Phosphate Contaminant Detection in Water Through a Paper-based Microfluidic Device

This report describes a project aimed at developing a low-cost, portable, on-site, user-friendly system for detecting different concentrations of phosphate in drinking water. Phosphate is a natural chemical, but toxic in large concentrations; detection is therefore important to avoid drinking contaminated water. Despite this fact, no cheap, and/or nontoxic system for phosphate detection is yet on the market. The detection system utilizes a paper-based microfluidic device to automate the electrochemical detection process, which normally requires expert use of lab equipment. When combined with a portable potentiostat that works with a mobile app, the device will allow untrained users to determine if any source of drinking water contains unsafe levels of phosphate without equipment or training, and to communicate that information to a central database for further analysis. Those of any background, particularly in developing countries, will be able to maintain health and raise awareness about clean water. Microfluidic devices are useful tools for the detection of water contaminants, but there is a gap in technology for the detection of phosphate. Our phosphate detection system is a paper-based microfluidic device with an already-developed voltammetry device that automates the detection process so that any user can safely find phosphate in water. The system will provide a binary analysis about whether the water is safe to consume or not. Completion of the project provides a valuable tool to both average customers in developing countries and scientific researchers in determining the safety of drinking water

Riparian reference condition: Using regional plant composition to guide functional improvements in the City of Austin

This technical report focuses on ways to restore riparian habitat within specific Austin creeks. This study is designed to serve as a template for restoration efforts with other urbanized creeks (Waller).As a result of an expanding and rapidly urbanizing metropolitan area, the riparian vegetation communities of Austin-area streams continue to diverge further from their natural state. In an effort to maintain the ecological function and the natural character of Austin watersheds, the City of Austin Watershed Protection Department has identified a need to characterize an archetype, or background condition of Edwards Plateau and Blackland Prairie riparian communities for use as a template for both benchmarking and target for stream restoration projects. Species composition, spatial arrangement and physical attributes of vegetation communities for 12 sites located in both smaller and larger watersheds were characterized using multiple belt-transects. Multivariate analyses including detrended correspondence analysis (DCA), analysis of similarity (ANOSIM), and similarity percentage (SIMPER) were performed by Community Analysis Package software (Seaby and Henderson 2007). Results show that there was a significant difference in plant community composition in all compared drainage areas and ecoregions for both ground cover and overstory communities (p<0.05). The analysis of similarity showed that the samples should be grouped by ecoregion and location within the watershed for overstory and ground cover communities. Recommended vegetation templates are presented as a guide for comparison to other riparian communities in the Austin area, and also a reference point for restoration of degraded systems. These quantitative species distribution lists are an important resource for riparian ecologists in this region.Waller Creek Working Grou

Successfully implementing research analytics and dashboards without scaring or scarring anyone!

The use of data and analytics in the field of research administration remains in explorations stages for many, if not most, higher education institutions. That is evidenced not only by the great demand and attendance seen for such sessions at NCURA’s Annual Meetings in 2022 and 2023, but also via prior research. This presentation will highlight the efforts implementing data-informed decision making based on research administration metrics, analytics, and dashboard examples. Emphasis will be placed on that you can’t manage what you can’t measure. The data analytics team at Emory supports all visions of our research administration leadership. Challenges, pain points, and lessons learned will be shared. Reasons for implementing collecting data and metrics will be shown. These include improving operational efficiencies, stakeholder satisfaction (e.g., faculty), as well as providing analytical insights to decision makers. The benefits of such initiatives will also be depicted with examples of successfully implemented metrics and analytics, including dashboard examples

Introduction to Research Administrations Dashboards using Tableau

This session will present on how to develop basic research administration dashboards using Tableau. A sample research administration dataset will be provided in Excel for anyone who would like to work along. Using that data set the presenter will show step by step how to import the data into Tableau and how to create basic worksheets and dashboards. Calculations and filters will be shown also. Attendees should download a trial version of Tableau the same week as the conference if they would like to work along the presenter

Introduction to Descriptive Research Administration Statistics using Excel

This session is a basic introduction to descriptive statistics for research administration professionals. No worries! Excel will be used throughout, nothing will be calculated by hand. Averages (means), medians, standard deviations, correlations and other basic statistical concepts will be explained using only research administration data as context. A sample research administration data set will be provided and Excel will be used to analyze the data. Some sample charts and best practices in creating these charts will also be shown. Again using Excel. This is the perfect session for anyone in research administration whose roles include analyzing data using descriptive statistics. Whether you are new to statistics or whether you can\u27t remember a statistics class you might have taken at some point. Basic knowledge of Excel would be helpful for this session