The most energetic planetary collisions attain shock pressures that result in abundant melting and vaporization. Accurate predictions of the extent of melting and vaporization require knowledge of ...vast regions of the phase diagrams of the constituent materials. To reach the liquid‐vapor phase boundary of silica, we conducted uniaxial shock‐and‐release experiments, where quartz was shocked to a state sufficient to initiate vaporization upon isentropic decompression (hundreds of GPa). The apparent temperature of the decompressing fluid was measured with a streaked optical pyrometer, and the bulk density was inferred by stagnation onto a standard window. To interpret the observed post‐shock temperatures, we developed a model for the apparent temperature of a material isentropically decompressing through the liquid‐vapor coexistence region. Using published thermodynamic data, we revised the liquid‐vapor boundary for silica and calculated the entropy on the quartz Hugoniot. The silica post‐shock temperature measurements, up to entropies beyond the critical point, are in excellent qualitative agreement with the predictions from the decompressing two‐phase mixture model. Shock‐and‐release experiments provide an accurate measurement of the temperature on the phase boundary for entropies below the critical point, with increasing uncertainties near and above the critical point entropy. Our new criteria for shock‐induced vaporization of quartz are much lower than previous estimates, primarily because of the revised entropy on the Hugoniot. As the thermodynamics of other silicates are expected to be similar to quartz, vaporization is a significant process during high‐velocity planetary collisions.
Key Points
We measured the temperature on the liquid‐vapor curve of silica
We calculated the entropy on the quartz Hugoniot
We provide new criteria for shock‐induced vaporization of silica
The present review was aimed to determine the influence of working conditions, occupational exposures to potential chemical and physical reproductive toxic agents and psychological stress during work ...on male fertility. Significant associations were reported between impaired semen parameters and the following chemical exposures: metals (lead, mercury), pesticides (dibromochlorophane, 2, 4-dichlorophenoxyacetic acid), ethylene glycol ethers and estrogens. The following physical exposures were shown to deteriorate sperm parameters: radiation (both ionized and microwaves) and heat. Psychological distress has another important contribution to infertility. Several studies indicated that stress has a negative impact on sperm parameters. Occupational parameters should be an important part of history taking among patients attending infertility clinics.
Recent discussions of the 'geography of gentrification' highlight the need for comparative analysis of the nature and consequences of inner-city transformation. In this paper, the authors map the ...effects of housing-market and policy changes in the 1990s, focusing on 23 large cities in the USA. Using evidence from field surveys and a mortgage-lending database, they measure the class selectivity of gentrification and its relation to processes of racial and ethnic discrimination. They find a strong resurgence of capital investment in the urban core, along with magnified class segregation. The boom of the 1990s and policies targeted towards 'new markets' narrowed certain types of racial and ethnic disparities in urban credit markets, but there is evidence of intensified discrimination and exclusion in gentrified neighborhoods.
Pancreas size is smaller at the onset of T1D and in individuals at risk for T1D, as measured by MRI. To determine whether pancreas volume predicts T1D progression, we measured pancreas size and ...dynamics in Type 1 Diabetes TrialNet Pathway to Prevention study participants with Stage 1 T1D, as defined by the presence of two or more autoantibodies and normal glucose tolerance. Individuals with Stage 1 T1D (n = 25, median age = 13.9 y.o.) exhibited a smaller pancreas volume than controls without T1D (n = 34, median age = 15.2 y.o, p < 0.001), but larger than individuals with Stage 3 T1D (n = 67, median age = 13.4 y.o, p < 0.05). This intermediate pancreas size in individuals with Stage 1 T1D persisted when pancreas volume was normalized by either body weight (pancreas volume index) or BMI. There was no correlation between the number or specificity of autoantibodies expressed and the pancreas volume index. Using longitudinal pancreas MRI in 25 autoantibody-positive individuals (total of 80 MRIs), we found that pancreas volume was stable over time, with no increase or decrease up to three years after the initial MRI (95% CI of slope: -0.094 to 0.5788 ml/month). Two of the 25 autoantibody-positive participants who developed Stage 3 T1D during follow up had the smallest pancreas volume index at study entry (0.43 +/- 0.04 ml/kg, p < 0.005 compared with those who did not progress to Stage 3). An additional 11 of the 25 participants developed impaired glucose tolerance during follow up. Initial pancreas volume index in the 13 total participants who developed Stage 2 or Stage 3 T1D (0.75 +/- 0.06 ml/kg) was significantly smaller (p < 0.05) than the 12 participants who retained normal glucose tolerance over the course of the study (0.95 +/- 0.05 ml/kg). These data suggest that small pancreas size may be predictive of progression of T1D.
Disclosure
J. Virostko: None. J.M. Williams: None. M.A. Hilmes: None. J.J. Wright: None. B.D. Hammel: None. L. Du: None. H. Kang: None. W.E. Russell: None. A.C. Powers: None. D.J. Moore: None.
Funding
JDRF (3-SRA-2019-759-M-B, 3-SRA-2015-102-M-B)
The debate between the proponents of the rent gap hypothesis and Steven Bourassa concerning its internal consistency centres on the role of land use in capitalised land rent. Bourassa argues that ...capitalised land rent is nonsensical because it is determined in part by land use which is in conflict with land rent theory. The paper explores the determinants of capitalised land rent by reviewing the rent gap hypothesis and related research, and argues that the issue of scale is implicit in the rent gap. Land rent can be determined at a minimum of two scales resulting in at least two different land rents. This argument rectifies Bourassa's contentions, and is consistent with the theoretical foundations of the rent gap.
Even today, infective endocarditis (IE) remains a severe and potentially fatal disease demanding sophisticated diagnostic strategies for detection of the causative microorganisms. Despite the use of ...appropriate laboratory techniques, classic microbiological diagnostics are characterized by a high rate of negative results.
Broad-range polymerase chain reaction (PCR) targeting bacterial and fungal rDNA followed by direct sequencing was applied to excised heart valves (n=52) collected from 51 patients with suspected infectious endocarditis and from 16 patients without any signs of IE during an 18-month period. The sensitivity, specificity, and the positive and negative predictive values for the bacterial broad-range PCR were 41.2%, 100.0%, 100.0%, and 34.8%, respectively, compared with 7.8%, 93.7%, 80.0%, and 24.2% for culture and 11.8%, 100.0%, 100.0%, and 26.2% for Gram staining. Without exception, database analyses allowed identification up to the (sub)species level comprising streptococcal (n=13), staphylococcal (n=4), enterococcal (n=2), and other signature sequences such as Bartonella quintana and Nocardia paucivorans. Fungal ribosomal sequences were not amplified. All valve tissues of the reference group were negative for both PCR and conventional methods, except one sample that was contaminated by molds.
Culture-independent molecular methods substantially improve the diagnostic outcome of microbiological examination of excised heart valves. Importantly, this was true not only for fastidious, slow-growing, and/or nonculturable microorganisms but also for easy-to-culture pathogens such as streptococci and staphylococci. Both patient management and empiric antibiotic therapy of IE are likely to benefit from improved knowledge of the spectrum of pathogens now causing IE.
Experiments on the National Ignition Facility (NIF) have provided clear evidence of ablator material mixing into the Hot-Spot, leading to degraded performance. However, inferring the amount of mix ...and Hot-Spot conditions from typical experimental observations (e.g. x-ray spectra and images) is highly challenging. We have developed an analysis method that utilizes machine learning assisted Bayesian inference to find the probability distributions of the Hot-Spot and mix conditions. This approach uses a neural network, trained on an idealized 2-dimensional representation of the Hot-Spot and mix distribution, and Bayesian inference to find the statistical distributions of Hot-Spot conditions that provide a match with observations. We have tested this method with synthetic data from simulations.
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