Ultracentrifugal and polyacrylamide gel electrophoretic studies of extractability and stability of almond meal proteins

Solubility and stability properties of almond proteins were determined using ultracentrifugation and gel electrophoresis to gain a better insight into the complexity of these proteins. Ultracentrifugal analyses of the water-extractable proteins of defatted almond meal revealed four fractions of 2S, 9S, 14S and 19S. The 14S fraction corresponds to amandin, the classical globulin isolated earlier, and constitutes 65–70% of the extractable proteins. Variation of ionic strength from 0 to 1·0 at pH 6–8 showed no evidence of association–dissociation reactions that are typical of many oilseed and legume proteins. Polyacrylamide gel electrophoresis of the water-extractable proteins under reducing conditions separated two pairs of major polypeptides of 44 and 42 kDa and 27 and 25 kDa that appeared to be the respective acidic and basic polypeptides of amandin corresponding to the classical legumin model. Sodium chloride had no effect on total protein extractability but variation of extraction pH showed a broad minimum in extractability at pH 3–5. In contrast, when a pH 9 extract was lowered in pH, the minimum in protein solubility was narrower and shifted upward to pH 5 largely as a result of the precipitation of amandin. Interaction of amandin with phytate may explain the lower pH of minimum solubility when the meal was extracted directly as opposed to lowering the pH of an alkaline extract. Amandin is a cryoprotein and was obtained in 90% purity by cooling a water extract of defatted meal. Incubation of a water extract of meal in the presence of azide for about 12 days revealed proteolytic nicking of the acidic polypeptides of amandin apparently as a result of attack by endogenous proteinase(s). © 1998 Society of Chemical Industry.     

Optimization for process plans in sheet metal forming

Determining a process plan in the early phase of the sheet metal forming process is a mandatory task for a process planner. The objective of a process planner is to find a feasible and cost optimal process plan which, in particular, optimizes the assignment of processing elements to processing steps of the production process. We propose to find such an assignment in an automatic way for all the hole features by splitting the entire task into three subsequent steps. At each step, the combinatorial optimization problem is modeled as a bin packing problem with conflicts, and heuristically solved by a specifically designed ant colony optimizer. It is ensured that, at each step, the process plan is feasible while minimizing the tooling costs. In our computational results, we compare our approach to the existing greedy heuristic when computing a process plan for five different practice-relevant sheet metal parts, and show that we can save up to 50 % of the entire tooling costs.     

Subspace histograms for outlier detection in linear time

Outlier detection algorithms are often computationally intensive because of their need to score each point in the data. Even simple distance-based algorithms have quadratic complexity. High-dimensional outlier detection algorithms such as subspace methods are often even more computationally intensive because of their need to explore different subspaces of the data. In this paper, we propose an exceedingly simple subspace outlier detection algorithm, which can be implemented in a few lines of code, and whose complexity is linear in the size of the data set and the space requirement is constant. We show that this outlier detection algorithm is much faster than both conventional and high-dimensional algorithms and also provides more accurate results. The approach uses randomized hashing to score data points and has a neat subspace interpretation. We provide a visual representation of this interpretability in terms of outlier sensitivity histograms. Furthermore, the approach can be easily generalized to data streams, where it provides an efficient approach to discover outliers in real time. We present experimental results showing the effectiveness of the approach over other state-of-the-art methods.     

Synthesis of Cubic Nanocrystalline Silicon Carbide (3C-SiC) Films by HW-CVD Method

Cubic nanocrystalline silicon carbide (3C-SiC) films have been deposited by using the hot wire chemical vapor deposition (HW-CVD) method at a low substrate temperature and at high deposition rate. Structural, optical and electrical properties of these films have been investigated as a function of H2 dilution ratio. The formation of 3C-SiC films has been confirmed from low angle XRD analysis, Raman spectroscopy, Fourier transform infrared (FTIR) spectroscopy, x-ray photoelectron spectroscopy (XPS) and dark and photoconductivity measurements. The FTIR spectroscopy analysis revealed that the bond densities of Si-H and C-H decrease while that of Si-C increases with increase in the H₂ dilution ratio. The total hydrogen content decreases with increase in H₂ dilution ratio and was found < 15 at. % over the entire range of H₂ dilution ratio studied whereas the band gap show an increasing trend with increase in the H₂ dilution ratio.     

Fluid-structure interaction modeling of complex parachute designs with the space-time finite element techniques

In recent years we introduced a number of enhancements to the space-time techniques we developed for computer modeling of Fluid-Structure Interaction (FSI) problems. These enhancements, which include more sophisticated fluid-structure coupling and improved mesh generation, are enabling us to address more of the computational challenges involved. Our objective here is to demonstrate the robustness of these techniques in FSI modeling of parachutes involving complex designs. As a numerical example, we have selected a conceptual parachute design with geometric complexities resembling those seen in some of the advanced parachute designs proposed and tested in recent times. We describe our FSI modeling techniques and how we compute the descent and glide performance of this conceptual parachute design.     

Investigation of flow structures and transport phenomena in bubble columns using particle image velocimetry and miniature pressure sensors

The bubble column reactors are usually operated in a heterogeneous regime where the liquid phase turbulence is generated by the bubble motion and the velocity gradients in the mean motion. The turbulent flow comprises of fluid elements moving in a random fashion with different sizes and energies, called ‘flow structures’. Both the large and small scale flow structures within a reactor play an important role in governing the local momentum, heat and mass transfer. The current work is focused on the estimation of the time averaged flow pattern and flow structures. The experimental data has been collected using miniature pressure sensors, PIV+shadowgraphy and LDA. The data was subjected/analyzed to/with multipoint linear stochastic estimation (MLSE), wavelet transforms, image processing and eddy isolation (EIM) to identify the flow structures. Two bubble columns have been used: a narrow rectangular (2D) column and a cylindrical (3D) column. Wavelet transforms (WT) were applied to isolate individual structures from PIV data to get their shape, size and energy in the 2D column. MLSE has been used to obtain the velocity profiles from pressure fluctuation signals. This data, augmented by PIV and LDA data, is subjected to WT and EIM to get the eddy age and its energy distribution. The data of the eddy shape size and energy was used to predict the mass transfer coefficient in the cylindrical bubble column as a test case. Overall, in this work we present a methodology to utilize the experimental data to get a better insight of the dynamics of flow structures, and propose a path forward for the deeper understanding of transport phenomena in bubble columns.     

Effect of food matrix and processing on release of almond protein during simulated digestion

The aims of the present work were to assess digestibility of almond protein in the upper gastrointestinal tract, evaluate the effects of food matrix on protein release and assess the persistence of immunoreactive polypeptides generated during simulated digestion. Prunin, the most abundant protein in almond flour, was sensitive to pepsin, with complete digestion after 20 min in the gastric phase. Addition of the surfactant phosphatidylcholine did not affect the rate and kinetic of digestion, as observed by SDS-PAGE analysis and HPLC, in the stomach and the small intestine of either natural or blanched almond flour. However, incorporation of almond flour into a food matrix, such as chocolate mousse and Victorian sponge cake, decreased the rate of almond protein degradation by pepsin and immunoreactivity of almond polypeptides detected by dot blots and sandwich ELISA retained better. Most of the almond protein identified by in-gel tryptic digestion and MALDI-TOF analysis corresponded to prunin, with pI values of 5–7.     

A practical method to evaluate radiographic unsharpness

A simple method for evaluation of total unsharpness of radiographs using wires of different diameters and plaque type penetrameters instead of knife edge method has been suggested. The theoretical basis of the method and experimental details are explained in this paper.     

A Cost-Minimization Model for Multicharacteristic Component Inspection

In this paper a mathematical model is developed for determining the optimal number of inspections for multicharacteristic components where failure can be catastrophic. The model optimizes the expected total cost per accepted component resulting from (1) type I errors, (2) type II errors, (3) cost of added inspection, and (4) ordering of quality characteristics for inspection. The model considers components with several characteristics to be inspected. Failure to meet the quality requirements of any one characteristic results in the rejection of the component. Taking into consideration all three costs referred to above, a mathematical expression for expected total cost per accepted component is obtained. Also, an expression is developed for finding the optimal sequence of characteristic inspection. Finally, a computational procedure is outlined to determine the optimal sequence of characteristic inspection and the optimal number of inspections using the two expressions stated above.     

Antimicrobial activity of silica coated silicon nano-tubes (SCSNT) and silica coated silicon nano-particles (SCSNP) synthesized by gas phase condensation

Silica-coated, silicon nanotubes (SCSNTs) and silica-coated, silicon nanoparticles (SCSNPs) have been synthesized by catalyst-free single-step gas phase condensation using the arc plasma process. Transmission electron microscopy and scanning tunneling microscopy showed that SCSNTs exhibited a wall thickness of less than 1 nm, with an average diameter of 14 nm and a length of several 100 nm. Both nano-structures had a high specific surface area. The present study has demonstrated cheaper, resistance-free and effective antibacterial activity in silica-coated silicon nano-structures, each for two Gram-positive and Gram-negative bacteria. The minimum inhibitory concentration (MIC) was estimated, using the optical densitometric technique, and by determining colony-forming units. The MIC was found to range in the order of micrograms, which is comparable to the reported MIC of metal oxides for these bacteria. SCSNTs were found to be more effective in limiting the growth of multidrug-resistant Staphylococcus aureus over SCSNPs at 10 μg/ml (IC 50 = 100 μg/ml).