111 resultados para class size

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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This paper presents a regional analysis of the effects of educational policies implemented in Spain between 1992 and 2003, focusing specifically on school failure rates. We consider the impact of expenditure per pupil, class size, and pupil-teacher ratio on dropout rates at the end of compulsory education and on the proportion of early school-leavers in the 18-24 year age group. Our results indicate that higher levels of educational expenditure per pupil and lower class sizes and pupil-teacher ratios reduce rates of dropout and early school-leaving (although class-size is not always significant). However, the magnitude of the effects of these variables is small at the average level.

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We study the effect of strong heterogeneities on the fracture of disordered materials using a fiber bundle model. The bundle is composed of two subsets of fibers, i.e. a fraction 0 ≤ α ≤ 1 of fibers is unbreakable, while the remaining 1 - α fraction is characterized by a distribution of breaking thresholds. Assuming global load sharing, we show analytically that there exists a critical fraction of the components αc which separates two qualitatively diferent regimes of the system: below αc the burst size distribution is a power law with the usual exponent Ƭ= 5/2, while above αc the exponent switches to a lower value Ƭ = 9/4 and a cutoff function occurs with a diverging characteristic size. Analyzing the macroscopic response of the system we demonstrate that the transition is conditioned to disorder distributions where the constitutive curve has a single maximum and an inflexion point defining a novel universality class of breakdown phenomena

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Background: Analyzing social differences in the health of adolescents is a challenge. The accuracy of adolescent's report on familial socio-economic position is unknown. The aims of the study were to examine the validity of measuring occupational social class and family level of education reported by adolescents aged 12 to 18, and the relationship between social position and self-reported health.Methods: A sample of 1453 Spanish adolescents 12 to 18 years old from urban and rural areas completed a self-administered questionnaire including the Child Health and Illness Profile-Adolescent Edition (CHIP-AE), and data on parental occupational social class (OSC) and level of education (LE). The responsible person for a sub-sample of teenagers (n = 91) were interviewed by phone. Kappa coefficients were estimated to analyze agreement between adolescents and proxy-respondents, and logistic regression models were adjusted to analyze factors associated with missing answers and disagreements. Effect size (ES) was calculated to analyze the relationship between OSC, LE and the CHIP-AE domain scores.Results: Missing answers were higher for father's (24.2%) and mother's (45.7%) occupational status than for parental education (8.4%, and 8.1% respectively), and belonging to a non-standard family was associated with more incomplete reporting of social position (OR = 4,98; 95%CI = 1,3–18,8) as was agreement between a parent and the adolescent. There were significant social class gradients, most notably for aspects of health related to resilience to threats to illness.ConclusionAdolescents can acceptably self-report on family occupation and level of education. Social class gradients are present in important aspects of health in adolescents.

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The effect of age at the first mating and herd size were evaluated in the reference Spanish Databank (BDporc) of 37 698 sows born between 1991 and 1995 and with individual lifetime records. The data included dates of births at entrance and culling, first mating, repetitive mating and conception, first farrowing and weaning records. Individual records were validated before the analysis by screening them through a tolerance “filter” in order to eliminate the extreme values from the analysis. The total database of the sows was classified in 7 classes according to age at the first mating (< 210, 210–220, 221–230, 231–240, 241–250, 251–270, and > 270 days) and in 6 classes of herd size (< 200, 200–300, 301–400, 401–600, 601–800, and > 800 sows). The total number of litters and number of weaned piglets obtained from each sow during the lifetime production were significantly (P < 0.05) greater for gilts between 221 and 240 d of age at the first mating. There was a significant (P < 0.001) effect of the herd size on the reproductive performance of the sow, and the best performance was obtained with herds with 401 to 600 sows compared to < 200 or > 800 sow-herds. Furthermore, a significant (P < 0.001) interaction between age at the first mating and herd size was detected and can be associated with a particular pattern for the herd size class 401–600 sows with the best performances obtained for the sows first mated at less than 200 days. For the other herd sizes, the results indicated that sows mated for the first time at the right age, 221–240 days, are more productive, both in the number and size of the parities throughout lifetime production.

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Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.

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Identification of CD8+ cytotoxic T lymphocyte (CTL) epitopes has traditionally relied upon testing of overlapping peptide libraries for their reactivity with T cells in vitro. Here, we pursued deep ligand sequencing (DLS) as an alternative method of directly identifying those ligands that are epitopes presented to CTLs by the class I human leukocyte antigens (HLA) of infected cells. Soluble class I HLA-A*11:01 (sHLA) was gathered from HIV-1 NL4-3-infected human CD4+ SUP-T1 cells. HLA-A*11:01 harvested from infected cells was immunoaffinity purified and acid boiled to release heavy and light chains from peptide ligands that were then recovered by size-exclusion filtration. The ligands were first fractionated by high-pH high-pressure liquid chromatography and then subjected to separation by nano-liquid chromatography (nano-LC)–mass spectrometry (MS) at low pH. Approximately 10 million ions were selected for sequencing by tandem mass spectrometry (MS/MS). HLA-A*11:01 ligand sequences were determined with PEAKS software and confirmed by comparison to spectra generated from synthetic peptides. DLS identified 42 viral ligands presented by HLA-A*11:01, and 37 of these were previously undetected. These data demonstrate that (i) HIV-1 Gag and Nef are extensively sampled, (ii) ligand length variants are prevalent, particularly within Gag and Nef hot spots where ligand sequences overlap, (iii) noncanonical ligands are T cell reactive, and (iv) HIV-1 ligands are derived from de novo synthesis rather than endocytic sampling. Next-generation immunotherapies must factor these nascent HIV-1 ligand length variants and the finding that CTL-reactive epitopes may be absent during infection of CD4+ T cells into strategies designed to enhance T cell immunity.

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This paper assesses empirically the importance of size discrimination and disaggregate data for deciding where to locate a start-up concern. We compare three econometric specifications using Catalan data: a multinomial logit with 4 and 41 alternatives (provinces and comarques, respectively) in which firm size is the main covariate; a conditional logit with 4 and 41 alternatives including attributes of the sites as well as size-site interactions; and a Poisson model on the comarques and the full spatial choice set (942 municipalities) with site-specific variables. Our results suggest that if these two issues are ignored, conclusions may be misleading. We provide evidence that large and small firms behave differently and conclude that Catalan firms tend to choose between comarques rather than between municipalities. Moreover, labour-intensive firms seem more likely to be located in the city of Barcelona. Keywords: Catalonia, industrial location, multinomial response model. JEL: C250, E30, R00, R12

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In this paper we explore the determinants of firm start-up size of Spanish manufacturing industries. The industries' barriers to entry affect the ability of potential entrants to enter the markets and the size range at which they decide to enter. In order to examine the relationships between barriers to entry and size we applied the quantile regression techniques. Our results indicate that the variables that characterize the structure of the market, the variables that are related to the behaviour of the incumbent firms and the rate of growth of the industries generate different barriers depending on the initial size of the entrants. Keywords: Entry, regression quantiles, start-up size. JEL classification: L110, L600

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This paper concerns the effects of territorial factors on the processes involved in the creation of manufacturing firms in Spanish cities. Most contributions have focused on regional factors rather than urban ones. Here we assume that it is possible to identify certain urban factors that attract new firms. We use data for the entry of firms in Spanish manufacturing industries between 1994 and 2002. This paper contributes to the existing literature on market entry. Key words: cities, regions, firm entry and Spanish economy. JEL: R0, R12, L60

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Much of the research on industry dynamics focuses on the interdependence between the sectorial rates of entry and exit. This paper argues that the size of firms and the reaction-adjustment period are important conditions missed in this literature. I illustrate the effects of this omission using data from the Spanish manufacturing industries between 1994 and 2001. Estimates from systems of equations models provide evidence of a conical revolving door phenomenon and of partial adjustments in the replacement-displacement of large firms. KEYWORDS: aggregation, industry dynamics, panel data, symmetry, simultaneity. JEL CLASSIFICATION: C33, C52, L60, L11

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We present experimental and theoretical analyses of data requirements for haplotype inference algorithms. Our experiments include a broad range of problem sizes under two standard models of tree distribution and were designed to yield statistically robust results despite the size of the sample space. Our results validate Gusfield's conjecture that a population size of n log n is required to give (with high probability) sufficient information to deduce the n haplotypes and their complete evolutionary history. The experimental results inspired our experimental finding with theoretical bounds on the population size. We also analyze the population size required to deduce some fixed fraction of the evolutionary history of a set of n haplotypes and establish linear bounds on the required sample size. These linear bounds are also shown theoretically.

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We introduce and study a class of infinite-horizon nonzero-sum non-cooperative stochastic games with infinitely many interacting agents using ideas of statistical mechanics. First we show, in the general case of asymmetric interactions, the existence of a strategy that allows any player to eliminate losses after a finite random time. In the special case of symmetric interactions, we also prove that, as time goes to infinity, the game converges to a Nash equilibrium. Moreover, assuming that all agents adopt the same strategy, using arguments related to those leading to perfect simulation algorithms, spatial mixing and ergodicity are proved. In turn, ergodicity allows us to prove “fixation”, i.e. that players will adopt a constant strategy after a finite time. The resulting dynamics is related to zerotemperature Glauber dynamics on random graphs of possibly infinite volume.