Growth in Unemployment Raises Poverty Rates: Most Low-Wage Earnings Constitute Supplement to Primary Household Income

Inequality with respect to personal earned income has increased in recent years. This trend has gone hand in hand with changes in both the employment constellations of households and the labor market activity of individuals (e.g. through 'minijobs'). In particular, the years since 2000 have seen a rise in the share of households with no market income because their members are either registered or hidden unemployed. These findings do not necessarily indicate an increase in relative poverty, because the latter depends on net household income and not just on individual primary incomes. While the risk of poverty also increased in recent years amongst low-wage earners, the rise only applied to those 47% of low-wage earners who live in households without another gainfully employed household member. More than half of all low-wage earners live in households that have a below-average risk of poverty. Unemployment still represents the principal risk factor for poverty. Whereas the likelihood of being poor in the event of unemployment was 29% in 1993, this risk had increased by ten percentage points by 2003. For an unemployed person living alone or whose spouse or partner was not working, the risk of poverty in 2003 was a substantial risk of 53%.

Calculation of Mutual Information for Partially Coherent Gaussian Channels with Applications to Fiber Optics

The mutual information between a complex-valued channel input and its complex-valued output is decomposed into four parts based on polar coordinates: an amplitude term, a phase term, and two mixed terms. Numerical results for the additive white Gaussian noise (AWGN) channel with various inputs show that, at high signal-to-noise ratio (SNR), the amplitude and phase terms dominate the mixed terms. For the AWGN channel with a Gaussian input, analytical expressions are derived for high SNR. The decomposition method is applied to partially coherent channels and a property of such channels called "spectral loss" is developed. Spectral loss occurs in nonlinear fiber-optic channels and it may be one effect that needs to be taken into account to explain the behavior of the capacity of nonlinear fiber-optic channels presented in recent studies.Comment: 30 pages, 9 figures, accepted for publication in IEEE Transactions on Information Theor

Mehr Armut durch steigende Arbeitslosigkeit: Niedriglöhne überwiegend als Zusatzeinkommen im Haushalt

In den letzten Jahren ist die Ungleichheit der individuellen Erwerbseinkommen gestiegen. Dies ging einher mit einer Veränderung der haushaltsspezifischen Erwerbskonstellation und der individuellen Erwerbsbeteiligung (z. B. Minijobs). Insbesondere ist seit 2000 ein steigender Anteil von Haushalten ohne Markteinkommen zu beobachten, weil deren Mitglieder arbeitslos sind oder zur stillen Reserve gehören. Diese Befunde bedeuten nicht zwangsläufig einen Anstieg der relativen Einkommensarmut, denn diese hängt vom Haushaltsnettoeinkommen und nicht allein von den individuellen Primäreinkommen ab. Zwar stieg in den letzten Jahren auch bei der Gruppe der Niedriglohnbezieher das Risiko der Einkommensarmut; dies betraf lediglich jene 47 % der Niedriglohnbezieher in Haushalten ohne einen weiteren Erwerbstätigen. Mehr als die Hälfte aller Niedriglohnbezieher lebt aber in Haushalten mit einem unterdurchschnittlichen Armutsrisiko. Das markanteste Armutsrisiko stellt nach wie vor Arbeitslosigkeit dar. Lag 1993 die Wahrscheinlichkeit, im Falle von Arbeitslosigkeit zur Gruppe der einkommensarmen Personen zu zählen, bei 29 %, war dieses Risiko im Jahre 2003 um 10 Prozentpunkte höher. Lebt ein Arbeitsloser allein im Haushalt oder übt dessen (Ehe-)Partner keine Erwerbstätigkeit aus, betrug das Armutsrisiko im Jahre 2003 sogar 53 %.

Automatic classification of spectra from the Infrared Astronomical Satellite (IRAS)

A new classification of Infrared spectra collected by the Infrared Astronomical Satellite (IRAS) is presented. The spectral classes were discovered automatically by a program called Auto Class 2. This program is a method for discovering (inducing) classes from a data base, utilizing a Bayesian probability approach. These classes can be used to give insight into the patterns that occur in the particular domain, in this case, infrared astronomical spectroscopy. The classified spectra are the entire Low Resolution Spectra (LRS) Atlas of 5,425 sources. There are seventy-seven classes in this classification and these in turn were meta-classified to produce nine meta-classes. The classification is presented as spectral plots, IRAS color-color plots, galactic distribution plots and class commentaries. Cross-reference tables, listing the sources by IRAS name and by Auto Class class, are also given. These classes show some of the well known classes, such as the black-body class, and silicate emission classes, but many other classes were unsuspected, while others show important subtle differences within the well known classes

Towards OSGeo Best Practices for Scientific Software Citation: Integration Options for Persistent Identifiers in OSGeo Project Repositories

As a contribution to the currently ongoing larger effort to establish Open Science as best practices in academia, this article focuses on the Open Source and Open Access tiers of the Open Science triad and community software projects. The current situation of research software development and the need to recognize it as a significant contribution to science is introduced in relation to Open Science. The adoption of the Open Science paradigms occurs at different speeds and on different levels within the various fields of science and crosscutting software communities. This is paralleled by the emerging of an underlying futuresafe technical infrastructure based on open standards to enable proper recognition for published articles, data, and software. Currently the number of journal publications about research software remains low in comparison to the amount of research code published on various software repositories in the WWW. Because common standards for the citation of software projects (containers) and versions of software are lacking, the FORCE11 group and the CodeMeta project recommending to establish Persistent Identifiers (PIDs), together with suitable metadata setss to reliably cite research software. This approach is compared to the best practices implemented by the OSGeo Foundation for geospatial community software projects. For GRASS GIS, a OSGeo project and one of the oldest geospatial open source community projects, the external requirements for DOI-based software citation are compared with the projects software documentation standards. Based on this status assessment, application scenarios are derived, how OSGeo projects can approach DOI-based software citation, both as a standalone option and also as a means to foster open access journal publications as part of reproducible Open Science

Towards OSGeo Best Practices for Scientific Software Citation: Integration Options for Persistent Identifiers fn OSGeo Project Repositories

As a contribution to the currently ongoing larger effort to establish Open Science as best practices in academia, this article focuses on the Open Source and Open Access tiers of the Open Science triad and community software projects. The current situation of research software development and the need to recognize it as a significant contribution to science is introduced in relation to Open Science. The adoption of the Open Science paradigms occurs at different speeds and on different levels within the various fields of science and crosscutting software communities. This is paralleled by the emerging of an underlying futuresafe technical infrastructure based on open standards to enable proper recognition for published articles, data, and software. Currently the number of journal publications about research software remains low in comparison to the amount of research code published on various software repositories in the WWW. Because common standards for the citation of software projects (containers) and versions of software are lacking, the FORCE11 group and the CodeMeta project recommending to establish Persistent Identifiers (PIDs), together with suitable metadata setss to reliably cite research software. This approach is compared to the best practices implemented by the OSGeo Foundation for geospatial community software projects. For GRASS GIS, a OSGeo project and one of the oldest geospatial open source community projects, the external requirements for DOI-based software citation are compared with the projects software documentation standards. Based on this status assessment, application scenarios are derived, how OSGeo projects can approach DOI-based software citation, both as a standalone option and also as a means to foster open access journal publications as part of reproducible Open Science