Dynamical local models for segmentation and prediction of financial time series

In the analysis and prediction of many real-world time series, the assumption of stationarity is not valid. A special form of non-stationarity, where the underlying generator switches between (approximately) stationary regimes, seems particularly appropriate for financial markets. We introduce a new model which combines a dynamic switching (controlled by a hidden Markov model) and a non-linear dynamical system. We show how to train this hybrid model in a maximum likelihood approach and evaluate its performance on both synthetic and financial data.

Local biomass control on the composition and reactivity of particulate organic matter in aquatic environments

Freshwater ecosystems have been recognized as important components of the global carbon cycle, and the flux of organic matter (OM) from freshwater to marine environments can significantly affect estuarine and coastal productivity. The focus of this study was the assessment of carbon dynamics in two aquatic environments, namely the Florida Everglades and small prairie streams in Kansas, with the aim of characterizing the biogeochemistry of OM. In the Everglades, particulate OM (POM) is mostly found as a layer of flocculent material (floc). While floc is believed to be the main energy source driving trophic dynamics in this oligotrophic wetland, not much is known about its biogeochemistry. The objective of this study was to determine the origin/sources of OM in floc using biomarkers and pigment-based chemotaxonomy to assess specific biomass contributions to this material, on a spatial (freshwater marshes vs. mangrove fringe) and seasonal (wet vs. dry) scales. It was found that floc OM is derived from the local vegetation (mainly algal components and macrophyte litter) and its composition is controlled by seasonal drivers of hydrology and local biomass productivity. Photo-reactivity experiments showed that light exposure on floc resulted in photo-dissolution of POC with the generation of significant amounts of both dissolved OM (DOM) and nutrients (N & P), potentially influencing nutrient dynamics in this ecosystem. The bio-reactivity experiments determined as the amount and rate of CO2 evolution during incubation were found to vary on seasonal and spatial scales and were highly influenced by phosphorus limitation. Not much is known on OM dynamics in small headwater streams. The objective of this study was to determine carbon dynamics in sediments from intermittent prairie streams, characterized by different vegetation cover for their watershed (C4 grasses) vs. riparian zone (C3 plants). In this study sedimentary OM was characterized using a biomarker and compound specific carbon stable isotope approach. It was found that the biomarker composition of these sediments is dominated by higher plant inputs from the riparian zone, although inputs from adjacent prairie grasses were also apparent. Conflicting to some extent with the River Continuum Concept, sediments of the upper reaches contained more degraded OM, while the lower reaches were enriched in fresh material deriving from higher plants and plankton sources as a result of hydrological regimes and particle sorting.

Age models and stable isotopes of sediment cores from the northern seas

Oxygen and carbon isotope measurements were carried out on tests of planktic foraminifers N. pachyderma (sin.) from eight sediment cores taken from the eastern Arctic Ocean, the Fram Strait, and the lceland Sea, in order to reconstruct Arctic Ocean and Norwegian-Greenland Sea circulation patterns and ice covers during the last 130,000 years. In addition, the influence of ice, temperature and salinity effects on the isotopic signal was quantified. Isotope measurements on foraminifers from sediment surface samples were used to elucidate the ecology of N. pachyderma (sin.). Changes in the oxygen and carbon isotope composition of N. pachyderma (sin.) from sediment surface samples document the horizontal and vertical changes of water mass boundaries controlled by water temperature and salinity, because N. pachyderma (sin.) shows drastic changes in depth habitats, depending on the water mass properties. It was able to be shown that in the investigated areas a regional and spatial apparent increase of the ice effect occurred. This happened especially during the termination I by direct advection of meltwaters from nearby continents or during the termination and in interglacials by supply of isotopically light water from rivers. A northwardly proceeding overprint of the 'global' ice effect, increasing from the Norwegian-Greenland Sea to the Arctic Ocean, was not able to be demonstrated. By means of a model the influence of temperature and salinity on the global ice volume signal during the last 130,000 years was recorded. In combination with the results of this study, the model was the basis for a reconstruction of the paleoceanographic development of the Arctic Ocean and the Norwegian-Greenland Sea during this time interval. The conception of a relatively thick and permanent sea ice cover in the Nordic Seas during glacial times should be replaced by the model of a seasonally and regionally highly variable ice cover. Only during isotope stage 5e may there have been a local deep water formation in the Fram Strait.

Do U.S. and Colombian macro factors improve the forecasting ability of unrestricted VAR models of the local term structure of interest rate?

Este estudio empírico compara la capacidad de los modelos Vectores auto-regresivos (VAR) sin restricciones para predecir la estructura temporal de las tasas de interés en Colombia -- Se comparan modelos VAR simples con modelos VAR aumentados con factores macroeconómicos y financieros colombianos y estadounidenses -- Encontramos que la inclusión de la información de los precios del petróleo, el riesgo de crédito de Colombia y un indicador internacional de la aversión al riesgo mejora la capacidad de predicción fuera de la muestra de los modelos VAR sin restricciones para vencimientos de corto plazo con frecuencia mensual -- Para vencimientos de mediano y largo plazo los modelos sin variables macroeconómicas presentan mejores pronósticos sugiriendo que las curvas de rendimiento de mediano y largo plazo ya incluyen toda la información significativa para pronosticarlos -- Este hallazgo tiene implicaciones importantes para los administradores de portafolios, participantes del mercado y responsables de las políticas

A critical analysis of e-government evaluation models at national and local municipal levels

Abstract: The importance of e-government models lies in their offering a basis to measure and guide e-government. There is still no agreement on how to assess a government online. Most of the e-government models are not based on research, nor are they validated. In most countries, e-government has not reached higher stages of growth. Several scholars have shown a confusing picture of e-government. What is lacking is an in-depth analysis of e-government models. Responding to the need for such an analysis, this study identifies the strengths and weaknesses of major national and local e-government evaluation models. The common limitations of most models are focusing on the government and not the citizen, missing qualitative measures, constructing the e-equivalent of a bureaucratic administration, and defining general criteria without sufficient validations. In addition, this study has found that the metrics defined for national e-government are not suitable for municipalities, and most of the existing studies have focused on national e-governments even though local ones are closer to citizens. There is a need for developing a good theoretical model for both national and local municipal e-government.

Local influence analysis in general spatial models

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Use of Coarse-resolution models of species' distributions to guide local conservation inferences

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter ( Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures

The Effects of Various Types of Feed additives on The Chemical Composition of Local Chicken Meat (Gallus domestica).

Abstract. This study aims to determine the effect of giving various types of feed additives to the chemical composition value of super chicken chicken (Gallus domestica). This research is an experimental research using 20 super chicken chickens that come from chicken growth research (growth study). The design used in this study was Completely Randomized Design (RAL), consisting of 4 treatments and 5 replications. The treatment given was (A0 = control (Vita chick 0.7 gram / liter; A1 = 20 ml / liter probio-FM; A2 = 0.08% MOS-oligosaccharide / kg of feed and A3 = herbal leuser KI 5 ml / liter). is a 90 day old super chicken breast Chicken Variable observed moisture content, protein content and fat content The data obtained were analyzed by using vocabulary and tested further by Duncan's Multiple Range Test The results showed that treatment (P> 0,05) to the value of water content and protein of super chicken fowl.Average value of water content at each treatment A0 (69,81%), A1 (70,74%), A2 (71,56%) and A3 (71,52%) while mean value of protein A0 (18,95%), A1 (19,61%), A2 (19,01%) and A3 (19,14%)) P <0,05) to the fat content of super chicken flesh, mean of fat content were A0 (2.02%), A1 (1.49%), A2 (1.37%) and A3 (2.0%).

Local and nonlocal integro-differential reaction-diffusion models for protein dynamics in Alzheimer's disease

In this work, integro-differential reaction-diffusion models are presented for the description of the temporal and spatial evolution of the concentrations of Abeta and tau proteins involved in Alzheimer's disease. Initially, a local model is analysed: this is obtained by coupling with an interaction term two heterodimer models, modified by adding diffusion and Holling functional terms of the second type. We then move on to the presentation of three nonlocal models, which differ according to the type of the growth (exponential, logistic or Gompertzian) considered for healthy proteins. In these models integral terms are introduced to consider the interaction between proteins that are located at different spatial points possibly far apart. For each of the models introduced, the determination of equilibrium points with their stability and a study of the clearance inequalities are carried out. In addition, since the integrals introduced imply a spatial nonlocality in the models exhibited, some general features of nonlocal models are presented. Afterwards, with the aim of developing simulations, it is decided to transfer the nonlocal models to a brain graph called connectome. Therefore, after setting out the construction of such a graph, we move on to the description of Laplacian and convolution operations on a graph. Taking advantage of all these elements, we finally move on to the translation of the continuous models described above into discrete models on the connectome. To conclude, the results of some simulations concerning the discrete models just derived are presented.

Influência do transporte e mudança de local de manejo nas variáveis fisiológicas e produtivas de cabras Alpinas

Estudaram-se o efeito do transporte e a mudança de local de manejo sobre a produção e a composição do leite e sobre as variáveis fisiológicas, utilizando-se 12 cabras da raça Alpina em final de lactação. Semanalmente, foram mensuradas a produção e composição do leite e a contagem de células somáticas, além do volume do leite residual após administração de ocitocina. Foram colhidas amostras de sangue para dosagem hormonal (cortisol) e enzimática (glicose) no plasma no dia do transporte: antes (7h10min) e após (8h20min, 8h30min e 10h30min) o transporte. Nas três semanas subsequentes ao transporte, também foram colhidas amostras de sangue às 8h20min. Obtiveram-se teores mais elevados (P<0,05) de cortisol e glicose após o transporte e a mudança de local de manejo, e menor produção de leite (P<0,05) um dia após o evento. Porcentagem de gordura (P<0,05) e contagem de células somáticas apresentaram diferenças significativas (P<0,05) após o transporte. Os resultados permitem concluir que o transporte é um agente estressor que pode, momentaneamente, influenciar a produção animal.

Técnicas de diagnóstico de influência local na análise espacial da produtividade da soja

A modelagem da estrutura de dependência espacial pela abordagem da geoestatística é fundamental para a definição de parâmetros que definem esta estrutura, e que são utilizados na interpolação de valores em locais não amostrados pela técnica de krigagem. Entretanto, a estimação de parâmetros pode ser muito afetada pela presença de observações atípicas nos dados amostrados. O desenvolvimento deste trabalho teve por objetivo utilizar técnicas de diagnóstico de influência local em modelos espaciais lineares gaussianos, utilizados em geoestatística, para avaliar a sensibilidade dos estimadores de máxima verossimilhança e máxima verossimilhança restrita na presença de dados discrepantes. Estudos com dados experimentais mostraram que tanto a presença de valores atípicos como de valores considerados influentes, pela análise de diagnóstico, pode exercer forte influência nos mapas temáticos, alterando, assim, a estrutura de dependência espacial. As aplicações de técnicas de diagnóstico de influência local devem fazer parte de toda análise geoestatística a fim de garantir que as informações contidas nos mapas temáticos tenham maior qualidade e possam ser utilizadas com maior segurança pelo agricultor.

The ichthyofauna of upper rio Capivari: defining conservation strategies based on the composition and distribution of fish species

Although the rio Capivari basin is recognized as an area of great importance for the ichthyofauna, it lacks virtually every basic requirement for the definition of appropriate conservation strategies, since not even its species composition is known. The objective of this work is to determine the composition and distribution of fish species in the upper rio Capivari basin, relating them to the local physical features, and to evaluate the effectiveness of proposed conservations units, delimited based on areas of native vegetation remains, on the conservation of local ichthyofauna. During 2007, 50 different watercourses were sampled with gillnets, cast nets and kick nets. A total of 1308 individuals belonging to 41 species were captured. Degree of conservation, altitude and width were the parameters that best explained fish species richness. Considering the recently proposed boundaries for potential conservation units in the region only 15 or 20 out of 41 species would be found in the State Park and Environmental Protection Area respectively. In practice, the proposed conservation units would not be effective tools for fish conservation, since it would be located in mountainous areas of high altitude, of headwaters streams and where few species are found. In such context, the conservation of specific stretches of larger rivers is critical.

Association between osteoporosis and rheumatoid arthritis in women: a cross-sectional study

CONTEXT AND OBJECTIVES: Osteoporosis has frequently been observed in patients with rheumatoid arthritis. The present study was undertaken in order to evaluate factors associated with osteoporosis among women with rheumatoid arthritis. DESIGN AND SETTING: Cross-sectional study, carried out in a public hospital in São Paulo. METHODS: The participants were 83 women with rheumatoid arthritis (53.7 ± 10.0 years old). Bone mineral density (BMD) and body composition were measured by dual energy X-ray absorptiometry. The patients were divided into three groups according to BMD: group 1, normal BMD (n = 24); group 2, osteopenia (n = 38); and group 3, osteoporosis (n = 21). Tests were performed to compare differences in means and correlations, with adjustments for age, duration of disease and cumulative corticosteroid. The relationships between clinical factors, physical activity score, dietary intake, body composition and biochemical parameters were analyzed using linear regression models. RESULTS: Mean calcium, vitamin D and omega-6 intakes were lower than the recommendations. Associations were found between BMD and age, disease duration, parathyroid hormone concentration and fat intake. The linear regression model showed that being older, with more years of disease and lower weight were negatively correlated with BMD [Total femur = 0.552 + 0.06 (weight) + 0.019 (total physical activity) - 0.05 (age) - 0.003 (disease duration); R² = 48.1; P < 0.001]. CONCLUSION: The present study indicates that nutritional factors and body composition are associated with bone mass in women with rheumatoid arthritis.

Body trunk fat and insulin resistance in post-pubertal obese adolescents

CONTEXT AND OBJECTIVE: Insulin resistance is a metabolic disorder commonly associated with excess body fat accumulation that may increase chronic disease risk. The present study was undertaken to evaluate the relationship between body composition and insulin resistance among obese adolescents. DESIGN AND SETTING: Cross-sectional study, at the Adolescence Center, Pediatric Department, Universidade Federal de São Paulo. METHODS: Body composition was assessed using dual-energy X-ray absorptiometry. Dietary intake was evaluated using a three-day dietary record. The biochemical evaluation comprised glucose, insulin, serum lipid, leptin and ghrelin measurements. Insulin resistance was calculated by means of the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Forty-nine post-pubertal obese adolescents participated in the study: 12 boys and 37 girls of mean age 16.6 (1.4) years and mean body mass index (BMI) of 35.0 (3.9) kg/m². The mean glucose, insulin and HOMA values were 90.3 (6.4) mg/dl, 16.6 (8.1) µIU/ml and 3.7 (1.9), respectively. Hyperinsulinemia and insulin resistance were observed in 40.2% and 57.1% of the subjects, respectively. Adolescents with insulin resistance had higher BMI and body trunk fat. There was a trend towards higher leptin concentration in obese individuals with insulin resistance. Insulin resistance was positively correlated with body trunk fat, BMI, body fat mass (kg), leptin and body fat percentage. Furthermore, there was a negative correlation between HOMA-IR and lean body mass. The body composition predicted 30% of the HOMA-IR levels, according to linear regression models. CONCLUSION: Body trunk fat was significantly associated with insulin resistance, demonstrating the clinical importance of abdominal obesity during adolescence.