Thermochemical stability of low-iron, manganese-enriched olivine in astrophysical environments

Low-iron, manganese-enriched (LIME) olivine grains are found in cometary samples returned by the Stardust mission from comet 81P/Wild 2. Similar grains are found in primitive meteoritic clasts and unequilibrated meteorite matrix. LIME olivine is thermodynamically stable in a vapor of solar composition at high temperature at total pressures of a millibar to a microbar, but enrichment of solar composition vapor in a dust of chondritic composition causes the FeO/MnO ratio of olivine to increase. The compositions of LIME olivines in primitive materials indicate oxygen fugacities close to those of a very reducing vapor of solar composition. The compositional zoning of LIME olivines in amoeboid olivine aggregates is consistent with equilibration with nebular vapor in the stability field of olivine, without re-equilibration at lower temperatures. A similar history is likely for LIME olivines found in comet samples and in interplanetary dust particles. LIME olivine is not likely to persist in nebular conditions in which silicate liquids are stable

Our Health Counts: Access to Health Risk Factors and Its Relationship to Diabetes in an Urban First Nations Population

This thesis explores the relationship between health access risk factors and diabetes in an urban First Nations population living in Canada. The proportion of Aboriginal peoples in Canada living in urban areas is increasing. Despite this, health data on urban Aboriginal populations in Canada is sparse and often unreliable. The Our Health Counts (OHC) study collected data from a self-identified urban First Nations population living in Hamilton, ON through respondent driven sampling. As statistical techniques for this data are not yet fully developed, advanced logistic regression modeling strategies were used to assess the relationship between health access risk factors and diabetes. Feeling health services were not culturally appropriate was significantly associated with an increased odds for diabetes (12.07, 95% 2.52, 57.91). A strong potential effect between diabetes was also found for the following barriers: not being able to locate a doctor in the area; feeling health care services accessed were inadequate and if health services were not being offered in the area. Furthermore, this study examined the sensitivity of results for various analysis strategies for data that were obtained using respondent driven sampling (RDS). This study could allow for the implementation of more targeted health interventions and the design of health policies that are more specific to target the urban First Nations population in Canada, as well as provide insight into the use of appropriate statistical methods for data collected through respondent driven sampling

Problems involving heat transfer with change of phase

In Part I, two-dimensional laminar film condensation is investigated on the basis of boundary layer theory. The case of flow past a semi-infinite flat plate, which is aligned parallel to a uniform mainstream with velocity Um*(x)=Uo*, is discussed by means of a perturbation analysis for both small and large rates of cooling at the surface. Predictions, for this similar solution of the boundary layer equations, are compared with exact numerical solutions in the case of steam-water condensation. The perturbation analysis is then extended to non-similar flows and results for steam-water condensation are compared with numerical solutions obtained using the Hartree-Womersley method. The cases Um*(x)=Uo* sin(x/z) and Um*(x)=Uo* (1- 1/8 x/c) are used for comparison. The numerical solutions are also studied to discuss separation in these condensation problems.Part II is devoted to the solidification of a cylindrical bar, initially at fusion temperature, when the outer surface temperature is lowered below fusion. The governing equations are solved numerically to obtain accurate results for the solidification process and. in addition a power series in the non-dimensional time is developed. Terms of this series are found both analytically and numerically. Interest surrounds the radius of convergence of such a series because of the similarity between the movements of the solidification front and the growth of the boundary layer for flow through a cylinder

Hypersensitivity Pneumonitis Associated with Environmental Mycobacteria

A previously healthy man working as a machine operator in an automotive factory developed respiratory symptoms. Medical evaluation showed abnormal pulmonary function tests, a lung biopsy showed hypersensitivity pneumonitis, and his illness was traced to his work environment. His physician asked the employer to remove him from exposure to metalworking fluids. Symptoms reoccurred when he was later reexposed to metalworking fluids, and further permanent decrement in his lung function occurred. Investigation of his workplace showed that five of six large reservoirs of metalworking fluids (cutting oils) grew Mycobacterium chelonae (or Mycobacterium immunogenum), an organism previously associated with outbreaks of hypersensitivity pneumonitis in automaking factories. His lung function remained stable after complete removal from exposure. The employer, metalworking fluid supplier, union, and the National Institute for Occupational Safety and Health were notified of this sentinel health event. No further cases have been documented in this workplace

Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline.

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline that identifies specific neuropathologies-amyloid plaques and cerebral amyloid angiopathy-in immunohistochemically-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotate > 70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieve strong plaque classification on a 10-WSI hold-out set (0.993 and 0.743 areas under the receiver operating characteristic and precision recall curve, respectively). Prediction confidence maps visualize morphology distributions at high resolution. Resulting network-derived amyloid beta (Aβ)-burden scores correlate well with established semi-quantitative scores on a 30-WSI blinded hold-out. Finally, saliency mapping demonstrates that networks learn patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologist's ability suggests a route to neuropathologic deep phenotyping