Open University of Catalonia

About: Open University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Context (language use) & Higher education. The organization has 1943 authors who have published 4646 publications receiving 64200 citations. The organization is also known as: Universitat Oberta de Catalunya & UOC.

Conviction Statistics as an Indicator of Crime Trends in Europe from 1990 to 2006

Abstract: Convictions statistics were the first criminal statistics available in Europe during the nineteenth century. Their main weaknesses as crime measures and for comparative purposes were identified by Alphonse de Candolle in the 1830s. Currently, they are seldom used by comparative criminologists, although they provide a less valid but more reliable measure of crime and formal social control than police statistics. This article uses conviction statistics, compiled from the four editions of the European Sourcebook of Crime and Criminal Justice Statistics, to study the evolution of persons convicted in European countries from 1990 to 2006. Trends in persons convicted for six offences –intentional homicide, assault, rape, robbery, theft, and drug offences– and up to 26 European countries are analysed. These trends are established for the whole of Europe as well as for a cluster of Western European countries and a cluster of Central and Eastern European countries. The analyses show similarities between both regions of Europe at the beginning and at the end of the period under study. After a general increase of the rate of persons convicted in the early 1990s in the whole of Europe, trends followed different directions in Western and in Central and Eastern Europe. However, during the 2000s, it can be observed, throughout Europe, a certain stability of the rates of persons convicted for intentional homicides, accompanied by a general decrease of the rate of persons convicted for property offences, and an increase of the rate of those convicted for drug offences. The latter goes together with an increase of the rate of persons convicted for non lethal violent offences, which only reached some stability at the end of the time series. These trends show that there is no general crime drop in Europe. After a discussion of possible theoretical explanations, a multifactor model, inspired by opportunity-based theories, is proposed to explain the trends observed.

Citizen Science Toward Transformative Learning

Abstract: Citizen science can raise people’s understanding of science while helping scientists conduct their research. Yet its potential for driving transformative learning is empirically underexplored. We p...

Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer’s disease dementia: a systematic review

Abstract: BACKGROUND An increase in lifespan in our society is a double-edged sword that entails a growing number of patients with neurocognitive disorders, Alzheimer's disease being the most prevalent. Advances in medical imaging and computational power enable new methods for the early detection of neurocognitive disorders with the goal of preventing or reducing cognitive decline. Computer-aided image analysis and early detection of changes in cognition is a promising approach for patients with mild cognitive impairment, sometimes a prodromal stage of Alzheimer's disease dementia. METHODS We conducted a systematic review following PRISMA guidelines of studies where machine learning was applied to neuroimaging data in order to predict whether patients with mild cognitive impairment might develop Alzheimer's disease dementia or remain stable. After removing duplicates, we screened 452 studies and selected 116 for qualitative analysis. RESULTS Most studies used magnetic resonance image (MRI) and positron emission tomography (PET) data but also magnetoencephalography. The datasets were mainly extracted from the Alzheimer's disease neuroimaging initiative (ADNI) database with some exceptions. Regarding the algorithms used, the most common was support vector machine with a mean accuracy of 75.4%, but convolutional neural networks achieved a higher mean accuracy of 78.5%. Studies combining MRI and PET achieved overall better classification accuracy than studies that only used one neuroimaging technique. In general, the more complex models such as those based on deep learning, combined with multimodal and multidimensional data (neuroimaging, clinical, cognitive, genetic, and behavioral) achieved the best performance. CONCLUSIONS Although the performance of the different methods still has room for improvement, the results are promising and this methodology has a great potential as a support tool for clinicians and healthcare professionals.

Human Capital and Regional Wage Gaps

Abstract: Lopez-Bazo E and Motellon E Human capital and regional wage gaps, Regional Studies This paper uses micro-level data to analyse the effect of human capital on regional wage differentials The results for the set of Spanish regions confirm that they differ in the endowment of human capital, but also that the return that individuals obtain from it varies sharply across regions Regional heterogeneity in returns is especially intense in the case of education, particularly when considering its effect on the employability of individuals These differences in endowment and, especially, in returns to human capital account for a significant proportion of regional wage gaps Lopez-Bazo E and Motellon E 人力资本及区域工资差距，区域研究。本文利用微观数据分析了人力资本对于区域工资差异的影响。西班牙区域研究结果证明了人力资源禀赋方面存在的差异，同时个体回报率也存在巨大的区域差异。回报率的区域异质性在教育领域表现尤为明显，特别在考虑其对个体就业率的影响时。秉赋上的差异尤其是人力资本回报率差异构成了区域工资的显著差异。 教育 经验 区域差异 人力资本回 报率 工资差异分解 Lopez-Bazo E et Motellon E Le capital humain et les ecarts des salaires regionaux, Regional Studies Cet article emploie des m