Kent State University

About: Kent State University is a education organization based out in Kent, Ohio, United States. It is known for research contribution in the topics: Liquid crystal & Population. The organization has 10897 authors who have published 24607 publications receiving 720309 citations. The organization is also known as: Kent State & KSU.

Averting biodiversity collapse in tropical forest protected areas

Abstract: The rapid disruption of tropical forests probably imperils global biodiversity more than any other contemporary phenomenon(1-3). With deforestation advancing quickly, protected areas are increasingly becoming final refuges for threatened species and natural ecosystem processes. However, many protected areas in the tropics are themselves vulnerable to human encroachment and other environmental stresses(4-9). As pressures mount, it is vital to know whether existing reserves can sustain their biodiversity. A critical constraint in addressing this question has been that data describing a broad array of biodiversity groups have been unavailable for a sufficiently large and representative sample of reserves. Here we present a uniquely comprehensive data set on changes over the past 20 to 30 years in 31 functional groups of species and 21 potential drivers of environmental change, for 60 protected areas stratified across the world's major tropical regions. Our analysis reveals great variation in reserve 'health': about half of all reserves have been effective or performed passably, but the rest are experiencing an erosion of biodiversity that is often alarmingly widespread taxonomically and functionally. Habitat disruption, hunting and forest-product exploitation were the strongest predictors of declining reserve health. Crucially, environmental changes immediately outside reserves seemed nearly as important as those inside in determining their ecological fate, with changes inside reserves strongly mirroring those occurring around them. These findings suggest that tropical protected areas are often intimately linked ecologically to their surrounding habitats, and that a failure to stem broad-scale loss and degradation of such habitats could sharply increase the likelihood of serious biodiversity declines.

Two-step boron and nitrogen doping in graphene for enhanced synergistic catalysis.

Abstract: Don't be a dope: be a double dope! Graphene was doped with both boron and nitrogen at well-defined doping sites to induce a synergistic effect that boosts its catalytic activity for oxygen reduction (see structure). The excellent catalytic performance of the new metal-free catalyst is comparable to that of commercial Pt/C.

Reducing Confusion about Grounded Theory and Qualitative Content Analysis: Similarities and Differences

Abstract: Introduction Using an appropriate research method for inquiry is critical to successful research. Grounded theory and qualitative content analysis share similarities. Both are based on naturalistic inquiry that entails identifying themes and patterns and involves rigorous coding. They are both used to analyze and interpret qualitative data; however, the similarities and differences in grounded theory and qualitative content analysis have not been clarified in the literature (Priest, Roberts, & Woods, 2002), nor have they been consistently considered. To illustrate, both have been considered equivalent approaches to interpret qualitative data (e.g., Priest et al., 2002). Grounded theory was treated as a research methodology, and content analysis as a method (e.g., Crotty, 2003); furthermore, grounded theory was considered a theoretical framework and content analysis a research method of textual data analysis (e.g., Patton, 2002). Qualitative content analysis was considered a strategy for the analysis of qualitative descriptive studies (Sandelowski, 2000) and a technique with overtones of other research methods, such as ethnographic and grounded theory (Altheide, 1987). Qualitative content analysis was unknown as a research method until recently, especially in English-speaking countries, because of the dominance of quantitative content analysis (Schreier, 2012). Moreover, a researcher's approach purportedly following grounded theory actually seems closer to qualitative content analysis or other methods (Sandelowski & Barroso, 2003; Suddaby, 2006). Sandelowski and Barroso (2003) cited the discrepancy between "method claims and the actual use of methods" (p. 905) in research papers. Novice researchers, especially students who want to conduct qualitative research, are often confused by the characteristics of the two as result of the lack of comparative references. Some researchers who stated they had used grounded theory actually used qualitative content analysis, which incorporates some procedures of grounded theory, such as open coding or memoing (Sandelowski & Barroso, 2003). Thus, the purpose of this paper is to clarify ambiguities about the characteristics of grounded theory and qualitative content analysis. Using our own research as examples, we have discussed the similarities and differences in the two in the following six areas: a) background and philosophical basis, b) unique characteristics of each method, c) goals and rationale of each method, d) data analysis process, e) outcomes of the research, and f) evaluation of trustworthiness of research. We have also discussed the strengths and weaknesses of each. Through this paper, we expect to provide knowledge that can assist novice researchers in the selection of appropriate research methods for their inquiries. Background and Philosophical Basis Grounded Theory The term grounded theory was introduced in The Discovery of Grounded Theory (1967) by Glaser and Strauss as "the discovery of theory from data--systematically obtained and analyzed in social research" (p. 1). Instead of verification of theories, they introduced a research method to arrive at a "theory suited to its supposed uses" contrasting with a "theory generated by logical deduction from a priori assumptions" (p. 3). According to Strauss and Corbin (1994) it is "a general methodology, a way of thinking about and conceptualizing data" (p. 275). The Grounded Theory Institute, run by Glaser, one of the founders of grounded theory, defined it as follows: Grounded Theory is an inductive methodology. Although many call Grounded Theory a qualitative method, it is not. It is a general method. It is the systematic generation of theory from systematic research. It is a set of rigorous research procedures leading to the emergence of conceptual categories. …

A benchmark study on the thermal conductivity of nanofluids

Abstract: This article reports on the International Nanofluid Property Benchmark Exercise, or INPBE, in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles or “nanofluids,” was measured by over 30 organizations worldwide, using a variety of experimental approaches, including the transient hot wire method, steady-state methods, and optical methods. The nanofluids tested in the exercise were comprised of aqueous and nonaqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (±10% or less) about the sample average with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio, as expected from classical theory. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however, such differences tend to disappear when the data are normalized to the measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.