PRICE FORECASTING FOR FUTURE CONTRACTS ON AGRIBUSINESS THROUGH NEURAL NETWORK AND MULTIVARIATE SPECTRAL ANALYSIS

This study aimed to compare the forecasting results from combining the two models,   Multivariate Singular Spectrum Analysis (MSSA)  and Artificial Neural Network (ANN), with the results obtained from classical forecasting and neural network models for prices of agricultural future contracts traded on BM&FBOVESPA. The forecasting results of the proposed combination, compared with those obtained from classical forecasting and neural network models showed the best performance for price forecasting. The use of the error measurements and predictive statistical test for the step-ahead confirm this. The research can help market professionals in the development and implementation of risk management policies due to the relevance of price forecasting as a planning tool, in addition to being useful in market behavior analysis in specifying the price trend of future contracts

Previsão de preços de commodities agrícolas através do modelo de análise espectral singular multivariada: Agricultural commodity price forecasting through the multivariate singular spectrum analysis model

Esta pesquisa teve como proposta realizar previsões dos preços de um grupo de commodities através do modelo espectral de análise multivariada e compará-las com aquelas obtidas por modelos clássicos de previsão. A escolha das commodities etanol, boi gordo, milho, café e soja deu-se por conta do destaque na pauta de exportações no ano de 2013. O modelo espectral multivariado demonstrou-se adequado, quando comparado com os demais, ao permitir melhores desempenhos preditivos. Os resultados obtidos no período fora da amostra, mediante o uso das medidas de erro e do teste estatístico, confirmam isso. A pesquisa pode ajudar os profissionais do mercado na formulação e na aplicação de políticas direcionadas ao setor agrícola por conta da relevância da previsão dos preços como instrumento de planejamento bem como na análise do comportamento do mercado agrícola ao especificar a tendência dos preços

Previsão de Preços Através da Análise Espectral Multivariada: Evidências para Commodities da BM&Fbovespa

This study aimed to forecast the prices of a group of commodities through the multivariate spectral analysis model and compare them with those obtained by classical forecasting and neural network models. The choice of commodities such as ethanol, cattle, corn, coffee and soy was due to the emphasis in the exports in 2013. The multivariate spectral model has proved to be suitable, when compared with others, by enabling a better predictive performance. The results obtained in the out-of-sample period, through the use of measurement error and statistical test, confirm this. This research may help market professionals in formulating and implementing policies targeted to the agricultural sector due to the relevance of price forecast as a planning instrument and analysis of the finance market behavior for those who need protection against price fluctuations.Esta pesquisa teve como proposta realizar previsões dos preços de um grupo de commodities através do modelo espectral de análise multivariada e compará-las com aquelas obtidas por modelos clássicos de previsão e de redes neurais. A escolha das commodities etanol, boi gordo, milho, café e soja deu-se por conta do destaque na pauta de exportações no ano de 2013. O modelo espectral multivariado demonstrou-se adequado, quando comparado com os demais, ao permitir melhores desempenhos preditivos. Os resultados obtidos no período fora da amostra, mediante o uso das medidas de erro e do teste estatístico, confirmam isso. A pesquisa pode auxiliar os profissionais do mercado na formulação e aplicação de políticas direcionadas ao setor agrícola por conta da relevância da previsão dos preços como instrumento de planejamento bem como na análise do comportamento do mercado financeiro para aqueles que necessitam de proteção a oscilações dos preços

O desenvolvimento de estratégias para evitar riscos, obter ouro e tornar a concorrência irrelevante - O caso da “Azul”.

RESUMO O objetivo deste estudo é comparar as estratégias do enfrentamento do risco de demanda utilizado pelas empresas americanas  “low cost/low fare” com o posicionamento e a estratégia da Azul, a mais recente  Companhia  do gênero criada no Brasil  e  co-ligada à Americana Jet Blue. A presente analise está voltada para o entendimento das condições que influenciam de maneira mais destacada  o planejamento estratégico  das empresas para a detecção de oportunidades de alto retorno, compatíveis com suas competências, em ambientes de risco  elevado.  Serão abordados  os conceitos do risco como chave para uma estratégia competitiva e o papel da incerteza na definição e implantação do planejamento estratégico. Na continuidade  serão apresentadas,  em resumo,  as principais  características das empresas de aviação “low cost/low fare” estadunidenses. Palavras chaves:  Empresas Aéreas,  low cost/low fare, risco, objetivos amplos, objetivos centrais

Unraveling structural and compositional information in 3D FinFET electronic devices

Non-planar Fin Field Effect Transistors (FinFET) are already present in modern devices. The evolution from the well-established 2D planar technology to the design of 3D nanostructures rose new fabrication processes, but a technique capable of full characterization, particularly their dopant distribution, in a representative (high statistics) way is still lacking. Here we propose a methodology based on Medium Energy Ion Scattering (MEIS) to address this query, allowing structural and compositional quantification of advanced 3D FinFET devices with nanometer spatial resolution. When ions are backscattered, their energy losses unfold the chemistry of the different 3D compounds present in the structure. The FinFET periodicity generates oscillatory features as a function of backscattered ion energy and, in fact, these features allow a complete description of the device dimensions. Additionally, each measurement is performed over more than thousand structures, being highly representative in a statistical meaning. Finally, independent measurements using electron microscopy corroborate the proposed methodolog

Severe Asthma Standard-of-Care Background Medication Reduction With Benralizumab: ANDHI in Practice Substudy

Background: The phase IIIb, randomized, parallel-group, placebo-controlled ANDHI double-blind (DB) study extended understanding of the efficacy of benralizumab for patients with severe eosinophilic asthma. Patients from ANDHI DB could join the 56-week ANDHI in Practice (IP) single-arm, open-label extension substudy. Objective: Assess potential for standard-of-care background medication reductions while maintaining asthma control with benralizumab. Methods: Following ANDHI DB completion, eligible adults were enrolled in ANDHI IP. After an 8-week run-in with benralizumab, there were 5 visits to potentially reduce background asthma medications for patients achieving and maintaining protocol-defined asthma control with benralizumab. Main outcome measures for non-oral corticosteroid (OCS)-dependent patients were the proportions with at least 1 background medication reduction (ie, lower inhaled corticosteroid dose, background medication discontinuation) and the number of adapted Global Initiative for Asthma (GINA) step reductions at end of treatment (EOT). Main outcomes for OCS-dependent patients were reductions in daily OCS dosage and proportion achieving OCS dosage of 5 mg or lower at EOT. Results: For non-OCS-dependent patients, 53.3% (n = 208 of 390) achieved at least 1 background medication reduction, increasing to 72.6% (n = 130 of 179) for patients who maintained protocol-defined asthma control at EOT. A total of 41.9% (n = 163 of 389) achieved at least 1 adapted GINA step reduction, increasing to 61.8% (n = 110 of 178) for patients with protocol-defined EOT asthma control. At ANDHI IP baseline, OCS dosages were 5 mg or lower for 40.4% (n = 40 of 99) of OCS-dependent patients. Of OCS-dependent patients, 50.5% (n = 50 of 99) eliminated OCS and 74.7% (n = 74 of 99) achieved dosages of 5 mg or lower at EOT. Conclusions: These findings demonstrate benralizumab's ability to improve asthma control, thereby allowing background medication reduction

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity