E/Valuating new media in language development

This paper addresses the need for a new approach to the educational evaluation of software that falls under the rubric "new media" or "multimedia" as distinct from previous generations of Computer-Assisted Language Learning (CALL) software. The authors argue that present approaches to CALL software evaluation are not appropriate for a new genre of CALL software distinguished by its shared assumptions about language learning and teaching as well as by its technical design. The paper sketches a research-based program called "E/Valuation" that aims to assist language educators to answer questions about the educational effectiveness of recent multimedia language learning software. The authors suggest that such program needs to take into account not only the nature of the new media and its potential to promote language learning in novel ways, but also current professional knowledge about language learning and teaching

WASH in Schools Empowers Girls' Education: Proceedings of the Menstrual Hygiene Management in Schools Virtual Conference 2013

This publication brings together the key elements of the 16 presentations made at the Second Annual Virtual MHM in WinS Conference at UNICEF Headquarters in New York City on 21 November 2013. Building on recommendations from the MHM 2012 virtual conference, the 2013 conference focused on the research tools and instruments being used to explore MHM barriers and practices and to evaluate the interventions being trialed or implemented in various contexts

BOSS-LDG: A Novel Computational Framework that Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery

We present a novel computational framework that connects Blue Waters, the NSF-supported, leadership-class supercomputer operated by NCSA, to the Laser Interferometer Gravitational-Wave Observatory (LIGO) Data Grid via Open Science Grid technology. To enable this computational infrastructure, we configured, for the first time, a LIGO Data Grid Tier-1 Center that can submit heterogeneous LIGO workflows using Open Science Grid facilities. In order to enable a seamless connection between the LIGO Data Grid and Blue Waters via Open Science Grid, we utilize Shifter to containerize LIGO's workflow software. This work represents the first time Open Science Grid, Shifter, and Blue Waters are unified to tackle a scientific problem and, in particular, it is the first time a framework of this nature is used in the context of large scale gravitational wave data analysis. This new framework has been used in the last several weeks of LIGO's second discovery campaign to run the most computationally demanding gravitational wave search workflows on Blue Waters, and accelerate discovery in the emergent field of gravitational wave astrophysics. We discuss the implications of this novel framework for a wider ecosystem of Higher Performance Computing users.Comment: 10 pages, 10 figures. Accepted as a Full Research Paper to the 13th IEEE International Conference on eScienc

The Application of Statistical Modeling to Identify Genetic Associations with Mild Traumatic Brain Injury Outcomes

Traumatic brain injury (TBI) is a growing health concern, with millions of TBI diagnoses in the United States each year. The vast majority of TBI diagnoses are mild traumatic brain injuries (mTBI), which can be challenging to manage due to variation in symptoms and outcomes. Most individuals with mTBI successfully recover quickly, but a small subset has a delayed recovery. Although the factors that contribute to this variation in recovery are not clearly understood, it is possible that genetic differences may play a role. Very few studies have investigated the association between single nucleotide polymorphisms (SNPs) with mTBI outcomes and this is an emerging area of research. In this study, we utilize data collected in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to test the association between 10 different SNPs and 7 TBI outcomes measured at six- and twelve-months post injury. Linear mixed models are utilized to investigate the association between genotypes and mTBI outcome measurements over time. Previous studies have primarily focused on a single time point at six months for one or two SNPs. This study seeks to expand the existing literature by using the TRACK-TBI Pilot data to evaluate multiple SNPs and multiple outcome assessments to discover their connections over time. The findings in this study demonstrate the potential benefits of using linear mixed models to identify relationships between genotypes and TBI outcomes over time --Abstract, p. i

Designing Improved Sediment Transport Visualizations

Monitoring, or more commonly, modeling of sediment transport in the coastal environment is a critical task with relevance to coastline stability, beach erosion, tracking environmental contaminants, and safety of navigation. Increased intensity and regularity of storms such as Superstorm Sandy heighten the importance of our understanding of sediment transport processes. A weakness of current modeling capabilities is the ability to easily visualize the result in an intuitive manner. Many of the available visualization software packages display only a single variable at once, usually as a two-dimensional, plan-view cross-section. With such limited display capabilities, sophisticated 3D models are undermined in both the interpretation of results and dissemination of information to the public. Here we explore a subset of existing modeling capabilities (specifically, modeling scour around man-made structures) and visualization solutions, examine their shortcomings and present a design for a 4D visualization for sediment transport studies that is based on perceptually-focused data visualization research and recent and ongoing developments in multivariate displays. Vector and scalar fields are co-displayed, yet kept independently identifiable utilizing human perception\u27s separation of color, texture, and motion. Bathymetry, sediment grain-size distribution, and forcing hydrodynamics are a subset of the variables investigated for simultaneous representation. Direct interaction with field data is tested to support rapid validation of sediment transport model results. Our goal is a tight integration of both simulated data and real world observations to support analysis and simulation of the impact of major sediment transport events such as hurricanes. We unite modeled results and field observations within a geodatabase designed as an application schema of the Arc Marine Data Model. Our real-world focus is on the Redbird Artificial Reef Site, roughly 18 nautical miles offshor- Delaware Bay, Delaware, where repeated surveys have identified active scour and bedform migration in 27 m water depth amongst the more than 900 deliberately sunken subway cars and vessels. Coincidently collected high-resolution multibeam bathymetry, backscatter, and side-scan sonar data from surface and autonomous underwater vehicle (AUV) systems along with complementary sub-bottom, grab sample, bottom imagery, and wave and current (via ADCP) datasets provide the basis for analysis. This site is particularly attractive due to overlap with the Delaware Bay Operational Forecast System (DBOFS), a model that provides historical and forecast oceanographic data that can be tested in hindcast against significant changes observed at the site during Superstorm Sandy and in predicting future changes through small-scale modeling around the individual reef objects

COLAEVA: Visual Analytics and Data Mining Web-Based Tool for Virtual Coaching of Older Adult Populations

The global population is aging in an unprecedented manner and the challenges for improving the lives of older adults are currently both a strong priority in the political and healthcare arena. In this sense, preventive measures and telemedicine have the potential to play an important role in improving the number of healthy years older adults may experience and virtual coaching is a promising research area to support this process. This paper presents COLAEVA, an interactive web application for older adult population clustering and evolution analysis. Its objective is to support caregivers in the design, validation and refinement of coaching plans adapted to specific population groups. COLAEVA enables coaching caregivers to interactively group similar older adults based on preliminary assessment data, using AI features, and to evaluate the influence of coaching plans once the final assessment is carried out for a baseline comparison. To evaluate COLAEVA, a usability test was carried out with 9 test participants obtaining an average SUS score of 71.1. Moreover, COLAEVA is available online to use and explore.This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 769830

Surface radiation budget for climate applications

The Surface Radiation Budget (SRB) consists of the upwelling and downwelling radiation fluxes at the surface, separately determined for the broadband shortwave (SW) (0 to 5 micron) and longwave (LW) (greater than 5 microns) spectral regions plus certain key parameters that control these fluxes, specifically, SW albedo, LW emissivity, and surface temperature. The uses and requirements for SRB data, critical assessment of current capabilities for producing these data, and directions for future research are presented

Exploration of the Implementation of an Integrated Electronic Laboratory Information Management System on Quality Diagnostics Service Indicators at a County Level Public Hospital in western Kenya.

Underinvestment in pathology and laboratory capacity caused by low visibility in research and in prioritization by public health leaders results in limited effective healthcare coverage and an estimated 1.1 million premature deaths annually in Low-and-Middle-Income Countries. Kenya’s public health laboratories provide a median 41% of the Essential Diagnostic List to their patients and in Kisumu County, as much as 44.2% of the population has little to no access to essential diagnostics. The government of Kisumu implemented the county Health Laboratory Strategic Plan 2018-2022 to address this public health challenge. Little information exists on the effectiveness of these initiatives and the realized impact on laboratory quality diagnostic services in the era of COVID-19. This study explored the implementation of one of the Strategic Plan’s initiatives, an electronic diagnostics data system at a county-level health facility, and the impact that has had on Malaria diagnostics from 2018 to 2022. This study found that the implementation of this electronic data system was not associated with increases in Malaria testing or informed treatment. It found that patients under 5 years old treated for Malaria were 1.07 times more likely to be treated presumptively in 2020 than in 2018. There have been significant decreases in all patients and total tests performed for Malaria since 2018 in spite of a significant Malaria positivity peak in 2020. More research needs to be done on the causes of these decreases and ways in which laboratory test results can better inform provider testing and treatment priorities