Compatible Ternary Blends of Chitosan/poly(vinyl alcohol)/poly(lactic acid) Produced by Oil-in-Water Emulsion Processing

Ternary compatible blends of chitosan, poly(vinyl alcohol), and poly(lactic acid) were prepared by an oil-in-water (O/W) emulsion process. Solutions of chitosan in aqueous acetic acid, poly(vinyl alcohol) (PVA) in water, and poly(lactic acid) (PLA) in chloroform were blended with a high shear mixer. PVA was used as an emulsifier to stabilize the emulsion and to reduce the interfacial tension between the solid polymers in the blends-produced. It proved to work very well because the emulsions were stable for periods of days or weeks and compatible blends were obtained When PVA was added. This effect was attributed to a synergistic effect of PVA and chitosan because the binary blends PVA/PLA and chitosan/PLA were completely incompatible; The blends were characterized by scanning electron microscopy (SEM), differential scanning calorimetry (DSC), thermal mechanical analysis (TMA), stress strain tests, and Fourier transform infrared spectroscopy (FTIR). The results indicated that despite the fact that the system contained distinct phases some degree of molecular miscibility occurred when the three components were present in the blend.

Determination of volatiles produced during radiation processing in Laurus cinnamomum

In order to protect food from pathogenic microorganisms as well as increase its shelf-life, while keeping sensorial properties (e.g., odor and taste), which are important properties required by spice buyers, it is necessary to analyze volatile formation from irradiation of medicinal and food herbs. Possible changes in the odor of these herbs are evaluated by characterizing different radiation doses and effects on sensorial properties, in order to allow better application of the irradiation technology. The aim of the present study was to analyze volatile formation on cinnamon (Laurus cinnamomum) samples after gamma irradiation. These samples were irradiated into plastic packages using a (60)Co facility. Radiation doses applied were 0, 5, 10, 15, 20 and 25 kGy. For the analysis of the samples, solid-phase microextraction (SPME) was applied, while for the analysis of volatile compounds, CG/MS. Spice irradiation showed the highest decrease in volatile compounds. For L. cinnamomum, the irradiation decreased volatile compounds by nearly 56% and 89.5%, respectively, comparing to volatile from a sample which had not been previously irradiated. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.

The chemistry of copper patination

The chemistry of copper patination was investigated by two series of experiments. The chemistry of an aqueous copper-sulphate solution was studied at concentrations and pH values near those predicted in an electrolyte on copper exposed to the atmosphere. The electrochemical reactions in an electrolyte in contact with cuprite were investigated in a reaction vessel which used cuprite powder in artificial rainwater to study the electrochemistry of the atmospheric corrosion and patination of copper. Typical sulphate concentrations in rainwater are sufficient to precipitate posnjakite (Cu4SO4(OH)(6)2H(2)O)), a possible precursor to brochantite, within an hour of wetting a cuprite surface. Brochantite (Cu4SO4(OH)(6)), the most commonly found copper salt in natural patinas is responsible for their green appearance. Precipitation of brochantite from the electrolyte resulted from an increase in pH due to the cathodic reduction of oxygen and an increase in cupric ion concentrations by cuprite oxidation. (C) 1998 Elsevier Science Ltd. All rights reserved.

Conformational selection of inhibitors and substrates by proteolytic enzymes: Implications for drug design and polypeptide processing

Inhibitors of proteolytic enzymes (proteases) are emerging as prospective treatments for diseases such as AIDS and viral infections, cancers, inflammatory disorders, and Alzheimer's disease. Generic approaches to the design of protease inhibitors are limited by the unpredictability of interactions between, and structural changes to, inhibitor and protease during binding. A computer analysis of superimposed crystal structures for 266 small molecule inhibitors bound to 48 proteases (16 aspartic, 17 serine, 8 cysteine, and 7 metallo) provides the first conclusive proof that inhibitors, including substrate analogues, commonly bind in an extended beta-strand conformation at the active sites of all these proteases. Representative superimposed structures are shown for (a) multiple inhibitors bound to a protease of each class, (b) single inhibitors each bound to multiple proteases, and (c) conformationally constrained inhibitors bound to proteases. Thus inhibitor/substrate conformation, rather than sequence/composition alone, influences protease recognition, and this has profound implications for inhibitor design. This conclusion is supported by NMR, CD, and binding studies for HIV-1 protease inhibitors/ substrates which, when preorganized in an extended conformation, have significantly higher protease affinity. Recognition is dependent upon conformational equilibria since helical and turn peptide conformations are not processed by proteases. Conformational selection explains the resistance of folded/structured regions of proteins to proteolytic degradation, the susceptibility of denatured proteins to processing, and the higher affinity of conformationally constrained 'extended' inhibitors/substrates for proteases. Other approaches to extended inhibitor conformations should similarly lead to high-affinity binding to a protease.

Quantification of free mycophenolic acid by high-performance liquid chromatography-atmospheric pressure chemical ionisation tandem mass spectrometry

To facilitate the investigation of free mycophenolic acid concentrations we developed a high-performance liquid chromatography tandem mass spectrometry method using indomethacin as an internal standard. Free drug was isolated from plasma samples (500 mul) using ultrafiltration, The analytes were extracted from the ultrafiltrate (200 mul) using C-18 solid-phase extraction. Detection was by selected reactant monitoring of mycophenolic acid (m/z 318.9-->190.9) and the internal standard (m/z 356.0-->297.1) with an atmospheric pressure chemical ionisation interface. The total chromatographic analysis time was 12 min. The method was found to be linear over the range investigated, 2.5-200 mug/l (r>0.990, n=6). The relative recovery of the method for the control samples studied (7.5, 40.0 and 150 mug/l) ranged from 95 to 104%. The imprecision of the method, expressed in terms of intra- and inter-day coefficients of variation, was

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.

Atmospheric pollutants monitoring by analysis of epiphytic lichens

The Canoparmelia texana epiphytic lichenized fungi was used to monitor atmospheric pollution in the Sao Paulo metropolitan region, SP, Brazil. The cluster analysis applied to the element concentration values confirmed the site groups of different levels of pollution due to industrial and vehicular emissions. In the distribution maps of element concentrations, higher concentrations of Ba and Mn were observed in the vicinity of industries and of a petrochemical complex. The highest concentration of Co found in lichens from the Sao Miguel Paulista site is due to the emissions from a metallurgical processing plant that produces this element. For Br and Zn, the highest concentrations could be associated both to vehicular and industrial emissions. Exploratory analyses revealed that the accumulation of toxic elements in C. texana may be of use in evaluating the human risk of cardiopulmonary mortality due to prolonged exposure to ambient levels of air pollution. (c) 2007 Elsevier Ltd. All rights reserved.

Recent advances in processing and characterization of periodic mesoporous MCM-41 silicate molecular sieves

The discovery of periodic mesoporous MCM-41 and related molecular sieves has attracted significant attention from a fundamental as well as applied perspective. They possess well-defined cylindrical/hexagonal mesopores with a simple geometry, tailored pore size, and reproducible surface properties. Hence, there is an ever-growing scientific interest in the challenges posed by their processing and characterization and by the refinement of various sorption models. Further, MCM-41-based materials are currently under intense investigation with respect to their utility as adsorbents, catalysts, supports, ion-exchangers, and molecular hosts. In this article, we provide a critical review of the developments in these areas with particular emphasis on adsorption characteristics, progress in controlling the pore sizes, and a comparison of pore size distributions using traditional and newer models. The model proposed by the authors for adsorption isotherms and criticalities in capillary condensation and hysteresis is found to explain unusual adsorption behavior in these materials while providing a convenient characterization tool.

New Zealand climate in the Neogene and implications for global atmospheric circulation

New Zealand has a good Neogene plant fossil record. During the Miocene it was without high topography and it was highly maritime, meaning that its climate, and the resulting vegetation, would be controlled dominantly by zonal climate conditions. Its vegetation record during this time suggests the climate passed from an ever-wet and cool but frostless phase in the Early Miocene in which Nothofagus subgenus Brassospora was prominent. Then it became seasonally dry, with vegetation in which palms and Eucalyptus were prominent and fires were frequent, and in the mid-Miocene, it developed a dry-climate vegetation dominated by Casuarinaceae. These changes are reflected in a sedimentological change from acidic to alkaline chemistry and the appearance of regular charcoal in the record. The vegetation then changed again to include a prominent herb component including Chenopodiaceae and Asteraceae. Sphagnum became prominent, and Nothofagus returned, but mainly as the subgenus Fuscospora (presently restricted to temperate climates). This is interpreted as a return to a generally wet, but now cold climate, in which outbreaks of cold polar air and frost were frequent. The transient drying out of a small maritime island and the accompanying vegetation/climate sequence could be explained by a higher frequency of the Sub-Tropical High Pressure (STHP) cells (the descending limbs of the Hadley cells) over New Zealand during the Miocene. This may have resulted from an increased frequency of 'blocking', a synoptic situation which occurs in the region today. An alternative hypothesis, that the global STHP belt lay at a significantly higher latitude in the early Neogene (perhaps 55degreesS) than today (about 30degreesS), is considered less likely because of physical constraints on STHP belt latitude. In either case, the difference between the early Neogene and present situation may have been a response to an increased polar-equatorial temperature gradient. This contrasts with current climate models for the geological past in which the latitude of the High Pressure belt impact is held invariant though geological time. (C) 2003 Elsevier Science B.V. All rights reserved.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Exploração da Point Cloud Library aplicada à percepção em sistemas autónomos

A navegação e a interpretação do meio envolvente por veículos autónomos em ambientes não estruturados continua a ser um grande desafio na actualidade. Sebastian Thrun, descreve em [Thr02], que o problema do mapeamento em sistemas robóticos é o da aquisição de um modelo espacial do meio envolvente do robô. Neste contexto, a integração de sistemas sensoriais em plataformas robóticas, que permitam a construção de mapas do mundo que as rodeia é de extrema importância. A informação recolhida desses dados pode ser interpretada, tendo aplicabilidade em tarefas de localização, navegação e manipulação de objectos. Até à bem pouco tempo, a generalidade dos sistemas robóticos que realizavam tarefas de mapeamento ou Simultaneous Localization And Mapping (SLAM), utilizavam dispositivos do tipo laser rangefinders e câmaras stereo. Estes equipamentos, para além de serem dispendiosos, fornecem apenas informação bidimensional, recolhidas através de cortes transversais 2D, no caso dos rangefinders. O paradigma deste tipo de tecnologia mudou consideravelmente, com o lançamento no mercado de câmaras RGB-D, como a desenvolvida pela PrimeSense TM e o subsequente lançamento da Kinect, pela Microsoft R para a Xbox 360 no final de 2010. A qualidade do sensor de profundidade, dada a natureza de baixo custo e a sua capacidade de aquisição de dados em tempo real, é incontornável, fazendo com que o sensor se tornasse instantaneamente popular entre pesquisadores e entusiastas. Este avanço tecnológico deu origem a várias ferramentas de desenvolvimento e interacção humana com este tipo de sensor, como por exemplo a Point Cloud Library [RC11] (PCL). Esta ferramenta tem como objectivo fornecer suporte para todos os blocos de construção comuns que uma aplicação 3D necessita, dando especial ênfase ao processamento de nuvens de pontos de n dimensões adquiridas a partir de câmaras RGB-D, bem como scanners laser, câmaras Time-of-Flight ou câmaras stereo. Neste contexto, é realizada nesta dissertação, a avaliação e comparação de alguns dos módulos e métodos constituintes da biblioteca PCL, para a resolução de problemas inerentes à construção e interpretação de mapas, em ambientes indoor não estruturados, utilizando os dados provenientes da Kinect. A partir desta avaliação, é proposta uma arquitectura de sistema que sistematiza o registo de nuvens de pontos, correspondentes a vistas parciais do mundo, num modelo global consistente. Os resultados da avaliação realizada à biblioteca PCL atestam a sua viabilidade, para a resolução dos problemas propostos. Prova da sua viabilidade, são os resultados práticos obtidos, da implementação da arquitectura de sistema proposta, que apresenta resultados de desempenho interessantes, como também boas perspectivas de integração deste tipo de conceitos e tecnologia em plataformas robóticas desenvolvidas no âmbito de projectos do Laboratório de Sistemas Autónomos (LSA).

Evaluation of atmospheric deposition and patterns of polycyclic aromatic hydrocarbons in façades of historic monuments of Oporto (Portugal)

Atmospheric pollution by motor vehicles is considered a relevant source of damage to architectural heritage. Thus the aim of this work was to assess the atmospheric depositions and patterns of polycyclic aromatic hydrocarbons (PAHs) in façades of historical monuments. Eighteen PAHs (16 PAHs considered by US EPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) were determined in thin black layers collected from façades of two historical monuments: Hospital Santo António and Lapa Church (Oporto, Portugal). Scanning electron microscopy (SEM) was used for morphological and elemental characterisation of thin black layers; PAHs were quantified by microwave-assisted extraction combined with liquid chromatography (MAE-LC). The thickness of thin black layers were 80–110 μm and they contained significant levels of iron, sulfur, calcium and phosphorus. Total concentrations of 18 PAHs ranged from 7.74 to 147.92 ng/g (mean of 45.52 ng/g) in thin black layers of Hospital Santo António, giving a range three times lower than at Lapa Church (5.44– 429.26 ng/g; mean of 110.25 ng/g); four to six rings compounds accounted at both monuments approximately for 80–85% of ΣPAHs. The diagnostic ratios showed that traffic emissions were significant source of PAHs in thin black layers. Composition profiles of PAHs in thin black layers of both monuments were similar to those of ambient air, thus showing that air pollution has a significant impact on the conditions and stone decay of historical building façades. The obtained results confirm that historical monuments in urban areas act as passive repositories for air pollutants present in the surrounding atmosphere.

ECG Analysis Using Consensus Clustering

Biosignals analysis has become widespread, upstaging their typical use in clinical settings. Electrocardiography (ECG) plays a central role in patient monitoring as a diagnosis tool in today's medicine and as an emerging biometric trait. In this paper we adopt a consensus clustering approach for the unsupervised analysis of an ECG-based biometric records. This type of analysis highlights natural groups within the population under investigation, which can be correlated with ground truth information in order to gain more insights about the data. Preliminary results are promising, for meaningful clusters are extracted from the population under analysis. © 2014 EURASIP.

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.