Juice from king palm (Archontophoenix alexandrae) leaf sheathes: chemical characterisation and use in soft drink formulation

The heart of palm is a food extracted from several species of palm trees. Only 10–20% of the raw material is transformed into canned hearts of palm, therefore this agro‐industry generates a large quantity of solid residue. The aim of this work was to extract and characterise a juice produced from this solid residue. This extract is compared with the traditional fruit juices (orange and pineapple juices), obtaining higher contents of minerals, such as magnesium (22.80 mg/100 g) and potassium (276.90 mg/100 g), phenolic compounds (gallic, 3,4‐dihydroxybenzoic, chlorogenic, syringic and caffeic acids) and high free radical scavenging capacity (expressed as 2,2‐diphenyl‐1‐picrylhydrazyl), which suggest high antioxidant activity. Additionally, a new soft drink was formulated using this king palm juice as its main ingredient. The soft drink samples formulated with this juice had high sensory acceptability and high intention of consumption, which suggests an important and low‐cost application for this industrial residue.     

Structured Output SVM for Remote Sensing Image Classification

Traditional kernel classifiers assume independence among the classification outputs. As a consequence, each misclassification receives the same weight in the loss function. Moreover, the kernel function only takes into account the similarity between input values and ignores possible relationships between the classes to be predicted. These assumptions are not consistent for most of real-life problems. In the particular case of remote sensing data, this is not a good assumption either. Segmentation of images acquired by airborne or satellite sensors is a very active field of research in which one tries to classify a pixel into a predefined set of classes of interest (e.g. water, grass, trees, etc.). In this situation, the classes share strong relationships, e.g. a tree is naturally (and spectrally) more similar to grass than to water. In this paper, we propose a first approach to remote sensing image classification using structured output learning. In our approach, the output space structure is encoded using a hierarchical tree, and these relations are added to the model in both the kernel and the loss function. The methodology gives rise to a set of new tools for structured classification, and generalizes the traditional non-structured classification methods. Comparison to standard SVM is done numerically, statistically and by visual inspection of the obtained classification maps. Good results are obtained in the challenging case of a multispectral image of very high spatial resolution acquired with QuickBird over a urban area.     

An experimental study for transmitting MPEG-2 streams over ATM networks

This paper presents a comparative study of different techniques aiming at transmitting MPEG-2 streams over ATM networks, with emphasis on the presentation of practical results achieved on an experimental platform available at LSI, a laboratory of the University of São Paulo, Brazil. This study has the purpose to determine some tuning parameters for optimizing the implementation of distributed multimedia applications on different network technologies. The focus of this experimental study has been on non-native ATM techniques like “Classical IP over ATM” and “LAN Emulation”, as well as native ATM techniques based on direct access service primitives to AAL5. The influence of different parameters, like packet length, buffer size, CPU speed, on the resulting throughput has been studied. Furthermore, a testing tool is being developed for assessing the transmission of MPEG-2 streams based on the practical experience achieved so far. These results will permit the evaluation of different network technologies and also help in the development of distributed multimedia applications like video-on-demand, videoconferencing and telemedicine.     

Resting energy expenditure and carbohydrate oxidation are higher in elderly patients with COPD: a case control study

ABSTRACT: BACKGROUND: Elderly patients with chronic obstructive pulmonary disease (COPD) usually have a compromised nutritional status which is an independent predictor of morbidity and mortality. To know the Resting Energy Expenditure (REE) and the substrate oxidation measurement is essential to prevent these complications. This study aimed to compare the REE, respiratory quotient (RQ) and body composition between patients with and without COPD. METHODS: This case-control study assessed 20 patients with chronic obstructive pulmonary disease attending a pulmonary rehabilitation program. The group of subjects without COPD (control group) consisted of 20 elderly patients attending a university gym, patients of a private service and a public healthy care. Consumption of oxygen (O2) and carbon dioxide (CO2) was determined by indirect calorimetry and used for calculating the resting energy expenditure and respiratory quotient. Body mass index (BMI) and waist circumference (WC) were also measured. Percentage of body fat (%BF), lean mass (kg) and muscle mass (kg) were determined by bioimpedance. The fat free mass index (FFMI) and muscle mass index (MMI) were then calculated. Results: The COPD group had lower BMI than control (p=0.02). However, WC, % BF, FFMI and MM-I did not differ between the groups. The COPD group had greater RQ (p=0.01), REE (p=0.009) and carbohydrate oxidation (p= 0.002). Conclusions: Elderly patients with COPD had higher REE, RQ and carbohydrate oxidation than controls.     

Quantification of soluble solids in reconstituted açaí (Euterpe oleracea Mart.) pulp using near‐infrared spectroscopy

Açaí consumption is increasing worldwide because of the growing recognition of its nutritional and therapeutic properties. This product is classified based on its soluble solids content (SS), but the determination of SS in pulp is time consuming, tedious and not suitable for modern food processing plants. As near‐infrared (NIR) systems have been implemented to measure various quality attributes of food products, the objective of this study was to evaluate the feasibility of NIR diffuse reflectance spectroscopy to quantify the SS content of açaí pulp. Partial least squares (PLS) regression models were constructed to predict the SS. An optimum PLS model required one latent variable [principal component (PC)1 = 97%] with a root‐mean‐square error of calibration (RMSEC) of 1.06% for the calibration data set and the root‐mean‐square error of prediction (RMSEP) of 1.03% for internal cross‐validation. External validation using an independent data set showed good performance (RMSEP = 1.33% and Rp² = 0.82). NIR spectroscopy is a reliable method with which to determine SS in açaí pulp and thereby to classify açaí pulp according to established minimum quality standards.     

Effect of particle type on the mechanisms of break up of nanoscale particle clusters

Nanoparticles tend to form large clusters (aggregates and agglomerates) which need to be broken up when dispersing in a liquid. The dispersion of nanoparticle clusters has been studied to investigate the kinetics and mechanisms of break up with two types of particles: fumed silica and aluminium oxide. Results obtained under different processing conditions using an in-line rotor-stator are reported. It could be concluded that break up occurs predominantly through erosion in the case of silica and shattering with aluminium oxide.     

Kinetic characterization of the deproteinization of trabecular and cortical bovine femur bones

The present study proposes an interpretation of the mechanism of bone deproteinization. Cortical and trabecular bovine femur bones were deproteinized using 6% NaOCl (37, 50, 60 °C). The kinetic parameters (rate constant and activation energy) were calculated, and the surface area of each type of bone was considered. A statistical analysis of the rate constants shows that cortical bone deproteinizes at a lower rate than trabecular. The activation energy is higher for trabecular than cortical bone, and no significant differences are found in the protein concentration values for both bones. Therefore, although trabecular bone deproteinizes at a higher rate than cortical, trabecular bone requires more energy for the deproteinization reaction to take place. Considering that both types of bones are constituted by mineral, protein, and water; the present work shows that the individual inner matrix architecture of trabecular and cortical bones, along with characteristics such as the mineral concentration and its bonding with collagen fibers, may be the responsible factors that control protein depletion.     

A simple strategy to generate light-responsive azobenzene-containing epoxy networks

Azobenzene containing epoxy networks are a class of photosensitive materials characterized by high thermal, optical and mechanical stability, promising for reversible optical storage applications. Here, we propose an encouraging two-step method to fabricate crosslinked coatings by simply reacting an amine-functionalized azobenzene and an epoxy resin in bulk for specified times to get soluble products (network precursors). Thin films based on these precursors were prepared, and thermally crosslinked in order to obtain high-T_g materials. The optical response of the materials was determined, both before and after crosslinking. In the case of the samples as prepared, the dynamic time response of the system is fast, as well as the relaxation of the photoinduced birefringence, as expected due to the high mobility of the chromophore. On the other hand, crosslinked systems have a slightly slower response, but higher values of remnant birefringence, providing stability of the photoinduced orientation, what makes them promising materials to use in optical storage applications. Besides, further analysis on the effect of temperature on the induced birefringence of the polymeric networks was also conducted to help optimization of material design. Finally, we had presented some preliminary investigations of surface relief grating recording in the obtained new materials.     

Predicting feature interactions by using inconsistency models

Internet applications, such as Email, VoIP and WWW, have been enhanced with many features. However, the introduction and modification of features may result in undesired behaviours, and this effect is known as feature interaction-FI.In this paper we propose a proactive approach for FI detection. Supported by sets of all possible events, predicates and inconsistent behaviours, we generate hypothetical new features that interact with a given feature. By predicting FIs, the feature subscriber may define, in advance, all mechanisms to resolve the FIs that may occur in the future.We adopt a semantic model, based on group theory, for the feature axiomatic specification. The algorithms that generate new features do not depend on the particular data structures used in the semantic model of the feature specification.