Socioeconomic status and learning from financial information

The majority of lower socioeconomic status (SES) households in the U.S. and Europe do not have stock investments, which is detrimental to wealth accumulation. Here, we examine one explanation for this puzzling fact, namely, that economic adversity may influence how people learn from financial information. Using experimental and survey data from the U.S. and Romania, we find that lower SES individuals form more pessimistic beliefs about the distribution of stock returns and are less likely to invest in stocks when these investments are likely to have good outcomes. SES-related differences in pessimism may help explain variation in investments across households

Carotenoides Pro-vitamina A em frutos de bananeira.

Os tipos de carotenóides variam muito nas frutas, sendo que aproximadamente 50 carotenóides possuem atividade pró-vitamina A. Dentre esses o β-caroteno é o mais importante e abundante em alimentos, seguido do α-caroteno e β-criptoxantina, os quais possuem a metade da atividade de vitamina A, comparativamente ao primeiro caroteno. Outros carotenóides não pró-vitamina A, porém com efeitos relevantes à saúde humana (e.g., antioxidante, antitumoral e inibidores da degeneração macular), também ocorrem em alimentos (luteína, zeaxantina e licopeno, por exemplo - RODRIGUEZ-AMAYA, 2001) e sua identificação em frutos de bananeira é considerado relevante. A banana destaca-se pelo seu alto potencial como alimento funcional, devido a seu alto consumo, principalmente em países subdesenvolvidos

Compostos fenólicos em frutos de bananeira.

Os compostos fenólicos são encontrados em muitas frutas e a quantificação desses metabólicos revela informações importantes a respeito da qualidade dos alimentos e dos potenciais benefícios à saúde (atividade antioxidante e atitumoral, e.g. - TALCOTT et al., 2003). A banana é amplamente consumida por todas as classes sociais e seu consumo é elevado, alcançando 162 Kg/pessoa/ano em algumas regiões da África (FAO, 2012)

Socioeconomic Status and Learning from Financial Information *

Abstract The majority of lower socioeconomic status (SES) households do not have any stock investments, which is detrimental to wealth accumulation. Here, we examine one potential driver of this puzzling fact, namely, that SES may influence the process by which people learn from information in financial markets. We find that low SES individuals, relative to medium or high SES ones, form more pessimistic beliefs about the distribution of stock investment outcomes and are less likely to invest in stocks. The pessimism bias in assessing risky assets induced by low SES is robust to several ways of measuring one's socioeconomic standing. These results, documented in controlled experimental settings in Romania and the U.S., as well as in a large non-laboratory sample of adults across all 50 states in the U.S., suggest that SES shapes in predictable ways people's beliefs about financial assets, which in turn may induce large differences across households in their propensity to participate in financial markets

Espectroscopia de infravermelho médio e quimiometria aplicadas a discriminação de acessos de bananeira.

O Brasil é o quinto produtor mundial de banana, tendo produzido aproximadamente 6,9 milhões de toneladas em 2010, em uma área aproximada de 487 mil hectares (FAO, 2012). Entretanto, há poucos cultivares para exploração comercial com potencial agronômico, tolerantes às pragas e doenças e que apresentem frutos com boas características pós-colheita e organolépticas. Uma das estratégias à solução desse problema é a seleção de novos genótipos, por meio do melhoramento genético, visando o aumento do valor nutricional e funcional (biofortificação), associado às boas características agronômicas

A machine learning and chemometrics assisted interpretation of spectroscopic data: a NMR-based metabolomics platform for the assessment of Brazilian propolis

In this work, a metabolomics dataset from 1H nuclear magnetic resonance spectroscopy of Brazilian propolis was analyzed using machine learning algorithms, including feature selection and classification methods. Partial least square-discriminant analysis (PLS-DA), random forest (RF), and wrapper methods combining decision trees and rules with evolutionary algorithms (EA) showed to be complementary approaches, allowing to obtain relevant information as to the importance of a given set of features, mostly related to the structural fingerprint of aliphatic and aromatic compounds typically found in propolis, e.g., fatty acids and phenolic compounds. The feature selection and decision tree-based algorithms used appear to be suitable tools for building classification models for the Brazilian propolis metabolomics regarding its geographic origin, with consistency, high accuracy, and avoiding redundant information as to the metabolic signature of relevant compounds.The work is partially funded by ERDF -European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and PEstOE/ EEI/UI0752/2011. RC's work is funded by a PhD grant from the Portuguese FCT ( ref. SFRH/BD/66201/2009)

New anti-perovskite-type Superconductor ZnNyNi3

We have synthesized a new superconductor ZnNyNi3 with Tc ~3 K. The crystal structure has the same anti-perovskite-type such as MgCNi3 and CdCNi3. As far as we know, this is the third superconducting material in Ni-based anti-perovskite series. For this material, superconducting parameters, lower-critical field Hc1(0), upper-critical field Hc2(0), coherence length x(0), penetration depth l(0), and Gintzburg -Landau parameter k(0) have been experimentally determined.Comment: 13 pages, 3 figures, 1 tabl

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.Financial support for this investigation by National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Biosciences National Laboratory (LNBioCNPEM/MCTI), Foundation for Support of Scientific and Technological Research in the State of Santa Catarina (FAPESC), and Portuguese Foundation for Science and Technology (FCT) is acknowledged. The research fellowship granted by CNPq to the first author is also acknowledged. The work was partially funded by a CNPq and FCT agreement through the PropMine grant

The Affective Impact of Financial Skewness on Neural Activity and Choice

Few finance theories consider the influence of “skewness” (or large and asymmetric but unlikely outcomes) on financial choice. We investigated the impact of skewed gambles on subjects' neural activity, self-reported affective responses, and subsequent preferences using functional magnetic resonance imaging (FMRI). Neurally, skewed gambles elicited more anterior insula activation than symmetric gambles equated for expected value and variance, and positively skewed gambles also specifically elicited more nucleus accumbens (NAcc) activation than negatively skewed gambles. Affectively, positively skewed gambles elicited more positive arousal and negatively skewed gambles elicited more negative arousal than symmetric gambles equated for expected value and variance. Subjects also preferred positively skewed gambles more, but negatively skewed gambles less than symmetric gambles of equal expected value. Individual differences in both NAcc activity and positive arousal predicted preferences for positively skewed gambles. These findings support an anticipatory affect account in which statistical properties of gambles—including skewness—can influence neural activity, affective responses, and ultimately, choice

Tenosynovial giant cell tumors as accidental findings after episodes of distortion of the ankle: two case reports

<p>Abstract</p> <p>Introduction</p> <p>Tenosynovial giant cell tumors are benign tumors of uncertain pathogenesis. They occur in the joints, tendons and synovial bursas. Due to a high recurrence rate of up to 50%, some authors call a giant cell tumor a semimalignant tumor. To date, less than 10 cases of tenosynovial giant cell tumor of the ankle have been published in the international medical literature.</p> <p>Case presentation</p> <p>In this case report, we present two patients with localized tumors that were detected accidentally after the occurrence of ankle sprains with persisting pain in the joint. The tumors were resected by open marginal surgery and regular follow-up examinations were carried out.</p> <p>Conclusions</p> <p>We present an unusual occurrence of a tumor along with a possible follow-up strategy, which has not been previously discussed in the international literature.</p