center density
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2021 ◽  
Author(s):  
Nathan Brown ◽  
Edward Rhodes

Luminescence thermochronology and thermometry can quantify recent changes in rock exhumation rates and rock surface temperatures, but these methods require accurate determination of several kinetic parameters. For K-feldspar thermoluminescence (TL) glow curves, which comprise overlapping signals of different thermal stability, it is challenging to develop measurements that capture these parameter values. Here, we present multiple-aliquot additive-dose (MAAD) TL dose response and fading measurements from bedrock-extracted K-feldspars. These measurements are compared with Monte Carlo simulations to identify best-fit values for recombination center density ($\rho$) and activation energy ($\Delta E$). This is done for each dataset separately, and then by combining dose-response and fading misfits to yield more precise $\rho$ and $\Delta E$ values consistent with both experiments. Finally, these values are used to estimate the characteristic dose ($D_0$) of samples. This approach produces kinetic parameter values consistent with comparable studies and results in expected fractional saturation differences between samples.


2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Yan Xu ◽  
Wen Bo Ding ◽  
Cheng Zhi Liu ◽  
J. L. Han

Nucleonic direct Urca processes and cooling of the massive neutron stars are studied by considering antikaon condensations. Calculations are performed in the relativistic mean field and isothermal interior approximations. Neutrino energy losses of the nucleonic direct Urca processes are reduced when the optical potential of antikaons changes from − 80 to − 130  MeV. If the center density of the massive neutron stars is a constant, the masses taper off with the optical potential of antikaons, and neutrino luminosities of the nucleonic direct Urca processes decrease for ρ CN = 0.5   fm − 3 but first increase and then decrease for larger ρ CN . Large optical potential of antikaons results in warming of the nonsuperfluid massive neutron stars. Massive neutron stars turn warmer with the protonic S 0 1 superfluids. However, the decline of the critical temperatures of the protonic S 0 1 superfluids for the large optical potential of antikaons can speed up the cooling of the massive neutron stars.


2020 ◽  
Vol 5 (1) ◽  
pp. e000562
Author(s):  
Anne M Stey ◽  
Alexandria Byskosh ◽  
Caryn Etkin ◽  
Robert Mackersie ◽  
Deborah M Stein ◽  
...  

BackgroundThere has been a proliferation of urban high-level trauma centers. The aim of this study was to describe the density of high-level adult trauma centers in the 15 largest cities in the USA and determine whether density was correlated with urban social determinants of health and violence rates.MethodsThe largest 15 US cities by population were identified. The American College of Surgeons’ (ACS) and states’ department of health websites were cross-referenced for designated high-level (levels 1 and 2) trauma centers in each city. Trauma centers and associated 20 min drive radius were mapped. High-level trauma centers per square mile and per population were calculated. The distance between high-level trauma centers was calculated. Publicly reported social determinants of health and violence data were tested for correlation with trauma center density.ResultsAmong the 15 largest cities, 14 cities had multiple high-level adult trauma centers. There was a median of one high-level trauma center per every 150 square kilometers with a range of one center per every 39 square kilometers in Philadelphia to one center per596 square kilometers in San Antonio. There was a median of one high-level trauma center per 285 034 people with a range of one center per 175 058 people in Columbus to one center per 870 044 people in San Francisco. The median minimum distance between high-level trauma centers in the 14 cities with multiple centers was 8 kilometers and ranged from 1 kilometer in Houston to 43 kilometers in San Antonio. Social determinants of health, specifically poverty rate and unemployment rate, were highly correlated with violence rates. However, there was no correlation between trauma center density and social determinants of health or violence rates.DiscussionHigh-level trauma centers density is not correlated with social determinants of health or violence rates.Level of evidenceVI.Study typeEconomic/decision.


2020 ◽  
Vol 64 (5/6) ◽  
pp. 16:1-16:10
Author(s):  
W. P. Kostenko ◽  
J. G. Torok ◽  
D. W. Demetriou

2020 ◽  
Vol 27 (7) ◽  
pp. 073507
Author(s):  
Deuk-Chul Kwon ◽  
Dong-Hun Yu ◽  
Hyoungcheol Kwon ◽  
Yeon Ho Im ◽  
Hyo-Chang Lee

2020 ◽  
Vol 21 (1) ◽  
pp. 57
Author(s):  
Antonio A. Andrade ◽  
Agnaldo J. Ferrari ◽  
José C. Interlando ◽  
Robson R. Araujo

In this work, we present constructions of algebraic lattices in Euclidean space with optimal center density in dimensions 2,3,4,5,6,8 and 12, which are rotated versions of the lattices Lambda_n, for n =2,3,4,5,6,8 and K_12. These algebraic lattices are constructed through canonical homomorphism via Z-modules of the ring of algebraic integers of a number field.


2020 ◽  
Vol 32 (17) ◽  
pp. 13465-13478 ◽  
Author(s):  
Yizhang Wang ◽  
Di Wang ◽  
Xiaofeng Zhang ◽  
Wei Pang ◽  
Chunyan Miao ◽  
...  

2019 ◽  
Vol 19 (04) ◽  
pp. 2050080
Author(s):  
Robson R. Araujo ◽  
Ana C. M. M. Chagas ◽  
Antonio A. Andrade ◽  
Trajano P. Nóbrega Neto

In this work, we computate the trace form [Formula: see text] associated to a cyclic number field [Formula: see text] of odd prime degree [Formula: see text], where [Formula: see text] ramified in [Formula: see text] and [Formula: see text] belongs to the ring of integers of [Formula: see text]. Furthermore, we use this trace form to calculate the expression of the center density of algebraic lattices constructed via the Minkowski embedding from some ideals in the ring of integers of [Formula: see text].


2019 ◽  
Vol 240 ◽  
pp. 233-237
Author(s):  
Zongchen Liu ◽  
Jiao Fu ◽  
Zhangcheng Liu ◽  
Yanfeng Wang ◽  
Shuwei Fan ◽  
...  

2019 ◽  
Vol 9 (13) ◽  
pp. 1802856 ◽  
Author(s):  
Yijie Deng ◽  
Bin Chi ◽  
Jing Li ◽  
Guanghua Wang ◽  
Long Zheng ◽  
...  

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