Driver Distraction and Reliance: Adaptive Cruise Control in the Context of Sensor Reliability and Algorithm Limits

This study investigated how system failures influenced drivers’reliance on Adaptive Cruise Control (ACC). A medium-fidelity driving simulatorwas used to evaluate the effect of driving condition (traffic, rain) and automation(manual control, ACC) on headway maintenance and brake response. Inconditions of rain, the signal continuity of the ACC sensors was degraded and inconditions of heavy traffic, the braking limits of the ACC system were exceeded.Dependent variables included response time to lead vehicle (LV) braking, numberof collisions, and both time headway (THW) and time-to-collision (TTC) atinstant of the brake response. Throughout the drive, a continuous (forced-paced)secondary task was introduced to determine how an in-vehicle task interactedwith ACC reliance. Results showed that the failure type influenced driver’sreliance on ACC with drivers relying more on ACC in traffic periods than in rainperiods. ACC appeared to offer a safety benefit when drivers were distracted withcomplex mental tasks in periods of heavy traffic

The Effect of Download Time on Consumer Attitude Toward the Retailer in eCommerce

Download time has been recognized as one of the most important technological impediments to electronic commerce (EC). Unfortunately, the exact consequences of this impediment are currently ill-defined. The goal of this study is to extend the work of Rose and Straub (1999) to identify how this technology impacts the success or failure of EC initiatives. Using marketing and systems response time theories, three hypotheses are proposed. First, that download time in a retailer\u27s Web application has a negative impact on consumer attitude toward that Web retailer. Second, that those effects increase in intensity as consumers attribute more of the cause for delay to the Web application. And third, that attitudes formed about a retailer predict consumer patronage intentions. A laboratory experiment is being undertaken to test these hypotheses

Change Blindness, Attention, and Driving Performance

Concern over older driver high traffic fatality rates has resulted in an effort to identify risk factors and to develop methods of assessment. This study examines two attention-related tasks, Useful Field of View (UFOV) and Change Blindness (CB), in relation to vision and cognitive test batteries and driving performance measures collected using a simulator and an instrumented vehicle. Eight older adults with Alzheimer’s disease and nine comparison subjects between 64 and 81 participated. Factor analysis results indicate that UFOV and CB relate to different factors. While UFOV relates to memory, decision-making, attention, and visual spatial ability, CB relates to vision and attention. The type of images used on a CB task influence how the task relates to driving performance measures. Researchers should be thoughtful when selecting images to include in CB tasks to maximize insight into real-world drivin

Differences in Simulated Car Following Behavior of Younger and Older Drivers

Older drivers are at risk for vehicle crashes due to impairments of visual processing and attention, placing these drivers at greater risk in driving tasks that require continuous attention to neighboring traffic, especially lead vehicles (LVs). We investigated car following behavior in 42 younger drivers (ages 18 to 44 years) and 58 older drivers (ages 65 to 86 years) in a driving simulator. The drivers were instructed to maintain two car lengths from a virtual LV. The LV varied its velocity according to a sum of three sine waves, making the velocity changes unpredictable to the drivers. A Fourier analysis was performed using the vehicle trajectory data to derive measures of coherence, gain, and delay as indices of car following behavior. These measures as well as headway distance were compared between the two groups. Older drivers were less able to match changes in the LV velocity indicated by lower coherence (0.76 v. 0.84, p=0.019) and larger gain (2.24 v. 1.74, p=0.031). However, these drivers followed further behind the LV than younger drivers, a potential compensatory strategy that may reduce collision risk for older drivers

pyseer : a comprehensive tool for microbial pangenome-wide association studies

Genome-wide association studies (GWAS) in microbes have different challenges to GWAS in eukaryotes. These have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results.Peer reviewe

Symmetry violations at BABAR

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd.2014 J. Phys.: Conf. Ser. 556 012042 (http://iopscience.iop.org/1742-6596/556/1/012042

Genome-wide identification of lineage and locus specific variation associated with pneumococcal carriage duration.

Streptococcus pneumoniae is a leading cause of invasive disease in infants, especially in low-income settings. Asymptomatic carriage in the nasopharynx is a prerequisite for disease, but variability in its duration is currently only understood at the serotype level. Here we developed a model to calculate the duration of carriage episodes from longitudinal swab data, and combined these results with whole genome sequence data. We estimated that pneumococcal genomic variation accounted for 63% of the phenotype variation, whereas the host traits considered here (age and previous carriage) accounted for less than 5%. We further partitioned this heritability into both lineage and locus effects, and quantified the amount attributable to the largest sources of variation in carriage duration: serotype (17%), drug-resistance (9%) and other significant locus effects (7%). A pan-genome-wide association study identified prophage sequences as being associated with decreased carriage duration independent of serotype, potentially by disruption of the competence mechanism. These findings support theoretical models of pneumococcal competition and antibiotic resistance

SuperDCA for genome-wide epistasis analysis

The potential for genome-wide modelling of epistasis has recently surfaced given the possibility of sequencing densely sampled populations and the emerging families of statistical interaction models. Direct coupling analysis (DCA) has previously been shown to yield valuable predictions for single protein structures, and has recently been extended to genome-wide analysis of bacteria, identifying novel interactions in the co-evolution between resistance, virulence and core genome elements. However, earlier computational DCA methods have not been scalable to enable model fitting simultaneously to 10(4)-10(5) polymorphisms, representing the amount of core genomic variation observed in analyses of many bacterial species. Here, we introduce a novel inference method (SuperDCA) that employs a new scoring principle, efficient parallelization, optimization and filtering on phylogenetic information to achieve scalability for up to 10(5) polymorphisms. Using two large population samples of Streptococcus pneumoniae, we demonstrate the ability of SuperDCA to make additional significant biological findings about this major human pathogen. We also show that our method can uncover signals of selection that are not detectable by genome-wide association analysis, even though our analysis does not require phenotypic measurements. SuperDCA, thus, holds considerable potential in building understanding about numerous organisms at a systems biological level.Peer reviewe

Horizontal gene transfer rate is not the primary determinant of observed antibiotic resistance frequencies in Streptococcus pneumoniae

The extent to which evolution is constrained by the rate at which horizontal gene transfer (HGT) allows DNA to move between genetic lineages is an open question, which we address in the context of antibiotic resistance in Streptococcus pneumoniae. We analyze microbiological, genomic, and epidemiological data from the largest-to-date sequenced pneumococcal carriage study in 955 infants from a refugee camp on the Thailand-Myanmar border. Using a unified framework, we simultaneously test prior hypotheses on rates of HGT and a key evolutionary covariate (duration of carriage) as determinants of resistance frequencies. We conclude that in this setting, there is little evidence of HGT playing a major role in determining resistance frequencies. Instead, observed resistance frequencies are best explained as the outcome of selection acting on a pool of variants, irrespective of the rate at which resistance determinants move between genetic lineages.ISSN:2375-254

Fast hierarchical Bayesian analysis of population structure

We present fastbaps, a fast solution to the genetic clustering problem. Fastbaps rapidly identifies an approximate fit to a Dirichlet process mixture model (DPM) for clustering multilocus genotype data. Our efficient model-based clustering approach is able to cluster datasets 10-100 times larger than the existing model-based methods, which we demonstrate by analyzing an alignment of over 110 000 sequences of HIV-1 pol genes. We also provide a method for rapidly partitioning an existing hierarchy in order to maximize the DPM model marginal likelihood, allowing us to split phylogenetic trees into clades and sub-clades using a population genomic model. Extensive tests on simulated data as well as a diverse set of real bacterial and viral datasets show that fastbaps provides comparable or improved solutions to previous model-based methods, while being significantly faster. The method is made freely available under an open source MIT licence as an easy to use R package at https://github.com/gtonkinhill/fastbaps.Peer reviewe