Application of fluid inclusion and rock-gas analysis in mineral exploration

Gases are known to form haloes around presently active geothermal systems and might be useful in exploration for older, extinct hydrothermal systems. Gases from such extinct hydrothermal systems can be liberated for analysis from fluid inclusions in hydrothermal minerals by thermal decrepitation or they can be desorbed from alteration mineral surfaces by heating. The most abundant of these gases, besides H2O, are usually CO2, CH4, CO and N2. We have used a gas chromatograph to analyze these gases in fluid inclusions in jasperoid around the Pueblo Viejo gold-silver deposit, in vein minerals from the Creede silver-lead-zinc deposit, and from clays in the alteration cap overlying veins at Creede to test for gas haloes useful in exploration. At Pueblo Viejo CO2 abundances in the jasperoid range from less than 1 mole percent (with respect to the system CH4-CO2-CO-N2-H2O) in the ore zone to as much as 6 mole percent in surrounding, barren jasperoid. Fluid inclusion analyses at Creede suggest that a drop in the CO2 content of the fluid may relate to ore deposition and clay directly above veins has large amounts of adsorbed CO2. These results suggest that primary gas abundances exhibit patterns in and around hydrothermal ore deposits that can be used in mineral exploration.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26245/1/0000325.pd

Automated, high-accuracy classification of textured microstructures using a convolutional neural network

Crystallographic texture is an important descriptor of material properties but requires time-intensive electron backscatter diffraction (EBSD) for identifying grain orientations. While some metrics such as grain size or grain aspect ratio can distinguish textured microstructures from untextured microstructures after significant grain growth, such morphological differences are not always visually observable. This paper explores the use of deep learning to classify experimentally measured textured microstructures without knowledge of crystallographic orientation. A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional neural network results are compared with a statistical Kolmogorov–Smirnov tests with traditional morphological metrics for describing microstructures. Results show that the convolutional neural network achieves a significantly improved classification accuracy, particularly at early stages of grain growth, highlighting the capability of deep learning to identify the subtle morphological patterns resulting from texture. The results demonstrate the potential of a convolutional neural network as a tool for reliable and automated microstructure classification with minimal preprocessing

Thymic Carcinomas and Second Malignancies: A Single-Center Review

Thymic carcinomas account for less than 0.01% of new cancer diagnoses annually and are more aggressive than thymomas. Autoimmune disorders have been associated with thymomas and only recently with thymic carcinomas. Second malignancies are well described after thymomas. The aim of this study was to analyze the incidence of second malignancies in patients with thymic carcinomas. All cases of thymic carcinomas were identified from the pathology archives of Indiana University. Histological materials were reviewed and further correlated with clinical data to identify incidence of second cancers in patients with thymic carcinomas. Histological material was available for review in 92 cases of thymic carcinoma. Clinical data were available for 85 patients. Fourteen of these (16.5%) patients had a second malignancy; these included small cell lung carcinoma, "testicular cancer", embryonal carcinoma, seminoma, breast carcinoma (two cases), prostatic adenocarcinoma, Hodgkin's lymphoma, thyroid carcinoma, bladder carcinoma (two cases), renal cell carcinoma, and melanoma. The latter could precede, be concurrent with, or follow the diagnosis thymic carcinoma. The incidence of second cancers in patients with thymic carcinomas is similar to that reported for thymomas. Abnormalities in immunological surveillance may be responsible for this high incidence of second malignancies in thymic tumors

Ageless Aluminum-Cerium-Based Alloys in High-Volume Die Casting for Improved Energy Efficiency

Strong chemical reactions between Al and Ce lead to the formation of intermetallics with exceptional thermal stability. The rapid formation of intermetallics directly from the liquid phase during solidification of Al-Ce alloys leads to an ultrafine microconstituent structure that effectively strengthens as-cast alloys without further microstructural optimization via thermal processing. Die casting is a high-volume manufacturing technology that accounts for greater than 40% of all cast Al products, whereas Ce is highly overproduced as a waste product of other rare earth element (REE) mining. Reducing heat treatments would stimulate significant improvements in manufacturing energy efficiency, exceeding (megatonnes/year) per large-scale heat-treatment line. In this study, multiple compositions were evaluated with wedge mold castings to test the sensitivity of alloys to the variable solidification rate inherent in high-pressure die casting. Once a suitable composition was determined, it was successfully demonstrated at 800 lbs/h in a 600-ton die caster, after which the as-die cast parts performed similarly to ubiquitous A380 in the same geometry without requiring heat treatment. This work demonstrates the compatibility of Al REE alloys with high-volume die-casting applications with minimal heat treatments

Contributions of high- and low-quality patches to a metapopulation with stochastic disturbance

© The Author(s), 2010. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Theoretical Ecology 5 (2012): 167-179, doi:10.1007/s12080-010-0106-9.Studies of time-invariant matrix metapopulation models indicate that metapopulation growth rate is usually more sensitive to the vital rates of individuals in high-quality (i.e., good) patches than in low-quality (i.e., bad) patches. This suggests that, given a choice, management efforts should focus on good rather than bad patches. Here, we examine the sensitivity of metapopulation growth rate for a two-patch matrix metapopulation model with and without stochastic disturbance and found cases where managers can more efficiently increase metapopulation growth rate by focusing efforts on the bad patch. In our model, net reproductive rate differs between the two patches so that in the absence of dispersal, one patch is high quality and the other low quality. Disturbance, when present, reduces net reproductive rate with equal frequency and intensity in both patches. The stochastic disturbance model gives qualitatively similar results to the deterministic model. In most cases, metapopulation growth rate was elastic to changes in net reproductive rate of individuals in the good patch than the bad patch. However, when the majority of individuals are located in the bad patch, metapopulation growth rate can be most elastic to net reproductive rate in the bad patch. We expand the model to include two stages and parameterize the patches using data for the softshell clam, Mya arenaria. With a two-stage demographic model, the elasticities of metapopulation growth rate to parameters in the bad patch increase, while elasticities to the same parameters in the good patch decrease. Metapopulation growth rate is most elastic to adult survival in the population of the good patch for all scenarios we examine. If the majority of the metapopulation is located in the bad patch, the elasticity to parameters of that population increase but do not surpass elasticity to parameters in the good patch. This model can be expanded to include additional patches, multiple stages, stochastic dispersal, and complex demography.Financial support was provided by the Woods Hole Oceanographic Institution Academic Programs Office; National Science Foundation grants OCE-0326734, OCE- 0215905, OCE-0349177, DEB-0235692, DEB-0816514, DMS- 0532378, OCE-1031256, and ATM-0428122; and by National Oceanic and Atmospheric Administration National Sea Grant College Program Office, Department of Commerce, under Grant No. NA86RG0075 (Woods Hole Oceanographic Institution Sea Grant Project No. R/0-32), and Grant No. NA16RG2273 (Woods Hole Oceanographic Institution Sea Grant Project No. R/0-35)

Year in review in Intensive Care Medicine 2009: II. Neurology, cardiovascular, experimental, pharmacology and sedation, communication and teaching

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