The coupling constant averaged exchange–correlation energy density

The exchange–correlation energy, central to density-functional theory, may be represented in terms of the coupling constant averaged (CCA) exchange–correlation energy density. We present an approach to calculate the CCA energy density using accurate ab initio methods and its application to simple atomic systems. This function provides a link between intrinsically non-local, many-body electronic structure methods and simple local and semi-local density-functional approximations (DFAs). The CCA energy density is resolved into separate exchange and correlation terms and the features of each compared with those of quantities commonly used to construct DFAs. In particular, the more complex structure of the correlation energy density is found to exhibit features that align well with those present in the Laplacian of the density, suggesting its role as a key variable to be used in the construction of improved semi-local correlation functionals. The accurate results presented in this work are also compared with those provided by the Laplacian-dependent Becke–Roussel model for the exchange energy

Validation of the Italian version of the Patient Reported Experience Measures for intermediate care services

Background: Intermediate care (IC) services are a key component of integrated care for elderly people, providing a link between hospital and home through provision of rehabilitation and health and social care. The Patient Reported Experience Measures (PREMs) are designed to measure user experience of care in IC settings. Objective: To examine the feasibility and the scaling properties of the Italian version of PREMs questionnaires for use in IC services. Methods: A cross-sectional survey was conducted on consecutive users of 1 home-based and 4 bed-based IC services in Emilia-Romagna (Italy). The main outcome measure was the PREMs questionnaire results. PREMs for each home- and bed-based IC services were translated, back-translated, and adapted through consensus among the members of the advisory board and pilot testing of face validity in 15 patients. A total of 199 questionnaires were returned from users of bed-based services and 185 were returned by mail from users of home-based services. The return rates and responses were examined. Mokken analysis was used to examine the scaling properties of the PREMs. Results: Analysis performed on the bed-based PREMs (N=154) revealed that 13 items measured the same construct and formed a moderate-strength scale (Loevinger H=0.488) with good reliability (Cronbach’s alpha =0.843). Analysis of home-based PREMs (N=134 records) revealed that 15 items constituted a strong scale (Loevinger H=0.543) with good reliability (Cronbach’s alpha =0.875). Conclusion: The Italian versions of the bed- and home-based IC-PREMs questionnaires proved to be valid and reliable tools to assess patients’ experience of care. Future plans include monitoring user experience over time in the same facilities and in other Italian IC settings for between-service benchmarking

Exchange-correlation functionals via local interpolation along the adiabatic connection

The construction of density-functional approximations is explored by modeling the adiabatic connection locally, using energy densities defined in terms of the electrostatic potential of the exchange−correlation hole. These local models are more amenable to the construction of size-consistent approximations than their global counterparts. In this work we use accurate input local ingredients to assess the accuracy of a range of local interpolation models against accurate exchange−correlation energy densities. The importance of the strictly correlated electrons (SCE) functional describing the strong coupling limit is emphasized, enabling the corresponding interpolated functionals to treat strong correlation effects. In addition to exploring the performance of such models numerically for the helium and beryllium isoelectronic series and the dissociation of the hydrogen molecule, an approximate analytic model is presented for the initial slope of the local adiabatic connection. Comparisons are made with approaches based on global models, and prospects for future approximations based on the local adiabatic connection are discussed

Factors affecting dairy farmers' attitudes towards antimicrobial medicine usage in cattle in England and Wales

There has been growing concern about bacterial resistance to antimicrobials in the farmed livestock sector. Attention has turned to sub-optimal use of antimicrobials as a driver of resistance. Recent reviews have identified a lack of data on the pattern of antimicrobial use as an impediment to the design of measures to tackle this growing problem. This paper reports on a study that explored use of antibiotics by dairy farmers and factors influencing their decision-making around this usage. We found that respondents had either recently reduced their use of antibiotics, or planned to do so. Advice from their veterinarian was instrumental in this. Over 70% thought reducing antibiotic usage would be a good thing to do. The most influential source of information used was their own veterinarian. Some 50% were unaware of the available guidelines on use in cattle production. However, 97% thought it important to keep treatment records. The Theory of Planned Behaviour was used to identify dairy farmers’ drivers and barriers to reduce use of antibiotics. Intention to reduce usage was weakly correlated with current and past practice of antibiotic use, whilst the strongest driver was respondents’ belief that their social and advisory network would approve of them doing this. The higher the proportion of income from milk production and the greater the chance of remaining in milk production, the significantly higher the likelihood of farmers exhibiting positive intention to reduce antibiotic usage. Such farmers may be more commercially minded than others and thus more cost-conscious or, perhaps, more aware of possible future restrictions. Strong correlation was found between farmers’ perception of their social referents’ beliefs and farmers’ intent to reduce antibiotic use. Policy makers should target these social referents, especially veterinarians, with information on the benefits from, and the means to, achieving reductions in antibiotic usage. Information on sub-optimal use of antibiotics as a driver of resistance in dairy herds and in humans along with advice on best farm practice to minimise risk of disease and ensure animal welfare, complemented with data on potential cost savings from reduced antibiotic use would help improve poor practice

Young children's cognitive achievement: home learning environment, language and ethnic background

For decades, research has shown differences in cognitive assessment scores between White and minority ethnic group(s) learners as well as differences across different minority ethnic groups. More recent data have indicated that the home learning environment and languages spoken can impact cognitive assessment and other corollary outcomes. This study uses the Millennium Cohort Study to jointly assess how minority ethnic group, home learning environment and home languages predict child cognitive assessment scores. Regression analyses were conducted using two assessment measures. The following is hypothesised: (1) cognitive achievement scores vary by minority ethnic group, (2) more home learning environment in early childhood leads to higher cognitive development scores and (3) English only in the home yields the highest cognitive scores while no English in the home yields the lowest. Findings reveal that there are differences in cognitive scores along ethnic group categories although there are also some unexpected findings. Home learning environment does not play as large a role as was predicted in raising the assessment scores overall for learners while speaking English in the home does, irrespective of ethnic background

Topological Analysis of Magnetically Induced Current Densities in Strong Magnetic Fields Using Stagnation Graphs

Stagnation graphs provide a useful tool to analyze the main topological features of the often complicated vector field associated with magnetically induced currents. Previously, these graphs have been constructed using response quantities appropriate for modest applied magnetic fields. We present an implementation capable of producing these graphs in arbitrarily strong magnetic fields, using current-density-functional theory. This enables us to study how the topology of the current vector field changes with the strength and orientation of the applied magnetic field. Applications to CH4, C2H2 and C2H4 are presented. In each case, we consider molecular geometries optimized in the presence of the magnetic field. The stagnation graphs reveal subtle changes to this vector field where the symmetry of the molecule remains constant. However, when the electronic state and symmetry of the corresponding equilibrium geometry changes with increasing field strength, the changes to the stagnation graph are extensive. We expect that the approach presented here will be helpful in interpreting changes in molecular structure and bonding in the strong-field regime

Modeling Ultrafast Electron Dynamics in Strong Magnetic Fields Using Real-Time Time-Dependent Electronic Structure Methods

An implementation of real-time time-dependent Hartree-Fock (RT-TDHF) and current-density-functional theory (RT-TDCDFT) for molecules in strong uniform magnetic fields is presented. In contrast to earlier implementations, the present work enables the use of the RT-TDCDFT formalism, which explicitly includes field dependent terms in the exchange-correlation functional. A range of current dependent exchange-correlation functionals based on the TPSS functional are considered, including a range-separated variant, which is particularly suitable for application to excited state calculations. The performance of a wide range of propagator algorithms for real-time methods is investigated in this context. A recently proposed molecular orbital pair decomposition analysis allows for assignment of electronic transitions, providing detailed information about which molecular orbitals are involved in each excitation. 1 The application of these methods is demonstrated for the electronic absorption spectra of N 2 and H 2 O both in the absence and in the presence of a magnetic field. The dependence of electronic spectra on the magnetic field strength and its orientation relative to the molecule is studied. The complex evolution of the absorption spectra with magnetic field is rationalised using the molecular orbital pair decomposition analysis, which provides crucial insight in strong fields where the spectra are radically different from their zero-field counterparts

Optimizing Molecular Geometries in Strong Magnetic Fields

An efficient implementation of geometrical derivatives at the Hartree-Fock (HF) and current-density-functional theory (CDFT) levels is presented for the study of molecular structure in strong magnetic fields. The required integral derivatives are constructed using a hybrid McMurchie-Davidson and Rys quadrature approach, which combines the amenability of the former to the evaluation of derivative integrals with the efficiency of the latter for basis sets with high angular momentum. In addition to its application to evaluating derivatives of four-centre integrals, this approach is also applied to gradients using the resolution-of-the-identity approximation, enabling efficient optimization of molecular structure for many-electron systems under a strong magnetic field. The CDFT contributions have been implemented for a wide range of density-functionals up to and including the meta-GGA level with current-density dependent contributions and (range-separated) hybrids for the first time. Illustrative applications are presented to the OH and benzene molecules, revealing the rich and complex chemistry induced by the presence of an external magnetic field. Challenges 1 for geometry optimization in strong fields are highlighted, along with the requirement for careful analysis of the resulting electronic structure at each stationary point. The importance of correlation effects is examined by comparison of results at the HF and CDFT levels. The present implementation of molecular gradients at the CDFT level provides a cost-effective approach to the study of molecular structure under strong magnetic fields, opening up many new possibilities for the study of chemistry in this regime