Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).

Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).

Reviewing the sustainability/stationarity of current account imbalances with tests for bounded integration

We investigate for 26 OECD economies whether their current account imbalances to GDP are driven by stochastic trends. Regarding bounded stationarity as the more natural counterpart of sustainability, results from Phillips–Perron tests for unit root and bounded unit root processes are contrasted. While the former hint at stationarity of current account imbalances for 12 economies, the latter indicate bounded stationarity for only six economies. Through panel-based test statistics, current account imbalances are diagnosed as bounded non-stationary. Thus, (spurious) rejections of the unit root hypothesis might be due to the existence of bounds reflecting hidden policy controls or financial crises.

The Determinants of Country Risk in Eastern European Countries. Evidence from Sovereign Bond Spreads. Bruges European Economic Research (BEER) Papers 8/November 2006

The paper studies country risk in two Central and Eastern European countries - Bulgaria and Poland. The long run relationship between the yield differential (spread) of Eastern European national bonds (denominated in US dollars) over a US Treasury bond on one the hand and the country’s fundamentals as well as an US interest rate on the other hand, is examined. The cointegrated VAR model is used. First, the yield differentials are analyzed on a country by country basis to extract stochastic trends which are common for all bonds in a given country. Thereafter, the risk is disentangled into country and higher level risk. This paper is among the first ones which use time series data to study the evidence from sovereign bond spreads in Eastern Europe.

Stochastic modelling of the reservoir lithological and petrophysical attributes. A case study of the Middle East carbonate reservoir

Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)

New trends in natural language processing: statistical natural language processing.

The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. Recently, more and more work is shifting toward hybrid methods that combine new empirical corpus-based methods, including the use of probabilistic and information-theoretic techniques, with traditional symbolic methods. This work is made possible by the recent availability of linguistic databases that add rich linguistic annotation to corpora of natural language text. Already, these methods have led to a dramatic improvement in the performance of a variety of NLP systems with similar improvement likely in the coming years. This paper focuses on these trends, surveying in particular three areas of recent progress: part-of-speech tagging, stochastic parsing, and lexical semantics.

Bipolar Disorder: Recent Advances And Future Trends In Bioanalytical Developments For Biomarker Discovery.

In this manuscript we briefly describe bipolar disorder (a depressive and manic mental disease), its classification, its effects on the patient, which sometimes include suicidal tendencies, and the drugs used for treatment. We also address the status quo with regard to diagnosis of bipolar disorder and recent advances in bioanalytical approaches for biomarker discovery. These approaches focus on blood samples (serum and plasma) and proteins as the main biomarker targets, and use various strategies for protein depletion. Strategies include use of commercially available kits or other homemade strategies and use of classical proteomics methods for protein identification based on bottom-up or top-down approaches, which used SELDI, ESI, or MALDI as sources for mass spectrometry, and up-to-date mass analyzers, for example Orbitrap. We also discuss some future objectives for treatment of this disorder and possible directions for the correct diagnosis of this still-unclear mental illness.

Trends and strategies of ozone application in environmental problems

Efforts presented by the scientific community in recent years towards the development of numerous green chemical processes and wastewater treatment technologies are presented and discussed. In the light of these approaches, environmentally friendly technologies, as well as the key role played by the well-known advanced oxidation processes, are discussed, giving special attention to the ones comprising ozone applications. Fundamentals and applied aspects dealing with ozone technology and its application are also presented.

Is size structure a good measure of future trends of plant populations? an empirical approach using five woody species from the Cerrado (Brazilian savanna)

Size distributions in woody plant populations have been used to assess their regeneration status, assuming that size structures with reverse-J shapes represent stable populations. We present an empirical approach of this issue using five woody species from the Cerrado. Considering count data for all plants of these five species over a 12-year period, we analyzed size distribution by: a) plotting frequency distributions and their adjustment to the negative exponential curve and b) calculating the Gini coefficient. To look for a relationship between size structure and future trends, we considered the size structures from the first census year. We analyzed changes in number over time and performed a simple population viability analysis, which gives the mean population growth rate, its variance and the probability of extinction in a given time period. Frequency distributions and the Gini coefficient were not able to predict future trends in population numbers. We recommend that managers should not use measures of size structure as a basis for management decisions without applying more appropriate demographic studies.

Reaction-diffusion stochastic lattice model for a predator-prey system

We have the purpose of analyzing the effect of explicit diffusion processes in a predator-prey stochastic lattice model. More precisely we wish to investigate the possible effects due to diffusion upon the thresholds of coexistence of species, i. e., the possible changes in the transition between the active state and the absorbing state devoid of predators. To accomplish this task we have performed time dependent simulations and dynamic mean-field approximations. Our results indicate that the diffusive process can enhance the species coexistence.

Time trends and predictors of mortality from ill-defined causes in old age: 9 year folllow-up of the Bambuí cohort study (Brazil)

The study objective was to examine differentials in time trends and predictors of deaths assigned to symptoms, signs and ill-defined conditions in comparison with other ill-defined conditions (ill-defined cardiovascular diseases, cancer and injury) in a population-based cohort study. Of 1,606 baseline participants aged 60 years and over, 524 died during 9-year follow-up and were included in this study. Deaths coded to "symptoms" declined by 77% in the period from 1997-1999 to 2003-2005. Deaths coded to other ill-defined conditions remained unchanged. The calendar period 2003-2005 (RR = 0.25; 95%CI: 0.09-0.70) and in-hospital deaths (RR = 0.16; 95%CI: 0.08-0.34) were independently associated with "symptoms", but not with other ill-defined conditions. Baseline socio-demographic characteristics and chronic diseases were not predictors of these outcomes. International and national agencies have focused on the reduction of deaths assigned to "symptoms" to improve the registration of vital statistics, while other ill-defined conditions have received little attention. Our data provide evidence supporting the need to redress this situation.

Recent trends in maternal, newborn, and child health in Brazil: progress toward Millennium Development Goals 4 and 5

We analyzed Brazil's efforts in reducing child mortality, improving maternal and child health, and reducing socioeconomic and regional inequalities from 1990 through 2007. We compiled and reanalyzed data from several sources, including vital statistics and population-based surveys. We also explored the roles of broad socioeconomic and demographic changes and the introduction of health sector and other reform measures in explaining the improvements observed. Our findings provide compelling evidence that proactive measures to reduce health disparities accompanied by socioeconomic progress can result in measurable improvements in the health of children and mothers in a relatively short interval. Our analysis of Brazil's successes and remaining challenges to reach and surpass Millennium Development Goals 4 and 5 can provide important lessons for other low- and middle-income countries

Trends in morbid obesity and in bariatric surgeries covered by the Brazilian public health system

Background Obesity is an increasingly serious public health problem on a global level. Morbid obesity, defined as a body mass index greater than 40 kg/m2, is associated with increased mortality and a high burden of obesity-related morbidities. Methods To study the prevalence of morbid obesity in Brazil, three national anthropometric surveys were reanalyzed. Data about bariatric surgeries were obtained from the Ministry of Health Hospital Information System, which is available online. Results A 255% rise in the prevalence of morbid obesity was observed, starting at 0.18% in 1975-1976 and growing to 0.33% in 1989 and 0.64% in 2002-2003. There was a higher rate in the South in the first two surveys, but the prevalence in the Southeast rose steadily, reaching 0.77% in 2002-2003 and overtaking the South. Since 1999, the Brazilian Unified Health System has covered surgical treatment for morbid obesity. From 2000 to 2006, there was a sixfold increase in the number of surgeries, which topped the 2,500 mark in 2006. The geographic distribution of these surgeries is heavily concentrated in the Southeast, the most developed region of Brazil, where there is also the highest prevalence of morbid obesity. This was followed by the Southern region. Conclusions The figures for the rise in morbid obesity in Brazil are startling, especially the increase among men. This is a situation that calls for further study, alongside measures to encourage the adoption of healthy lifestyles. Preventive measures aimed at slowing down or reversing the obesity epidemic are urgently required

A spatial approach for the epidemiology of antibiotic use and resistance in community-based studies: the emergence of urban clusters of Escherichia coli quinolone resistance in Sao Paulo, Brasil

Background: Population antimicrobial use may influence resistance emergence. Resistance is an ecological phenomenon due to potential transmissibility. We investigated spatial and temporal patterns of ciprofloxacin (CIP) population consumption related to E. coli resistance emergence and dissemination in a major Brazilian city. A total of 4,372 urinary tract infection E. coli cases, with 723 CIP resistant, were identified in 2002 from two outpatient centres. Cases were address geocoded in a digital map. Raw CIP consumption data was transformed into usage density in DDDs by CIP selling points influence zones determination. A stochastic model coupled with a Geographical Information System was applied for relating resistance and usage density and for detecting city areas of high/low resistance risk. Results: E. coli CIP resistant cluster emergence was detected and significantly related to usage density at a level of 5 to 9 CIP DDDs. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. Conclusions: There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. The usage density of 5-9 CIP DDDs per 1,000 inhabitants within the same influence zone was the resistance triggering level. This level led to E. coli resistance clustering, proving that individual resistance emergence and dissemination was affected by antimicrobial population consumption.

Crossover between the extended and localized regimes in stochastic partially self-avoiding walks in one-dimensional disordered systems

Consider N sites randomly and uniformly distributed in a d-dimensional hypercube. A walker explores this disordered medium going to the nearest site, which has not been visited in the last mu (memory) steps. The walker trajectory is composed of a transient part and a periodic part (cycle). For one-dimensional systems, travelers can or cannot explore all available space, giving rise to a crossover between localized and extended regimes at the critical memory mu(1) = log(2) N. The deterministic rule can be softened to consider more realistic situations with the inclusion of a stochastic parameter T (temperature). In this case, the walker movement is driven by a probability density function parameterized by T and a cost function. The cost function increases as the distance between two sites and favors hops to closer sites. As the temperature increases, the walker can escape from cycles that are reminiscent of the deterministic nature and extend the exploration. Here, we report an analytical model and numerical studies of the influence of the temperature and the critical memory in the exploration of one-dimensional disordered systems.