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Estimation of surface longwave radiation components from ground-based historical net radiation and weather data
A methodology for estimating ground upwelling, clear-sky and cloud downwelling longwave radiations (L↑, Lsky ↓, and Lcld↓) and net shortwave radiation (Sn) at 30-min temporal scales based on long-term ground-based net radiations and meteorological observations is described. Components of surface radiation can be estimated from empirical models, cloud radiation models, and remote sensing observations. The proposed method combines the local calibration of empirical models and the radiative energy balance method to obtain the dual-directional, dual-spectral components of the surface radiation for the offline land surface process modeling and ecosystem study. By extracting information of radiation components from long-term net radiation and concurrent weather data, the utility of tower net radiation observations is maximized. Four test sites with multiyears' radiation records were used to evaluate the method. The results show that when compared with the results of empirical models using default parameters the proposed method is able to produce more accurate estimates of longwave surface components (Lg ↑, Lsky↓, Lcld↓) and net shortwave radiation (Sn). Overall, the estimated and observed surface radiation components show high correlations (>0.90), high index of agreement (>0.89), and low errors (root mean square error <30 W m-2 and bias <11 W m-2) at all of the test sites. The advantage of this scheme is that the refinement is achieved using the information from the historical net radiation and weather data at each observation site without additional measurements. This method is applicable for many existing observation sites worldwide which have long-term (at least 1 year) continuous net radiation records. Copyright 2008 by the American Geophysical Union
The abnormal electrical and optical properties in Na and Ni codoped BiFeO3 nanoparticles
published_or_final_versio
Abnormal variation of band gap in Zn doped Bi0.9La0.1FeO3 nanoparticles: Role of Fe-O-Fe bond angle and Fe-O bond anisotropy
published_or_final_versio
Star Formation Rate Indicators in Wide-Field Infrared Survey Preliminary Release
With the goal of investigating the degree to which theMIR luminosity in
theWidefield Infrared Survey Explorer (WISE) traces the SFR, we analyze 3.4,
4.6, 12 and 22 {\mu}m data in a sample of {\guillemotright} 140,000
star-forming galaxies or star-forming regions covering a wide range in
metallicity 7.66 < 12 + log(O/H) < 9.46, with redshift z < 0.4. These
star-forming galaxies or star-forming regions are selected by matching the WISE
Preliminary Release Catalog with the star-forming galaxy Catalog in SDSS DR8
provided by JHU/MPA 1.We study the relationship between the luminosity at 3.4,
4.6, 12 and 22 {\mu}m from WISE and H\alpha luminosity in SDSS DR8. From these
comparisons, we derive reference SFR indicators for use in our analysis. Linear
correlations between SFR and the 3.4, 4.6, 12 and 22 {\mu}m luminosity are
found, and calibrations of SFRs based on L(3.4), L(4.6), L(12) and L(22) are
proposed. The calibrations hold for galaxies with verified spectral
observations. The dispersion in the relation between 3.4, 4.6, 12 and 22 {\mu}m
luminosity and SFR relates to the galaxy's properties, such as 4000 {\deg}A
break and galaxy color.Comment: 10 pages, 3 figure
Health-related quality of life as measured with EQ-5D among populations with and without specific chronic conditions: A population-based survey in Shaanxi province, China
© 2013 Tan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Introduction: The aim of this study was to examine health-related quality of life (HRQoL) as measured by EQ-5D and to investigate the influence of chronic conditions and other risk factors on HRQoL based on a distributed sample located in Shaanxi Province, China. Methods: A multi-stage stratified cluster sampling method was performed to select subjects. EQ-5D was employed to measure the HRQoL. The likelihood that individuals with selected chronic diseases would report any problem in the EQ-5D dimensions was calculated and tested relative to that of each of the two reference groups. Multivariable linear regression models were used to investigate factors associated with EQ VAS. Results: The most frequently reported problems involved pain/discomfort (8.8%) and anxiety/depression (7.6%). Nearly half of the respondents who reported problems in any of the five dimensions were chronic patients. Higher EQ VAS scores were associated with the male gender, higher level of education, employment, younger age, an urban area of residence, access to free medical service and higher levels of physical activity. Except for anemia, all the selected chronic diseases were indicative of a negative EQ VAS score. The three leading risk factors were cerebrovascular disease, cancer and mental disease. Increases in age, number of chronic conditions and frequency of physical activity were found to have a gradient effect. Conclusion: The results of the present work add to the volume of knowledge regarding population health status in this area, apart from the known health status using mortality and morbidity data. Medical, policy, social and individual attention should be given to the management of chronic diseases and improvement of HRQoL. Longitudinal studies must be performed to monitor changes in HRQoL and to permit evaluation of the outcomes of chronic disease intervention programs. © 2013 Tan et al.National Nature Science Foundation (No. 8107239
Development of integrated approaches for hydrological data assimilation through combination of ensemble Kalman filter and particle filter methods
Natural Science Foundation of China; National Key Research and Development Plan; Natural Sciences and Engineering Research Council of Canada
Numerical simulation of blood flow and pressure drop in the pulmonary arterial and venous circulation
A novel multiscale mathematical and computational model of the pulmonary circulation is presented and used to analyse both arterial and venous pressure and flow. This work is a major advance over previous studies by Olufsen et al. (Ann Biomed Eng 28:1281–1299, 2012) which only considered the arterial circulation. For the first three generations of vessels within the pulmonary circulation, geometry is specified from patient-specific measurements obtained using magnetic resonance imaging (MRI). Blood flow and pressure in the larger arteries and veins are predicted using a nonlinear, cross-sectional-area-averaged system of equations for a Newtonian fluid in an elastic tube. Inflow into the main pulmonary artery is obtained from MRI measurements, while pressure entering the left atrium from the main pulmonary vein is kept constant at the normal mean value of 2 mmHg. Each terminal vessel in the network of ‘large’ arteries is connected to its corresponding terminal vein via a network of vessels representing the vascular bed of smaller arteries and veins. We develop and implement an algorithm to calculate the admittance of each vascular bed, using bifurcating structured trees and recursion. The structured-tree models take into account the geometry and material properties of the ‘smaller’ arteries and veins of radii ≥ 50 μ m. We study the effects on flow and pressure associated with three classes of pulmonary hypertension expressed via stiffening of larger and smaller vessels, and vascular rarefaction. The results of simulating these pathological conditions are in agreement with clinical observations, showing that the model has potential for assisting with diagnosis and treatment for circulatory diseases within the lung
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