CrossRoads, Spring/Summer 2005; quarterly publication of the Governor's Traffic Safety Bureau, Iowa Department of Public Safety

Quarterly publication of the Governor's Traffic Safety Bureau, Iowa Department of Public Safety containing traffic safety and related information and news articles

CrossRoads, Autumn 2006; quarterly publication of the Governor's Traffic Safety Bureau, Iowa Department of Public Safety

Quarterly publication of the Governor's Traffic Safety Bureau, Iowa Department of Public Safety containing traffic safety and related information and news articles

On the efficiency and sensitivity of a pyramidal classification algorithm

In this paper we propose a Pyramidal Classification Algorithm,which together with an appropriate aggregation index producesan indexed pseudo-hierarchy (in the strict sense) withoutinversions nor crossings. The computer implementation of thealgorithm makes it possible to carry out some simulation testsby Monte Carlo methods in order to study the efficiency andsensitivity of the pyramidal methods of the Maximum, Minimumand UPGMA. The results shown in this paper may help to choosebetween the three classification methods proposed, in order toobtain the classification that best fits the original structureof the population, provided we have an a priori informationconcerning this structure.

Assessing an intuitive condition for stability under a range of traffic conditions via a generalised Lu-Kumar network

We argue the importance both of developing simple sufficientconditions for the stability of general multiclass queueing networks and also of assessing such conditions under a range of assumptions on the weight of the traffic flowing between service stations. To achieve the former, we review a peak-rate stability condition and extend its range of application and for the latter, we introduce a generalisation of the Lu-Kumar network on which the stability condition may be tested for a range of traffic configurations. The peak-rate condition is close to exact when the between-station traffic is light, but degrades as this traffic increases.

Classification of cell death: recommendations of the Nomenclature Committee on Cell Death 2009

Different types of cell death are often defined by morphological criteria, without a clear reference to precise biochemical mechanisms. The Nomenclature Committee on Cell Death (NCCD) proposes unified criteria for the definition of cell death and of its different morphologies, while formulating several caveats against the misuse of words and concepts that slow down progress in the area of cell death research. Authors, reviewers and editors of scientific periodicals are invited to abandon expressions like 'percentage apoptosis' and to replace them with more accurate descriptions of the biochemical and cellular parameters that are actually measured. Moreover, at the present stage, it should be accepted that caspase-independent mechanisms can cooperate with (or substitute for) caspases in the execution of lethal signaling pathways and that 'autophagic cell death' is a type of cell death occurring together with (but not necessarily by) autophagic vacuolization. This study details the 2009 recommendations of the NCCD on the use of cell death-related terminology including 'entosis', 'mitotic catastrophe', 'necrosis', 'necroptosis' and 'pyroptosis'.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

Saving our science from ourselves: the plight of biological classification

Saving our science from ourselves: the plight of biological classification. Biological classification ( nomenclature, taxonomy, and systematics) is being sold short. The desire for new technologies, faster and cheaper taxonomic descriptions, identifications, and revisions is symptomatic of a lack of appreciation and understanding of classification. The problem of gadget-driven science, a lack of best practice and the inability to accept classification as a descriptive and empirical science are discussed. The worst cases scenario is a future in which classifications are purely artificial and uninformative.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.

An Examination of Iowa State Patrol Traffic Stops, October 2000 - March 2002

this report describes traffic law enforcement data collected by the Iowa State Patrol (ISP) related to traffic stops made by Troopers for October 1, 2000 through March 30, 2002. The data contained in this report summarizes the activities of approximately 435 troopers who are assigned to 15 posts throughout the State of Iowa The purpose of this voluntary data collection process was to provide the ISP with the ability to review traffic law enforcement variables in relation to traffic stops. The methodology for this research project was developed and implemented by ISP. Following the data collection period, the Iowa Division of Criminal and Juvenile Justice Planning (CJJP) was asked to assist in the analysis and reporting phase of this ambitious project.

Extensive gene traffic on the mammalian X chromosome.

Mammalian sex chromosomes have undergone profound changes since evolving from ancestral autosomes. By examining retroposed genes in the human and mouse genomes, we demonstrate that, during evolution, the mammalian X chromosome has generated and recruited a disproportionately high number of functional retroposed genes, whereas the autosomes experienced lower gene turnover. Most autosomal copies originating from X-linked genes exhibited testis-biased expression. Such export is incompatible with mutational bias and is likely driven by natural selection to attain male germline function. However, the excess recruitment is consistent with a combination of both natural selection and mutational bias.

Natural classification of knots

The principal objective of the knot theory is to provide a simple way of classifying and ordering all the knot types. Here, we propose a natural classification of knots based on their intrinsic position in the knot space that is defined by the set of knots to which a given knot can be converted by individual intersegmental passages. In addition, we characterize various knots using a set of simple quantum numbers that can be determined upon inspection of minimal crossing diagram of a knot. These numbers include: crossing number; average three-dimensional writhe; number of topological domains; and the average relaxation value

Les diatomées : histoire naturelle, préparation, classification & description des principales espèces. avec une Introduction à l'étude des diatomées. et un Exposé de la classification des diatomées. 2, 2 / par Le Dr J. Pelletan ; par M. J. Deby ; par M. Paul Petit

Comprend : Introduction à l'étude des diatomées ; Exposé de la classification des diatomées

Les diatomées : histoire naturelle, préparation, classification & description des principales espèces. avec une Introduction à l'étude des diatomées. et un Exposé de la classification des diatomées. 1 / par Le Dr J. Pelletan ; par M. J. Deby ; par M. Paul Petit

Comprend : Introduction à l'étude des diatomées ; Exposé de la classification des diatomées