Visual Behavior in Social Interaction

Visual behavior appears to provide information at several different communicational levels in social interaction. As a dependent variable, it has been used to measure stable individual and group differences, the regulation of the flow of conversation, and the search for feedback in an interaction. As an independent variable, it has been shown to influence emotional responses and cognitive attributions. Research efforts to specify and understand the functioning of visual behavior at each level are reviewed. An example of a multi-level approach to an area is provided by a survey of the research on visual behavior in relation to interpersonal attraction and involvement. Finally, some speculations about future questions and concerns are presented.     

Eyewitness accuracy and confidence: Within- versus between-subjects correlations.

Previous researchers using between-subjects comparisons have found eyewitness confidence and accuracy to be only negligibly correlated. In this study, we examined the predictive power of confidence in within-subject terms. Ninety-six subjects answered, and made confidence ratings for, a series of questions about a crime they witnessed. The average between-subjects and within-subject accuracy–confidence correlations were comparably low: r?=?14 (pr?=?.17 (pr?=?-.09 within subjects), but more strongly with confidence (r?=?-.27 within subjects). This pattern was obtained for both between-subjects and within-subject comparisons. The theoretical and practical implications of these results are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mining protein kinases regulation using graphical models

Abnormal kinase activity is a frequent cause of diseases, which makes kinases a promising pharmacological target. Thus, it is critical to identify the characteristics of protein kinases regulation by studying the activation and inhibition of kinase subunits in response to varied stimuli. Bayesian network (BN) is a formalism for probabilistic reasoning that has been widely used for learning dependency models. However, for high-dimensional discrete random vectors the set of plausible models becomes large and a full comparison of all the posterior probabilities related to the competing models becomes infeasible. A solution to this problem is based on the Markov Chain Monte Carlo (MCMC) method. This paper proposes a BN-based framework to discover the dependency correlations of kinase regulation. Our approach is to apply the MCMC method to generate a sequence of samples from a probability distribution, by which to approximate the distribution. The frequent connections (edges) are identified from the obtained sampling graphical models. Our results point to a number of novel candidate regulation patterns that are interesting in biology and include inferred associations that were unknown.     

Modeling conserved structure patterns for functional noncoding RNA

RNA regulation has been increasingly recognized as a potential and perhaps overlooked genetics of higher organisms. Noncoding RNAs (ncRNA) may play various catalytic and regulatory roles in the genetic operating system. Recent studies using comparative genomics and molecular genetics show evidence of the presence of varied ncRNAs. Unlike protein coding genes, there is a lack of comparable information or outstanding signal for ncRNAs. Traditional computational linguistics show limitations in modeling complicated secondary structures and prevent us from identifying structure-function relationships of ncRNAs. This paper presents a novel approach, based on a set of distance constraints, to model the predicted RNA secondary structures. Further, a filtering schema is presented to identify matched models for the queried secondary structures.     

Impact of Copper-Doped Mesoporous Bioactive Glass Nanospheres on the Polymerisation Kinetics and Shrinkage Stress of Dental Resin Composites

We embedded copper-doped mesoporous bioactive glass nanospheres (Cu-MBGN) with antibacterial and ion-releasing properties into experimental dental composites and investigated the effect of Cu-MBGN on the polymerisation properties. We prepared seven composites with a BisGMA/TEGDMA (60/40) matrix and 65 wt.% total filler content, added Cu-MBGN or a combination of Cu-MBGN and silanised silica to the silanised barium glass base, and examined nine parameters: light transmittance, degree of conversion (DC), maximum polymerisation rate (R_max), time to reach R_max, linear shrinkage, shrinkage stress (PSS), maximum PSS rate, time to reach maximum PSS rate, and depth of cure. Cu-MBGN without silica accelerated polymerisation, reduced light transmission, and had the highest DC (58.8 ± 0.9%) and R_max (9.8 ± 0.2%/s), but lower shrinkage (3 ± 0.05%) and similar PSS (0.89 ± 0.07 MPa) versus the inert reference (0.83 ± 0.13 MPa). Combined Cu-MBGN and silica slowed the R_max and achieved a similar DC but resulted in higher shrinkage. However, using a combined 5 wt.% Cu-MBGN and silica, the PSS resembled that of the inert reference. The synergistic action of 5 wt.% Cu-MBGN and silanised silica in combination with silanised barium glass resulted in a material with the highest likelihood for dental applications in future.     

Struktur und Schmelzverhalten von 4,4′-substituierten Thiobenzaniliden

Structure and Melting Behaviour of 4,4′-Substituted Thiobenzanilides The synthesis of 4,4′-substituted thiobenzanilides, by means of thionisation of the respective substituted carbonamides, gives exclusively compounds which do not form a liquid crystal phase on melting. This result corresponds with the experience that this reaction should preferably yield the strongly angular E-conformation.