Variety Of Kernels Research Articles

Effect of solvent on the extraction of phenolic compounds and antioxidant capacity of hazelnut kernel.

Hazelnut kernel phenolic compounds were recovered applying two different extraction approaches, namely ultrasound-assisted solid/liquid extraction (UA-SLE) and solid-phase extraction (SPE). Different solvents were tested evaluating total phenolic compounds and total flavonoids contents together to antioxidant activity. The optimum extraction conditions, in terms of the highest value of total phenolic compounds extracted together to other parameters like simplicity and cost were selected for method validation and individual phenolic compounds analysis. The UA-SLE protocol performed using 0.1 g of defatted sample and 15 mL of extraction solvent (1 mL methanol/1 mL water/8 mL methanol 0.1% formic acid/5 mL acetonitrile) was selected. The analysis of hazelnut kernel individual phenolic compounds was obtained by HPLC coupled with DAD and MS detections. Quantitative analysis was performed using a mixture of six phenolic compounds belonging to phenolic classes' representative of hazelnut. Then, the method was fully validated and the resulting RSD% values for retention time repeatability were below 1%. A good linearity was obtained giving R2 no lower than 0.997.The accuracy of the extraction method was also assessed. Finally, the method was applied to the analysis of phenolic compounds in three different hazelnut kernel varieties observing a similar qualitative profile with differences in the quantity of detected compounds.

Surprise: The classic white seedling 3 mutant in maize lacks plastoquinone-9 but can still make carotenoids.

Surprise: The classic white seedling 3 mutant in maize lacks plastoquinone-9 but can still make carotenoids.

Biodiesel from “Morelos” Rice: Synthesis, Oxidative Stability, and Corrosivity

Rice bran is a by-product of great production worldwide and its use for the synthesis of biodiesel does not affect the food chain and therefore it is an excellent alternative for the production of biofuels with low carbon footprint. In this work, the synthesis of biodiesel was carried out from the raw rice bran oil of a kernel variety called “Morelos rice.” The stability and corrosivity characteristics of biodiesel were determined. Biodiesel stability was determined both under storage conditions and under accelerated oxidation conditions, and its corrosivity was evaluated by electrochemical impedance spectroscopy at 110°C under aerated conditions. The results showed that, due to the high instability of the rice bran, its raw oil had a high content of free fatty acids. The synthesized biodiesel showed excellent stability under storage conditions of up to five months, and its oxidative stability was much higher than that established in international standards. On the other hand, biodiesel showed low corrosivity and this was only significant once oxidative degradation began.

Technical Notes on Volume Averaging in Porous Media I: How to Choose a Spatial Averaging Operator for Periodic and Quasiperiodic Structures

This paper is a first of a series aiming at revisiting technical aspects of the volume averaging theory. Here, we discuss the choice of the spatial averaging operator for periodic and quasiperiodic structures. We show that spatial averaging must be defined in terms of a convolution and analyze the properties of a variety of kernels, with a particular focus on the smoothness of average fields, the ability to attenuate geometrical fluctuations, Taylor series expansions, averaging of periodic fields and resilience to perturbations of periodicity. We conclude with a set of recommendations regarding kernels to use in the volume averaging theory.

Evaluation of some engineering properties of cucumber (Cucumis sativus L.) seeds and kernels based on image processing

In this study, a method based on digital image processing was employed to investigate effect of the moisture content on gravimetrical and frictional properties of the cucumber seeds and kernels. This research indicated that the application of visual machines and the image processing could be a rapid method that enables accurate measurement of the dimensional parameters of two varieties of this product meticulously. The length, width, and thickness of the seeds of Rashid variety ranged from 6.40 to 9.07, 2.91 to 4.21 and 0.65 to1.50mm, respectively; the corresponding value of Negin variety ranged from 6.89 to 9.07, 2.49 to 4.21, and 0.69 to 1.68mm, respectively. Kernel and shell ratios of the Rashid variety were found to be 69.811 and 30.189%, respectively; the corresponding values of the Negin variety were found to be 72.727 and 27.273%, respectively. Despite the bulk densities of the two varieties of cucumber seeds and kernels that decreased with the moisture content, true density and porosity of the two varieties of cucumber seeds and kernels increased. As the moisture content increased from 5.04 to 21.12% (d.b), the angle of the static friction of the seeds of Negin variety increased from 30.39° to 37.18°, 28.83° to 34.99°, 24.37° to 30.04°, and 15.77° to 19.57° for wood, rubber, iron, and galvanized, respectively,; the corresponding value of the Negin variety increased from 21.12° to 27.16°, 24.43° to 31.41°, 19.90° to 25.59° and 14.09° to 18.12° as the moisture content increased from 5.02 to 21.02% (d.b).

LogCA

With the end of Dennard scaling, architects have increasingly turned to special-purpose hardware accelerators to improve the performance and energy efficiency for some applications. Unfortunately, accelerators don't always live up to their expectations and may under-perform in some situations. Understanding the factors which effect the performance of an accelerator is crucial for both architects and programmers early in the design stage. Detailed models can be highly accurate, but often require low-level details which are not available until late in the design cycle. In contrast, simple analytical models can provide useful insights by abstracting away low-level system details. In this paper, we propose LogCA---a high-level performance model for hardware accelerators. LogCA helps both programmers and architects identify performance bounds and design bottlenecks early in the design cycle, and provide insight into which optimizations may alleviate these bottlenecks. We validate our model across a variety of kernels, ranging from sub-linear to super-linear complexities on both on-chip and off-chip accelerators. We also describe the utility of LogCA using two retrospective case studies. First, we discuss the evolution of interface design in SUN/Oracle's encryption accelerators. Second, we discuss the evolution of memory interface design in three different GPU architectures. In both cases, we show that the adopted design optimizations for these machines are similar to LogCA's suggested optimizations. We argue that architects and programmers can use insights from these retrospective studies for improving future designs.

An adaptive Huber method for nonlinear systems of Volterra integral equations with weakly singular kernels and solutions

Numerical methods for solving nonlinear systems of weakly singular Volterra integral equations (VIEs) possessing weakly singular solutions appear almost nonexistent in the literature, except for a few treatments of single first kind Abel equations. To reduce this gap, an extension is presented, of the adaptive Huber method designed for VIEs with singular kernels such as K(t,τ)=(t−τ)−1/2 and K(t,τ)=exp[−λ(t−τ)](t−τ)−1/2 (where λ≥0) and a variety of nonsingular kernels. The method was thus far restricted to bounded solutions having at least two derivatives. Under a number of assumptions specified, the extension applies to solutions Uμ(t) that can be written as sums of singular components cμt−1/2 (with unknown coefficients cμ), and nonsingular components U¯μ(t). In the solution process, factor t−1/2 is handled analytically, whereas cμ and U¯μ(t) are determined numerically. Computational experiments reveal that the extended method determines singular solutions equally well as the unextended method determined nonsingular solutions. The method is intended primarily for a class of VIEs encountered in electroanalytical chemistry, but it can also be of interest to other application areas.

Energy aware synthesis of application kernels through composition of data-paths on a CGRA

Transistor supply voltages no longer scales at the same rate as transistor density and frequency of operation. This has led to the Dark Silicon problem, wherein only a fraction of transistors can operate at maximum frequency and nominal voltage, in order to ensure that the chip functions within the power and thermal budgets. Heterogeneous computing systems which consist of General Purpose Processors (GPPs), Graphic Processing Units (GPUs) and application specific accelerators can provide improved performance while keeping power dissipation at a realistic level. For the accelerators to be effective, they have to be specialized for related classes of application kernels and have to be synthesized from high level specifications. Coarse Grained Reconfigurable has been proposed as accelerators for a variety of application kernels. For CGRAs to be used as accelerators in the Dark Silicon era, a synthesis framework which focuses on optimizing energy efficiency, while achieving the target performance is essential. However, existing compilation techniques for CGRAs focuses on optimizing only for performance, and any reduction in energy is just a side-effect. In this paper we explore synthesizing application kernels expressed as functions, on a coarse grained composable reconfigurable array (CGCRA). The proposed reconfigurable array comprises HyperCells, which are reconfigurable macro-cells that facilitate modeling power and performance in terms of easily measurable parameters. The proposed synthesis approach takes kernels expressed in a functional language, applies a sequence of well known program transformations, explores trade-offs between throughput and energy using the power and performance models, and realizes the kernels on the CGCRA. This approach when used to map a set of signal processing and linear algebra kernels achieves resource utilization varying from 50% to 80%.

Implementation of the maximum entropy method for analytic continuation

We present Maxent, a tool for performing analytic continuation of spectral functions using the maximum entropy method. The code operates on discrete imaginary axis datasets (values with uncertainties) and transforms this input to the real axis. The code works for imaginary time and Matsubara frequency data and implements the ‘Legendre’ representation of finite temperature Green’s functions. It implements a variety of kernels, default models, and grids for continuing bosonic, fermionic, anomalous, and other data. Our implementation is licensed under GPLv3 and extensively documented. This paper shows the use of the programs in detail. Program summaryProgram Title: maxentProgram Filesdoi:http://dx.doi.org/10.17632/rf3p4psdhs.1Licensing provisions: GPLv3Programming language: C++Nature of problem: The analytic continuation of imaginary axis correlation functions to real frequency/time variables is an ill-posed problem which has an infinite number of solutions.Solution method: The maximum entropy method obtains a possible solution that maximizes entropy, enforces sum rules, and otherwise produces ‘smooth’ curves. Our implementation allows for input in Matsubara frequencies, imaginary time, or a Legendre expansion. It implements a range of bosonic, fermionic and generalized kernels for normal and anomalous Green’s functions, self-energies, and two-particle response functions.External routines/libraries: ALPSCore [1][2], GSL, HDF5 [1]B. Bauer, et al., The ALPS project release 2.0: open source software for strongly correlated systems, J. Stat. Mech. Theor. Exp. 2011 (05) (2011) P05001. arXiv:1101.2646, doi:10.1088/17425468/2011/ 05/P05001.[2]A. Gaenko, E. Gull, A.E. Antipov, L. Gamper, G. Carcassi, J. Paki, R. Levy, M. Dolfi, J. Greitemann, J.P.F. LeBlanc, Alpscore: Version 0.5.4doi: 10.5281/zenodo.50203.

Fast and Accurate Evaluation of Double Surface Integrals in Time-Domain Integral Equation Formulations

A novel integration approach is developed for efficiently evaluating double surface integrals in time-domain integral equation formulations. The approach mainly consists of an angular integration scheme for inner 2-D integrals and a modified outer integration scheme. The approach proposed can handle the singularity and near-hypersingularity of the 4-D integrals, and is sufficiently general for arbitrary types of basis functions over planar domains. As several numerical results will demonstrate, the proposed approach has high accuracy and rapid convergence rate for a variety of integral kernels.

Physical properties and mathematical modeling of melon (Cucumis melo L.) seeds and kernels

In the present research, some physical properties of Somsori and Varamin varieties of melon seeds and kernels were studied; three principal dimensions (length, width and thickness) of melon seeds and kernels were measured using image processing technique. Results indicated that mass of the Somsori and Varamin varieties seeds was equal to 0.043 and 0.052g, respectively. The corresponding value for melon kernels was found to be 0.031 and 0.036, respectively. True density of the Somsori and Varamin varieties seeds was equal to 1182.612 and 1132.058kgm−3, respectively. The corresponding value for melon kernels was found to be 1479.731 and 1535.911kgm−3, respectively. Results showed that with increasing volume of container from 500mL to 600mL bulk density of the seeds increased. But with increasing volume of container from 600mL to 1500mL, bulk density of the seeds decreased. Also with increasing volume of container from 500mL to 1000mL bulk density of the kernels increased. But with increasing volume of container from 1000mL to 1500mL, bulk density of the kernels decreased. Values of coefficient of friction of seeds and kernels on rubber surface were more than the iron, galvanized and plywood surfaces, but values of coefficient of friction of seeds and kernels on galvanized surface were less the other surfaces. Comparison between three methods of measuring angle of repose showed that values based on pouring method and filling method were more and less than the other methods, respectively.

Feasibility of detecting Aflatoxin B1 in single maize kernels using hyperspectral imaging

The feasibility of detecting Aflatoxin B1 (AFB1) in single maize kernel inoculated with Aspergillus flavus conidia in the field, as well as its spatial distribution in the kernels, was assessed using near-infrared hyperspectral imaging (HSI) technique. Firstly, an image mask was applied to a pixel-based image mosaic to remove background and shading. Secondly, bad lines in spectra imaging caused by inherent defects of Mercury Cadmium Telluride (MCT) detector were removed through an interactive analysis based on principal component analysis (PCA). Then a PCA procedure was carried out again on the cleaned image, key wavelengths such as 1729 and 2344nm were shown clearly from the loading line plot of the seventh principal component (PC7). And the pixel of AFB1 extracted from the 5-dimensional scatter plot space formed by five principal components (PCs) from PC4 to PC8 (especially PC7 and PC5) were taken as the input of the spectral angle mapper (SAM) classifier, accuracies of the three varieties of kernels reached 96.15%, 80%, and 82.61% respectively if kernels containing either high (⩾100ppb) or low (<10ppb) levels of aflatoxin. A slightly better test result could be got if the kernels placed with different germ orientation. Finally, the repeatability was verified using the fourth variety of kernels.

Penetration of juice into rice through vacuum drying

Vacuum drying was employed to penetrate rice with juice. Red beetroot juice, good source of color and functional compounds, was used. After mixing with beetroot juice and vacuum drying, cracks were formed in the rice kernel surface and the rice kernels were a red-violet color. The degree of visual kernel surface cracking, the fracturability of whole rice kernels, and the DPPH scavenging activity were increased with increasing amounts of added juice. The visual kernel surface cracking was found to be beneficial for deep penetration and juice accumulation within three varieties of rice kernels (Sanpatong 1, Kaow Dok Mali 105, and Chainat 1) and two storage time periods (one month and one year). The final moisture content of the rice kernels after vacuum drying was sufficiently low for good storage quality. No heat treatment is required. The findings imply that other functional liquids/solutions would be also vacuum-impregnated in rice grains. Functional properties of rice could be effectively improved with a vacuum drying technique.

On Bayesian Adaptive Video Super Resolution

Although multiframe super resolution has been extensively studied in past decades, super resolving real-world video sequences still remains challenging. In existing systems, either the motion models are oversimplified or important factors such as blur kernel and noise level are assumed to be known. Such models cannot capture the intrinsic characteristics that may differ from one sequence to another. In this paper, we propose a Bayesian approach to adaptive video super resolution via simultaneously estimating underlying motion, blur kernel, and noise level while reconstructing the original high-resolution frames. As a result, our system not only produces very promising super resolution results outperforming the state of the art, but also adapts to a variety of noise levels and blur kernels. To further analyze the effect of noise and blur kernel, we perform a two-step analysis using the Cramer-Rao bounds. We study how blur kernel and noise influence motion estimation with aliasing signals, how noise affects super resolution with perfect motion, and finally how blur kernel and noise influence super resolution with unknown motion. Our analysis results confirm empirical observations, in particular that an intermediate size blur kernel achieves the optimal image reconstruction results.

Study on Spectrum Estimation in Biophoton Emission Signal Analysis of Wheat Varieties

The photon emission signal in visible range (380 nm–630 nm) was measured from various wheat kernels by means of a low noise photomultiplier system. To study the features of the photon emission signal, the spectrum estimation method of the photon emission signal is described for the first time. The biophoton emission signal, belonging to four varieties of wheat, is analyzed in time domain and frequency domain. It shows that the intensity of the biophoton emission signal for four varieties of wheat kernels is relatively weak and has dramatic changes over time. Mean and mean square value are obviously different in four varieties; the range was, respectively, 3.7837 and 74.8819. The difference of variance is not significant. The range is 1.1764. The results of power spectrum estimation deduced that the biophoton emission signal is a low frequency signal, and its power spectrum is mostly distributed in the frequency less than 0.1 Hz. Then three parameters, which are spectral edge frequency, spectral gravity frequency, and power spectral entropy, are adopted to explain the features of the kernels’ spontaneous biophoton emission signal. It shows that the parameters of the spontaneous biophoton emission signal for different varieties of wheat are similar.

Automatic Feature Selection via Weighted Kernels and Regularization

Selecting important features in nonlinear kernel spaces is a difficult challenge in both classification and regression problems. This article proposes to achieve feature selection by optimizing a simple criterion: a feature-regularized loss function. Features within the kernel are weighted, and a lasso penalty is placed on these weights to encourage sparsity. This feature-regularized loss function is minimized by estimating the weights in conjunction with the coefficients of the original classification or regression problem, thereby automatically procuring a subset of important features. The algorithm, KerNel Iterative Feature Extraction (KNIFE), is applicable to a wide variety of kernels and high-dimensional kernel problems. In addition, a modification of KNIFE gives a computationally attractive method for graphically depicting nonlinear relationships between features by estimating their feature weights over a range of regularization parameters. The utility of KNIFE in selecting features through simulations and examples for both kernel regression and support vector machines is demonstrated. Feature path realizations also give graphical representations of important features and the nonlinear relationships among variables. Supplementary materials with computer code and an appendix on convergence analysis are available online.

Movimiento de polen entre maíces nativos de Yucatán y mantenimiento de diversidad genética

En Yucatán, México, el cultivo de diferentes poblaciones nativas de maíz en el sistema milpa favorece el intercambio de polen. Para evaluar la relación entre el flujo de polen y la dinámica de diversidad genética en 2005 y 2006, una población de grano blanco y otra amarilla de tipo Xmejen-nal y Xnuc-nal, se asociaron con calabaza. La variedad de grano amarillo fue sembrada alrededor del blanco. Se cosecharon 540 mazorcas en 8 direcciones, de la periferia al centro, el porcentaje de grano amarillo en la variedad blanca se usó como indicador de la tasa de cruzamiento. Para cada dirección se realizaron análisis de regresión simple entre la distancia y el porcentaje de granos amarillos. Los mayores porcentajes de cruzamiento en los tipos Xmejen-nal (44 %) y Xnuc-nal (42 %) se obtuvieron en dirección noreste-suroeste en 2005; y dirección sureste-noroeste en Xmejen-nal (37 %) y Xnuc-nal (41 %) en 2006. La dirección e intensidad del viento dominante determinaron las trayectorias del polen y la tasa de cruzamiento disminuyó con la distancia a la fuente polen. El intercambio genético es promovido por el manejo y distribución de los genotipos en tiempo y espacio, y el flujo génico entre poblaciones promueve la diversidad intrapoblacional

Effect of Electrohydrodynamic and Batch Drying on Rice Fissuring

The effects of high-voltage electrostatic field (10 kV), batch drying (45°C), and natural air-drying (26°C) on the impact strength of a brown rice kernel (Oryza Sativa L.) variety of Khazar were investigated under three levels of kinetic impact loading (10, 23, and 37 mJ) with 10 replications. Results showed that the effects of kinetic impact loading on the breakage susceptibility index (BSI) of artificially dried rice grains were significant at 1% confidence level. With increasing kinetic impact loading, the average value of BSI increased. The sound brown rice grains became stronger in natural air-drying as the drying duration increased at low drying temperatures. High-voltage electrostatic field and batch drying considerably increased the rate of breakage susceptibility but the EHD drying was inherently energy efficient with a low surface drying temperature.

A coagulation–disintegration model of Oort–Hulst cluster-formation

We propose and analyse a model for the collision of highly energetic particles in which collisions cause the complete fragmentation of the particles into dust and in which particles nucleate and grow through the accretion of dust. This is inspired by the work of Oort and van Hulst. We analyse a variety of aggregation and disintegration kernels, using asymptotic techniques to illustrate the form of solutions, and find steady states and self-similar behaviour.

SNP identification and allelic-specific PCR markers development for TaGW2, a gene linked to wheat kernel weight

TaGW2, an orthologous gene of rice OsGW2, has been associated with kernel width and weight of bread wheat (Triticum aestivum). Difference in TaGW2 coding sequence was not found among different wheat varieties in previous researches. In this study, we found eight exons and seven introns in TaGW2 with a full-length cDNA sequence of 1,275 bp, which contains a conserved function domain and seven splice sites that shared homology with rice OsGW2. A single T-base insertion in the eighth exon of TaGW2 on chromosome 6A was detected in a large-kernel wheat variety, Lankaodali. This insertion mutation reduces the coding protein sequence from normal 424 amino acids (~47.2 kDa) to 328 amino acids (~37.1 kDa) by truncating 96 amino acids. The result was validated by identifying histidine-tagged TaGW2 proteins encoded by both alleles of the mutant and the wild types in SDS-PAGE. Allele-specific PCR markers were developed based on the single nucleotide polymorphism (SNP) site. The SNP markers were genotyped for an F(2) segregation population from the cross of Lankaodali × Chinese Spring. Seed traits of F(2:3) families were evaluated in three different environments. The association analysis indicated that F(2:3) families with the mutated TaGW2 allele significantly increased kernel width (KW) and thousand-kernel weight (TKW), and slightly improved kernel length (KL). Using the SNP markers, another two varieties harbored the mutated TaGW2 allele were successfully identified from 22 additional wheat varieties, and they both have large KW and TKW. Cloning and sequencing of the gene further confirmed the functions of the mutated allele of TaGW2 in the two large kernel varieties. The results suggested that TaGW2 may negatively regulate kernel size variation, which shares the same function as OsGW2 in rice. The successful development of SNP markers provides a useful tool for improving kernel yield in wheat.