The Development of a Reading Book on House Construction Civilization Based on Project-Based Learning to Improve Children's Social Intelligence Character by Gregorius Ari Nugrahanta, Hilary Relita Vertikasari Sekarningrum, Brigita Sherlyta Erlansa Putri

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Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models by Tzu-Hsien Yang, Ying-Hsien Huang, Yuan-Han Lee, Jie-Nan Lai, Kuang-Den Chen, Mindy Ming-Huey Guo, Yan Pan, Chun-Yu Chen, Wei-Sheng Wu, Ho-Chang Kuo

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Correction: Behavioural ethogram to inform ex-situ initiatives for a critically endangered bird – the case of the Plains-wanderer by Monique Van Sluys, Yvette Pauligk, Alicia Burns, Alicia Burns, Alicia Burns, Mark O’Riordan, Richard Matkovics, Chris Hartnett, Benjamin J. Pitcher, Benjamin J. Pitcher

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Behavioural ethogram to inform ex-situ initiatives for a critically endangered bird – the case of the Plains-wanderer by Monique Van Sluys, Yvette Pauligk, Alicia Burns, Alicia Burns, Alicia Burns, Mark O’Riordan, Richard Matkovics, Chris Hartnett, Benjamin J. Pitcher, Benjamin J. Pitcher

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Coral Reef Conservation Strategies for Everyone by Kathryn E. Lohr, Joshua T. Patterson

“…Patterson, and published by the Program in Fisheries and Aquatic Sciences, School of Forest Resources and Conservation, September 2016. …”
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Coral Reef Conservation Strategies for Everyone by Kathryn E. Lohr, Joshua T. Patterson

“…Patterson, and published by the Program in Fisheries and Aquatic Sciences, School of Forest Resources and Conservation, September 2016. …”
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Prognostic risk modeling of endometrial cancer using programmed cell death-related genes: a comprehensive machine learning approach by Tianshu Chen, Yuhan Yang, Zhizhong Huang, Feng Pan, Zhendi Xiao, Kunxue Gong, Wenguang Huang, Liu Xu, Xueqin Liu, Caiyun Fang

“…This study aimed to develop a robust predictive model integrating programmed cell death-related genes and advanced machine learning techniques. …”
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Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning by Mi Liu, Xingxing Gao, Hongfa Wang, Yiping Zhang, Xiaojun Li, Renlai Zhu, Yunru Sheng

“…It has been reported that programmed cell death (PCD) plays a critical role in the development and progression of sepsis, which has the potential to be a diagnosis and prognosis indicator for patient with sepsis. …”
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Remote sensing applications for managing a large-scale restoration dynamics project throughout the City of Gold Coast conservation estate by Jean-Marc Hero, Luke Shoo, Michael Duncan, Darren Roche, Jesse Kenny, Howard Taylor, Tim Robson, Sanjeev Kumar Srivastava, Josh Veitch-Michaelis

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Methodological bases for the design of flexible educational programs in a network format by Elena Mikhailovna Efimova, Denis Olegovich Efimov

“…The purpose of the research is determination of the methodology for constructing effective network educational programs, based on the formation of the student’s personality and his practical preparation for future professional activity through individual development. …”
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The Pedagogical Content Knowledge of the School of Education Pre-Service Teachers in Test Construction by Lorie Anne Socorro Moreno, Ronald Quileste

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Exploring perspectives of type 2 diabetes prevention program coaches and training delivery staff on e-learning training: a qualitative study by Kaela D. Cranston, Natalie J. Grieve, Mary E. Jung

“…E-learning training for diabetes prevention program coaches was designed and developed with input from end users. …”
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Floating Point Multiple-Precision Fused Multiply Add Architecture for Deep Learning Computation on Artix 7 FPGA Board by VINOTHENI, M. S., JAWAHAR SENTHIL KUMAR, V.

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An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer by Lihuan Dai, Jinxue Yin, Xin Xin, Chun Yao, Yongfang Tang, Xiaohong Xia, Yuanlin Chen, Shuying Lai, Guoliang Lu, Jie Huang, Purong Zhang, Jiansheng Li, Xiangguang Chen, Xi Zhong

“…Abstract Background Programmed death ligand 1 (PD-L1) expression status, closely related to immunotherapy outcomes, is a reliable biomarker for screening patients who may benefit from immunotherapy. …”
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How did conservation agriculture go to scale? by Ricardo Ramirez, Cynthia Neudoerffer, Michael Salomons

“…The three outcome areas of the Scaling-Up Conservation Agriculture in East Africa (SUCA) Program were: the adoption of conservation agriculture systems, an enabling institutional environment, and the promotion of enabling policies. …”
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PENERAPAN TEORI KONSTRUKTIVISTIK PADA PEMBELAJARAN BAHASA ARAB DI KELOMPOK 28 PROGRAM INTENSIFIKASI BAHASA ARAB IAIN SYEKH NURJATI CIREBON by Hikmah Uswatun Ummi, Indrya Mulyaningsih

“…<p>Use appropriate teaching methods teachers' creativity. Learning foreign languages, especially Arabic Arabic Intensification Program IAIN Sheikh Nurjati Cirebon using various methods. …”
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Registrars’ experience with research in family medicine training programmes in South Africa by Emcy Louw, Robert J. Mash

“…Conclusion: Training programmes should revise the teaching of research and improve institutional processes. …”
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THE APPLICATION OF AUTHENTIC ASSESSMENT WITH FEEDBACK TO IMPROVE THE COMPETENCE OF MTS 2 BANDUNG STUDENTS IN CONSTRUCTING A SCIENTIFIC REPORT OF MOTION MATERIAL IN SCIENCE LEARNING by A. Y. Nuryantini, T. Setiadi, K. Kurniawan, I. Farida

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Towards sustainable construction: estimating compressive strength of waste foundry sand-blended green concrete using a hybrid machine learning approach by Hoang Nhat-Duc, Nguyen Quoc-Lam

“…LightGBM is used to construct a functional mapping between the CS and its influencing factors. …”
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Determinants of WhatsApp and Telegram usage for learning support in Nigerian universities: a quantitative study by Chinyere Ori Elom, Hayford Mensah Ayerakwa, Sikiru Ibrahim-Olesin, Eric Worlanyo Deffor, Chidebe Chijioke Uwaleke, Robert Ugochukwu Onyeneke

“…The determinants of the use of WhatsApp and Telegram to enhance learning among students include age, gender, wealth status of parents/guardians, student’s faculty/program, location of school, and level of student in school. …”
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