The log-periodic-AR(1)-GARCH(1,1) model for financial crashes

This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.Comment: 17 pages, 4 figures, 12 tables, to appear in Europen Physical Journal

A randomised, controlled trial of a dietary intervention for adults with major depression (the "SMILES" trial): study protocol

Despite increased investment in its recognition and treatment, depression remains a substantial health and economic burden worldwide. Current treatment strategies generally focus on biological and psychological pathways, largely neglecting the role of lifestyle. There is emerging evidence to suggest that diet and nutrition play an important role in the risk, and the genesis, of depression. However, there are limited data regarding the therapeutic impact of dietary changes on existing mental illness. Using a randomised controlled trial design, we aim to investigate the efficacy and cost-efficacy of a dietary program for the treatment of Major Depressive Episodes. <br /

Direitos humanos e justiciabilidade: pesquisa no Tribunal de Justiça do Rio de Janeiro

Publicado em português, espanhol e inglês.Título em espanhol: Derechos humanos y justiciabilidad: una investigación en Rio de Janeiro. -- Título em inglês: Human rights and justiciability: a survey conducted in Rio de Janeiro."A proposta deste artigo é analisar as informações obtidas no âmbito da pesquisa intitulada “Direitos Humanos no Tribunal de Justiça do Rio de Janeiro: concepção, aplicação e formação”, que tem por objetivo investigar o grau de justiciabilidade dos direitos humanos na prestação jurisdicional dos magistrados de primeira instância da Comarca da Capital do Tribunal de Justiça do Estado do Rio de Janeiro. O estudo conclui que o tipo de vara e a cor do juiz, bem como o grau de conhecimento a respeito dos sistemas internacionais de proteção dos direitos humanos da OEA e da ONU, constituem variáveis significativas para explicar o comportamento dos magistrados no tocante à utilização das normativas internacionais para a fundamentação das sentenças. A elucidação empírica das variáveis supramencionadas revela-se de grande valia na implementação de programas destinados a ampliar o conhecimento dos magistrados na matéria. A pesquisa foi contemplada com o apoio da Faperj.

The log-periodic-AR(1)-GARCH(1,1) model for financial crashes

This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.

Francesco Durante and the first intracranial tumor successfully operated on with long survival (1884)

Francesco Durante was born in Sicily, precisely Letojanni Gallodoro. He contributed to the history of neurosurgery in not only Italy but the whole world. In June 1884, he removed a left frontal meningioma, describing a personal technique of craniotomy with a discontinuous osteotangential section flap. It was the first such operation to be performed in any country after which the patient had a long survival. The important and pioneering contribution made by Durante to the history of neurosurgery is testified by his Treaty on Pathology and Surgical Therapy. Durante's procedure for craniotomy remained the best for several years. His contributions are still valid in medicine today, within not only the neurosurgical community but also other surgical disciplines, because he also developed innovative practices in the fields of oncology, general surgery, and orthopedics in addition to designing special surgical instruments

K-medoid clustering of premotor firing patterns supports fine decoding of macaque reach-and-grasp

Cortical control of reach-and-grasp movements is one of the key challenges of brain machine interfaces (BMI). Recent advancements enabled tetraplegic subjects to control robotic arms through this approach. However, the fine control of such movements is usually automatic rather than controlled by the patient, and this might not be the optimal solution in real life environments. Here we show that fine properties of reach-and-grasp movement can be decoded thanks to K-medoid clustering. We recorded the activity of 71 neurons from the premotor cortex of a macaque performing different reach-and-grasp movements depending on the shape and the position of the object presented. The K-medoid algorithm selected in an unsupervised way four firing patterns associated with specific clusters of neurons' activity. Describing the cortical activity during each movement through the distances from these four medoids and feeding the resulting vector into a support vector machine (SVM) algorithm enabled the identification of the specific movement performed. This decoding approach could in future support a finer control of robotic arms - or other devices - through cortical BMI

Core Fermentation (CoFe) granules focus coordinated glycolytic mRNA localization and translation to fuel glucose fermentation

SummaryGlycolysis is a fundamental metabolic pathway for glucose catabolism across biology, and glycolytic enzymes are amongst the most abundant proteins in cells. Their expression at such levels provides a particular challenge. Here we demonstrate that the glycolytic mRNAs are localized to granules in yeast and human cells. Detailed live cell and smFISH studies in yeast show that the mRNAs are actively translated in granules, and this translation appears critical for the localization. Furthermore, this arrangement is likely to facilitate the higher level organisation and control of the glycolytic pathway. Indeed, the degree of fermentation required by cells is intrinsically connected to the extent of mRNA localization to granules. On this basis, we term these granules, Core Fermentation (CoFe) granules; they appear to represent translation factories allowing high-level co-ordinated enzyme synthesis for a critical metabolic pathway.</jats:p