Effect of water on the oxygen barrier properties of poly(ethylene terephthalate) and polylactide films

The aim of this work was to study the variations in the oxygen diffusion, solubility, and permeability coefficients of polylactide (PLA) films at different temperatures (5, 23, and 40°C) and water activities (0–0.9). The results were compared with the oxygen diffusion, solubility, and permeability coefficients obtained for poly(ethylene terephthalate) (PET) films under the same experimental conditions. The water sorption isotherm for PLA films was also determined. Diffusion coefficients were determined with the half‐sorption time method. Also, a consistency test for continuous‐flow permeability experimental data was run to obtain the diffusion coefficient with the lowest experimental error and to confirm that oxygen underwent Fickian diffusion in the PLA films. The permeability coefficients were obtained from steady‐state permeability experiments. The results indicated that the PLA films absorbed very low amounts of water, and no significant variation of the absorbed water with the temperature was found. The oxygen permeability coefficients obtained for PLA films (2–12 × 10^?18 kg m/m² s Pa) were higher than those obtained for PET films (1–6 × 10^?19 kg m/m² s Pa) at different temperatures and water activities. Moreover, the permeability coefficients for PLA and PET films did not change significantly with changes in the water activity at temperatures lower than 23°C. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 1790–1803, 2004     

The effectiveness of the combined use of VIX and Support Vector Machines on the prediction of S&P 500

The aim of this research is to analyse the effectiveness of the Chicago Board Options Exchange Market Volatility Index (VIX) when used with Support Vector Machines (SVMs) in order to forecast the weekly change in the S&P 500 index. The data provided cover the period between 3 January 2000 and 30 December 2011. A trading simulation is implemented so that statistical efficiency is complemented by measures of economic performance. The inputs retained are traditional technical trading rules commonly used in the analysis of equity markets such as Relative Strength Index, Moving Average Convergence Divergence, VIX and the daily return of the S&P 500. The SVM identifies the best situations in which to buy or sell in the market. The two outputs of the SVM are the movement of the market and the degree of set membership. The obtained results show that SVM using VIX produce better results than the Buy and Hold strategy or SVM without VIX. The influence of VIX in the trading system is particularly significant when bearish periods appear. Moreover, the SVM allows the reduction in the Maximum Drawdown and the annualised standard deviation.     

Catalysts based in cerium oxide for wet oxidation of acrylic acid in the prevention of environmental risks

Acrylic acid is a refractory compound for the non-catalytic wet oxidation (WO) process and can seriously damage the environment when released in industrial effluents. Oxidation of acrylic acid by catalytic wet oxidation (CWO) was studied in slurry conditions in a high-pressure batch reactor at 200 °C and 15 bar of oxygen partial pressure. Several solid cerium-based catalysts prepared in our laboratory were used (Ag/Ce, Co/Ce, Mn/Ce, CeO, MnO) and evaluated in terms of activity, selectivity and stability. Mn/Ce shows the higher activity in 2 h with 97.7% reduction of total organic carbon (TOC) followed by: MnO(95.5%)>Ag/Ce(85.0%)>Co/Ce(65.1%)>CeO(61.2%). Attempts were also carried out to analyze the influence of different Mn/Ce molar ratios. High percentages of Mn lead to practically total organic carbon concentration (TOC) abatements while low ratios lead to the formation of non-oxidizable compounds. Acrylic acid was readily degraded by all the catalysts pointing out the high importance of using a catalytic process. pH was an indicator of the reaction pathway and acetic acid was found as the major reaction intermediate compound; however it is completely oxidized after 2 h with exception for Co/Ce, CeO and MnO. Carbon adsorption and leaching of metals were poorly found for Mn/Ce indicating high stability. The catalyst microstructure after the reaction was analyzed and formation of whiskers of β-MnO₂ (or less probably MnOOH) were observed at the catalyst surface. Therefore, Mn/Ce revealed to be a promising catalyst for the treatment of effluents containing acrylic acid; nevertheless, its commercialization depends on further research.     

Inductive Model Generation for Text Classification Using a Bipartite Heterogeneous Network

Algorithms for numeric data classification have been applied for text classification. Usually the vector space model is used to represent text collections. The characteristics of this representation such as sparsity and high dimensionality sometimes impair the quality of general-purpose classifiers. Networks can be used to represent text collections, avoiding the high sparsity and allowing to model relationships among different objects that compose a text collection. Such network- based representations can improve the quality of the classification results. One of the simplest ways to represent textual collections by a network is through a bipartite heterogeneous network, which is composed of objects that represent the documents connected to objects that represent the terms. Heterogeneous bipartite networks do not require computation of similarities or relations among the objects and can be used to model any type of text collection. Due to the advantages of representing text collections through bipartite heterogeneous networks, in this article we present a text classifier which builds a classification model using the structure of a bipartite heterogeneous network. Such an algorithm, referred to as IMBHN （Inductive Model Based on Bipartite Heterogeneous Network）, induces a classification model assigning weights to objects that represent the terms for each class of the text collection. An empirical evaluation using a large amount of text collections from different domains shows that the proposed IMBHN algorithm produces significantly better results than k-NN, C4.5, SVM, and Naive Bayes algorithms.     

Water flux,DSC, and cytotoxicity characterization of membranes of cellulose acetate produced from sugar cane bagasse,using PEG 600

Summary In this article, cellulose acetate produced through the homogeneous acetylation of sugar cane bagasse cellulose was used to produce membranes, using poly(ethyleneglycol) 600 (PEG 600) as an admixture. The membranes were characterized using water flux measurements (Payne’s cup), differential scanning calorimetry (DSC) and neutral red uptake (cytotoxicity). The results showed that PEG 600 acts as a crystallinity inductor and/or pore former in the cellulose acetate matrix. The induction of crystallinity is important for this system since it had not been reported on the literature yet. The results also demonstrated that the studied membranes present a nontoxic behavior.     

Incremental inconsistency detection with low memory overhead

Ensuring models’ consistency is a key concern when using a model‐based development approach. Therefore, model inconsistency detection has received significant attention over the last years. To be useful, inconsistency detection has to be sound, efficient, and scalable. Incremental detection is one way to achieve efficiency in the presence of large models. In most of the existing approaches, incrementalization is carried out at the expense of the memory consumption that becomes proportional to the model size and the number of consistency rules. In this paper, we propose a new incremental inconsistency detection approach that only consumes a small and model size‐independent amount of memory. It will therefore scale better to projects using large models and many consistency rules. Copyright © 2012 John Wiley & Sons, Ltd.     

String analysis by sliding positioning strategy

Discovering frequent factors from long strings is an important problem in many applications, such as biosequence mining. In classical approaches, the algorithms process a vast database of small strings. However, in this paper we analyze a small database of long strings. The main difference resides in the high number of patterns to analyze. To tackle the problem, we have developed a new algorithm for discovering frequent factors in long strings. We present an Apriori-like solution which exploits the fact that any super-pattern of a non-frequent pattern cannot be frequent. The SANSPOS algorithm does a multiple-pass, candidate generation and test approach. Multiple length patterns can be generated in a pass. This algorithm uses a new data structure to arrange nodes in a trie. A Positioning Matrix is defined as a new positioning strategy. By using Positioning Matrices, we can apply advanced prune heuristics in a trie with a minimal computational cost. The Positioning Matrices let us process strings including Short Tandem Repeats and calculate different interestingness measures efficiently. Furthermore, in our algorithm we apply parallelism to transverse different sections of the input strings concurrently, speeding up the resulting running time. The algorithm has been successfully used in natural language and biological sequence contexts.     

Ontology-based similarity for product information retrieval

Product development of today is becoming increasingly knowledge intensive. Specifically, design teams face considerable challenges in making effective use of increasing amounts of information. In order to support product information retrieval and reuse, one approach is to use case-based reasoning (CBR) in which problems are solved “by using or adapting solutions to old problems.” In CBR, a case includes both a representation of the problem and a solution to that problem. Case-based reasoning uses similarity measures to identify cases which are more relevant to the problem to be solved. However, most non-numeric similarity measures are based on syntactic grounds, which often fail to produce good matches when confronted with the meaning associated to the words they compare. To overcome this limitation, ontologies can be used to produce similarity measures that are based on semantics. This paper presents an ontology-based approach that can determine the similarity between two classes using feature-based similarity measures that replace features with attributes. The proposed approach is evaluated against other existing similarities. Finally, the effectiveness of the proposed approach is illustrated with a case study on product–service–system design problems.     

Chemical analysis of ozonized theobroma fat

Ozonized theobroma fat is used as raw material in the manufacture of pessaries and cosmetic creams. Ozonization of theobroma fat with water was carried out at different applied ozone dosages, and the resultant PV, acid value, iodine value, total hydroperoxide content, and FA content were determined. PV and total hydroperoxide content showed a notable increase with applied ozone dosage up to 35.7 mg/g. Acid value varied slightly from 4.1 to 9.9 mg KOH/g, and the iodine value fell to zero. PV and total hydroperoxide content increased slightly with a higher applied ozone dosage. The comparison of total hydroperoxide measurement using ferrous oxidation in xylenol orange assay and traditional iodometric assay for PV determination showed a significant linear correlation. Small amounts of oleic acid were found in ozonized theobroma fat samples with iodine value equaling zero, which demonstrated that iodine value determination is an inexact assay. During ozonization of theobroma fat, an increase in acid value of 18.9-fold with respect to the initial value was observed owing to decomposition of peroxide.