First-principles calculation of field emission from metal surfaces

The field-emission current from realistic metal surfaces is evaluated within the density-functional theory using the Landauer-Buttiker approach. The electronic density in the surface region and the potential barrier induced by the finite electric field are calculated self-consistently using a Green's-function embedding scheme and the full-potential linearized-augmented plane-wave method. Application of this formalism to the (100) and (111) faces of Au and Cu demonstrates the sensitivity of the field-emission current to the surface electronic structure close to the Fermi energy

Soil Carbon Turnover and Changes in Soil Nitrogen under the Agropastoral System in Brazilian Savannas (Cerrados).

Na publicação - Cesar Miranda (National Beef Cattle Research Center, Brazilian Agricultural Research Corporation, Mato Grosso do Sul State, Brazil)

Using Administrative Data to Count and Classify Households with Local Applications

Households rather than individuals are being increasingly used for research and to target and evaluate public policy. As a result accurate and timely household level statistics have become an increasing necessity especially at local level. However, official sources of information on households are fragmented with significant gaps and inaccuracies that limit their usefulness. This paper reviews present statistical arrangements and then describes a new approach to data collection and household classification which combine various local administrative sources. An intermediate step is the creation of local population counts which are converted into household types and these methods are described in two companion papers previously published in this journal. The utility and advantages of the approach are demonstrated using the example of the six Olympic London Boroughs for whom the data collection was undertaken in 2011 and the analysis subsequently

Structural analysis of the factors pertaining to attitudes toward and consciousness of organ donation : Comparison between Japanese and Americans

The purpose of this study is to analyze the background factors relating to opinions on organ donation through factorial and structural comparisons between Japanese and Americans. The data were obtained from responses to a questionnaire (371 Japanese and 41 Americans). The main findings are as follows: 1. Most of the factors, ‘a will for organ donation depending on a recipient’, ‘view of remains’, ‘understanding of brain death’ and so on showed significant differences between Japanese and Americans. 2. Japanese had a better understanding of brain death. On the other hand, the ratio of Americans who were willing to donate an organ was higher than that of Japanese. 3. It was revealed that “the approval of organ donation for the third person, not only for one's family” had an impact for having donor card showing the approval for organ donation. Furthermore, as underlying factors generating differences on organ transplant opinions, differences were found among Japanese between “approval of organ transplant” and the attitude assuming that oneself or a member of one's family was the person concerned with organ transplantation. There were also differences between Japanese and Americans on ideas about a view for life and death such as soul existence or view of remains. The argument for transplantation in Japan should consider these structural differences

Resolution-of-identity approach to Hartree-Fock, hybrid density functionals, RPA, MP2, and \textit{GW} with numeric atom-centered orbital basis functions

Efficient implementations of electronic structure methods are essential for first-principles modeling of molecules and solids. We here present a particularly efficient common framework for methods beyond semilocal density-functional theory, including Hartree-Fock (HF), hybrid density functionals, random-phase approximation (RPA), second-order M{\o}ller-Plesset perturbation theory (MP2), and the $GW$ method. This computational framework allows us to use compact and accurate numeric atom-centered orbitals (popular in many implementations of semilocal density-functional theory) as basis functions. The essence of our framework is to employ the "resolution of identity (RI)" technique to facilitate the treatment of both the two-electron Coulomb repulsion integrals (required in all these approaches) as well as the linear density-response function (required for RPA and $GW$). This is possible because these quantities can be expressed in terms of products of single-particle basis functions, which can in turn be expanded in a set of auxiliary basis functions (ABFs). The construction of ABFs lies at the heart of the RI technique, and here we propose a simple prescription for constructing the ABFs which can be applied regardless of whether the underlying radial functions have a specific analytical shape (e.g., Gaussian) or are numerically tabulated. We demonstrate the accuracy of our RI implementation for Gaussian and NAO basis functions, as well as the convergence behavior of our NAO basis sets for the above-mentioned methods. Benchmark results are presented for the ionization energies of 50 selected atoms and molecules from the G2 ion test set as obtained with $GW$ and MP2 self-energy methods, and the G2-I atomization energies as well as the S22 molecular interaction energies as obtained with the RPA method.Comment: 58 pages, 15 figures, and 7 table

Predictors of Long-Term Care Utilization by Dutch Hospital Patients aged 65+

Background Long-term care is often associated with high health care expenditures. In the Netherlands, an ageing population will likely increase the demand for long-term care within the near future. The development of risk profiles will not only be useful for projecting future demand, but also for providing clues that may prevent or delay long-term care utilization. Here, we report our identification of predictors of long-term care utilization in a cohort of hospital patients aged 65+ following their discharge from hospital discharge and who, prior to hospital admission, were living at home. Methods The data were obtained from three national databases in the Netherlands: the national hospital discharge register, the long-term care expenses register and the population register. Multinomial logistic regression was applied to determine which variables were the best predictors of long-term care utilization. The model included demographic characteristics and several medical diagnoses. The outcome variables were discharge to home with no formal care (reference category), discharge to home with home care, admission to a nursing home and admission to a home for the elderly. Results The study cohort consisted of 262,439 hospitalized patients. A higher age, longer stay in the hospital and absence of

The Persisting Burden of Intracerebral Haemorrhage: Can Effective Treatments Be Found?

Colin Josephson, Rustam Al-Shahi Salman, and colleagues discuss the effectiveness of treatments for intracerebral haemorrhage

A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay

<p>Abstract</p> <p>Background</p> <p>Patients with a prolonged intensive care unit (ICU) length of stay account for a disproportionate amount of resource use. Early identification of patients at risk for a prolonged length of stay can lead to quality enhancements that reduce ICU stay. This study developed and validated a model that identifies patients at risk for a prolonged ICU stay.</p> <p>Methods</p> <p>We performed a retrospective cohort study of 343,555 admissions to 83 ICUs in 31 U.S. hospitals from 2002-2007. We examined the distribution of ICU length of stay to identify a threshold where clinicians might be concerned about a prolonged stay; this resulted in choosing a 5-day cut-point. From patients remaining in the ICU on day 5 we developed a multivariable regression model that predicted remaining ICU stay. Predictor variables included information gathered at admission, day 1, and ICU day 5. Data from 12,640 admissions during 2002-2005 were used to develop the model, and the remaining 12,904 admissions to internally validate the model. Finally, we used data on 11,903 admissions during 2006-2007 to externally validate the model.</p> <p>Results</p> <p>The variables that had the greatest impact on remaining ICU length of stay were those measured on day 5, not at admission or during day 1. Mechanical ventilation, PaO₂: FiO₂ratio, other physiologic components, and sedation on day 5 accounted for 81.6% of the variation in predicted remaining ICU stay. In the external validation set observed ICU stay was 11.99 days and predicted total ICU stay (5 days + day 5 predicted remaining stay) was 11.62 days, a difference of 8.7 hours. For the same patients, the difference between mean observed and mean predicted ICU stay using the APACHE day 1 model was 149.3 hours. The new model's r²was 20.2% across individuals and 44.3% across units.</p> <p>Conclusions</p> <p>A model that uses patient data from ICU days 1 and 5 accurately predicts a prolonged ICU stay. These predictions are more accurate than those based on ICU day 1 data alone. The model can be used to benchmark ICU performance and to alert physicians to explore care alternatives aimed at reducing ICU stay.</p