Redesigning pictographs for patients with low health literacy and establishing preliminary steps for delivery via smart phones.

BackgroundPictographs (or pictograms) have been widely utilized to convey medication related messages and to address nonadherence among patients with low health literacy. Yet, patients do not always interpret the intended messages on commonly used pictographs correctly and there are questions how they may be delivered on mobile devices.ObjectiveOur objectives are to refine a set of pictographs to use as medication reminders and to establish preliminary steps for delivery via smart phones.MethodsCard sorting was used to identify existing pictographs that focus group members found "not easy" to understand. Participants then explored improvements to these pictographs while iterations were sketched in real-time by a graphic artist. Feedback was also solicited on how selected pictographs might be delivered via smart phones in a sequential reminder message. The study was conducted at a community learning center that provides literacy services to underserved populations in Seattle, WA. Participants aged 18 years and older who met the criteria for low health literacy using S-TOFHLA were recruited.ResultsAmong the 45 participants screened for health literacy, 29 were eligible and consented to participate. Across four focus group sessions, participants examined 91 commonly used pictographs, 20 of these were ultimately refined to improve comprehensibility using participatory design approaches. All participants in the fifth focus group owned and used cell phones and provided feedback on preferred sequencing of pictographs to represent medication messages.ConclusionLow literacy adults found a substantial number of common medication label pictographs difficult to understand. Participative design processes helped generate new pictographs, as well as feedback on the sequencing of messages on cell phones, that may be evaluated in future research

FairLedger: A Fair Blockchain Protocol for Financial Institutions

Financial institutions are currently looking into technologies for permissioned blockchains. A major effort in this direction is Hyperledger, an open source project hosted by the Linux Foundation and backed by a consortium of over a hundred companies. A key component in permissioned blockchain protocols is a byzantine fault tolerant (BFT) consensus engine that orders transactions. However, currently available BFT solutions in Hyperledger (as well as in the literature at large) are inadequate for financial settings; they are not designed to ensure fairness or to tolerate selfish behavior that arises when financial institutions strive to maximize their own profit. We present FairLedger, a permissioned blockchain BFT protocol, which is fair, designed to deal with rational behavior, and, no less important, easy to understand and implement. The secret sauce of our protocol is a new communication abstraction, called detectable all-to-all (DA2A), which allows us to detect participants (byzantine or rational) that deviate from the protocol, and punish them. We implement FairLedger in the Hyperledger open source project, using Iroha framework, one of the biggest projects therein. To evaluate FairLegder's performance, we also implement it in the PBFT framework and compare the two protocols. Our results show that in failure-free scenarios FairLedger achieves better throughput than both Iroha's implementation and PBFT in wide-area settings

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

ranacapa: An R package and Shiny web app to explore environmental DNA data with exploratory statistics and interactive visualizations.

Environmental DNA (eDNA) metabarcoding is becoming a core tool in ecology and conservation biology, and is being used in a growing number of education, biodiversity monitoring, and public outreach programs in which professional research scientists engage community partners in primary research. Results from eDNA analyses can engage and educate natural resource managers, students, community scientists, and naturalists, but without significant training in bioinformatics, it can be difficult for this diverse audience to interact with eDNA results. Here we present the R package ranacapa, at the core of which is a Shiny web app that helps perform exploratory biodiversity analyses and visualizations of eDNA results. The app requires a taxonomy-by-sample matrix and a simple metadata file with descriptive information about each sample. The app enables users to explore the data with interactive figures and presents results from simple community ecology analyses. We demonstrate the value of ranacapa to two groups of community partners engaging with eDNA metabarcoding results

Online cooperation learning environment : a thesis presented in partial fulfillment of the requirements for the degree of Master of Science in Computer Science at Massey University, Albany, New Zealand

This project aims to create an online cooperation learning environment for students who study the same paper. Firstly, the whole class will be divided into several tutorial peer groups. One tutorial group includes five to seven students. The students can discuss with each other in the same study group, which is assigned by the lecturer. This is achieved via an online cooperation learning environment application (OCLE), which consists of a web based J2EE application and a peer to peer (P2P) java application, cooperative learning tool (CLT). It can reduce web server traffic significantly during online tutorial discussion time

Computational Strategies for Scalable Genomics Analysis.

The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications

Temporal verification in secure group communication system design

The paper discusses an experience in using a real-time UML/SysML profile and a formal verification toolkit to check a secure group communication system against temporal requirements. A generic framework is proposed and specialized for hierarchical groups

A food chain approach to control of Shiga toxin-producing Escherichia coli in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Science at Massey University, Palmerston North, New Zealand

Part of Chapter 3 has been published as: Browne, A.S., Midwinter, A.C., Withers, H., Cookson, A.L., Biggs, P.J., Marshall J.C., Benschop, J., Hathaway, S., Haack, N., Akhter, R., & French, N.P. (2018). Molecular epidemiology of Shiga toxin-producing Escherichia coli (STEC) on New Zealand dairy farms: Application of a culture-independent assay and whole-genome sequencing. Applied and Environmental Microbiology, 84(14). DOI: 10.1128/AEM.00481-18This thesis describes the prevalence and molecular epidemiology of Shiga toxin-producing Escherichia coli (STEC) in New Zealand using microbiological, genomic, molecular, and statistical methods. STEC are a zoonotic pathogen that can cause bloody diarrhoea and acute kidney failure. Cattle are a well-recognized STEC reservoir, and previous research has identified living near cattle and contact with their faeces as an increased risk for human infection. Seven STEC serogroups (O157, O26, O45, O103, O111, O121, O145), known as the ‘Top 7’ STEC, have been identified as an increased risk to human health, with the New Zealand meat industry undertaking testing to ensure that veal beef exports to some international markets are free of these ‘Top 7’ serogroups. A random stratified cross-sectional study of ‘Top 7’ STEC prevalence of young dairy calves (n=1,508) on New Zealand dairy farms (n=102) found that approximately 20% of calves and 75% of farms were positive for one or more of the ‘Top 7’ STEC. ‘Top 7’ STEC prevalence was positively associated with increased number of calves in a calf pen, and prevalence significantly varied by region. This study utilized a new culture-independent diagnostic test, NeoSEEK (PCR/MALDI-TOF method), and used statistical and microbiological techniques to evaluate the sensitivity and specificity of the method for this and further studies. A longitudinal study evaluating prevalence and transmission of ‘Top 7’ STEC in animals and the dairy farm environment found evidence of calf-to-calf, dam-to-calf, and environment-to-calf transmission. Whole genome sequencing analysis and prevalence data revealed cross-contamination of young veal calf hides occurs during transport and lairage to processing plants. Analysis of New Zealand serogroup O26 bacterial isolates (n=152), in comparison to publicly available genome sequence data (n=252) from other countries (n=14), suggested introduction of STEC and non-STEC O26 into New Zealand during few periods in the 20th and early 21st century. Populations of New Zealand serogroup O26 E. coli are monophyletic, possibly due to minimal live cattle importations into the country. Further research in this area should focus on effective interventions at the farm and meat processing level to decrease the risk of veal beef contamination, while protecting public health