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.

Regulation of proteasome structure and function

Proteasomes are cylindrical particles made up of a stack of four heptameric rings. In animal cells the outer rings are made up of 7 different types of alpha subunits and the inner rings are composed of 7 out of 10 possible different beta subunits. Regulatory complexes can bind to the ends of the cylinder.We have investigated aspects of the assembly, activity and subunit composition of core proteasome particles and 26S proteasomes, the localization of proteasome subpopulations, and the possible role of phosphorylation in determining proteasome localization, activities and association with regulatory components.

The acquisition of an artificial logographic script and bilingual working memory : Evidence for L1-specific orthographic processing skills transfer in Chinese-English bilinguals

Studies of orthographic skills transfer between languages focus mostly on working memory (WM) ability in alphabetic first language (L1) speakers when learning another, often alphabetically congruent, language. We report two studies that, instead, explored the transferability of L1 orthographic processing skills in WM in logographic-L1 and alphabetic-L1 speakers. English-French bilingual and English monolingual (alphabetic-L1) speakers, and Chinese-English (logographic-L1) speakers, learned a set of artificial logographs and associated meanings (Study 1). The logographs were used in WM tasks with and without concurrent articulatory or visuo-spatial suppression. The logographic-L1 bilinguals were markedly less affected by articulatory suppression than alphabetic-L1 monolinguals (who did not differ from their bilingual peers). Bilinguals overall were less affected by spatial interference, reflecting superior phonological processing skills or, conceivably, greater executive control. A comparison of span sizes for meaningful and meaningless logographs (Study 2) replicated these findings. However, the logographic-L1 bilinguals’ spans in L1 were measurably greater than those of their alphabetic-L1 (bilingual and monolingual) peers; a finding unaccounted for by faster articulation rates or differences in general intelligence. The overall pattern of results suggests an advantage (possibly perceptual) for logographic-L1 speakers, over and above the bilingual advantage also seen elsewhere in third language (L3) acquisition.

A tensor encoding model for semantic processing

This paper develops and evaluates an enhanced corpus based approach for semantic processing. Corpus based models that build representations of words directly from text do not require pre-existing linguistic knowledge, and have demonstrated psychologically relevant performance on a number of cognitive tasks. However, they have been criticised in the past for not incorporating sufficient structural information. Using ideas underpinning recent attempts to overcome this weakness, we develop an enhanced tensor encoding model to build representations of word meaning for semantic processing. Our enhanced model demonstrates superior performance when compared to a robust baseline model on a number of semantic processing tasks.

A practical signal processing approach for condition monitoring of low speed machinery using Peak-Hold-Down-Sample algorithm

A simple and effective down-sample algorithm, Peak-Hold-Down-Sample (PHDS) algorithm is developed in this paper to enable a rapid and efficient data transfer in remote condition monitoring applications. The algorithm is particularly useful for high frequency Condition Monitoring (CM) techniques, and for low speed machine applications since the combination of the high sampling frequency and low rotating speed will generally lead to large unwieldy data size. The effectiveness of the algorithm was evaluated and tested on four sets of data in the study. One set of the data was extracted from the condition monitoring signal of a practical industry application. Another set of data was acquired from a low speed machine test rig in the laboratory. The other two sets of data were computer simulated bearing defect signals having either a single or multiple bearing defects. The results disclose that the PHDS algorithm can substantially reduce the size of data while preserving the critical bearing defect information for all the data sets used in this work even when a large down-sample ratio was used (i.e., 500 times down-sampled). In contrast, the down-sample process using existing normal down-sample technique in signal processing eliminates the useful and critical information such as bearing defect frequencies in a signal when the same down-sample ratio was employed. Noise and artificial frequency components were also induced by the normal down-sample technique, thus limits its usefulness for machine condition monitoring applications.

The impact of anxiety on processing efficiency : implications for the attentional control theory

The Attentional Control Theory (ACT) proposes that high-anxious individuals maintain performance effectiveness (accuracy) at the expense of processing efficiency (response time), in particular, the two central executive functions of inhibition and shifting. In contrast, research has generally failed to consider the third executive function which relates to the function of updating. In the current study, seventy-five participants completed the Parametric Go/No-Go and n-back tasks, as well as the State-Trait Anxiety Inventory in order to explore the effects of anxiety on attention. Results indicated that anxiety lead to decay in processing efficiency, but not in performance effectiveness, across all three Central Executive functions (inhibition, set-shifting and updating). Interestingly, participants with high levels of trait anxiety also exhibited impaired performance effectiveness on the n-back task designed to measure the updating function. Findings are discussed in relation to developing a new model of ACT that also includes the role of preattentive processes and dual-task coordination when exploring the effects of anxiety on task performance.

Partial melt processing and electrical properties of Bi-Sr-Ca-Cu-o superconducting thick films on (100) MgO substrates

Superconducting thick films of Bi2Sr2CaCu2Oy (Bi-2212) on single-crystalline (100) MgO substrates have been prepared using a doctor-blade technique and a partial-melt process. It is found that the phase composition and the amount of Ag addition to the paste affect the structure and superconducting properties of the partially melted thick films. The optimum heat treatment schedule for obtaining high Jc has been determined for each paste. The heat treatment ensures attainment of high purity for the crystalline Bi-2212 phase and high orientation of Bi-2212 crystals, in which the c-axis is perpendicular to the substrate. The highest Tc, obtained by resistivity measurement, is 92.2 K. The best value for Jct (transport) of these thick films, measured at 77 K in self-field, is 8 × 10 3 Acm -2.

Inflammation, hepatic enzymes and resistance training in individuals with metabolic risk factors

AIMS: Increases in inflammatory markers, hepatic enzymes and physical inactivity are associated with the development of the metabolic syndrome (MetS). We examined whether inflammatory markers and hepatic enzymes are correlated with traditional risk factors for MetS and studied the effects of resistance training (RT) on these emerging risk factors in individuals with a high number of metabolic risk factors (HiMF, 2.9 +/- 0.8) and those with a low number of metabolic risk factors (LoMF, 0.5 +/- 0.5). METHODS: Twenty-eight men and 27 women aged 50.8 +/- 6.5 years (mean +/- sd) participated in the study. Participants were randomized to four groups, HiMF training (HiMFT), HiMF control (HiMFC), LoMF training (LoMFT) and LoMF control (LoMFC). Before and after 10 weeks of RT [3 days/week, seven exercises, three sets with intensity gradually increased from 40-50% of one repetition maximum (1RM) to 75-85% of 1RM], blood samples were obtained for the measurement of pro-inflammatory cytokines, C-reactive protein (CRP), gamma-glutamyltransferase (GGT) and alanine aminotransferase (ALT). RESULTS: At baseline, HiMF had higher interleukin-6 (33.9%), CRP (57.1%), GGT (45.2%) and ALT (40.6%) levels, compared with LoMF (all P < 0.05). CRP, GGT and ALT correlated with the number of risk factors (r = 0.48, 0.51 and 0.57, respectively, all P < 0.01) and with other anthropometric and clinical measures (r range from 0.26 to 0.60, P < 0.05). RT did not significantly alter inflammatory markers or hepatic enzymes (all P > 0.05). CONCLUSIONS: HiMF was associated with increased inflammatory markers and hepatic enzyme concentrations. RT did not reduce inflammatory markers and hepatic enzymes in individuals with HiMF.

Social signal processing for pain monitoring using a hidden conditional random field

utomatic pain monitoring has the potential to greatly improve patient diagnosis and outcomes by providing a continuous objective measure. One of the most promising methods is to do this via automatically detecting facial expressions. However, current approaches have failed due to their inability to: 1) integrate the rigid and non-rigid head motion into a single feature representation, and 2) incorporate the salient temporal patterns into the classification stage. In this paper, we tackle the first problem by developing a “histogram of facial action units” representation using Active Appearance Model (AAM) face features, and then utilize a Hidden Conditional Random Field (HCRF) to overcome the second issue. We show that both of these methods improve the performance on the task of pain detection in sequence level compared to current state-of-the-art-methods on the UNBC-McMaster Shoulder Pain Archive.

Featureless visual processing for SLAM in changing outdoor environments

Vision-based SLAM is mostly a solved problem providing clear, sharp images can be obtained. However, in outdoor environments a number of factors such as rough terrain, high speeds and hardware limitations can result in these conditions not being met. High speed transit on rough terrain can lead to image blur and under/over exposure, problems that cannot easily be dealt with using low cost hardware. Furthermore, recently there has been a growth in interest in lifelong autonomy for robots, which brings with it the challenge in outdoor environments of dealing with a moving sun and lack of constant artificial lighting. In this paper, we present a lightweight approach to visual localization and visual odometry that addresses the challenges posed by perceptual change and low cost cameras. The approach combines low resolution imagery with the SLAM algorithm, RatSLAM. We test the system using a cheap consumer camera mounted on a small vehicle in a mixed urban and vegetated environment, at times ranging from dawn to dusk and in conditions ranging from sunny weather to rain. We first show that the system is able to provide reliable mapping and recall over the course of the day and incrementally incorporate new visual scenes from different times into an existing map. We then restrict the system to only learning visual scenes at one time of day, and show that the system is still able to localize and map at other times of day. The results demonstrate the viability of the approach in situations where image quality is poor and environmental or hardware factors preclude the use of visual features.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Abstract: Texture enhancement is an important component of image processing, with extensive application in science and engineering. The quality of medical images, quantified using the texture of the images, plays a significant role in the routine diagnosis performed by medical practitioners. Previously, image texture enhancement was performed using classical integral order differential mask operators. Recently, first order fractional differential operators were implemented to enhance images. Experiments conclude that the use of the fractional differential not only maintains the low frequency contour features in the smooth areas of the image, but also nonlinearly enhances edges and textures corresponding to high-frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we applied the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other fractional differential operators, our new algorithms provide higher signal to noise values, which leads to superior image quality.

Digital social signal processing - theorectical underpinning and research agenda

Organizations make increasingly use of social media in order to compete for customer awareness and improve the quality of their goods and services. Multiple techniques of social media analysis are already in use. Nevertheless, theoretical underpinnings and a sound research agenda are still unavailable in this field at the present time. In order to contribute to setting up such an agenda, we introduce digital social signal processing (DSSP) as a new research stream in IS that requires multi-facetted investigations. Our DSSP concept is founded upon a set of four sequential activities: sensing digital social signals that are emitted by individuals on social media; decoding online data of social media in order to reconstruct digital social signals; matching the signals with consumers’ life events; and configuring individualized goods and service offerings tailored to the individual needs of customers. We further contribute to tying loose ends of different research areas together, in order to frame DSSP as a field for further investigation. We conclude with developing a research agenda.

A genetic analysis of serotonergic biosynthetic and metabolic enzymes in migraine using a DNA pooling approach

Migraine is a common debilitating primary headache disorder with significant mental, physical and social health implications. The brain neurotransmitter 5-hydroxytryptamine (5-HT; serotonin) is involved in nociceptive pathways and has been implicated in the pathophysiology of migraine. With few genetic studies investigating biosynthetic and metabolic enzymes governing the rate of 5-HT activity and their relationship to migraine, it was the objective of this study to assess genetic variants within the human tryptophan hydroxylase (TPH), amino acid decarboxylase (AADC) and monoamine oxidase A (MAOA) genes in migraine susceptibility. This objective was undertaken using a high-throughput DNA pooling experimental design, which proved to be a very accurate, sensitive and specific method of estimating allele frequencies for single nucleotide polymorphism, insertion deletion and variable number tandem repeat loci. Application of DNA pooling to a wide array of genetic loci provides greater scope in the assessment of population-based genetic association study designs. Despite the application of this high-throughput genotyping method, negative results from the two-stage DNA pooling design used to screen loci within the TPH, AADC and MAOA genes did not support their role in migraine susceptibility.