Individual differences in drivers’ cognitive processing of road safety messages

Using Gray and McNaughton's (2000) revised reinforcement sensitivity theory (r-RST), we examined the influence of personality on processing of words presented in gain-framed and loss-framed anti-speeding messages and how the processing biases associated with personality influenced message acceptance. The r-RST predicts that the nervous system regulates personality and that behaviour is dependent upon the activation of the behavioural activation system (BAS), activated by reward cues and the fight-flight-freeze system (FFFS), activated by punishment cues. According to r-RST, individuals differ in the sensitivities of their BAS and FFFS (i.e., weak to strong), which in turn leads to stable patterns of behaviour in the presence of rewards and punishments, respectively. It was hypothesised that individual differences in personality (i.e., strength of the BAS and the FFFS) would influence the degree of both message processing (as measured by reaction time to previously viewed message words) and message acceptance (measured three ways by perceived message effectiveness, behavioural intentions, and attitudes). Specifically, it was anticipated that, individuals with a stronger BAS would process the words presented in the gain-frame messages faster than those with a weaker BAS and individuals with a stronger FFFS would process the words presented in the loss-frame messages faster than those with a weaker FFFS. Further, it was expected that greater processing (faster reaction times) would be associated with greater acceptance for that message. Driver licence holding students (N = 108) were recruited to view one of four anti-speeding messages (i.e., social gain-frame, social loss-frame, physical gain-frame, and physical loss-frame). A computerised lexical decision task assessed participants’ subsequent reaction times to message words, as an indicator of the extent of processing of the previously viewed message. Self-report measures assessed personality and the three message acceptance measures. As predicted, the degree of initial processing of the content of the social gain-framed message mediated the relationship between the reward sensitive trait and message effectiveness. Initial processing of the physical loss-framed message partially mediated the relationship between the punishment sensitive trait and both message effectiveness and behavioural intention ratings. These results show that reward sensitivity and punishment sensitivity traits influence cognitive processing of gain-framed and loss-framed message content, respectively, and subsequently, message effectiveness and behavioural intention ratings. Specifically, a range of road safety messages (i.e., gain-frame and loss-frame messages) could be designed which align with the processing biases associated with personality and which would target those individuals who are sensitive to rewards and those who are sensitive to punishments.     

Biomass production and small-scale testing of freeze-dried lactic acid bacteria starter strains for cassava fermentations

Based on their predominance in Gari fermentations, as well as suitable technological properties, Lactobacillus plantarum, Lactobacillus fermentum, Weissella paramesenteroides and Leuconostoc mesenteroides strains were investigated for their suitability for development as starter strains for this African traditional fermented cassava product. The strains were grown in optimized growth media in 2 L fermenters, harvested and freeze dried, and then tested in lab-scale cassava mash fermentation trials for their ability to ferment the cassava. The strains performed well and rapidly increased the titratable acidity from 1.1 to 1.3% at 24 h to 1.3–1.6% at 48 h. The benefit of including starter cultures was that it lowered the pH of the product much faster and to lower levels than in the uninoculated control fermentation. The results furthermore indicated that especially the L. plantarum-group strains could be produced as starter strains at low cost. Overall, the results of this study showed that starter strains could be easily and economically produced, and thus represent a feasible possibility for further development for application in the field.     

Haven or hell? Telework,flexibility and family in the e-society: a Marxist analysis

The reconfiguration of the home-work boundary that at-home telework entails has significant implications for gender issues and the use of ubiquitous information and communications technologies (ICTs). By presenting a Marx-inspired dialectical analysis of the family and home as both ‘haven and hell’, we develop a critique of proposed advantages for women home workers. Not only do we question the ability of ICTs to deliver the promises made on their behalf – we show how this socio-technical innovation may in fact contribute to compounding the double-burden of work associated with gender roles within the home. Contemporary critical understanding of the e-society should incorporate the influence of at-home teleworking because of its implications for the use of ubiquitous ICTs in the home environment, the shaping of work relations and its impact on gender issues. This increasing use of ICTs outside of the workplace is matched by the growing consensus within the European Union on the desirability of flexible working coupled with family friendly policies. This paper explores some of the rhetoric and research surrounding the proposed benefits of at home ‘telework’ and the likely cost–benefits, from an employee's perspective, in terms of increased freedom, reduced burden and ‘flexibility’.     

Inferential structure of the NEO Five-Factor Inventory: Construct validity of the Big Four personality clusters.

Four studies investigated the dimensionality of the NEO Five-Factor Inventory (NEO-FFI; P. T. Costa & R. R. McCrae, 1992). In Study 1, four inferential dimensions and four clusters represented the NEO-FFI when 114 undergraduates freely sorted items into categories. Construct validity for four item-clusters derived from the inferential space was obtained in Study 2 based on self-report with 304 undergraduates. Study 3 validated these inferential clusters using self and peer reports for 420 undergraduates. Study 4 validated the cluster scales for predicting quality of life and significant social and cultural behaviours for 110 undergraduates. Implications for implicit personality theory, the number of dimensions issue in personality, and test construction are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of bacterial extracellular polymers in metal uptake in pure bacterial culture and activated sludge—I. Effects of metal concentration

A gel filtration technique afforded a good separation between metal complexed with bacterial extracellular polymers and free metal ions. The complexation of polymers extracted from cultures of Klehsiella aerogenes and activated sludge with cadmium, nickel, manganese and cobalt was demonstrated. The extraction of extracellular polymers from cultures of K. aerogenes and activated sludge reduced the capacity of the cells and flocs to adsorb metal. Adsorption and complexation of metals by cells of K. aerogenes and extracellular polymers extracted from activated sludge were fitted to Freundlich equilibrium isotherms. Saturation of activated sludge polymer binding sites occurred at 10 mg 1^?1 metal additions for all the metals studied except manganese which was complexed to a very limited extent. Cells of K. aerogenes exhibited no saturation effects in the range of metal concentrations studied.Precipitation of metals below a concentration of 1 mg 1^?1 was minimal, with the exception of cadmium precipitation. At a concentration of 10 mg 1^?1, precipitation of cadmium, cobalt and manganese may have been the major mechanism of metal removal. The more soluble metals generally displayed the lowest removals. Concentrations of extracellular polymers and soluble chelating agents may be important in controlling removals of metals which are largely soluble in activated sludge.     

A neutral loss activation method for improved phosphopeptide sequence analysis by quadrupole ion trap mass spectrometry

Recent advances in phosphopeptide enrichment prior to mass spectrometric analysis show genuine promise for characterization of phosphoproteomes. Tandem mass spectrometry of phosphopeptide ions, using collision-activated dissociation (CAD), often produces product ions dominated by the neutral loss of phosphoric acid. Here we describe a novel method, termed Pseudo MS(n), for phosphopeptide ion dissociation in quadrupole ion trap mass spectrometers. The method induces collisional activation of product ions, those resulting from neutral loss(es) of phosphoric acid, following activation of the precursor ion. Thus, the principal neutral loss product ions are converted into a variety of structurally informative species. Since product ions from both the original precursor activation and all subsequent neutral loss product activations are simultaneously stored, the method generates a "composite" spectrum containing fragments derived from multiple precursors. In comparison to analysis by conventional MS/MS (CAD), Pseudo MS(n) shows improved phosphopeptide ion dissociation for 7 out of 10 synthetic phosphopeptides, as judged by an automated search algorithm (TurboSEQUEST). A similar overall improvement was observed upon application of Pseudo MS(n) to peptides generated by enzymatic digestion of a single phosphoprotein. Finally, when applied to a complex phosphopeptide mixture, several phosphopeptides mis-assigned by TurboSEQUEST under the conventional CAD approach were successfully identified after analysis by Pseudo MS(n).     

Isolation,characterization, and quantitative analysis of Microviridin J,a new Microcystis metabolite toxic to Daphnia

This paper describes the purification and characterization of microviridin J, a newly discovered metabolite of Microcystis that causes a lethal molting disruption in Daphnia spp., upon ingestion of living cyanobacterial cells. Microviridin J consists of an acetylated chain of 13 amino acids arranged in three rings and two side chains. Unlike other known isoforms of microviridin, microviridin J contains arginine that imparts a unique solution conformation characterized by proximal hydrophobic interactions between Arg and other regions of the molecule. This eventually results in the formation and stabilization of an additional ring system. Microviridin J potently inhibits porcine trypsin, bovine chymotrypsin, and daphnid trypsin-like proteases. The activity against trypsin is most likely due to Arg and its distinctive conformational interactions. Overall, the data presented for microviridin J emphasize once again the ability of cyanobacteria to produce numerous and potent environmental toxins.     

Stability of feature selection algorithms: a study on high-dimensional spaces

With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive work on the stability of learning algorithms, the stability of feature selection algorithms has been relatively neglected. This study is an attempt to fill that gap by quantifying the sensitivity of feature selection algorithms to variations in the training set. We assess the stability of feature selection algorithms based on the stability of the feature preferences that they express in the form of weights-scores, ranks, or a selected feature subset. We examine a number of measures to quantify the stability of feature preferences and propose an empirical way to estimate them. We perform a series of experiments with several feature selection algorithms on a set of proteomics datasets. The experiments allow us to explore the merits of each stability measure and create stability profiles of the feature selection algorithms. Finally, we show how stability profiles can support the choice of a feature selection algorithm. Alexandros Kalousis received the B.Sc. degree in computer science, in 1994, and the M.Sc. degree in advanced information systems, in 1997, both from the University of Athens, Greece. He received the Ph.D. degree in meta-learning for classification algorithm selection from the University of Geneva, Department of Computer Science, Geneva, in 2002. Since then he is a Senior Researcher in the same university. His research interests include relational learning with kernels and distances, stability of feature selection algorithms, and feature extraction from spectral data. Julien Prados is a Ph.D. student at the University of Geneva, Switzerland. In 1999 and 2001, he received the B.Sc. and M.Sc. degrees in computer science from the University Joseph Fourier (Grenoble, France). After a year of work in industry, he joined the Geneva Artificial Intelligence Laboratory, where he is working on bioinformatics and datamining tools for mass spectrometry data analysis. Melanie Hilario has a Ph.D. in computer science from the University of Paris VI and currently works at the University of Geneva’s Artificial Intelligence Laboratory. She has initiated and participated in several European research projects on neuro-symbolic integration, meta-learning, and biological text mining. She has served on the program committees of many conferences and workshops in machine learning, data mining, and artificial intelligence. She is currently an Associate Editor of theInternational Journal on Artificial Intelligence Toolsand a member of the Editorial Board of theIntelligent Data Analysis journal.