Review of the area planning process (b)

This paper offers a commentary on the area planning reports form primary schools published by each of the Education and Library Boards (ELB) in June 2014. The format of the reports are broadly similar for each ELB, although there are some differences amongst them. All provide an overview on the policy context for the area planning process, a statistical picture of the schools in the ELB and detail on the issues considered for sets of schools within the ELB.

Distinctive effects of G-CSF, GM-CSF and TNFalpha on neutrophil apoptosis in systemic lupus erythematosus.

OBJECTIVE: To investigate the influence of culture with G-CSF GM-CSF and TNFalpha on neutrophil apoptosis, comparing neutrophils from SLE patients with rheumatoid arthritis (RA) patients and healthy control subjects. METHODS: Neutrophils were isolated from SLE (n= 10), RA (n= 10) and healthy control subjects (n= 10), and cultured with two different concentrations of G-CSF, GM-CSF and TNFalpha. Proportion of apoptotic neutrophils at T=0, T=2hrs and T=24hrs was measured using FITC-labelled annexinV and flow cytometry. RESULTS: Significantly more neutrophils were apoptotic at T=0 in the SLE subjects than in the other groups (median, range--Control 3.5% (0.3-7.9) SLE 9.5% (2.9-29.1) RA 3.0% (0.4-23.0) p

Prosodic Characteristics of Skilled Reading: Fluency and Expressiveness in 8- 10-year-old Readers

Statistical methods of describing prosody were used to study fluency, expressiveness and their relationship among 8-10-year-old readers. There were robust relationships between expressiveness and variables associated with pitch mobility; and between fluency and measures associated with temporal organization. Interactions indicated that the relationships were not simple. Differences between groups depended on sentence content and position. Some measures offer a basis for rules aimed at assigning individuals to skill categories. The effects suggest psychological hypotheses about the underlying mechanisms.

High tolerance to gate misalignment in low voltage gate-underlap double gate MOSFETs

.In this letter, we demonstrate for the first time that gate misalignment is not a critical limiting factor for low voltage operation in gate-underlap double gate (DG) devices. Our results show that underlap architecture significantly extends the tolerable limit of gate misalignment in 25 nm devices. DG MOSFETs with high degree of gate misalignment and optimal gate-underlap design can perform comparably or even better than self-aligned nonunderlap devices. Results show that spacer-to-straggle (s/sigma) ratio, a key design parameter for underlap devices, should be within the range of 2.3-3.0 to accommodate back gate misalignment. These results are very significant as the stringent process control requirements for achieving self-alignment in nanoscale planar DG MOSFETs are considerably relaxed

Environmental context explains Levy and Brownian movement patterns of marine predators

An optimal search theory, the so-called Levy-flight foraging hypothesis(1), predicts that predators should adopt search strategies known as Levy flights where prey is sparse and distributed unpredictably, but that Brownian movement is sufficiently efficient for locating abundant prey(2-4). Empirical studies have generated controversy because the accuracy of statistical methods that have been used to identify Levy behaviour has recently been questioned(5,6). Consequently, whether foragers exhibit Levy flights in the wild remains unclear. Crucially, moreover, it has not been tested whether observed movement patterns across natural landscapes having different expected resource distributions conform to the theory's central predictions. Here we use maximum-likelihood methods to test for Levy patterns in relation to environmental gradients in the largest animal movement data set assembled for this purpose. Strong support was found for Levy search patterns across 14 species of open-ocean predatory fish (sharks, tuna, billfish and ocean sunfish), with some individuals switching between Levy and Brownian movement as they traversed different habitat types. We tested the spatial occurrence of these two principal patterns and found Levy behaviour to be associated with less productive waters (sparser prey) and Brownian movements to be associated with productive shelf or convergence-front habitats (abundant prey). These results are consistent with the Levy-flight foraging hypothesis(1,7), supporting the contention(8,9) that organism search strategies naturally evolved in such a way that they exploit optimal Levy patterns.

How crucial is back gate misalignment/oversize in double gate MOSFETs for ultra-low-voltage analog/rf applications?

In the present work, by investigating the influence of source/drain (S/D) extension region engineering (also known as gate-underlap architecture) in planar Double Gate (DG) SOI MOSFETs, we offer new design insights to achieve high tolerance to gate misalignment/oversize in nanoscale devices for ultra-low-voltage (ULV) analog/rf applications. Our results show that (i) misaligned gate-underlap devices perform significantly better than DC devices with abrupt source/drain junctions with identical misalignment, (ii) misaligned gate underlap performance (with S/D optimization) exceeds perfectly aligned DG devices with abrupt S/D regions and (iii) 25% back gate misalignment can be tolerated without any significant degradation in cut-off frequency (f(T)) and intrinsic voltage gain (A(VO)). Gate-underlap DG devices designed with spacer-to-straggle ratio lying within the range 2.5 to 3.0 show best tolerance to misaligned/oversize back gate and indeed are better than self-aligned DG MOSFETs with non-underlap (abrupt) S/D regions. Impact of gate length and silicon film thickness scaling is also discussed. These results are very significant as the tolerable limit of misaligned/oversized back gate is considerably extended and the stringent process control requirements to achieve self-alignment can be relaxed for nanoscale planar ULV DG MOSFETs operating in weak-inversion region. The present work provides new opportunities for realizing future ULV analog/rf design with nanoscale gate-underlap DG MOSFETs. (C) 2008 Elsevier Ltd. All rights reserved.

Psychology Statistics for Dummies

The quick, easy way to master all the statistics you'll ever need The bad news first: if you want a psychology degree you'll need to know statistics. Now for the good news: Psychology Statistics For Dummies. Featuring jargon-free explanations, step-by-step instructions and dozens of real-life examples, Psychology Statistics For Dummies makes the knotty world of statistics a lot less baffling. Rather than padding the text with concepts and procedures irrelevant to the task, the authors focus only on the statistics psychology students need to know. As an alternative to typical, lead-heavy statistics texts or supplements to assigned course reading, this is one book psychology students won't want to be without. Ease into statistics – start out with an introduction to how statistics are used by psychologists, including the types of variables they use and how they measure them Get your feet wet – quickly learn the basics of descriptive statistics, such as central tendency and measures of dispersion, along with common ways of graphically depicting information Meet your new best friend – learn the ins and outs of SPSS, the most popular statistics software package among psychology students, including how to input, manipulate and analyse data Analyse this – get up to speed on statistical analysis core concepts, such as probability and inference, hypothesis testing, distributions, Z-scores and effect sizes Correlate that – get the lowdown on common procedures for defining relationships between variables, including linear regressions, associations between categorical data and more Analyse by inference – master key methods in inferential statistics, including techniques for analysing independent groups designs and repeated-measures research designs Open the book and find: Ways to describe statistical data How to use SPSS statistical software Probability theory and statistical inference Descriptive statistics basics How to test hypotheses Correlations and other relationships between variables Core concepts in statistical analysis for psychology Analysing research designs Learn to: Use SPSS to analyse data Master statistical methods and procedures using psychology-based explanations and examples Create better reports Identify key concepts and pass your course

Thermoforming carbon fibre-reinforced thermoplastic composites

The use of carbon fibre composites is growing in many sectors but their use remains stronger in very high value industries such as aerospace where the demands of the application more easily justify the high energy input needed and the corresponding costs incurred. This energy and cost input is returned through gains over the whole life of the product, with for example, longer maintenance intervals for an aircraft and lower fuel burn. Thermoplastic composites however have a different energy and cost profile compared to traditional thermosets with notable differences in recyclability, but this profile is not well quantified or documented. This study considers the key process control parameters and identifies an optimal window for processing, along with the effect this has on the final characteristics of the manufactured parts. Interactions between parameters and corresponding sensitivities are extracted from the results.

Assessment Method for a Power Analysis to Identify Differentially Expressed Pathways

Gene expression data can provide a very rich source of information for elucidating the biological function on the pathway level if the experimental design considers the needs of the statistical analysis methods. The purpose of this paper is to provide a comparative analysis of statistical methods for detecting the differentially expression of pathways (DEP). In contrast to many other studies conducted so far, we use three novel simulation types, producing a more realistic correlation structure than previous simulation methods. This includes also the generation of surrogate data from two large-scale microarray experiments from prostate cancer and ALL. As a result from our comprehensive analysis of 41,004 parameter configurations, we find that each method should only be applied if certain conditions of the data from a pathway are met. Further, we provide method-specific estimates for the optimal sample size for microarray experiments aiming to identify DEP in order to avoid an underpowered design. Our study highlights the sensitivity of the studied methods on the parameters of the system. © 2012 Tripahti and Emmert-Streib.

Detecting sequence dependent transcriptional pauses from RNA and protein number time series

Background: Evidence suggests that in prokaryotes sequence-dependent transcriptional pauses a?ect the dynamics of transcription and translation, as well as of small genetic circuits. So far, a few pause-prone sequences have been identi?ed from in vitro measurements of transcription elongation kinetics.

Results: Using a stochastic model of gene expression at the nucleotide and codon levels with realistic parameter values, we investigate three di?erent but related questions and present statistical methods for their analysis. First, we show that information from in vivo RNA and protein temporal numbers is su?cient to discriminate between models with and without a pause site in their coding sequence. Second, we demonstrate that it is possible to separate a large variety of models from each other with pauses of various durations and locations in the template by means of a hierarchical clustering and a random forest classi?er. Third, we introduce an approximate likelihood function that allows to estimate the location of a pause site.

Conclusions: This method can aid in detecting unknown pause-prone sequences from temporal measurements of RNA and protein numbers at a genome-wide scale and thus elucidate possible roles that these sequences play in the dynamics of genetic networks and phenotype.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.

Individual Differences in Children’s Paths to Arithmetical Development

Cross-sectional and longitudinal data consistently indicate that mathematical difficulties are more prevalent in older than in younger children (e.g. Department of Education, 2011). Children’s trajectories can take a variety of shapes such as linear, flat, curvilinear and uneven, and shape has been found to vary within children and across tasks (J Jordan et al. 2009). There has been an increase in the use of statistical methods which are specifically designed to study development, and this has greatly improved our understanding of children’s mathematical development. However, the effects of many cognitive and social variables (e.g. working memory and verbal ability) on mathematical development are unclear. It is likely that greater consistency between studies will be achieved by adopting a componential approach to study mathematics, rather than treating mathematics as a unitary concept.

A revised age for the Kawakawa/Oruanui tephra, a key marker for the Last Glacial Maximum in New Zealand

The Kawakawa/Oruanui tephra (KOT) is a key chronostratigraphic marker in terrestrial and marine deposits of the New Zealand (NZ) sector of the southwest Pacific. Erupted early during the Last Glacial Maximum (LGM), the wide distribution of the KOT enables inter-regional alignment of proxy records and facilitates comparison between NZ climatic variations and those from well-dated records elsewhere. We present 22 new radiocarbon ages for the KOT from sites and materials considered optimal for dating, and apply Bayesian statistical methods via OxCal4.1.7 that incorporate stratigraphic information to develop a new age probability model for KOT. The revised calibrated age, ±2 standard deviations, for the eruption of the KOT is 25,360 ± 160 cal yr BP. The age revision provides a basis for refining marine reservoir ages for the LGM in the southwest Pacific.

Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification

Aims/hypothesis: Diabetic nephropathy is a major diabetic complication, and diabetes is the leading cause of end-stage renal disease (ESRD). Family studies suggest a hereditary component for diabetic nephropathy. However, only a few genes have been associated with diabetic nephropathy or ESRD in diabetic patients. Our aim was to detect novel genetic variants associated with diabetic nephropathy and ESRD. Methods: We exploited a novel algorithm, ‘Bag of Naive Bayes’, whose marker selection strategy is complementary to that of conventional genome-wide association models based on univariate association tests. The analysis was performed on a genome-wide association study of 3,464 patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study and subsequently replicated with 4,263 type 1 diabetes patients from the Steno Diabetes Centre, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK collection (UK–Republic of Ireland) and the Genetics of Kidneys in Diabetes US Study (GoKinD US). Results: Five genetic loci (WNT4/ZBTB40-rs12137135, RGMA/MCTP2-rs17709344, MAPRE1P2-rs1670754, SEMA6D/SLC24A5-rs12917114 and SIK1-rs2838302) were associated with ESRD in the FinnDiane study. An association between ESRD and rs17709344, tagging the previously identified rs12437854 and located between the RGMA and MCTP2 genes, was replicated in independent case–control cohorts. rs12917114 near SEMA6D was associated with ESRD in the replication cohorts under the genotypic model (p < 0.05), and rs12137135 upstream of WNT4 was associated with ESRD in Steno. Conclusions/interpretation: This study supports the previously identified findings on the RGMA/MCTP2 region and suggests novel susceptibility loci for ESRD. This highlights the importance of applying complementary statistical methods to detect novel genetic variants in diabetic nephropathy and, in general, in complex diseases.