Convivial Quarantines: Cultivating Co-presence at a Distance

Qualitative Sociology - Sociology’s focus on sociality and co-presence has long oriented studies of commensality—the social dimension of eating together. This literature commonly...     

Covid and Public Funds: More Opportunities for a Misuse? The Case of the Intermediate Governments of Galicia

Public Organization Review - Corruption and inefficiency of public funds pose a risk in public administrations. This paper analyses the corruption risk at the local level by analysing indicators of...     

Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables

Many real-world optimization problems involve two different subsets of variables: decision variables, and those variables which are not present in the cost function but constrain the solutions, and thus, must be considered during optimization. Thus, dependencies between and within both subsets of variables must be considered. In this paper, an estimation of distribution algorithm (EDA) is implemented to solve this type of complex optimization problems. A Gaussian Bayesian network is used to build an abstraction model of the search space in each iteration to identify patterns among the variables. As the algorithm is initialized from data, we introduce a new hyper-parameter to control the influence of the initial data in the decisions made during the EDA execution. The results show that our algorithm improves the cost function more than the expert knowledge does.

     

A general framework for path convexities

Journal of Combinatorial Optimization - In this work we deal with the so-called path convexities, defined over special collections of paths. For example, the collection of the shortest paths in a...     

Return to Education and the Changing Role of Credentials in the Croatian Labor Market

The countries of Central and Eastern Europe experienced a rapid increase of return to education with the advent of the transition. We look at the dynamics of wage premiums in Croatia and estimate how much the return to education has changed between 1996 and 2004 on the basis of labor force survey data. We also extend the paper in order to address additional features of the wage structure, such as non-linearities in the return to education associated with attainment of credentials. We find that contrary to most transition countries, premiums for education in Croatia began to grow only after the mid 1990s. However, by 2004, they reached the levels of premiums found in other transition countries and advanced market economies, thus creating market incentives for investment in education. We also find that major part of this higher rate of return came through higher return to credentials.

Reference database of hematological parameters for growing and aging rats

The normal hematological values in various phases of the rat life provide a valuable guide to researchers and could be useful for experimental works. However, database information available on the literature are incomplete. Aim: This study aimed to present normal hematological parameters of young and aged rats.

Methods: Male and female rats were distributed into seven experimental groups with 1, 2, 3, 6, 12, 18, and 24 months of age. Blood samples taken from the tails were analyzed. Normal hematological values were determined for each age group.

Results: Rats showed a progressive weight gain with advancing age, predominantly after 3 months of life. With advancing age, differences were found on hematological parameters: some of them showed a progressive rise with age and others did not. Hemoglobin levels and hematocrit did not change while the number of circulating red blood cells suffered slight increase.

Conclusion: The present study determined the normal values for absolute and relative hematological parameters in Wistar rats from 2 to 24 months for male and female rats. The results can be used in studies of effects of aging, feeding, and medications on growing and aging rats.     

Les déterminants des déplacements de la courbe de Beveridge (et de l'appariement sur le marché du travail)

Les auteurs s'interrogent sur les politiques et facteurs qui influent sur la correspondance entre offre et demande de travail. Ils repèrent d'abord les déplacements de la courbe de Beveridge dans douze pays de l'OCDE (2000–2013) – avec trois méthodes complémentaires – avant de les expliquer avec un modèle à variable dépendante limitée. L'analyse montre que la croissance de la population active et la législation protectrice de l'emploi facilitent l'appariement, à l'inverse des qualifications moyennes et du chômage de longue durée. De même, l'effet favorable des politiques actives (partage d'emploi, aide à l'entrepreneuriat) contraste avec un effet nettement défavorable des politiques passives (allocations chômage, imposition du travail).     

U.K. Foot and Mouth Disease: A Systemic Risk Assessment of Existing Controls

This article details a systemic analysis of the controls in place and possible interventions available to further reduce the risk of a foot and mouth disease (FMD) outbreak in the United Kingdom. Using a research‐based network analysis tool, we identify vulnerabilities within the multibarrier control system and their corresponding critical control points (CCPs). CCPs represent opportunities for active intervention that produce the greatest improvement to United Kingdom's resilience to future FMD outbreaks. Using an adapted ‘features, events, and processes’ (FEPs) methodology and network analysis, our results suggest that movements of animals and goods associated with legal activities significantly influence the system's behavior due to their higher frequency and ability to combine and create scenarios of exposure similar in origin to the U.K. FMD outbreaks of 1967/8 and 2001. The systemic risk assessment highlights areas outside of disease control that are relevant to disease spread. Further, it proves to be a powerful tool for demonstrating the need for implementing disease controls that have not previously been part of the system.     

Classification Algorithm for Skin Color (CASCo): A new tool to measure skin color in social science research

Objective

A growing body of literature reveals that skin color has significant effects on people's income, health, education, and employment. However, the ways in which skin color has been measured in empirical research have been criticized for being inaccurate, if not subjective and biased.

Objective

Introduce an objective, automatic, accessible and customizable Classification Algorithm for Skin Color (CASCo).

Methods

We review the methods traditionally used to measure skin color (verbal scales, visual aids or color palettes, photo elicitation, spectrometers and image-based algorithms), noting their shortcomings. We highlight the need for a different tool to measure skin color

Results

We present CASCo, a (social researcher-friendly) Python library that uses face detection, skin segmentation and k-means clustering algorithms to determine the skin tone category of portraits.

Conclusion

After assessing the merits and shortcomings of all the methods available, we argue CASCo is well equipped to overcome most challenges and objections posed against its alternatives. While acknowledging its limitations, we contend that CASCo should complement researchers. toolkit in this area.