History-dependent percolation on multiplex networks

The structure of interconnected systems and its impact on the system dynamics is a much-studied cross-disciplinary topic. Although various critical phenomena have been found in different models, study of the connections between different percolation transitions is still lacking. Here we propose a unified framework to study the origins of the discontinuous transitions of the percolation process on interacting networks. The model evolves in generations with the result of the present percolation depending on the previous state, and thus is history-dependent. Both theoretical analysis and Monte Carlo simulations reveal that the nature of the transition remains the same at finite generations but exhibits an abrupt change for the infinite generation. We use brain functional correlation and morphological similarity data to show that our model also provides a general method to explore the network structure and can contribute to many practical applications, such as detecting the abnormal structures of human brain networks.     

Building a gold standard to construct search filters: a case study with biomarkers for oral cancer

Objective:

To support clinical researchers, librarians and informationists may need search filters for particular tasks. Development of filters typically depends on a “gold standard” dataset. This paper describes generalizable methods for creating a gold standard to support future filter development and evaluation using oral squamous cell carcinoma (OSCC) as a case study. OSCC is the most common malignancy affecting the oral cavity. Investigation of biomarkers with potential prognostic utility is an active area of research in OSCC. The methods discussed here should be useful for designing quality search filters in similar domains.

Methods:

The authors searched MEDLINE for prognostic studies of OSCC, developed annotation guidelines for screeners, ran three calibration trials before annotating the remaining body of citations, and measured inter-annotator agreement (IAA).

Results:

We retrieved 1,818 citations. After calibration, we screened the remaining citations (n = 1,767; 97.2%); IAA was substantial (kappa = 0.76). The dataset has 497 (27.3%) citations representing OSCC studies of potential prognostic biomarkers.

Conclusions:

The gold standard dataset is likely to be high quality and useful for future development and evaluation of filters for OSCC studies of potential prognostic biomarkers.

Implications:

The methodology we used is generalizable to other domains requiring a reference standard to evaluate the performance of search filters. A gold standard is essential because the labels regarding relevance enable computation of diagnostic metrics, such as sensitivity and specificity. Librarians and informationists with data analysis skills could contribute to developing gold standard datasets and subsequent filters tuned for their patrons'' domains of interest.     

Higher Education,College Degree Major,and Police Occupational Attitudes

Existing police research has produced mixed results regarding the benefits of college education on the outlooks of officers. In addressing many of the well-documented methodological concerns of prior research, the current study augments the existing police education-occupational attitudes literature by examining the impact of varying levels of education (i.e. high school, some college, and bachelor’s degree and higher) on officers’ job satisfaction, views of top management, and role orientation(s). In addition, among those with a bachelor’s degree, the relevance of degree major on officers’ occupational outlooks is assessed. Our results address and inform advocacy efforts to make college education a bona fide occupational qualification.     

Detecting bias in meta-analyses of distance education research: big pictures we can rely on

This article has two interrelated purposes. The first is to explain how various forms of bias, if introduced during any stage of a meta-analysis, can provide the consumer with a misimpression of the state of a research literature. Five of the most important bias-producing aspects of a meta-analysis are presented and discussed. Second, armed with this information, we examine 15 meta-analyses of the literatures of distance education (DE), online learning (OL), and blended learning (BL), conducted from 2000 to 2014, with the intention of assessing potential sources of bias in each. All of these meta-analyses address the question: “How do students taking courses through DE, OL, and BL compare to students engaged in pure classroom instruction in terms of learning achievement outcomes?” We argue that questions asked by primary researchers must change to reflect issues that will drive improvements in designing and implementing DE, OL, and BL courses.     

Acute short-term sleep deprivation does not affect metacognitive monitoring captured by confidence ratings: a systematic literature review

This article presents the results of a systematic review of the literature surrounding the effects that acute sleep deprivation has on metacognitive monitoring. Metacognitive monitoring refers to the ability to accurately assess one’s own performance and state of knowledge. The mechanism behind this assessment is captured by subjective feelings of confidence concerning the accuracy of our judgments or performance. These judgments influence decision behavior. How well these subjective feelings fit with reality is critical for good decision making. For example, a driver who is overconfident in their ability to remain vigilant after a night without sleep is at risk of having an accident. A learner who is overconfident in their ability to perform well on an exam without sleep is at risk of failing. A break down in metacognitive monitoring might be responsible for the increase in poor decision making observed when people are sleep deprived. Using defined search terms and exclusion criteria, electronic database searches identified ten empirical studies suitable for review. Participants in these studies completed performance-based tasks, typically cognitive, while remaining awake for 28–63 hours. In all studies, metacognitive monitoring was assessed via confidence ratings either pre-, on-, or post-task. Extended wakefulness had a significant negative effect on performance in most studies. Evidencing good monitoring, however, the monitoring estimates such as confidence also tended to decline. Moreover, two critical variables that assess the fit of these estimates to actual performance (bias and discrimination) were mostly unaffected by the number of hours awake. Still, some results indicated that these variables may be affected by substances intended to fight sleep deprivation, such as modafinil. Within the limitations of extant literature (e.g., a sampling bias towards young adult male participants), empirical observations to date converge to suggest that metacognitive monitoring remains largely unaffected by the examined quantities of acute sleep deprivation (up to 63 hours).     

A factor analytic and reliability study of the devereux elementary school behavior rating scale

The inter-rater and test-retest reliabilities of the Devereux Elementary School Behavior (DESB) Rating Scale were found to be satisfactory when averaged over two raters. Two separate factor analyses of the eleven subscales revealed three broadband factors: Classroom Management Problem, Self-Reliant Learner, and Seeks Teacher Approval. Each broad-band or major factor is composed of a cluster of subscales that describe the different facets of the three main factors.