Search

In this paper, I present contextualizing factors, dimensions, and key markers of algorithm literacies, paying attention to the context of parenting and parenthood amidst datafication. Analyzing data from "think-aloud" interviews with 30 parents of children aged between 0 and 18, across England, I draw upon media and digital literacies scholarship to focus, first, in this paper, on the competencies, conversations, and events which contextualize parents' literacies with algorithmic interfaces. Next, I draw out four dimensions of parents' algorithm literacies including algorithm awareness, technical competencies, critical capacities, and championing their and their children's best interests, identifying practical markers for each dimension. I reflect on the broader implications of these for parenting and parenthood in datafied societies, and note that algorithm literacies are, forever, a work in progress, in fluidity and flux across the diverse courses of parenting journeys, deeply contextualized in the resources and restraints that parents encounter in their daily lives. [ABSTRACT FROM AUTHOR]

In this paper, I ask how parents understand and make sense of their children's relationships with social media algorithms. Drawing upon 30 think-aloud interviews with parents raising children aged 0 to 18 in England, in this paper, I pay attention to parents' understandings of and consequent approaches to platform algorithms in relation to their children's lives. I locate this work within user-centric research on people's understandings of algorithms, and research about parents' perspectives on data and datafication in relation to sharenting. Through my data, I draw out four modes – misunderstandings, parked understandings, transactional understandings and pro-active understandings. I suggest that parents' often flawed understandings of their children's myriad interfaces with algorithms deserve scrutiny not through a lens of blame or individualised parental (ir) responsibility but within cross-cutting contexts of parenting cultures and families' diverse contextual resources and restraints. I conclude by highlighting attention to parents' approaches to algorithms in children's lives as critical to parents' data and algorithm literacies. Prior State of Knowledge: Parents in diverse contexts try to understand and support their children's digital lives, and also often share content about their children on a variety of platforms. Prior research has shed significant light on the datafication of childhood. Novel Contributions: This study investigates parents' diverse understandings of algorithms underlying social media platforms and the ways in which they approach algorithms in their children's lives. Practical Implications: Parents' knowledge about algorithms and datafication is uneven. Policymakers need to better support adult media literacies, including data and algorithm literacies. Schools' communication to families and carers could also become key vehicles to raise awareness about datafication. [ABSTRACT FROM AUTHOR]

Background: Childhood respiratory tract infections (RTIs) are common and can lead to unnecessary antibiotic use and antimicrobial resistance. The CHIldren with COugh (CHICO) intervention incorporates a clinician-focused algorithm (STARWAVe) to predict future hospitalisation risk, elicitation of carer concerns, and a carer-focused personalised leaflet recording treatment decisions and safety-netting information. Aim: To examine the implementation of the CHICO intervention by primary care clinicians. Design and setting: A qualitative study with primary care clinicians in England taking part in the CHICO randomised controlled trial. Method: Interviews explored the CHICO intervention's acceptability and use. Clinicians from a range of practices with high and low antibiotic dispensing rates were recruited. Normalisation process theory underpinned data collection and thematic analysis. Results: Most clinicians liked the intervention because it was quick and easy to use, it helped elicit carer concerns, and reassured clinicians and carers of the appropriateness of treatment decisions. However, clinicians used it as a supportive aid for treatment decisions rather than as a tool for behaviour change. The accompanying advice leaflet helped explain treatment decisions and support self-care. The intervention did not always align with clinicians' usual processes, which could affect use. Increased familiarisation with the algorithm led to reduced intervention use, which was further reduced during the COVID-19 pandemic as a result of changes to practice and remote consultations. Conclusion: Clinicians found the CHICO intervention useful to support decision making around antibiotic prescribing and it helped discussions with carers about concerns and treatment decisions. The intervention may need to be adapted to align more with clinicians' consultation flow and remote consultations. [ABSTRACT FROM AUTHOR]

Copyright of Firat University Journal of Experimental & Computational Engineering (FUJECE) is the property of Firat University Journal of Experimental & Computational Engineering (FUJECE) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The latest data on teacher recruitment and retention in England shows that teacher supply is in a critical state, representing a substantial risk to the quality of education. Last year's initial teacher training (ITT) recruitment was below target in almost every secondary subject, while this year's applications data suggests significant improvements for the current cycle are unlikely. Meanwhile, little progress has been made on reducing high teacher workload since the pandemic, which has a strong impact on retention. This affirms that actions that are ambitious and radical, yet costeffective are urgently needed. The aim of the National Foundation for Educational Research's (NFER) annual series of Teacher Labour Market reports is to monitor the progress the school system in England is making towards meeting the teacher supply challenge. The report summarises new research and key trends in teacher recruitment, retention and working conditions and points towards policy actions that are likely to have the greatest impact on addressing the challenges. [ABSTRACT FROM AUTHOR]

It is uncommon for risk groups defined by statistical or artificial intelligence (AI) models to be chosen by jointly considering model performance and potential interventions available. We develop a framework to rapidly guide choice of risk groups in this manner, and apply it to guide breast cancer screening intervals using an AI model. Linear programming is used to define risk groups that minimize expected advanced cancer incidence subject to resource constraints. In the application risk stratification performance is estimated from a case–control study (2044 cases, 1:1 matching), and other parameters are taken from screening trials and the screening programme in England. Under the model, re-screening in 1 year for the highest 4% AI model risk, in 3 years for the middle 64%, and in 4 years for 32% of the population at lowest risk, was expected to reduce the number of advanced cancers diagnosed by approximately 18 advanced cancers per 1000 diagnosed with triennial screening, for the same average number of screens in the population as triennial screening for all. Sensitivity analyses found the choice of thresholds was robust to model parameters, but the estimated reduction in advanced cancers was not precise and requires further evaluation. Our framework helps define thresholds with the greatest chance of success for reducing the population health burden of cancer when used in risk-adapted screening, which should be further evaluated such as in health-economic modelling based on computer simulation models, and real-world evaluations. [ABSTRACT FROM AUTHOR]

Despite the increasing ethnic diversity of England's school-age population, academic literature on ethnic school segregation remains small, dated and hindered by methodological challenges. This study seeks to address these issues by measuring ethnic school segregation between 2006–2019 using two methodological innovations. Firstly, it is the first national study in England to adopt a multi-group segregation index to measure segregation between five major groups in a single concise metric. Secondly, it uses a clustering algorithm to group local schools into 'pseudo-neighbourhoods', which allows for segregation to be measured within local educational markets. The article shows that between 2006 and 2019 the median level of ethnic school segregation within English pseudo-neighbourhoods fell by 25%, which suggests students from different ethnic groups have become more evenly spread across local schools. Additionally, areas in the North of England were typically found to have higher levels of segregation than those in the South. [ABSTRACT FROM AUTHOR]

Well parameterized epidemiological models including accurate representation of contacts are fundamental to controlling epidemics. However, age-stratified contacts are typically estimated from pre-pandemic/peace-time surveys, even though interventions and public response likely alter contacts. Here, we fit age-stratified models, including re-estimation of relative contact rates between age classes, to public data describing the 2020-2021 COVID-19 outbreak in England. This data includes age-stratified population size, cases, deaths, hospital admissions and results from the Coronavirus Infection Survey (almost 9000 observations in all). Fitting stochastic compartmental models to such detailed data is extremely challenging, especially considering the large number of model parameters being estimated (over 150). An efficient new inference algorithm ABC-MBP combining existing approximate Bayesian computation (ABC) methodology with model-based proposals (MBPs) is applied. Modified contact rates are inferred alongside time-varying reproduction numbers that quantify changes in overall transmission due to pandemic response, and age-stratified proportions of asymptomatic cases, hospitalization rates and deaths. These inferences are robust to a range of assumptions including the values of parameters that cannot be estimated from available data. ABC-MBP is shown to enable reliable joint analysis of complex epidemiological data yielding consistent parametrization of dynamic transmission models that can inform data-driven public health policy and interventions. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'. [ABSTRACT FROM AUTHOR]

Fairness in assessment has become increasingly topical and controversial in recent years. Assessment theoreticians are writing more about fairness and assessment practitioners have developed processes and good practice to minimise unfairness. There is also increased scrutiny by students, parents and the wider public – not only of the fairness of assessments themselves and their outcomes, but of their use, notably for selection for college or university. This is in a context of continued awareness of inequalities in society and their impact on education and assessment. And on top of all these questions has been the impact – and the continuing long shadow – of Covid. Can there be fair assessment in such an unfair world? We consider three types of challenge to fair assessment: •Theoretical challenges •Challenges from thinking about social justice •Challenges from the way that statistics were used to award assessment outcomes in 2020 (particularly in England) [ABSTRACT FROM AUTHOR]

Objectives: Current British HIV Association (BHIVA) guidelines recommend the use of FRAX for the routine assessment of bone fracture risk in people living with HIV over 50 years of age every 3 years. Bone mineral density measurement with dual‐energy X‐ray absorptiometry (DXA) scan is recommended for those with increased fracture risk (FRAX major > 10%). Our objectives were to estimate the prevalence of and risk factors for osteoporosis in a population of PLWH aged > 50 years and assess the utility of FRAX in predicting the presence of DXA‐proven osteoporosis in this cohort. Methods: This was a cross‐sectional study of a cohort of PLWH aged > 50 years attending the Chelsea and Westminster Hospital and who had a DXA scan between January 2009 and December 2018. FRAX scores were calculated using the Sheffield algorithm. Multiple regression models and Cohen's kappa values were used to assess risk factors for osteoporosis and agreement between FRAX and DXA scan results, respectively. Results: In all, 744 patients were included (92.9% male, mean age 56 ± 5 years). The prevalence rates of osteoporosis (at DXA scans) and osteopenia were 12.2% and 63.7%, respectively. FRAX major was > 10% in only two patients, while 90/91 (98.9%) patients with osteoporosis had a normal FRAX score. The presence of osteoporosis was significantly associated with low body mass index and estimated glomerular filtration rate (p < 0.05). Conclusion: Our results indicate that FRAX scores did not predict the presence of osteoporosis in our population of PLWH over 50 years of age and therefore FRAX scores may not be the appropriate tool to define eligibility to perform DXA scans in PLWH. [ABSTRACT FROM AUTHOR]

Background: Health surveys provide a rich array of information but on relatively small numbers of individuals and evidence suggests that they are becoming less representative as response levels fall. Routinely collected administrative data offer more extensive population coverage but typically comprise fewer health topics. We explore whether data combination and multiple imputation of health variables from survey data is a simple and robust way of generating these variables in the general population. Methods: We use the UK Integrated Household Survey and the English 2011 population census both of which included self-rated general health. Setting aside the census self-rated health data we multiply imputed self-rated health responses for the census using the survey data and compared these with the actual census results in 576 unique groups defined by age, sex, housing tenure and geographic region. Results: Compared with original census data across the groups, multiply imputed proportions of bad or very bad self-rated health were not a markedly better fit than those simply derived from the survey proportions. Conclusion: While multiple imputation may have the potential to augment population data with information from surveys, further testing and refinement is required. [ABSTRACT FROM AUTHOR]

Automated zone-design methods are increasingly being used to create zoning systems for a range of purposes, such as the release of census statistics or the investigation of neighbourhood effects on health, Inevitably, the characteristics originally underpinning the design of a zoning system (eg, population size or homogeneity of the built environment) change through time. Rather than designing a completely new system every time substantive change occurs, or retaining an existing system which will become increasingly unfit for purpose, an alternative is to modify the existing system such that zones which still meet the design criteria are retained, but those which are no longer fit for purpose are split or merged. This paper defines the first generic methodology for the automated maintenance of existing zoning systems. Using bespoke, publicly available, software (AZTo0I), the methodology is employed to modify the 2001 Census output geographies within six local authority districts in England and Wales in order to make them suitable for the release of contemporary population-related data. Automated maintenance of an existing system is found to be a more iterative and constrained problem than designing a completely new system; design constraints frequently have to be relaxed and manual intervention is occasionally required. Nonetheless, existing zone-design techniques can be successfully adapted and implemented to automatically maintain an existing system. The findings of this paper are of direct relevance both to the Office for National Statistics in their design of the 2011 Census output geographies for England and Wales and to any other countries or organisations seeking to maintain an existing zoning system. [ABSTRACT FROM AUTHOR]

A large-scale multiple surveillance system for infectious disease outbreaks has been in operation in England and Wales since the early 1990s. Changes to the statistical algorithm at the heart of the system were proposed and the purpose of this paper is to compare two new algorithms with the original algorithm. Test data to evaluate performance are created from weekly counts of the number of cases of each of more than 2000 diseases over a twenty-year period. The time series of each disease is separated into one series giving the baseline (background) disease incidence and a second series giving disease outbreaks. One series is shifted forward by twelve months and the two are then recombined, giving a realistic series in which it is known where outbreaks have been added. The metrics used to evaluate performance include a scoring rule that appropriately balances sensitivity against specificity and is sensitive to variation in probabilities near 1. In the context of disease surveillance, a scoring rule can be adapted to reflect the size of outbreaks and this was done. Results indicate that the two new algorithms are comparable to each other and better than the algorithm they were designed to replace. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to calculate the rate of suicide in different religious groups in people of South Asian origin in the UK. Design/methodology/approach - A cross-sectional, secondary analysis of a national data set. A name recognition algorithm was used to identify people of South Asian origin and their religion. Standardized mortality ratios (SMRs) were calculated using this data and data from the national census. Setting: a population study of all those who died by suicide in England and Wales in 2001. Participants: all cases of suicide and undetermined intent identified by the Office for National Statistics for England and Wales. Findings - There were 4,848 suicides in the UK in 2001 of which 125 (2.6 percent) were identified as people of South Asian origin by the algorithm. The suicide rate for all people of South Asian origin was 5.50/100,000 compared to 9.31/100,000 for the population of England and Wales. The age SMR for those whose names were of Hindu, Muslim or Sikh origin were 0.88, 0.47 and 0.85, respectively. Female South Asians have lower rates of suicide, than their South Asian male counterparts. Research limitations/implications - Religious classification by the computerized program does not guarantee religious affiliation. The data set were confined to one year because religion was not collected prior to the 2001 census. Originality/value - The rates of suicide for South Asian sub-populations in the UK differ by gender and religion. [ABSTRACT FROM AUTHOR]

Background: The literature contains limited information on the problems faced by dying patients with COVID-19 and the effectiveness of interventions to manage these. Aim: The aim of this audit was to assess the utility of our end-of-life care plan, and specifically the effectiveness of our standardised end-of-life care treatment algorithms, in dying patients with COVID-19. Design: The audit primarily involved data extraction from the end-of-life care plan, which includes four hourly nursing (ward nurses) assessments of specific problems: patients with problems were managed according to standardised treatment algorithms, and the intervention was deemed to be effective if the problem was not present at subsequent assessments. Setting/participants: This audit was undertaken at a general hospital in England, covered the 8 weeks from 16 March to 11 May 2020 and included all inpatients with COVID-19 who had an end-of-life care plan (and died). Results: Sixty-one patients met the audit criteria: the commonest problem was shortness of breath (57.5%), which was generally controlled with conservative doses of morphine (10–20 mg/24 h via a syringe pump). Cough and audible respiratory secretions were relatively uncommon. The second most common problem was agitation/delirium (55.5%), which was generally controlled with standard pharmacological interventions. The cumulative number of patients with shortness of breath, agitation and audible respiratory secretions increased over the last 72 h of life, but most patients were symptom controlled at the point of death. Conclusion: Patients dying of COVID-19 experience similar end-of-life problems to other groups of patients. Moreover, they generally respond to standard interventions for these end-of-life problems. [ABSTRACT FROM AUTHOR]

Background: Red blood cells are essential for modern medicine but managing their collection and supply to cope with fluctuating demands represents a major challenge. As deterministic models based on predicted population changes have been problematic, there remains a need for more precise and reliable prediction of use. Here, we develop three new time-series methods to predict red cell use 4 to 52 weeks ahead.Study Design and Methods: From daily aggregates of red blood cell (RBC) units issued from 2005 to 2011 from the NHS Blood and Transplant, we generated a new set of non-overlapping weekly data by summing the daily data over 7 days and derived the average blood use per week over 4-week and 52-week periods. We used three new methods for linear prediction of blood use by computing the coefficients using Minimum Mean Squared Error (MMSE) algorithm.Results: We optimized the time-window size, order of the prediction, and order of the polynomial fit for our data set. By exploiting the annual periodicity of the data, we achieved significant improvements in long-term predictions, as well as modest improvements in short-term predictions. The new methods predicted mean RBC use with a standard deviation of the percentage error of 2.5% for 4 weeks ahead and 3.4% for 52 weeks ahead.Conclusion: This paradigm allows short- and long-term prediction of RBC use and could provide reliable and precise prediction up to 52 weeks ahead to improve the efficiency of blood services and sufficiency of blood supply with reduced costs. [ABSTRACT FROM AUTHOR]

In 2012, The Royal College of Physicians (RCP) developed a National Early Warning Score (NEWS) as a standardised approach to assessment and response to critical illness. This paper reports the authors’ experiences whilst implementing NEWS across one large inner London NHS Trust. NEWS was introduced to all adult areas between November 2013 and January 2014. All healthcare staff completed the RCP’s online e-learning module and received scenario-based teaching. One of the challenges was the Trust’s geographical location over three sites. Comparisons across all sites will be made over time as data become available. Introducing NEWS has been a challenging but exciting initiative. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to evaluate the feasibility of a screening test for looked after children in order to identify undetected psychiatric disorders. Design/methodology/approach – Children aged four to 16 in care in one London Borough for four consecutive months were eligible for screening. Carers, teachers and children aged over 11 were asked to complete the Strengths and Difficulties Questionnaire (SDQ). Where the SDQ suggested that a psychiatric disorder was "possible" or "probable", participants were then invited to complete the Developmental and Well-Being Assessment, which was rated by a senior psychiatrist to generate diagnoses if appropriate. Findings – The paper finds that over one year, 23 children were eligible for screening. A total of 18 underwent the initial stage of screening, and seven were subsequently diagnosed with a formal psychiatric disorder. Originality/value – This study illustrates the unmet need for mental health interventions among children looked after by the local authority and confirms the feasibility of a simple screening protocol. [ABSTRACT FROM AUTHOR]

Background and purpose : Chemistry examinations can favour the deployment of algorithmic procedures like Le Chatelier’s Principle (LCP) rather than reasoning using chemical principles. This study investigated the explanatory resources which high school students use to answer equilibrium problems and whether the marks given for examination answers require students to use approaches beyond direct application of LCP. Sample : The questionnaire was administered to 162 students studying their first year of advanced chemistry (age 16/17) in three high achieving London high schools. Design and methods : The students’ explanations of reversible chemical systems were inductively coded to identify the explanatory approaches used and interviews with 13 students were used to check for consistency. AS level examination questions on reversible reactions were analysed to identify the types of explanations sought and the students’ performance in these examinations was compared to questionnaire answers. Results : 19% of students used a holistic explanatory approach: when the rates of forward and reverse reactions are correctly described, recognising their simultaneous and mutually dependent nature. 36% used a mirrored reactions approach when the connected nature of the forward and reverse reactions is identified, but not their mutual dependency. 42% failed to recognize the interdependence of forward and reverse reactions (reactions not connected approach). Only 4% of marks for AS examination questions on reversible chemical systems asked for responses which went beyond either direct application of LCP or recall of equilibrium knowledge. 37% of students attained an A grade in their AS national examinations. Conclusions : Examinations favour the application of LCP making it possible to obtain the highest grade with little understanding of reversible chemical systems beyond a direct application of this algorithm. Therefore students’ understanding may be attenuated so that they are unable to use kinetic sub-micro level ideas which will support the building of deeper energetic conceptions at university. [ABSTRACT FROM PUBLISHER]

Computer-Aided Assessments (CAAs) have been used increasingly at Brunel University for over 10 years to test students' mathematical abilities. Recently, we have focussed on providing very rich feedback to the students; given the work involved in designing and coding such feedback, it is important to study the impact of the interaction between students and feedback. To make feedback more focussed, examination scripts have been analysed to identify common student errors and misconceptions. These have then been used to code distracters in multiple-choice and responsive numerical input-type questions. Since random parameters are used in all questions developed, distracters have to be coded as algebraic or algorithmic mal-rules. This paper reports on the methodology used to identify students' errors and misconceptions and how the evidence collected was used to code the distracters. The paper also provides hard evidence that real learning has taken place while students have interacted with the CAAs. Statistical analyses of exam performance over eight years indicate that students are able to improve performance in subsequent formative and summative assessments provided that they have truly engaged with the CAA, especially by spending time studying the feedback provided. [ABSTRACT FROM AUTHOR]

Copyright of Current Sociology is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: In elite football (soccer), periodic health examination (PHE) could provide prognostic factors to predict injury risk. Objective: To develop and internally validate a prognostic model to predict individualised indirect (non-contact) muscle injury (IMI) risk during a season in elite footballers, only using PHE-derived candidate prognostic factors. Methods: Routinely collected preseason PHE and injury data were used from 152 players over 5 seasons (1st July 2013 to 19th May 2018). Ten candidate prognostic factors (12 parameters) were included in model development. Multiple imputation was used to handle missing values. The outcome was any time-loss, index indirect muscle injury (I-IMI) affecting the lower extremity. A full logistic regression model was fitted, and a parsimonious model developed using backward-selection to remove factors that exceeded a threshold that was equivalent to Akaike's Information Criterion (alpha 0.157). Predictive performance was assessed through calibration, discrimination and decision-curve analysis, averaged across all imputed datasets. The model was internally validated using bootstrapping and adjusted for overfitting. Results: During 317 participant-seasons, 138 I-IMIs were recorded. The parsimonious model included only age and frequency of previous IMIs; apparent calibration was perfect, but discrimination was modest (C-index = 0.641, 95% confidence interval (CI) = 0.580 to 0.703), with clinical utility evident between risk thresholds of 37–71%. After validation and overfitting adjustment, performance deteriorated (C-index = 0.589 (95% CI = 0.528 to 0.651); calibration-in-the-large = − 0.009 (95% CI = − 0.239 to 0.239); calibration slope = 0.718 (95% CI = 0.275 to 1.161)). Conclusion: The selected PHE data were insufficient prognostic factors from which to develop a useful model for predicting IMI risk in elite footballers. Further research should prioritise identifying novel prognostic factors to improve future risk prediction models in this field. Trial registration: NCT03782389 [ABSTRACT FROM AUTHOR]

Background Over the past decade, acute kidney injury (AKI) has become a global priority for improving patient safety and health outcomes. In the UK, a confidential inquiry into AKI led to the publication of clinical guidance and a range of policy initiatives. National patient safety directives have focused on the mandatory establishment of clinical decision support systems (CDSSs) within all acute National Health Service (NHS) trusts to improve the detection, alerting and response to AKI. We studied the organisational work of implementing AKI CDSSs within routine hospital care. Methods An ethnographic study comprising nonparticipant observation and interviews was conducted in two NHS hospitals, delivering AKI quality improvement programmes, located in one region of England. Three researchers conducted a total of 49 interviews and 150 hours of observation over an 18-month period. Analysis was conducted collaboratively and iteratively around emergent themes, relating to the organisational work of technology adoption. Results The two hospitals developed and implemented AKI CDSSs using very different approaches. Nevertheless, both resulted in adaptive work and trade-offs relating to the technology, the users, the organisation and the wider system of care. A common tension was associated with attempts to maximise benefit while minimise additional burden. In both hospitals, resource pressures exacerbated the tensions of translating AKI recommendations into routine practice. Conclusions Our analysis highlights a conflicted relationship between external context (policy and resources), and organisational structure and culture (eg, digital capability, attitudes to quality improvement). Greater consideration is required to the long-term effectiveness of the approaches taken, particularly in light of the ongoing need for adaptation to incorporate new practices into routine work. [ABSTRACT FROM AUTHOR]

Background: We have developed an open-source ALgorithm for Generating Address Exposures (ALGAE) that cleans residential address records to construct address histories and assign spatially-determined exposures to cohort participants. The first application of this algorithm was to construct prenatal and early life air pollution exposure for individuals of the Avon Longitudinal Study of Parents and Children (ALSPAC) in the South West of England, using previously estimated particulate matter ≤10  µm (PM10) concentrations.Methods: ALSPAC recruited 14 541 pregnant women between 1991 and 1992. We assigned trimester-specific estimated PM10 exposures for 12 752 pregnancies, and first year of life exposures for 12 525 births, based on maternal residence and residential mobility.Results: Average PM10 exposure was 32.6  µg/m3 [standard deviation (S.D.) 3.0  µg/m3] during pregnancy and 31.4 µg/m3 (S.D. 2.6  µg/m3) during the first year of life; 6.7% of women changed address during pregnancy, and 18.0% moved during first year of life of their infant. Exposure differences ranged from -5.3  µg/m3 to 12.4  µg/m3 (up to 26% difference) during pregnancy and -7.22  µg/m3 to 7.64  µg/m3 (up to 27% difference) in the first year of life, when comparing estimated exposure using the address at birth and that assessed using the complete cleaned address history. For the majority of individuals exposure changed by <5%, but some relatively large changes were seen both in pregnancy and in infancy.Conclusions: ALGAE provides a generic and adaptable, open-source solution to clean addresses stored in a cohort contact database and assign life stage-specific exposure estimates with the potential to reduce exposure misclassification. [ABSTRACT FROM AUTHOR]

Background: Blood products are essential for modern medicine, but managing their collection and supply in the face of fluctuating demands represents a major challenge. As deterministic models based on predicted changes in population have been problematic, there remains a need for more precise and reliable prediction of demands. Here, we propose a paradigm incorporating four different time-series methods to predict red blood cell (RBC) issues 4 to 24 weeks ahead.Study Design and Methods: We used daily aggregates of RBC units issued from 2005 to 2011 from the National Health Service Blood and Transplant. We generated a new set of nonoverlapping weekly data by summing the daily data over 7 days and derived the average blood issues per week over 4-week periods. We used four methods for linear prediction of blood demand by computing the coefficients with the minimum mean squared error and weighted least squares error algorithms.Results: We optimized the time-window size, order of the prediction, and order of the polynomial fit for our data set. The four time-series methods, essentially using different weightings to data points, gave very similar results and predicted mean RBC issues with a standard deviation of the percentage error of 3.0% for 4 weeks ahead and 4.0% for 24 weeks ahead.Conclusion: This paradigm allows prediction of demand for RBCs and could be developed to provide reliable and precise prediction up to 24 weeks ahead to improve the efficiency of blood services and sufficiency of blood supply with reduced costs. [ABSTRACT FROM AUTHOR]

Background Area-based initiatives that include a focus on community empowerment are increasingly being seen as potentially an important way of improving health and reducing inequalities. However, there is little empirical evidence on the pathways between communities having more control and health outcomes. Purpose To identify pathways to health improvement in a community-led area-based community empowerment initiative. Methods Longitudinal data on mental health, community control, area belonging, satisfaction, social cohesion and safety were collected over two time points, 6 months apart from 48 participants engaged in the Big Local programme, England. Qualitative comparative analysis (QCA) was used to explore pathways to health improvement. Results There was no clear single pathway that led to mental health improvement but positive changes in 'neighbourhood belonging' featured in 4/5 health improvement configurations. Further, where respondents experienced no improvement in key social participation/control factors, they experienced no health improvement. Conclusion This study demonstrates a potential pathway between an improvement in 'neighbourhood belonging' and improved mental health outcomes in a community empowerment initiative. Increasing neighbourhood belonging could be a key target for mental health improvement interventions. [ABSTRACT FROM AUTHOR]

Background: Establishing and sustaining enteral feeding in critically ill children is challenging and has met with many problems. Aims and objectives: The aim of this study was to investigate (a) how actual calorie intake compared with estimated caloric requirements and (b) whether feeding guideline adherence resulted in improved nutritional intake. Design and methods: A prospective observational study was undertaken over 1 month in a tertiary referral paediatric intensive care unit (PICU) in the northwest of England. Results: Forty-seven children were studied, with a wide range of diagnoses in a 1-month period. Only 47% of the children had enteral feeds started within our 6 h post-admission target. Over half (55%) of the children received less than half of their estimated calorie requirements, but if feeding guidelines were followed, this resulted in a significantly higher ( p = 0·004) delivery of the child's estimated requirements. Conclusions: This study found that many children are not receiving adequate nutrition in PICU and that the use of feeding guidelines significantly improves calorie delivery in PICU patients. Relevance to clinical practice: This paper highlights the dearth of research related to enteral feeding in critically ill children. We found that the use of feeding guidelines improved calorie delivery and so units should be encouraged to develop their own guidelines based on the best evidence available. [ABSTRACT FROM AUTHOR]

Background: The co‐occurrence of internalizing disorders is a common form of psychiatric comorbidity, raising questions about the boundaries between these diagnostic categories. We employ network psychometrics in order to: (a) determine whether internalizing symptoms cluster in a manner reflecting DSM diagnostic criteria, (b) gauge how distinct these diagnostic clusters are and (c) examine whether this network structure changes from childhood to early and then late adolescence. Method: Symptom‐level data were obtained for service users in publicly funded mental health services in England between 2011 and 2015 (N = 37,162). A symptom network (i.e. Gaussian graphical model) was estimated, and a community detection algorithm was used to explore the clustering of symptoms. Results: The estimated network was densely connected and characterized by a multitude of weak associations between symptoms. Six communities of symptoms were identified; however, they were weakly demarcated. Two of these communities corresponded to social phobia and panic disorder, and four did not clearly correspond with DSM diagnostic categories. The network structure was largely consistent by sex and across three age groups (8–11, 12–14 and 15–18 years). Symptom connectivity in the two older age groups was significantly greater compared to the youngest group and there were differences in centrality across the age groups, highlighting the age‐specific relevance of certain symptoms. Conclusions: These findings clearly demonstrate the interconnected nature of internalizing symptoms, challenging the view that such pathology takes the form of distinct disorders. [ABSTRACT FROM AUTHOR]

In this paper we present a novel Case-Based Reasoning (CBR) system called CABAROST (CAsed-BAsed ROSTering) which was developed for personnel scheduling problems. CBR is used to capture and store examples of personnel manager behaviour which are then used to solve future problems. Previous examples of constraint violations in schedules and the repairs that were used to solve the violations are stored as cases. The sequence in which violations are repaired can have a great impact on schedule quality. A novel memetic algorithm is proposed which evolves good quality sequences of repairs generated by CABAROST. The algorithm was tested on instances of the real-world nurse rostering problem at the Queens Medical Centre NHS Trust in Nottingham. [ABSTRACT FROM AUTHOR]

In this paper, an automatic near-real time (NRT) flood detection approach is presented, which combines histogram thresholding and segmentation based classification, specifically oriented to the analysis of single-polarized very high resolution Synthetic Aperture Radar (SAR) satellite data. The challenge of SAR-based flood detection is addressed in a completely unsupervised way, which assumes no training data and therefore no prior information about the class statistics to be available concerning the area of investigation. This is usually the case in NRT-disaster management, where the collection of ground truth information is not feasible due to time-constraints. A simple thresholding algorithm can be used in the most of the cases to distinguish between "flood" and "non-flood" pixels in a high resolution SAR image to detect the largest part of an inundation area. Due to the fact that local gray-level changes may not be distinguished by global thresholding techniques in large satellite scenes the thresholding algorithm is integrated into a split-based approach for the derivation of a global threshold by the analysis and combination of the split inherent information. The derived global threshold is then integrated into a multiscale segmentation step combining the advantages of small-, medium- and large-scale per parcel segmentation. Experimental investigations performed on a TerraSAR-X Stripmap scene from southwest England during large scale flooding in the summer 2007 show high classification accuracies of the proposed split-based approach in combination with image segmentation and optional integration of digital elevation models. [ABSTRACT FROM AUTHOR]

This paper summarizes the ongoing research on the Bishopsgate Tower in the City of London designed by Kohn Pedersen Fox Associates. We present a pre-rational geometry computational solution targeting a constraint-aware exploration of the architectural design-space, while interactively optimizing building performance in terms of constructability and cost-efficiency. We document a novel approach in building metrics optimization supported by parametric technologies and embedded analytical algorithms. The process is indicative of how computational methods will develop in the future and help designers find solutions for increasingly complex spaces. [ABSTRACT FROM AUTHOR]

Objective: To determine the validity of assessing and recording the neurodevelopmental outcome of very preterm infants during routine clinical follow-up in England.Design: Children born <30 weeks gestation, attending routine clinical follow-up at post-term ages 20-28 months, were recruited. Data on neurodevelopmental outcomes were recorded by the reviewing clinician in a standardised format in the child's electronic patient record, based on a set of key questions designed to be used without formal training or developmental testing. Using a predefined algorithm, each participant was classified as having 'no', 'mild/moderate' or 'severe' impairment in cognitive, communication and motor domains. All participants also received a research assessment by a single assessor using the Bayley Scales of Infant Development, third edition (Bayley-III). The sensitivity and specificity of routine data in capturing impairment (any Bayley-III score <85) or severe impairment (any Bayley-III score <70) was calculated.Results: 190 children participated. The validity of routine assessments in identifying children with no impairment and no severe impairment was high across all domains (specificities 83.9%-100.0% and 96.6%-100.0%, respectively). However, identification of impairments, particularly in the cognitive (sensitivity 69.7% (55.1%-84.3%)) and communication (sensitivity (53.2% (42.0%-64.5%)) domains, was poor.Conclusions: Neurodevelopmental status determined during routine clinical assessment lacks adequate sensitivity in cognitive and communication domains. It is uncertain whether this reflects the assessment or/and the recording of findings. As early intervention may improve education and social outcomes, this is an important area for healthcare quality improvement research. [ABSTRACT FROM AUTHOR]

Background: The 2014 guidelines on cardiovascular risk assessment and lipid modification from the National Institute for Health and Care Excellence (NICE) recommend statin therapy for adults with prevalent cardiovascular disease (CVD), and for adults with a 10-year CVD risk of ≥10%, estimated using the QRISK2 algorithm.Aim: To determine risk factor levels required to exceed the risk threshold for statin therapy, and to estimate the number of adults in England who would require statin therapy under the guidelines.Design and Setting: Cross-sectional study using a sample representative of the English population aged 30-84 years.Method: To estimate 10-year CVD risk different combinations of risk factor levels were entered into the QRISK2 algorithm. The NICE guidelines were applied to the sample using data from the Health Survey for England 2011.Results: Even with optimal risk factor levels, males of different ethnicities would exceed the 10% risk threshold between the ages of 60 and 70 years, and females would exceed the threshold between 65 and 75 years. Under the NICE guidelines, 11.8 million males and females (37% of the adults aged 30-84 years) would require statin therapy, most of them (9.8 million) for primary prevention. When analysed by age, 95% of males and 66% of females without CVD in ages 60-74 years, including all males and females in ages 75-84 years, would require statin therapy.Conclusion: Under the 2014 NICE guidelines, 11.8 million (37%) adults in England aged 30-84 years, including almost all males >60 years in all females >75 years, require statin therapy. [ABSTRACT FROM AUTHOR]

Background: NHS England has mandated the use in hospital laboratories of an automated early warning algorithm to create a consistent method for the detection of acute kidney injury (AKI). It generates an 'alert' based on changes in serum creatinine level to notify attending clinicians of a possible incident case of the condition, and to provide an assessment of its severity. We aimed to explore the feasibility of secondary data analysis to reproduce the algorithm outside of the hospital laboratory, and to describe the epidemiology of AKI across primary and secondary care within a region.Methods: Using the Hampshire Health Record Analytical database, a patient-anonymised database linking primary care, secondary care and hospital laboratory data, we applied the algorithm to one year (1st January-31st December 2014) of retrospective longitudinal data. We developed database queries to modularise the collection of data from various sectors of the local health system, recreate the functions of the algorithm and undertake data cleaning.Results: Of a regional population of 642,337 patients, 176,113 (27.4%) had two or more serum creatinine test results available, with testing more common amongst older age groups. We identified 5361 (or 0.8%) with incident AKI indicated by the algorithm, generating a total of 13,845 individual AKI alerts. A cross-sectional assessment of each patient's first alert found that more than two-thirds of cases originated in the community, of which nearly half did not lead to a hospital admission.Conclusion: It is possible to reproduce the algorithm using linked primary care, secondary care and hospital laboratory data, although data completeness, data quality and technical issues must be overcome. Linked data is essential to follow the significant proportion of people with AKI who transition from primary to secondary care, and can be used to assess clinical outcomes and the impact of interventions across the health system. This study emphasises that the development of data systems bridging across different sectors of the health and social care system can provide benefits for researchers, clinicians, healthcare providers and commissioners. [ABSTRACT FROM AUTHOR]

Patient-reported outcome measures (PROMs) are now routinely collected in the English National Health Service and used to compare and reward hospital performance within a high-powered pay-for-performance scheme. However, PROMs are prone to missing data. For example, hospitals often fail to administer the pre-operative questionnaire at hospital admission, or patients may refuse to participate or fail to return their post-operative questionnaire. A key concern with missing PROMs is that the individuals with complete information tend to be an unrepresentative sample of patients within each provider and inferences based on the complete cases will be misleading. This study proposes a strategy for addressing missing data in the English PROM survey using multiple imputation techniques and investigates its impact on assessing provider performance. We find that inferences about relative provider performance are sensitive to the assumptions made about the reasons for the missing data. [ABSTRACT FROM AUTHOR]

Multiple drug intolerance to antihypertensive medications (MDI-HTN) is an overlooked cause of nonadherence. In this study, 55 patients with MDI-HTN were managed with a novel treatment algorithm utilizing sequentially initiated monotherapies or combinations of maximally tolerated doses of fractional tablet doses, liquid formulations, transdermal preparations, and off-label tablet medications. A total of 10% of referred patients had MDI-HTN, resulting in insufficient pharmacotherapy and baseline office blood pressure (OBP) of 178±24/94±15 mm Hg. At baseline, patients were intolerant to 7.6±3.6 antihypertensives; they were receiving 1.4±1.1 medications. After 6 months on the novel MDI-HTN treatment algorithm, both OBP and home blood pressure (HBP) were significantly reduced, with patients receiving 2.0±1.2 medications. At 12 months, OBP was reduced from baseline by 17±5/9±3 mm Hg (P<.01, P<.05) and HBP was reduced by 11±5/12±3 mm Hg (P<.01 for both) while patients were receiving 1.9±1.1 medications. Application of a stratified medicine approach allowed patients to tolerate increased numbers of medications and achieved significant long-term lowering of blood pressure. [ABSTRACT FROM AUTHOR]

The article focuses on the usage of algorithm in public service. Numerous papers, articles and books have demonstrated and discussed the method, and algorithms have been successfully applied to many problems in industry, commerce and government. Using algorithms in the public sector, should at least be aware of all the available methods and when to apply them. There is a particularly straightforward case in local government in which algorithms were successfully applied. The implementation of the Social Services Act of 1970 involved social workers whose work had previously been governed by one area of legislation only, in a much wider range of responsibilities and hence in the need to act in accordance with a much wider range of legislation. The traditional view that if they had more to learn they should receive more training would have been counter-productive. Sections of the legislation were selected, the algorithms were designed by Cambridge Consultants (Training) Ltd, vetted by expert committees and tried out extensively by social workers, who found that they could use them quickly and effectively.

Comments on the annual BINDT conference regarding radiography in Harrogate, England. Presentations of the automated digital and computed radiography theme; Use of defect recognition algorithms on digital images; Selection of the papers related to the topics discuss in the conference.

Purpose: This comparative study examines the categorisation of patients undergoing surgical repair of inguinal hernia in the diagnosis-related group (DRG) systems of 11 European countries (Austria, England, Estonia, Finland, France, Germany, Ireland, the Netherlands, Poland, Spain and Sweden). Understanding the design and operation of DRG systems for this common surgical procedure is important, given their increasing use internationally for hospital reimbursement and performance measurement. Methods: A common definition was used to identify inguinal hernia patients and the corresponding data were extracted from national databases. The analysis compared the variables and algorithms for classifying these patients to DRGs across the participating countries, as well as the number, composition and relative resource intensity of groups. An index case and six standardised vignettes were grouped using each country's DRG system and the associated quasi-prices were calculated. Results: The number of groups to which inguinal hernia patients are assigned is typically three or four, but ranges from two in Poland to ten in France. In most systems, categorising patients is contingent on procedure, principal and secondary diagnoses, and age, with treatment setting (day case/inpatient) being less common. Added to these, the French system also incorporates length of stay and whether the patient died. More resource intensive DRGs generally contained patients who were older, treated as inpatients, did not die, had (more severe) complications and/or co-morbidities, and/or underwent laparoscopic repair. There are cross-country disparities in day case rates and the use of laparoscopic repairs. Conclusions: The categorisation of inguinal hernia patients varies across the 11 European DRG systems under study. By highlighting the main differences across these systems, this comparative analysis allows the relevant decision makers to assess the adequacy and specificity of their own DRG systems. [ABSTRACT FROM AUTHOR]

Background: Patients at high risk of emergency hospitalisation are particularly likely to experience fragmentation in care. The virtual ward model attempts to integrate health and social care by offering multidisciplinary case management to people at high predicted risk of unplanned hospitalisation. Objective: To describe the care practice in three virtual ward sites in England and to explore how well each site had achieved meaningful integration. Method: Case studies conducted in Croydon, Devon and Wandsworth during 2011-2012, consisting of semi-structured interviews, workshops, and site visits. Results: Different versions of the virtual wards intervention had been implemented in each site. In Croydon, multidisciplinary care had reverted back to one-to-one case management. Conclusions: To integrate successfully, virtual ward projects should safeguard the multidisciplinary nature of the intervention, ensure the active involvement of General Practitioners, and establish feedback processes to monitor performance such as the number of professions represented at each team meeting. [ABSTRACT FROM AUTHOR]

This research explores the relationship between support worker utilisation and patient- and team-level characteristics using a prospective longitudinal study of 20 older people's community rehabilitation teams. Between January and September 2009, 462 Whole Time Equivalent Staff and 1913 patients participated in the study. Patient dependency, health status (Therapy Outcome Measures, EQ-5D and Levels of Care tool) and demographic data were collected alongside detailed staff activity data for patients during the recruitment period. Multivariate analyses were used to determine the relationship between the proportion of care delivered by support workers team and patient variables. Support workers delivered up to 36% of direct patient care and spent less time per patient contact (36.0 minutes, SD 37.7, range 0-600) than qualified professionals (mean time per contact 75.8 minutes, SD 32.9, range 0-334). Less-dependent and female patients had a greater proportion of support worker input, with a 4.9% increase in face-to-face support worker time for every 0.1 unit increase in EQ-5D (95% CI 0.3-9.6, P = 0.038), while females had an additional 5.1% of their total contact time with support workers compared with males (95% CI 1.9-8.4, P = 0.002). In an analysis without EQ-5D, older patients had a greater proportion of support worker time ( P = 0.006). Other factors associated with support worker input include the referral source, intensity of care, usual living arrangements and proportion of support staff in a team. Results indicate that patient- and team-level factors are a determinant in the proportion of support worker care delivered to older people in the community, suggesting that it may be appropriate to introduce a more explicit targeted deployment of support workers based on patient-level characteristics, which may facilitate a more effective use of qualified practitioner time for more complex, dependent patients. [ABSTRACT FROM AUTHOR]

Background: The United Kingdom NHS Breast Screening Programme was established in 1988, and women aged between 50 and 70 are routinely invited at three yearly intervals. Expected United Kingdom interval cancer rates have been calculated previously, but this is the first publication from an exercise to collate individual-based interval cancer data at a national level.Methods: Interval cancer case ascertainment is achieved by the regular exchange of data between Regional Breast Screening Quality Assurance Reference Centres and Cancer Registries. The present analysis includes interval cancers identified in women screened between 1st April 1997 and 31st March 2003, who were aged between 50 and 64 at the time of their last routine screen.Results: In the periods >0-<12 months, 12-<24 months and 24-<36 months after a negative screen, we found overall interval cancer rates and regional ranges of 0.55 (0.43-0.76), 1.13 (0.92-1.47) and 1.22 (0.93-1.57) per 1000 women screened, respectively. Rates in the period 33-<36 months showed a decline, possibly associated with early re-screening or delayed presentation.Conclusions: Interval cancer rates were higher than the expected rates in the 24-month period after a negative screen, but were similar to published results from other countries. Increases in background incidence may mean that the expected rates are underestimated. It is also possible that, as a result of incomplete case ascertainment, interval cancers rates were underestimated in some regions in which rates were less than the expected. [ABSTRACT FROM AUTHOR]

An adaptive wavelet neural network (AWNN)-based method has been proposed to determine dynamic available transfer capability (DATC) in the electricity markets, having bilateral as well as multilateral contracts. Mexican hat wavelet basis function has been used as the activation function in the hidden layer of the network. Wavelet parameters, that is, translations and dilations of the AWNN, have been initialised using Euclidean distance-based clustering method. The AWNN has been trained using back propagation gradient descent training algorithm. The relevant features to be used, as input to the AWNN, are identified using a random forest technique. To demonstrate the effectiveness of the proposed AWNN-based method for the DATC determination, it has been tested on 39-bus New England system and a 246-bus Indian system and its results have been compared to the radial basis function neural network (RBFNN). [ABSTRACT FROM AUTHOR]

A geometrical analysis of the meander decorative patterns on a Roman pavement mosaic found at the Roman villa in Chedworth, UK, is presented. The analysis reveals that the intricate swastika meander pattern consisting of four closed curves could easily have been constructed using a very simple hypothesized algorithm. The algorithm also explains the design of Roman swastika meanders found throughout the Roman Empire. Connections are indicated between these patterns and the sona traditional art of Angola as well as the kolam traditional art of Tamil South India. The analysis and algorithm described have applications to the classification of geometric mosaic patterns, the design of new patterns and the reconstruction of mosaics that have been partially destroyed by the ravages of time. [ABSTRACT FROM AUTHOR]

A terrestrial laser scanner was used to take four scans of an area of trees, approximately 480 m2 in area, within a coniferous tree stand situated in Leicestershire, UK. A number of measurements were extracted from the point cloud and compared with field measurements. Automatic stem recognition was achieved for all stems except those at the edge of the study plot. From the locations of detected stems, diameter at breast height (DBH) was measured with two least-squares shape-fitting algorithms and a circular Hough transformation method; the results were then compared with field measurements. The root mean squared error (RMSE) for DBH measurement from the laser scanner was found to be in the range 0.019-0.037 m, using three measures. Stem density (1031 stems ha-1) and basal area (73 m2 ha-1) were also measured with reasonable accuracy. Estimation of tree volume was not as successful, in contradiction to previous research, as upper diameters and heights of trees could not be measured. This was probably a result of previous research being focused on low-density forest stands. This study presents an assessment of laser scanning capabilities in a forest environment with high (1000 stems ha-1) stand density, and finds automation of the analysis to yield some important tree and stand variables to be very effective. [ABSTRACT FROM AUTHOR]

The Tower of London Test (TOL) used to assess executive functions was inspired in Artificial Intelligence tasks used to test problem-solving algorithms. In this study, we compare the performance of humans and of exploration algorithms. Instead of absolute execution times, we focus on how the execution time varies with the tasks and/or the number of moves. This approach used in Algorithmic Complexity provides a fair comparison between humans and computers, although humans are several orders of magnitude slower. On easy tasks (1 to 5 moves), healthy elderly persons performed like exploration algorithms using bounded memory resources, i.e., the execution time grew exponentially with the number of moves. This result was replicated with a group of healthy young participants. However, for difficult tasks (5 to 8 moves) the execution time of young participants did not increase significantly, whereas for exploration algorithms, the execution time keeps on increasing exponentially. A pre-and post-test control task showed a 25% improvement of visuo-motor skills but this was insufficient to explain this result. The findings suggest that naive participants used systematic exploration to solve the problem but under the effect of practice, they developed markedly more efficient strategies using the information acquired during the test. [ABSTRACT FROM AUTHOR]

In this article I offer a challenge to the usual account of the development of the Manchester Baby. In doing so, I focus on the contribution made to the project by the topologist Max Newman and other members of the Manchester Department of Mathematics. Based on a re-examination of the primary source material, I suggest that a much more significant role was played by mathematicians than is allowed for in the dominant discourse. I argue that there was a single computer-building project at Manchester in the years immediately following World War II which was conceived, led, funded, supplied and staffed by Newman supported by his long-time friend Patrick Blackett. [ABSTRACT FROM AUTHOR]

The aim of the study is to devise a new reliable dynamic route guidance approach by integrating the A* algorithm, the concept of reliability and an existing route guidance method into a single package. A new purpose-developed software tool, the Imperial College Navigation Software (ICNavS), is presented, so as to implement and demonstrate the new approach on a real road network, using simulated data. A summary of the background of the program is given, followed by a procedure developed in order to model the features of real road networks as well as missing data. Then, a simulation experiment on a part of West London's road network is carried out and the results are presented. [ABSTRACT FROM AUTHOR]

Twenty samples from soils developed over the Northampton Sand ironstone formation were collected from, in and around the town of Wellingborough, Northamptonshire, UK. The total arsenic (As) content ranged from ca. 20-100 mg kg- 1and the bioaccessible As content, as measured by a physiologically based in vitro extraction test, ranged from 1 to 6 mg kg- 1. A chemometric algorithm for mixture resolution, when applied to total element and total organic carbon concentration of the soils, was able to identify chemically distinct soil constituents and their associated As content. Multiple linear regression (MLR) modelling, using the As content of the intrinsic soil constituents and their first order interactions as independent variables, was able to predict the bioaccessible As content of the soils (R2 = 0.85) with an uncertainty of 1.33 mg kg- 1. Although the MLR model showed that the interactions between the soil constituents were the key factors controlling the bioaccessible fraction in each soil most of the total As was found to be bound to an Fe oxide soil constituent. The model predictions shown are currently only valid for the geological and soil chemical setting investigated here, extrapolation to other geological settings would require additional investigations. [ABSTRACT FROM AUTHOR]