University of Michigan Library Holding: Kinh tế Việt Nam - Thăng trầm và đột phá

The University of Michigan's Library Holding of the title Kinh tế Việt Nam - Thăng trầm và đột phá, published in 2009 by Hanoi-based the National Political Publishing House, Vietnam.

Creative Empathy

This chapter is designed to inform and educate the reader about the trials and tribulations of two young men with disabilities. Their journey through the K–16 educational system is discussed, as are their triumphs and struggles as they learn to survive in a nondisabled world. The chapter relates the two men's scenarios to the theory of social justice as well as breaks down the most common myths and misconceptions about people with exceptionalities. The chapter concludes by conveying instructional strategies developed by the University of Michigan School of Education's Teaching Works and the University of Florida's CEEDAR Center and the Council for Exceptional Children that can be used by any teacher to get to know their students well and develop successful intervention strategies.

Mai’a K. Davis Cross, Ireneusz Paweł Karolewski (red.), European-Russian Power Relations in Turbulent Times, University of Michigan Press, Ann Arbor 2021, ss. 311.

Recenzja

Reviewer Acknowledgements

Journal of Agricultural Studies (JAS) would like to acknowledge the following reviewers for their assistance with peer review of manuscripts for this issue. Many authors, regardless of whether JAS publishes their work, appreciate the helpful feedback provided by the reviewers. Their comments and suggestions were of great help to the authors in improving the quality of their papers. Each of the reviewers listed below returned at least one review for this issue.Reviewers for Volume 9, Number 4Ahmad Reza Pirali Zefrehei, Gorgan Univ. of Agricultural Sci. & Natural Resources, IranAlessandra M. Lima Naoe, Federal University of Tocantins, BrazilAndré Luiz Rodrigues Magalhães, UFAPE, BrazilCamilla H. M. Camargos, University of Campinas, BrazilEmmanuel E. Omeje, University of Nigeria, NigeriaEric Krawczyk, University of Michigan, USAEric Owusu Danquah, CSIR-Crops Research Institute, GhanaJorge A. López, University Tiradentes, BrazilJuliana Nneka Ikpe, Akanu Ibiam Federal Polytechnic, NigeriaLuh Suriati, Warmadewa University, IndonesiaNkemkanma Vivian Agi, Rivers State University Port Harcourt, NigeriaRaul Pașcalău, Banat's University, RomaniaSaiful Irwan Zubairi, Universiti Kebangsaan Malaysia (UKM), MalaysiaShakirudeen Abimbola Lawal, University of Cape Town, South AfricaSomaia Alkhair, Alzaeim Alazhari University, SudanToncho Gospodinov Penev, Trakia University, BulgariaZakaria Fouad Abdallah, National Research Centre, EgyptRichard WilliamsEditorial AssistantJournal of Agricultural Studies--------------------------------------Macrothink Institute5348 Vegas Dr.#825Las Vegas, Nevada 89108United StatesPhone: 1-702-953-1852 ext.521Email 1: [email protected] 2: [email protected]: http://jas.macrothink.org

Learning from 2020: How the Challenges of Remote Teaching Reinforce the Need for Care-Informed Pedagogy

How did instructors design their sociology courses for remote teaching during the 2020–2021 academic year, and what challenges did they face in teaching those courses? To answer these questions, we surveyed lead instructors and graduate teaching assistants (n = 77) in the Sociology Department at the University of Michigan, supplemented by interviews with students and our experiences as remote course consultants. Through this case study, we found that instructors cited increased workload and lack of connection as challenges with remote teaching, in addition to pandemic-related struggles. Most instructors reported using either synchronous or a mix of synchronous and asynchronous instruction in course design, incorporating both formative and summative assessments, and implementing communication and community-building strategies to establish connections with and among students. We argue that these challenges and course designs highlight the importance of care-informed pedagogy to not only remote teaching in 2020–2021 but also sociology instruction in general.

Ray tracing intraocular lens calculation performance improved by AI-powered postoperative lens position prediction

AimsTo assess whether incorporating a machine learning (ML) method for accurate prediction of postoperative anterior chamber depth (ACD) improves cataract surgery refraction prediction performance of a commonly used ray tracing power calculation suite (OKULIX).Methods and analysisA dataset of 4357 eyes of 4357 patients with cataract was gathered at the Kellogg Eye Center, University of Michigan. A previously developed machine learning (ML)–based method was used to predict the postoperative ACD based on preoperative biometry measured with the Lenstar LS900 optical biometer. Refraction predictions were computed with standard OKULIX postoperative ACD predictions and ML-based predictions of postoperative ACD. The performance of the ray tracing approach with and without ML-based ACD prediction was evaluated using mean absolute error (MAE) and median absolute error (MedAE) in refraction prediction as metrics.ResultsReplacing the standard OKULIX postoperative ACD with the ML-predicted ACD resulted in statistically significant reductions in both MAE (1.7% after zeroing mean error) and MedAE (2.1% after zeroing mean error). ML-predicted ACD substantially improved performance in eyes with short and long axial lengths (p<0.01).ConclusionsUsing an ML-powered postoperative ACD prediction method improves the prediction accuracy of the OKULIX ray tracing suite by a clinically small but statistically significant amount, with the greatest effect seen in long eyes.