How Effective are Unemployment Benefit Sanctions? Looking Beyond Unemployment Exit

This paper provides a comprehensive evaluation of the effects of benefit sanctions on post-unemployment outcomes such as post-unemployment employment stability and earnings. We use rich register data which allow us to distinguish between a warning that a benefit reduction may take place in the near future and the actual withdrawal of unemployment benefits. Adopting a multivariate mixed proportional hazard approach to address selectivity, we find that warnings do not affect subsequent employment stability but do reduce post-unemployment earnings. Actual benefit reductions lower the quality of post-unemployment jobs both in terms of job duration as well as in terms of earnings. Copyright © 2012 John Wiley & Sons, Ltd.

Carcinoembryonic antigen (CEA) in non digestive cancerous and normal tissues.

Carcinoembryonic antigen (CEA), immunologically identical to CEA derived from colonic carcinoma, was identified and purified from perchloric acid (PCA) extracts of bronchial and mammary carcinoma. CEA extracted from bronchial and mammary carcinoma was quantitated by single radial immunodiffusion and was found to be in average about 50-75 times less abundant in these tumors than in colonic carcinoma. CEA could also be detected in one normal breast in lactation and at lower concentrations in normal lung (1000-4000 times lower than in colonic carcinoma). The small amounts of CEA present in normal tissues are distinct from the glycoprotein of small mol. wt showing only partial identity with CEA, that we recently identified and extracted in much larger quantities from normal lung and spleen. The demonstration of the presence of CEA in non digestive carcinoma by classical gel precipitation analysis suggests that the CEA detected in the plasma of such patients by radioimmunoassay is also identical to colonic carcinoma CEA. Our comparative study of plasma CEA from bronchial and colonic carcinoma, showing that CEA from both types of patient has the same elution pattern on Sephadex G-200 and gives parallel inhibition curves in the radioimmunoassay, is in favor of this hypothesis. However, it should not be concluded that all positive CEA radioimmunoassay indicate the presence of an antigen identical to colonic carcinoma CEA. A word of warning concerning the interpretation of radioimmunoassay is required by the observation that the addition of mg amounts of PCA extract of normal plasma, cleared of CEA by Sephadex filtration, could interfere in the test and mimic the presence of CEA.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.