5,877 research outputs found

    The Impact of the Participation Rate - Whatever it is -on University Enrolment

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    In the period from 1960 to 1976 the participation rate in university education increased dramatically and has since fallen. During this same period the size of the university age group doubled, so there was a period of great expansion in university enrolment. Popula- tion projections show a decline of the order of 20% in the size of the university age group between 1982 and 1996, and many believe that university enrolments must inevitably drop too, although the participation rate will be a major determinant of what happens. The factors which influence participation rates using the period 1960 to 1978, and the way in which participation rates are measured are examined. This is then applied to a discussion of the level of undergraduate enrolment in the period to 1996.De 1960 à 1976 le taux de participation dans les études universitaires a augmenté d'une manière spectaculaire. Depuis lors il est tombé. Pendant cette même période le nombre de la population en âge de fréquenter l'Université a doublé, de façon qu 'il y a eu une grande augmentation dans les inscriptions. Les études qui ont été faites sur la population montrent qu 'entre 1982 et 1996 il y aura une diminution de l'ordre du 20% dans le nombre des per-sonnes qui ont l'âge requis pour fréquenter l'Université. Par conséquent, l'on croit que les inscriptions doivent inévitablement diminuer aussi, bien que le taux de participation soit le facteur déterminant de ce qui arrive. Les facteurs qui influencent les taux de participa-tion pendant la période de 1960 à 1978 et le mode de calcul des taux de participation sont examinés. Ceci, par la suite, fait l'objet d'une discussion sur le niveau d'inscription aux études sousgraduées dès maintenant à 1996

    Draft Genome Sequence of Dietzia sp. Strain UCD-THP (Phylum Actinobacteria).

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    Here, we present the draft genome sequence of an actinobacterium, Dietzia sp. strain UCD-THP, isolated from a residential toilet handle. The assembly contains 3,915,613 bp. The genome sequences of only two other Dietzia species have been published, those of Dietzia alimentaria and Dietzia cinnamea

    Exact Maximal Height Distribution of Fluctuating Interfaces

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    We present an exact solution for the distribution P(h_m,L) of the maximal height h_m (measured with respect to the average spatial height) in the steady state of a fluctuating Edwards-Wilkinson interface in a one dimensional system of size L with both periodic and free boundary conditions. For the periodic case, we show that P(h_m,L)=L^{-1/2}f(h_m L^{-1/2}) for all L where the function f(x) is the Airy distribution function that describes the probability density of the area under a Brownian excursion over a unit interval. For the free boundary case, the same scaling holds but the scaling function is different from that of the periodic case. Numerical simulations are in excellent agreement with our analytical results. Our results provide an exactly solvable case for the distribution of extremum of a set of strongly correlated random variables.Comment: 4 pages revtex (two-column), 1 .eps figure include

    Examining the context of instruction to facilitate student success

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    © 2015, © The Author(s) 2015. Identifying effective instructional practices and effective teachers is an important issue in educational research, policy, and practice. However, many schools have resorted to measuring these constructs with student test scores, ignoring the instructional context. In this introductory article to the special issue, we highlight the importance of the instructional context as facilitating of teacher-student relationships, effective instructional practices, and supporting of student success

    Metagenomic Sequencing of an In Vitro-Simulated Microbial Community

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    Background: Microbial life dominates the earth, but many species are difficult or even impossible to study under laboratory conditions. Sequencing DNA directly from the environment, a technique commonly referred to as metagenomics, is an important tool for cataloging microbial life. This culture-independent approach involves collecting samples that include microbes in them, extracting DNA from the samples, and sequencing the DNA. A sample may contain many different microorganisms, macroorganisms, and even free-floating environmental DNA. A fundamental challenge in metagenomics has been estimating the abundance of organisms in a sample based on the frequency with which the organism's DNA was observed in reads generated via DNA sequencing. Methodology/Principal Findings: We created mixtures of ten microbial species for which genome sequences are known. Each mixture contained an equal number of cells of each species. We then extracted DNA from the mixtures, sequenced the DNA, and measured the frequency with which genomic regions from each organism was observed in the sequenced DNA. We found that the observed frequency of reads mapping to each organism did not reflect the equal numbers of cells that were known to be included in each mixture. The relative organism abundances varied significantly depending on the DNA extraction and sequencing protocol utilized. Conclusions/Significance: We describe a new data resource for measuring the accuracy of metagenomic binning methods, created by in vitro-simulation of a metagenomic community. Our in vitro simulation can be used to complement previous in silico benchmark studies. In constructing a synthetic community and sequencing its metagenome, we encountered several sources of observation bias that likely affect most metagenomic experiments to date and present challenges for comparative metagenomic studies. DNA preparation methods have a particularly profound effect in our study, implying that samples prepared with different protocols are not suitable for comparative metagenomics
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