Lupin seed coat as a promising food ingredient: physicochemical,nutritional, antioxidant properties,and effect of genotype and environment

The high proportion of seed coat of legume lupins results in big milling lose during kernel flour production, though the seed coat could be value-added as human food. The physicochemical and nutritional properties and antioxidant capacities of seed coats of six Australian sweet lupin cultivars grown at two locations were evaluated. Results showed that genotype, environment and their interaction were significant for seed coat percentage, proximate composition, dietary fibre content, polyphenols and antioxidant capacities. Strong correlations between seed coat lightness and polyphenol content were found. A comparison using multivariate analysis of the seed coat properties showed clear separation based on growing sites. This study indicates the enormous potential of Australian sweet lupin seed coat as an ‘antioxidant dietary fibre’ food source. The results could also benefit to breed varieties with desirable levels of nutrients and phytochemicals.     

Uptake of Nickel(II) Ion by Silica-o-Phenylenediamine Derived from Rice Husk Ash

Silicon - The silica-ortho-phenylenediamine(RHAOPDA) derived from Rice Husk Ash and o- phenylenediamine (OPDA) were synthesized. The prepared material was characterized by different techniques; N2-...     

Survey of data-selection methods in statistical machine translation

Statistical machine translation has seen significant improvements in quality over the past several years. The single biggest factor in this improvement has been the accumulation of ever larger stores of data. We now find ourselves, however, the victims of our own success, in that it has become increasingly difficult to train on such large sets of data, due to limitations in memory, processing power, and ultimately, speed (i.e. data-to-models takes an inordinate amount of time). Moreover, the training data has a wide quality spectrum. A variety of methods for data cleaning and data selection have been developed to address these issues. Each of these methods employs a search or filtering algorithm to select a subset of the data, given a defined set of feature functions. In this paper we provide a comparative overview of research in this area based on application scenario, feature functions and search method.     

Co-immobilization of chitosan and dermatan sulfate from Raja montagui skin on polyethylene terephthalate surfaces: Characterization and antibiofilm activity

In this work, polyethylene terephthalate (PET) was chemically modified by covalent co-immobilization of two separate layers of bioactive polymers composed of chitosan and a new dermatan sulfate isolated from Raja montagui skin. The new materials obtained were characterized by determination of carboxyl groups, ATR-FTIR spectroscopy, drop water contact angle, SEM, and TGA measurements. The different immobilizations modified the surface characteristics; especially when the first layer was dermatan sulfate (PET–DS–Chito) which presented the best surface wettability (71?±?3°). It also reduced the ability of Staphylococcus epidermidis to form biofilm on PET surfaces which could decrease the virulence of vascular prosthesis infections.     

A new correlation for vapor pressure prediction of natural gas mixture

In this study, the Antoine equation of vapor pressure prediction for pure substances has been extended to predict vapor pressure values of a natural gas mixture at a temperature range of 125–230 K. The correlation was modified by applying the software MATLAB 8.2 R2013b (The MathWorks, Natick, MA). The developed correlation for multicomponent natural gas mixture is predictable with few input data of critical temperature, critical pressure, and the acentric factor. For the examined natural gas mixture, the predicted vapor pressures show comparable values with those obtained by applying well-known and accurate cubical equation of state (EOS) of Soave–Redlich–Kwong (SRK) and Peng–Robinson (PR) for the whole range of studied temperatures. From the results, an average absolute deviation of 1.735% for the developed correlation in this work was obtained from the actual results calculated experimentally, which is lower than that obtained by SRK EOS and close to results of PR EOS.     

Natural Convection of Nanofluid in Cylindrical Enclosure Filled with Porous Media

A numerical study has been carried out to investigate the effect of aspect ratio on heat transfer by natural convection of nanofluid taking Cu nano particles and the water as based fluid. The flow is laminar, steady state, axisymmetric two-dimensional in a vertical cylindrical channel filled with porous media. Heat is generated uniformly along the center of the channel with its vertical surface remain with cooled constant wall temperature and insulated horizontal top and bottom surfaces. The governing equations which used are continuity, momentum and energy equations using Darcy law and Boussinesq＇s approximation which are transformed to dimensionless equations. The finite difference approach is used to obtain all the computational results using the MATLAB-7 program. The parameters affected on the system are Rayleigh number ranging within （10≤ Ra ≤ 103）, aspect ratio （1 ≤ As 〈 5） and the volume fraction （0 ≤0 〈 0.2）. The results obtained are presented graphically in the form of streamline and isotherm contour plots and the results show that as ~ increase from 0.01 to 0.2 the value of the mean Nusselt number increase 50.4% for Ra = 1,000.     

Water Conservation in Oman

ABSTRACT

Limited resources and growing needs for water have triggered a nationwide campaign for water conservation in the Sultanate of Oman. A land and soil survey study of Oman shows the availability of more arable land than present water resources could support. Groundwater is the main source for agricultural production. Overpumping at rates higher than the natural recharge has resulted in lowering of the ground water table, while seawater intrusion has led to an increase in soil salinity. A comprehensive water program is underway to: (1) conserve water through efficent irrigation, use of soil additives, modern irrigation systems, agronomic management, and institutionalization; and (2) augmentation of resources via introduction of more desalinization plants, more waste water treatment, use of brackish water; water fog collection, and water harvesting by building recharge dams.     

Hybrid Erasure-Error Protocols for Wireless Video

Many recently proposed cross-layer protocols for wireless video, have advocated the relay of corrupted packet to higher layers. Such protocols lead to both errors and erasures at the compressed video application layer. We generically refer to such schemes as hybrid erasure-error protocols (HEEPs). In this paper, we analyze the utility of HEEPs for efficient transmission of video over wireless channels. In order to maintain the generic nature of the deductions in this paper, we base our analysis on two (rather abstract) communication schemes for wireless video: hybrid error-erasure cross-layer design (CLD) and hybrid error-erasure cross-layer design with side-information (CLDS). We make a comparative analysis of the channel capacities of these schemes over single and multi-hop wireless channels to identify the conditions under which the HEEPs can provide improved performance over conventional (CON) protocols. In addition, we employ Reed Solomon (RS) and low-density parity check (LDPC)-code-based forward-error correction (FEC) schemes to illustrate that the improvement in capacity can easily enable an FEC scheme employed in conjunction with a HEEP to provide improved throughput. Finally we compare the performance of CON, CLD, and CLDS in terms of video quality using the H.264 video standard. The simulation results show a significant advantage for the HEEPs     

Ensemble diversified learning for image classification with noisy labels

Multimedia Tools and Applications - In this work, we develop a new approach for learning a deep neural network for image classification with noisy labels using ensemble diversified learning. We...     

A new family of nonredundant transforms using hybrid wavelets and directional filter banks.

We propose a new family of nonredundant geometrical image transforms that are based on wavelets and directional filter banks. We convert the wavelet basis functions in the finest scales to a flexible and rich set of directional basis elements by employing directional filter banks, where we form a nonredundant transform family, which exhibits both directional and nondirectional basis functions. We demonstrate the potential of the proposed transforms using nonlinear approximation. In addition, we employ the proposed family in two key image processing applications, image coding and denoising, and show its efficiency for these applications.