Análise das isotermas de adsorção de Cu(II), Cd(II), Ni(II) e Zn(II) pela N-(3,4-dihidroxibenzil) quitosana empregando o método da regressão não linear

Adsorption of Cu(II), Ni(II), Pb(II) and Zn(II) ions from aqueous solutions by N-(3,4-dihydroxybenzyl) chitosan have been carried out. The Langmuir (L), Freundlich (F), Langmuir - Freundlich (LF), Redlich-Peterson (RP) and Tóth (T) adsorption isotherms models have been applied to fit the experimental data. Nonlinear regression computational program "Enzefitte", which is a library of the more commonly used adsorption isotherm equations for obtaining tabular outuput suitable for plotting theoretical of fitted isotherms, has been used to estimate the adsorption parameters. These parameters were used to calculate the amount adsorbed q calc., a function of concentration (C).

Non-Linear Journal Bearing Model for Analysis of Superharmonic Vibrations of Rotor Systems

A rotating machine usually consists of a rotor and bearings that supports it. The nonidealities in these components may excite vibration of the rotating system. The uncontrolled vibrations may lead to excessive wearing of the components of the rotating machine or reduce the process quality. Vibrations may be harmful even when amplitudes are seemingly low, as is usually the case in superharmonic vibration that takes place below the first critical speed of the rotating machine. Superharmonic vibration is excited when the rotational velocity of the machine is a fraction of the natural frequency of the system. In such a situation, a part of the machine’s rotational energy is transformed into vibration energy. The amount of vibration energy should be minimised in the design of rotating machines. The superharmonic vibration phenomena can be studied by analysing the coupled rotor-bearing system employing a multibody simulation approach. This research is focused on the modelling of hydrodynamic journal bearings and rotorbearing systems supported by journal bearings. In particular, the non-idealities affecting the rotor-bearing system and their effect on the superharmonic vibration of the rotating system are analysed. A comparison of computationally efficient journal bearing models is carried out in order to validate one model for further development. The selected bearing model is improved in order to take the waviness of the shaft journal into account. The improved model is implemented and analyzed in a multibody simulation code. A rotor-bearing system that consists of a flexible tube roll, two journal bearings and a supporting structure is analysed employing the multibody simulation technique. The modelled non-idealities are the shell thickness variation in the tube roll and the waviness of the shaft journal in the bearing assembly. Both modelled non-idealities may cause subharmonic resonance in the system. In multibody simulation, the coupled effect of the non-idealities can be captured in the analysis. Additionally one non-ideality is presented that does not excite the vibrations itself but affects the response of the rotorbearing system, namely the waviness of the bearing bushing which is the non-rotating part of the bearing system. The modelled system is verified with measurements performed on a test rig. In the measurements the waviness of bearing bushing was not measured and therefore it’s affect on the response was not verified. In conclusion, the selected modelling approach is an appropriate method when analysing the response of the rotor-bearing system. When comparing the simulated results to the measured ones, the overall agreement between the results is concluded to be good.

Approximation to the theory of affinities to manage the problems of the groupping process

New economic and enterprise needs have increased the interest and utility of the methods of the grouping process based on the theory of uncertainty. A fuzzy grouping (clustering) process is a key phase of knowledge acquisition and reduction complexity regarding different groups of objects. Here, we considered some elements of the theory of affinities and uncertain pretopology that form a significant support tool for a fuzzy clustering process. A Galois lattice is introduced in order to provide a clearer vision of the results. We made an homogeneous grouping process of the economic regions of Russian Federation and Ukraine. The obtained results gave us a large panorama of a regional economic situation of two countries as well as the key guidelines for the decision-making. The mathematical method is very sensible to any changes the regional economy can have. We gave an alternative method of the grouping process under uncertainty.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Forecasting the maximum compensation offer in the automobile BI claims negotiation process

Most motor bodily injury (BI) claims are settled by negotiation, with fewer than 5% of cases going to court. A well-defined negotiation strategy is thus very useful for insurance companies. In this paper we assume that the monetary compensation awarded in court is the upper amount to be offered by the insurer in the negotiation process. Using a real database, a log-linear model is implemented to estimate the maximal offer. Non-spherical disturbances are detected. Correlation occurs when various claims are settled in the same judicial verdict. Group wise heteroscedasticity is due to the influence of the forensic valuation on the final compensation amount. An alternative approximation based on generalized inference theory is applied to estimate confidence intervals on variance components, since classical interval estimates may be unreliable for datasets with unbalanced structures.

Cálculo ab initio de intensidades Raman dinâmicas utilizando a teoria da resposta linear

In this paper a methodology for the computation of Raman scattering cross-sections and depolarization ratios within the Placzek Polarizability Theory is described. The polarizability gradients are derived from the values of the dynamic polarizabilities computed at the excitation frequencies using ab initio Linear Response Theory. A sample application of the computational program, at the HF, MP2 and CCSD levels of theory, is presented for H2O and NH3. The results show that high correlated levels of theory are needed to achieve good agreement with experimental data.

Control of permanent magnet linear synchronous motor in motion control applications

The aim of the thesis is to study the principles of the permanent magnet linear synchronous motor (PMLSM) and to develop a simulator model of direct force controlled PMLSM. The basic motor model is described by the traditional two-axis equations. The end effects, cogging force and friction model are also included into the final motor model. Direct thrust force control of PMLSM is described and modelled. The full system model is proven by comparison with the data provided by the motor manufacturer.

New approximation to the third-order density : application to the calculation of correlated multicenter indices

In this work we present the formulas for the calculation of exact three-center electron sharing indices (3c-ESI) and introduce two new approximate expressions for correlated wave functions. The 3c-ESI uses the third-order density, the diagonal of the third-order reduced density matrix, but the approximations suggested in this work only involve natural orbitals and occupancies. In addition, the first calculations of 3c-ESI using Valdemoro's, Nakatsuji's and Mazziotti's approximation for the third-order reduced density matrix are also presented for comparison. Our results on a test set of molecules, including 32 3c-ESI values, prove that the new approximation based on the cubic root of natural occupancies performs the best, yielding absolute errors below 0.07 and an average absolute error of 0.015. Furthemore, this approximation seems to be rather insensitive to the amount of electron correlation present in the system. This newly developed methodology provides a computational inexpensive method to calculate 3c-ESI from correlated wave functions and opens new avenues to approximate high-order reduced density matrices in other contexts, such as the contracted Schrödinger equation and the anti-Hermitian contracted Schrödinger equation

Alquilbenzeno sulfonato linear: uma abordagem ambiental e analítica

The environmental impact of detergents and other consumer products is behind the continued interest in the chemistry of the surfactants used. Of these, linear alkylbenzene sulfonates (LASs) are most widely employed in detergent formulations. The precursors to LASs are linear alkylbenzenes (LABs). There is also interest in the chemistry of these hydrocarbons, because they are usually present in commercial LASs (due to incomplete sulfonation), or form as one of their degradation products. Additionally, they may be employed as molecular tracers of domestic waste in the aquatic environment. The following aspects are covered in the present review: The chemistry of surfactants, in particular LAS; environmental impact of the production of LAS; environmental and toxicological effects of LAS; mechanisms of removal of LAS in the environment, and methods for monitoring LAS and LAB, the latter in domestic wastes. Classical and novel analytical methods employed for the determination of LAS and LAB are discussed in detail, and a brief comment on detergents in Brazil is given.

Tracing the Origin and Spread of Agriculture in Europe

The origins of early farming and its spread to Europe have been the subject of major interest for some time. The main controversy today is over the nature of the Neolithic transition in Europe: the extent to which the spread was, for the most part, indigenous and animated by imitatio (cultural diffusion) or else was driven by an influx of dispersing populations (demic diffusion). We analyze the spatiotemporal dynamics of the transition using radiocarbon dates from 735 early Neolithic sites in Europe, the Near East, and Anatolia. We compute great-circle and shortest-path distances from each site to 35 possible agricultural centers of origin—ten are based on early sites in the Middle East and 25 arehypothetical locations set at 58 latitude/longitude intervals. We perform a linear fit of distance versus age (and viceversa) for each center. For certain centers, high correlation coefficients (R . 0.8) are obtained. This implies that a steady rate or speed is a good overall approximation for this historical development. The average rate of the Neolithic spread over Europe is 0.6–1.3 km/y (95% confidence interval). This is consistent with the prediction of demic diffusion(0.6–1.1 km/y). An interpolative map of correlation coefficients, obtained by using shortest-path distances, shows thatthe origins of agriculture were most likely to have occurred in the northern Levantine/Mesopotamian area

Utilização do índice de retenção linear para caracterização de compostos voláteis em café solúvel utilizando GC-MS e coluna HP-Innowax

Gas chromatography coupled with mass spectrometry (GC-MS) is widely used for the characterization of volatile compounds. However, due to the complexity of the soluble coffee matrix, a complete identification of the components should not be based on mass spectra interpretation only. The linear index of retention (LRI) is frequently used to give support to mass spectra. The aim of this work is to investigate the characterization of the volatile compounds in soluble coffee samples by GC-MS using LRI values found with a HP-INNOWAX column. The method used allows a significant increase of the reliability of identifying compounds.

Readout electronics for low dark count pixel detectors based on geiger mode avalanche photodiodes fabricated in conventional CMOS technologies for future linear colliders

The high sensitivity and excellent timing accuracy of Geiger mode avalanche photodiodes makes them ideal sensors as pixel detectors for particle tracking in high energy physics experiments to be performed in future linear colliders. Nevertheless, it is well known that these sensors suffer from dark counts and afterpulsing noise, which induce false hits (indistinguishable from event detection) as well as an increase of the necessary area of the readout system. In this work, we present a comparison between APDs fabricated in a high voltage 0.35 µm and a high integration 0.13 µm commercially available CMOS technologies that has been performed to determine which of them best fits the particle collider requirements. In addition, a readout circuit that allows low noise operation is introduced. Experimental characterization of the proposed pixel is also presented in this work.

Vias de síntese linear e convergente: qual é mais verde?

A comparative study of a convergent and the linear synthetic pathway with respect to their relative greenish allowed the quantification of the advantages of the former with respect to atomic productivity as well as robustness. The calculations show that convergent pathways provide a decrease of costs together with a decrease of E factor and an increase of atomic economy which means that greenish is accompanied by an economic advantage. The influence of other features of the convergent pathways synthesis on the improvement of the synthesis greenish is discussed qualitatively.

Utilização do sensor linear de luz ILX554 em espectroscopia óptica

This technical note describes the construction of a low-cost optical detector. This device is composed by a high-sensitive linear light sensor (model ILX554) and a microcontroller. The performance of the detector was demonstrated by the detection of emission and Raman spectra of the several atomic systems and the results reproduce those found in the literature.