Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

The study of electricity markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring process produced. Currently, lots of information concerning electricity markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability of the stored data.

An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

NEPHROTOXICITY ATTRIBUTED TO MEGLUMINE ANTIMONIATE (GLUCANTIME) IN THE TREATMENT OF GENERALIZED CUTANEOUS LEISHMANIASIS

Background: Pentavalent antimonials have became of basic importance for the treatment of leishmaniasis. Their most severe side effects have been reported to be increased hepatic enzyme levels and electrocardiographic abnormalities. Nephrotoxicity has been rarely related. Observations: We report a case of generalized cutaneous leishmaniasis involving a 50-year old male patient who was submitted to treatment with meglumine antimoniate (Glucantime). He developed acute renal failure (ARF) due to acute tubular necrosis (ATN), followed by death after receiving a total of 53 ampoules of Glucantime. Conclusions: The treatment with Glucantime was responsible by ARF diagnosed in this patient. The previous urine osmolarity and serum creatinine levels were normal and the autopsy showed ATN. It should be pointed out if ARF may also be explained by massive deposits of immunocomplexes by leishmania antibodies and antigens due to the antigenic break by the antimonial compound, since our patient presented countless lesions covering the entire tegument, similar to the Hexheimer phenomenon, but at the autopsy no glomerular alterations were seen.

Fractional Order Generalized Information

This paper formulates a novel expression for entropy inspired in the properties of Fractional Calculus. The characteristics of the generalized fractional entropy are tested both in standard probability distributions and real world data series. The results reveal that tuning the fractional order allow an high sensitivity to the signal evolution, which is useful in describing the dynamics of complex systems. The concepts are also extended to relative distances and tested with several sets of data, confirming the goodness of the generalization.

Application of Continuous Wavelet Transform to the Analysis of the Modulus of the Fractional Fourier Transform Bands for Resolving Two Component Mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Multidimensional Scaling Visualization using Parametric Similarity Indices

In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of ‘points’. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of “shapes”. This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

Generalized Extraction of Real-Time Parameters for Homogeneous Synchronous Dataflow Graphs

23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2015). 4 to 6, Mar, 2015. Turku, Finland.

Acute generalized exanthematous pustulosis (AGEP). Case report

Acute Generalized Exanthematous Pustulosis (AGEP) is a drug-induced dermatosis characterized by an acute episode of sterile pustules over erythematous-edematous skin. It is accompanied by an episode of fever, which regresses a few days after discontinuation of the drug that caused the condition or as a result of corticosteroid treatment. The main triggering drugs are antibiotics, mainly beta-lactam ones. Other medications, such as antifungal agents, non steroid anti-inflammatory drugs, analgesics, antiarrhythmic, anticonvulsant and antidepressant drugs, may also be responsible. Histologically, it is characterized by the existence of vasculitis, associated with non-follicular subcorneal pustules. A case of a Caucasian female outpatient unit of Dermatology with AGEP, who presented with generalized pustulosis lesions after the use of cephalosporin for urinary infection is related. The diagnosis was confirmed by the clinical and pathological correlations, the resolution of the dermatosis after discontinuation of the drug and use of systemic corticosteroid treatment, and the recurrence of the disorder after the introduction of a similar drug. The importance of the recognition of this drug-induced dermatosis is given by its main differential clinical and histological diagnoses: generalized pustular psoriasis and subcorneal pustulosis.

Probabilistic Stereo Egomotion Transform

In this paper we propose a novel fully probabilistic solution to the stereo egomotion estimation problem. We extend the notion of probabilistic correspondence to the stereo case which allow us to compute the whole 6D motion information in a probabilistic way. We compare the developed approach against other known state-of-the-art methods for stereo egomotion estimation, and the obtained results compare favorably both for the linear and angular velocities estimation.

Infliximab in Recalcitrant Generalized Pustular Arthropatic Psoriasis

Generalized pustular psoriasis is an unstable inflammatory type of psoriasis, with widespread areas of erythema and sterile pustules, associated with fever and systemic symptoms. Infliximab is a monoclonal antibody with anti-TNFalpha activity, approved for use in psoriasis. We describe a male patient with a long history of stable arthropathic psoriasis, hospitalized with a generalized pustular psoriasis and acute exacerbation of articular complaints. The disease was resistant to multiple therapies (acitretin, methotrexate and corticosteroids), so the patient was started on infliximab, with a very rapid response of both cutaneous and articular symptoms. He had complete clearing of lesions at week 12, and marked improvement of the articular symptoms. No recurrence occurred at 8 months of follow-up with infliximab every 8 weeks. Infliximab had an extremely rapid therapeutic action response on a recalcitrant generalized pustular psoriasis. The articular response was also excellent, with significant improvement of quality of life.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Cardiac involvement in total generalized lipodystrophy (Berardinelli- Seip syndrome)

Total generalized lipodystrophy (Berardinelli--Seip Syndrome) is a rare hereditary disease characterized by insulin-resistant diabetes mellitus and a small quantity of adipose tissue and is of unknown origin. Common cardiovascular alterations related to this syndrome are cardiac hypertrophy and arterial hypertension. This article reports a case of Berardinelli--Seip syndrome and reviews the literature with special emphasis on the cardiovascular manifestations of this syndrome.

Modelos Mixtos-Aditivos Generalizados para el Estudio de Fenómenos Biológicos y Sociales Descriptos por Datos Agregados y/o Longitudinales. Generalized Mixed Additive Models for the Study of Biological and Social Phenomenons from Longitudinal and/or Aggregated Data.

Este proyecto propone extender y generalizar los procesos de estimación e inferencia de modelos aditivos generalizados multivariados para variables aleatorias no gaussianas, que describen comportamientos de fenómenos biológicos y sociales y cuyas representaciones originan series longitudinales y datos agregados (clusters). Se genera teniendo como objeto para las aplicaciones inmediatas, el desarrollo de metodología de modelación para la comprensión de procesos biológicos, ambientales y sociales de las áreas de Salud y las Ciencias Sociales, la condicionan la presencia de fenómenos específicos, como el de las enfermedades.Es así que el plan que se propone intenta estrechar la relación entre la Matemática Aplicada, desde un enfoque bajo incertidumbre y las Ciencias Biológicas y Sociales, en general, generando nuevas herramientas para poder analizar y explicar muchos problemas sobre los cuales tienen cada vez mas información experimental y/o observacional.Se propone, en forma secuencial, comenzando por variables aleatorias discretas (Yi, con función de varianza menor que una potencia par del valor esperado E(Y)) generar una clase unificada de modelos aditivos (paramétricos y no paramétricos) generalizados, la cual contenga como casos particulares a los modelos lineales generalizados, no lineales generalizados, los aditivos generalizados, los de media marginales generalizados (enfoques GEE1 -Liang y Zeger, 1986- y GEE2 -Zhao y Prentice, 1990; Zeger y Qaqish, 1992; Yan y Fine, 2004), iniciando una conexión con los modelos lineales mixtos generalizados para variables latentes (GLLAMM, Skrondal y Rabe-Hesketh, 2004), partiendo de estructuras de datos correlacionados. Esto permitirá definir distribuciones condicionales de las respuestas, dadas las covariables y las variables latentes y estimar ecuaciones estructurales para las VL, incluyendo regresiones de VL sobre las covariables y regresiones de VL sobre otras VL y modelos específicos para considerar jerarquías de variación ya reconocidas. Cómo definir modelos que consideren estructuras espaciales o temporales, de manera tal que permitan la presencia de factores jerárquicos, fijos o aleatorios, medidos con error como es el caso de las situaciones que se presentan en las Ciencias Sociales y en Epidemiología, es un desafío a nivel estadístico. Se proyecta esa forma secuencial para la construcción de metodología tanto de estimación como de inferencia, comenzando con variables aleatorias Poisson y Bernoulli, incluyendo los existentes MLG, hasta los actuales modelos generalizados jerárquicos, conextando con los GLLAMM, partiendo de estructuras de datos correlacionados. Esta familia de modelos se generará para estructuras de variables/vectores, covariables y componentes aleatorios jerárquicos que describan fenómenos de las Ciencias Sociales y la Epidemiología.

The period function of the generalized Lotka-Volterra centers

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