisco Bacar, Hilário Biché Faque

“…Here we assess the impacts of an armed conflict on fragmentation, change intensity, and the pattern and process of changes in LULC in three districts in Mozambique. To evaluate these effects, we used Multi-temporal satellite images (Landsat 5 TM and Landsat 8 OLI-TIRS) in combination with fieldwork, geographic information systems, landscape ecology metrics, and the Random Forest machine learning algorithm. …”
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Some Elements of Operational Modal Analysis by Rune Brincker

“…This paper gives an overview of the main components of operational modal analysis (OMA) and can serve as a tutorial for research oriented OMA applications. …”
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On the Search for Supersingular Elliptic Curves and Their Applications by Ismel Martinez-Diaz, Rashad Ali, Muhammad Kamran Jamil

“…As our main result, we define for the first time an objective function to measure the supersingularity in ordinary curves, and we apply local search and a genetic algorithm using that function. …”
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