Too sleepy to drive : self-perception and regulation of driving when sleepy

Background: Sleepiness is a direct contributor to a substantial proportion of fatal and severe road cashes. A number of technological solutions designed to detect sleepiness have been developed, but self-awareness of increasing sleepiness remains a critical component in on-road strategies for mitigating this risk. In order to take appropriate action when sleepy, drivers’ perceptions of their level of sleepiness must be accurate. Aims: This study aimed to assess capacity to accurately identify sleepiness and self-regulate driving cessation during a validated driving simulator task. Participants: Participants comprised 26 young adult drivers (20-28 years). The drivers had open licenses but no other exclusion criteria where used. Methods: Participants woke at 5am, and took part in a laboratory-based hazard perception driving simulation, either at mid-morning or mid-afternoon. Established physiological measures (including EEG) and subjective measures (sleepiness ratings) previously found sensitive to changes in sleepiness levels were utilised. Participants were instructed to ‘drive’ until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 39 minutes (±18 minutes). Almost all (23/26) of the participants then achieved sleep during the nap opportunity. These data suggest that the participants’ perceptions of sleepiness were specific. However, EEG data from a number of participants suggested very high levels of sleepiness prior to driving cessation, suggesting poor sensitivity. Conclusions: Participants reported high levels of sleepiness while driving after very moderate sleep restriction. They were able to identify increasing sleepiness during the test period, could decide to cease driving and in most cases were sufficiently sleepy to achieve sleep during the daytime session. However, the levels of sleepiness achieved prior to driving cessation suggest poor accuracy in self-perception and regulation. This presents practical issues for the implementation of fatigue and sleep-related strategies to improve driver safety.

Understanding hydrochemical processes using 3D models and hydrochemical facies in Wairau Plain groundwater, Marlborough

Three dimensional models and groundwater quality are combined to better understand and conceptualise groundwater systems in complex geological settings in the Wairau Plain, Marlborough. Hydrochemical facies, which are characteristic of distinct evolutionary pathways and a common hydrologic history of groundwaters, are identified within geological formations to assess natural water-rock interactions, redox potential and human agricultural impact on groundwater quality in the Wairau Plain.

Assessing the representativeness of a groundwater quality monitoring network

The monitoring sites comprising a state of the environment (SOE) network must be carefully selected to ensure that they will be representative of the broader resource. Hierarchical cluster analysis (HCA) is a data-driven technique that can potentially be employed to assess the representativeness of a SOE monitoring network. The objective of this paper is to explore the use of HCA as an approach for assessing the representativeness of the New Zealand National Groundwater Monitoring Programme (NGMP), which is comprised of 110 monitoring sites across the country.

Forecasting volatility and correlation : the role of option implied measures

Forecasts of volatility and correlation are important inputs into many practical financial problems. Broadly speaking, there are two ways of generating forecasts of these variables. Firstly, time-series models apply a statistical weighting scheme to historical measurements of the variable of interest. The alternative methodology extracts forecasts from the market traded value of option contracts. An efficient options market should be able to produce superior forecasts as it utilises a larger information set of not only historical information but also the market equilibrium expectation of options market participants. While much research has been conducted into the relative merits of these approaches, this thesis extends the literature along several lines through three empirical studies. Firstly, it is demonstrated that there exist statistically significant benefits to taking the volatility risk premium into account for the implied volatility for the purposes of univariate volatility forecasting. Secondly, high-frequency option implied measures are shown to lead to superior forecasts of the intraday stochastic component of intraday volatility and that these then lead on to superior forecasts of intraday total volatility. Finally, the use of realised and option implied measures of equicorrelation are shown to dominate measures based on daily returns.

A DRD2 and ANKK1 haplotype is associated with nicotine dependence

To test the importance of the dopamine D2 receptor (DRD2) region in nicotine dependence, 150 smokers and 228 controls were genotyped for the DRD2 C957T, -141delC and ANKK1 TaqIA polymorphisms (rs6277, rs1799732 and rs1800497, respectively). The -141delC SNP did not show any association but both the C957T and TaqIA SNPs showed association at the allele, genotype, haplotype and combined genotype levels. The 957C/TaqI A1 haplotype was more than 3.5 times as likely to be associated with nicotine dependence compared with the 957T/TaqI A1 haplotype (P = 0.003). Analysis of the combined genotypes of both SNPs revealed that individuals who were homozygous for the 957C-allele (CC) and had either one or two copies of the TaqI A1-allele were 3.3 times as likely to have nicotine dependence compared to all other genotype combinations (P = 0.0003) and that these genotypes accounted for approximately 13% of the susceptibility to nicotine addiction in our population. Our findings suggest that the DRD2 C957T polymorphism and the ANKK1 TaqIA polymorphism are key contributors to the genetic susceptibility to nicotine dependence.

A CAD interface for GEANT4

Often CAD models already exist for parts of a geometry being simulated using GEANT4. Direct import of these CAD models into GEANT4 however,may not be possible and complex components may be diffcult to define via other means. Solutions that allow for users to work around the limited support in the GEANT4 toolkit for loading predefined CAD geometries have been presented by others, however these solutions require intermediate file format conversion using commercial software. Here within we describe a technique that allows for CAD models to be directly loaded as geometry without the need for commercial software and intermediate file format conversion. Robustness of the interface was tested using a set of CAD models of various complexity; for the models used in testing, no import errors were reported and all geometry was found to be navigable by GEANT4. Funding source: Cancer Australia (Department of Health and Ageing) Research Grant 614217

Document clustering evaluation : Divergence from a random baseline

Divergence from a random baseline is a technique for the evaluation of document clustering. It ensures cluster quality measures are performing work that prevents ineffective clusterings from giving high scores to clusterings that provide no useful result. These concepts are defined and analysed using intrinsic and extrinsic approaches to the evaluation of document cluster quality. This includes the classical clusters to categories approach and a novel approach that uses ad hoc information retrieval. The divergence from a random baseline approach is able to differentiate ineffective clusterings encountered in the INEX XML Mining track. It also appears to perform a normalisation similar to the Normalised Mutual Information (NMI) measure but it can be applied to any measure of cluster quality. When it is applied to the intrinsic measure of distortion as measured by RMSE, subtraction from a random baseline provides a clear optimum that is not apparent otherwise. This approach can be applied to any clustering evaluation. This paper describes its use in the context of document clustering evaluation.

Effect of caffeine on adenosine-induced reversible perfusion defects assessed by automated analysis

Objectives This prospective study investigated the effects of caffeine ingestion on the extent of adenosine-induced perfusion abnormalities during myocardial perfusion imaging (MPI). Methods Thirty patients with inducible perfusion abnormalities on standard (caffeine-abstinent) adenosine MPI underwent repeat testing with supplementary coffee intake. Baseline and test MPIs were assessed for stress percent defect, rest percent defect, and percent defect reversibility. Plasma levels of caffeine and metabolites were assessed on both occasions and correlated with MPI findings. Results Despite significant increases in caffeine [mean difference 3,106 μg/L (95% CI 2,460 to 3,752 μg/L; P < .001)] and metabolite concentrations over a wide range, there was no statistically significant change in stress percent defect and percent defect reversibility between the baseline and test scans. The increase in caffeine concentration between the baseline and the test phases did not affect percent defect reversibility (average change −0.003 for every 100 μg/L increase; 95% CI −0.17 to 0.16; P = .97). Conclusion There was no significant relationship between the extent of adenosine-induced coronary flow heterogeneity and the serum concentration of caffeine or its principal metabolites. Hence, the stringent requirements for prolonged abstinence from caffeine before adenosine MPI—based on limited studies—appear ill-founded.

Age of blood and recipient factors determine the severity of transfusion-related acute lung injury (TRALI)

Introduction Critical care patients frequently receive blood transfusions. Some reports show an association between aged or stored blood and increased morbidity and mortality, including the development of transfusion-related acute lung injury (TRALI). However, the existence of conflicting data endorses the need for research to either reject this association, or to confirm it and elucidate the underlying mechanisms. Methods Twenty-eight sheep were randomised into two groups, receiving saline or lipopolysaccharide (LPS). Sheep were further randomised to also receive transfusion of pooled and heat-inactivated supernatant from fresh (Day 1) or stored (Day 42) non-leucoreduced human packed red blood cells (PRBC) or an infusion of saline. TRALI was defined by hypoxaemia during or within two hours of transfusion and histological evidence of pulmonary oedema. Regression modelling compared physiology between groups, and to a previous study, using stored platelet concentrates (PLT). Samples of the transfused blood products also underwent cytokine array and biochemical analyses, and their neutrophil priming ability was measured in vitro. Results TRALI did not develop in sheep that first received saline-infusion. In contrast, 80% of sheep that first received LPS-infusion developed TRALI following transfusion with "stored PRBC." The decreased mean arterial pressure and cardiac output as well as increased central venous pressure and body temperature were more severe for TRALI induced by "stored PRBC" than by "stored PLT." Storage-related accumulation of several factors was demonstrated in both "stored PRBC" and "stored PLT", and was associated with increased in vitro neutrophil priming. Concentrations of several factors were higher in the "stored PRBC" than in the "stored PLT," however, there was no difference to neutrophil priming in vitro. Conclusions In this in vivo ovine model, both recipient and blood product factors contributed to the development of TRALI. Sick (LPS infused) sheep rather than healthy (saline infused) sheep predominantly developed TRALI when transfused with supernatant from stored but not fresh PRBC. "Stored PRBC" induced a more severe injury than "stored PLT" and had a different storage lesion profile, suggesting that these outcomes may be associated with storage lesion factors unique to each blood product type. Therefore, the transfusion of fresh rather than stored PRBC may minimise the risk of TRALI.

Cyclic Imide and Open-Chain Amide Carboxylic Acid Derivatives from the Facile Reaction of cis-Cyclohexane-1,2-dicarboxylic Anhydride with Three Substituted Anilines

The structures of the compounds from the reaction of cis-cyclohexane-1,2-dicarboxylic anhydride with 4-chloroaniline [rac-N-(4-chlorophenyl)-2-carboxycycloclohexane-1-carboxamide] (1), 4-bromoaniline [2-(4-bromophenyl)-perhydroisoindolyl-1,3-dione] (2) and 3-hydroxy-4-carboxyaniline (5-aminosalicylic acid) [2-(3-hydroxy-4-carboxyphenyl)-perhydroisoindolyl-1,3-dione] (3) have been determined at 200 K. Crystals of the open-chain amide carboxylic acid 1 are orthorhombic, space group Pbcn, with unit cell dimensions a = 20.1753(10), b = 8.6267(4), c = 15.9940(9) Å, and Z = 8. Compounds 2 and 3 are cyclic imides, with 1 monoclinic having space group P21 and cell dimensions a = 11.5321(3), b = 6.7095(2), c = 17.2040(5) Å, β = 102.527(3)o. Compound 3 is orthorhombic with cell dimensions a = 6.4642(3), b = 12.8196(5), c = 16.4197(7) Å. Molecules of 1 form hydrogen-bonded cyclic dimers which are extended into a two-dimensional layered structure through amide-group associations: 3 forms into one-dimensional zigzag chains through carboxylic acid…imide O-atom hydrogen bonds, while compound 2 is essentially unassociated. With both cyclic imides 2 and 3, disorder is found which involves the presence of partial enantiomeric replacement of the cis-cyclohexane-1,2-substituted ring systems.

A sequential Monte Carlo approach to the sequential design for discriminating between rival continuous data models

Here we present a sequential Monte Carlo approach to Bayesian sequential design for the incorporation of model uncertainty. The methodology is demonstrated through the development and implementation of two model discrimination utilities; mutual information and total separation, but it can also be applied more generally if one has different experimental aims. A sequential Monte Carlo algorithm is run for each rival model (in parallel), and provides a convenient estimate of the marginal likelihood (of each model) given the data, which can be used for model comparison and in the evaluation of utility functions. A major benefit of this approach is that it requires very little problem specific tuning and is also computationally efficient when compared to full Markov chain Monte Carlo approaches. This research is motivated by applications in drug development and chemical engineering.

Bayesian experimental design for models with intractable likelihoods

In this paper we present a methodology for designing experiments for efficiently estimating the parameters of models with computationally intractable likelihoods. The approach combines a commonly used methodology for robust experimental design, based on Markov chain Monte Carlo sampling, with approximate Bayesian computation (ABC) to ensure that no likelihood evaluations are required. The utility function considered for precise parameter estimation is based upon the precision of the ABC posterior distribution, which we form efficiently via the ABC rejection algorithm based on pre-computed model simulations. Our focus is on stochastic models and, in particular, we investigate the methodology for Markov process models of epidemics and macroparasite population evolution. The macroparasite example involves a multivariate process and we assess the loss of information from not observing all variables.

Clines in cuticular hydrocarbons in two Drosophila species with independent population histories

We took a comparative approach utilizing clines to investigate the extent to which natural selection may have shaped population divergence in cuticular hydrocarbons (CHCs) that are also under sexual selection in Drosophila. We detected the presence of CHC clines along a latitudinal gradient on the east coast of Australia in two fly species with independent phylogenetic and population histories, suggesting adaptation to shared abiotic factors. For both species, significant associations were detected between clinal variation in CHCs and temperature variation along the gradient, suggesting temperature maxima as a candidate abiotic factor shaping CHC variation among populations. However, rainfall and humidity correlated with CHC variation to differing extents in the two species, suggesting that response to these abiotic factors may vary in a species-specific manner. Our results suggest that natural selection, in addition to sexual selection, plays a significant role in structuring among-population variation in sexually selected traits in Drosophila.

Driver sleepiness self-regulation : physiological and subjective evidence

Introduction: Sleepiness contributes to a substantial proportion of fatal and severe road crashes. Efforts to reduce the incidence of sleep-related crashes have largely focussed on driver education to promote self-regulation of driving behaviour. However, effective self-regulation requires accurate self-perception of sleepiness. The aim of this study was to assess capacity to accurately identify sleepiness, and self-regulate driving cessation, during a validated driving simulator task. Methods: Participants comprised 26 young adult drivers (20-28 years) who had open licenses. No other exclusion criteria where used. Participants were partially sleep deprived (05:00 wake up) and completed a laboratory-based hazard perception driving simulation, counterbalanced to either at mid-morning or mid-afternoon. Established physiological measures (i.e., EEG, EOG) and subjective measures (Karolinska Sleepiness Scale), previously found sensitive to changes in sleepiness levels, were utilised. Participants were instructed to ‘drive’ on the simulator until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 36.1 minutes (±17.7 minutes). Subjective sleepiness increased significantly from the beginning (KSS=6.6±0.7) to the end (KSS=8.2±0.5) of the driving period. No significant differences were found for EEG spectral power measures of sleepiness (i.e., theta or alpha spectral power) from the start of the driving task to the point of cessation of driving. During the nap opportunity, 88% of the participants (23/26) were able to reach sleep onset with an average latency of 9.9 minutes (±7.5 minutes). The average nap duration was 15.1 minutes (±8.1 minutes). Sleep architecture during the nap was predominately comprised of Stages I and II (combined 92%). Discussion: Participants reported high levels of sleepiness during daytime driving after very moderate sleep restriction. They were able to report increasing sleepiness during the test period despite no observed change in standard physiological indices of sleepiness. This increased subjective sleepiness had behavioural validity as the participants had high ‘napability’ at the point of driving cessation, with most achieving some degree of subsequent sleep. This study suggests that the nature of a safety instruction (i.e. how to view sleepiness) can be a determinant of driver behaviour.