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Effectively developing robust predictive models for forecasting infectious disease dynamics over space and time relies on successful surveillance strategies to accurately assess host infection status. We are constantly refining these models to improve our understanding of transmission and persistence dynamics in host populations but are continuously challenged with difficulties in accurately diagnosing host infection status. These challenges are especially persistent for pathogens of the Mycobacterium tuberculosis Complex (MTBC), which cause tuberculosis (TB) disease in a wide array of mammalian hosts. These challenges are further exacerbated when working with MTBC pathogens in free-ranging wildlife hosts. Although TB disease in humans is a primary concern, TB in free-ranging wildlife hosts poses a large threat to human and animal health. One recently described and novel MTBC pathogen is Mycobacterium mungi, which infects the highly social, group-living banded mongoose (Mungos mungo). M. mungi poses a large threat to human and animal health as banded mongoose hosts thrive in urbanized areas and live in close proximity to humans, but despite this threat, accurately diagnosing M. mungi infection status remains a primary challenge. Here, I develop a host response-based assay for differentiating banded mongoose with clinical M. mungi disease from individuals that are putatively healthy using transcriptional biomarkers in whole blood. To our knowledge, this is the first evaluation of host response-based transcriptional signatures to detect TB infection in unstimulated whole blood collected from a free-ranging wildlife species. I found that the expression of two genes, GBP5 and DUSP3, are significantly upregulated (GBP5, p < .05; DUSP3, p < .005) in banded mongoose with clinical M. mungi disease when compared to that of putatively healthy individuals. These results are consistent with studies of active M. tuberculosis disease in humans and support the use of host response-based assays using blood transcriptional biomarkers for diagnosing TB in free-ranging wildlife hosts. These findings are important for improving surveillance strategies for diagnosing M. mungi infection status in banded mongoose and will be essential in refining predictive models for forecasting transmission and persistence dynamics over space and time. / Creating models to predict how diseases circulate and persist within a population is dependent on our ability to accurately diagnose if a host is infected. Diagnosing infection is difficult for some diseases, including tuberculosis (TB) pathogens, which infect humans and many other mammalian species. While vast improvements have been made in diagnosing TB infection in humans, diagnosing TB in free-ranging wildlife species is a constant challenge. These challenges are further exacerbated across the different pathogen species of TB. Although TB disease in humans is a primary concern, TB in free-ranging wildlife hosts poses a large threat to human and animal health. One recently discovered TB pathogen is Mycobacterium mungi, which infects free-ranging banded mongoose (Mungos mungo). This pathogen poses a large threat to human and animals health since banded mongoose thrive in urbanized areas and live in close proximity to humans. Despite this threat, accurately diagnosing M. mungi infection in banded mongoose remains a challenge. Here, I develop a diagnostic molecular tool that uses banded mongoose blood to measure the expression of specific genes and differentiate diseased individuals from seemingly healthy individuals. To our knowledge, this is the first study that has used this specific approach for diagnosing TB in a free-ranging wildlife species. I found that the expression of two genes are significantly increased in banded mongoose with clinical M. mungi disease when compared to that of seemingly healthy individuals. These results are consistent with studies human TB disease in humans and support the use of this approach for diagnosing TB in free-ranging wildlife hosts. These findings are important for improving diagnostics for M. mungi infection in banded mongoose and will be essential in refining models for predicting how this disease circulates and persists over space and time.

Les diagnostics lasers ont prouvé leur potentiel pour l'analyse des écoulements et des phénomènes de combustion par la mesure de champs de vitesses, de concentration d'espèces et de température. La diffusion Raman spontanée (DRS) est une des rares méthodes permettant de mesurer la température et la concentration de manière in-situ avec la possibilité de sonder plusieurs espèces simultanément. L'analyse des flammes turbulentes par DRS est difficile en raison de la nécessité de mesures mono-coup avec de fortes résolutions spatiales et temporelles et de la présence de lumière parasite. L'originalité de notre nouveau dispositif de mesure réside dans l'utilisation d'un obturateur électro-optique à base de cellule de Pockels (OCP), permettant d'éliminer les lumières non polarisées de fond de flamme, compatible avec une mesure 1D. Une réduction significative de l'émission de flamme et une amélioration du rapport signal sur bruit des espèces Raman actives ont été obtenues. La capacité de la DRS en tant que méthode de thermométrie mono-coup a été testée avec succès dans le cas d'une flamme de prémélange et de diffusion laminaire fuligineuse. L'écart relatif entre les températures moyennes mesurées dans les gaz brûlés et celles données par la modélisation de flamme est inférieur à 1 %. L'analyse de la thermométrie Raman à basse température a montré qu'une meilleure précision était obtenue avec la modélisation de 02 comparée à celle N2. Par la suite, le potentiel de la DRS à fournir des mesures simultanées de concentrations instantanées de N2, 02 et CO dans les flammes a été validé. Une évaluation des performances de différents détecteurs CCD accompagnés de l'OCP a également été réalisée. Les résultats obtenus avec la BI-CCD et la BI-EMCCD pour la température, le gradient de température et la forte densité sont en bon accord avec les calculs laminaires 1D de flamme adiabatique fournis par COSILAB. La BI-EMCCD a montré qu'elle est le détecteur le plus sensible pour la détection des espèces à faibles concentrations comme le CO. Enfin, des mesures par DRS ont été obtenues dans une flamme-jet de diffusion turbulente, en présence des suies illustrant le potentiel de cette technique pour construire une base de données importante pour la modélisation numérique des flammes / Laser diagnostics have been proven to be an indispensable tool to analyze the flow and combustion phenomena by allowing non-intrusive measurements of the velocity field, concentration and temperature. Spontaneous Raman Scattering (SRS) is one of the few methods providing simultaneously in-situ temperature and multi-species concentrations. Measurement in turbulent flames by SRS is still challenging due to the emission background and the requirement of single-shot measurements with high spatial and temporal resolutions. The originality of the present approach consists in use of a large aperture Pockels cell based electro-optical shutter (PCS), that allows removing unpolarised background flame emission and compatible with a 1D measurement. A significant reduction of flame emission was observed and consequently signal to noise ratio was enhanced. The ability of SRS in terms of thermometric single-shot method was demonstrated successfully in premixed laminar flames and sooty laminar diffusion flames. The measured temperature in burnt gases and those calculated by adiabatic flame modelling was within 1 %. Thermometric Raman analysis for low temperatures demonstrates the reliability of measurements, with a better accuracy for 02 compared to N2. Subsequently, the ability of SRS technique to simultaneously measure instantaneous concentrations of N2, 02 and CO was demonstrated. The ability to measure single-shot scalar values accurately is assessed by comparing different CCD detectors with the PCS. The results obtained from the BI-CCD and the BI-EMCCD concerning temperature, temperature gradient and high density were in good agreement with the COSILAB calculation for 1D laminar adiabatic flame. The BI-EMCCD observed to be the most sensitive in detecting low concentration elements like CO. Finally, SRS technique was applied to a turbulent sooting jet flame, illustrating the potentiel of this technique to build an important database for flame modelling

Increasingly growing consumption of natural gas all around the world requires development of new transporting equipment and optimization of existing pipelines and gas pumping facilities. As a special case, Russian gas pumping system has the longest pipes with large diameter, which carry great amounts of natural gas. So, as reconstruction and modernization needs large investments, a need of more effective and low cost tool appeared. As a result diagnostics became the most wide-spread method for lifecycle assessment, and lifecycle extension for gas pumping units and pipelines.One of the most effective method for diagnostics of gas pumping units is parametric diagnostics. It is based on evaluation of measurement of several termo-gas dynamic parameters of gas pumping units, such as pressures, temperatures and rotational speed of turbines and compressors.In my work I developed and examined a special case of parametric diagnostics – methodic for evaluation of technical state and output parameters for gas pumping unit “Ural-16”. My work contains detailed analysis of various defects, classified by different GPU’s systems. The results of this analysis are later used in development of the methodic for calculation of output parameters for gas pumping unit.GPU is an extremely complex object for diagnostics. Around 200 combinations of Gas Turbine engines with centrifugal superchargers, different operational conditions and other aspects require development of separate methodic almost for each gas pumping unit type.Development of each methodic is a complex work which requires gathering of all possible parametric and statistical data for the examined gas pumping unit. Also parameters of compressed gas are measured. Thus as a result a number of equations are formed which finally allow to calculate such parameters as efficiency, fuel gas consumption and technical state coefficient which couldn’t be measured directly by existing measuring equipment installed on the gas compressor station.

Für die diagnostische Inferenz unter Unsicherheit werden Bayessche Netze untersucht. Grundlage dafür bildet eine adäquate einheitliche Repräsentation des notwendigen Wissens. Dies ist sowohl generisches als auch auf Erfahrungen beruhendes spezifisches Wissen, welches in einer Wissensbasis gespeichert wird. Zur Wissensverarbeitung wird eine Kombination der Problemlösungsmethoden des Concept Based und Case Based Reasoning eingesetzt. Concept Based Reasoning wird für die Diagnose-, Therapie- und Medikationsempfehlung und -evaluierung über generischesWissen eingesetzt. Sonderfälle in Form von spezifischen Patientenfällen werden durch das Case Based Reasoning verarbeitet. Darüber hinaus erlaubt der Einsatz von Bayesschen Netze den Umgang mit Unsicherheit, Unschärfe und Unvollständigkeit. Es können so die gültigen allgemeinen Konzepte nach derenWahrscheinlichkeit ausgegeben werden. Dazu werden verschiedene Inferenzmechanismen vorgestellt und anschließend im Rahmen der Entwicklung eines Prototypen evaluiert. Mit Hilfe von Tests wird die Klassifizierung von Diagnosen durch das Netz bewertet.:1 Einleitung 2 Repräsentation und Inferenz 3 Inferenzmechanismen 4 Prototypische Softwarearchitektur 5 Evaluation 6 Zusammenfassung

ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California / Unique vehicle designs encourage the use of the builder to complete its own failure analysis. Current failure analysis practices use telemetry and diagnostic technology developed over the past 100 years to identify root-cause. When telemetry isn't available speculation is used to create a list of prioritized, potential causes. Prognostic technology consists of generic algorithms that identify equipment that has failed and is going to fail while the equipment is still at the factory allowing the equipment to be repaired or replaced while it is still on the ground for any spacecraft, satellite, launch vehicle and missile.

Were he alive today, would Louis Pasteur still champion culture methods he pioneered over 150 years ago for identifying bacterial pathogens? Or, might he suggest that new molecular techniques may prove a better way forward for quickly detecting the true microbial diversity of wounds? As modern clinicians faced with treating complex patients with diabetic foot infections (DFI), should we still request venerated and familiar culture and sensitivity methods, or is it time to ask for newer molecular tests, such as 16S rRNA gene sequencing? Or, are molecular techniques as yet too experimental, non-specific and expensive for current clinical use? While molecular techniques help us to identify more microorganisms from a DFI, can they tell us ‘who done it?', that is, which are the causative pathogens and which are merely colonizers? Furthermore, can molecular techniques provide clinically relevant, rapid information on the virulence of wound isolates and their antibiotic sensitivities? We herein review current knowledge on the microbiology of DFI, from standard culture methods to the current era of rapid and comprehensive ‘crime scene investigation' (CSI) techniques.

Measurements of neutron emission from a fusion plasma can provide a wealth of information on the underlying temporal, spatial and energy distributions of reacting ions and how they are affected by a wide range of magneto-hydro-dynamic (MHD) instabilities. This thesis focuses on the interpretation of the experimental measurements recorded by neutron flux monitors with and without spectroscopic capabilities installed on the Mega Ampere Spherical Tokamak (MAST). In particular, the temporally and spatially resolved measurements of the neutron rate measured by the neutron camera, which also possesses spectroscopic capabilities, are combined with the temporally resolved measurements of the total neutron rate provided by the absolutely calibrated fission chamber in order to study the properties of the fast ion distributions in different plasma scenarios. The first part of the thesis describes in detail the two forward modelling methods, which employ the set of interconnected codes developed to interpret experimental observations such as neutron count rate profiles and recoil proton pulse height spectra provided by the neutron camera. In the second part of the thesis the developed methods are applied to model the neutron camera observations performed in a variety of plasma scenarios. The first method, which involves only TRANSP/NUBEAM and LINE2 codes, was used to validate the neutron count rate profiles measured by the neutron camera in three different plasma scenarios covering the wide range of total neutron rate typically observed on MAST. In addition, the first framework was applied to model the changes in the total and local neutron rates caused by fishbone instability as well as to estimate the Hydrogen and Deuterium ion ratio. The second modelling method, which involves TRANSP/NUBEAM, LINE2, DRESS and NRESP, was used to validate the measured recoil proton pulse height spectra in a MHD-quiescent plasma scenario.