Modeling Fuzzy Data in Qualitative Marketing Research

In marketing, qualitative data are used in theory development to investigate marketing phenomena in more depth. After qualitative data are collected, the judgment-based classification of items into categories is routinely used to summarize and communicate the information contained in the data. In this article, the authors provide marketing researchers with a method that (1) provides useful substantive information about the proportion and degree to which items belong to several categories and (2) measures the classification accuracy of the judges. The model is called the fuzzy latent class model (FLCM), because it extends Dillon and Mulani\u27s (1984) latent class model by freeing it from the restrictive assumption that all items are crisp for a given categorization. Instead, FLCM allows for items to be either crisp or fuzzy. Crisp items belong exclusively to one category, whereas fuzzy items belong—in varying degree—to multiple categories. This relaxation in the assumption about the nature of qualitative data makes FLCM more widely applicable: Qualitative data in marketing research are often fuzzy, because they involve open-ended descriptions of complex phenomena. The authors also propose a moment-based measure of overall data fuzziness that is bounded by 0 (completely crisp) and 1 (completely fuzzy)

Low-Temperature Growth of Graphene on a Semiconductor

The industrial realization of graphene has so far been limited by challenges related to the quality, reproducibility, and high process temperatures required to manufacture graphene on suitable substrates. We demonstrate that epitaxial graphene can be grown on transition metal treated 6H-SiC(0001) surfaces, with an onset of graphitization starting around $450-500^\circ\text{C}$. From the chemical reaction between SiC and thin films of Fe or Ru, $\text{sp}^{3}$ carbon is liberated from the SiC crystal and converted to $\text{sp}^{2}$ carbon at the surface. The quality of the graphene is demonstrated using angle-resolved photoemission spectroscopy and low-energy electron diffraction. Furthermore, the orientation and placement of the graphene layers relative to the SiC substrate is verified using angle-resolved absorption spectroscopy and energy-dependent photoelectron spectroscopy, respectively. With subsequent thermal treatments to higher temperatures, a steerable diffusion of the metal layers into the bulk SiC is achieved. The result is graphene supported on magnetic silicide or optionally, directly on semiconductor, at temperatures ideal for further large-scale processing into graphene based device structures.Comment: 10 pages, 4 figures, 51 reference

A Simplified Method for Patterning Graphene on Dielectric Layers

The large-scale formation of patterned, quasi-freestanding graphene structures supported on a dielectric has so far been limited by the need to transfer the graphene onto a suitable substrate and contamination from the associated processing steps. We report μm scale, few-layer graphene structures formed at moderate temperatures (600–700 °C) and supported directly on an interfacial dielectric formed by oxidizing Si layers at the graphene/substrate interface. We show that the thickness of this underlying dielectric support can be tailored further by an additional Si intercalation of the graphene prior to oxidation. This produces quasi-freestanding, patterned graphene on dielectric SiO2 with a tunable thickness on demand, thus facilitating a new pathway to integrated graphene microelectronics

A pooled-analysis of age and sex based coronary artery calcium scores percentiles

Funding The authors of this publication did not receive any grant from funding agencies in the public, commercial, or not-for-profit sector to support this research effort. Dr. Paolo Raggi was supported by a grant (RES0016825) from the Faculty of Medicine and Dentistry at the University of Alberta, Edmonton, AB, Canada. Dr. Matthew J. Budoff has Grant support from general electric and NIH. None of the other authors declares a conflict of interest. Publisher Copyright: © 2020 [The Author/The Authors]Background: Age and sex based coronary artery calcium score (CAC) percentiles have been used to improve coronary artery disease (CAD) risk prediction. However, the main limitation of the CACs percentiles currently in use is that they are often based on single studies. We performed a pooled analysis of all available studies that reported on CAC percentiles, in order to develop more generalizable age and sex nomograms. Methods: PubMed/Medline and Embase were searched for studies that reported nomograms of age and sex-based CACs percentiles. Studies were included if they reported data collected among asymptomatic individuals without a history of cardiovascular disease. Absolute CACs for each specific percentile stratum were pooled and new percentiles were generated taking into account the sample size of the study. Results: We found 831 studies, of which 12 met the inclusion criteria. Data on CACs percentiles of 134,336 Western and 33,488 Asians were pooled separately, rendering a weighted CACs percentile nomogram available at https://www.calciumscorecalculator.com. Our weighted percentiles differed by up to 24% from the nomograms in use today. Conclusions: Our pooled age and sex based CACs percentiles based on over 155,000 individuals should provide a measure of risk that is more applicable to a wider population than the ones currently in use and hopefully will lead to better risk assessment and treatment decisions.Peer reviewe

When are intermediate processes of the same stochastic order?

Let Zm(n) represent the mth largest order statistic in a random sample of size n. Here we study the process Z[mt](n), t> 0, where m(n) is an intermediate sequence such that m --> [infinity], m/n --> 0 as n --> [infinity].intermediate order statistics differentiable domains of attraction extremal distribution