Breaking the boundaries: Geographical approaches to integrating 200 years of the Census

The census and similar sources of data have been published for two centuries so the information that they contain should provide an unparalleled insight into the changing population of Britain over this time period. To date, however, the seemingly trivial problem of changes in boundaries has seriously hampered the use of these sources as they make it impossible to create long run time series of spatially detailed data. The paper reviews methodologies that attempt to resolve this problem by using geographical information systems and areal inter-polation to allow the reallocation of data from one set of administrative units onto another. This makes it possible to examine change over time for a standard geography and thus it becomes possible to unlock the spatial detail and the temporal depth that are held in the census and in related sources.

A meta-heuristic approach to parallel code generation

The efficient generation of parallel code for multi-processor environments, is a large and complicated issue. Attempts to address this problem have always resulted in significant input from users. Because of constraints on user knowledge and time, the automation of the process is a promising and practically important research area. In recent years heuristic approaches have been used to capture available knowledge and make it available for the parallelisation process. Here, the introduction of a novel approach of neural network techniques is combined with an expert system technique to enhance the availability of knowledge to aid in the automatic generation of parallel code.

Local network-based measures to assess the inferability of different regulatory networks

The purpose of this study is to compare the inferability of various synthetic as well as real biological regulatory networks. In order to assess differences we apply local network-based measures. That means, instead of applying global measures, we investigate and assess an inference algorithm locally, on the level of individual edges and subnetworks. We demonstrate the behaviour of our local network-based measures with respect to different regulatory networks by conducting large-scale simulations. As inference algorithm we use exemplarily ARACNE. The results from our exploratory analysis allow us not only to gain new insights into the strength and weakness of an inference algorithm with respect to characteristics of different regulatory networks, but also to obtain information that could be used to design novel problem-specific statistical estimators.

Lest we forget: Remembering the consequences of child neglect - A clarion call to "feisty advocates"

It is widely acknowledged that, across the United Kingdom and the USA, childcare practitioners often struggle with cases of child neglect, because of the difficulties involved in attempting to define the problem at hand, and balancing these cases with others in the caseload that may appear more pressing, such as physical abuse. Consequently, in an attempt to refocus the lens of professional policy and practice, this article will profile a number of research studies that have highlighted the profound developmental deficits that neglect can cause, relative to other forms of child maltreatment, and a range of interventions that have proven to be effective with these types of cases. The article concludes with a discussion of the potential negative impact of the current financial crisis for neglected children.

Do focus groups contribute anything to the contingent valuation process?

The qualitative aspects of the Contingent Valuation Method (CVM) are largely ignored by (environmental) economists. This paper aims to instigate a discussion on (a) the usefulness of qualitative data to the contingent valuation process in general; and (b) the use and applicability of the focus group method in particular. We consider the range and uses of focus groups within the CVM and highlight problems with their analysis that have, to date, largely been ignored. A potential solution to circumvent the problem of non-independence of group data is suggested. While there are several distinct and worthwhile uses for qualitative data, focus groups should not automatically be taken as the only or best method to produce these insights even though they are the major one considered in this article. (C) 1999 Elsevier Science B.V. All rights reserved.

The p-hub Model with Hub-catchment Areas, Existing Hubs, and Simulation: A Case Study of Serbian Intermodal Terminals

This paper addresses the problem of optimally locating intermodal freight terminals in Serbia. To solve this problem and determine the effects of the resulting scenarios, two modeling approaches were combined. The first approach is based on multiple-assignment hub-network design, and the second is based on simulation. The multiple-assignment p-hub network location model was used to determine the optimal location of intermodal terminals. Simulation was used as a tool to estimate intermodal transport flow volumes, due to the unreliability and unavailability of specific statistical data, and as a method for quantitatively analyzing the economic, time, and environmental effects of different scenarios of intermodal terminal development. The results presented here represent a summary, with some extension, of the research realized in the IMOD-X project (Intermodal Solutions for Competitive Transport in Serbia).

First steps: study protocol for a randomized controlled trial of the effectiveness of the Group Family Nurse Partnership (gFNP) program compared to routine care in improving outcomes for high-risk mothers and their children and preventing abuse

Background: Evidence from the USA suggests that the home-based Family Nurse Partnership program (FNP), extending from early pregnancy until infants are 24 months, can reduce the risk of child abuse and neglect throughout childhood. FNP is now widely available in the UK. A new variant, Group Family Nurse Partnership (gFNP) offers similar content but in a group context and for a shorter time, until infants are 12 months old. Each group comprises 8 to 12 women with similar expected delivery dates and their partners. Its implementation has been established but there is no evidence of its effectiveness.

Methods/Design: The study comprises a multi-site randomized controlled trial designed to identify the benefits of gFNP compared to standard care. Participants (not eligible for FNP) must be either aged <20 years at their last menstrual period (LMP) with one or more previous live births, or aged 20 to 24 at LMP with low educational qualifications and no previous live births. 'Low educational qualifications' is defined as not having both Maths and English Language GCSE at grade C or higher or, if they have both, no more than four in total at grade C or higher. Exclusions are: under 20 years and previously received home-based FNP and, in either age group, severe psychotic mental illness or not able to communicate in English. Consenting women are randomly allocated (minimized by site and maternal age group) when between 10 and 16 weeks pregnant to either to the 44 session gFNP program or to standard care after the collection of baseline information. Researchers are blind to group assignment. The primary outcomes at 12 months are child abuse potential based on the revised Adult-Adolescent Parenting Inventory and parent/infant interaction coded using the CARE Index based on a video-taped interaction. Secondary outcomes are maternal depression, parenting stress, health related quality of life, social support, and use of services.

Discussion: This is the first study of the effectiveness of gFNP in the UK. Results should inform decision-making about its delivery alongside universal services, potentially enabling a wider range of families to benefit from the FNP curriculum and approach to supporting parenting.

Using ancestry-informative markers to identify fine structure across 15 populations of European origin

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia. 

Evaluation of information extraction techniques to label extracted data from e-commerce web page

Automatically determining and assigning shared and meaningful text labels to data extracted from an e-Commerce web page is a challenging problem. An e-Commerce web page can display a list of data records, each of which can contain a combination of data items (e.g. product name and price) and explicit labels, which describe some of these data items. Recent advances in extraction techniques have made it much easier to precisely extract individual data items and labels from a web page, however, there are two open problems: 1. assigning an explicit label to a data item, and 2. determining labels for the remaining data items. Furthermore, improvements in the availability and coverage of vocabularies, especially in the context of e-Commerce web sites, means that we now have access to a bank of relevant, meaningful and shared labels which can be assigned to extracted data items. However, there is a need for a technique which will take as input a set of extracted data items and assign automatically to them the most relevant and meaningful labels from a shared vocabulary. We observe that the Information Extraction (IE) community has developed a great number of techniques which solve problems similar to our own. In this work-in-progress paper we propose our intention to theoretically and experimentally evaluate different IE techniques to ascertain which is most suitable to solve this problem.

Assessment of clinical response to ivacaftor with lung clearance index in cystic fibrosis patients with a G551D-CFTR mutation and preserved spirometry:A randomised controlled trial

Background: Ivacaftor has shown a clinical benefit in patients with cystic fibrosis who have the G551D-CFTR mutation and reduced lung function. Lung clearance index (LCI) using multiple-breath washout might be an alternative to and more sensitive method than forced expiratory volume in 1 s (FEV₁) to assess treatment response in the growing number of children and young adults with cystic fibrosis who have normal spirometry. The aim of the study was to assess the treatment effects of ivacaftor on LCI in patients with cystic fibrosis, a G551D-CFTR mutation, and an FEV₁ >90% predicted. Methods: This phase 2, multicentre, placebo-controlled, double-blind 2×2 crossover study of ivacaftor treatment was conducted in patients with cystic fibrosis, at least one G551D-CFTR allele, and an FEV₁ >90% predicted. Patients also had to have an LCI higher than 7·4 at screening, age of 6 years or older, and a weight higher than or equal to 15 kg. Eligible patients were randomly allocated to receive one of two treatment sequences (placebo first followed by ivacaftor 150 mg twice daily [sequence 1] or ivacaftor 150 mg twice daily first followed by placebo [sequence 2]) of 28 days' treatment in each period, with a 28-day washout between the two treatment periods. Randomisation (ratio 1:1) was done with block sizes of 4, and all site personnel including the investigator, the study monitor, and the Vertex study team were masked to treatment assignment. The primary outcome measure was change from baseline in LCI. The study is registered at ClinicalTrials.gov, NCT01262352. Findings: Between February and November, 2011, 21 patients were enrolled, of which 11 were assigned to the sequence 1 group, and 10 to the sequence 2 group. 20 of these patients received treatment and 17 completed the trial (eight in sequence 1 group and 9 in sequence 2 group). Treatment with ivacaftor led to significant improvements compared with placebo in LCI (difference between groups in the average of mean changes from baseline at days 15 and 29 was -2·16 [95% CI -2·88 to -1·44]; p<0·0001). Adverse events experienced by study participants were similar between treatment groups; at least one adverse event was reported by 15 (79%) of 19 patients who received placebo and 13 (72%) of 18 patients who received ivacaftor. No deaths occurred during study period. Interpretation: In patients with cystic fibrosis aged 6 years or older who have at least one G551D-CFTR allele, ivacaftor led to improvements in LCI. LCI might be a more sensitive alternative to FEV₁ in detecting response to intervention in these patients with mild lung disease. Funding: Vertex Pharmaceuticals Incorporated. © 2013 Elsevier Ltd.