The incidence of long-term unemployment : evidence from Greece

In this article, I use the 2000-2004 data from the Greek Labour Force Survey in order to estimate a logit model for the incidence of long-term unemployment. The model computed is similar to the one estimated by Obben et al. (2002). It is found that attributes of the individual such as gender, age category, marital status and region of residence affect the odds of being long-term unemployed. On the other hand, the level of someone's qualification does not affect the odds of whether someone will be short or long-term unemployed

What determines self-employment? : a comparative study

This article consists of a comparative study of the incidence of self-employment (SE) between Greece, which has the highest rate of SE in the European Union and the United Kingdom, which has amongst the lowest. Data from the Greek and the UK Labour Force Surveys are used in order to assess how personal attributes of an individual have an impact on the incidence of SE. It is found that common patterns exist between these two countries. In particular, it is found that for both countries, males have greater odds of being self-employed than females, older people have greater odds than younger, individuals employed in the primary and tertiary sectors have greater odds than the ones employed in the secondary, and that individuals with primary or secondary education have greater odds of being self-employed than individuals holding higher degrees. The incidence of SE is also found to differ according to the occupation of the individual. On the other hand, the findings indicate that individuals, residing in London, have greater odds of being self-employed than individuals working outside UK's capital, whereas in Greece the pattern is reversed

EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices

In recent years, advances in deep learning have resulted in unprecedented leaps in diverse tasks spanning from speech and object recognition to context awareness and health monitoring. As a result, an increasing number of AI-enabled applications are being developed targeting ubiquitous and mobile devices. While deep neural networks (DNNs) are getting bigger and more complex, they also impose a heavy computational and energy burden on the host devices, which has led to the integration of various specialized processors in commodity devices. Given the broad range of competing DNN architectures and the heterogeneity of the target hardware, there is an emerging need to understand the compatibility between DNN-platform pairs and the expected performance benefits on each platform. This work attempts to demystify this landscape by systematically evaluating a collection of state-of-the-art DNNs on a wide variety of commodity devices. In this respect, we identify potential bottlenecks in each architecture and provide important guidelines that can assist the community in the co-design of more efficient DNNs and accelerators.Comment: Accepted at MobiSys 2019: 3rd International Workshop on Embedded and Mobile Deep Learning (EMDL), 201

Does overhead irrigation with salt affect growth, yield, and phenolic content of lentil plants?

Overhead irrigation of lentil plants with salt (100 mM NaCl) did not have any significant impact on plant growth, while chlorophyll content and chlorophyll fluorescence parameter F-v/F-m were affected. Under such poor irrigation water quality, the malondialdehyde content in leaves was increased due to the lipid peroxidation of membranes. In seeds, the total phenolic content (TPC) was correlated to their total antioxidant capacity (TAC). High performance liquid chromatography-mass spectrometry (HPLC-MS) detection showed that flavonoids (catechin, epicatechin, rutin, p-coumaric acid, quercetin, kaempferol, gallic acid and resveratrol) appear to be the compounds with the greatest influence on the TAC values. Catechin is the most abundant phenolic compound in lentil seeds. Overhead irrigation with salt reduced the concentration of almost all phenolic compounds analyzed from lentil seed extracts

A Phantom Menace: On the Morphology of the Galactic Center Excess

The characteristics of the Galactic Center Excess (GCE) emission observed in gamma-ray energies -- especially the morphology of the GCE -- remain a hotly debated subject. The manner in which the dominant diffuse gamma-ray background is modeled has been claimed to have a determining effect on the preferred morphology. In this work, we compare two distinct approaches to the galactic diffuse gamma-ray emission background: the first approach models this emission through templates calculated from a sequence of well-defined astrophysical assumptions, while the second approach divides surrogates for the background gamma-ray emission into cylindrical galactocentric rings with free independent normalizations. At the latitudes that we focus on, we find that the former approach works better, and that the overall best fit is obtained for an astrophysically motivated fit when the GCE follows the morphology expected of dark matter annihilation. Quantitatively, the improvement compared to the best ring-based fits is roughly 6500 in the chi^2 and roughly 4000 in the log of the Bayesian evidence.Comment: 10 pages (including the appendix), code available at https://github.com/samueldmcdermott/gcep

Did LIGO detect dark matter?

We consider the possibility that the black-hole (BH) binary detected by LIGO may be a signature of dark matter. Interestingly enough, there remains a window for masses $20\,M_\odot \lesssim M_{\rm bh} \lesssim 100\, M_\odot$ where primordial black holes (PBHs) may constitute the dark matter. If two BHs in a galactic halo pass sufficiently close, they radiate enough energy in gravitational waves to become gravitationally bound. The bound BHs will rapidly spiral inward due to emission of gravitational radiation and ultimately merge. Uncertainties in the rate for such events arise from our imprecise knowledge of the phase-space structure of galactic halos on the smallest scales. Still, reasonable estimates span a range that overlaps the $2-53$ Gpc$^{-3}$ yr$^{-1}$ rate estimated from GW150914, thus raising the possibility that LIGO has detected PBH dark matter. PBH mergers are likely to be distributed spatially more like dark matter than luminous matter and have no optical nor neutrino counterparts. They may be distinguished from mergers of BHs from more traditional astrophysical sources through the observed mass spectrum, their high ellipticities, or their stochastic gravitational wave background. Next generation experiments will be invaluable in performing these tests.Comment: 5 pages, 2 figures, updated to match version published in PR