Dynamics and orchestral effects in late Eighteenth-Century portuguese organ music: the works of José Marques e Silva (1782-1837) and the organs of António Xavier Machado e Cerveira (1756-1828)

A maioria dos órgãos históricos portugueses data dos finais do século XVIII ou do princípio do século XIX. Durante este período foi construído um invulgar número de instrumentos em Lisboa e nas áreas circundantes por António Xavier Machado e Cerveira (1756-1828) e outros organeiros menos prolíficos. O estudo desses órgãos, muitos dos quais (restaurados ou não) se encontram próximos das condições originais, permite a identificação de um tipo de instrumento com uma morfologia específica, claramente emancipada do chamado «órgão ibérico». No entanto, até muito recentemente, não era conhecida música que se adaptasse às idiossincrasisas daqueles instrumentos. O recente estudo das obras para órgão de José Marques e Silva (1782-1837) permitiu clarificar esta situação. Bem conhecido durante a sua vida como organista e compositor, José Marques e Silva foi um dos ultimos mestres do Seminário Patriarcal. A importância da sua produção musical reside não só num substancial número de obras com autoria firmemente estabelecida – escritas, na maior parte, para coro misto com acompanhamento de órgão obbligato – mas também na íntima relação entre a sua escrita e a morfologia dos órgãos construídos em Portugal durante a sua vida. Este artigo enfatiza a importância de José Marques e Silva (indubitavelmente, o mais significativo compositor português para órgão do seu tempo) sublinhando a relevância das suas obras para órgão solo, cujo uso extensivo de escrita idiomática e indicações de registação fazem delas um dos mais importantes documentos só início do século XIX sobre a prática organística em Portugal.

Fractional dynamics and MDS visualization of earthquake phenomena

This paper analyses earthquake data in the perspective of dynamical systems and fractional calculus (FC). This new standpoint uses Multidimensional Scaling (MDS) as a powerful clustering and visualization tool. FC extends the concepts of integrals and derivatives to non-integer and complex orders. MDS is a technique that produces spatial or geometric representations of complex objects, such that those objects that are perceived to be similar in some sense are placed on the MDS maps forming clusters. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analysed. The events are characterized by their magnitude and spatiotemporal distributions and are divided into fifty groups, according to the Flinn–Engdahl (F–E) seismic regions of Earth. Several correlation indices are proposed to quantify the similarities among regions. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools for understanding the global behaviour of earthquakes.

Multidimensional scaling analysis of the dynamics of a country economy

This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process.

Fractional dynamics of genetic algorithms using hexagonal space tessellation

The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.

Deregulated expression of selected histone methylases and demethylases in prostate carcinoma

Prostate cancer (PCa), a leading cause of cancer-related morbidity and mortality, arises through the acquisition of genetic and epigenetic alterations. Deregulation of histone methyltransferases (HMTs) or demethylases (HDMs) has been associated with PCa development and progression. However, the precise influence of altered HMTs or HDMs expression and respective histone marks in PCa onset and progression remains largely unknown. To clarify the role of HMTs and HDMs in prostate carcinogenesis, expression levels of 37 HMTs and 20 HDMs were assessed in normal prostate and PCa tissue samples by RT-qPCR. SMYD3, SUV39H2, PRMT6, KDM5A, and KDM6A were upregulated, whereas KMT2A-E (MLL1-5) and KDM4B were downregulated in PCa, compared with normal prostate tissues. Remarkably, PRMT6 was the histone modifier that best discriminated normal from tumorous tissue samples. Interestingly, EZH2 and SMYD3 expression levels significantly correlated with less differentiated and more aggressive tumors. Remarkably, SMYD3 expression levels were of independent prognostic value for the prediction of disease-specific survival of PCa patients with clinically localized disease submitted to radical prostatectomy. We concluded that expression profiling of HMTs and HDMs, especially SMYD3, might be of clinical usefulness for the assessment of PCa patients and assist in pre-therapeutic decision-making.

Regulation of histone H2A.Z expression is mediated by sirtuin 1 in prostate cancer

Histone variants seem to play a major role in gene expression regulation. In prostate cancer, H2A.Z and its acetylated form are implicated in oncogenes’ upregulation. SIRT1, which may act either as tumor suppressor or oncogene, reduces H2A.Z levels in cardiomyocytes, via proteasome-mediated degradation, and this mechanism might be impaired in prostate cancer cells due to sirtuin 1 downregulation. Thus, we aimed to characterize the mechanisms underlying H2A.Z and SIRT1 deregulation in prostate carcinogenesis and how they interact. We found that H2AFZ and SIRT1 were up- and downregulated, respectively, at transcript level in primary prostate cancer and high-grade prostatic intraepithelial neoplasia compared to normal prostatic tissues. Induced SIRT1 overexpression in prostate cancer cell lines resulted in almost complete absence of H2A.Z. Inhibition of mTOR had a modest effect on H2A.Z levels, but proteasome inhibition prevented the marked reduction of H2A.Z due to sirtuin 1 overexpression. Prostate cancer cells exposed to epigenetic modifying drugs trichostatin A, alone or combined with 5-aza-2’-deoxycytidine, increased H2AFZ transcript, although with a concomitant decrease in protein levels. Conversely, SIRT1 transcript and protein levels increased after exposure. ChIP revealed an increase of activation marks within the TSS region for both genes. Remarkably, inhibition of sirtuin 1 with nicotinamide, increased H2A.Z levels, whereas activation of sirtuin 1 by resveratrol led to an abrupt decrease in H2A.Z. Finally, protein-ligation assay showed that exposure to epigenetic modifying drugs fostered the interaction between sirtuin 1 and H2A.Z. We concluded that sirtuin 1 and H2A.Z deregulation in prostate cancer are reciprocally related. Epigenetic mechanisms, mostly histone post-translational modifications, are likely involved and impair sirtuin 1-mediated downregulation of H2A.Z via proteasome-mediated degradation. Epigenetic modifying drugs in conjunction with enzymatic modulators are able to restore the normal functions of sirtuin 1 and might constitute relevant tools for targeted therapy of prostate cancer patients

Phenotypic impact of deregulated expression of class I histone deacetylases in urothelial cell carcinoma of the bladder

Deregulated expression of histone deacetylases (HDACs) has been implicated in tumorigenesis. Herein, we investigated class I HDACs expression in bladder urothelial cell carcinoma (BUCC), its prognostic value and biological significance. Significantly increased transcript levels of all HDACs were found in BUCC compared to 20 normal mucosas, and these were higher in lower grade and stage tumors. Increased HDAC3 levels were associated with improved patient survival. SiRNA experiments showed decrease cell viability and motility, and increased apoptosis. We concluded that class I HDACs play an important role in bladder carcinogenesis through deregulation of proliferation, migration and apoptosis, constituting putative therapeutic targets

Laxity dynamics and LLF schedulability analysis on multiprocessor platforms

LLF (Least Laxity First) scheduling, which assigns a higher priority to a task with a smaller laxity, has been known as an optimal preemptive scheduling algorithm on a single processor platform. However, little work has been made to illuminate its characteristics upon multiprocessor platforms. In this paper, we identify the dynamics of laxity from the system’s viewpoint and translate the dynamics into LLF multiprocessor schedulability analysis. More specifically, we first characterize laxity properties under LLF scheduling, focusing on laxity dynamics associated with a deadline miss. These laxity dynamics describe a lower bound, which leads to the deadline miss, on the number of tasks of certain laxity values at certain time instants. This lower bound is significant because it represents invariants for highly dynamic system parameters (laxity values). Since the laxity of a task is dependent of the amount of interference of higher-priority tasks, we can then derive a set of conditions to check whether a given task system can go into the laxity dynamics towards a deadline miss. This way, to the author’s best knowledge, we propose the first LLF multiprocessor schedulability test based on its own laxity properties. We also develop an improved schedulability test that exploits slack values. We mathematically prove that the proposed LLF tests dominate the state-of-the-art EDZL tests. We also present simulation results to evaluate schedulability performance of both the original and improved LLF tests in a quantitative manner.

Ligand-Induced structural changes in TEM‑1 probed by molecular dynamics and relative binding free energy calculations

The TEM family of enzymes has had a crucial impact on the pharmaceutical industry due to their important role in antibiotic resistance. Even with the latest technologies in structural biology and genomics, no 3D structure of a TEM- 1/antibiotic complex is known previous to acylation. Therefore, the comprehension of their capability in acylate antibiotics is based on the protein macromolecular structure uncomplexed. In this work, molecular docking, molecular dynamic simulations, and relative free energy calculations were applied in order to get a comprehensive and thorough analysis of TEM-1/ampicillin and TEM-1/amoxicillin complexes. We described the complexes and analyzed the effect of ligand binding on the overall structure. We clearly demonstrate that the key residues involved in the stability of the ligand (hot-spots) vary with the nature of the ligand. Structural effects such as (i) the distances between interfacial residues (Ser70−Oγ and Lys73−Nζ, Lys73−Nζ and Ser130−Oγ, and Ser70−Oγ−Ser130−Oγ), (ii) side chain rotamer variation (Tyr105 and Glu240), and (iii) the presence of conserved waters can be also influenced by ligand binding. This study supports the hypothesis that TEM-1 suffers structural modifications upon ligand binding.

Simulation model for driving dynamics, energy use and power supply

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Power law analysis of financial index dynamics

Power law PL and fractional calculus are two faces of phenomena with long memory behavior. This paper applies PL description to analyze different periods of the business cycle. With such purpose the evolution of ten important stock market indices DAX, Dow Jones, NASDAQ, Nikkei, NYSE, S&P500, SSEC, HSI, TWII, and BSE over time is studied. An evolutionary algorithm is used for the fitting of the PL parameters. It is observed that the PL curve fitting constitutes a good tool for revealing the signal main characteristics leading to the emergence of the global financial dynamic evolution.

Relativistic time effects in financial dynamics

Financial time series have a complex dynamic nature. Many techniques were adopted having in mind standard paradigms of time flow. This paper explores an alternative route involving relativistic effects. It is observed that the measuring perspective influences the results and that we can have different time textures.

Analysis of temperature time-series: embedding dynamics into the MDS method

Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.

Symbolic fractional dynamics

Fractional dynamics reveals long range memory properties of systems described by means of signals represented by real numbers. Alternatively, dynamical systems and signals can adopt a representation where states are quantified using a set of symbols. Such signals occur both in nature and in man made processes and have the potential of a aftermath as relevant as the classical counterpart. This paper explores the association of Fractional calculus and symbolic dynamics. The results are visualized by means of the multidimensional technique and reveal the association between the fractal dimension and one definition of fractional derivative.

Complex dynamics of financial indices

This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.