Equity offerings, stock price crash risk, and the impact of securities regulation: international evidence

We examine whether earnings manipulation around seasoned equity offerings (SEOs) is associated with an increase in the likelihood of a stock price crash post-issue and test whether the enactment of securities regulations attenuate the relation between SEOs and crash risk. Empirical evidence documents that managerial tendency to conceal bad news increases the likelihood of a stock price crash (Jin and Myers, 2006; Hutton, Marcus, and Tehranian, 2009). We test this hypothesis using a sample of firms from 29 EU countries that enacted the Market Abuse Directive (MAD). Consistent with our hypothesis, we find that equity issuers that engage in earnings management experience a significant increase in crash risk post-SEO relative to control groups of non-issuers; this effect is stronger for equity issuers with poor information environments. In addition, our findings show a significant decline in crash risk post-issue after the enactment of MAD that is stronger for firms that actively manage earnings. This decline in post-issue crash risk is more effective in countries with high ex-ante institutional quality and enforcement. These results suggest that the implementation of MAD helps to mitigate managers’ ability to manipulate earnings around SEOs.

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Inovação como fator de competitividade da cadeia de valor da moda

Tese de Doutoramento em Engenharia Têxtil

Direito Eleitoral e inelegibilidades por desvio de conduta: reflexões a partir da experiência brasileira

Dissertação de mestrado em Direito Administrativo

Innovation in “low-tech” industries: Portuguese footwear industry

ICEIM – International Conference in Entrepreneurship and Innovation Management, Roma, 17-18 de setembro de 2015.

Criação de um sistema de apoio para o suporte avançado de vida

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Relation between oral health and socioeconomic variables among schoolchildren aged 12 in the City of Manaus - AM

Studies have shown that the age of 12 was determined as the age of global monitoring of caries for international comparisons and monitoring of disease trends. The aimed was to evaluate the prevalence of dental caries, fluorosis and periodontal condition and their relation with socioeconomic factors among schoolchildren aged twelve in the city of Manaus, AM. This study with a probabilistic sample of 661 children was conducted, 609 from public and 52 from private schools, in 2008. Dental caries, periodontal condition and dental fluorosis were evaluated. In order to obtain the socioeconomic classification of each child (high, upper middle, middle, lower middle, low and lower low socioeconomic classes), the guardians were given a questionnaire. The mean decayed teeth, missing teeth, and filled teeth (DMFT) found at age twelve was 1.89. It was observed that the presence of dental calculus was the most severe periodontal condition detected in 39.48%. In relation to dental fluorosis, there was a low prevalence in the children examined, i.e., the more pronounced lines of opacity only occasionally merge, forming small white areas. The study showed a significant association of 5% among social class with dental caries and periodontal condition. In schoolchildren of Manaus there are low mean of DMFT and fluorosis, but a high occurrence of gingival bleeding.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Trans-cultural aspects of social anxiety disorder and related conditions: a Brazilian case series and a review of international clinical studies

Cross-cultural studies have much to teach clinicians and researchers alike about psychopathology in general and about social anxiety disorder (SAD) in particular. Unfortunately, little is known about the degree and the mechanisms through which cultural environment may influence clinical manifestations of SAD. OBJECTIVE: Our objective was to identify culture-related clinical patterns in SAD and related disorders. METHODS: We described socio-demographic and clinical characteristics of a sample of 62 adult outpatients with SAD seen at a university clinic for anxiety and depressive disorders in Rio de Janeiro, Brazil, and compared them with those reported in clinical samples from North America, Europe, Asia and Oceania identified through a systematic review in Medline, PsychINFO, and LILACS. RESULTS: Our comparison of trans-cultural features of SAD lends partial support to Heimberg's (1997) contention that the majority of socio-demographic features and symptoms of this disorder are relatively independent of geographic and cultural differences. CONCLUSION: Patients with SAD were almost universally characterized by: 1) a predominance of males in clinical samples; 2) early onset of the disorder; 3) high educational attainment; and 4) great frequency of comorbidities.

Brazilian norms for the International Affective Picture System (IAPS): comparison of the affective ratings for new stimuli between Brazilian and North-American subjects

OBJECTIVE: The study presents the Brazilian norms for 240 new stimuli from International Affective Picture System (IAPS), a database of affective images widely used in research, compared to the North-American normative ratings. METHODS: The participants were 448 Brazilian university students from several courses (269 women and 179 men) with mean age of 24.2 (SD = 7.8), that evaluated the IAPS pictures in the valence, arousal and dominance dimensions by the Self-Assessment Manikin (SAM) scales. Data were compared across the populations by Pearson linear correlation and Student's t-tests. RESULTS: Correlations were highly significant for all dimensions; however, Brazilians' averages for arousal were higher than North-Americans'. CONCLUSIONS: The results show stability in relation to the first part of the Brazilian standardization and they are also consistent with the North-American standards, despite minor differences relating to interpretation of the arousal dimension, demonstrating that IAPS is a reliable instrument for experimental studies in the Brazilian population.

Avaliação quantitativa da geodiversidade: desenvolvimento de instrumentos metodológicos com aplicação ao ordenamento do território

Tese de Doutoramento em Ciências (Especialidade de Geologia)

Supercritical fluid and pharmaceutical applications. Part I: Process classification

The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)