University of North Carolina at Charlotte

About: University of North Carolina at Charlotte is a education organization based out in Charlotte, North Carolina, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 8772 authors who have published 22239 publications receiving 562529 citations. The organization is also known as: UNC Charlotte & UNCC.

Epidemiological modeling of invasion in heterogeneous landscapes: spread of sudden oak death in California (1990–2030)

Abstract: The spread of emerging infectious diseases (EIDs) in natural environments poses substantial risks to biodiversity and ecosystem function. As EIDs and their impacts grow, landscape- to regional-scale models of disease dynamics are increasingly needed for quantitative prediction of epidemic outcomes and design of practicable strategies for control. Here we use spatio-temporal, stochastic epidemiological modeling in combination with realistic geographical modeling to predict the spread of the sudden oak death pathogen (Phytophthora ramorum) through heterogeneous host populations in wildland forests, subject to fluctuating weather conditions. The model considers three stochastic processes: (1) the production of inoculum at a given site; (2) the chance that inoculum is dispersed within and among sites; and (3) the probability of infection following transmission to susceptible host vegetation. We parameterized the model using Markov chain Monte Carlo (MCMC) estimation from snapshots of local- and regional-scale data on disease spread, taking account of landscape heterogeneity and the principal scales of spread. Our application of the model to Californian landscapes over a 40-year period (1990–2030), since the approximate time of pathogen introduction, revealed key parameters driving the spatial spread of disease and the magnitude of stochastic variability in epidemic outcomes. Results show that most disease spread occurs via local dispersal (<250 m) but infrequent long-distance dispersal events can substantially accelerate epidemic spread in regions with high host availability and suitable weather conditions. In the absence of extensive control, we predict a ten-fold increase in disease spread between 2010 and 2030 with most infection concentrated along the north coast between San Francisco and Oregon. Long-range dispersal of inoculum to susceptible host communities in the Sierra Nevada foothills and coastal southern California leads to little secondary infection due to lower host availability and less suitable weather conditions. However, a shift to wetter and milder conditions in future years would double the amount of disease spread in California through 2030. This research illustrates how stochastic epidemiological models can be applied to realistic geographies and used to increase predictive understanding of disease dynamics in large, heterogeneous regions.

A Scalable Blockchain Framework for Secure Transactions in IoT

Abstract: Internet of Things (IoT) and blockchain (BC) technologies have been dominating their respective research domains for some time. IoT offers automation at the finest level in different fields, while BC provides secure transaction processing for asset exchanges. The capability of IoT devices to generate transactions prompts their integration with BC as the next logical step. The biggest challenges in this integration are the scalability of ledger and rate of transaction execution in BC. On one hand, due to their large numbers, IoT devices will generate transactions at a rate which current block chain solutions cannot handle. On the other hand, implementing BC peers onto IoT devices is impossible due to resource constraints. This prohibits direct integration of both technologies in their current state. In this paper, we propose a solution to address these challenges by using a local peer network to bridge the gap. It restricts the number of transactions which enters the global BC by implementing a scalable local ledger, without compromising on the peer validation of transactions at local and global level. The testbed evaluations show significant reduction in the block weight and ledger size on global peers. The solution also indirectly improves the transaction processing rate of all peers due to load distribution.

A model for evaluation and selection of suppliers in global textile and apparel supply chains

Abstract: Purpose – The issue affecting US textile/apparel companies in global business competition is to find suitable suppliers for their operations. The selection and evaluation of their global suppliers to meet the goal of having effective and efficient supply chain operations and strengthening their position in the market become critical for US textile/apparel manufacturers to maintain their competitiveness in today's market. Aims to develop an evaluation model.Design/methodology/approach – The development of a simple, flexible, and easy to use evaluation model that includes the consideration of five main clusters to reflect the performance of a global supplier in a textile/apparel supply chain.Findings – A case presented in this paper shows that the model provides textile/apparel companies with an easy way to evaluate their suppliers and make their selection of suppliers more efficient and effective. Most textile/apparel companies using this model can help them establish strategic alliance with global supplie...

Evidence-Based Practice for Teaching Academics to Students With Severe Developmental Disabilities

Abstract: A review of the literature was conducted for articles published between 2003 and 2010 to build a case for the degree to which evidence-based practices were documented for teaching academic skills to students with severe developmental disabilities. This review extended earlier comprehensive work in literacy, mathematics, and science for the population in question. A total of 18 studies met the Horner et al. (2005) quality indicator criteria. In general, time delay and task analytic instruction were found to be evidence-based practices. In addition, specific target responses were defined to show academic learning, with the most prevalent target responses being discrete responses; the type of systematic prompting and feedback used most often was time delay, while the component used least often was stimulus fading/shaping; and teaching formats used most often were massed trials and one-to-one instruction.