889 resultados para Data structure
Resumo:
This paper describes a new module of the expert system SISTEMAT used for the prediction of the skeletons of neolignans by (13)C NMR, (1)H NMR and botanical data obtained from the literature. SISTEMAT is composed of MACRONO, SISCONST, C13MACH, H1MACH and SISOCBOT programs, each analyzing data of the neolignan in question to predict the carbon skeleton of the compound. From these results, the global probability is computed and the most probable skeleton predicted. SISTEMAT predicted the skeletons of 75% of the 20 neolignans tested, in a rapid and simple procedure demonstrating its advantage for the structural elucidation of new compounds.
Resumo:
We report a novel method for calculating flash points of acyclic alkanes from flash point numbers, N(FP), which can be calculated from experimental or calculated boiling point numbers (Y(BP)) with the equation N(FP) = 1.020Y(BP) - 1.083 Flash points (FP) are then determined from the relationship FP(K) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901 For it data set of 102 linear and branched alkanes, the correlation of literature and predicted flash points has R(2) = 0.985 and an average absolute deviation of 3.38 K. N(FP) values can also be estimated directly from molecular structure to produce an even closer correspondence of literature and predicted FP values. Furthermore, N(FP) values provide a new method to evaluate the reliability of literature flash point data.
Resumo:
In order to extend previous SAR and QSAR studies, 3D-QSAR analysis has been performed using CoMFA and CoMSIA approaches applied to a set of 39 alpha-(N)-heterocyclic carboxaldehydes thiosemicarbazones with their inhibitory activity values (IC(50)) evaluated against ribonucleotide reductase (RNR) of H.Ep.-2 cells (human epidermoid carcinoma), taken from selected literature. Both rigid and field alignment methods, taking the unsubstituted 2-formylpyridine thiosemicarbazone in its syn conformation as template, have been used to generate multiple predictive CoMFA and CoMSIA models derived from training sets and validated with the corresponding test sets. Acceptable predictive correlation coefficients (Q(cv)(2) from 0.360 to 0.609 for CoMFA and Q(cv)(2) from 0.394 to 0.580 for CoMSIA models) with high fitted correlation coefficients (r` from 0.881 to 0.981 for CoMFA and r(2) from 0.938 to 0.993 for CoMSIA models) and low standard errors (s from 0.135 to 0.383 for CoMFA and s from 0.098 to 0.240 for CoMSIA models) were obtained. More precise CoMFA and CoMSIA models have been derived considering the subset of thiosemicarbazones (TSC) substituted only at 5-position of the pyridine ring (n=22). Reasonable predictive correlation coefficients (Q(cv)(2) from 0.486 to 0.683 for CoMFA and Q(cv)(2) from 0.565 to 0.791 for CoMSIA models) with high fitted correlation coefficients (r(2) from 0.896 to 0.997 for CoMFA and r(2) from 0.991 to 0.998 for CoMSIA models) and very low standard errors (s from 0.040 to 0.179 for CoMFA and s from 0.029 to 0.068 for CoMSIA models) were obtained. The stability of each CoMFA and CoMSIA models was further assessed by performing bootstrapping analysis. For the two sets the generated CoMSIA models showed, in general, better statistics than the corresponding CoMFA models. The analysis of CoMFA and CoMSIA contour maps suggest that a hydrogen bond acceptor near the nitrogen of the pyridine ring can enhance inhibitory activity values. This observation agrees with literature data, which suggests that the nitrogen pyridine lone pairs can complex with the iron ion leading to species that inhibits RNR. The derived CoMFA and CoMSIA models contribute to understand the structural features of this class of TSC as antitumor agents in terms of steric, electrostatic, hydrophobic and hydrogen bond donor and hydrogen bond acceptor fields as well as to the rational design of this key enzyme inhibitors.
Resumo:
The structure of chemically prepared poly-p-phenylenediamine (PpPD) was investigated by Resonance Raman (RR), FTIR, UV-VIS-NIR, X-ray photoelectron (XPS), X-ray Absorption at Nitrogen K edge (N K XANES), and Electron paramagnetic Resonance (EPR) spectroscopies. XPS, EPR and N K XANES data reveal that polymeric structure is formed mainly by radical cations and dication nitrogens. It excludes the possibility that PpPD chains have azo or phenazinic nitrogens, as commonly is supposed in the literature. The RR spectrum of PpPD shows two characteristic bands at 1527 cm(-1) and 1590 cm(-1) that were assigned to nu C=N and nu C=C of dication units, respectively, similar to polyaniline in pernigraniline base form. The presence of radical cations was confirmed by Raman data owing to the presence of bands at 1325/1370 cm(-1), characteristic of nu C-N of polaronic segments. Thus, all results indicate that PpPD has a doped PANT-like structure, with semi-quinoid and quinoid rings, and has no phenazinic rings, as observed for poly-o-phenylenediamine. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Julocrotine, N-(2,6-dioxo-l-phenethyl-piperidin-3-yl)-2-methyl-butyramide, is a potent antiproliferative agent against the promastigote and amastigote forms of Leishmania amazonensis (L.). In this work, the crystal structure of Julocrotine was solved by X-ray diffraction, and its geometrical parameters were compared with theoretical calculations at the B3LYP and HF level of theory. IR and NMR spectra also have been obtained and compared with theoretical calculations. IR absorptions calculated with the B3LYP level of theory employed together with the 6-311G+(d,p) basis set, are close to those observed experimentally. Theoretical NMR calculations show little deviation from experimental results. The results show that the theory is in accordance with the experimental data. (C) 2007 Wiley Periodicals, Inc.
Resumo:
In the treatment of cyclometallated dimer [Pd(dmba)(mu-Cl)](2) (dmba = N,N-dimethylbenzylamine) with AgNO(3) and acetonitrile the result was the monomeric cationic precursor [Pd(dmba)(NCMe)(2)](NO(3)) (NCMe=acetonitrile) (1). Compound 1 reacted with m-nitroaniline (m-NAN) and pirazine (pz), originating [Pd(dmba)(ONO(2))(m-NAN)] (2) and [{Pd(dmba)(ONO(2))}(2)(mu-pz)] center dot H(2)O (3), respectively. These compounds were characterized by elemental analysis, IR and NMR spectroscopy. The IR spectra of (2-3) display typical bands of monodentade O-bonded nitrate groups, whereas the NMR data of 3 are consistent with the presence of bridging pyrazine ligands. The structure of compound 3 was determined by Xray diffraction analysis. This packing consists of a supramolecular chain formed by hydrogen bonding between the water molecule and nitrato ligands of two consecutive [Pd(2)(dmba)(2)(ONO(2))2(mu-pz)] units. (c) 2008 Elsevier Ltd. All rights reserved.
Resumo:
The purpose of this paper is to make quantitative and qualitative analysis of foreign citizens who may participate on the Swedish labor market (in text refers to as ‘immigrants’). This research covers the period 1973-2005 and gives prediction figures of immigrant population, age and gender structure, and education attainment in 2010. To cope with data regarding immigrants from different countries, the population was divided into six groups. The main chapter is divided into two parts. The first part specifies division of immigrants into groups by country of origin according to geographical, ethnical, economical and historical criteria. Brief characteristics and geographic position, dynamic and structure description were given for each group; historical review explain rapid changes in immigrant population. Statistical models for description and estimation future population were given. The second part specifies education and qualification level of the immigrants according to international and Swedish standards. Models for estimating age and gender structure, level of education and professional orientation of immigrants in different groups are given. Inferences were made regarding ethnic, gender and education structure of immigrants; the distribution of immigrants among Swedish counties is given. Discussion part presents the results of the research, gives perspectives for the future brief evaluation of the role of immigrants on the Swedish labor market.
Resumo:
In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.
Numerical Simulation Of Sediment Transport And Bedmorphology Around A Hydraulic Structure On A River
Resumo:
Scour around hydraulic structures is a critical problem in hydraulic engineering. Under prediction of scour depth may lead to costly failures of the structure, while over prediction might result in unnecessary costs. Unfortunately, up-to-date empirical scour prediction formulas are based on laboratory experiments that are not always able to reproduce field conditions due to complicated geometry of rivers and temporal and spatial scales of a physical model. However, computational fluid dynamics (CFD) tools can perform using real field dimensions and operating conditions to predict sediment scour around hydraulic structures. In Korea, after completing the Four Major Rivers Restoration Project, several new weirs have been built across Han, Nakdong, Geum and Yeongsan Rivers. Consequently, sediment deposition and bed erosion around such structures have became a major issue in these four rivers. In this study, an application of an open source CFD software package, the TELEMAC-MASCARET, to simulate sediment transport and bed morphology around Gangjeong weir, which is the largest multipurpose weir built on Nakdong River. A real bathymetry of the river and a geometry of the weir have been implemented into the numerical model. The numerical simulation is carried out with a real hydrograph at the upstream boundary. The bedmorphology obtained from the numerical results has been validated against field observation data, and a maximum of simulated scour depth is compared with the results obtained by empirical formulas of Hoffmans. Agreement between numerical computations, observed data and empirical formulas is judged to be satisfactory on all major comparisons. The outcome of this study does not only point out the locations where deposition and erosion might take place depending on the weir gate operation, but also analyzes the mechanism of formation and evolution of scour holes after the weir gates.
Resumo:
The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.
Resumo:
Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.
Resumo:
Esta tese utiliza a informação contida em preços internacionais para identificar parâmetros de modelos de comércio sob competição imperfeita, desta forma permitindo inferência sobre o comportamento das exportações, sobre os ganhos de troca da abertura comercial e sobre a variedade de bens produzidos domesticamente. Em primeiro lugar, investigamos o repasse cambial, no longo prazo, para os preços praticados por exportadores brasileiros. O foco no longo prazo permite controlar os efeitos da rigidez de preço no curto prazo, de maneira que o repasse incompleto evidencie competição imperfeita com preços flexíveis. Em segundo lugar, calculamos os ganhos de troca de novas variedades de bens importados baseando-nos em estimativas para as elasticidades de substituição desagregadas. Finalmente, qualificamos a ênfase da literatura de comércio em ganhos de eficiência no lugar de ganhos de variedade, demonstrando que a variedade de bens produzidos domesticamente se amplia após aberturas comerciais desde que as firmas tenham uma margem de decisão em bens intermediários ou na qualificação da mão de obra.
Resumo:
This paper argues that changes in the returns to occupational tasks have contributed to changes in the wage distribution over the last three decades. Using Current Population Survey (CPS) data, we first show that the 1990s polarization of wages is explained by changes in wage setting between and within occupations, which are well captured by tasks measures linked to technological change and offshorability. Using a decomposition based on Firpo, Fortin, and Lemieux (2009), we find that technological change and deunionization played a central role in the 1980s and 1990s, while offshorability became an important factor from the 1990s onwards.
Resumo:
This paper investigates whether there is evidence of structural change in the Brazilian term structure of interest rates. Multivariate cointegration techniques are used to verify this evidence. Two econometrics models are estimated. The rst one is a Vector Autoregressive Model with Error Correction Mechanism (VECM) with smooth transition in the deterministic coe¢ cients (Ripatti and Saikkonen [25]). The second one is a VECM with abrupt structural change formulated by Hansen [13]. Two datasets were analysed. The rst one contains a nominal interest rate with maturity up to three years. The second data set focuses on maturity up to one year. The rst data set focuses on a sample period from 1995 to 2010 and the second from 1998 to 2010. The frequency is monthly. The estimated models suggest the existence of structural change in the Brazilian term structure. It was possible to document the existence of multiple regimes using both techniques for both databases. The risk premium for di¤erent spreads varied considerably during the earliest period of both samples and seemed to converge to stable and lower values at the end of the sample period. Long-term risk premiums seemed to converge to inter-national standards, although the Brazilian term structure is still subject to liquidity problems for longer maturities.
Resumo:
The systemic financial crisis that started in 2008 in the United States had some severe effects in the economic activity and required the bailout of financial institutions with the use of taxpayer’s money. It also originated claims for stronger regulatory framework in order to avoid another threat in the financial market. The Dodd Frank Act was proposed and approved in the United States in the aftermath of the crisis and brought, among many other features, the creation of the Financial Stability Oversight Council and the tougher inspection of financial institutions with asset above 50 billion dollars. The objective of this work is to study the causal effect of the Dodd Frank Act on the behavior of the treatment group subject to monitoring by the Financial Stability Oversight Council (financial institutions with assets above 50 billion dollars) regarding capital and compensation structure in comparison to the group that was not treated. We use data from Compustat and our empirical strategy is the Regression Discontinuity Design, not usually applied to the banking literature, but very useful for the present work since it allows us to compare the treatment group and the non-treatment group in the year of the enactment of the law (2010). No change of behavior was observed for the Capital Structure. In the Compensation Schemes, however, a decrease was found in the item other compensation for CEOs and CFOs. We also performed a robustness check by running a placebo test on the variables in the year before the law was enacted. No significance was found, which supports the conclusion that our main results were caused by the enactment of the DFA.