Introduction/Background: Guidelines from the World Health Organization currently recommend targeting a body mass index (BMI) between 18.5 and 24.9 kg/m2 based on the lowest risk of mortality observed in epidemiological studies. However, these recommendations are based on population observations and do not take into account potential inter-individual differences. We hypothesized that genetic and non-genetic differences in adiposity, anthropometric, and metabolic measures result in inter-individual variation in the optimal BMI. Methods: Genetic variants associated with BMI as well as related adiposity, anthropometric, and metabolic phenotypes (e.g. triglyceride (TG)) were combined into polygenic risk scores (PRS), cumulative risk scores derived from the weighted contributions of each variant. 387,692 participants in the UK Biobank were split by quantiles of PRS or clinical biomarkers such as C-reactive protein (CRP), and alanine aminotransferase (ALT). The BMI linked with the lowest risk of all-cause and cause-specific mortality outcomes (“nadir value”) was then compared across quantiles (“Cox meta-regression model”). Our results were replicated using the non-linear mendelian randomization (NLMR) model to assess causality. Results: The nadir value for the BMI–all-cause mortality relationship differed across percentiles of BMI PRS, suggesting inter-individual variation in optimal BMI based on genetics (p = 0.005). There was a difference of 1.90 kg/m2 in predicted optimal BMI between individuals in the top and bottom 5th BMI PRS percentile. Individuals having above and below median TG (p = 1.29×10-4), CRP (p = 7.92 × 10-5), and ALT (p = 2.70 × 10-8) levels differed in nadir for this relationship. There was no difference in the computed nadir between the Cox meta-regression or NLMR models (p = 0.102). Conclusions: The impact of BMI on mortality is heterogenous due to individual genetic and clinical biomarker level differences. Although we cannot confirm that are results are causal, genetics and clinical biomarkers have potential use for making more tailored BMI recommendations for patients. / Thesis / Master of Science (MSc) / The World Health Organization (WHO) recommends targeting a body mass index (BMI) between 18.5 - 24.9 kg/m2 for optimal health. However, this recommendation does not take into account individual differences in genetics or biology. Our project aimed to determine whether the optimal BMI, or the BMI associated with the lowest risk of mortality, varies due to genetic or biological variation. Analyses were conducted across 387,692 individuals. We divided participants into groups according to genetic risk for obesity or clinical biomarker profile. Our results show that the optimal BMI varies according to genetic or biomarker profile. WHO recommendations do not account for this variation, as the optimal BMI can fall under the normal 18.5 - 24.9 kg/m2 or overweight 25.0 – 29.0 kg/m2 WHO BMI categories depending on individual genetic or biomarker profile. Thus, there is potential for using genetic and/or biomarker profiles to make more precise BMI recommendations for patients.

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This thesis proposes and evaluates a new cooperative guidance law called General Vector Explicit - Impact Time and Angle Control Guidance (GENEX-ITACG). The motivation for GENEX-ITACG came from an explicit trajectory shaping guidance law called General Vector Explicit Guidance (GENEX). GENEX simultaneously achieves design specifications on miss distance and terminal missile approach angle while also providing a design parameter that adjusts the aggressiveness of this approach angle. Encouraged by the applicability of this user parameter, GENEX-ITACG is an extension that allows a salvo of missiles to cooperatively achieve the same objectives of GENEX against a stationary target through the incorporation of a cooperative trajectory shaping guidance law called Impact Time and Angle Control Guidance (ITACG). ITACG allows a salvo of missile to simultaneously hit a stationary target at a prescribed impact angle and impact time. This predetermined impact time is what allows each missile involved in the salvo attack to simultaneously arrived at the target with unique approach angles, which greatly increases the probability of success against well defended targets. GENEX-ITACG further increases this probability of kill by allowing each missile to approach the target with a unique approach angle rate through the use of a user design parameter. The incorporation of ITACG into GENEX is accomplished through the use of linear optimal control by casting the cost function of GENEX into the formulation of ITACG. The feasibility GENEXITACG is demonstrated across three scenarios that demonstrate the ITACG portion of the guidance law, the GENEX portion of the guidance law, and finally the entirety of the guidance law. The results indicate that GENEX-ITACG is able to successfully guide a salvo of missiles to simultaneously hit a stationary target at a predefined terminal impact angle and impact time, while also allowing the user to adjust the aggressiveness of approach.

In this thesis, we develop some inferential results for one-shot device testing data analysis. These extend and generalize existing methods in the literature. First, a competing-risk model is introduced for one-shot testing data under accelerated life-tests. One-shot devices are products which will be destroyed immediately after use. Therefore, we can observe only a binary status as data, success or failure, of such products instead of its lifetime. Many one-shot devices contain multiple components and failure of any one of them will lead to the failure of the device. Failed devices are inspected to identify the specific cause of failure. Since the exact lifetime is not observed, EM algorithm becomes a natural tool to obtain the maximum likelihood estimates of the model parameters. Here, we develop the EM algorithm for competing exponential and Weibull cases. Second, a semi-parametric approach is developed for simple one-shot device testing data. Semi-parametric estimation is a model that consists of parametric and non-parametric components. For this purpose, we only assume the hazards at different stress levels are proportional to each other, but no distributional assumption is made on the lifetimes. This provides a greater flexibility in model fitting and enables us to examine the relationship between the reliability of devices and the stress factors. Third, Bayesian inference is developed for one-shot device testing data under exponential distribution and Weibull distribution with non-constant shape parameters for competing risks. Bayesian framework provides statistical inference from another perspective. It assumes the model parameters to be random and then improves the inference by incorporating expert's experience as prior information. This method is shown to be very useful if we have limited failure observation wherein the maximum likelihood estimator may not exist. The thesis proceeds as follows. In Chapter 2, we assume the one-shot devices to have two components with lifetimes having exponential distributions with multiple stress factors. We then develop an EM algorithm for developing likelihood inference for the model parameters as well as some useful reliability characteristics. In Chapter 3, we generalize to the situation when lifetimes follow a Weibull distribution with non-constant shape parameters. In Chapter 4, we propose a semi-parametric model for simple one-shot device test data based on proportional hazards model and develop associated inferential results. In Chapter 5, we consider the competing risk model with exponential lifetimes and develop inference by adopting the Bayesian approach. In Chapter 6, we generalize these results on Bayesian inference to the situation when the lifetimes have a Weibull distribution. Finally, we provide some concluding remarks and indicate some future research directions in Chapter 7. / Thesis / Doctor of Philosophy (PhD)

Background: The landmark EXTREME trial established cisplatin, 5-fluorouracil and cetuximab (PFE) as first-line chemotherapy (1L-ChT) for recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC). We were interested in outcome differences of R/M HNSCC in 1L-ChT and factors influencing outcome in certain subgroups, especially patients receiving PFE, and the value of PFE compared to other 1L-ChT regimens to provide real world evidence (RWE). Methods: For this retrospective monocentric study, 124 R/M HNSCC patients without curative surgical or radiotherapy options receiving at least one cycle of 1L-ChT were eligible. We analyzed their outcome using Kaplan-Meier plot and Cox regression to identify predictors for prolonged survival. Results: Subgroups benefiting significantly from PFE were patients suffering from an index HNSCC outside the oropharynx. The PFE regimen proved to be superior to all other 1L-ChT regimens in clinical routine. Significant outcome differences between PFE treatment within or outside controlled trials were not seen. Conclusion: This retrospective analysis provides RWE for factors linked to improved outcome. Subgroup analyses highlight the lasting value of PFE among the growing spectrum of 1L-ChT. Importantly, fit smokers with high level alcohol consumption benefit from PFE; considering the patient’s lifestyle factors, PFE should not be ignored in decision-making.

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No description available.

Hybrid solar-Brayton systems utilize both solar thermal energy and supplementary renewable fuels to provide controllable and dispatchable power output, which renders them a promising way to meet the growing energy demand and reduce the carbon footprints. However, existing testing facilities for key components in such hybrid systems often fail to accomplish the testing requirements, hence impeding the improvement of the renewable energy share and the overall efficiency. A novel testing facility is urgently needed in order to thoroughly stimulate and analyze the component characteristics. This research work focuses on the development of a gas turbine simulator as an innovative testing facility for hot, pressurized components in hybrid solar-Brayton systems. The dual-flow choked nozzle based flow control has been proposed, explained, and analyzed in comparison to the single-flow layout. The basic idea of gas turbine simulator has been experimentally implemented and validated on a prototype, verifying its functionality. By incorporating a PLC-based control system, an automated gas turbine simulator has been designed and modified based on the prototype. Its performance with regard to stabilizing boundaries and tracking trajectories has been evaluated by experiments. Based on the experimental results, the gas turbine simulator prototype has proven its ability to establish controllable boundary conditions and migrate operating points for the impinging receiver. Through manual adjustments, excellent quasi-steady state performance has been obtained, with the precision for pressure control reaching ±0.005 bar at ambient temperature and ±0.015 bar at high temperature of 797.1-931.5 °C. The manual operation time has been identified at 23.1 s for establishing the receiver boundaries, and at 70 s for changing operating points. With the help of the proposed control strategy, the automated gas turbine simulator has eliminated the need for manual adjustments, and demonstrated the ability to maintain the safe and convergent operation for the receiver. The performance in boundary condition stabilization has been satisfactory, with enhanced steady-state accuracy comparing to the prototype by virtue of the PID controller. The transient-state fluctuations in pressure control have been effectively restrained within an acceptable region with deviations of ±0.018 bar to ±0.076 bar from the desired 2.400 bar operating pressure. The capability of tracking linear and nonlinear trajectories has also been testified, with the precision level between ±0.023 bar and ±0.037 bar. Finally, in view of the good stability, high precision, and rapid response manifested in the experimental studies, the gas turbine simulator has validated its ability to imitate the steady and transient characteristics of gas turbines on the boundaries of the test section. It also grants the possibilities to conduct control variable studies and wide-range transition studies. The gas turbine simulator is a suitable testing facility for the key components in hybrid solar-Brayton systems. / Hybrid solenergi-Brayton-system använder både solvärmeenergi och kompletterande förnybara bränslen för att ge kontrollerbar och sändbar effekt, vilket gör dem till ett lovande sätt att möta den växande energiefterfrågan och minska koldioxidavtrycken. Men befintliga testanläggningar för nyckelkomponenter i sådana hybridsystem misslyckas ofta med att uppfylla testkraven, vilket hindrar förbättringen av andelen förnybar energi och den totala effektiviteten. En ny testanläggning behövs omgående för att grundligt stimulera och analysera komponentens egenskaper. Detta forskningsarbete fokuserar på utvecklingen av en gasturbinsimulator som en innovativ testanläggning för varma, trycksatta komponenter i hybridsolar-Brayton-system. Den dubbelströms strypta munstycksbaserade flödeskontrollen har föreslagits, förklarats och analyserats i jämförelse med enkelflödeslayouten. Den grundläggande idén med gasturbinsimulator har experimentellt implementerats och validerats på en prototyp, vilket verifierar dess funktionalitet. Genom att införliva ett PLC-baserat styrsystem har en automatiserad gasturbinsimulator designats och modifierats utifrån prototypen. Dess prestanda med avseende på stabilisering av gränser och spårning av banor har utvärderats genom experiment. Baserat på de experimentella resultaten har prototypen av gasturbinsimulatorn bevisat sin förmåga att upprätta kontrollerbara gränsförhållanden och migrera arbetspunkter för den träffande mottagaren. Genom manuella justeringar har man erhållit utmärkt prestanda i nästan konstant tillstånd, med precisionen för tryckkontroll som når ±0,005 bar vid omgivningstemperatur och ±0,015 bar vid hög temperatur på 797,1-931,5 °C. Den manuella drifttiden har identifierats till 23,1 s för att fastställa mottagargränserna och till 70 s för att byta arbetspunkter. Med hjälp av den föreslagna styrstrategin har den automatiserade gasturbinsimulatorn eliminerat behovet av manuella justeringar och visat förmågan att upprätthålla en säker och konvergent drift för mottagaren. Prestandan vid gränstillståndsstabilisering har varit tillfredsställande, med förbättrad steady-state noggrannhet jämfört med prototypen tack vare PID-regulatorn. De transienta tillståndsfluktuationerna i tryckregleringen har effektivt begränsats inom ett acceptabelt område med avvikelser på ±0,018 bar till ±0,076 bar från det önskade 2,400 bar arbetstrycket. Förmågan att spåra linjära och olinjära banor har också vittnats, med precisionsnivån mellan ±0,023 bar och ±0,037 bar. Slutligen, med tanke på den goda stabiliteten, höga precisionen och snabba responsen som manifesteras i de experimentella studierna, har gasturbinsimulatorn validerat sin förmåga att imitera de stabila och transienta egenskaperna hos gasturbiner på gränserna för testsektionen. Det ger också möjlighet att genomföra kontrollvariabelstudier och omfattande övergångsstudier. Gasturbinsimulatorn är en lämplig testanläggning för nyckelkomponenterna i hybridsolar-Brayton-system.

<p>    </p> <p>The counting process is the fundamental of many real-world problems with event data. Poisson process, used as the background intensity of Hawkes process, is the most commonly used point process. The Hawkes process, a self-exciting point process fits to temporal event data, spatial-temporal event data, and event data with covariates. We study the Hawkes process that fits to heterogeneous drug overdose data via a novel semi-parametric approach. The counting process is also related to survival data based on the fact that they both study the occurrences of events over time. We fit a Cox model to temporal event data with a large corpus that is processed into high dimensional covariates. We study the significant features that influence the intensity of events. </p>

The thesis investigates the impact of age-biased sampling on the accuracy of lifetime prediction models for traffic signs. The bias in question originates from age-biased sampling as a result of the inspection paradox. This phenomenon occurs because longer intervals have a higher probability of being observed compared to shorter intervals, leading to a skewed representation in the data. The research employs a dual approach: firstly, conducting an extensive analysis of real data on traffic sign longevity using a Weibull Survival Model. This analysis is based on the data set compiled by Saleh et al., (2023). Secondly, the study sets up a Monte Carlo simulation to systematically explore the effects of varying degrees and patterns of age bias on the sample. The simulation parameters are derived from the original Weibull Model parameters, obtained from the real dataset. This approach ensures that the simulations closely replicate the actual parameters and estimates. The comparison of the true shape, scale, intercept, and the coefficients associated with the covariates against the simulated estimates indicates a significant bias in the dataset. The study also examines the impact of this bias on the predictive capabilities of various models: Weibull Modeling, Cox Proportional Hazards, Kaplan Meier, and Random Survival Forest. This is done by comparing the true means and medians of the simulated data with the estimates from each model. The findings show that all models exhibit large deviations from the actual means and medians at varying bias levels in the simulated data. The accuracy of the predictions is measured using the Brier Score. This score also shows significant deviations from the prediction accuracy of the original Weibull Model applied to the real dataset, especially when the bias levels vary across simulated datasets. Given these findings, the study advises against using the aforementioned methods for lifetime modeling of traffic signs when there is age bias due to the inspection paradox.