Computational approach for reliable and robust system-in-package design

A computational modelling approach integrated with optimisation and statistical methods that can aid the development of reliable and robust electronic packages and systems is presented. The design for reliability methodology is demonstrated for the design of a SiP structure. In this study the focus is on the procedure for representing the uncertainties in the package design parameters, their impact on reliability and robustness of the package design and how these can be included in the design optimisation modelling framework. The analysis of thermo-mechanical behaviour of the package is conducted using non-linear transient finite element simulations. Key system responses of interest, the fatigue life-time of the lead-free solder interconnects and warpage of the package, are predicted and used subsequently for design purposes. The design tasks are to identify the optimal SiP designs by varying several package input parameters so that the reliability and the robustness of the package are improved and in the same time specified performance criteria are also satisfied

Phenotypical characterization in "Plasmopara halstedii" (sunflower downy mildew) isolates of several races

Phenotypic variation (morphological and pathogenic characters), and genetic variability were studied in 50 isolates of seven Plasmopara halstedii (sunflower downy mildew) races 100, 300, 304, 314, 710, 704 and 714. There were significant morphological, aggressiveness, and genetic differences for pathogen isolates. However, there was no relationship between morphology of zoosporangia and sporangiophores and pathogenic and genetic characteristics for the races used in our study. Also, our results provided evidence that no relation between pathogenic traits and multilocus haplotypes may be established in P. halstedii. The hypothesis explaining the absence of relationships among phenotypic and genetic characteristics is discussed.

Pl2 resistance gene differentiates the pathogenicity in four "Plasmopara halstedii" (sunflower downy mildew) races 304, 704, 314 and 714

In order to clarify the role of Pl2 resistance gene in differentiation the pathogenicity in Plasmopara halstedii (sunflower downy mildew), analyses were carried out in four pathotypes: isolates of races 304 and 314 that do not overcome Pl2 gene, and isolates of races 704 and 714 that can overcome Pl2 gene. Based on the reaction for the P. halstedii isolates to sunflower hybrids varying only in Pl resistance genes, isolates of races 704 and 714 were more virulent than isolates of races 304 and 314. Index of aggressiveness was calculated for pathogen isolates and revealed the presence of significant differences between isolates of races 304 and 314 (more aggressive) and isolates of races 704 and 714 (less aggressive). There were morphological and genetic variations for the four P. halstedii isolates without a correlation with pathogenic diversity. The importance of the Pl2 resistance gene to differentiate the pathogenicity in sunflower downy mildew was discussed.

Environmental context explains Lévy 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.

Xanthoria parietina as a biomonitor of airborne heavy metal pollution in forest sites in the North East of Morocco

Xanthoria parietina, common foliose lichen, growing in its natural habitat, was analysed for the concentration of five heavy metals (Fe, Cr, Zn, Pb and Cu) from different forest sites of North East of Morocco (Kenitra, Sidi Boughaba, Mkhinza, Ceinture Verte near Temara city, Skhirate, Bouznika and Mohammedia). The quantification was carried out by inductively coupled plasma - atomic emission spectrometry (ICP-AES). Results were highly significant p<0,001. The concentration of metals is correlated with the vehicular activity and urbanization. The total metal concentration is highest at the Kenitra area, followed by Ceinture Verte site near Temara city, which experience heavy traffic throughout the year. Scanning electron microscopy (SEM) of particulate matter on lichen of Xanthoria parietina was assessed as a complementary technique to wet chemical analysis for source apportionment of airborne contaminant. Analysis revealed high level of Cu, Cr, Zn and Pb in samples near roads.  

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.