The factor structure of executive function in childhood and adolescence

Executive functioning (EF) plays a major role in many domains of human behaviour, including self-regulation, academic achievement, and even sports expertise. While a significant proportion of cross-sectional research has focused on the developmental pathways of EF, the existing literature is fractionated due to a wide range of methodologies applied to narrow age ranges, impeding comparison across a broad range of age groups. The current study used a cross-sectional design to investigate the factor structure of EF within late childhood and adolescence. A total of 2166 Flemish children and adolescents completed seven tasks of the Cambridge Brain Sciences test battery. Based on the existing literature, a Confirmatory Factor Analysis was performed, which indicated that a unitary factor model provides the best fit for the youngest age group (7–12 years). For the adolescents (12–18 years), the factor structure consists of four different components, including working memory, shifting, inhibition and planning. With regard to differences between early (12–15 years) and late (15–18 years) adolescents, working memory, inhibition and planning show higher scores for the late adolescents, while there was no difference on shifting. The current study is one of the first to administer the same seven EF tests in a considerably large sample of children and adolescents, and as such contributes to the understanding of the developmental trends in EF. Future studies, especially with longitudinal designs, are encouraged to further increase the knowledge concerning the factor structure of EF, and the development of the different EF components

Haplotype Analysis Improved Evidence for Candidate Genes for Intramuscular Fat Percentage from a Genome Wide Association Study of Cattle

In genome wide association studies (GWAS), haplotype analyses of SNP data are neglected in favour of single point analysis of associations. In a recent GWAS, we found that none of the known candidate genes for intramuscular fat (IMF) had been identified. In this study, data from the GWAS for these candidate genes were re-analysed as haplotypes. First, we confirmed that the methodology would find evidence for association between haplotypes in candidate genes of the calpain-calpastatin complex and musculus longissimus lumborum peak force (LLPF), because these genes had been confirmed through single point analysis in the GWAS. Then, for intramuscular fat percent (IMF), we found significant partial haplotype substitution effects for the genes ADIPOQ and CXCR4, as well as suggestive associations to the genes CEBPA, FASN, and CAPN1. Haplotypes for these genes explained 80% more of the phenotypic variance compared to the best single SNP. For some genes the analyses suggested that there was more than one causative mutation in some genes, or confirmed that some causative mutations are limited to particular subgroups of a species. Fitting the SNPs and their interactions simultaneously explained a similar amount of the phenotypic variance compared to haplotype analyses. Haplotype analysis is a neglected part of the suite of tools used to analyse GWAS data, would be a useful method to extract more information from these data sets, and may contribute to reducing the missing heritability problem

Genome-wide association studies for feedlot and growth traits in cattle

A genome wide-association study for production traits in cattle was carried out using genotype data from the 10K Affymetrix (Santa Clara, CA) and the 50K Illumina (San Diego, CA) SNP chips. The results for residual feed intake (RFI), BW, and hip height in 3 beef breed types (Bos indicus, Bos taurus, and B. indicus × B. taurus), and for stature in dairy cattle, are presented. The aims were to discover SNP associated with all traits studied, but especially RFI, and further to test the consistency of SNP effects across different cattle populations and breed types. The data were analyzed within data sets and within breed types by using a mixed model and fitting 1 SNP at a time. In each case, the number of significant SNP was more than expected by chance alone. A total of 75 SNP from the reference population with 50K chip data were significant (P < 0.001) for RFI, with a false discovery rate of 68%. These 75 SNP were mapped on 24 different BTA. Of the 75 SNP, the 9 most significant SNP were detected on BTA 3, 5, 7, and 8, with P ≤ 6.0 × 10 . In a population of Angus cattle divergently selected for high and low RFI and 10K chip data, 111 SNP were significantly (P < 0.001) associated with RFI, with a false discovery rate of 7%. Approximately 103 of these SNP were therefore likely to represent true positives. Because of the small number of SNP common to both the 10K and 50K SNP chips, only 27 SNP were significantly (P < 0.05) associated with RFI in the 2 populations. However, other chromosome regions were found that contained SNP significantly associated with RFI in both data sets, although no SNP within the region showed a consistent effect on RFI. The SNP effects were consistent between data sets only when estimated within the same breed type

Techno-economic evaluation of five-level nested neutral point clamped converter topology for transformer-less connection of high-power wind energy conversion systems

Developers and operators are interested in improving the reliability and reducing the associated costs of wind power plants (WPPs) because of the continuous increase in the power capacity of wind energy conversion systems (WECSs) and the increasing development of WPPs. The electrical subsystem of the WPP experiences the highest failure rate and constitutes a significant proportion of its total cost. Reliability of the WECS can be increased and its cost reduced by eliminating the wind turbine transformer from the electrical subsystem. This study gives a techno-economic evaluation of a five-level nested neutral point clamped (NNPC) converter topology for transformer-less connection of high- power WECSs. The approach entailed the calculation of reliability of five-level NNPC converter topology deployed in the grid-side of a WECSs. This method presents a mathematical formula for deriving the reliability of a five-level NNPC converter topology by using the reliability block diagram and reliability estimation-based models in the military handbook (MIL-HDBK-217F). The cost analysis model shows that the total cost of the five-level diode clamped converter topology was higher than the five-level NNPC converter topology. The study could be extended by carrying out accurate modelling of the mission profile of the presented converter by using multi-domain simulation technique

Structural models of genome-wide covariance identify multiple common dimensions in autism

Common genetic variation has been associated with multiple symptoms in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous neurodevelopmental condition is limited. Here, we developed a structural equation modelling framework to directly model genome-wide covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent using a case-only design. We identified three independent genetic factors most strongly linked to language/cognition, behaviour and motor development, respectively, when studying a population-representative sample (N=5,331). These analyses revealed novel associations. For example, developmental delay in acquiring personal-social skills was inversely related to language, while developmental motor delay was linked to self-injurious behaviour. We largely confirmed the three-factorial structure in independent ASD-simplex families (N=1,946), but uncovered simplex-specific genetic overlap between behaviour and language phenotypes. Thus, the common genetic architecture in ASD is multi-dimensional and contributes, in combination with ascertainment-specific patterns, to phenotypic heterogeneity

The strike rate index: a new index for journal quality based on journal size and the h-index of citations

Quantifying the impact of scientific research is almost always controversial, and there is a need for a uniform method that can be applied across all fields. Increasingly, however, the quantification has been summed up in the impact factor of the journal in which the work is published, which is known to show differences between fields. Here the h-index, a way to summarize an individual's highly cited work, was calculated for journals over a twenty year time span and compared to the size of the journal in four fields, Agriculture, Condensed Matter Physics, Genetics and Heredity and Mathematical Physics. There is a linear log-log relationship between the h-index and the size of the journal: the larger the journal, the more likely it is to have a high h-index. The four fields cannot be separated from each other suggesting that this relationship applies to all fields. A strike rate index (SRI) based on the log relationship of the h-index and the size of the journal shows a similar distribution in the four fields, with similar thresholds for quality, allowing journals across diverse fields to be compared to each other. The SRI explains more than four times the variation in citation counts compared to the impact factor

Decision-support for arsenic- and salt- mitigation in Bangladesh: the ASTRA approach

Bangladesh faces a growing water crisis. Limitations to safe water access arise from the widespread pathogenic contamination of its surface waters, the severe arsenic contamination of its aquifers and the growing salinity in the country’s coastal regions. Appropriate water supply methods are identified for some of these contexts, it is challenging to select resilient water supply solutions for the low-income, rural areas of Bangladesh. The ASTRA tool is developed to support the identification of potentially appropriate drinking water methods and to aid their implementation in this context. It can be seen as the combination of a multidisciplinary sourcebook and a decision-support instrument. This paper outlines the main mitigation routes as the (i) targeting of contamination-free groundwater, (ii) treatment of arsenic- and salt-contaminated aquifers and (iii) utilization of non-groundwater sources. The paper also describes the tool-inventory and the context factors applied to determine functional ranges of the included water supply methods