Shaping Attitudes in Public Child Welfare: An Innovative MSW Training Program

Children investigated by child welfare are at significant risk for poor cognitive, emotional, social, behavioral and economic outcomes. In 2000, California formed the Child Welfare Services Group to propose changes in how child welfare services are delivered, the CWS Redesign. California State University, Long Beach’s child welfare training program developed its complement. Fundamentally, Redesign calls for partnering with families and communities to strengthen families, prevent unnecessary placements or re-unite families successfully. These changes are a paradigm shift in attitudes toward birth families and communities. In a qualitative study, interns logged their observations and subsequent impressions of CWS-Client encounters to explore how attitudes are learned. Majority of interns observed positive, collaborative encounters and perceived birth parents as motivated. Their impressions support introducing interns to birth families on the front-end of CWS training

A study to identify factors impacting upon the decision-making processes of elective home education professionals when determining the suitability of parental provision

This thesis identifies the factors influencing the decision-making of home education professionals as they attempt to establish whether children are receiving a suitable education at home. This task represents the core element of a home education officer’s role yet it is fraught with challenges. The regulatory framework which underpins England’s system of elective home education is problematic. Emanating from archaic legislation, government policy in this area is sparse. Consequently, the practice of officers overseeing home education lacks the regulatory scaffolding evident within school provision. The absence of comprehensive policy has left professionals vulnerable. Customary practice is regularly criticised by home educators and their advocates. Detractors within the home education community regularly reject the validity of the professional role, accusing officers of re-interpreting guidance. Recent interest in home education has led to an increase in academic and advocacy-based research. However, with a focus on parental motives and children’s outcomes, the practice of professionals has been neglected. This research aims to readdress the balance by affirming professionals’ stakeholder status and exploring their perspective of contemporary home education. This study investigates the interplay between the regulatory and the personal within the professional practice of home education officers. Similar to the parental community, the realm of the professional is typically beyond the reach of outsiders. This then is the intimate insider project of a home education professional. Phenomenologically motivated, unstructured conversations with 8 home education officers are explored to reveal previously inaccessible practice details. Interpretive analysis of personal accounts indicates the extent to which home education guidance is embedded within practice, activated via an experiential toolkit. Research findings demonstrate professional practice is primarily influenced by education law and whilst procedures vary, professional beliefs are consensual and consistent. The findings of this research provide valuable insights for policy makers and the suggested recommendations could significantly improve the infrastructure and management of elective home education

Advanced Fluorescence Microscopy Techniques-FRAP, FLIP, FLAP, FRET and FLIM

Fluorescence microscopy provides an efficient and unique approach to study fixed and living cells because of its versatility, specificity, and high sensitivity. Fluorescence microscopes can both detect the fluorescence emitted from labeled molecules in biological samples as images or photometric data from which intensities and emission spectra can be deduced. By exploiting the characteristics of fluorescence, various techniques have been developed that enable the visualization and analysis of complex dynamic events in cells, organelles, and sub-organelle components within the biological specimen. The techniques described here are fluorescence recovery after photobleaching (FRAP), the related fluorescence loss in photobleaching (FLIP), fluorescence localization after photobleaching (FLAP), Forster or fluorescence resonance energy transfer (FRET) and the different ways how to measure FRET, such as acceptor bleaching, sensitized emission, polarization anisotropy, and fluorescence lifetime imaging microscopy (FLIM). First, a brief introduction into the mechanisms underlying fluorescence as a physical phenomenon and fluorescence, confocal, and multiphoton microscopy is given. Subsequently, these advanced microscopy techniques are introduced in more detail, with a description of how these techniques are performed, what needs to be considered, and what practical advantages they can bring to cell biological research

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious

Total Quality Management

Many U.S. executives have come to realize that in order to regain their share of the marketplace, a process must be set in motion geared towards achieving higher quality levels, and increased productivity. This can be accomplished through Total Quality Management (TQM). Total Quality Management is a continuous improvement process affecting all functions at all levels of an organization. TQM integrates fundamental technical tools, e.g., Quality Function Deployment, Taguchi Methods, Statistical Process Control, and the Just-In-Time methodology, and existing management techniques into a disciplined approach focused on continuous improvement. The objective of this research report was to examine the ultimate integration of Man, Methods, Machine, and Material; better known as Total Quality Management