Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models

Data analysis can be carried out based on a stochastic model that reflects the analyst's understanding of how the system in question behaves. The stochastic model describes where in the system randomness is present and how the randomness plays a role in generating data. The likelihood of the data defined by the model summarizes the evidence provided by observations of the system. Drawing inference from the likelihood of the data, however, can be far from being simple or straightforward, especially in modern statistical data analyses. Complex probability models and big data call for new computational methods to translate the likelihood of data into inference results. In this thesis, I present two innovations in computational inference for complex stochastic models. The first innovation lies in the development of a method that enables inference on coupled dynamic systems that are partially observed. The high dimensionality of the model that defines the joint distribution of the coupled dynamic processes makes computational inference a challenge. I focus on the case where the probability model is not analytically tractable, which makes the computational inference even more challenging. A mechanistic model of a dynamic process that is defined via a simulation algorithm can lead to analytically intractable models. I show that algorithms that utilize the Markov structure and the mixing property of stochastic dynamic systems can enable fully likelihood based inference for these high dimensional analytically intractable models. I demonstrate theoretically that these algorithms can substantially reduce the computational cost for inference, and the reduction may be orders of magnitude in practice. Spatiotemporal dynamics of measles transmission are inferred from data collected at linked geographic locations, as an illustration that this algorithm can offer an advance in scientific inference. The second innovation involves a generalization of the framework in which samples from a probability distribution with unnormalized density are drawn using Markov chain Monte Carlo algorithms. The new framework generalizes the widely used Metropolis-Hastings acceptance or rejection strategy. The resulting method is straightforward to implement in a broad range of MCMC algorithms, including the most frequently used ones such as random walk Metropolis, Metropolis adjusted Langevin, Hamiltonian Monte Carlo, or the bouncy particle sampler. Numerical studies show that this new framework enables flexible tuning of parameters and facilitates faster mixing of the Markov chain, especially when the target probability density has complex structure.PHDStatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145801/1/joonhap_1.pd

THERMAL HYDRAULIC ISSUES OF CONTAINMENT FILTERED VENTING SYSTEM FOR A LONG OPERATING TIME

This study investigated the thermal hydraulic issues in the Containment Filtered Venting System (CFVS) for a long operating time using the MELCOR computer code. The modeling of the CFVS, including the models for pool scrubbing and the filter, was added to the input file for the OPR-1000, and a Station Blackout (SBO) was chosen as an accident scenario. Although depressurization in the containment building as a primary objective of the CFVS was successful, the decontamination feature by scrubbing and filtering in the CFVS for a long operating time could fail by the continuous evaporation of the scrubbing solution. After the operation of the CFVS, the atmosphere temperature in the CFVS became slightly above the water saturation temperature owing to the release of an amount of steam with high temperature from the containment building to the scrubbing solution. Reduced pipe diameters at the inlet and outlet of the CFVS vessel mitigated the evaporation of scrubbing water by controlling the amount of high-temperature steam and the water saturation temperature

Raoultella ornithinolytica in a healthy, young person: rapidly progressive sinusitis with orbital and intracranial involvement

Raoultella ornithinolytica is an encapsulated, Gram-negative, nonmotile, rod belonging to the Enterobacteriaceae family. Infections involving the gastrointestinal tract and the hepatopancreatobiliary system are most frequently reported, especially in immunocompromised patients. The authors present an unusual case of acute complicated sinusitis with orbital and intracranial involvement caused by R. ornithinolytica. The infection was rapidly progressive, even though the patient was a healthy, young person without any co-morbidities. The patient’s condition improved after antibiotic treatment and multiple ophthalmic and sinus surgeries

Could real-time ultrasonography guidance be useful for the effective deployment of FemoSeal in common femoral arteriotomy?

A vascular closure device is used for hemostasis after a procedure involving an arterial puncture. The increasing frequency of endovascular arterial interventions has caused these devices to play a more important role in clinical practice. FemoSeal is a popular vascular closure device, and its safety and effectiveness have been verified. However, complications still occur in some cases, including even disastrous complications on occasion. Even with little experience, it is possible to reduce the complication rate by using real-time ultrasonography monitoring during the deployment of this device. Based on our experiences, presented herein, we suggest that complications related to FemoSeal could be reduced by using our method

Yonsei Experience in Robotic Urologic Surgery - Application in Various Urological Procedures

PURPOSE: The da Vinci robot system has been used to perform complex reconstructive procedures in a minimally invasive fashion. Robot-assisted laparoscopic radical prostatectomy has recently established as one of the standard cares. Based on experience with the robotic prostatectomy, its use is naturally expanding into other urologic surgeries. We examine our practical pattern and application of da Vinci robot system in urologic field. PATIENTS AND METHODS: Robotic urologic surgery has been performed during a period from July 2005 to August 2008 in a total of 708 cases. Surgery was performed by 7 operators. In our series, radical prostatectomy was performed in 623 cases, partial nephrectomy in 43 cases, radical cystectomy in 11 cases, nephroureterectomy in 18 cases and other surgeries in 15 cases. RESULTS: In the first year, robotic urologic surgery was performed in 43 cases. However, in the second year, it was performed in 164 cases, and it was performed in 407 cases in the third year. In the first year, only prostatectomy was performed. In the second year, partial nephrectomy (2 cases), nephroureterectomy (3 cases) and cystectomy (1 case) were performed. In the third year, other urologic surgeries than prostatectomy were performed in 64 cases. The first robotic surgery was performed with long operative time. For instance, the operative time of prostatectomy, partial nephrectomy, cystectomy and nephroureterectomy was 418, 222, 340 and 320 minutes, respectively. Overall, the mean operative time of prostatectomy, partial nephrectomy, cystectomy and nephrourectectomy was 179, 173, 309, and 206 minutes, respectively. CONCLUSION: Based on our experience at a single-institution, robot system can be used both safely and efficiently in many areas of urologic surgeries including prostatectomy. Once this system is familiar to surgeons, it will be used in a wide range of urologic surgeryope

Exosomes from Human Adipose Tissue-Derived Mesenchymal Stem Cells Promote Epidermal Barrier Repair by Inducing de Novo Synthesis of Ceramides in Atopic Dermatitis.

Atopic dermatitis (AD) is a multifactorial, heterogeneous disease associated with epidermal barrier disruption and intense systemic inflammation. Previously, we showed that exosomes derived from human adipose tissue-derived mesenchymal stem cells (ASC-exosomes) attenuate AD-like symptoms by reducing multiple inflammatory cytokine levels. Here, we investigated ASC-exosomes' effects on skin barrier restoration by analyzing protein and lipid contents. We found that subcutaneous injection of ASC-exosomes in an oxazolone-induced dermatitis model remarkably reduced trans-epidermal water loss, while enhancing stratum corneum (SC) hydration and markedly decreasing the levels of inflammatory cytokines such as IL-4, IL-5, IL-13, TNF-α, IFN-γ, IL-17, and TSLP, all in a dose-dependent manner. Interestingly, ASC-exosomes induced the production of ceramides and dihydroceramides. Electron microscopic analysis revealed enhanced epidermal lamellar bodies and formation of lamellar layer at the interface of the SC and stratum granulosum with ASC-exosomes treatment. Deep RNA sequencing analysis of skin lesions demonstrated that ASC-exosomes restores the expression of genes involved in skin barrier, lipid metabolism, cell cycle, and inflammatory response in the diseased area. Collectively, our results suggest that ASC-exosomes effectively restore epidermal barrier functions in AD by facilitating the de novo synthesis of ceramides, resulting in a promising cell-free therapeutic option for treating AD

Sequences of the Cytochrome C Oxidase Subunit I (COI) Gene are Suitable for Species Identification of Korean Calliphorinae Flies of Forensic Importance (Diptera: Calliphoridae)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75068/1/j.1556-4029.2009.01126.x.pd