Secondary Metabolic Profile as a Tool for Distinction and Characterization of Cultivars of Black Pepper (Piper nigrum L.) Cultivated in Pará State,Brazil

This study evaluated the chemical compositions of the leaves and fruits of eight black pepper cultivars cultivated in Pará State (Amazon, Brazil). Hydrodistillation and gas chromatography–mass spectrometry were employed to extract and analyze the volatile compounds, respectively. Sesquiterpene hydrocarbons were predominant (58.5–90.9%) in the cultivars “Cingapura”, “Equador”, “Guajarina”, “Iaçará”, and “Kottanadan”, and “Bragantina”, “Clonada”, and “Uthirankota” displayed oxygenated sesquiterpenoids (50.6–75.0%). The multivariate statistical analysis applied using volatile composition grouped the samples into four groups: γ-Elemene, curzerene, and δ-elemene (“Equador”/“Guajarina”, I); δ-elemene (“Iaçará”/“Kottanadan”/“Cingapura”, II); elemol (“Clonada”/“Uthirankota”, III) and α-muurolol, bicyclogermacrene, and cubebol (“Bragantina”, IV). The major compounds in all fruit samples were monoterpene hydrocarbons such as α-pinene, β-pinene, and limonene. Among the cultivar leaves, phenolics content (44.75–140.53 mg GAE·g⁻¹ FW), the enzymatic activity of phenylalanine-ammonia lyase (20.19–57.22 µU·mL⁻¹), and carotenoids (0.21–2.31 µg·mL⁻¹) displayed significant variations. Due to black pepper’s susceptibility to Fusarium infection, a molecular docking analysis was carried out on Fusarium protein targets using each cultivar’s volatile components. F. oxysporum endoglucanase was identified as the preferential protein target of the compounds. These results can be used to identify chemical markers related to the susceptibility degree of black pepper cultivars to plant diseases prevalent in Pará State.     

Dielectric behavior of PVDF/POMA blends that have a low doped POMA content

The real (ε′) and imaginary (ε″) components of the complex permittivity of blends of PVDF [poly(vinylidene fluoride)] with POMA [poly(o‐methoxyaniline)] doped with toluenosulfonic acid (TSA) containing 1, 2.5, and 5 wt % POMA–TSA were determined in the frequency interval between 10² and 3 × 10⁶ Hz and in the temperature range from ?120 up to 120°C. It was observed that the values of ε′ and ε″ had a greater increase with the POMA–TSA content and with a temperature in the region of frequencies below 10 kHz. This effect decreased with frequency and it was attributed to interfacial polarization. This polarization was caused by the blend heterogeneity, formed by conductive POMA–TSA agglomerates dispersed in an insulating matrix of PVDF. The equation of Maxwell–Garnett, modified by Cohen, was used to evaluate the permittivity and conductivity behavior of POMA–TSA in the blends. A strong decrease was observed in POMA–TSA conductivity in the blend, which was bigger the lower the POMA–TSA content in the blend. This decrease could have been caused either by the POMA dedoping during the blend preparation process or by its dispersion into the insulating matrix. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 752–758, 2003     

Master batch approach for developing PVDF/EVA/CNT nanocomposites with co-continuous morphology and improved electrical conductivity

Conducting polymer composites constituted by co-continuous poly (vinylidene fluoride) (PVDF)/ ethylene- vinyl acetate copolymer (EVA) blends with multiwalled carbon nanotube (CNT) were prepared by melt mixing using different procedures. The effect of the master batch approach on the conductivity, morphology, mechanical, thermal and rheological properties of PVDF/EVA/CNT nanocomposites was compared with that based on one step mixing strategy. The selective extraction experiments revealed that CNT was preferentially localized in the EVA phase in all situations, even when PVDF@CNT master batch was employed. Nanocomposites prepared with EVA@CNT master batch displayed higher conductivity, whose value reached around 10⁻¹ S m⁻¹ with the addition of 0.56 vol% of CNT. The better electrical performance was attributed to the better distribution of the filler, as indicated by transmission electron microscopy and rheological behavior. The electrical and rheological behavior were also investigated as a function of the CNT content.     

A Genre-Aware Approach to Focused Crawling

Focused crawlers have as their main goal to crawl Web pages that are relevant to a specific topic or user interest, playing an important role for a great variety of applications. In general, they work by trying to find and crawl all kinds of pages deemed as related to an implicitly declared topic. However, users are often not simply interested in any document about a topic, but instead they may want only documents of a given type or genre on that topic to be retrieved. In this article, we describe an approach to focused crawling that exploits not only content-related information but also genre information present in Web pages to guide the crawling process. This approach has been designed to address situations in which the specific topic of interest can be expressed by specifying two sets of terms, the first describing genre aspects of the desired pages and the second related to the subject or content of these pages, thus requiring no training or any kind of preprocessing. The effectiveness, efficiency and scalability of the proposed approach are demonstrated by a set of experiments involving the crawling of pages related to syllabi of computer science courses, job offers in the computer science field and sale offers of computer equipments. These experiments show that focused crawlers constructed according to our genre-aware approach achieve levels of F1 superior to 88%, requiring the analysis of no more than 65% of the visited pages in order to find 90% of the relevant pages. In addition, we experimentally analyze the impact of term selection on our approach and evaluate a proposed strategy for semi-automatic generation of such terms. This analysis shows that a small set of terms selected by an expert or a set of terms specified by a typical user familiar with the topic is usually enough to produce good results and that such a semi-automatic strategy is very effective in supporting the task of selecting the sets of terms required to guide a crawling process.     

Design Optimization of Composite Prosthetic Tubes Using GA-ANN Algorithm Considering Tsai-Wu Failure Criteria

The investigation of possible failures in composite materials is a matter of very great importance, and the Tsai-Wu criterion is an effective criterion for analyzing those flaws in anisotropic materials and defining whether the material at a given load will or will not suffer structural failure. In this study, an optimization procedure is proposed to minimize the maximum value of Tsai-Wu of laminated composite tubes subject to axial loading. Artificial neural networks and genetic algorithms are chosen as optimization tools. The results of this study show that the developed algorithm converges faster. Then, the maximum Tsai-Wu value is used as the objective function and the fiber orientations are the constraints in the optimization process. The results yielded by them are compared and discussed. Optimal results are compared with respect to the usual initial design. The design approach is recommended for structures where composites are the key load-carrying members such as orthopedic prosthesis.     

Improving the yield of NoC-based systems through fault diagnosis and adaptive routing

We propose an effective and low cost method to increase the yield and the lifetime of torus NoCs. The method consists in detecting and diagnosing NoC interconnect faults using BIST structures and activating alternative paths for the faulty links. Alternative paths use the inherent redundancy of the torus topology, thus leading to minimal performance, area, and power overhead. We assume an extended interconnect fault model comprising stuck-at and pairwise shorts within a single link or between any two links in the network. Experimental results for a 3×3 NoC show that the proposed approach can correctly diagnose 93% of all possible interconnect faults and can mitigate 42% of those faults (representing 94.4% of the solvable faults) with a worst case performance penalty of 8% and 1% of area overhead. We also demonstrate the scalability of the method by presenting its application to larger NoCs.     

Model-based testing approaches selection for software projects

Selecting software technologies for software projects represents a challenge to software engineers. It is known that software projects differ from each other by presenting different characteristics that can complicate the selection of such technologies. This is not different when considering model-based testing. There are many approaches with different characteristics described in the technical literature that can be used in software projects. However, there is no indication as to how they can fit a software project. Therefore, a strategy to select model-based testing approaches for software projects called Porantim is fully described in this paper. Porantim is based on a body of knowledge describing model-based testing approaches and their characterization attributes (identified by secondary and primary experimental studies), and a process to guide by adequacy and impact criteria regarding the use of this sort of software technology that can be used by software engineers to select model-based testing approaches for software projects.     

Algorithms for the Homogeneous Set Sandwich Problem

A homogeneous set is a non-trivial module of a graph, i.e. a non-empty, non-unitary, proper subset of a graph's vertices such that all its elements present exactly the same outer neighborhood. Given two graphs the Homogeneous Set Sandwich Problem (HSSP) asks whether there exists a sandwich graph which has a homogeneous set. In 2001 Tang et al. published an all-fast algorithm which was recently proven wrong, so that the HSSP's known upper bound would have been reset thereafter at the former determined by Cerioli et al. in 1998. We present, notwithstanding, new deterministic algorithms which have it established at We give as well two even faster randomized algorithms, whose simplicity might lend them didactic usefulness. We believe that, besides providing efficient easy-to-implement procedures to solve it, the study of these new approaches allows a fairly thorough understanding of the problem.     

Proteomics Unveils Post-Mortem Changes in Beef Muscle Proteins and Provides Insight into Variations in Meat Quality Traits of Crossbred Young Steers and Heifers Raised in Feedlot

Proteomics has been widely used to study muscle biology and meat quality traits from different species including beef. Beef proteomics studies allow a better understanding of the biological processes related to meat quality trait determination. This study aimed to decipher by means of two-dimensional electrophoresis (2D-PAGE), mass spectrometry and bioinformatics the changes in post-mortem muscle with a focus on proteins differentially expressed in the Longissimus thoracis (LT) muscle of immunocastrated young heifers and steers. Carcass traits, chemical composition, pH, instrumental color (L*, a*, b*), cooking loss and Warner-Bratzler shear force (WBSF) of meat from F1 Montana-Nellore cattle were also evaluated. Backfat thickness (BFT) and intramuscular fat content (IMF) were 46.8% and 63.6% higher in heifers (p < 0.05), respectively, while evaporation losses (EL) were 10.22% lower compared to steers. No differences (p > 0.05) were observed for tenderness evaluated by WBSF (3, 10, and 17 days post-mortem), pH, and color traits (L*, a* and b*) between the experimental groups. The study revealed several proteins to be differentially expressed proteins in heifers compared steers (p < 0.05). In heifers, proteins involved in nutrient transport (TF, ALB, and MB), energy metabolism (ALDOA, GAPDH, and PKM), and oxidative stress and response to stress (HSPA8 and CA3) were associated with a greater BFT and IMF deposition. The higher expression of these proteins indicated greater oxidative capacity and lower glycolytic activity in the LT muscle of heifers. In steers, there was greater abundance of protein expression related to muscle contraction and proteins of structure (ACTA1, TPM2 and TNNT3), energy metabolism (ENO1, ENO3, PYGM, PGM1 and TPI1) and ATP metabolism (ATP5F1B, PEBP1 and AK1), indicating greater glycogenolysis in LT muscle, suggesting a shift in the glycolytic/oxidative fibers of steers.