Can we detect Li K X-ray in lithium compounds using energy dispersive spectroscopy?

Lithium is the key element for the development of battery and new technology and the development of an analytical technique to spatially and quantitatively resolve this element is of key importance. Detection of Li K in pure metallic lithium is now possible in the Scanning Electron Microscope (SEM) with newly designed Energy Dispersive Spectroscopy (EDS). However, this work is clearly showing, for the first time using EDS, the detection of Li K in several binary lithium compounds (LiH, Li3 N, Li2 S, LiF and LiCl). Experimental Li K X-rays intensity is compared with a specially modified Monte Carlo simulation program showing discrepancies between theoretical and experimental Li K measurements. The effect of chemical bounding on the X-rays emission using density functional theory with the all-electron linearized augmented plane wave is showing that the emission of Li K from the binary compounds studied should be, at least, 12 times lower than in metallic Li. SCANNING 38:571-578, 2016. © 2016 Wiley Periodicals, Inc.

More reliable inference for the dissimilarity index of segregation.

The most widely used measure of segregation is the so-called dissimilarity index. It is now well understood that this measure also reflects randomness in the allocation of individuals to units (i.e. it measures deviations from evenness, not deviations from randomness). This leads to potentially large values of the segregation index when unit sizes and/or minority proportions are small, even if there is no underlying systematic segregation. Our response to this is to produce adjustments to the index, based on an underlying statistical model. We specify the assignment problem in a very general way, with differences in conditional assignment probabilities underlying the resulting segregation. From this, we derive a likelihood ratio test for the presence of any systematic segregation, and bias adjustments to the dissimilarity index. We further develop the asymptotic distribution theory for testing hypotheses concerning the magnitude of the segregation index and show that the use of bootstrap methods can improve the size and power properties of test procedures considerably. We illustrate these methods by comparing dissimilarity indices across school districts in England to measure social segregation.

Child health: evidence on the roles of family income and maternal mental health from a UK birth cohort.

There is a growing literature showing an association between higher family income and better child health. This paper uses cohort data with rich information on mother's early life events, her health, child-health-related behaviours, and her child's health to examine this association for the UK and to identify some of the mechanisms through which income affects child health. The paper examines the cross-sectional association between income and health, finds the expected association, but concludes that the association with current income cannot be distinguished from one between permanent income and child health. It then focuses on the mechanisms by which income translates into better child health; these include parental behaviours that may affect child health and parental health, including maternal mental health. Controlling for these factors, there is almost no direct impact of income. A significant role is played by mother's own health, particularly her mental health. No clear role is played by child-health production behaviours of the mother. Examining the maternal mental health-child health link in more detail suggests a role for maternal anxiety and somaticism.

Local neighbourhood and mental health: evidence from the UK.

This paper examines the association between neighbourhood and levels and changes in common mental disorders. Using data from a large scale nationally representative survey of individuals and households (the British Household Panel Survey), it locates individuals in their local neighbourhoods. These are defined as the nearest 500-800 persons centered around each individual in the survey. These 'bespoke' neighbourhoods are characterised according to five dimensions--disadvantage, mobility, age, ethnicity and urbanness--derived from factor analysis of the census characteristics of the residents of neighbourhoods in 1991. These dimensions measure characteristics of place that have been argued to be associated with mental ill health. The paper estimates multilevel models of the level and 5-year changes of common mental disorders (measured by the twelve item version of the General Health Questionnaire). Three and two level models are estimated, all of which allow for individual and household characteristics that may act as confounders of any neighbourhood effect. The results show the extent of association between neighbourhood and both levels and changes in mental health is limited. Less than one percent of the variance across individuals is at the neighbourhood level. The neighbourhood characteristics are not generally statistically associated with levels or changes in mental ill health. There is some evidence of interaction between neighbourhood characteristics and gender and ethnicity, but while statistically significant these interactions are small in size compared to the main effects of individual and household characteristics. What appears to be important for levels of common mental disorders are the observed characteristics of individuals and their households, not of place.