The heart rate after inhibition of nitric oxide release in the anaesthetized dog

BACKGROUND AND PURPOSE: The North American Symptomatic Carotid Endarterectomy Trail (NASCET) demonstrated the benefit of carotid endarterectomy for symptomatic patients with > or = 70% carotid stenosis. Screening for detection of significant carotid occlusive disease has relied on duplex Doppler imaging. However, traditional duplex categories (50% to 79%, 80% to 99%) are not directly applicable to NASCET. We sought to evaluate duplex criteria for determination of > or = 70% carotid stenosis. METHODS: Duplex scan and arteriograms of 110 patients (210 carotids), performed within 1 month of each other, were reviewed by blinded readers. Arteriographic stenosis was determined by the NASCET method. Duplex measurements of peak systolic and end-diastolic velocity (PSV, EDV) were recorded, and ratios of velocities in the internal and common carotid arteries (ICA, CCA) were calculated. Receiver-operator characteristic (ROC) curves of sensitivity, specificity, positive and negative predictive values (PPV, NPV), and accuracy were determined. RESULTS: Interobserver agreement for measurement of arteriographic stenosis was "almost perfect" (kappa=0.86). The criteria chosen for detection of > or = 70% stenosis were PSVICA>210 cm/s (sensitivity, 94%; specificity, 77%; PPV, 68% NPV, 96% accuracy, 83%) EDVICA>70 cm/s (sensitivity, 92%; specificity, 60%; PPV, 73%; NPV, 86%; accuracy 77%), PSVica/PSVCCA >3.0 (sensitivity, 91%; specificity, 78%; PPV, 70%; NPV, 94%; accuracy, 83%), and EDVICA/EDVCCA>3.3 (sensitivity, 100%; specificity, 65%; PPV, 65% NPV, 100%; accuracy, 79%). CONCLUSIONS: We conclude that > or = 70% carotid stenosis can be reliably determined by duplex Doppler ultrasound. Individual vascular laboratories must validate their own results.     

Disciplined: Using Educational Studies to Analyse 'Humanities Computing'

Humanities Computing is an emergent field. The activities describedas ‘Humanities Computing’ continue to expand innumber and sophistication, yet no concrete definition of thefield exists, and there are few academic departments that specializein this area. Most introspection regarding the role, meaning,and focus of "Humanities Computing" has come from a practicaland pragmatic perspective from scholars and educators withinthe field itself. This article provides an alternative, externalized,viewpoint of the focus of Humanities Computing, by analysingthe discipline through its community, research, curriculum,teaching programmes, and the message they deliver, either consciouslyor unconsciously, about the scope of the discipline. It engageswith Educational Theory to provide a means to analyse, measure,and define the field, and focuses specifically on the ACH/ALLC2005 Conference to identify and analyse those who are involvedwith the humanities computing community.     

Clustering of domains of functionally related enzymes in the interaction database PRECISE by the generation of primary sequence patterns

The PRECISE database was developed by our laboratory to allow for the systematic study of the ligand interactions common to a set of functionally related enzymes, where an interaction site is defined broadly as any residue(s) that interact with a ligand. During the construction of PRECISE, enzyme chains are extracted from the protein data bank (PDB) and clustered according to functional homology as defined by the enzyme commission (EC) nomenclature system. A sequence representative is chosen from each cluster based on the criterion set forth by the non-redundant PDB set, and pair-wise alignments of each cluster member to the representative are performed. Atom-based residue–ligand interactions are calculated for each cluster member, and the summation of ligand interactions for all cluster members at each aligned position is determined. Although we were able to successfully align most clusters using a simple dynamic programming algorithm, several cluster created exhibited poor pair-wise alignments of each cluster member to its sequence representative. We hypothesized that the observed alignment problems were, in most cases, due to the incorrect separation and alignment of different domains in multi-domain proteins, a mistake that frequently causes error proliferation in functional annotation. Here we present the results of generating primary sequence patterns for each poorly aligned cluster in PRECISE to assess the extent to which multi-domain proteins that are incorrectly aligned contributes to poor pair-wise alignments of each cluster member to its representative. This requires the use of an iterative locally optimal pair-wise alignment algorithm to build a hierarchical similarity-based sequence pattern for a set of functionally related enzymes. Our results show that poor alignments in PRECISE are caused most frequently by the misalignment of multi-domain proteins, and that the generation of primary sequence patterns for the assignment of sequence family membership yields better alignments for the functionally related enzyme clusters in PRECISE than our original alignment algorithm.     

From the User Interface to the Consumer Interface

Business success requires that advances in technology be designed and applied within a human context. Too often technological advance has occurred without reference to human behavior. While research appreciates that electronic consumers are computer users, and vice-versa, few understand exactly how this is transforming consumer behavior. In other words, technological imagination has surpassed our knowledge of media-based consumer behavior. This paper seeks to re-dress the balance of understanding. By (i) integrating themes in human-computer interaction (HCI) with consumer behavior models and (ii) placing the results within a framework of relevant research issues, we present the conceptual foundations for a consumer interface.     

Finite-sample investigation of likelihood and Bayes inference for the symmetric von Mises-Fisher distribution

We consider likelihood and Bayes analyses for the symmetric matrix von Mises-Fisher (matrix Fisher) distribution, which is a common model for three-dimensional orientations (represented by 3×3 orthogonal matrices with a positive determinant). One important characteristic of this model is a 3×3 rotation matrix representing the modal rotation, and an important challenge is to establish accurate confidence regions for it with an interpretable geometry for practical implementation. While we provide some extensions of one-sample likelihood theory (e.g., Euler angle parametrizations of modal rotation), our main contribution is the development of MCMC-based Bayes inference through non-informative priors. In one-sample problems, the Bayes methods allow the construction of inference regions with transparent geometry and accurate frequentist coverages in a way that standard likelihood inference cannot. Simulation is used to evaluate the performance of Bayes and likelihood inference regions. Furthermore, we illustrate how the Bayes framework extends inference from one-sample problems to more complicated one-way random effects models based on the symmetric matrix Fisher model in a computationally straightforward manner. The inference methods are then applied to a human kinematics example for illustration.     

Application of NOAA-AVHRR NDVI time-series data to assess changes in Saudi Arabia's rangelands

The primary objective of this study was to assess the condition of a portion of Saudi Arabia's rangelands and evaluate the effects of grazing by the animal herds of indigenous nomads over the last decade. Because of the desertic condition of these rangelands, changes in vegetation cover are more subtle than would be the case for other, less arid areas. Consequently, a new analytic methodology for the detection of desertification of arid and hyper-arid rangelands was developed specifically for this project. The conceptual framework for the analysis is the use of the coefficient of variation (COV) of the monthly Normalized Difference Vegetation Index (NDVI, maximum-value composite) as a measure of vegetative biomass change. A higher NDVI COV for a given pixel (excluding cases of changes in land use) represents a greater change in vegetation biomass in the ground area represented by that pixel. Linear regression was used to determine the trend in COV values for each pixel over the 12-year period for which data was available; pixels with a negative slope are considered to represent ground areas with decreasing amounts of vegetation. Results were validated by tests of statistical significance and by comparison of the theoretical results to vegetation change and land-cover data from the remote sensing systems and from reconnaissance flights over select areas. These desertification trend results were then combined with land-cover information to provide an assessment of desertification status.     

Macroscale factors affecting diatom abundance: a synergistic use of Continuous Plankton Recorder and satellite remote sensing data

Diatoms exist in almost every aquatic regime; they are responsible for ～20% of global carbon fixation and ～25% of global primary production, and are regarded as a key food for copepods, which are subsequently consumed by larger predators such as fish and marine mammals. A decreasing abundance and a vulnerability to climatic change in the North Atlantic Ocean have been reported in the literature. In the present work, a data matrix composed of concurrent satellite remote sensing and Continuous Plankton Recorder (CPR) in situ measurements was collated for the same spatial and temporal coverage in the Northeast Atlantic. Artificial neural networks (ANNs) were applied to recognize and learn the complex non-monotonic and non-linear relationships between diatom abundance and spatiotemporal environmental factors. Because of their ability to mimic non-linear systems, ANNs proved far more effective in modelling the diatom distribution in the marine ecosystem. The results of this study reveal that diatoms have a regular seasonal cycle, with their abundance most strongly influenced by sea surface temperature (SST) and light intensity. The models indicate that extreme positive SSTs decrease diatom abundances regardless of other climatic conditions. These results provide information on the ecology of diatoms that may advance our understanding of the potential response of diatoms to climatic change.     

A reliability and usability study of TRACEr-RAV: the technique for the retrospective analysis of cognitive errors--for rail, Australian version

The aim of this study was to compare the usability and reliability of two human error identification tools: TRACEr-Rail (developed by the Rail Safety and Standards Board in the UK) and TRACEr-RAV (an Australian specific version of the tool). Following an attempt to modify TRACEr-Rail to more appropriately suit the Australian rail context, it was predicted that TRACEr-RAV would be rated as more usable and be applied more consistently by Australian users than TRACEr-Rail. In Experiment 1, twenty-five rail employees used either TRACEr-Rail or TRACEr-RAV1 to extract and classify errors from six Australian rail incident reports. In Experiment 2, eleven university students used both TRACEr-Rail and TRACEr-RAV2 to extract and classify errors from three incident summaries. The results revealed that although modification of TRACEr-Rail to become TRACEr-RAV1 and TRACEr-RAV2 did not result in improved inter-rater reliability, modification resulted in improved ratings of usability in Experiment 2. Most participants in Experiment 2 preferred TRACEr-RAV2 to TRACEr-Rail. The poor inter-rater reliability observed was most likely the result of inadequate training, limited practice in using the tools, and insufficient human factors knowledge.