Hierarchical graphical bayesian models in psychology

The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological research. The aim of this contribution is to introduce suggestions for the improvement of hierarchical Bayesian graphical models in psychology. This novel set of suggestions stems from the description and comparison between two main approaches concerned with the use of plate notation and distribution pictograms. It is concluded that the combination of relevant aspects of both models might improve the use of powerful hierarchical Bayesian graphical models in psychology

Evidence for the Adverse Effect of Starvation on Bone Quality: A Review of the Literature

Malnutrition and starvation’s possible adverse impacts on bone health and bone quality first came into the spotlight after the horrors of the Holocaust and the ghettos of World War II. Famine and food restrictions led to a mean caloric intake of 200–800 calories a day in the ghettos and concentration camps, resulting in catabolysis and starvation of the inhabitants and prisoners. Severely increased risks of fracture, poor bone mineral density, and decreased cortical strength were noted in several case series and descriptive reports addressing the medical issues of these individuals. A severe effect of severely diminished food intake and frequently concomitant calcium- and Vitamin D deficiencies was subsequently proven in both animal models and the most common cause of starvation in developed countries is anorexia nervosa. This review attempts to summarize the literature available on the impact of the metabolic response to Starvation on overall bone health and bone quality

Individual differences in causal learning and decision making

This is an accepted author manuscript of an article subsequently published by Elsevier. The final published version can be found here: http://dx.doi.org/10.1016/j.actpsy.2005.04.003In judgment and decision making tasks, people tend to neglect the overall frequency of base-rates when they estimate the probability of an event; this is known as the base-rate fallacy. In causal learning, despite people s accuracy at judging causal strength according to one or other normative model (i.e., Power PC, DP), they tend to misperceive base-rate information (e.g., the cause density effect). The present study investigates the relationship between causal learning and decision making by asking whether people weight base-rate information in the same way when estimating causal strength and when making judgments or inferences about the likelihood of an event. The results suggest that people differ according to the weight they place on base-rate information, but the way individuals do this is consistent across causal and decision making tasks. We interpret the results as reflecting a tendency to differentially weight base-rate information which generalizes to a variety of tasks. Additionally, this study provides evidence that causal learning and decision making share some component processes

Surface-modified nanoparticles as anti-biofilm filler for dental polymers

The objective of the study was to synthesis silica nanoparticles modified with (i) a tertiary amine bearing two t-cinnamaldehyde substituents or (ii) dimethyl-octyl ammonium, alongside the well-studied quaternary ammonium polyethyleneimine nanoparticles. These were to be evaluated for their chemical and mechanical properties, as well for antibacterial and antibiofilm activity. Samples were incorporated in commercial dental resin material and the degree of monomer conversion, mechanical strength, and water contact angle were tested to characterize the effect of the nanoparticles on resin material. Antibacterial activity was evaluated with the direct contact test and the biofilm inhibition test against Streptococcus mutans. Addition of cinnamaldehyde-modified particles preserved the degree of conversion and compressive strength of the base material and increased surface hydrophobicity. Quaternary ammonium functional groups led to a decrease in the degree of conversion and to low compressive strength, without altering the hydrophilic nature of the base material. In the direct contact test and the anti-biofilm test, the polyethyleneimine particles exhibited the strongest antibacterial effect. The cinnamaldehyde-modified particles displayed antibiofilm activity, silica particles with quaternary ammonium were ineffective. Immobilization of t-cinnamaldehyde onto a solid surface via amine linkers provided a better alternative to the well-known quaternary ammonium bactericides

The effects of mental steps and compatibility on Bayesian reasoning

Four laboratory studies were conducted to test the hypothesis that correct Bayesian reasoning can be predicted by two factors of task complexity — the number of mental steps required to reach the normative solution, and the compatibility between the framing of data presented and the framing of the question posed. The findings show that participants performed better on frequency format questions only when one mental step was required to solve the task and when the data were in a compatible frequency format. By contrast, participants performed more poorly on more complicated tasks which required more mental steps (in a compatible frequency or probability format) or when the data and question formats were incompatible (Studies 1 and 2). Incompatibility between data and question formats was also associated with higher reaction times (Study 2b). Furthermore, on problems that incorporated incompatibility between the data sample size and the target (question) sample size, participants performed better on the probability question than the frequency question, regardless of data format (Study 3). The latter findings highlight the ecological advantage of translating data into probability terms, which are normalized in a range between 0 and 1, and thus can be transferred from one situation to another

Statistical Literacy Among Applied Linguists and Second Language Acquisition Researchers

The importance of statistical knowledge in applied linguistics and second language acquisition (SLA) research has been emphasized in recent publications. However, the last investigation of the statistical literacy of applied linguists occurred more than 25 years ago (Lazaraton, Riggenbach, & Ediger, 1987). The current study undertook a partial replication of this older work by investigating (a) applied linguists’ general experiences with statistics, (b) underlying factors that constitute applied linguists’ knowledge about and attitudes toward statistics, and (c) variables that predict attitudes toward statistics and statistical self-efficacy. Three hundred thirty-one scholars of applied linguistics and SLA completed a questionnaire. Eighty percent had taken a statistics class; however, only 14% of doctoral students and 30% of professors felt that their statistical training was adequate. A factor analysis of participants’ knowledge of statistical terms revealed three factors: common inferential statistics knowledge, advanced statistics knowledge, and basic descriptive statistics knowledge. An analysis of participants’ attitudes toward statistics revealed two factors: statistics are important and lack of statistical confidence. Regression analyses found that a quantitative research orientation was the strongest predictor of positive attitudes toward statistics; nevertheless, participants also expressed support for qualitative research. Recommendations for improving quantitative methods in our field are made based on our findings

Screening for prostate cancer: systematic review and meta-analysis of randomised controlled trials

Objective To examine the evidence on the benefits and harms of screening for prostate cancer

Book reviews

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45456/1/11077_2004_Article_BF00137631.pd

Alternative Antimicrobial Approach: Nano-Antimicrobial Materials

Despite numerous existing potent antibiotics and other antimicrobial means, bacterial infections are still a major cause of morbidity and mortality. Moreover, the need to develop additional bactericidal means has significantly increased due to the growing concern regarding multidrug-resistant bacterial strains and biofilm associated infections. Consequently, attention has been especially devoted to new and emerging nanoparticle-based materials in the field of antimicrobial chemotherapy. The present review discusses the activities of nanoparticles as an antimicrobial means, their mode of action, nanoparticle effect on drug-resistant bacteria, and the risks attendant on their use as antibacterial agents. Factors contributing to nanoparticle performance in the clinical setting, their unique properties, and mechanism of action as antibacterial agents are discussed in detail