Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.

Heterogeneity in vaccination coverage explains the size and occurrence of measles epidemics in German surveillance data

The objective of this study was to characterize empirically the association between vaccination coverage and the size and occurrence of measles epidemics in Germany. In order to achieve this we analysed data routinely collected by the Robert Koch Institute, which comprise the weekly number of reported measles cases at all ages as well as estimates of vaccination coverage at the average age of entry into the school system. Coverage levels within each federal state of Germany are incorporated into a multivariate time-series model for infectious disease counts, which captures occasional outbreaks by means of an autoregressive component. The observed incidence pattern of measles for all ages is best described by using the log proportion of unvaccinated school starters in the autoregressive component of the model.

Chances and risks of publication of quality data - the perspectives of Swiss physicians and nurses

Background The release of quality data from acute care hospitals to the general public is based on the aim to inform the public, to provide transparency and to foster quality-based competition among providers. Due to the expected mechanisms of action and possibly the adverse consequences of public quality comparison, it is a controversial topic. The perspective of physicians and nurses is of particular importance in this context. They are mainly responsible for the collection of quality-control data, and are directly confronted with the results of public comparison. The research focus of this qualitative study was to discover what the views and opinions of the Swiss physicians and nurses were regarding these issues. It was investigated as to how the two professional groups appraised the opportunities as well as the risks of the release of quality data in Switzerland. Methods A qualitative approach was chosen to answer the research question. For data collection, four focus groups were conducted with physicians and nurses who were employed in Swiss acute care hospitals. Qualitative content analysis was applied to the data. Results The results revealed that both occupational groups had a very critical and negative attitude regarding the recent developments. The perceived risks were dominating their view. In summary, their main concerns were: the reduction of complexity, the one-sided focus on measurable quality variables, risk selection, the threat of data manipulation and the abuse of published information by the media. An additional concern was that the impression is given that the complex construct of quality can be reduced to a few key figures, and it that it is constructed from a false message which then influences society and politics. This critical attitude is associated with the different value system and the professional self-concept that both physicians and nurses have, in comparison to the underlying principles of a market-based economy and the economic orientation of health care business. Conclusions The critical and negative attitude of Swiss physicians and nurses must, under all conditions, be heeded to and investigated regarding its impact on work motivation and identification with the profession. At the same time, the two professional groups are obligated to reflect upon their critical attitude and take a proactive role in the development of appropriate quality indicators for the publication of quality data in Switzerland.

Antimicrobial use in Swiss dairy farms: quantification and evaluation of data quality

Data on antimicrobial use play a key role in the development of policies for the containment of antimicrobial resistance. On-farm data could provide a detailed overview of the antimicrobial use, but technical and methodological aspects of data collection and interpretation, as well as data quality need to be further assessed. The aims of this study were (1) to quantify antimicrobial use in the study population using different units of measurement and contrast the results obtained, (2) to evaluate data quality of farm records on antimicrobial use, and (3) to compare data quality of different recording systems. During 1 year, data on antimicrobial use were collected from 97 dairy farms. Antimicrobial consumption was quantified using: (1) the incidence density of antimicrobial treatments; (2) the weight of active substance; (3) the used daily dose and (4) the used course dose for antimicrobials for intestinal, intrauterine and systemic use; and (5) the used unit dose, for antimicrobials for intramammary use. Data quality was evaluated by describing completeness and accuracy of the recorded information, and by comparing farmers' and veterinarians' records. Relative consumption of antimicrobials depended on the unit of measurement: used doses reflected the treatment intensity better than weight of active substance. The use of antimicrobials classified as high priority was low, although under- and overdosing were frequently observed. Electronic recording systems allowed better traceability of the animals treated. Recording drug name or dosage often resulted in incomplete or inaccurate information. Veterinarians tended to record more drugs than farmers. The integration of veterinarian and farm data would improve data quality.

The Design and Analysis of Partner Studies of HIV Transmission

Common goals in epidemiologic studies of infectious diseases include identification of the infectious agent, description of the modes of transmission and characterization of factors that influence the probability of transmission from infected to uninfected individuals. In the case of AIDS, the agent has been identified as the Human Immunodeficiency Virus (HIV), and transmission is known to occur through a variety of contact mechanisms including unprotected sexual intercourse, transfusion of infected blood products and sharing of needles in intravenous drug use. Relatively little is known about the probability of IV transmission associated with the various modes of contact, or the role that other cofactors play in promoting or suppressing transmission. Here, transmission probability refers to the probability that the virus is transmitted to a susceptible individual following exposure consisting of a series of potentially infectious contacts. The infectivity of HIV for a given route of transmission is defined to be the per contact probability of infection. Knowledge of infectivity and its relationship to other factors is important in understanding the dynamics of the AIDS epidemic and in suggesting appropriate measures to control its spread. The primary source of empirical data about infectivity comes from sexual partners of infected individuals. Partner studies consist of a series of such partnerships, usually heterosexual and monogamous, each composed of an initially infected "index case" and a partner who may or may not be infected by the time of data collection. However, because the infection times of both partners may be unknown and the history of contacts uncertain, any quantitative characterization of infectivity is extremely difficult. Thus, most statistical analyses of partner study data involve the simplifying assumption that infectivity is a constant common to all partnerships. The major objectives of this work are to describe and discuss the design and analysis of partner studies, providing a general statistical framework for investigations of infectivity and risk factors for HIV transmission. The development is largely based on three papers: Jewell and Shiboski (1990), Kim and Lagakos (1990), and Shiboski and Jewell (1992).

On Time Series Analysis of Public Health and Biomedical Data

A time series is a sequence of observations made over time. Examples in public health include daily ozone concentrations, weekly admissions to an emergency department or annual expenditures on health care in the United States. Time series models are used to describe the dependence of the response at each time on predictor variables including covariates and possibly previous values in the series. Time series methods are necessary to account for the correlation among repeated responses over time. This paper gives an overview of time series ideas and methods used in public health research.

Cervical soft tissue imaging using a mobile CBCT scanner with a flat panel detector in comparison with corresponding CT and MRI data sets

OBJECTIVE: The aim of this study was to evaluate soft tissue image quality of a mobile cone-beam computed tomography (CBCT) scanner with an integrated flat-panel detector. STUDY DESIGN: Eight fresh human cadavers were used in this study. For evaluation of soft tissue visualization, CBCT data sets and corresponding computed tomography (CT) and magnetic resonance imaging (MRI) data sets were acquired. Evaluation was performed with the help of 10 defined cervical anatomical structures. RESULTS: The statistical analysis of the scoring results of 3 examiners revealed the CBCT images to be of inferior quality regarding the visualization of most of the predefined structures. Visualization without a significant difference was found regarding the demarcation of the vertebral bodies and the pyramidal cartilages, the arteriosclerosis of the carotids (compared with CT), and the laryngeal skeleton (compared with MRI). Regarding arteriosclerosis of the carotids compared with MRI, CBCT proved to be superior. CONCLUSIONS: The integration of a flat-panel detector improves soft tissue visualization using a mobile CBCT scanner.

Integrating structured and unstructured data in a business-intelligence-system

The recent liberalization of the German energy market has forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse giving insight into the time series to understand market and pricing mechanisms, it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the appropriate interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects, and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

BrainMaps.org - Interactive High-Resolution Digital Brain Atlases and Virtual Microscopy

BrainMaps.org is an interactive high-resolution digital brain atlas and virtual microscope that is based on over 20 million megapixels of scanned images of serial sections of both primate and non-primate brains and that is integrated with a high-speed database for querying and retrieving data about brain structure and function over the internet. Complete brain datasets for various species, including Homo sapiens, Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, and Tyto alba, are accessible online. The methods and tools we describe are useful for both research and teaching, and can be replicated by labs seeking to increase accessibility and sharing of neuroanatomical data. These tools offer the possibility of visualizing and exploring completely digitized sections of brains at a sub-neuronal level, and can facilitate large-scale connectional tracing, histochemical and stereological analyses.

Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

Combining follow-up and change data is valid in meta-analyses of continuous outcomes: a meta-epidemiological study

OBJECTIVE To investigate whether it is valid to combine follow-up and change data when conducting meta-analyses of continuous outcomes. STUDY DESIGN AND SETTING Meta-epidemiological study of randomized controlled trials in patients with osteoarthritis of the knee/hip, which assessed patient-reported pain. We calculated standardized mean differences (SMDs) based on follow-up and change data, and pooled within-trial differences in SMDs. We also derived pooled SMDs indicating the largest treatment effect within a trial (optimistic selection of SMDs) and derived pooled SMDs from the estimate indicating the smallest treatment effect within a trial (pessimistic selection of SMDs). RESULTS A total of 21 meta-analyses with 189 trials with 292 randomized comparisons in 41,256 patients were included. On average, SMDs were 0.04 standard deviation units more beneficial when follow-up values were used (difference in SMDs: -0.04; 95% confidence interval: -0.13, 0.06; P=0.44). In 13 meta-analyses (62%), there was a relevant difference in clinical and/or significance level between optimistic and pessimistic pooled SMDs. CONCLUSION On average, there is no relevant difference between follow-up and change data SMDs, and combining these estimates in meta-analysis is generally valid. Decision on which type of data to use when both follow-up and change data are available should be prespecified in the meta-analysis protocol.

Use of audiovisual messages from land user to land user for sharing knowledge about SLM: experiences from a pilot project in Kenya and Tajikistan

The global World Overview of Conservation Approaches and Technologies (WOCAT) initiative has developed standardised tools and methods to compile and evaluate knowledge available about SLM. This knowledge is now combined and enriched with audiovisual information in order to give a voice to land users, reach a broad range of stakeholders, and assist in scaling up SLM to reverse trends of degradation, desertification, and drought. Five video products, adapted to the needs of different target groups, are created and embedded in already existing platforms for knowledge sharing of SLM such as the WOCAT database and Google Earth application. A pilot project was carried out in Kenya and Tajikistan to verify ideas and tools while at the same time assessing the usefulness of the suggested products on the ground. Video has the potential to bridge the gap between different actor groups and enable communication and sharing on different levels and scales: locally, regionally, and globally. Furthermore, it is an innovative tool to link local and scientific knowledge, raise awareness, and support advocacy for SLM. Keywords: Sustainable Land Management (SLM), knowledge sharing, audiovisual messages, video, World Overview of Conservation Approaches and Technologies (WOCAT)

Identifiability of diffusion and sorption parameters from in situ diffusion experiments by using simultaneously tracer dilution and claystone data

In situ diffusion experiments are performed in geological formations at underground research laboratories to overcome the limitations of laboratory diffusion experiments and investigate scale effects. Tracer concentrations are monitored at the injection interval during the experiment (dilution data) and measured from host rock samples around the injection interval at the end of the experiment (overcoring data). Diffusion and sorption parameters are derived from the inverse numerical modeling of the measured tracer data. The identifiability and the uncertainties of tritium and Na-22(+) diffusion and sorption parameters are studied here by synthetic experiments having the same characteristics as the in situ diffusion and retention (DR) experiment performed on Opalinus Clay. Contrary to previous identifiability analyses of in situ diffusion experiments, which used either dilution or overcoring data at approximate locations, our analysis of the parameter identifiability relies simultaneously on dilution and overcoring data, accounts for the actual position of the overcoring samples in the claystone, uses realistic values of the standard deviation of the measurement errors, relies on model identification criteria to select the most appropriate hypothesis about the existence of a borehole disturbed zone and addresses the effect of errors in the location of the sampling profiles. The simultaneous use of dilution and overcoring data provides accurate parameter estimates in the presence of measurement errors, allows the identification of the right hypothesis about the borehole disturbed zone and diminishes other model uncertainties such as those caused by errors in the volume of the circulation system and the effective diffusion coefficient of the filter. The proper interpretation of the experiment requires the right hypothesis about the borehole disturbed zone. A wrong assumption leads to large estimation errors. The use of model identification criteria helps in the selection of the best model. Small errors in the depth of the overcoring samples lead to large parameter estimation errors. Therefore, attention should be paid to minimize the errors in positioning the depth of the samples. The results of the identifiability analysis do not depend on the particular realization of random numbers. (C) 2012 Elsevier B.V. All rights reserved.