Optimum Power Randomization for the Minimization of Outage Probability

Cataloged from PDF version of article.The optimum power randomization problem is studied to minimize outage probability in flat block-fading Gaussian channels under an average transmit power constraint and in the presence of channel distribution information at the transmitter. When the probability density function of the channel power gain is continuously differentiable with a finite second moment, it is shown that the outage probability curve is a nonincreasing function of the normalized transmit power with at least one inflection point and the total number of inflection points is odd. Based on this result, it is proved that the optimum power transmission strategy involves randomization between at most two power levels. In the case of a single inflection point, the optimum strategy simplifies to on-off signaling for weak transmitters. Through analytical and numerical discussions, it is shown that the proposed framework can be adapted to a wide variety of scenarios including log-normal shadowing, diversity combining over Rayleigh fading channels, Nakagami-m fading, spectrum sharing, and jamming applications. We also show that power randomization does not necessarily improve the outage performance when the finite second moment assumption is violated by the power distribution of the fading. © 2013 IEEE

Performance of Indian crossbred wool on khadi spinning system

HP Crossbred, JK Crossbred and JK Merino yarns have been spun on the New Model Charkha (NMC) spinning system to find out the suitability of Indian crossbred wool in Khadi sector. These crossbred wools produced in the north temperature region of India have been spun into medium quality yarn linear density of 42 tex. The pure crossbred wool yarns have higher U%, imperfections and hairiness index; and lower tenacity, elongation-at-break and coefficient of friction. The mixing of Australian merino wool with JK crossbred wool significantly improves yarn performance in terms of fineness (31 tex), evenness (U%), imperfections and hairiness index. The tenacity, elongation-at-break and coefficient of friction of mixed yarns increase significantly by mixing of Australian merino wool with JK crossbred wool. These findings will help in increasing the utilization of crossbred wool and reducing the costing of end products

Performance of Indian crossbred wool on khadi spinning system

127-132HP Crossbred, JK Crossbred and JK Merino yarns have been spun on the New Model Charkha (NMC) spinning system to find out the suitability of Indian crossbred wool in Khadi sector. These crossbred wools produced in the north temperature region of India have been spun into medium quality yarn linear density of 42 tex. The pure crossbred wool yarns have higher U%, imperfections and hairiness index; and lower tenacity, elongation-at-break and coefficient of friction. The mixing of Australian merino wool with JK crossbred wool significantly improves yarn performance in terms of fineness (31 tex), evenness (U%), imperfections and hairiness index. The tenacity, elongation-at-break and coefficient of friction of mixed yarns increase significantly by mixing of Australian merino wool with JK crossbred wool. These findings will help in increasing the utilization of crossbred wool and reducing the costing of end products

Response Functions to Critical Shocks in Social Sciences: An Empirical and Numerical Study

We show that, provided one focuses on properly selected episodes, one can apply to the social sciences the same observational strategy that has proved successful in natural sciences such as astrophysics or geodynamics. For instance, in order to probe the cohesion of a policy, one can, in different countries, study the reactions to some huge and sudden exogenous shocks, which we call Dirac shocks. This approach naturally leads to the notion of structural (as opposed or complementary to temporal) forecast. Although structural predictions are by far the most common way to test theories in the natural sciences, they have been much less used in the social sciences. The Dirac shock approach opens the way to testing structural predictions in the social sciences. The examples reported here suggest that critical events are able to reveal pre-existing ``cracks'' because they probe the social cohesion which is an indicator and predictor of future evolution of the system, and in some cases foreshadows a bifurcation. We complement our empirical work with numerical simulations of the response function (``damage spreading'') to Dirac shocks in the Sznajd model of consensus build-up. We quantify the slow relaxation of the difference between perturbed and unperturbed systems, the conditions under which the consensus is modified by the shock and the large variability from one realization to another

Development of cost-effective SNP assays for chickpea genome analysis and breeding

A total of 1499 ESTs generated from 26 different Cicer species, available in the public domain at the time of analysis, were used for in silico identification of SNPs using the bioinformatic tools developed at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) (http://hpc.icrisat.org/PBSWeb). Cluster analysis provided a total of 118 clusters, of which 11 clusters contained sequences from more than one Cicer species. Further, these clusters were assembled into 19 contigs and 184 putative SNPs were identified in 15 contigs. However, only 73 SNPs involved restriction enzyme sites for development of the CAPS assays as identified through the SNP2CAPs program. Primer pairs were designed for only 8 contigs (CL3a, CL3c, CL3d, CL3e, CL4a, CL10, CL20 and CL99) which had SNPs, resulting in putative recognition sites to commonly used restriction enzymes. Results of the demonstrates the utility of Cicer EST resources and the availability of bioinformatics analysis pipelines for the large-scale identification of SNPs on the HPC (High Performance Computer) at ICRISAT and the development of costeffective CAPS assay for SNP genotyping. It is anticipated that the availability of large number of ESTs from more than one genotype of cultivated chickpea (C. arietinum) in the near future will make it possible to develop larger number of SNPs in cultivated chickpea germplasm for genome analysis and breeding application

Molecular markers and genomic resources for disease resistance in peanut-A review

Recent polyploidation of peanut genome and geographical isolation has rendered peanut to be a highly monomorphic species. Due to its narrow genetic base, cultivated peanut has been susceptible to various diseases, causing economic loss to farmers. Availability of only a few disease resistance sources in cultivated peanut has resulted in limited success using the conventional breeding practices. Also, scarcity of markers has been the major limiting factor to precisely identify the disease resistance genomic regions. Recent identification of large number of molecular markers using advanced genomic resources and high throughput sequencing technologies has and will continue to assist in improvement of peanut diversity and breeding. This review gives an update on recent discovery of molecular markers associated with major diseases and the available genomic resources in peanut

Differential physio-biochemical and metabolic responses of peanut (Arachis hypogaea L.) under multiple abiotic stress conditions

The frequency and severity of extreme climatic conditions such as drought, salinity, cold, and heat are increasing due to climate change. Moreover, in the field, plants are affected by multiple abiotic stresses simultaneously or sequentially. Thus, it is imperative to compare the effects of stress combinations on crop plants relative to individual stresses. This study investigated the differential regulation of physio-biochemical and metabolomics parameters in peanut (Arachis hypogaea L.) under individual (salt, drought, cold, and heat) and combined stress treatments using multivariate correlation analysis. The results showed that combined heat, salt, and drought stress compounds the stress effect of individual stresses. Combined stresses that included heat had the highest electrolyte leakage and lowest relative water content. Lipid peroxidation and chlorophyll contents did not significantly change under combined stresses. Biochemical parameters, such as free amino acids, polyphenol, starch, and sugars, significantly changed under combined stresses compared to individual stresses. Free amino acids increased under combined stresses that included heat; starch, sugars, and polyphenols increased under combined stresses that included drought; proline concentration increased under combined stresses that included salt. Metabolomics data that were obtained under different individual and combined stresses can be used to identify molecular phenotypes that are involved in the acclimation response of plants under changing abiotic stress conditions. Peanut metabolomics identified 160 metabolites, including amino acids, sugars, sugar alcohols, organic acids, fatty acids, sugar acids, and other organic compounds. Pathway enrichment analysis revealed that abiotic stresses significantly affected amino acid, amino sugar, and sugar metabolism. The stress treatments affected the metabolites that were associated with the tricarboxylic acid (TCA) and urea cycles and associated amino acid biosynthesis pathway intermediates. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and heatmap analysis identified potential marker metabolites (pinitol, malic acid, and xylopyranose) that were associated with abiotic stress combinations, which could be used in breeding efforts to develop peanut cultivars that are resilient to climate change. The study will also facilitate researchers to explore different stress indicators to identify resistant cultivars for future crop improvement programs