Exploring inequities in child welfare and child protection services: Explaining the ‘inverse intervention law’

Attempts to record, understand and respond to variations in child welfare and protection reporting, service patterns and outcomes are international, numerous and longstanding. Reframing such variations as an issue of inequity between children and between families opens the way to a new approach to explaining the profound difference in intervention rates between and within countries and administrative districts. Recent accounts of variation have frequently been based on the idea that there is a binary division between bias and risk (or need). Here we propose seeing supply (bias) and demand (risk) factors as two aspects of a single system, both framed, in part, by social structures. A recent finding from a study of intervention rates in England, the 'inverse intervention law', is used to illustrate the complex ways in which a range of factors interact to produce intervention rates. In turn, this analysis raises profound moral, policy, practice and research questions about current child welfare and child protection services.

The κ− μ / Inverse Gamma Fading Model

Statistical distributions have been extensively used in modeling fading effects in conventional and modern wireless communications. In the present work, we propose a novel κ − µ composite shadowed fading model, which is based on the valid assumption that the mean signal power follows the inverse gamma distribution instead of the lognormal or commonly used gamma distributions. This distribution has a simple relationship with the gamma distribution, but most importantly, its semi heavy-tailed characteristics constitute it suitable for applications relating to modeling of shadowed fading. Furthermore, the derived probability density function of the κ − µ / inverse gamma composite distribution admits a rather simple algebraic representation that renders it convenient to handle both analytically and numerically. The validity and utility of this fading model are demonstrated by means of modeling the fading effects encountered in body centric communications channels, which have been known to be susceptible to the shadowing effect. To this end, extensive comparisons are provided between theoretical and respective real-time measurement results. It is shown that these comparisons exhibit accurate fitting of the new model for various measurement set ups that correspond to realistic communication scenarios.

The η − µ / Inverse Gamma Composite Fading Model

In this paper we propose a new composite fadingmodel which assumes that the mean signal power of an η−µ signalenvelope follows an inverse gamma distribution. The inversegamma distribution has a simple relationship with the gammadistribution and can be used to model shadowed fading due to itssemi heavy-tailed characteristics. To demonstrate the utility of thenew η−µ / inverse gamma composite fading model, we investigatethe characteristics of the shadowed fading behavior observed inbody centric communications channels which are known to besusceptible to shadowing effects, particularly generated by thehuman body. It is shown that the η−µ / inverse gamma compositefading model provided an excellent fit to the measurement data.Moreover, using Kullback-Leibler divergence, the η −µ / inversegamma composite fading model was found to provide a better fitto the measured data than the κ − µ / inverse gamma compositefading model, for the communication scenarios considered here.

Inverse Association Between Gluteofemoral Obesity and Risk of Barrett's Esophagus in a Pooled Analysis

BACKGROUND & AIMS: Gluteofemoral obesity (determined by measurement of subcutaneous fat in hip and thigh regions) could reduce risks of cardiovascular and diabetic disorders associated with abdominal obesity. We evaluated whether gluteofemoral obesity also reduces risk of Barrett's esophagus (BE), a premalignant lesion associated with abdominal obesity.

METHODS: We collected data from non-Hispanic white participants in 8 studies in the Barrett's and Esophageal Adenocarcinoma Consortium. We compared measures of hip circumference (as a proxy for gluteofemoral obesity) from cases of BE (n=1559) separately with 2 control groups: 2557 population-based controls and 2064 individuals with gastroesophageal reflux disease (GERD controls). Study-specific odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using individual participant data and multivariable logistic regression and combined using random effects meta-analysis.

RESULTS: We found an inverse relationship between hip circumference and BE (OR per 5 cm increase, 0.88; 95% CI, 0.81-0.96), compared with population-based controls in a multivariable model that included waist circumference. This association was not observed in models that did not include waist circumference. Similar results were observed in analyses stratified by frequency of GERD symptoms. The inverse association with hip circumference was only statistically significant among men (vs population-based controls: OR, 0.85; 95% CI, 0.76-0.96 for men; OR, 0.93; 95% CI, 0.74-1.16 for women). For men, within each category of waist circumference, a larger hip circumference was associated with decreased risk of BE. Increasing waist circumference was associated with increased risk of BE in the mutually adjusted population-based and GERD control models.

CONCLUSIONS: Although abdominal obesity is associated with increased risk of BE, there is an inverse association between gluteofemoral obesity and BE, particularly among men.

VLSI design and implementation of 2-D Inverse Discrete Wavelet Transform

This paper proposes a JPEG-2000 compliant architecture capable of computing the 2 -D Inverse Discrete Wavelet Transform. The proposed architecture uses a single processor and a row-based schedule to minimize control and routing complexity and to ensure that processor utilization is kept at 100%. The design incorporates the handling of borders through the use of symmetric extension. The architecture has been implemented on the Xilinx Virtex2 FPGA.

Avoiding Overfitting in Inverse Modeling of Chloride Migration in Concrete

Inverse analysis for reactive transport of chlorides through concrete in the presence of electric field is presented. The model is solved using MATLAB’s built-in solvers “pdepe.m” and “ode15s.m”. The results from the model are compared with experimental measurements from accelerated migration test and a function representing the lack of fit is formed. This function is optimised with respect to varying amount of key parameters defining the model. Levenberg-Marquardt trust-region optimisation approach is employed. The paper presents a method by which the degree of inter-dependency between parameters and sensitivity (significance) of each parameter towards model predictions can be studied on models with or without clearly defined governing equations. Eigen value analysis of the Hessian matrix was employed to investigate and avoid over-parametrisation in inverse analysis. We investigated simultaneous fitting of parameters for diffusivity, chloride binding as defined by Freundlich isotherm (thermodynamic) and binding rate (kinetic parameter). Fitting of more than 2 parameters, simultaneously, demonstrates a high degree of parameter inter-dependency. This finding is significant as mathematical models for representing chloride transport rely on several parameters for each mode of transport (i.e., diffusivity, binding, etc.), which combined may lead to unreliable simultaneous estimation of parameters.