3,846 research outputs found
Re-appraisal of Johnstonotite
Johnstonotite is a mixture of spessartite and
grossularite
A new analysis of Dundasite from Tasmania
Dundasite was first described by W. F. Petterd
in 1893, and an analysis of Tasmanian material was
published in 1910
Petterdite re-analysed
Petterdite is mimetite with about 5%-17% pyromorphit.e in solid solution
The occurrence of rhenium
The element rhenium is known to form only one
extremely rare mineral dzhezkazganite. Much of
the rhenium in nature occurs in small quantities,
usually in the parts per million range substituting
for molybdenum which is a chemically
similar element. An investigation was carried out
to determine the amount of rhenium in some
molybdenites of Tasmanian origin
Immunopathogenesis of canine chronic ulcerative stomatitis.
Canine Chronic Ulcerative Stomatitis is a spontaneously occurring inflammatory disease of the oral mucosa. An immune-mediated pathogenesis is suspected though not yet proven. We have recently reported on the clinical and histologic features, and identification of select leukocyte cell populations within the lesion. A clinical and histologic similarity to oral lichen planus of people was proposed. In the present study, these initial observations are extended by examining lesions from 24 dogs with clinical evidence of chronic ulcerative stomatitis. Because dogs with chronic ulcerative stomatitis often have concurrent periodontal disease, we wondered if dental plaque/biofilm may be a common instigator of inflammation in both lesions. We hypothesized that dogs with chronic ulcerative stomatitis would exhibit a spectrum of pathologic changes and phenotype of infiltrating leukocytes that would inform lesion pathogenesis and that these changes would differ from inflammatory phenotypes in periodontitis. Previously we identified chronic ulcerative stomatitis lesions to be rich in FoxP3+ and IL17+ cells. As such, we suspect that these leukocytes play an important role in lesion pathogenesis. The current study confirms the presence of moderate to large numbers of FoxP3+ T cells and IL17+ cells in all ulcerative stomatitis lesions using confocal immunofluorescence. Interestingly, the majority of IL17+ cells were determined to be non-T cells and IL17+ cell frequencies were negatively correlated with severity on the clinical scoring system. Three histologic subtypes of ulcerative stomatitis were determined; lichenoid, deep stomatitis and granulomatous. Periodontitis lesions, like stomatitis lesions, were B cell and plasma cell rich, but otherwise differed from the stomatitis lesions. Direct immunofluorescence results did not support an autoantibody-mediated autoimmune disease process. This investigation contributes to the body of literature regarding leukocyte involvement in canine idiopathic inflammatory disease pathogenesis
The impact of flooding on road transport: A depth-disruption function
\ua9 2017 Transport networks underpin economic activity by enabling the movement of goods and people. During extreme weather events transport infrastructure can be directly or indirectly damaged, posing a threat to human safety, and causing significant disruption and associated economic and social impacts. Flooding, especially as a result of intense precipitation, is the predominant cause of weather-related disruption to the transport sector. Existing approaches to assess the disruptive impact of flooding on road transport fail to capture the interactions between floodwater and the transport system, typically assuming a road is fully operational or fully blocked, which is not supported by observations. In this paper we develop a relationship between depth of standing water and vehicle speed. The function that describes this relationship has been constructed by fitting a curve to video analysis supplemented by a range of quantitative data that has be extracted from existing studies and other safety literature. The proposed relationship is a good fit to the observed data, with an R-squared of 0.95. The significance of this work is that it is simple to incorporate our function into existing transport models to produce better estimates of flood induced delays and we demonstrate this with an example from the 28th June 2012 flood in Newcastle upon Tyne, UK
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