Analysis of Deforested Area Using Google Earth Engine in The Period 2001-2020 In the Apurimac Region

The objective of this study is to analyze the deforestation of forest cover in the Apurimac region between 2001 and 2020 using the Google Earth Engine (GEE) platform, a planetary-scale platform for the analysis of environmental data. The methodology used in the analysis of the deforested area is based on the classification of cover, using a supervised classification method developed by the University of Maryland, based on a "decision tree".

Capturing Student Achievement and Learning Pathways at the University of Maryland, Baltimore County

In 2015, the University of Maryland, Baltimore County (UMBC) recognized the need to capture knowledge, skills, and abilities acquired by students in both co-curricular and curricular endeavors not being captured in any identifiable way. The Vice President of Information Technology and Chief Information Officer desired to document competencies gained by students in the variety of contexts on campus and to track student, faculty, and staff achievements in a way that would both benefit each individual while also supporting the mission of the institution. This vision led to the adoption of a digital badging initiative resulting in a scalable process for implementing new badges throughout the university community. UMBC's digital badging program became the springboard for the institution's entrance into the Comprehensive Learner Record (CLR) realm whose objective is to capture all credentials earned by students, whether they be awarded before, during, or following their tenure at the institution.

Comprehensive Learner Record as a Vehicle for Assessment and Learning Transparency in a Skills Economy

This chapter outlines assessment technology that supports the development of Comprehensive Learner Record, or CLR. Here the authors present the theoretical landscape upon which current credentialing innovation builds, explore advancements through a case study of practice between University of Maryland, Baltimore County (UMBC) and the Greater Washington Partnership (GWP), and culminate with an overview of the assessment technology that ultimately facilitates recognition, validation, and portability of learning in the form of a comprehensive learner record.

Syndromic Surveillance-Based Estimates of Vaccine Efficacy Against COVID-Like Illness from Emerging Omicron and COVID-19 Variants

New infections from the omicron variant of SARS-CoV-2 have been increasing dramatically in South Africa since first identification in November 2021. Despite increasing uptake of COVID-19 vaccine, there are concerns vaccine protection against omicron may be reduced compared to other variants. We sought to characterize a surrogate measure of vaccine efficacy in Gauteng, South Africa by leveraging real-time syndromic surveillance data. The University of Maryland Global COVID Trends and Impact Survey (UMD-CTIS) is an online, cross-sectional survey conducted among users sampled from the Facebook active user base. We derived three COVID-like illness (CLI) definitions (stringent, classic, and broad) using combinations of self-reported symptoms (present or not in the prior 24 hours) that broadly tracked with reported COVID-19 cases during June 18, 2021 - December 14, 2021 (inclusive of the delta wave and up-trend of the omicron wave). We used syndromic-surveillance-based CLI prevalence measures among the vaccinated (PV) and unvaccinated (PU) respondents to estimate VECLIP = 1 - (PV/PU), a proxy for vaccine efficacy, during the delta (June 18-July 18, N= 9,387 surveys) and omicron (December 4-14, N= 2,389 surveys) wave periods. We assume no waning immunity, CLI prevalence approximates incident infection with each variant, and vaccinated and unvaccinated survey respondents in the two variant wave periods are exchangeable. The vaccine appears to have consistently lower VECLIP against omicron, compared to delta, regardless of the CLI definition used. Stringent CLI (i.e. anosmia plus fever, cough and/or myalgias) yielded a delta VECLIP = 0.85 [0.54, 0.95] higher than omicron VECLIP = 0.62 [0.46, 0.72]. Classic CLI (cough plus anosmia, fever, and/or myalgias) gave lower estimates (delta VECLIP = 0.76 [0.54, 0.87], omicron VECLIP = 0.51 [0.42, 0.59]), but omicron was still lower than delta. We acknowledge the potential for measurement, confounding, and selection bias, as well as limitations for generalizability for these self-reported, syndromic surveillance-based VECLIP measures. Thus VECLIP as estimates of true, population-level vaccine efficacy should therefore be taken with caution. Nevertheless, these preliminary findings demonstrating declining VECLIP raise concern for a true decline in vaccine efficacy versus waning immunity as a potential contributor to the omicron variant taking hold in Gauteng and elsewhere.

Rust Roland and Huang Ming-Hui: The Feeling Economy: How Artificial Intelligence Is Creating the Era of Empathy

“The Feeling Economy: How Artificial Intelligence Is Creating the Era of Empathy”, a book written by distinguished business scholars, professors Rust and Huang from the University of Maryland and National Taiwan University, looks at the ramifications of developing AI for the population. To help demystify the levels of intelligence required of AI, the book classifies different types of economy using three concepts: mechanical (physical), thinking, and feeling economy regarding the relationship with AI primarily, but not exclusively.

Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base

Simultaneously tracking the global impact of COVID-19 is challenging because of regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide standardized data streams to support monitoring and decision-making worldwide, in real time, and with limited local resources. The University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, has invited daily cross-sectional samples from the social media platform's active users to participate in the survey since its launch on April 23, 2020. We analyzed UMD-CTIS survey data through December 20, 2020, from 31,142,582 responses representing 114 countries/territories weighted for nonresponse and adjusted to basic demographics. We show consistent respondent demographics over time for many countries/territories. Machine Learning models trained on national and pooled global data verified known symptom indicators. COVID-like illness (CLI) signals were correlated with government benchmark data. Importantly, the best benchmarked UMD-CTIS signal uses a single survey item whereby respondents report on CLI in their local community. In regions with strained health infrastructure but active social media users, we show it is possible to define COVID-19 impact trajectories using a remote platform independent of local government resources. This syndromic surveillance public health tool is the largest global health survey to date and, with brief participant engagement, can provide meaningful, timely insights into the global COVID-19 pandemic at a local scale.

Editors’ Note

We are honored to introduce our inaugural issue as editors of the Israel Studies Review. For just over a decade, the journal was in the most competent hands of Yoram Peri and Paul Scham and their team at the University of Maryland. Under their leadership, the journal changed its name, transitioned to three issues per year, and enhanced its status as a leading scholarly journal in the area of Israel Studies, providing a scholarly platform to a diverse array of perspectives from multiple disciplines. Yoram and Paul themselves built on the foundations laid by Ilan Peleg, who transformed the journal from a newsletter to a full-fledged, peer-reviewed academic periodical. We are fully cognizant of the very big shoes we have to fill!

Advancing Age Inclusivity in a Pandemic: Age-Friendly University (AFU) Campuses Take Action

The COVID-19 pandemic presented extraordinary challenges for professionals in the aging field across campuses and communities, calling for rethinking and redesigning how their work was structured, their programs were delivered, and their connections were sustained. The pandemic also made clear the value of being an age-friendly institution of higher education, especially as we experience historic changes in age demographics. This symposium features campus leaders representing institutional partners of the Age-Friendly University (AFU) global initiative (endorsed by GSA’s Academy for Gerontology in Higher Education) who will discuss how their age-friendly programs were adapted during the pandemic to continue to advance age inclusivity. These diverse responses exemplify the vast potential of age-friendly opportunities. June and Andreoletti (Central Connecticut State University) will discuss how the Scholars for Life! program supported the engagement of older learners in the neighboring community through the engagement of faculty. Elfenbein (University of North Georgia) will describe how learning experiences for older learners and intergenerational exchange were created beyond the classroom through the Personal Enrichment, Action and Knowledge (PEAK) program. Terhune (Northern Kentucky University) will describe how student support practices and services were adapted to provide working adult students with guidance for navigating their educational needs during the pandemic. Kheirbek (University of Maryland, Baltimore) will describe how age-friendly collaborations with the institution’s medical school leveraged intergenerational connections and technology to foster social connection for hospitalized older adults. Gautam and Melillo (UMass Lowell) discuss how a campus partnership with the Learning in Retirement Association (LIRA) adapted efforts around healthy aging.

An Age- Friendly Campus Partnership for Hospitalized Older Adults in the COVID Era and Beyond

As hospitals isolate COVID-19 patients to prevent the spread of this highly contagious disease, patients and family are separated during times of critical illness. For many older adults inflicted with coronavirus it is not the fear of dying that matters the most, it is the fear of dying alone. Utilizing the 4Ms approach, University of Maryland, Baltimore (UMB) and University of Maryland Medical Center (UMMC) responded with several initiatives including intergenerational programs designed to shape and inform the development of future healthcare clinicians in addressing what matters the most to patients and leveraging technology to connect them with families, provide mobility opportunities, monitor medications, and reduce errors.

First person – Jun-yi Zhu and Xiaohu Huang

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Disease Models & Mechanisms, helping early-career researchers promote themselves alongside their papers. Jun-yi Zhu and Xiaohu Huang are first authors on ‘ Pharmacological or genetic inhibition of hypoxia signaling attenuates oncogenic RAS-induced cancer phenotypes’, published in DMM. Jun-yi is an assistant professor in the lab of Zhe Han at the University of Maryland School of Medicine, Baltimore, MD, USA, investigating the use of Drosophila as a model to study human disease mechanisms and treatment approaches. Xiaohu is a postdoc in the same lab, investigating gene functions in cardiovascular development and genetic diseases.