New ionic liquids and salts derived from β-Lactam antibiotics

In recent years ionic liquids (ILs) have been increasing the popularity and the number of applications. Ionic liquids were used mainly as solvent in organic synthesis, but in recent years they are also used in analytical chemistry, separation chemistry and material science. Additional to significant developments in their chemical properties and applications, ionic liquids are now bringing unexpected opportunities at the interface of chemistry with the life sciences. Ionic liquids (ILs) are currently defined as salts that are composed solely of cations and anions which melt below 100ºC. Our goal in this work is to explore the dual activity of the ionic liquids, due to the presence of two different ions, an anion with bacterial activity as β-lactam antibiotics and different kinds of cations. In this work the anions of ILs and salts were derived from three different antibiotics: ampicillin, penicillin and amoxicillin. The cations were derived from substituted ammonium, phosphonium pyridinium and methylimidazolium salts, such as: tetraethyl ammonium, trihexiltetradecilphosphonium, cetylpyridinium, choline (an essential nutrient), 1-ethyl-3-methylimidazolium, and 1-ethanol-3-methyl imidazolium structures. Commercial ammonium and phosponium halogen salts were first transformed into hydroxides on ionic exchange column (Amberlite IRA-400) in methanol. The prepared hydroxides were then neutralized with β-lactam antibiotics. After crystallization we obtained pure ILs and salts containing β-lactam antibiotics. This work presents a novel method for preparation of new salts of antibiotics with low melting point and their chemistry and microbiological characterization.

Produção de carvão activado a partir de resíduos da indústria de curtumes

As aparas de wet-blue e de wet-white constituem um resíduo sólido da indústria de curtumes com um elevado teor em carbono, tornando relevante a sua utilização na preparação de materiais de interesse tecnológico. Este trabalho teve como objectivo a preparação de carvões activados a partir de resíduos da indústria de curtumes. Os métodos de activação utilizados para a preparação dos carvões activados foram a activação física com dióxido de carbono e activação química com hidróxido de potássio. A carbonização dos resíduos foi estudada na gama de temperaturas de 500 ºC a 800 ºC, verificando-se que a sua carbonização se pode considerar completa para a temperatura de 800 ºC. Na activação física os precursores foram previamente carbonizados sob uma atmosfera inerte a 800 ºC e posteriormente activados a 940 ºC usando o CO2 como agente activante. Na etapa de activação variou-se o tempo de activação (20, 40 e 60 minutos) de modo a estudar a influência do grau de queima nas propriedades texturais dos carvões activados. O carvão activado obtido pelo método de activação física com maior área superficial específica foi o carvão preparado a partir do resíduo de wet-blue para um tempo de activação de 40 minutos e grau de queima de 23 % (SBET = 152 m2/g). Para a activação química, procedeu-se à impregnação dos precursores com KOH usando razões mássicas de impregnação KOH:precursor de 0,5:1, 1:1 e 3:1. A impregnação foi efectuada directamente nos resíduos de wet-blue e de wet-white e nos resíduos de wet-blue e de wet-white carbonizados. A activação foi efectuada a 940 ºC sob uma atmosfera inerte, com uma velocidade de aquecimento de 5 ºC/min, e um tempo de activação de 1 hora. No caso da série de carvões activados obtidos por impregnação do precursor, o carvão que exibe melhores propriedades texturais é o carvão activado preparado por impregnação na razão de 1:1 a partir do resíduo de wet-blue (SBET = 1696 m2/g). Na série de carvões activados preparados por impregnação do precursor carbonizado, o carvão com melhores propriedades texturais é o carvão proveniente da impregnação do carbonizado do resíduo de wet-blue na razão de 3:1 (SBET = 1507 m2/g). Os carvões activados obtidos por este método de activação são essencialmente microporosos e com elevada área superficial específica. Testes de adsorção preliminares mostram que estes carvões activados têm um bom desempenho para a remoção de cor de efluentes da indústria de curtumes. Concluiu-se que por activação química com KOH dos resíduos de wet-blue e wet-white se obtêm carvões activados com boas propriedades texturais, elevadas áreas superficiais específicas e elevado volume de microporos, quando comparadas com as dos carvões activados resultantes da activação física. Deste modo, chegou-se à conclusão que ambos os resíduos são bons precursores para a produção de carvão activado, mais propriamente recorrendo à activação química, reduzindo assim o volume de resíduos da indústria de curtumes destinados ao aterro.

Influencing factors on bread-derived exposure to ochratoxin A: type, origin and composition

The nearly ubiquitous consumption of cereals all over the world renders them an important position in international nutrition, but concurrently allocates exposure to possible contained contaminants. Mycotoxins are natural food contaminants, difficult to predict, evade, and reduce, so it is important to establish the real contribution of each contaminated food product, with the aim to evaluate mycotoxin exposure. This was the key objective of this survey and analysis for ochratoxin A content on 274 samples of commercialized bread in the Portuguese market, during the winter 2007. Different bread products were analyzed through an HPLC-FD method, including traditional types, novel segments, and different grain based bread products. A wide-ranging low level contamination was observed in all regions and types of bread products analyzed, especially in the Porto and Coimbra regions, and in the maize and whole-grain or fiber-enriched bread. Nevertheless, the exposure through contaminated wheat bread continues to be the most significant, given its high consumption and dominance in relation to the other types of bread.

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.

Analysis of financial data series using fractional Fourier transform and multidimensional scaling

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

Recomendação de conteúdos multimédia

A quantidade e variedade de conteúdos multimédia actualmente disponíveis cons- tituem um desafio para os utilizadores dado que o espaço de procura e escolha de fontes e conteúdos excede o tempo e a capacidade de processamento dos utilizado- res. Este problema da selecção, em função do perfil do utilizador, de informação em grandes conjuntos heterogéneos de dados é complexo e requer ferramentas específicas. Os Sistemas de Recomendação surgem neste contexto e são capazes de sugerir ao utilizador itens que se coadunam com os seus gostos, interesses ou necessidades, i.e., o seu perfil, recorrendo a metodologias de inteligência artificial. O principal objectivo desta tese é demonstrar que é possível recomendar em tempo útil conteúdos multimédia a partir do perfil pessoal e social do utilizador, recorrendo exclusivamente a fontes públicas e heterogéneas de dados. Neste sen- tido, concebeu-se e desenvolveu-se um Sistema de Recomendação de conteúdos multimédia baseado no conteúdo, i.e., nas características dos itens, no historial e preferências pessoais e nas interacções sociais do utilizador. Os conteúdos mul- timédia recomendados, i.e., os itens sugeridos ao utilizador, são provenientes da estação televisiva britânica, British Broadcasting Corporation (BBC), e estão classificados de acordo com as categorias dos programas da BBC. O perfil do utilizador é construído levando em conta o historial, o contexto, as preferências pessoais e as actividades sociais. O YouTube é a fonte do histo- rial pessoal utilizada, permitindo simular a principal fonte deste tipo de dados - a Set-Top Box (STB). O historial do utilizador é constituído pelo conjunto de vídeos YouTube e programas da BBC vistos pelo utilizador. O conteúdo dos vídeos do YouTube está classificado segundo as categorias de vídeo do próprio YouTube, sendo efectuado o mapeamento para as categorias dos programas da BBC. A informação social, que é proveniente das redes sociais Facebook e Twit- ter, é recolhida através da plataforma Beancounter. As actividades sociais do utilizador obtidas são filtradas para extrair os filmes e séries que são, por sua vez, enriquecidos semanticamente através do recurso a repositórios abertos de dados interligados. Neste caso, os filmes e séries são classificados através dos géneros da IMDb e, posteriormente, mapeados para as categorias de programas da BBC. Por último, a informação do contexto e das preferências explícitas, através da classificação dos itens recomendados, do utilizador são também contempladas. O sistema desenvolvido efectua recomendações em tempo real baseado nas actividades das redes sociais Facebook e Twitter, no historial de vídeos Youtube e de programas da BBC vistos e preferências explícitas. Foram realizados testes com cinco utilizadores e o tempo médio de resposta do sistema para criar o conjunto inicial de recomendações foi 30 s. As recomendações personalizadas são geradas e actualizadas mediante pedido expresso do utilizador.

Share GFS – Games, Films & Series: sistema de recomendação

Esta dissertação incide sobre o estudo e análise de uma solução para a criação de um sistema de recomendação para uma comunidade de consumidores de media e no consequente desenvolvimento da mesma cujo âmbito inicial engloba consumidores de jogos, filmes e/ou séries, com o intuito de lhes proporcionar a oportunidade de partilharem experiências, bem como manterem um registo das mesmas. Com a informação adquirida, o sistema reúne condições para proceder a sugestões direcionadas a cada membro da comunidade. O sistema atualiza a sua informação mediante as ações e os dados fornecidos pelos membros, bem como pelo seu feedback às sugestões. Esta aprendizagem ao longo do tempo permite que as sugestões do sistema evoluam juntamente com a mudança de preferência dos membros ou se autocorrijam. O sistema toma iniciativa de sugerir mediante determinadas ações, mas também pode ser invocada uma sugestão diretamente pelo utilizador, na medida em que este não precisa de esperar por sugestões, podendo pedir ao sistema que as forneça num determinado momento. Nos testes realizados foi possível apurar que o sistema de recomendação desenvolvido forneceu sugestões adequadas a cada utilizador específico, tomando em linha de conta as suas ações prévias. Para além deste facto, o sistema não forneceu qualquer sugestão quando o histórico destas tinha provado incomodar o utilizador.

Radioactivity levels of 238U and 232Th decay series and related dose rates in the surroundings of a coal power plant using high resolution g-spectrometry

Gamma radiations measurements were carried out in the vicinity of a coal-fired power plant located in the southwest coastline of Portugal. Two different gamma detectors were used to assess the environmental radiation within a circular area of 20 km centred in the coal plant: a scintillometer (SPP2 NF, Saphymo) and a high purity germanium detector (HPGe, Canberra). Fifty urban and suburban measurements locations were established within the defined area and two measurements campaigns were carried out. The results of the total gamma radiation ranged from 20.83 to 98.33 counts per second (c.p.s.) for both measurement campaigns and outdoor doses rates ranged from 77.65 to 366.51 Gy/h. Natural emitting nuclides from the U-238 and Th-232 decay series were identified as well as the natural emitting nuclide K-40. The radionuclide concentration from the uranium and thorium series determined by gamma spectrometry ranged from 0.93 to 73.68 Bq/kg, while for K-40 the concentration ranged from 84.14 to 904.38 Bq/kg. The obtained results were used primarily to define the variability in measured environmental radiation and to determine the coal plant’s influence in the measured radiation levels. The highest values were measured at two locations near the power plant and at locations between the distance of 6 and 20 km away from the stacks, mainly in the prevailing wind direction. The results showed an increase or at least an influence from the coal-fired plant operations, both qualitatively and quantitatively.

Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

Aerobic Exercise Does Not Predict Brain Derived Neurotrophic Factor And Cortisol Alterations in Depressed Patients

The pathophysiology of depression is related to neurobiological changes that occur in the monoamine system, hypothalamic-pituitary-adrenal axis, neurogenesis system and the neuroimmune system. In recent years, there has been a growing interest in the research of the effects of exercise on brain function, with a special focus on its effects on brainderived neurotrophic factor (BDNF), cortisol and other biomarkers. Thus, the aim of this study is to present a review investigating the acute and chronic effects of aerobic exercise on BDNF and cortisol levels in individuals with depression. It was not possible to establish an interaction between aerobic exercise and concentration of BDNF and cortisol, which may actually be the result of the divergence of methods, such as type of exercises, duration of the sessions, and prescribed intensity and frequency of sessions.

Fractional State Space Analysis of Temperature Time Series

Atmospheric temperatures characterize Earth as a slow dynamics spatiotemporal system, revealing long-memory and complex behavior. Temperature time series of 54 worldwide geographic locations are considered as representative of the Earth weather dynamics. These data are then interpreted as the time evolution of a set of state space variables describing a complex system. The data are analyzed by means of multidimensional scaling (MDS), and the fractional state space portrait (fSSP). A centennial perspective covering the period from 1910 to 2012 allows MDS to identify similarities among different Earth’s locations. The multivariate mutual information is proposed to determine the “optimal” order of the time derivative for the fSSP representation. The fSSP emerges as a valuable alternative for visualizing system dynamics.

Plant derived and dietary phenolic antioxidants: Anticancer properties

n this paper, a review of the literature on the phenolic compounds with anticancer activity published between 2008 and 2012 is presented. In this overview only phenolic antioxidant compounds that display significant anticancer activity have been described. In the first part of this review, the oxidative and nitrosative stress relation with cancer are described. In the second part, the plant-derived food extracts, containing identified phenolic antioxidants, the phenolic antioxidants isolated from plants and plant-derived food or commercially available and the synthetic ones, along with the type of cancer and cells where they exert anticancer activity, are described and summarized in tables. The principal mechanisms for their anti-proliferative effects were also described. Finally, a critical analysis of the studies and directions for future research are included in the conclusion.