Band filling and interband scattering effects in MgB2_2: C vs Al doping

We argue, based on band structure calculations and Eliashberg theory, that the observed decrease of $T_c$ of Al and C doped MgB$_2$ samples can be understood mainly in terms of a band filling effect due to the electron doping by Al and C. A simple scaling of the electron-phonon coupling constant $\lambda$ by the variation of the density of states as function of electron doping is sufficient to capture the experimentally observed behavior. Further, we also explain the long standing open question of the experimental observation of a nearly constant $\pi$ gap as function of doping by a compensation of the effect of band filling and interband scattering. Both effects together generate a nearly constant $\pi$ gap and shift the merging point of both gaps to higher doping concentrations, resolving the discrepancy between experiment and theoretical predictions based on interband scattering only.Comment: accepted by PR

Pathways towards reverse logistics adoption in Indian educational institutes: a challenging factors analysis

Reverse logistics (RL) has been proven to have a positive effect on addressing the issue of effectively utilizing resources. India has a population of over one billion people with most of it dominated by youth. Developing RL strategies and exposing it to students will encourage them to find ways to manage the limited resources available in our country. This study is focused on identifying the challenges of RL implementation in education institutes in India and finding the inter-relationship among them. The most crucial barrier to RL implementation in educational institutes is also sought in the process. We initially review the RL practices in the Indian sub-continent to examine the challenges of effectively implementing RL. We then identify the challenges of RL based on literature and discussions with experts from the education industry. The experts selected for this study include administrators from schools and universities in Kerala, India (South India). A survey was conducted in two phases. The Fuzzy-DEMATEL technique was applied to determine the inter-relationship between the challenges and obtain the causal diagram. Initially, 45 challenges were identified. Based on responses from experts from phase one of the survey, it was narrowed down to 29 crucial challenges. A pairwise comparison among the challenges was then done by experts in the education field. Finally, on the application of Fuzzy-DEMATEL, a causal diagram was generated to indicate the extent of influence of the RL challenges. Our findings indicate that educational institutions are faced with lack of awareness about reverse logistic, lack of responsibilities about environment, resistance to change, lack of supplies on supplier end, lack of knowledge, and no proper outlet for disposal in managing RL operations in educational institutes. The challenges identified in our study is unique to the Indian sub-continent and provides a result based on the current scenario of RL implementation in Indian educational institutes. The findings from our study indicate a unique perspective of RL implementation challenges. We analyzed 29 challenges to obtain our findings. Furthermore, we use Fuzzy-DEMATEL as our analysis tool to facilitate finding results. We present this as the uniqueness of our study from the available literature

Fuzzy Bio-Inspired K-Nearest Neighbor Techniques for Spatial Data Analysis in Coimbatore Region

In this research work, agricultural Data Mining data are summarized. An improved Soil Data Prediction Model is developed to estimate the above parameters at locations for Coimbatore city. 142 locations were investigated for the development of the model. The model involves multiple regression equation, chi-square test and Bio inspired K-Nearest Neighbor classification. The correlation analysis measures the degree of association between two sets of quantitative data, while regression analysis explains the variation in one variable, based on the variation in one or more of these variables

Impact of Lysinibacillus macroides, a potential plant growth promoting rhizobacteria on growth, yield and nutritional value of tomato Plant (Solanum lycopersicum L. f1 hybrid Sachriya)

Plant growth promoting bacteria enhance the growth in plants by solubilizing insoluble minerals, producing phytohormones and by secreting enzymes that resist pathogen attack. The present study was aimed at identifying the potential of Lysinibacillus macroides isolated from pea plant possessing rich microbial rhizobiome diversity in promoting the growth of tomato plant (Solanum lycopersicum L). Potential of L. macroides in the promotion of S. lycopersicum L. growth by increased shoot length, terminal leaf length and breadth was assessed. Anatomical sectioning of stem and root revealed no varied cellular pattern indicating that the supplemented bioculture is not toxic to S. lycopersicum. Plantlets treated with L. macroides along with organic compost showed an increased total phenol content (17.58±0.4 mg/g) compared to control samples (12.44±0.41 mg/g). Carbohydrate content was noticed to be around 1.3 folds higher in the L. macroides plus compost mixture supplemented slots compared to control sample. Significant increase in shoot length was evident in the L. macroides plus compost supplied slots (23.4±2.7 cm). Plant growth promoting properties might be due to the nitrogen fixing activity of the bacteria which enrich the soil composition along with the nutrients supplied by the organic compost. Rich microbial rhizobiome diversity in pea plant and the usage of L. macroides from a non-conventional source improves the diversity of the available PGPR for agricultural practices. Further research is needed to detect the mechanism of growth promotion and to explore the plant microbe interaction pathway

Improved Soil Data Prediction Model Base Bioinspired K-Nearest Neighbor Techniques for Spatial Data Analysis in Coimbatore Region

In this research paper, agricultural Data Mining data are summarized. An improved Soil Data Prediction Model is developed to estimate the above parameters at locations for Coimbatore city. 142 locations were investigated for the development of the model. The model involves multiple regression equation, chi-square test and Bio inspired k-nearest neighbor classification. The GIS was used to manage the database and to develop thematic maps for depth, N value, free swell, liquid limit, plastic limit, plastic index, percentage gravel, percentage sand and percentage slit and clay. Field and laboratory studies were conducted in four locations and are compared with the predicted values

Upper critical field anisotropy in BaFe2-xCoxAs2 single crystals synthesized without flux

The upper critical field was measured upto 12 T for three BaFe2-xCoxAs2 single crystals with estimated Co concentrations of x = 0.082, x = 0.117 and x = 0.143. HC2 versus temperature was measured from temperature dependent resistivity, for various applied magnetic fields, H || ab and H || c. The [dHC2/dT]T=Tc, normalized with the corresponding TC, decreases with increasing Co content, for both directions. The anisotropy {\gamma} defined as HC2 || ab / HC2 || c shows a distinct increase with Co content, and its temperature dependence shows a peak close to the TC. Magneto transport measurements, in the spin density wave regions, showed significant negative MR for H || ab and positive MR of H || c in the x = 0.082 sample. The implications of these results are discussed.Comment: 12 pages 7 figure