Using the Diffusion of Innovation Concept to Explain the Factors That Contribute to the Adoption Rate of E-journal Publishing

This paper reports on the factors that contribute to the adoption rate of e-journal publishing based upon responses from 82 Malaysian journal publishers. Drawing upon the theory of innovation diffusion, the study examines the role of awareness, three organization variables (publication size, age of the journal, and experience of editors), and attributes of e-journals (relative advantage, compatibility, complexity, trialability and observability) as influences to the rate of e-journal publishing adoption. Findings show that only two attributes—complexity and trialability—emerge as significant contributors to e-journal adoption rates, and all three organization variables—journal's age, publication size, and editorial experience—are significant. Collectively, these five significant variables explained 57.8% of the variance in adoption rate. We discuss the results and implication of the findings with respect to the wider context of e-journal publishing.     

Blind source separation filters-based-fault detection and isolation in a three tank system

Fault detection and Isolation takes a strategic position in modern industrial processes for which various approaches are proposed. These approaches are usually developed and based on a consistency test between an observed state of the process provided by sensors and an expected behaviour provided by a mathematical model of the system. These methods require a reliable model of the system to be monitored which is a complex task. Alternatively, we propose in this paper to use blind source separation filters (BSSFs) in order to detect and isolate faults in a three tank pilot plant. This technique is very beneficial as it uses blind identification without an explicit mathematical model of the system. The independent component analysis (ICA), relying on the assumption of the statistical independence of the extracted sources, is used as a tool for each BSSF to extract signals of the process under consideration. The experimental results show the effectiveness and robustness of this approach in detecting and isolating faults that are on sensors in the system.     

An integrated model for economic design of chi-square control chart and maintenance planning

Considered process in this article is a two-stage dependent process. Each item in this process has two quality characteristics as x and y while x and y are related to the stage 1 and 2, respectively. Each stage has two operational states as the in-control state and out-of-control state and transition time from the in-control state to the out-of-control state follows a general continues distribution function. The process is monitored using a chi-square control chart. An integrated model that coordinates the decisions related to the economic design of the used control chart and maintenance planning is presented. For the evaluation of the integrated model performance, a stand-alone maintenance model is also presented, and the performance of these two models is compared with each other.     

A coordinate descent algorithm for computing penalized smooth quantile regression

The computation of penalized quantile regression estimates is often computationally intensive in high dimensions. In this paper we propose a coordinate descent algorithm for computing the penalized smooth quantile regression (cdaSQR) with convex and nonconvex penalties. The cdaSQR approach is based on the approximation of the objective check function, which is not differentiable at zero, by a modified check function which is differentiable at zero. Then, using the maximization-minimization trick of the gcdnet algorithm (Yang and Zou in, J Comput Graph Stat 22(2):396–415, 2013), we update each coefficient simply and efficiently. In our implementation, we consider the convex penalties \(\ell _1+\ell _2\) and the nonconvex penalties SCAD (or MCP) \(+ \ell _2\). We establishe the convergence property of the csdSQR with \(\ell _1+\ell _2\) penalty. The numerical results show that our implementation is an order of magnitude faster than its competitors. Using simulations we compare the speed of our algorithm to its competitors. Finally, the performance of our algorithm is illustrated on three real data sets from diabetes, leukemia and Bardet–Bidel syndrome gene expression studies.     

Habitat fragmentation and conservation strategies for a rare forest habitat in the Florida Keys archipelago

Habitat loss and fragmentation are principal causes for population declines and the loss of biodiversity across the globe. In the United States, tropical hardwood hammock is a threatened forest ecosystem that occurs only in extreme south Florida, primarily on the Florida Keys archipelago. This rare forest type is characterized by high plant diversity that is strongly influenced by tropical, mast-producing trees and shrubs of West Indian origin. Tropical hardwood hammocks in the Florida Keys provide important habitat for resident and migratory birds, particularly Neotropical species that rely on suitable stopover habitat during migration. The Florida Keys are under intense development pressure, particularly in higher elevation sites where tropical hardwood hammock occurs. With exception of a survey completed during 1991 in the Upper Keys, information regarding habitat loss and current coverage, conservation status, and how best to conserve remaining patches of this rare forest habitat are lacking. We used a Geographic Information Systems approach to assess the extent of loss and fragmentation of tropical hardwood hammock in the upper Keys during 1991–2004, quantify area and number of hammock patches under private ownership and in conservation status throughout the Florida Keys as of 2004, and evaluate strategies to most effectively conserve large blocks of remaining tropical hardwood hammock. Total remaining hammock habitat throughout the Keys encompassed 3,712 ha and hammock habitat declined by 31% in the upper Keys during 1991–2004. Hammock habitat in the upper Keys encompassed 1,962 ha among 124 habitat patches (median = 1.5 ha, range = 0.1–205.7 ha), of which 1,066 ha (54%) were under conservation status. Hammock habitat in the lower Keys encompassed 1,750 ha among 102 patches (median = 4.4 ha, range = 0.3–96.3 ha), of which 1,283 ha (73%) were protected under conservation status. Approximately 37% of total remaining hammock habitat remained unprotected. However, our analyses revealed that many unprotected areas >20 ha were contiguous with protected hammocks. Safeguarding 22 partially protected patches >20 ha (17% of remaining patches) would protect an additional 750 ha of hammock habitat, which represents 55% of all remaining unprotected hammock habitat in the Keys, and would increase the mean patch size of these larger forest patches from 55 to 89 ha. Consequently, strategically focusing conservation efforts on remaining forest patches of tropical hardwood hammock >20 ha in size and contiguous to existing protected areas represents the most effective use of conservation dollars and would provide greater ecological benefits than conservation of small patches of highly fragmented habitat.     

“She was a little bit unrealistic”: Choice in healthcare decision making for older people

This paper examines autonomy, choice, options, and power in healthcare decision making for older people. Using discourse analysis and a case study from data gathered as part of an ethnographic field study we critique a common conceptualization of healthcare decision making as patients choosing from an array of options offered by healthcare providers. A discourse of “giving options and being realistic” used by healthcare providers is contrasted with the experience of a single patient's transitional care from hospital to home after hip fracture. This illustrates how a wide variety of actors, institutions, values, and resources take precedence in determining a discharge destination. While the accounts given by healthcare providers cast patient choice in respectful terms, an ethnographic approach illustrates that the “choices” are structured by a discourse which simplifies the complexity of what is offered and who gets to choose. In the case study the patient's choice was subjugated by expertise and institutional concerns; her options were largely illusory; and her autonomy was “at risk” due to her age, poor health, and limited resources. We use Foucault's ideas about discourse and governmentality to question the scope of agency in healthcare decision making. We argue that the conceptualization of informed patients making autonomous choices acts as “misdirection” which deflects problem solving and discussion away from a productive examination of the differences between healthcare system offerings and client needs. We conclude by posing questions to reorient the debate surrounding healthcare decision making for older adults and recommend a more participatory approach to designing social services.     

When exposure is subject to nondifferential misclassification,are validation data helpful in testing for an exposure–disease association?

Consider assessing the evidence for an exposure variable and a disease variable being associated, when the true exposure variable is more costly to obtain than an error‐prone but nondifferential surrogate exposure variable. From a study design perspective, there are choices regarding the best use of limited resources. Should one acquire the true exposure status for fewer subjects or the surrogate exposure status for more subjects? The issue of validation is also central, i.e., should we simultaneously measure the true and surrogate exposure variables on a subset of study subjects? Using large‐sample theory, we provide a framework for quantifying the power of testing for an exposure–disease association as a function of study cost. This enables us to present comparisons of different study designs under different suppositions about both the relative cost and the performance (sensitivity and specificity) of the surrogate variable. We present simulations to show the applicability of our theoretical framework, and we provide a case‐study comparing results from an actual study to what could have been seen had true exposure status been ascertained for a different proportion of study subjects. We also describe an extension of our ideas to a more complex situation involving covariates. The Canadian Journal of Statistics 47: 222–237; 2019 © 2019 Statistical Society of Canada     

Inequality of opportunity and (unequal) opportunities in the youth labour market: How is the Arab world different?

The Middle East and North Africa (MENA) labour market is emblematic of widespread youth unemployment and high discouragement rates, experiencing disproportionately high levels of unemployment among educated young people. Using ILO School-to-Work Transition Surveys for Egypt, Jordan and Tunisia, the authors explore whether this is related to inequality of opportunity or to deeper structural characteristics that create a mismatch between skill demand and supply on the labour market. The low availability of high-skilled jobs and the low value placed on skills gained through the system of vocational training are found to have high explanatory power.     

B Butterfly Campaign: A social marketing campaign to promote normal childbirth among first-time pregnant women

Problem

The steep increase and inappropriateness of caesarean birth represent a healthcare problem in Iran.

Multivariate association test for rare variants controlling for cryptic and family relatedness

In genetic studies of complex diseases, multiple measures of related phenotypes are often collected. Jointly analyzing these phenotypes may improve statistical power to detect sets of rare variants affecting multiple traits. In this work, we consider association testing between a set of rare variants and multiple phenotypes in family‐based designs. We use a mixed linear model to express the correlations among the phenotypes and between related individuals. Given the many sources of correlations in this situation, deriving an appropriate test statistic is not straightforward. We derive a vector of score statistics, whose joint distribution is approximated using a copula. This allows us to have closed‐form expressions for the p‐values of several test statistics. A comprehensive simulation study and an application to Genetic Analysis Workshop 18 data highlight the gains associated with joint testing over univariate approaches, especially in the presence of pleiotropy or highly correlated phenotypes. The Canadian Journal of Statistics 47: 90–107; 2019 © 2018 Statistical Society of Canada