Revenue Elasticity of the Main federal Taxes in Mexico

An inelastic tax system increases the uncertainty associated with tax revenue collection. This results in continuous short-term adjustments to maintain the stability of tax collection. In this paper, we estimate the revenue elasticity of the principal taxes in Mexico, finding a much greater elasticity than that found in previous studies. A cointegration model between the revenue and taxes is used which satisfies strong exogeneity, providing a basis for congruent and reliable projections. Using this model, the tax revenue projected for 2011 is much lower than the estimates prepared by Mexico’s federal government.Federal taxes, long-term revenue elasticity, cointegration, strong exogeneity, forecasts

João Calvino (1509-1564) : entre a erudição e o zelo, a excelência para a Glória de Deus

Revista Lusófona de Ciência das Religiõe

History in Songs and Songs in History

[Abstract] Through music Ireland expresses its culture like no other nation in the world. Important events and the people involved in them are recorded in music to preserve them in people´s memory. Ireland has a long history of conflict between the the Irish and the British and music, as an expression of culture, provides so much information about the different ideologies. The objective of this work is to explore the connection that exists between music and history in the isle of Ireland. The first part of the work focuses on different types of songs and styles that are used to express certain ideas and ideologies like rebel songs or emigration songs. This part helps to classify some of the songs that are presented in the work. After this, a few events and some of the protagonists that were involved are analysed from a historical perspective in order to see how they are represented in music. The events analysed have a relevant role in Irish history. Namely, they are the Great Famine, the emigration, the Easter Rising, the Irish War of Independence and the Irish Civil War. In the third part of the work I focus on three Irish songs and analyse their backgrounds and story as a way to show these songs in their historical and cultural context and see how they became so important. The analysis of the songs is carried out using with a bibliography that deals, mainly, with history and Irish music separately. However, some sources about music and history together are used too. As a result, music proved to be a good mechanism to explore history from a different perspective to the narrative that can be found in classic history books. The relationship between music and history works in both ways, since one part gives depth to the other. Finally, in Ireland, music has a great symbolical power and the use of language, for instance, can produce political reactions, as can be seen with the Irish Anthem.Traballo fin de grao (UDC.FIL). Inglés: estudios lingüísticos y literarios. Curso 2019/202

Uniqueness of the Fock quantization of scalar fields under mode preserving canonical transformations varying in time

We study the Fock quantization of scalar fields of Klein-Gordon type in nonstationary scenarios propagating in spacetimes with compact spatial sections, allowing for different field descriptions that are related by means of certain nonlocal linear canonical transformations that depend on time. More specifically, we consider transformations that do not mix eigenmodes of the Laplace-Beltrami operator, which are supposed to be dynamically decoupled. In addition, we assume that the canonical transformations admit an asymptotic expansion for large eigenvalues (in norm) of the Laplace-Beltrami operator in the form of a series of half integer powers. Canonical transformations of this kind are found in the study of scalar perturbations in inflationary cosmologies, relating for instance the physical degrees of freedom of these perturbations after gauge fixing with gauge invariant canonical pairs of Bardeen quantities. We characterize all possible transformations of this type and show that, independently of the initial field description, the combined criterion of requiring (i) invariance of the vacuum under the spatial symmetries and (ii) a unitary implementation of the dynamics, leads to a unique equivalence class of Fock quantizations, all of them related by unitary transformations. This conclusion provides even further robustness to the validity of the proposed criterion, completing the results that have already appeared in the literature about the uniqueness of the Fock quantization under changes of field description when one permits exclusively local time dependent canonical transformations that scale the field configuration.Comment: 12 pages, submitted to Phys. Rev.

Musical Cross Synthesis using Matrix Factorisation

The focus of this work is to explore a new method for the creative analysis and manipulation of musical audio content. Given a target song and a source song, the goal is reconstruct the harmonic and rhythmic structure of the target with the timbral components from the source, in such a way that so that both the target and the source material are recognizable by the listener. We refer to this operation as musical cross-synthesis. For this purpose, we propose the use of a Matrix Factorisation method, more specifically, Shift-Invariant Probabilistic Latent Component Analysis (PLCA). The input to the PLCA algorithm are beat synchronous CQT basis functions of the source whose temporal activations are used to approximate the CQT of the target. Using the shift invariant property of the PLCA allows each basis function to be subjected to a range of possible pitch shifts which increases the flexibility of the source to represent the target. To create the resulting musical cross-synthesis the beat synchronous, pitch-shifted CQT basis functions are inverted and concatenated in time

Sistemas Não Cooperativos para Registo de Assiduidade em Ambiente de Sala de Aula

Over the years, high school dropout, college dropout, in particular, has always been a hot topic. With the advancement of technology and Artificial Intelligence and Machine Learning, we necessarily have to think of ways to help mitigate this problem. If there are factors that we cannot control, such as the economic ones, there are others where our actions can be directed. One factor that allows us to evaluate the risk of dropping out of school is student attendance. Although this data can be manually analyzed to make these detections, it would be more efficient to have a capable system of recording this attendance, since the human capacity to analyze data is finite, and often can only infer this situation too late. Of course, a system that only registers attendance will not give a definitive answer, but it will be an essential first step. Thus, a system that can reconcile the detection of a subject and his face while being able to constantly monitor where the subject is, always to be able to identify him even if he moves from one place to another, together with facial recognition, seem to be determining factors to bring a system of this calibre to a successful conclusion. This type of system is generally very much related to the quality of the data and its annotations, so it is vital to collect or obtain quality data to help solve the various problems presented. Considering what has been described, the main goal of this dissertation is to try to start solving the problem of school dropout, namely through the study, validation and testing of several state­of­the­art methods in the area of object detection, namely people and faces, but also tracking. The same work will have to be done on face recognition methods, being able to indicate the best state­of­the­art methods for each task. As mentioned in the previous paragraph, a significant limitation to this type of task is the data quality since it is not always possible to find a set that perfectly fits our context. Thus, to solve this gap, we will also present a dataset with about 40,000 images, thoroughly annotated frame by frame and that we believe to be an asset in solving this problem. In addition to the above, and in order not only to give a more meaningful and targeted response to our detailed data but also to provide a preliminary view of how one of the system’s tasks might work, we will present two experiments with our data in the area of detection. The first will involve finetuning our data, while the second will involve training it from scratch and then presenting its results as proof of the correct choice of the state­of­the­art method.Ao longo dos anos, o abandono escolar, o universitário em particular, tem sido sempre um tema em grande destaque. Com o avanço de várias áreas tecnológicas, assim como da Inteligência Artificial e da Aprendizagem Automática temos necessariamente de pensar em maneiras de ajudar a mitigar este problema. Se há fatores que não podemos controlar, como os económicos, há outros onde a nossa ação pode ser dirigida. Um dos fatores que permite avaliar o risco de abandono escolar é a assiduidade dos estudantes. Embora, naturalmente, estes dados possam ser analisados manualmente para fazer estas deteções, seria mais eficiente ter um sistema que fosse capaz de registar esta assiduidade, uma vez que a capacidade humana para os analisar é finita e muitas vezes apenas consegue inferir esta situação demasiado tarde. Naturalmente que um sistema que registe apenas assiduidade não irá ser capaz de dar uma resposta definitiva, mas será um primeiro passe importante. Deste modo, um sistema que seja capaz de conciliar a deteção de uma pessoa e da sua face enquanto é capaz de monitorizar de forma constante o sítio onde a pessoa está, para ser sempre capaz de a identificar mesmo que mude de sítio em conjunto com o seu reconhecimento facial, parecem ser fatores determinantes para levar a bom porto um sistema deste calibre. Este tipo de sistemas está, geralmente, muito relacionado com a qualidade dos dados e das suas anotações, pelo que é extraordinariamente importante ser capaz de recolher ou obter dados de qualidade que auxiliem na resolução dos diversos problemas apresentados. Tendo em atenção aquilo que foi sendo descrito, o principal objetivo desta dissertação passa por tentar dar início à resolução do problema do abandono escolar, nomeadamente através do estudo, validação e teste de diversos métodos estado­da­arte no que diz respeito à área da deteção de objetos, nomeadamente de pessoas e faces, mas também de tracking. O mesmo trabalho terá de ser realizado nos métodos de reconhecimento facial, sendo capaz no final de poder indicar os melhores métodos estado­da­arte de cada tarefa. Como referido no parágrafo anterior, uma limitação grande a este tipo de tarefas é a respetiva qualidade dos dados, visto que nem sempre e possível encontrar um conjunto que se adeque perfeitamente ao nosso contexto. Assim, de modo a solucionar esta lacuna iremos também apresentar um dataset com cerca de 40,000 imagens, completamente anotado frame a frame e que acreditamos ser uma mais valia na resolução deste problema. Para além do referido, e de modo não só a dar uma resposta mais significativa e dirigida aos nossos dados em particular, mas também para que seja possível ter uma visão preliminar daquilo que poderá ser o funcionamento de uma das tarefas do sistema, iremos apresentar duas experiências com os nossos dados, na área da deteção. A primeira irá envolver o finetuning dos nossos dados, enquanto que a segunda levará a um treino iniciado de raiz, apresentando depois os seus resultados como uma prova da escolha acertada do método de estado da arte

Determinants of Box Products of Paths

Suppose that G is the graph obtained by taking the box product of a path of length n and a path of length m. Let M be the adjacency matrix of G. If n=m, H.M. Rara showed in 1996 that det(M)=0. We extend this result to allow n and m to be any positive integers, and show that, if gcd(n+1,m+1)>1, then det(M)=0; otherwise, if gcd(n+1,m+1)=1, then det(M)=(-1)^(nm/2)

A New Model to Improve Project Time-Cost Trade-Off in Uncertain Environments

The time–cost trade-off problem (TCTP) is fundamental to project scheduling. Risks in estimation of project cost and duration are significant due to uncertainty. This uncertainty cannot be eliminated by any scheduling or estimation techniques. Therefore, a model that can represent uncertainty in the real world to solve time–cost trade-off problems is needed. In this chapter, fuzzy logic is utilized to consider affecting uncertainties in project duration and cost. An optimization algorithm based on time-driven activity-based costing (TDABC) is applied to provide a trade-off between project time and cost. The presented model could solve the time–cost trade-off problem while accounting for uncertainty in project cost and duration. This could help generate a more reliable schedule and mitigate the risk of projects running overbudget or behind schedule