Computer Aided Detection and measurement of peripheral artery disease.

Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and a fast 3D morphology operation. The CAM stage aims to accurately measure the artery diameters from the detected vessel centerline, compensating for the partial volume effect using Expectation Maximization (EM) and a Markov Random field (MRF). The system has been evaluated on phantom data and also applied to fifteen (15) CTA datasets, where the detection accuracy of stenosis was 88% and the measurement accuracy was with an 8% error.

A biophysical model of atrial fibrillation ablation: what can a surgeon learn from a computer model?

AIMS: Surgical ablation procedures for treating atrial fibrillation have been shown to be highly successful. However, the ideal ablation pattern still remains to be determined. This article reports on a systematic study of the effectiveness of the performance of different ablation line patterns. METHODS AND RESULTS: This study of ablation line patterns was performed in a biophysical model of human atria by combining basic lines: (i) in the right atrium: isthmus line, line between vena cavae and appendage line and (ii) in the left atrium: several versions of pulmonary vein isolation, connection of pulmonary veins, isthmus line, and appendage line. Success rates and the presence of residual atrial flutter were documented. Basic patterns yielded conversion rates of only 10-25 and 10-55% in the right and the left atria, respectively. The best result for pulmonary vein isolation was obtained when a single closed line encompassed all veins (55%). Combination of lines in the right/left atrium only led to a success rate of 65/80%. Higher rates, up to 90-100%, could be obtained if right and left lines were combined. The inclusion of a left isthmus line was found to be essential for avoiding uncommon left atrial flutter. CONCLUSION: Some patterns studied achieved a high conversion rate, although using a smaller number of lines than those of the Maze III procedure. The biophysical atrial model is shown to be effective in the search for promising alternative ablation strategies.

Iowa public library statistics, 1974.

This is the statistical portion of the annual survey results of the State Library of Iowa for 1974.

Water-oriented outdoor recreation, fish and wildlife : executive summary, 1978.

The information presented in this summary document has been based on the comprehensive,"Task Force Report on Water-Oriented Outdoor Recreation, Fish and Wildlife." The overriding principle the main task force report conveyed is that Iowa should not forsake the remaining water-oriented fish and wildlife resource base in the name of economic development.The reader should refer to the task force document for more detailed information.

Vital Statistics of Iowa, 2013

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Vital Statistics of Iowa, 2014

This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Resilient housing : a new resource-oriented approach

The institutional regimes framework has previously been applied to the institutional conditions that support or hinder the sustainability of housing stocks. This resource-based approach identifies the actors across different sectors that have an interest in housing, how they use housing, the mechanisms affecting their use (public policy, use rights, contracts, etc.) and the effects of their uses on the sustainability of housing within the context of the built environment. The potential of the institutional regimes framework is explored for its suitability to the many considerations of housing resilience. By identifying all the goods and services offered by the resource 'housing stock', researchers and decision-makers could improve the resilience of housing by better accounting for the ecosystem services used by housing, decreasing the vulnerability of housing to disturbances, and maximizing recovery and reorganization following a disturbance. The institutional regimes framework is found to be a promising tool for addressing housing resilience. Further questions are raised for translating this conceptual framework into a practical application underpinned with empirical data.

Kernel-PCA data integration with enhanced interpretability

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge.

GIS-Based Accident Location and Analysis System (GIS-ALAS) Project Report: Phase 1, 1998

This report summarizes progress made in Phase 1 of the GIS-based Accident Location and Analysis System (GIS-ALAS) project. The GIS-ALAS project builds on several longstanding efforts by the Iowa Department of Transportation (DOT), law enforcement agencies, Iowa State University, and several other entities to create a locationally-referenced highway accident database for Iowa. Most notable of these efforts is the Iowa DOT’s development of a PC-based accident location and analysis system (PC-ALAS), a system that has been well received by users since it was introduced in 1989. With its pull-down menu structure, PC-ALAS is more portable and user-friendly than its mainframe predecessor. Users can obtain accident statistics for locations during specified time periods. Searches may be refined to identify accidents of specific types or involving drivers with certain characteristics. Output can be viewed on a computer screen, sent to a file, or printed using pre-defined formats.