4,202 research outputs found
La determinación de los salarios en el mercado de trabajo : el caso de Islandia y Noruega
En este trabajo examinamos el comportamiento del mercado de trabajo de Islandia y Noruega en las últimas décadas y en particular analizamos el proceso de formación salarial desde la óptica de la teoría de la reacción en cadena (TRC). Nuestras ecuaciones de salarios estimadas indican que en ambos países los salarios vienen determinados por los mismos factores: a) un componente que muestra la influencia que ejercen las decisiones del pasado en las decisiones presentes, b) la productividad del empleo, c) los subsidios de desempleo y d) la tasa de desempleo. Así, nuestros resultados refuerzan la hipótesis de la TRC sobre la importancia de utilizar conjuntamente variables estacionarias (instituciones del mercado de trabajo) y variables no estacionarias (variables con tendencia) para analizar el comportamiento del mercado de trabajo o de alguno de sus componentes, como en este caso el proceso de formación salarial.Fil: Salvador, Pablo F..
Consejo Nacional de Investigaciones Científicas y TécnicasFil: Salvi, Mauro.
Universidad Nacional de Cuy
Sensitivity limits of a Raman atom interferometer as a gravity gradiometer
We evaluate the sensitivity of a dual cloud atom interferometer to the
measurement of vertical gravity gradient. We study the influence of most
relevant experimental parameters on noise and long-term drifts. Results are
also applied to the case of doubly differential measurements of the
gravitational signal from local source masses. We achieve a short term
sensitivity of 3*10^(-9) g/Hz^(-1/2) to differential gravity acceleration,
limited by the quantum projection noise of the instrument. Active control of
the most critical parameters allows to reach a resolution of 5*10^(-11) g after
8000 s on the measurement of differential gravity acceleration. The long term
stability is compatible with a measurement of the gravitational constant G at
the level of 10^(-4) after an integration time of about 100 hours.Comment: 19 pages, 20 figure
Role of Atypical Chemokine Receptors in Microglial Activation and Polarization.
Inflammatory reactions occurring in the central nervous system (CNS), known as neuroinflammation, are key components of the pathogenic mechanisms underlying several neurological diseases. The chemokine system plays a crucial role in the recruitment and activation of immune and non-immune cells in the brain, as well as in the regulation of microglia phenotype and function. Chemokines belong to a heterogeneous family of chemotactic agonists that signal through the interaction with G protein-coupled receptors (GPCRs). Recently, a small subset of chemokine receptors, now identified as “atypical chemokine receptors” (ACKRs), has been described. These receptors lack classic GPCR signaling and chemotactic activity and are believed to limit inflammation through their ability to scavenge chemokines at the inflammatory sites. Recent studies have highlighted a role for ACKRs in neuroinflammation. However, in the CNS, the role of ACKRs seems to be more complex than the simple control of inflammation. For instance, CXCR7/ACKR3 was shown to control T cell trafficking through the regulation of CXCL12 internalization at CNS endothelial barriers. Furthermore, D6/ACKR2 KO mice were protected in a model of experimental autoimmune encephalomyelitis (EAE). D6/ACKR2 KO showed an abnormal accumulation of dendritic cells at the immunization and a subsequent impairment in T cell priming. Finally, CCRL2, an ACKR-related protein, was shown to play a role in the control of the resolution phase of EAE. Indeed, CCRL2 KO mice showed exacerbated, non- resolving disease with protracted inflammation and increased demyelination. This phenotype was associated with increased microglia and macrophage activation markers and imbalanced M1 vs. M2 polarization. This review will summarize the current knowledge on the role of the ACKRs in neuroinflammation with a particular attention to their role in microglial polarization and function
The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Recently, deep learning frameworks have rapidly become the main methodology for analyzing medical images. Due to their powerful learning ability and advantages in dealing with complex patterns, deep learning algorithms are ideal for image analysis challenges, particularly in the field of digital pathology. The variety of image analysis tasks in the context of deep learning includes classification (e.g., healthy vs. cancerous tissue), detection (e.g., lymphocytes and mitosis counting), and segmentation (e.g., nuclei and glands segmentation). The majority of recent machine learning methods in digital pathology have a pre- and/or post-processing stage which is integrated with a deep neural network. These stages, based on traditional image processing methods, are employed to make the subsequent classification, detection, or segmentation problem easier to solve. Several studies have shown how the integration of pre- and post-processing methods within a deep learning pipeline can further increase the model's performance when compared to the network by itself. The aim of this review is to provide an overview on the types of methods that are used within deep learning frameworks either to optimally prepare the input (pre-processing) or to improve the results of the network output (post-processing), focusing on digital pathology image analysis. Many of the techniques presented here, especially the post-processing methods, are not limited to digital pathology but can be extended to almost any image analysis field
High Enthalpy Flow Characterization Using Tunable Diode Laser Absorption Spectroscopy
This research aims at analysing thermo-chemical properties of the hypersonic high-enthalpy flow in the L2K wind tunnel, situated in Köln at the German Aerospace Center (DLR). In the L2K wind tunnel, Martian atmosphere can be created, and the facility can simulate heat load conditions encountered during atmospheric entry of Martian missions. The focus of this project is the analysis of the non-intrusive experimental technique "Tunable Diode Laser Absorption Spectroscopy" (TDLAS), based on line of sight absorption spectroscopy, and applied to hypersonic flow. A simplified Martian atmosphere (97% CO2 and 3% N2) was used. A new interpretation for CO-TDLAS experimental technique applied to hypersonic wind tunnel flow analysis was developed. Numerical simulations with the DLR-TAU non-equilibrium flow solver were used as support of this analysis, and match between simulations and experiments was observed. Flow speed and absorption line’s width were measured, and the knowledge of L2K’s flow structure was extended
Effects of defoliation at fruit set on vine physiology and berry composition in cabernet sauvignon grapevines
Grapevine canopy defoliation is a fundamentally important technique for the productivity and quality of grapes. Leaf removal is a pivotal operation on high-density vines which aims to improve air circulation, light exposure, and leaf gas exchange. The effects of leaf removal (LR) on vine physiology and berry composition in Cabernet Sauvignon grapevines were studied during the 2018–2019 growing season in the Bolgheri area, Tuscany, Italy. The basal leaves were removed at fruit set at two severity levels (removal of four basal leaves of each shoot (LR4) and removal of eight basal leaves (LR8)). The two treatments were compared with the not defoliated control (CTRL). The following physiological parameters of vines were measured: leaf gas exchange, leaf water potential, chlorophyll fluorescence and indirect chlorophyll content. The results showed that defoliation increased single leaf photosynthesis. In addition, qualitative grape parameters (phenolic and technological analyses) and daytime and night-time berry temperature were studied. The results showed that leaf removal had an impact on total soluble solids (°Brix), titratable acidity, and pH. The LR8-treated grapes had higher titratable acidity, while those in the LR4 treatment had higher °Brix and extractable anthocyanin and polyphenol content. Berry weight was not significantly influenced by the timing and severity of basal defoliation. Therefore, this research aims to investigate the effects of defoliation at the fruit set on vines performance
The relationship between seismic deformation and deep seated gravitational
This paper re-evaluates the origin of some peculiar patterns of ground deformation observed by
space geodetic techniques during the two earthquakes of September 26th of the Colfiorito seismic
sequence. The surface displacement field due to the fault dislocation, as modeled with the classic
Okada elastic formulations, shows some areas with high residuals which cannot be attributed to
unsimulated model complexities. The latter was investigated using geomorphological analysis, by
recognising the geologic evidence of deep seated gravitational slope deformations (DSGSD) of the
block-slide type. The shape and direction of the co-seismic ground displacement observed in these
areas are correlated with the expected pattern of movement produced by the reactivation of the
identified DSGSD. At least a few centimetres of negative Line of Sight ground displacement was
determined for the Costa Picchio, Mt. Pennino, and Mt. Prefoglio areas. A considerable horizontal
component of movement in the Costa Picchio DSGSD is evident from a qualitative analysis of
ascending and descending interferograms. The timing of the geodetic data indicates that the ground
movement occurred during the seismic shaking, and that it did not progress appreciably during the
following months. In this work it has been verified the seismic triggering of DSGSD previously
hypothesized by many authors. A further implication is that in the assessment of DSGSD hazard it is
necessary to consider the seismic input as an important cause of acceleration of the deformation rates
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