To find out a simple and efficient equation to estimate maize ear grain weight on farm (in situ), twenty three maize crosses along with two synthetics were grown in the field. On the experimental farm of the Dept. of Field Crop Sci., College of Agric., Univ. of Baghdad, seeds of twenty five maize genotypes were grown in the fall season of 2013 with three replicates. At dough stage of the kernels, five naked ears of each experimental units were measured for length and maximum diameter. This will sum up 125 ears of the trial. The volumes of ears were calculated as cylinder (length× r2× 3.1416). Grain weight of all ears were determined after harvesting and drying to 15% grain moisture. A constant was calculated by dividing ear grain weight by each ear volume. Estimated ear grain weights were tested against observed by applying correlation coefficient and it was found to be positive and highly significant (r= 0.998**). The observed and estimated values of ear grain weights were tested by t-test. The two means of observed and estimated ear grain weights were fit to 0.89 probability of t-value. The final equation to estimate ear grain weight in situ is= r2× L× 0.94, where r is radius of ear and L is ear length. However, in case of super hybrids of high ear fertility and kernel filling, estimated ear grain weight will be= r2× L.
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Many purposes require communicating audio files between the users using different applications of social media. The security level of these applications is limited; at the same time many audio files are secured and must be accessed by authorized persons only, while, most present works attempt to hide single audio file in certain cover media. In this paper, a new approach of hiding three audio signals with unequal sizes in single color digital image has been proposed using the frequencies transform of this image. In the proposed approach, the Fast Fourier Transform was adopted where each audio signal is embedded in specific region with high frequencies in the frequency spectrum of the cover image to sa
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Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.
In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe
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Context and its influence in direction of reference by Abi Hussein Al Basri
The gas chromatography (GC) method in analytical chemistry is a quick and accurate method to detect volatile components like ethanol. A method for determining volatile components known as Headspace chromatography (HS-GC) was developed along with an internal standard method (ISM) to identify ethanol in fermented broth in the laboratory. The aim of this research is determining the concentration of ethanol in fermented broth using capillary column (ZB-1). This method can analyze ethanol concentrations in the fermented medium broth ranging from 10 to 200 g/L. The validation of this method was done in order to obtain the results to be of high precision and the significant, precision was represented as the relative standard deviation (RSD) which
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This study has applied the theoretical framework of conceptual metaphor theory to the analysis of the source and target domains of metaphors that are used in two English nineteenth century sonnets, both written by contemporaneous female poets. The quantitative and qualitative results of the textual analysis have clearly revealed that Elizabeth Barrett Browning’s sonnet 23 centres around the conceptual mapping of the journey of love and life with that of possession. In contrast, Christina Rossetti’s sonnet Remember tackles the central conceptual mapping of death as a journey in relation to its further experiential connections. In addition, the application of conceptual metaphor theory in identifying the frequencies and densities of metap
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The haplotype association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease.Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls.It starts with inferring haplotypes from genotypes followed by a haplotype co-classification and marginal screening for disease-associated haplotypes.Unfortunately,phasing uncertainty may have a strong effects on the haplotype co-classification and therefore on the accuracy of predicting risk haplotypes.Here,to address the issue,we propose an alternative approach:In Stage 1,we select potential risk genotypes inste
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