Towards Centrifugal Compressor Stages Virtual Testing

Flow features inside centrifugal compressor stages are very complicated to simulate with numerical tools due to the highly complex geometry and varying gas conditions all across the machine. For this reason, a big effort is currently being made to increase the fidelity of the numerical models during the design and validation phases. Computational Fluid Dynamics (CFD) plays an increasing role in the assessment of the performance prediction of centrifugal compressor stages. Historically, CFD was considered reliable for performance prediction on a qualitatively level, whereas tests were necessary to predict compressors performance on a quantitatively basis. In fact "standard" CFD with only the flow-path and blades included into the computational domain is known to be weak in capturing efficiency level and operating range accurately due to the under-estimation of losses and the lack of secondary flows modeling. This research project aims to fill the gap in accuracy between "standard" CFD and tests data by including a high fidelity reproduction of the gas domain and the use of advanced numerical models and tools introduced in the author's OEM in-house CFD code. In other words, this thesis describes a methodology by which virtual tests can be conducted on single stages and multistage centrifugal compressors in a similar fashion to a typical rig test that guarantee end users to operate machines with a confidence level not achievable before. Furthermore, the new "high fidelity" approach allowed understanding flow phenomena not fully captured before, increasing aerodynamicists capability and confidence in designing high efficiency and high reliable centrifugal compressor stages.

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.

Combinations of prognostic tools for identification of high-risk normotensive patients with acute symptomatic pulmonary embolism

In haemodynamically stable patients with acute symptomatic pulmonary embolism (PE), studies have not evaluated the usefulness of combining the measurement of cardiac troponin, transthoracic echocardiogram (TTE), and lower extremity complete compression ultrasound (CCUS) testing for predicting the risk of PE-related death.

Transport of Functionally Appropriate Tools by Capuchin Monkeys (Cebus apella)

Capuchin monkeys are notable among New World monkeys for their widespread use of tools. They use both hammer tools and insertion tools in the wild to acquire food that would be unobtainable otherwise. Evidence indicates that capuchins transport stones to anvil sites and use the most functionally efficient stones to crack nuts. We investigated capuchins’ assessment of functionality by testing their ability to select a tool that was appropriate for two different tool-use tasks: A stone for a hammer task and a stick for an insertion task. To select the appropriate tools, the monkeys investigated a baited tool-use apparatus (insertion or hammer), traveled to a location in their enclosure where they could no longer see the apparatus, made a selection between two tools (stick or stone), and then could transport the tool back to the apparatus to obtain a walnut. Four capuchins were first trained to select and use the appropriate tool for each apparatus. After training, they were then tested by allowing them to view a baited apparatus and then travel to a location 8 m distant where they could select a tool while out of view of the apparatus. All four monkeys chose the correct tool significantly more than expected and transported the tools back to the apparatus. Results confirm capuchins’ propensity for transporting tools, demonstrate their capacity to select the functionally appropriate tool for two different tool-use tasks, and indicate that they can retain the memory of the correct choice during a travel time of several seconds.

Screening and testing for endocrine disruption in fish-biomarkers as "signposts," not "traffic lights," in risk assessment

Biomarkers are currently best used as mechanistic "signposts" rather than as "traffic lights" in the environmental risk assessment of endocrine-disrupting chemicals (EDCs). In field studies, biomarkers of exposure [e.g., vitellogenin (VTG) induction in male fish] are powerful tools for tracking single substances and mixtures of concern. Biomarkers also provide linkage between field and laboratory data, thereby playing an important role in directing the need for and design of fish chronic tests for EDCs. It is the adverse effect end points (e.g., altered development, growth, and/or reproduction) from such tests that are most valuable for calculating adverseNOEC (no observed effect concentration) or adverseEC10 (effective concentration for a 10% response) and subsequently deriving predicted no effect concentrations (PNECs). With current uncertainties, biomarkerNOEC or biomarkerEC10 data should not be used in isolation to derive PNECs. In the future, however, there may be scope to increasingly use biomarker data in environmental decision making, if plausible linkages can be made across levels of organization such that adverse outcomes might be envisaged relative to biomarker responses. For biomarkers to fulfil their potential, they should be mechanistically relevant and reproducible (as measured by interlaboratory comparisons of the same protocol). VTG is a good example of such a biomarker in that it provides an insight to the mode of action (estrogenicity) that is vital to fish reproductive health. Interlaboratory reproducibility data for VTG are also encouraging; recent comparisons (using the same immunoassay protocol) have provided coefficients of variation (CVs) of 38-55% (comparable to published CVs of 19-58% for fish survival and growth end points used in regulatory test guidelines). While concern over environmental xenoestrogens has led to the evaluation of reproductive biomarkers in fish, it must be remembered that many substances act via diverse mechanisms of action such that the environmental risk assessment for EDCs is a broad and complex issue. Also, biomarkers such as secondary sexual characteristics, gonadosomatic indices, plasma steroids, and gonadal histology have significant potential for guiding interspecies assessments of EDCs and designing fish chronic tests. To strengthen the utility of EDC biomarkers in fish, we need to establish a historical control database (also considering natural variability) to help differentiate between statistically detectable versus biologically significant responses. In conclusion, as research continues to develop a range of useful EDC biomarkers, environmental decision-making needs to move forward, and it is proposed that the "biomarkers as signposts" approach is a pragmatic way forward in the current risk assessment of EDCs.

STATE-AND-TRANSITION MODELING AND ADAPTIVE MANAGEMENT: TOOLS FOR FUTURE CO-DEVELOPMENT OF MADAGASCAR’S NATURAL RESOURCES AND PEOPLE

Madagascar’s terrestrial and aquatic ecosystems have long supported a unique set of ecological communities, many of whom are endemic to the tropical island. Those same ecosystems have been a source of valuable natural resources to some of the poorest people in the world. Nevertheless, with pride, ingenuity and resourcefulness, the Malagasy people of the southwest coast, being of Vezo identity, subsist with low development fishing techniques aimed at an increasingly threatened host of aquatic seascapes. Mangroves, sea grass bed, and coral reefs of the region are under increased pressure from the general populace for both food provisions and support of economic opportunity. Besides purveyors and extractors, the coastal waters are also subject to a number of natural stressors, including cyclones and invasive, predator species of both flora and fauna. In addition, the aquatic ecosystems of the region are undergoing increased nutrient and sediment runoff due, in part, to Madagascar’s heavy reliance on land for agricultural purposes (Scales, 2011). Moreover, its coastal waters, like so many throughout the world, have been proven to be warming at an alarming rate over the past few decades. In recognizing the intimate interconnectedness of the both the social and ecological systems, conservation organizations have invoked a host of complimentary conservation and social development efforts with the dual aim of preserving or restoring the health of both the coastal ecosystems and the people of the region. This paper provides a way of thinking more holistically about the social-ecological system within a resiliency frame of understanding. Secondly, it applies a platform known as state-and-transition modeling to give form to the process. State-and-transition modeling is an iterative investigation into the physical makeup of a system of study as well as the boundaries and influences on that state, and has been used in restorative ecology for more than a decade. Lastly, that model is sited within an adaptive management scheme that provides a structured, cyclical, objective-oriented process for testing stakeholders cognitive understanding of the ecosystem through a pragmatic implementation and monitoring a host of small-scale interventions developed as part of the adaptive management process. Throughout, evidence of the application of the theories and frameworks are offered, with every effort made to retool conservation-minded development practitioners with a comprehensive strategy for addressing the increasingly fragile social-ecological systems of southwest Madagascar. It is offered, in conclusion, that the seascapes of the region would be an excellent case study worthy of future application of state-and-transition modeling and adaptive management as frameworks for conservation-minded development practitioners whose multiple projects, each with its own objective, have been implemented with a single goal in mind: preserve and protect the state of the supporting environment while providing for the basic needs of the local Malagasy people.

Novel screening tools for latent tuberculosis: time to leave an old friend?

PURPOSE OF REVIEW: Therapeutic inhibition of tumour necrosis factor-alpha strongly increases the risk of reactivation in latent tuberculosis infection. Recent blood tests based on antigen-specific T cell response and measuring production of interferon-gamma, so called interferon-gamma release assays (IGRAs), are promising novel tools to identify infected patients. The performance of diagnostic testing for latent tuberculosis infection in patients with rheumatic diseases will be discussed. RECENT FINDINGS: In patients with rheumatoid arthritis, IGRAs are more sensitive and more specific than traditional tuberculin skin testing. They are unaffected by Bacillus-Calmette-Guérin vaccination and most nontuberculous mycobacteria. Most comparative studies show a better performance of the IGRAs than tuberculin skin testing in terms of a higher specificity. The rate of indeterminate results may be affected by glucocorticoids and the underlying disease but appears independent of disease-modifying antirheumatic drugs. Despite using identical Mycobacterium tuberculosis antigens, the two commercially available tests show differences in clinical performance. SUMMARY: The current information about the performance of the tuberculin skin testing and the IGRAs in the detection of latent tuberculosis infection in patients with rheumatic diseases strongly suggest a clinically relevant advantage of the IGRAs. Their use will help to reduce overuse and underuse of preventive treatment in tumour necrosis factor inhibition.

NEW TOOLS FOR MONITORING GAMMA CAMERA UNIFORMITY

Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.

DNA testing in neurologic diseases

DNA testing is available for a growing number of hereditary diseases in neurology and other specialties. In addition to guiding breeding decisions, DNA tests are important tools in the diagnosis of diseases, particularly in conditions for which clinical signs are relatively nonspecific. DNA testing also can provide valuable insight into the risk of hereditary disease when decisions about treating comorbidities are being made. Advances in technology and bioinformatics will make broad screening for potential disease-causing mutations available soon. As DNA tests come into more common use, it is critical that clinicians understand the proper application and interpretation of these test results.

Towards an Earlier Diagnosis of Primary Ciliary Dyskinesia: Which Patients Should Undergo Detailed Diagnostic Testing?

Primary ciliary dyskinesia is a rare heterogeneous recessive genetic disorder of motile cilia, leading to chronic upper and lower respiratory symptoms. Prevalence is estimated at around 1:10,000, but many patients remain undiagnosed, while others receive the label incorrectly. Proper diagnosis is complicated by the fact that the key symptoms such as wet cough, chronic rhinitis and recurrent upper and lower respiratory infection, are common and nonspecific. There is no single gold standard test to diagnose PCD. Presently, the diagnosis is made by augmenting the medical history and physical examination with in patients with a compatible medical history following a demanding combination of tests including nasal nitric oxide, high- speed video microscopy, transmission electron microscopy, genetics, and ciliary culture. These tests are costly and need sophisticated equipment and experienced staff, restricting use to highly specialised centers. Therefore, it would be desirable to have a screening test for identifying those patients who should undergo detailed diagnostic testing. Three recent studies focused on potential screening tools: one paper assessed the validity of nasal nitric oxide for screening, and two studies developed new symptom-based screening tools. These simple tools are welcome, and hopefully remind physicians whom to refer for definitive testing. However, they have been developed in tertiary care settings, where 10 to 50% of tested patients have PCD. Sensitivity and specificity of the tools are reasonable, but positive and negative predictive values may be poor in primary or secondary care settings. While these studies take an important step forward towards an earlier diagnosis of PCD, more remains to be done before we have tools tailored to different health care settings.

An architectural model for software testing lesson learned systems

Software testing is a key aspect of software reliability and quality assurance in a context where software development constantly has to overcome mammoth challenges in a continuously changing environment. One of the characteristics of software testing is that it has a large intellectual capital component and can thus benefit from the use of the experience gained from past projects. Software testing can, then, potentially benefit from solutions provided by the knowledge management discipline. There are in fact a number of proposals concerning effective knowledge management related to several software engineering processes. Objective: We defend the use of a lesson learned system for software testing. The reason is that such a system is an effective knowledge management resource enabling testers and managers to take advantage of the experience locked away in the brains of the testers. To do this, the experience has to be gathered, disseminated and reused. Method: After analyzing the proposals for managing software testing experience, significant weaknesses have been detected in the current systems of this type. The architectural model proposed here for lesson learned systems is designed to try to avoid these weaknesses. This model (i) defines the structure of the software testing lessons learned; (ii) sets up procedures for lesson learned management; and (iii) supports the design of software tools to manage the lessons learned. Results: A different approach, based on the management of the lessons learned that software testing engineers gather from everyday experience, with two basic goals: usefulness and applicability. Conclusion: The architectural model proposed here lays the groundwork to overcome the obstacles to sharing and reusing experience gained in the software testing and test management. As such, it provides guidance for developing software testing lesson learned systems.

LED bulbs technical specification and testing procedure for solar home systems

The definition of technical specifications and the corresponding laboratory procedures are necessary steps in order to assure the quality of the devices prior to be installed in Solar Home Systems (SHS). To clarify and unify criteria a European project supported the development of the Universal Technical Standard for Solar Home Systems (UTSfSHS). Its principles were to generate simple and affordable technical requirements to be optimized in order to facilitate the implementation of tests with basic and simple laboratory tools even on the same SHS electrification program countries. These requirements cover the main aspects of this type of installations and its lighting chapter was developed based on the most used technology at that time: fluorescent tubes and CFLs. However, with the consolidation of the new LED solid state lighting devices, particular attention is being given to this matter and new procedures are required. In this work we develop a complete set of technical specifications and test procedures that have been designed within the frame of the UTSfSHS, based on an intense review of the scientific and technical publications related to LED lighting and their practical application. They apply to lamp reliability, performance and safety under normal, extreme and abnormal operating conditions as a simple but complete quality meter tool for any LED bulb.

The development of a wind tunnel DAQ system by using Labview tools

This paper presents the experimental three-year learning activity developed by a group of teachers in a wind tunnel facility. The authors, leading a team of students, carried out a project consisting of the design, assembly and testing of a wind tunnel. The project included all stages of the process from its initial specifications to its final quality flow assessments, going through the calculation of each element, and the building of the whole wind tunnel. The group of (final year) students was responsible for the whole wind tunnel project as a part of their bachelor degree project. The paper focuses on the development of wind tunnel data acquisition software. This automatic tool is essential to improve the automation of the data acquisition of the wind tunnel facility systems, in particular for a 6DOF multi-axis force/torque sensor. This work can be considered as a typical example of real engineering practice: a set of specifications that has to be modified due to the constraints imposed throughout the project, in order to obtain the final result

A systematic mapping study on testing technique experiments: has the situation changed since 2000?

Context: Empirical Software Engineering (ESE) replication researchers need to store and manipulate experimental data for several purposes, in particular analysis and reporting. Current research needs call for sharing and preservation of experimental data as well. In a previous work, we analyzed Replication Data Management (RDM) needs. A novel concept, called Experimental Ecosystem, was proposed to solve current deficiencies in RDM approaches. The empirical ecosystem provides replication researchers with a common framework that integrates transparently local heterogeneous data sources. A typical situation where the Empirical Ecosystem is applicable, is when several members of a research group, or several research groups collaborating together, need to share and access each other experimental results. However, to be able to apply the Empirical Ecosystem concept and deliver all promised benefits, it is necessary to analyze the software architectures and tools that can properly support it.

Testing ancient RNA–protein interactions

The past decade in molecular biology has seen remarkable advances in the study of the origin and early evolution of life. The mathematical tools for analyzing DNA and protein sequences, coupled with the availability of complete microbial genome sequences, provide insight almost as far back as the age of the nucleic acids themselves. Experimental evolution in the laboratory and especially in vitro evolution of RNA provide insight into a hypothetical world where RNA, or a close relative, may have debuted as a primary functional and informational molecule. The ability to isolate new functional RNAs from random sequences now ultimately makes the world of possible primitive chemical interactions accessible even when the molecules or reactions are no longer present in modern species. Thus we can at last form direct experimental tests of specific models for the origin of RNA–protein associations, such as those that influenced the genetic code. This marks a turning point for probing the origin and early history of life at the molecular level.