Nonparametric inference under a monotone hazard ratio order

The ratio of the hazard functions of two populations or two strata of a single population plays an important role in time-to-event analysis. Cox regression is commonly used to estimate the hazard ratio under the assumption that it is constant in time, which is known as the proportional hazards assumption. However, this assumption is often violated in practice, and when it is violated, the parameter estimated by Cox regression is difficult to interpret. The hazard ratio can be estimated in a nonparametric manner using smoothing, but smoothing-based estimators are sensitive to the selection of tuning parameters, and it is often difficult to perform valid inference with such estimators. In some cases, it is known that the hazard ratio function is monotone. In this article, we demonstrate that monotonicity of the hazard ratio function defines an invariant stochastic order, and we study the properties of this order. Furthermore, we introduce an estimator of the hazard ratio function under a monotonicity constraint. We demonstrate that our estimator converges in distribution to a mean-zero limit, and we use this result to construct asymptotically valid confidence intervals. Finally, we conduct numerical studies to assess the finite-sample behavior of our estimator, and we use our methods to estimate the hazard ratio of progression-free survival in pulmonary adenocarcinoma patients treated with gefitinib or carboplatin-paclitaxel

An Analysis Of Using Semi-Permeable Membrane Devices To Assess Persistent Organic Pollutants In Ambient Air Of Alaska

Thesis (Ph.D.) University of Alaska Fairbanks, 2006A region of concern for persistent organic pollutants (POPS) contamination is the Arctic, because of POPs' ability to migrate long distances through the atmosphere toward cold regions, condense out of the atmosphere in those region, deposit in sensitive arctic ecosystems and bioaccumulate in Arctic species. Thus, monitoring of POP concentrations in the Arctic is necessary. However, traditional active air monitoring techniques for POPs may not be feasible in the Arctic, because of logistics and cost. While these issues may be overcome using passive air sampling devices, questions arise about the interpretation of the contaminant concentrations detected using the passive air samplers. In this dissertation semi-permeable membrane devices (SPMDs) containing triolein were characterized and evaluated for use in sampling the ambient air of Alaska for three classes of POPS (organochlorines [OCs], polychlorinated biphenyls [PCBs] and polyaromatic hydrocarbons [PAHs]). In addition, a SPMD-based sampling campaign for POPS was conducted simultaneously at five sites in Alaska during a one-year period. The POP concentrations obtained from the SPMDs were examined to determine the spatial and seasonal variability at the locations. POP concentrations detected in SPMDs were influenced by exposure to sunlight, concentrations of particulate-bound contaminants and changes in temperature. PAH concentrations in a SPMD mounted in a sunlight-blocking deployment unit were higher than in a SPMD exposed to sunlight (P = 0.007). PCB concentrations in SPMD exposed to filtered and non-filtered air were significantly different (P < 0.0001). Derived PAH air concentrations measured using SPMD were within a factor of approximately 7 of those obtained from an air sampler in Barrow, Alaska. The field study showed three distinct groups of samples. Barrow was separated from the sub-Arctic samples and a Homer sample (September-December) was distinct from the sub-Arctic samples. The separations suggest different air masses are being sampled by SPMDs. Lower concentrations of total POPs were measured at the coastal sites than the Interior sites

Atomic ionization by sterile-to-active neutrino conversion and constraints on dark matter sterile neutrinos with germanium detectors

The transition magnetic moment of a sterile-to-active neutrino conversion gives rise to not only radiative decay of a sterile neutrino, but also its non-standard interaction (NSI) with matter. For sterile neutrinos of keV-mass as dark matter candidates, their decay signals are actively searched for in cosmic X-ray spectra. In this work, we consider the NSI that leads to atomic ionization, which can be detected by direct dark matter experiments. It is found that this inelastic scattering process for a nonrelativistic sterile neutrino has a pronounced enhancement in the differential cross section at energy transfer about half of its mass, manifesting experimentally as peaks in the measurable energy spectra. The enhancement effects gradually smear out as the sterile neutrino becomes relativistic. Using data taken with germanium detectors that have fine energy resolution in keV and sub-keV regimes, constraints on sterile neutrino mass and its transition magnetic moment are derived and compared with those from astrophysical observations

Cardiovascular Disease in Diabetic Nephropathy Patients: Cell Adhesion Molecules as Potential Markers?

Cardiovascular disease is a major complication of diabetes mellitus, especially for patients with diabetic nephropathy. The underlying factor or pathogenic mechanism that links diabetic nephropathy with cardiovascular disease is not known. The endothelial cell adhesion molecules, intercellular adhesion molecule-1 or vascular cell adhesion molecule-1, play a crucial role in the initiation of atherosclerosis. Levels of both cell adhesion molecules are raised by the diabetic and kidney disease states. This review focuses on these important cell adhesion molecules and their role in the pathogenesis of cardiovascular disease in diabetes and diabetic nephropathy

Parallelism encapsulation in C++

Object oriented programming features information hiding and encapsulation, meaning that 1) each object hides the the implementation details tram access from outside and only a set of methods (interface routines) are visible outside of the object, and 2) changes to the implementation of the object do not require changes to the code that uses the object, so long as the interface is stable. However, the interface mechanism in C++ is not adequate to achieve information hiding and encapsulation when writing parallel C++ programs, since the methods are assumed to be invoked in sequence and no parallel interactions are represented by them. Also, even when the methods are the same, changes to the implementation details of the methods often affect the interaction pattern of the methods so the parallel code that uses the methods must be rewitten. To achieve information hiding and encapsulation, we propose adding path expressions to the class interface. Thus either dynamic or automatic parallelization can be used to achieve parallelism encapsulation. A new concept of data dependence analysis is introduced which uses the parallelism described by path expressions to efficiently and automatically parallelize an object-oriented program

Parallel algorithms for decomposed linear programs

New parallel algorithms for solving the decomposed linear programs are developed. Direct parallelization of the sequential algorithm results in very limited performance improvement using multiple processors. By redesigning the algorithm, we achieved more than 2*P times performance improvement over the sequential algorithm, where P is the number of processors used in parallel computation. Furthermore, a particular variation of the sequential algorithm runs more than 2 times faster than the original sequential algorithm. The new parallel algorithm linearly speedups the new sequential algorithm

Parallelizing WHILE loops

Two methods for parallelizing WHILE loops are presented. The first method converts a WHILE loop into a FORALL construct, and the second method pipelines a WHILE loop. Each of the methods is based on a transformation that makes explicit the loop counting. Also, we propose two parallel WHILE constructs

NASA IceCube: CubeSat Demonstration of a Commercial 883-GHz Cloud Radiometer

On April 18 2017, NASA Goddard Space Flight Center’s IceCube 3U CubeSat was launched by an ATLAS V rocket from Cape Canaveral Air Force Station on board a Cygnus resupply spacecraft, as part of NASA’s CubeSat Launch Initiative. Onboard IceCube was an 883 GHz radiometer tuned to detecting ice content in clouds, marking the first time such frequency was used from low-Earth orbit. IceCube successfully demonstrated retrieval of ice water path, generating the first ever global cloud ice map at 883 GHz. Its success provides valuable lessons on how to approach a severely resource-limited space mission and provides great insight into how this experience can be applied to future high-risk, “non-class” missions for NASA and others. IceCube marks the first official NASA Earth Science CubeSat technology demonstration mission. The spacecraft was completed in about 2.5 years starting April 2014 through launch provider delivery in December of 2016. The mission was jointly funded by NASA’s Earth Science Technology Office, after competitive selection, and by NASA’s Earth Science Directorate. IceCube began its technology demonstration mission in June 2017, providing a pathway to advancing the understanding of ice clouds and their role in climate models; quite a tall order for a tiny spacecraft