Adsorption of Cationic Surface Active Agents at Barium Sulphate/Solution Interface

486-49

Conductance of Tetraalkylammonium Bromides in Formamide- Water Mixtures at 25ᵒ*

1015-101

Morphological And Molecular Characterization Of Eggplant Lines For Resistant To Phomopsis Blight And Fruit Rot

The F4 lines of eggplant derived from the crosses of Dohazari G x BAU Begun-1 and Laffa S x BAU Begun-1 were evaluated for resistance to phomopsis blight and fruit rot under confined field conditions. The inoculated plants exhibited differential disease reactions. Among the parents, BAU Begun-1 was resistant whereas Dohazari G and Laffa S were susceptible to Phomopsis vexans. All the phenotypes of F4 progenies showed resistant reaction to the disease. Significant differences were observed among the phenotypes in all the yield components. High genotypic and phenotypic coefficient of variation, heritability and per cent genetic advance were estimated for number of fruits per plant, number of secondary branch per plant, fruit length and fruit breadth. Significant positive correlation was observed between yield contributing characters. Random amplified polymorphic DNA technique was used for assessing genetic variation and relationship among parent cultivars and their F4 progenies of eggplant. Amplification with five decamer primers generated 69.0% polymorphic bands. Comparatively higher genetic distance was observed between Laffa S vs. green globose (Dohazari G x BAU Begun-1). The dendogram constructed from Neis genetic distance produced two main clusters, the parent cultivars and six F4 lines formed cluster 1 and one line in cluster 2. F4 lines of the tested phenotypes showed similar disease reaction and divided into same sub cluster. The parent cultivars were different in case of disease reaction and finally divided into two groups, susceptible cultivars Laffa S and Dohazari G belonged to group 1 and the resistant parent BAU Begun-1 formed another group. Int. J. Agril. Res. Innov. & Tech. 3 (1): 35-46, June, 2013 DOI: http://dx.doi.org/10.3329/ijarit.v3i1.1605

Two quantum analogues of Fisher information from a large deviation viewpoint of quantum estimation

We discuss two quantum analogues of Fisher information, symmetric logarithmic derivative (SLD) Fisher information and Kubo-Mori-Bogoljubov (KMB) Fisher information from a large deviation viewpoint of quantum estimation and prove that the former gives the true bound and the latter gives the bound of consistent superefficient estimators. In another comparison, it is shown that the difference between them is characterized by the change of the order of limits.Comment: LaTeX with iopart.cls, iopart12.clo, iopams.st

Microfinance Institutions: Instrumental for Promoting Financial Inclusion

This opinion paper provides a general overview of microfinance / microcredit which is considered one the major program to minimize the poverty, women empowerment and to socioeconomically inclusive society. There are number of success and failure stories mostly from Africa, Asia, and Latin America; however, the microfinance is global agenda of contemporary world. Based secondary sources, and own experience, the paper provides the general overview of microcredit, its success, the obstacles of microfinance and outlines very brief cases of Nepal and Bangladesh. And finally, paper provides a brief recommendation on how microcredit can be successful especially to the developing world

Importance of composition and hygroscopicity of BC particles to the effect of BC mitigation on cloud properties: Application to California conditions

Black carbon (BC) has many effects on climate including the direct effect on atmospheric absorption, indirect and semi-direct effects on clouds, snow effects, and others. While most of these are positive (warming), the first indirect effect is negative and quantifying its magnitude in addition to other BC feedbacks is important for supporting policies that mitigate BC. We use the detailed aerosol chemistry parcel model of Russell and Seinfeld (1998), observationally constrained by initial measured aerosol concentrations from five California sites, to provide simulated cloud drop number (CDN) concentrations against which two GCM calculations – one run at the global scale and one nested from the global-to-regional scale are compared. The GCM results reflect the combined effects of their emission inventories, advection schemes, and cloud parameterizations. BC-type particles contributed between 16 and 20% of cloud droplets at all sites even in the presence of more hygroscopic particles. While this chemically detailed parcel model result is based on simplified cloud dynamics and does not consider semi-direct or cloud absorption effects, the cloud drop number concentrations are similar to the simulations of both Chen et al. (2010b) and Jacobson (2010) for the average cloud conditions in California. Reducing BC particle concentration by 50% decreased the cloud droplet concentration by between 6% and 9% resulting in the formation of fewer, larger cloud droplets that correspond to a lower cloud albedo. This trend is similar to Chen et al. (2010b) and Jacobson (2010) when BC particles were modeled as hygroscopic. This reduction in CDN in California due to the decrease in activated BC particles supports the concern raised by Chen et al. (2010a) that the cloud albedo effect of BC particles has a cooling effect that partially offsets the direct forcing reduction if other warming effects of BC on clouds are unchanged. These results suggests that for regions like the California sites studied here, where BC mitigation targets fossil fuel sources, a critical aspect of the modeled reduction is the chemical composition and associated hygroscopicity of the BC particles removed as well as their relative contribution to the atmospheric particle concentrations

Machine Learning and Grounded Theory: New Opportunities for Mixed-Design Research

In this emerging research forum paper, we propose a novel framework for mixed-design research by integrating machine learning (ML) with grounded theory (GT). Contrary to existing belief that ML can only be used for prediction and not for explaining a phenomenon, in this paper, we illustrate that ML and GT complement each other’s strengths and weaknesses and can be integrated through mixed design research for theory building. We also propose a framework and guidelines to integrate ML in GT, with an example from an ongoing research project. This paper not only attempts to addresses the call for methodologies to employ ML techniques in social sciences research but also provides clear guidelines for executing such empirical researc