994 resultados para Linear Constraint Relations
Resumo:
The scaling of body parts is central to the expression of morphology across body sizes and to the generation of morphological diversity within and among species. Although patterns of scaling-relationship evolution have been well documented for over one hundred years, little is known regarding how selection acts to generate these patterns. In part, this is because it is unclear the extent to which the elements of log-linear scaling relationships-the intercept or mean trait size and the slope-can evolve independently. Here, using the wing-body size scaling relationship in Drosophila melanogaster as an empirical model, we use artificial selection to demonstrate that the slope of a morphological scaling relationship between an organ (the wing) and body size can evolve independently of mean organ or body size. We discuss our findings in the context of how selection likely operates on morphological scaling relationships in nature, the developmental basis for evolved changes in scaling, and the general approach of using individual-based selection experiments to study the expression and evolution of morphological scaling.
Resumo:
This paper asks whether collective industrial relations can be promoted by means other than seeking change in public policy. Recent research points to the increasing significance of transnational private regulation (TPR) in developing economies. There is an emerging consensus that market incentives to improve wages and conditions of work can have a modest positive effect on measurable outcomes like hours of work, and health and safety. However, it appears that TPR has little impact on the capacity of workers to pursue such improvements for themselves via collective action. The paper takes a closer look at the potential of TPR to enhance worker voice and participation. It argues that this potential cannot be properly evaluated without understanding how local actors mobilise the social and political resources that TPR provides. The case studies presented show how different TPR schemes have been used by unions in Africa as a means to pursue the interests of members. The authors found that the scale of the impact of TPR in all of the contexts studied depended almost entirely on the existing capacities and resources of the unions involved. TPR led to the creation of collective industrial relations processes, or helped unions to ensure that certain enterprises participated in existing industrial relations processes, but did virtually nothing to enhance the political and organisational capacity of the unions to influence the outcomes of those processes in terms of wages and conditions of employment. The paper concludes that the potential of TPR to promote the emergence of collective industrial relations systems is very low.
Resumo:
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).
Resumo:
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.
Resumo:
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.
Resumo:
The Garvey-Kelson relations (GKRs) are algebraic expressions originally developed to predict nuclear masses. In this letter we show that the GKRs provide a fruitful framework for the prediction of other physical observables that also display a slowly-varying dynamics. Based on this concept, we extend the GKRs to the study of nuclear charge radii. The GKRs are tested on 455 out of the approximately 800 nuclei whose charge radius is experimentally known. We find a rms deviation between the GK predictions and the experimental values of only 0.01 fm. This should be contrasted against some of the most successful microscopic models that yield rms deviations almost three times as large. Predictions -with reliable uncertainties- are provided for 116 nuclei whose charge radius is presently unknown.
Resumo:
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.
Resumo:
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.
Resumo:
I reconsider the short-term effects of fiscal policy when both government spending and taxes are allowed to respond to the level of public debt. I embed the long-term government budget constraint in a VAR, and apply this common trends model to US quarterly data. The results overturn some widely held beliefs on fiscal policy effects. The main finding is that expansionary fiscal policy has contractionary effects on output and inflation. Ricardian effects may dominate when fiscal expansions are expected to be adjusted by future tax rises or spending cuts. The evidence supports RBC models with distortionary taxation. We can discard some alternative interpretations that are based on monetary policy reactions or supply-side effects.
Resumo:
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.
Resumo:
In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications.
Resumo:
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.
Resumo:
This article presents data from two samples of Catalan adolescents from 12 to 16 years and their parents in 2003 and 2008. The main aim is to explore the changing relationships between parents and their children and the impact that the use of ICT has on these changes. The results show that over the time there is a greater involvement of parents in communicating with their children about this issue, which involves no greater satisfaction of adolescents with such communication, possibly by the perception of lack of control that his/her father or mother has