Using Firm-Level Data to Assess Gender Wage Discrimination in the Belgian Labour Market

In this paper we explore a matched employer-employee data set to investigate the presence of gender wage discrimination in the Belgian private economy labour market. We identify and measure gender wage discrimination from firm-level data using a labour index decomposition pioneered by Hellerstein and Neumark (1995), which allows us to compare direct estimates of a gender productivity differential with those of a gender labour costs differential. We take advantage of the panel structure of the data set and identify gender wage discrimination from within-firm variation. Moreover, inspired by recent developments in the production function estimation literature, we address the problem of endogeneity in input choice using a structural production function estimator (Levinsohn and Petrin, 2003). Our results suggest that there is no gender wage discrimination inside private firms located in Belgium.labour productivity; wages; gender discrimination; structural production function estimation; panel data

ANN Model For SiGe HBTs Constructed From Time-Domain Large-Signal Measurements

We construct a large-signal artificial neural network (ANN) model for SiGe HBTs, directly from time-domain large-signal measurements. It is known that HBTs are very sensitive to self-heating and therefore we explicitly study the effect on the model accuracy of the incorporation of the self-heating effect in the behavioural model description. Finally, we show that this type of models can be accurate at extreme operating conditions, where classical compact models start to fail

Health monitoring of federated future internet experimentation facilities

The federation of Future Internet testbeds as envisaged by the Fed4FIRE project is a complex undertaking. It combines a large number of existing, independent testbeds in a single federation, and presents them to the experimenter as if it were a single infrastructure. Operating and using such an infrastructure requires a profound knowledge of the status of the health of the underlying independent systems. Inspired by network monitoring techniques used to operate the Internet today, this paper considers how a centralized health monitoring system can be set up in a federated environment of Future Internet Experimentation Facilities. We show why it is a vital tool for experimenters and First Level Support in the federation, which health monitoring information must be captured, and how this information can be displayed most appropriately

Residual doses in recent alluvial sediments from the ardenne (S Belgium)

peer reviewedWe report on our first investigations into the potential of optical dating for determining the rate of river flood sedimentation in the Ardenne region (S Belgium). Two samples collected from a recent alluvial deposit were used to investigate the extent of resetting in different particle size fractions of quartz (4-11 mu m, 63-90 mu m, 90-125 mu m, 125-180 mu m, 180-212 mu m and 212-250 mu m) as well as in polymineral fine (4-11 mu m) grains. Both samples show satisfactory OSL and IRSL characteristics. The IRSL signals from the polymineral fine grains yield an equivalent dose (D-e) of 3-4 Gy, while a D-e of 0.3-0.6 Gy was measured using large aliquots of quartz. Small aliquot analyses of 63-90 mu m and 212-250 mu m quartz grains confirm that the coarser fraction contains more grains with lower D-e's. Furthermore, for a modern sample (< 3 years old), similar to 60% of the aliquots yields a D-e consistent with zero, indicating that these contain only well-bleached grains. These findings suggest that it might be possible to extract the true burial dose from dose distributions measured using small aliquots of coarse-grained (e.g. 212-250 mu m) quartz

The sequence of the 5.8 S ribosomal RNA of the crustacean <i>Artemia salina</i>. With a proposal for a general secondary structure model for 5.8 S ribosomal RNA

We report the primary structure of 5.8 S rRNA from the crustacean Artemia salina. The preparation shows length heterogeneity at the 5′-terminus, but consists of uninterrupted RNA chains, in contrast to some insect 5.8 S rRNAs, which consist of two chains of unequal length separated in the gene by a short spacer. The sequence was aligned with those of 11 other 5.8 S rRNAs and a general secondary structure model derived. It has four helical regions in common with the model of Nazar et al. (J. Biol. Chem. 250, 8591–8597 (1975)), but for a fifth helix a different base pairing scheme was found preferable, and the terminal sequences are presumed to bind to 28 S rRNA instead of binding to each other. In the case of yeast, where both the 5.8 S and 26 S rRNA sequences are known, the existence of five helices in 5.8 S rRNA is shown to be compatible with a 5.8 S - 26 S rRNA interaction model

Evaluation of resistive-plate-chamber-based TOF-PET applied to in-beam particle therapy monitoring

Particle therapy is a highly conformal radiotherapy technique which reduces the dose deposited to the surrounding normal tissues. In order to fully exploit its advantages, treatment monitoring is necessary to minimize uncertainties related to the dose delivery. Up to now, the only clinically feasible technique for the monitoring of therapeutic irradiation with particle beams is Positron Emission Tomography (PET). In this work we have compared a Resistive Plate Chamber (RPC)-based PET scanner with a scintillation-crystal-based PET scanner for this application. In general, the main advantages of the RPC-PET system are its excellent timing resolution, low cost, and the possibility of building large area systems. We simulated a partial-ring scannerbeam monitoring, which has an intrinsically low positron yield compared to diagnostic PET. In addition, for in-beam PET there is a further data loss due to the partial ring configuration. In order to improve the performance of the RPC-based scanner, an improved version of the RPC detector (modifying the thickness of the gas and glass layers), providing a larger sensitivity, has been simulated and compared with an axially extended version of the crystal-based device. The improved version of the RPC shows better performance than the prototype, but the extended version of the crystal-based PET outperforms all other options. based on an RPC prototype under construction within the Fondazione per Adroterapia Oncologica (TERA). For comparison with the crystal-based PET scanner we have chosen the geometry of a commercially available PET scanner, the Philips Gemini TF. The coincidence time resolution used in the simulations takes into account the current achievable values as well as expected improvements of both technologies. Several scenarios (including patient data) have been simulated to evaluate the performance of different scanners. Initial results have shown that the low sensitivity of the RPC hampers its application to hadro

Improved quantum algorithms for the ordered search problem via semidefinite programming

One of the most basic computational problems is the task of finding a desired item in an ordered list of N items. While the best classical algorithm for this problem uses log_2 N queries to the list, a quantum computer can solve the problem using a constant factor fewer queries. However, the precise value of this constant is unknown. By characterizing a class of quantum query algorithms for ordered search in terms of a semidefinite program, we find new quantum algorithms for small instances of the ordered search problem. Extending these algorithms to arbitrarily large instances using recursion, we show that there is an exact quantum ordered search algorithm using 4 log_{605} N \approx 0.433 log_2 N queries, which improves upon the previously best known exact algorithm.Comment: 8 pages, 4 figure

Present and LGM permafrost from climate simulations : contribution of statistical downscaling

We quantify the agreement between permafrost distributions from PMIP2 (Paleoclimate Modeling Intercomparison Project) climate models and permafrost data. We evaluate the ability of several climate models to represent permafrost and assess the variability between their results. &lt;br&gt;&lt;br&gt; Studying a heterogeneous variable such as permafrost implies conducting analysis at a smaller spatial scale compared with climate models resolution. Our approach consists of applying statistical downscaling methods (SDMs) on large- or regional-scale atmospheric variables provided by climate models, leading to local-scale permafrost modelling. Among the SDMs, we first choose a transfer function approach based on Generalized Additive Models (GAMs) to produce high-resolution climatology of air temperature at the surface. Then we define permafrost distribution over Eurasia by air temperature conditions. In a first validation step on present climate (CTRL period), this method shows some limitations with non-systematic improvements in comparison with the large-scale fields. &lt;br&gt;&lt;br&gt; So, we develop an alternative method of statistical downscaling based on a Multinomial Logistic GAM (ML-GAM), which directly predicts the occurrence probabilities of local-scale permafrost. The obtained permafrost distributions appear in a better agreement with CTRL data. In average for the nine PMIP2 models, we measure a global agreement with CTRL permafrost data that is better when using ML-GAM than when applying the GAM method with air temperature conditions. In both cases, the provided local information reduces the variability between climate models results. This also confirms that a simple relationship between permafrost and the air temperature only is not always sufficient to represent local-scale permafrost. &lt;br&gt;&lt;br&gt; Finally, we apply each method on a very different climate, the Last Glacial Maximum (LGM) time period, in order to quantify the ability of climate models to represent LGM permafrost. The prediction of the SDMs (GAM and ML-GAM) is not significantly in better agreement with LGM permafrost data than large-scale fields. At the LGM, both methods do not reduce the variability between climate models results. We show that LGM permafrost distribution from climate models strongly depends on large-scale air temperature at the surface. LGM simulations from climate models lead to larger differences with LGM data than in the CTRL period. These differences reduce the contribution of downscaling