Verification and validation of numerical models of the transport of insulation debris

Damage to insulation materials located near to a primary circuit coolant leak may compromise the operation of the emergency core cooling system (ECCS). Insulation material in the form of mineral wool fiber agglomerates (MWFA) maybe transported to the containment sump strainers, where they may block or penetrate the strainers. Though the impact of MWFA on the pressure drop across the strainers is minimal, corrosion products formed over time may also accumulate in the fiber cakes on the strainers, which can lead to a significant increase in the strainer pressure drop and result in cavitation in the ECCS. An experimental and theoretical study performed by the Helmholtz-Zentrum Dresden-Rossendorf and the Hochschule Zittau/Görlitz is investigating the phenomena that maybe observed in the containment vessel during a primary circuit coolant leak. The study entails the generation of fiber agglomerates, the determination of their transport properties in single and multi-effect experiments and the long-term effect that corrosion and erosion of the containment internals by the coolant has on the strainer pressure drop. The focus of this paper is on the verification and validation of numerical models that can predict the transport of MWFA. A number of pseudo-continuous dispersed phases of spherical wetted agglomerates represent the MWFA. The size, density, the relative viscosity of the fluid-fiber agglomerate mixture and the turbulent dispersion all affect how the fiber agglomerates are transported. In the cases described here, the size is kept constant while the density is modified. This definition affects both the terminal velocity and volume fraction of the dispersed phases. Note that the relative viscosity is only significant at high concentrations. Three single effect experiments were used to provide validation data on the transport of the fiber agglomerates under conditions of sedimentation in quiescent fluid, sedimentation in a horizontal flow and suspension in a horizontal flow. The experiments were performed in a rectangular column for the quiescent fluid and a racetrack type channel that provided a near uniform horizontal flow. The numerical models of sedimentation in the column and the racetrack channel found that the sedimentation characteristics are consistent with the experiments. For channel suspension, the heavier fibers tend to accumulate at the channel base even at high velocities, while lighter phases are more likely to be transported around the channel.

Validation of the Paediatric food allergy quality of life questionnaire (PFA-QL)

Objective - The aim of the current study was to validate child (PFA-QL) and parent–proxy (PFA-QL-PF) versions of the scale in a specialist allergy clinic and in parents of children with food allergy. Methods - For the clinic sample, a generic QoL scale (PedsQL) and the PFA-QL were completed by 103 children (age 6–16 yrs) with peanut or tree nut allergy; test–retest reliability of the PFA-QL was tested in 50 stable patients. For the non-clinical sample, 756 parents of food allergic children completed the PFA-QL-PF, the Child Health Questionnaire (CHQ-PF50), Food Allergy Quality of Life Parental Burden Scale (FAQL-PB) and a Food Allergy Impact Measure. Results - The PFA-QL and PFA-QL-PF had good internal consistency (a's of 0.77–0.82), and there was moderate-to-good agreement between the generic- and disease-specific questionnaires. The PFA-QL was stable over time in the clinic sample, and in both samples, girls were reported to have poorer QoL than boys. Conclusions - The PFA-QL and PFA-QL-PF are reliable and valid scales for use in both clinical and non-clinical populations. Unlike other available tools, they were developed and validated in the UK and thus provide a culture-specific choice for research, clinical trials and clinical practice in the UK. Validation in other countries is now needed.

Validation of the food allergy quality of life:parental burden questionnaire in the UK

Purpose - Food allergy can have a profound effect on quality of life (QoL) of the family. The Food Allergy Quality of Life—Parental Burden Questionnaire (FAQL-PB) was developed on a US sample to assess the QoL of parents with food allergic children. The aim of this study was to examine the reliability and validity of the FAQL-PB in a UK sample and to assess the effect of asking about parental burden in the last week compared with parental burden in general, with no time limit for recall given. Methods - A total of 1,200 parents who had at least one child with food allergy were sent the FAQL-PB and the Child Health Questionnaire (CHQ-PF50); of whom only 63 % responded. Results - Factor analysis of the FAQL-PB revealed two factors: limitations on life and emotional distress. The total scale and the two sub-scales had high internal reliability (all a > 0.85). There were small to moderate but significant correlations between total FAQL-PB scores and health and parental impact measures on the CHQ-PF50 (p < 0.01). Significantly greater parental burden was reported for the no-time limited compared with the time-limited version (p < 0.01). Conclusions - The FAQL-PB is a reliable and valid measure for use in the UK. The scale could be used in clinic to assess the physical and emotional quality of life in addition to the impact on total quality of life.

Regression analysis of ranked segment parameters for optic nerve head classification:a pilot study

Purpose: To determine whether curve-fitting analysis of the ranked segment distributions of topographic optic nerve head (ONH) parameters, derived using the Heidelberg Retina Tomograph (HRT), provide a more effective statistical descriptor to differentiate the normal from the glaucomatous ONH. Methods: The sample comprised of 22 normal control subjects (mean age 66.9 years; S.D. 7.8) and 22 glaucoma patients (mean age 72.1 years; S.D. 6.9) confirmed by reproducible visual field defects on the Humphrey Field Analyser. Three 10°-images of the ONH were obtained using the HRT. The mean topography image was determined and the HRT software was used to calculate the rim volume, rim area to disc area ratio, normalised rim area to disc area ratio and retinal nerve fibre cross-sectional area for each patient at 10°-sectoral intervals. The values were ranked in descending order, and each ranked-segment curve of ordered values was fitted using the least squares method. Results: There was no difference in disc area between the groups. The group mean cup-disc area ratio was significantly lower in the normal group (0.204 ± 0.16) compared with the glaucoma group (0.533 ± 0.083) (p < 0.001). The visual field indices, mean deviation and corrected pattern S.D., were significantly greater (p < 0.001) in the glaucoma group (-9.09 dB ± 3.3 and 7.91 ± 3.4, respectively) compared with the normal group (-0.15 dB ± 0.9 and 0.95 dB ± 0.8, respectively). Univariate linear regression provided the best overall fit to the ranked segment data. The equation parameters of the regression line manually applied to the normalised rim area-disc area and the rim area-disc area ratio data, correctly classified 100% of normal subjects and glaucoma patients. In this study sample, the regression analysis of ranked segment parameters method was more effective than conventional ranked segment analysis, in which glaucoma patients were misclassified in approximately 50% of cases. Further investigation in larger samples will enable the calculation of confidence intervals for normality. These reference standards will then need to be investigated for an independent sample to fully validate the technique. Conclusions: Using a curve-fitting approach to fit ranked segment curves retains information relating to the topographic nature of neural loss. Such methodology appears to overcome some of the deficiencies of conventional ranked segment analysis, and subject to validation in larger scale studies, may potentially be of clinical utility for detecting and monitoring glaucomatous damage. © 2007 The College of Optometrists.

Parametric study of femtosecond inscription of microstructures for OCT artefact fabrication

As optical coherence tomography (OCT) becomes widespread, validation and characterization of systems becomes important. Reference standards are required to qualitatively and quantitatively measure the performance between difference systems. This would allow the performance degradation of the system over time to be monitored. In this report, the properties of the femtosecond inscribed structures from three different systems for making suitable OCT characterization artefacts (phantoms) are analyzed. The parameter test samples are directly inscribed inside transparent materials. The structures are characterized using an optical microscope and a swept-source OCT. The high reproducibility of the inscribed structures shows high potential for producing multi-modality OCT calibration and characterization phantoms. Such that a single artefact can be used to characterize multiple performance parameters such the resolution, linearity, distortion, and imaging depths. © 2012 SPIE.

An artificial neural network stratifies the risks of reintervention and mortality after endovascular aneurysm repair:a retrospective observational study

Background Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. Methods Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. Results 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/ volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p0.001) Conclusion This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

B2B service brand identity:scale development and validation

Several brand identity frameworks have been published in the B2C and the B2B brand marketing literature. A reliable, valid and parsimonious service brand identity scale that empirically establishes the construct's dimensionality in a B2B market has yet to be developed. This paper reports the findings of a study conducted amongst 421 senior executives working in the UK IT Service sector to develop and validate a B2B Service Brand Identity Scale. Following established scale development procedures support is provided for a B2B Service Brand Identity Scale comprising five dimensions; employee and client focus, visual identity, brand personality, consistent communications and human resource initiatives. Concluding remarks discuss theoretical and managerial implications with limitations and directions for future research. © 2011 Elsevier Inc.

Development and validation of an instrument to predict online student success using faculty perceptions

Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Social determinants of fruit and vegetable intake and validation of Pro-Children Eating Habits Questionnaire for 3rd and 5th grade children

BACKGROUND: The Pro Children Eating Habits Questionnaire has been evaluated as a valid and reliable tool in Europe to measure determinants of fruit and vegetable intake for children; however, it has not been validation for United States populations. The purpose of this study was to (1) assess the reliability and discrimination validity of fruit and vegetable correlates for the Pro Children Eating Habits Questionnaire; (2) investigate the predictive validity of determinants of fruit and vegetable consumption for multi-ethnic elementary school children; and, (3) to assess the association of social determinants with fruit and vegetable consumption. METHODS: One hundred and thirty elementary school students from the 3rd and 5th grades completed this cross-sectional study. RESULTS: Fruit and vegetable determinants, had satisfactory internal consistencies. No differences were found between the test and the retest for the individual questions with the exception of the question for mean perceived vegetable intake. The discriminatory validity indicated the questionnaire could show differences across grade and gender levels for barriers of fruit and vegetables but not for other factors. Grade together with gender explained barriers to eating fruit and vegetables. Greater availability of fruit in the home and school was associated with higher frequency of consumption. CONCLUSIONS: The results of this study indicate the Pro-Children Eating Habits Questionnaire may be a reliable and valid tool for assessing fruit and vegetable consumption of children in the United States.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Validation of an Analytical Method for the Identification of SmartWater CSI Forensic Marking Technology

SmartWater is a chemical taggant used as a crime deterrent. The chemical taggant is a colorless liquid that fluoresces yellow under ultra-violet (UV) light and contains distinctive, identifiable and traceable elemental composition. For instance, upon a break and entry scenario, the burglar is sprayed with a solution that has an elemental signature custom-made to a specific location. The residues of this taggant persist on skin and other objects and can be easily recovered for further analysis. The product has been effectively used in Europe as a crime deterrent and has been recently introduced in South Florida. In 2014, Fourt Lauderdale Police Department reported the use of SmartWater products with a reduction in burglaries of 14% [1]. The International Forensic Research Institute (IFRI) at FIU validated the scientific foundation of the methods of recovery and analysis of these chemical tagging systems using LA-ICP-MS. Analytical figures of merit of the method such as precision, accuracy, limits of detection, linearity and selectivity are reported in this study. Moreover, blind samples were analyzed by LA-ICP-MS to compare the chemical signatures to the company’s database and evaluate error rates and the accuracy of the method. This study demonstrated that LA-ICP-MS could be used to effectively detect these traceable taggants to assist law enforcement agencies in the United States with cases involving transfer of these forensic coding systems.

Patterns of weight change after the diagnosis of type 2 diabetes in Scotland and their relationship with glycaemic control, mortality and cardiovascular outcomes: a retrospective cohort study

Acknowledgements The authors would like to thank the Scottish Diabetes Research Network Epidemiology Group for granting permission to use this database. They also thank the data management team in the University of Aberdeen who were the initial conduit for access to these data and also provided validation to the various data cleaning criteria applied. Jeremy J Walker, University of Edinburgh, was invaluable for the original funding application and initial exploration of data. HSRU is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Funding Chief Scientist Office (CSO) reference number: CZG/2/571.

Distribution network reconfiguration validation with uncertain loads - network configuration determination and application

Automatic load transfer (ALT) on the 11 kV network is the process by which circuit breakers on the network are switched to form open points in order to feed load from different primary substations. Some of the potential benefits that may be gained from dynamically using ALT include maximising utilisation of existing assets, voltage regulation and reduced losses. One of the key issues, that has yet to be properly addressed in published research, is how to validate that the modelled benefits really exist. On an 11 kV distribution network where the load is continually changing and the load on each distribution substation is unlikely to be monitored - reduction in losses from moving the normally open point is particularly difficult to prove. This study proposes a method to overcome this problem and uses measured primary feeder data from two parts of the Western Power Distribution 11 kV Network under different configurations. The process of choosing the different configurations is based on a heuristic modelling method of locating minimum voltages to help reduce losses.

A Qualitative Study of Contextual Factors’ Impact on the Adaptation of a Caregiver-mediated Early Autism Intervention in South Africa

Background: Autism Spectrum Disorder (ASD) is a major global health challenge as the majority of individuals with ASD live in low- and middle-income countries (LMICs) and receive little to no services or support from health or social care systems. Despite this global crisis, the development and validation of ASD interventions has almost exclusively occurred in high-income countries, leaving many unanswered questions regarding what contextual factors would need to be considered to ensure the effectiveness of interventions in LMICs. This study sought to conduct explorative research on the contextual adaptation of a caregiver-mediated early ASD intervention for use in a low-resource setting in South Africa.

Methods: Participants included 22 caregivers of children with autism, including mothers (n=16), fathers (n=4), and grandmothers (n=2). Four focus groups discussions were conducted in Cape Town, South Africa with caregivers and lasted between 1.5-3.5 hours in length. Data was recorded, translated, and transcribed by research personnel. Data was then coded for emerging themes and analyzed using the NVivo qualitative data analysis software package.

Results: Nine contextual factors were reported to be important for the adaptation process including culture, language, location of treatment, cost of treatment, type of service provider, familial needs, length of treatment, support, and parenting practices. One contextual factor, evidence-based treatment, was reported to be both important and not important for adaptation by caregivers. The contextual factor of stigma was identified as an emerging theme and a specifically relevant challenge when developing an ASD intervention for use in a South African context.

Conclusions: Eleven contextual factors were discussed in detail by caregivers and examples were given regarding the challenges, sources, and preferences related to the contextual adaptation of a parent-mediated early ASD intervention in South Africa. Caregivers reported a preference for an affordable, in-home, individualized early ASD intervention, where they have an active voice in shaping treatment goals. Distrust of community-based nurses and health workers to deliver an early ASD intervention and challenges associated with ASD-based stigma were two unanticipated findings from this data set. Implications for practice and further research are discussed.