342 research outputs found
Rational Expectations and the Puzzling No-Effect of the Minimum Wage
This paper argues that expectations are an important element that need to be included into the analysis of the effects of the minimum wage on employment. We show in a standard matching model that these effects are higher the lower is the likelihood associated to the minimum wage variation. This property also helps explaining the controversial results found in the empirical literature. When the policy is anticipated, the observed effect at the time of the actual variation is small and hard to identify. The model is tested on Spanish data, taking advantage of the unexpected change in the minimum wage following the election of Zapatero in 2004.Minimum wage, Expectations, Heterogeneous matches
Employment Protection and Labor Productivity: Positive or Negative?
Since the 1980s, many European countries have implemented labor market reforms, introducing more flexible labor contracts. This paper develops a matching model with heterogeneous matches in order to analyse the impact of employment protection on labor productivity. Several channels affects productivity. On one hand, flexible contracts reduce mismatching: low productive jobs are destroyed at no cost with a positive impact on the overall productivity. On the other hand, they imply lower human capital investment, reducing labor productivity. We analyze a third channel: the selection of the employees. Low costs of dismissal reduce the incentive of firms to invest in screening applicants, therefore increasing the uncertainty about their unobserved skills and productivity.Employment protection, Stochastic.job matching model, Screening
Screening ex-ante or screening on-the-job? The impact of the employment contract
This paper studies how employers collect information about the quality of workers. Two are the strategies: screening ex-ante, through the recruitment process, and monitoring new hires at work, or screening on-the-job. Using two datasets representative of workers in Great Britain, we provide empirical evidence that the optimal choice is related to the type of employment contract offered by the .rm. Our estimates show that temporary workers are associated with lower recruitment effort - in terms of lower cost and higher speed - and closer monitoring than permanent employees. But this relation depends crucially on the type of jobs. Differences in screening effort are substantial for low-level occupations, while the gap is marginal or not significant for high-skilled jobs.Fixed-term contracts, Recruitment, Monitoring
Rational Expectations and the Puzzling No-Effect of the Minimum Wage
This paper argues that expectations are an important element that needs to be included into the analysis of the effects of the minimum wage on employment. We show in a standard matching model that the observed employment effect is higher the lower is the likelihood associated with the minimum wage variation. On the other side, there is a significant anticipation effect, ignored in the literature. This property is able to explain the controversial results found in the empirical studies. When the policy is anticipated, the effect at the time of the actual variation is small and potentially hard to identify. The model is tested on Spanish data, taking advantage of the unexpected change in the minimum wage following the election of Zapatero in 2004.minimum wage, expectations, heterogeneous matches
Effects of dopaminergic pathways on human neutrophil
The existence of a bidirectional communication between the immune system and the central nervous system was postulated some years ago by different researchers. More recently some evidence supports the notion that immune system can be affected by dopamine (DA).
DA is a neurotransmitter of the central nervous system that exerts its effects through the activation of the five dopaminergic receptors (DR). DA can affect some functions of the cells of the immune system and this topic was widely investigated on the cells of adaptive immunity.
Therefore, we decided to focus our attention on the different cell populations of the innate immunity and to explore the data present in literature about the evidence of the existence of a dopaminergic regulation of these cells.
The first part of the thesis is a description of dopamine and of the dopaminergic system, with reference to interactions with the immune system, in particular the innate immunity. Moreover, in the last part of this first chapter are mentioned some diseases involving the innate immunity in which the role of dopaminergic pathway was postulated and in some case demonstrated.
The second chapter is devoted to the characterization from the physiological point of view of the other major actors of the work, neutrophils (PMN). Also in this case, at the end of the chapter there is a section dedicated to the relevance of PMN in diseases in which the immune component is relevant.
The third chapter represents the main results of my PhD project, based on the investigation of the role and relevance of the dopaminergic system in human neutrophils. The aim of this PhD research program was in fact, to characterize the presence of DR and if dopaminergic agent can affect some pivotal function of neutrophil in a receptor-dependent manner.
Finally, a last chapter resumed the other projects that I have followed during the three year of my PhD course. The two attached files represent the results of some of them, that were conclude and published
Conceptual models and databases for searching the genome
Genomics is an extremely complex domain, in terms of concepts, their relations, and their representations in data. This tutorial introduces the use of ER models in the context of genomic systems: conceptual models are of great help for simplifying this domain and making it actionable. We carry out a review of successful models presented in the literature for representing biologically relevant entities and grounding them in databases. We draw a difference between conceptual models that aim to explain the domain and conceptual models that aim to support database design and heterogeneous data integration. Genomic experiments and/or sequences are described by several metadata, specifying information on the sampled organism, the used technology, and the organizational process behind the experiment. Instead, we call data the actual regions of the genome that have been read by sequencing technologies and encoded into a machiner readable representation. First, we show how data and metadata can be modeled, then we exploit the proposed models for designing search systems, visualizers, and analysis environments. Both domains of human genomics and viral genomics are addressed, surveying several use cases and applications of broader public interest. The tutorial is relevant to the EDBT community because it demonstrates the usefulness of conceptual models’ principles within very current domains; in addition, it offers a concrete example of conceptual models’ use, setting the premises for interdisciplinary collaboration with a greater public (possibly including life science researchers)
General Adaptive Neighborhood Image Processing for Biomedical Applications
In biomedical imaging, the image processing techniques using spatially invariant transformations, with fixed operational windows, give efficient and compact computing structures, with the conventional separation between data and operations. Nevertheless, these operators have several strong drawbacks, such as removing significant details, changing some meaningful parts of large objects, and creating artificial patterns. This kind of approaches is generally not sufficiently relevant for helping the biomedical professionals to perform accurate diagnosis and therapy by using image processing techniques. Alternative approaches addressing context-dependent processing have been proposed with the introduction of spatially-adaptive operators (Bouannaya and Schonfeld, 2008; Ciuc et al., 2000; Gordon and Rangayyan, 1984;Maragos and Vachier, 2009; Roerdink, 2009; Salembier, 1992), where the adaptive concept results from the spatial adjustment of the sliding operational window. A spatially-adaptive image processing approach implies that operators will no longer be spatially invariant, but must vary over the whole image with adaptive windows, taking locally into account the image context by involving the geometrical, morphological or radiometric aspects. Nevertheless, most of the adaptive approaches require a priori or extrinsic informations on the image for efficient processing and analysis. An original approach, called General Adaptive Neighborhood Image Processing (GANIP), has been introduced and applied in the past few years by Debayle & Pinoli (2006a;b); Pinoli and Debayle (2007). This approach allows the building of multiscale and spatially adaptive image processing transforms using context-dependent intrinsic operational windows. With the help of a specified analyzing criterion (such as luminance, contrast, ...) and of the General Linear Image Processing (GLIP) (Oppenheim, 1967; Pinoli, 1997a), such transforms perform a more significant spatial and radiometric analysis. Indeed, they take intrinsically into account the local radiometric, morphological or geometrical characteristics of an image, and are consistent with the physical (transmitted or reflected light or electromagnetic radiation) and/or physiological (human visual perception) settings underlying the image formation processes. The proposed GAN-based transforms are very useful and outperforms several classical or modern techniques (Gonzalez and Woods, 2008) - such as linear spatial transforms, frequency noise filtering, anisotropic diffusion, thresholding, region-based transforms - used for image filtering and segmentation (Debayle and Pinoli, 2006b; 2009a; Pinoli and Debayle, 2007). This book chapter aims to first expose the fundamentals of the GANIP approach (Section 2) by introducing the GLIP frameworks, the General Adaptive Neighborhood (GAN) sets and two kinds of GAN-based image transforms: the GAN morphological filters and the GAN Choquet filters. Thereafter in Section 3, several GANIP processes are illustrated in the fields of image restoration, image enhancement and image segmentation on practical biomedical application examples. Finally, Section 4 gives some conclusions and prospects of the proposed GANIP approach
A geometric dissimilarity criterion between Jordan spatial mosaics. Theoretical aspects and application to segmentation evaluation
International audienceAn image segmentation process often results in a special spatial set, called a mosaic, as the subdivision of a domain S within the n-dimensional Euclidean space. In this paper, S will be a compact domain and the study will be focused on finite Jordan mosaics, that is to say mosaics with a finite number of regions and where the boundary of each region is a Jordan hypersurface. The first part of this paper addresses the problem of comparing a Jordan mosaic to a given reference Jordan mosaic and introduces the (Epsilon) dissimilarity criterion. The second part will show that the (Epsilon) dissimilarity criterion can be used to perform the evaluation of image segmentation processes. It will be compared to classical criterions in regard to several geometric transformations. The pros and cons of these criterions are presented and discussed, showing that the dissimilarity criterion outperforms the other ones
On the linear combination of the Gaussian and student's <i>t</i> random field and the integral geometry of its excursion sets
International audienceIn this paper, a random field, denoted by GTβν, is defined from the linear combination of two independent random fields, one is a Gaussian random field and the second is a student's t random field with v degrees of freedom scaled by β. The goal is to give the analytical expressions of the expected Euler-Poincaré characteristic of the GTβν excursion sets on a compact subset S of R2. The motivation comes from the need to model the topography of 3D rough surfaces represented by a 3D map of correlated and randomly distributed heights with respect to a GTβν random field. The analytical and empirical Euler-Poincaré characteristics are compared in order to test the GTβν model on the real surface
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