Early and post transition metal complexes as a single of combined components in the ethylene and isoprene polynerization

In this work is reported, in a first step, the effect of different experimental parameters and their relation with polymer properties using the homogeneous binary catalyst system composed by Ni(α-diimine)Cl2 (α-diimine = 1,4-bis(2,6-diisopropylphenyl)- acenaphthenediimine) and {TpMs*}V(Ntbu)Cl2 (TpMs* = hydridobis(3-mesitylpyrazol-1- yl)(5-mesitylpyrazol-1-yl)) activated with MAO. This complexes combination produces, in a single reactor, polyethylene blends with different and controlled properties dependent on the polymerization temperature, solvent and Nickel molar fraction (xNi). In second, the control of linear low density polyethylene (LLDPE) production was possible, using a combination of catalyst precursors {TpMs}NiCl (TpMs = hydridotris(3- mesitylpyrazol-1-yl)) and Cp2ZrCl2, activated with MAO/TMA, as Tandem catalytic system. The catalytic activities as well as the polymer properties are dependent on xNi. Polyethylene with different Mw and controlled branches is produced only with ethylene monomer. Last, the application group 3 metals catalysts based, M(allyl)2Cl(MgCl2)2.4THF (M = Nd, La and Y), in isoprene polymerization with different cocatalysts systems and experimental parameters is reported. High yields and polyisoprene with good and controlled properties were produced. The metal center, cocatalysts and the experimental parameters are determinant for the polymers properties and their control. High conversions in cis-1,4- or trans-1,4-polyisoprene were obtained and the polymer microstructure depending of cocatalyst and metal type. Combinations of Y and La precursors were effective systems for the cis/transpolyisoprene blends production, and the control of cis-trans-1,4-microstructures by Yttrium molar fraction (xY) variation was possible.

O problema da criação e consolidação de conhecimento na Philips Components Display - PCD - Unidade São José dos Campos

Analisa o modelo de criação de conhecimento da Philips Components Display e confronta-o com um modelo teórico. Aborda as diferenças culturais na aplicação do modelo teórico e que impactos essas diferenças representas na aplicalidade desse modelo na cultura da PCD e brasileira

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

It is well known that cointegration between the level of two variables (e.g. prices and dividends) is a necessary condition to assess the empirical validity of a present-value model (PVM) linking them. The work on cointegration,namelyon long-run co-movements, has been so prevalent that it is often over-looked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. This amounts to investigate whether short-run co-movememts steming from common cyclical feature restrictions are also present in such a system. In this paper we test for the presence of such co-movement on long- and short-term interest rates and on price and dividend for the U.S. economy. We focuss on the potential improvement in forecasting accuracies when imposing those two types of restrictions coming from economic theory.

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Multivariate unit root tests

A new multivariate test for the detection ofunit roots is proposed. Use is made ofthe possible correlations between the disturbances of difIerent series, and constrained and unconstrained SURE estimators are employed. The corresponding asymptotic distributions, for the case oftwo series, are obtained and a table with criticai vaIues is generated. Some simulations indivate that the procedure performs better than the existing alternatives.

Simulation-based smoothing and filtering in factor stochastic volatility models : two econometric applications

In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.

Simulation -based smoothing and filtering in factor stochastic volatility models : two econometric applications (July-2001)

The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

Employing the Components of the Human Development Index to Drive Resources to Educational Policies

A new form of composition of the indicators employed to generate the United Nations Human Development Index (HDI) is presented here. This form of composition is based on the assumption that random errors affect the measurement of each indicator. This assumption allows for replacing the vector of evaluations according to each indicator by vectors of probabilities of being the best or the worst according to such attribute. The probabilistic composition of such probabilities of preference according to each indicator into probabilities of being the best or the worst according to all of them generates indices that may unveil, on one hand, performances to be followed and, on the other hand, extreme conditions that an additive composition would hide. Differences between the results of application of the diverse forms of composition are examined in the case of the HDI and in the case of the districts version of the HDI employed to compare Brazilian municipalities. It is verified that the smallest correlation between the education.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

Using a sequence of nested multivariate models that are VAR-based, we discuss different layers of restrictions imposed by present-value models (PVM hereafter) on the VAR in levels for series that are subject to present-value restrictions. Our focus is novel - we are interested in the short-run restrictions entailed by PVMs (Vahid and Engle, 1993, 1997) and their implications for forecasting. Using a well-known database, kept by Robert Shiller, we implement a forecasting competition that imposes different layers of PVM restrictions. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to the unrestricted VAR. Moreover, imposing short-run restrictions produces forecast winners 70% of the time for the target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

Solid phase microextraction as a reliable alternative to conventional extraction techniques to evaluate the pattern of hydrolytically released components in Vitis vinifera L. grapes

In present research, headspace solid-phase microextraction (HS-SPME) followed by gas chromatography–mass spectrometry (GC–qMS), was evaluated as a reliable and improved alternative to the commonly used liquid–liquid extraction (LLE) technique for the establishment of the pattern of hydrolytically released components of 7 Vitis vinifera L. grape varieties, commonly used to produce the world-famous Madeira wine. Since there is no data available on their glycosidic fractions, at a first step, two hydrolyse procedures, acid and enzymatic, were carried out using Boal grapes as matrix. Several parameters susceptible of influencing the hydrolytic process were studied. The best results, expressed as GC peak area, number of identified components and reproducibility, were obtained using ProZym M with b-glucosidase activity at 35 °C for 42 h. For the extraction of hydrolytically released components, HS-SPME technique was evaluated as a reliable and improved alternative to the conventional extraction technique, LLE (ethyl acetate). HS-SPME using DVB/CAR/PDMS as coating fiber displayed an extraction capacity two fold higher than LLE (ethyl acetate). The hydrolyzed fraction was mainly characterized by the occurrence of aliphatic and aromatic alcohols, followed by acids, esters, carbonyl compounds, terpenoids, and volatile phenols. Concerning to terpenoids its contribution to the total hydrolyzed fraction is highest for Malvasia Cândida (23%) and Malvasia Roxa (13%), and their presence according previous studies, even at low concentration, is important from a sensorial point of view (can impart floral notes to the wines), due to their low odor threshold (μg/L). According to the obtained data by principal component analysis (PCA), the sensorial properties of Madeira wines produced by Malvasia Cândida and Malvasia Roxa could be improved by hydrolysis procedure, since their hydrolyzed fraction is mainly characterized by terpenoids (e.g. linalool, geraniol) which are responsible for floral notes. Bual and Sercial grapes are characterized by aromatic alcohols (e.g. benzyl alcohol, 2-phenylethyl alcohol), so an improvement in sensorial characteristics (citrus, sweet and floral odors) of the corresponding wines, as result of hydrolytic process, is expected.

Prevalence of the metabolic syndrome and its components in Brazilian women with polycystic ovary syndrome

SOARES, Elvira Maria Mafaldo et al. Prevalence of the metabolic syndrome and its components in Brazilian women with polycystic ovary syndrome. Fertility and Sterility, v.89, n.3, p.649-655, mar. 2008

Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Síndrome metabólica e fatores associados: estudo comparativo com mulheres que apresentaram pré-eclâmpsia e gravidez normal, acompanhadas cinco anos após o parto

Preeclampsia is defined as an extremely serious complication of the pregnancy-puerperium cycle with delayed emergence of cardiovascular risk factors, including metabolic syndrome. The research aimed estimate the prevalences of metabolic syndrome and associated factors in women with preeclampsia and normal pregnancy followed five years after childbirth. This is a cross-sectional observational study using a quantitative approach, conducted at a maternity school in the city of Natal in Rio Grande do Norte state. The sample was composed of 70 women with previous preeclampsia and 75 normal selected by simple random probability sampling. Subjects were analyzed for sociodemographic, obstetric, clinical, anthropometric and biochemical parameters. International Diabetes Federation criteria were adopted to diagnose metabol ic syndrome. The Kolmogorov-Smirnov, Mann-Whitney, Student s t, Pearson s chi-squared, and Fisher s exact tests, in addition to simple logistic regression, were used for data analysis, at a 5% significance level (p ≤ 0.05). Statistical tests demonstrated elevated body mass index (p = 0.001), predominance of family history of diabetes mellitus (p = 0.022) and significantly higher prevalence of metabolic syndrome in the preeclampsia group (37.1%) when compared to normal (22.7%) (p = 0.042). Intergroup comparison showed a high number of metabolic syndrome components in women with previous preeclampsia. Altered systolic and diastolic blood pressure (p < 0.001) was the most prevalent, followed by low concentrations of high-density lipoproteins (p = 0.049), and hyperglycemia (p=0.030). There was a predominance of the metabolic syndrome in women with schooling 0-9 years (42.4%) (p = 0.005), body mass index above 30Kg.m 2 (52.3%) (p < 0.001), uric acid high (62.5%) (p = 0.050 and family history of hypertension (38.5%) (p< 0.001). Multivariate analysis of the data showed that the body mass index above 30 kg.m2, education level less than 10 years of study (p < 0.001) and family history of hypertension (p = 0.002) remained associated with the metabolic syndrome after multivariate analysis of the data. It is considered Women with previous preeclampsia exhibited high prevalence of metabolic syndrome and their individual components in relation to normal, especially, altered systolic and diastolic blood pressure, low concentrations of high-density lipoproteins and hyperglycemia. The factors associated to this ou tcome were obesity, less than 10 years of schooling, and family history of hypertension. Overall, this study identified young women with a history of PE exposed to a higher cardiovascular risk than normal

Interação da deficiência hídrica e da toxicidade do alumínio em guandu cultivado em hidroponia

O objetivo deste trabalho foi avaliar o efeito da interação da deficiência hídrica e da toxicidade do alumínio no crescimento inicial e teores de prolina livre em duas cultivares de guandu, IAPAR 43-Aratã e IAC Fava Larga, cultivadas em hidroponia. As plântulas foram submetidas aos estresses em solução nutritiva (pH 3,8), nos potenciais osmóticos de 0, -0,004, -0,006, -0,008 e -0,010 MPa, com 0, 0,25, 0,50, 0,75 e 1 mmol dm-3 de Al3+. O experimento foi conduzido em sala de crescimento, sob luminária com irradiância média de 190 mmol m-2 s-1 , fotoperíodo de 12 horas e temperatura de 25+1ºC. O delineamento experimental foi inteiramente casualizado, em arranjo fatorial 2x5x5 (duas cultivares de guandu, cinco potenciais osmóticos e cinco níveis de alumínio), com quatro repetições. Os dados foram submetidos às análises de regressão polinomial, agrupamento e componentes principais. A deficiência hídrica causa redução do crescimento da parte aérea do guandu, e a toxicidade do alumínio provoca diminuição do crescimento radicular. Houve aumento nos teores de prolina livre nas duas cultivares sob deficiência hídrica, e apenas na IAC Fava Larga sob toxicidade de alumínio. Na análise multivariada, foi observada alta correlação no crescimento e no acúmulo de prolina na cultivar IAC Fava Larga, o que evidencia provável tolerância aos estresses associados.