Assessing the Performance of a MIMO SDR Testbed with Dual Transceiver Implementation

Software Defined Radio testbeds are becoming increasingly used in the wireless networking community, given their feature of leaving wireless network designer full control of the PHY layer. On the other hand, SDR testbeds are formed of very complex software/hardware tools, in which implementation bugs are likely and difficult to identify. For this reason, assessment of the results provided by an SDR platform should be a fundamental, preliminary step in the performance evaluation process. In this paper, we provide a thorough assessment of the MIMONet SDR platform for network-level exploitation of MIMO technology. To assess the platform, we have used two different implementations of an OFDM transceiver: one based on Matlab, the other on the GNU Radio software. We have then crossvalidated performance by means of extensive measurements using the two alternative implementations. We have also designed and implemented a fine grained SNR and BER estimation methodology, that allowed us to carefully validate performance of the two software implementations against theoretical predictions. When collectively considered, the results of our measurements promote MIMONet as the first SDR testbed with carefully validated performance

Comparison Metrics for Time-histories: Application to Bridge Aerodynamics

Wind effects can be critical for the design of lifelines such as long-span bridges. The existence of a significant number of aerodynamic force models, used to assess the performance of bridges, poses an important question regarding their comparison and validation. This study utilizes a unified set of metrics for a quantitative comparison of time-histories in bridge aerodynamics with a host of characteristics. Accordingly, nine comparison metrics are included to quantify the discrepancies in local and global signal features such as phase, time-varying frequency and magnitude content, probability density, nonstationarity and nonlinearity. Among these, seven metrics available in the literature are introduced after recasting them for time-histories associated with bridge aerodynamics. Two additional metrics are established to overcome the shortcomings of the existing metrics. The performance of the comparison metrics is first assessed using generic signals with prescribed signal features. Subsequently, the metrics are applied to a practical example from bridge aerodynamics to quantify the discrepancies in the aerodynamic forces and response based on numerical and semi-analytical aerodynamic models. In this context, it is demonstrated how a discussion based on the set of comparison metrics presented here can aid a model evaluation by offering deeper insight. The outcome of the study is intended to provide a framework for quantitative comparison and validation of aerodynamic models based on the underlying physics of fluid-structure interaction. Immediate further applications are expected for the comparison of time-histories that are simulated by data-driven approaches

A speech envelope landmark for syllable encoding in human superior temporal gyrus.

The most salient acoustic features in speech are the modulations in its intensity, captured by the amplitude envelope. Perceptually, the envelope is necessary for speech comprehension. Yet, the neural computations that represent the envelope and their linguistic implications are heavily debated. We used high-density intracranial recordings, while participants listened to speech, to determine how the envelope is represented in human speech cortical areas on the superior temporal gyrus (STG). We found that a well-defined zone in middle STG detects acoustic onset edges (local maxima in the envelope rate of change). Acoustic analyses demonstrated that timing of acoustic onset edges cues syllabic nucleus onsets, while their slope cues syllabic stress. Synthesized amplitude-modulated tone stimuli showed that steeper slopes elicited greater responses, confirming cortical encoding of amplitude change, not absolute amplitude. Overall, STG encoding of the timing and magnitude of acoustic onset edges underlies the perception of speech temporal structure

Wave modelling - the state of the art

This paper is the product of the wave modelling community and it tries to make a picture of the present situation in this branch of science, exploring the previous and the most recent results and looking ahead towards the solution of the problems we presently face. Both theory and applications are considered. The many faces of the subject imply separate discussions. This is reflected into the single sections, seven of them, each dealing with a specific topic, the whole providing a broad and solid overview of the present state of the art. After an introduction framing the problem and the approach we followed, we deal in sequence with the following subjects: (Section) 2, generation by wind; 3, nonlinear interactions in deep water; 4, white-capping dissipation; 5, nonlinear interactions in shallow water; 6, dissipation at the sea bottom; 7, wave propagation; 8, numerics. The two final sections, 9 and 10, summarize the present situation from a general point of view and try to look at the future developments

Classification and modeling of power line noise using machine learning techniques

A thesis submitted in ful lment of the requirements for the degree of Doctor of Philosophy in the School of Electrical and Information Engineering Faculty of Engineering and Built Environment June 2017The realization of robust, reliable and e cient data transmission have been the theme of recent research, most importantly in real channel such as the noisy, fading prone power line communication (PLC) channel. The focus is to exploit old techniques or create new techniques capable of improving the transmission reliability and also increasing the transmission capacity of the real communication channels. Multi-carrier modulation scheme such as Orthogonal Frequency Division Multiplexing (OFDM) utilizing conventional single-carrier modulation is developed to facilitate a robust data transmission, increasing transmission capacity (e cient bandwidth usage) and further reducing design complexity in PLC systems. On the contrary, the reliability of data transmission is subjected to several inhibiting factors as a result of the varying nature of the PLC channel. These inhibiting factors include noise, perturbation and disturbances. Contrary to the Additive White Gaussian noise (AWGN) model often assumed in several communication systems, this noise model fails to capture the attributes of noise encountered on the PLC channel. This is because periodic noise or random noise pulses injected by power electronic appliances on the network is a deviation from the AWGN. The nature of the noise is categorized as non-white non-Gaussian and unstable due to its impulsive attributes, thus, it is labeled as Non-additive White Gaussian Noise (NAWGN). These noise and disturbances results into long burst errors that corrupts signals being transmitted, thus, the PLC is labeled as a horrible or burst error channel. The e cient and optimal performance of a conventional linear receiver in the white Gaussian noise environment can therefore be made to drastically degrade in this NAWGN environment. Therefore, transmission reliability in such environment can be greatly enhanced if we know and exploit the knowledge of the channel's statistical attributes, thus, the need for developing statistical channel model based on empirical data. In this thesis, attention is focused on developing a recon gurable software de ned un-coded single-carrier and multicarrier PLC transceiver as a tool for realizing an optimized channel model for the narrowband PLC (NB-PLC) channel. First, a novel recon gurable software de ned un-coded single-carrier and multi-carrier PLC transceiver is developed for real-time NB-PLC transmission. The transceivers can be adapted to implement di erent waveforms for several real-time scenarios and performance evaluation. Due to the varying noise parameters obtained from country to country as a result of the dependence of noise impairment on mains voltages, topology of power line, place and time, the developed transceivers is capable of facilitating constant measurement campaigns to capture these varying noise parameters before statistical and mathematically inclined channel models are derived. Furthermore, the single-carrier (Binary Phase Shift Keying (BPSK), Di erential BPSK (DBPSK), Quadrature Phase Shift Keying (QPSK) and Di erential QPSK (DQPSK)) PLC transceiver system developed is used to facilitate a First-Order semi-hidden Fritchman Markov modeling (SHFMM) of the NB-PLC channel utilizing the e cient iterative Baum- Welch algorithm (BWA) for parameter estimation. The performance of each modulation scheme is evaluated in a mildly and heavily disturbed scenarios for both residential and laboratory site considered. The First-Order estimated error statistics of the realized First- Order SHFMM have been analytically validated in terms of performance metrics such as: log-likelihood ratio (LLR), error-free run distribution (EFRD), error probabilities, mean square error (MSE) and Chi-square ( 2) test. The reliability of the model results is also con rmed by an excellent match between the empirically obtained error sequence and the SHFMM regenerated error sequence as shown by the error-free run distribution plot. This thesis also reports a novel development of a low cost, low complexity Frequency-shift keying (FSK) - On-o keying (OOK) in-house hybrid PLC and VLC system. The functionality of this hybrid PLC-VLC transceiver system was ascertained at both residential and laboratory site at three di erent times of the day: morning, afternoon and evening. A First and Second-Order SHFMM of the hybrid system is realized. The error statistics of the realized First and Second-Order SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE and Chi-square ( 2). The Second-Order SHFMMs have also been analytically validated to be superior to the First-Order SHFMMs although at the expense of added computational complexity. The reliability of both First and Second-Order SHFMM results is con rmed by an excellent match between the empirical error sequences and SHFMM re-generated error sequences as shown by the EFRD plot. In addition, the multi-carrier (QPSK-OFDM, Di erential QPSK (DQPSK)-OFDM) and Di erential 8-PSK (D8PSK)-OFDM) PLC transceiver system developed is used to facilitate a First and Second-Order modeling of the NB-PLC system using the SHFMM and BWA for parameter estimation. The performance of each OFDM modulation scheme in evaluated and compared taking into consideration the mildly and heavily disturbed noise scenarios for the two measurement sites considered. The estimated error statistics of the realized SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE and Chi-square ( 2) test. The estimated Second-Order SHFMMs have been analytically validated to be outperform the First-Order SHFMMs although with added computational complexity. The reliability of the models is con rmed by an excellent match between the empirical data and SHFMM generated data as shown by the EFRD plot. The statistical models obtained using Baum-Welch to adjust the parameters of the adopted SHFMM are often locally maximized. To solve this problem, a novel Metropolis-Hastings algorithm, a Bayesian inference approach based on Markov Chain Monte Carlo (MCMC) is developed to optimize the parameters of the adopted SHFMM. The algorithm is used to optimize the model results obtained from the single-carrier and multi-carrier PLC systems as well as that of the hybrid PLC-VLC system. Consequently, as deduced from the results, the models obtained utilizing the novel Metropolis-Hastings algorithm are more precise, near optimal model with parameter sets that are closer to the global maxima. Generally, the model results obtained in this thesis are relevant in enhancing transmission reliability on the PLC channel through the use of the models to improve the adopted modulation schemes, create adaptive modulation techniques, develop and evaluate forward error correction (FEC) codes such as a concatenation of Reed-Solomon and Permutation codes and other robust codes suitable for exploiting and mitigating noise impairments encountered on the low voltage NB-PLC channel. Furthermore, the recon gurable software de ned NB-PLC transceiver test-bed developed can be utilized for future measurement campaign as well as adapted for multiple-input and multiple-output (MIMO) PLC applications.MT201

Classification and modeling of power line noise using machine learning techniques

A thesis submitted in ful lment of the requirements for the degree of Doctor of Philosophy in the School of Electrical and Information Engineering Faculty of Engineering and Built Environment June 2017The realization of robust, reliable and e cient data transmission have been the theme of recent research, most importantly in real channel such as the noisy, fading prone power line communication (PLC) channel. The focus is to exploit old techniques or create new techniques capable of improving the transmission reliability and also increasing the transmission capacity of the real communication channels. Multi-carrier modulation scheme such as Orthogonal Frequency Division Multiplexing (OFDM) utilizing conventional single-carrier modulation is developed to facilitate a robust data transmission, increasing transmission capacity (e cient bandwidth usage) and further reducing design complexity in PLC systems. On the contrary, the reliability of data transmission is subjected to several inhibiting factors as a result of the varying nature of the PLC channel. These inhibiting factors include noise, perturbation and disturbances. Contrary to the Additive White Gaussian noise (AWGN) model often assumed in several communication systems, this noise model fails to capture the attributes of noise encountered on the PLC channel. This is because periodic noise or random noise pulses injected by power electronic appliances on the network is a deviation from the AWGN. The nature of the noise is categorized as non-white non-Gaussian and unstable due to its impulsive attributes, thus, it is labeled as Non-additive White Gaussian Noise (NAWGN). These noise and disturbances results into long burst errors that corrupts signals being transmitted, thus, the PLC is labeled as a horrible or burst error channel. The e cient and optimal performance of a conventional linear receiver in the white Gaussian noise environment can therefore be made to drastically degrade in this NAWGN environment. Therefore, transmission reliability in such environment can be greatly enhanced if we know and exploit the knowledge of the channel's statistical attributes, thus, the need for developing statistical channel model based on empirical data. In this thesis, attention is focused on developing a recon gurable software de ned un-coded single-carrier and multicarrier PLC transceiver as a tool for realizing an optimized channel model for the narrowband PLC (NB-PLC) channel. First, a novel recon gurable software de ned un-coded single-carrier and multi-carrier PLC transceiver is developed for real-time NB-PLC transmission. The transceivers can be adapted to implement di erent waveforms for several real-time scenarios and performance evaluation. Due to the varying noise parameters obtained from country to country as a result of the dependence of noise impairment on mains voltages, topology of power line, place and time, the developed transceivers is capable of facilitating constant measurement campaigns to capture these varying noise parameters before statistical and mathematically inclined channel models are derived. Furthermore, the single-carrier (Binary Phase Shift Keying (BPSK), Di erential BPSK (DBPSK), Quadrature Phase Shift Keying (QPSK) and Di erential QPSK (DQPSK)) PLC transceiver system developed is used to facilitate a First-Order semi-hidden Fritchman Markov modeling (SHFMM) of the NB-PLC channel utilizing the e cient iterative Baum- Welch algorithm (BWA) for parameter estimation. The performance of each modulation scheme is evaluated in a mildly and heavily disturbed scenarios for both residential and laboratory site considered. The First-Order estimated error statistics of the realized First- Order SHFMM have been analytically validated in terms of performance metrics such as: log-likelihood ratio (LLR), error-free run distribution (EFRD), error probabilities, mean square error (MSE) and Chi-square ( 2) test. The reliability of the model results is also con rmed by an excellent match between the empirically obtained error sequence and the SHFMM regenerated error sequence as shown by the error-free run distribution plot. This thesis also reports a novel development of a low cost, low complexity Frequency-shift keying (FSK) - On-o keying (OOK) in-house hybrid PLC and VLC system. The functionality of this hybrid PLC-VLC transceiver system was ascertained at both residential and laboratory site at three di erent times of the day: morning, afternoon and evening. A First and Second-Order SHFMM of the hybrid system is realized. The error statistics of the realized First and Second-Order SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE and Chi-square ( 2). The Second-Order SHFMMs have also been analytically validated to be superior to the First-Order SHFMMs although at the expense of added computational complexity. The reliability of both First and Second-Order SHFMM results is con rmed by an excellent match between the empirical error sequences and SHFMM re-generated error sequences as shown by the EFRD plot. In addition, the multi-carrier (QPSK-OFDM, Di erential QPSK (DQPSK)-OFDM) and Di erential 8-PSK (D8PSK)-OFDM) PLC transceiver system developed is used to facilitate a First and Second-Order modeling of the NB-PLC system using the SHFMM and BWA for parameter estimation. The performance of each OFDM modulation scheme in evaluated and compared taking into consideration the mildly and heavily disturbed noise scenarios for the two measurement sites considered. The estimated error statistics of the realized SHFMMs have been analytically validated in terms of LLR, EFRD, error probabilities, MSE and Chi-square ( 2) test. The estimated Second-Order SHFMMs have been analytically validated to be outperform the First-Order SHFMMs although with added computational complexity. The reliability of the models is con rmed by an excellent match between the empirical data and SHFMM generated data as shown by the EFRD plot. The statistical models obtained using Baum-Welch to adjust the parameters of the adopted SHFMM are often locally maximized. To solve this problem, a novel Metropolis-Hastings algorithm, a Bayesian inference approach based on Markov Chain Monte Carlo (MCMC) is developed to optimize the parameters of the adopted SHFMM. The algorithm is used to optimize the model results obtained from the single-carrier and multi-carrier PLC systems as well as that of the hybrid PLC-VLC system. Consequently, as deduced from the results, the models obtained utilizing the novel Metropolis-Hastings algorithm are more precise, near optimal model with parameter sets that are closer to the global maxima. Generally, the model results obtained in this thesis are relevant in enhancing transmission reliability on the PLC channel through the use of the models to improve the adopted modulation schemes, create adaptive modulation techniques, develop and evaluate forward error correction (FEC) codes such as a concatenation of Reed-Solomon and Permutation codes and other robust codes suitable for exploiting and mitigating noise impairments encountered on the low voltage NB-PLC channel. Furthermore, the recon gurable software de ned NB-PLC transceiver test-bed developed can be utilized for future measurement campaign as well as adapted for multiple-input and multiple-output (MIMO) PLC applications.MT201

Identification of markers for dietary intake and health status by GC-MS based metabolite profiling approaches

Markers are compounds that can be used as indicators of an exposure, a metabolic state, or any other effect. Metabolomics and metabolite profiling approaches for marker discovery will increasingly gain significance. In the context of food, diet, and health, these approaches allow among others the identification of dietary intake markers, which can complement and verify traditional dietary assessment methods in epidemiologic studies. Consequently, the investigation of associations between diet and health status in general, and also in particular diet-related diseases will be improved. Compared to classical biomarker studies, metabolomics enables a more comprehensive investigation of clinical markers for diagnosis, prognosis and monitoring of diseases, such as type 2 diabetes mellitus. Especially, early diagnosis in pre-disease states, where symptoms are not yet evident, are of particular interest. The aim of this thesis was to evaluate the application of GC-MS based metabolite profiling approaches for the identification of markers for dietary intake and health status. In this respect, volatile organic compounds and sugar compounds were analyzed to discover marker candidates in urine and plasma samples from a cross-sectional study with 300 participants, as well as from a human intervention study with diabetic, prediabetic and healthy participants. In the past, the search for markers of dietary intake mostly focused on non-volatile metabolites. To explore the potential of the volatilome, urine samples of a cross-sectional study were analyzed aiming to exemplary identify markers of coffee consumption using an untargeted HS-SPME-GC×GC-MS method. Six marker candidates were identified from a profile of 138 volatile organic compounds with the most robust represented by 3,4-dimethyl-2,5-furandione. Moreover, the correlation with the general dietary intake data highlighted the volatilome as a particularly interesting source for the detection of new dietary markers. The chromatographic separation of sugar compounds is often insufficient due to the high structural similarities. Therefore, in most studies common and well-known sugar compounds are analyzed in human body fluids. Within the scope of this thesis, a semitargeted GC-MS sugar profiling method was developed, which revealed a more complex sugar profile, both in urine and plasma, than described so far or expected. Rare sugar compounds such as psicose and trehalose were detected. However, the knowledge about their origin and presence in urine or plasma is limited to date. Moreover, the maltose concentration in urine was shown to be dependent on sex and menopause status (pre- and post-menopausal) a relationship with the vaginal microbiota is suggested here. In addition, the association of the urinary sugar profile with dietary intake data enabled the identification and confirmation of several new and also known marker candidates as for example, for consumption of avocado, dairy products and alcohol. The plasma sugar profiles of healthy, prediabetic and diabetic volunteers after an oral glucose tolerance test could be clearly distinguished, independent of glucose. Remarkably, a variety of sugar compounds showed marked postprandial differences dependent on health status. For example, trehalose showed a profile similar to the insulin-dependent profile of glucose. However, the origin and underlying biological mechanism for those sugar compounds remain to be elucidated. During the application of the one-dimensional GC-MS sugar profiling method to urine and plasma samples, it became evident that even more sugar compounds might be present, although in low concentrations, but were not detected due to limitations of the analytical method. Therefore, the one-dimensional method was transferred into a two-dimensional GC×GC-MS method. Improved sensitivity and separation finally enabled the detection of 84 instead of 55 sugar compounds in urine. The two-dimensional method was applied in an intervention study with apples, and revealed marker candidates for apple consumption for future validation. Overall, the results illustrate the benefit of a comprehensive analysis of sugar compounds in urine and plasma, including minor and rare sugar derivatives. The GC-MS based metabolite profiling approaches addressing the volatilome and the sugar profile, respectively, were demonstrated to be promising approaches for the identification of markers for dietary intake and health status. Future work should address the identification of unknown compounds, the adaptation of the GC×GC-MS sugar profiling method for quantitative purposes, and especially the validation of the identified marker candidates with respect to their suitability to more accurately assess dietary intake or diabetic state. High priority should also be given to the biochemical mechanisms and the origin of the compounds as well as their physiological or pathophysiological function in human metabolism.Marker sind Substanzen, die als Indikatoren für eine Exposition, einen metabolischen Zustand oder einen Effekt herangezogen werden. Metabolomics und Metabolite profiling-Ansätze gewinnen in der Markerforschung zunehmend an Bedeutung. Metabolomics ermöglicht die Identifizierung von Markern für den Lebensmittelverzehr, die in Zukunft unter anderem in epidemiologischen Studien zur Ergänzung und Überprüfung traditioneller Ernährungserhebungsmethoden Verwendung finden werden. In der Konsequenz können Zusammenhänge zwischen Ernährung und Gesundheit im Allgemeinen, sowie ernährungsabhängigen Erkrankungen im Speziellen, besser beschrieben werden. Außerdem können mittels Metabolomics auch Marker identifiziert werden, die im klinischen Rahmen eine Diagnose, Prognose oder Überwachung von Behandlungsmaßnahmen für eine Erkrankung ermöglichen, wie z.B. bei Typ 2 Diabetes mellitus. Von besonderem Interesse sind dabei Marker, die eine frühzeitige Diagnose, das heißt vor der Manifestation von Symptomen, ermöglichen. Ziel der vorliegenden Arbeit war es, die Verwendung von GC-MS basierten Metabolite profiling-Ansätzen zur Identifizierung von Markern für den Lebensmittelverzehr und den Gesundheitsstatus zu prüfen. Einen besonderen Schwerpunkt bildeten dabei volatile organische Verbindungen und Zuckerverbindungen, die in Urin- und Plasmaproben einer Querschnittsstudie mit 300 Probanden sowie einer humanen Interventionsstudie mit Diabetikern, Prädiabetikern und Gesunden analysiert wurden. Bei der bisherigen Suche nach Markern für den Lebensmittelverzehr lag das Augenmerk vor allem auf nicht-volatilen Metaboliten. Um das Potential des Volatiloms zu eruieren, wurden Urinproben einer Querschnittsstudie mithilfe einer ungerichteten HS-SPME-GC×GC-MS Methode analysiert und darin beispielhaft nach Markern für den Kaffeekonsum gesucht. Aus dem Urinprofil mit 138 volatilen Verbindungen wurden sechs plausible Kandidaten identifiziert, von denen sich 3,4-Dimethyl-2,5-furandion als der robusteste Marker erwies. Mittels einer Korrelationsanalyse anhand von Verzehrsdaten weiterer Lebensmittel wurde darüber hinaus gezeigt, dass das Volatilom eine vielversprechende Quelle neuer Marker für den Lebensmittelverzehr ist. Zucker lassen sich aufgrund ihrer strukturellen Ähnlichkeit häufig nur unzureichend chromatographisch trennen, daher werden in humanen Matrices bisher mehrheitlich nur wenige bekannte Zuckerverbindungen erfasst. Im Rahmen dieser Arbeit wurde eine semi-gerichtete GC-MS Zuckerprofiling-Methode entwickelt, mit der gezeigt werden konnte, dass das humane Zuckerprofil im Urin und im Plasma erheblich komplexer ist, als bisher beschrieben und angenommen. Verschiedene Zuckerverbindungen, wie beispielsweise Psicose oder Trehalose, über deren Herkunft und Vorhandensein im Urin oder in Plasma fast nichts bekannt ist, wurden nachgewiesen. Im Urin zeigten sich darüber hinaus Unterschiede in der Maltosekonzentration in Abhängigkeit vom Geschlecht sowie dem prä- und postmenopausalen Status, die vermutlich im Zusammenhang mit der vaginalen Mikrobiota stehen. Die Assoziation der Zuckerprofile mit dem Lebensmittelverzehr ermöglichte zudem die Identifizierung neuer und Bestätigung bekannter Marker, beispielsweise für den Verzehr von Avocado und Milchprodukten, sowie für Alkoholkonsum. Im Plasma von Gesunden, Prädiabetikern und Diabetikern wurden nach einem oralen Glucosetoleranztest deutliche Unterschiede im Zuckerprofil festgestellt. Interessanterweise zeigten eine Reihe neuer Zuckerverbindungen markante postprandiale Unterschiede abhängig vom Gesundheitszustand. Beispielsweise zeigte Trehalose ein ähnliches Profil wie die insulinabhängige Glucose. Jedoch ist weder über den Mechanismus noch zur Herkunft dieser Zucker etwas bekannt. Bereits die bisherigen Ergebnisse des Zuckerprofilings in Urin und Plasma zeigten, dass zusätzliche Zuckerverbindungen, wenn auch in sehr geringer Konzentration, vorhanden sind. Daher wurde die eindimensionale Methode zu einer zweidimensionalen GC×GC-MS-Methode mit verbesserter Sensitivität und Trennung weiterentwickelt, was nun die Erfassung von 84 statt 55 Zuckerverbindungen in Urin ermöglicht. Erste Auswertungen der Messdaten einer Interventionsstudie mit Äpfeln zeigten, dass diese Methode die Identifizierung von potentiellen Markern für den Verzehr von Äpfeln ermöglicht. Die Ergebnisse verdeutlichen, welches Potential in der umfassenden Analyse von Zuckern, einschließlich seltener Verbindungen, steckt. GC-MS basierte Metabolite profiling-Ansätze, wie hier für das Volatilom und das Zuckerprofil gezeigt, sind geeignete Methoden für die Identifizierung von Markern des Lebensmittelverzehrs und des Gesundheitsstatus. Die Identifizierung bisher unbekannter Verbindungen, die Weiterentwicklung der Zuckeranalytik zu einer quantitativen Methode und insbesondere die Validierung der identifizierten Marker bezüglich ihrer Eignung, den Lebensmittelverzehr bzw. den diabetischen Status akkurater zu erfassen, sind zukünftige Ziele. Besonders herausfordernd ist es dabei, die mechanistischen Zusammenhänge aufzuklären, insbesondere im Hinblick auf Herkunft, Vorhandensein und Funktion der detektierten Zuckerverbindungen im menschlichen Metabolismus

A modeling-based assessment of acousto-optic sensing for monitoring high-intensity focused ultrasound lesion formation

Real-time acousto-optic (AO) sensing - a dual-wave modality that combines ultrasound with diffuse light to probe the optical properties of turbid media - has been demonstrated to non-invasively detect changes in ex vivo tissue optical properties during high-intensity focused ultrasound (HIFU) exposure. The AO signal indicates the onset of lesion formation and predicts resulting lesion volumes. Although proof-of-concept experiments have been successful, many of the underlying parameters and mechanisms affecting thermally induced optical property changes and the AO detectability of HIFU lesion formation are not well understood. In thesis, a numerical simulation was developed to model the AO sensing process and capture the relevant acoustic, thermal, and optical transport processes. The simulation required data that described how optical properties changed with heating. Experiments were carried out where excised chicken breast was exposed to thermal bath heating and changes in the optical absorption and scattering spectra (500 nm - 1100 nm) were measured using a scanning spectrophotometer and an integrating sphere assembly. Results showed that the standard thermal dose model currently used for guiding HIFU treatments needs to be adjusted to describe thermally induced optical property changes. To model the entire AO process, coupled models were used for ultrasound propagation, tissue heating, and diffusive light transport. The angular spectrum method was used to model the acoustic field from the HIFU source. Spatial-temporal temperature elevations induced by the absorption of ultrasound were modeled using a finite-difference time-domain solution to the Pennes bioheat equation. The thermal dose model was then used to determine optical properties based on the temperature history. The diffuse optical field in the tissue was then calculated using a GPU-accelerated Monte Carlo algorithm, which accounted for light-sound interactions and AO signal detection. The simulation was used to determine the optimal design for an AO guided HIFU system by evaluating the robustness of the systems signal to changes in tissue thickness, lesion optical contrast, and lesion location. It was determined that AO sensing is a clinically viable technique for guiding the ablation of large volumes and that real-time sensing may be feasible in the breast and prostate