Dynamic facial expressions of emotions are discriminated at birth

The ability to discriminate between different facial expressions is fundamental since the first stages of postnatal life. The aim of this study is to investigate whether 2-days-old newborns are capable to discriminate facial expressions of emotions as they naturally take place in everyday interactions, that is in motion. When two dynamic displays depicting a happy and a disgusted facial expression were simultaneously presented (i.e., visual preference paradigm), newborns did not manifest any visual preference (Experiment 1). Nonetheless, after being habituated to a happy or disgusted dynamic emotional expression (i.e., habituation paradigm), newborns successfully discriminated between the two (Experiment 2). These results indicate that at birth newborns are sensitive to dynamic faces expressing emotions

The runaway taxpayer

In order to analyse the determinants of tax evasion, the existing literature on individual tax compliance typically takes a prior-to-audit point of view. This paper focuses on a post-audit, post-detection -so far unexplored- framework, by investigating what happens after tax evasion has been discovered and noncompliant taxpayers are asked to pay their debts. We fi rst develop a two-period dynamic model of individual choice, considering an individual that has been already audited and detected as tax evader, who knows that Tax Authorities are looking for her to cash the due amount. We derive the optimal decision of running away in order to avoid paying the bill, and show that the experience of a prior tax notice reduces the probability to behave as a scofflaw. We then exploit information on post-audit, post-detection tax compliance provided by an Italian collection agency for the period 2004-2007 to empirically test the effectiveness of the prior notice against scofflaws. The evidence from alternative logit model speci cations supports our theoretical prediction: experiencing a tax notice reduces the probability of running away by about 10%. However, this may prove to be insufficient to discourage some individuals to runaway in order to avoid paying their dues

Family history of cancer and the risk of cancer: a network of case-control studies

Background The risk of many cancers is higher in subjects with a family history (FH) of cancer at a concordant site. However, few studies investigated FH of cancer at discordant sites. Patients and methods This study is based on a network of Italian and Swiss case-control studies on 13 cancer sites conducted between 1991 and 2009, and including more than 12 000 cases and 11 000 controls. We collected information on history of any cancer in first degree relatives, and age at diagnosis. Odds ratios (ORs) for FH were calculated by multiple logistic regression models, adjusted for major confounding factors. Results All sites showed an excess risk in relation to FH of cancer at the same site. Increased risks were also found for oral and pharyngeal cancer and FH of laryngeal cancer (OR = 3.3), esophageal cancer and FH of oral and pharyngeal cancer (OR = 4.1), breast cancer and FH of colorectal cancer (OR = 1.5) and of hemolymphopoietic cancers (OR = 1.7), ovarian cancer and FH of breast cancer (OR = 2.3), and prostate cancer and FH of bladder cancer (OR = 3.4). For most cancer sites, the association with FH was stronger when the proband was affected at age <60 years. Conclusions Our results point to several potential cancer syndromes that appear among close relatives and may indicate the presence of genetic factors influencing multiple cancer site

Desempenho de linhagens elites de arroz irrigado de ciclo precoce do Programa de Melhoramento Genético da Embrapa em ensaios VCU no RS - safra 2008/09.

O objetivo deste trabalho foi avaliar o desempenho em rendimento de grãos e características agronômicas de interesse das linhagens de ciclo precoce geradas pelo programa de melhoramento genético da Embrapa, em diferentes regiões orizícolas do Rio Grande do Sul, para verificar a possibilidade de indicação de novas cultivares

Ensaio regional de linhagens de arroz irrigado do Programa de Melhoramento Genético da Embrapa no RS - safra 2008/09.

O Ensaio Regional de linhagens de arroz irrigado visa selecionar genótipos que apresentem alta adaptabilidade e estabilidade aos diversos ambientes em que são cultivadas e que expressem elevado rendimento de grãos, associado à características agronômicas, industriais e culinárias adequadas. Este experimento teve como objetivo avaliar linhagens do programa da Embrapa no Ensaio Regional de Rendimento

Long Run and Short Run Constraints in the Access to Private Health Care Services: Evidence from Selected European Countries

This paper aims at distinguishing long-run and short-run constraints in the access to private health care services. To this end, we apply the methodology proposed by Carneiro and Heckman (2003) to the SHARE database, a survey conducted in a number of European countries, involving some 22,000 individuals over the age of 50. Micro-data includes information on health and health consumption, and socioeconomic variables (like income and wealth). Our results show that the problem of short-run constraints in the access to private health care services could be real, especially in Italy, Greece, and to some extent Spain. Moreover, there appear to be differences in the role of credit constraints, both considering more specific services, and gender differences

Longer fixation duration while viewing face images

The spatio-temporal properties of saccadic eye movements can be influenced by the cognitive demand and the characteristics of the observed scene. Probably due to its crucial role in social communication, it is argued that face perception may involve different cognitive processes compared with non-face object or scene perception. In this study, we investigated whether and how face and natural scene images can influence the patterns of visuomotor activity. We recorded monkeys’ saccadic eye movements as they freely viewed monkey face and natural scene images. The face and natural scene images attracted similar number of fixations, but viewing of faces was accompanied by longer fixations compared with natural scenes. These longer fixations were dependent on the context of facial features. The duration of fixations directed at facial contours decreased when the face images were scrambled, and increased at the later stage of normal face viewing. The results suggest that face and natural scene images can generate different patterns of visuomotor activity. The extra fixation duration on faces may be correlated with the detailed analysis of facial features

Desempenho de linhagens elite de arroz irrigado de ciclo médio do Programa de Melhoramento Genético da Embrapa em ensaios VCU no RS - safra 2008/09.

O objetivo deste trabalho foi avaliar o desempenho das linhagens geradas pelo Programa de Melhoramento Genético da Embrapa, em diferente regiões orizícolas do Rio Grande do Sul, visando possível lançamento de novas cultivares

Feature Selection for Classification with QAOA

Feature selection is of great importance in Machine Learning, where it can be used to reduce the dimensionality of classification, ranking and prediction problems. The removal of redundant and noisy features can improve both the accuracy and scalability of the trained models. However, feature selection is a computationally expensive task with a solution space that grows combinatorically. In this work, we consider in particular a quadratic feature selection problem that can be tackled with the Quantum Approximate Optimization Algorithm (QAOA), already employed in combinatorial optimization. First we represent the feature selection problem with the QUBO formulation, which is then mapped to an Ising spin Hamiltonian. Then we apply QAOA with the goal of finding the ground state of this Hamiltonian, which corresponds to the optimal selection of features. In our experiments, we consider seven different real-world datasets with dimensionality up to 21 and run QAOA on both a quantum simulator and, for small datasets, the 7-qubit IBM (ibm-perth) quantum computer. We use the set of selected features to train a classification model and evaluate its accuracy. Our analysis shows that it is possible to tackle the feature selection problem with QAOA and that currently available quantum devices can be used effectively. Future studies could test a wider range of classification models as well as improve the effectiveness of QAOA by exploring better performing optimizers for its classical step