Extent of Yield Gap and Constraints in Different Adoption Level of Chickpea in Madhya Pradesh

The study is formulated to assess the extent of yield gap at different adoption levels and identify the constraints responsible for the existing yield gap in chickpea production technology of Madhya Pradesh. The study was carried out in the Khargone district with 60 sample farmers form 5 villages in the state. The study reveals that adoption of improved production technology has lagged far behind. The chickpea productivity could be increased in the area through the judicious use of improved inputs and practices for that purpose. On the other hand, the proper use of improved technology and improved practices of chickpea production need to be demonstrated. Hence, farmers should given priority to use their resources on the basis of economic viability with proper management of their farm so that emphasis should be given on resources availability and their economic use. Economic study to be conducted suggests optimal cropping pattern and practices including recommendations for varying quantities of fertilizer applications under varying price and output situations

Intelligent Recommendation System for Higher Education

Education domain is very vast and the data is increasing every day. Extracting information from this data requires various data mining techniques. Educational data mining combines various methods of data mining, machine learning and statistics; which are appropriate for the unique data that comes from educational sector. Most of the education recommendation systems available help students to choose particular stream for graduate education after successful schooling or to choose particular career options after graduation. Counseling students during their course of graduate education will help him to comprehend subjects in better ways that will results in enhancing his understanding about subjects. This is possible by knowing the ability of student in learning subjects in past semesters and also mining the similar learning patterns from the past databases. Most educational systems allow students to plan out their subjects (particularly electives) during the beginning of the semester or course. The student is not fully aware about what subjects are good for his career, in which field he is interested in, or how would he perform. Recommending students to choose electives by considering his learning ability, his area of interest, extra-curricular activities and his performance in prerequisites would facilitate students to give a better performance and avoid their risk of failure. This would allow student to specialize in his domain of interest. This early prediction benefits the students to take necessary steps in advance to avoid poor performance and to improve their academic scores. To develop this system, various algorithms and recommendation techniques have to be applied. This paper reviews various data mining and machine learning approaches which are used in educational field and how it can be implemented

Modeling of single mode optical fiber having a complicated refractive index profile by using modified scalar finite element method

A numerical method based on modified scalar finite element method (SC-FEM) is presented and programmed on MATLAB platform for optical fiber modeling purpose. We have estimated the dispersion graph, mode cut off condition, and group delay and waveguide dispersion for highly complicated chirped type refractive index profile fiber. The convergence study of our FEM formulation is carried out with respect to the number of division in core. It has been found that the numerical error becomes less than 2 % when the number of divisions in the core is more then 30. To predict the accurate waveguide dispersion characteristics, we need to compute expression (d^2 (Vb))/(dV^2 ) numerically by the FEM method. For that the normalized propagation constant b (in terms of β) should be an accurate enough up to around 6 decimal points. To achieve this target, we have used 1 million sampling points in our FEM simulations. Further to validate our results we have derived the higher order polynomial expression for each case. Comparison with other methods in calculation of normalized propagation constant is found to be satisfactory. In traditional FEM analysis a spurious solution is generated because the functional does not satisfy the boundary conditions in the original waveguide problem, However in our analysis a new term that compensate the missing boundary condition has been added in the functional to eliminate the spurious solutions. Our study will be useful for the analysis of optical fiber having varying refractive index profile

Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection

Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide-receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized

Sediment Transport Model for a Surface Irrigation System

Controlling irrigation-induced soil erosion is one of the important issues of irrigation management and surface water impairment. Irrigation models are useful in managing the irrigation and the associated ill effects on agricultural environment. In this paper, a physically based surface irrigation model was developed to predict sediment transport in irrigated furrows by integrating an irrigation hydraulic model with a quasi-steady state sediment transport model to predict sediment load in furrow irrigation. The irrigation hydraulic model simulates flow in a furrow irrigation system using the analytically solved zero-inertial overland flow equations and 1D-Green-Ampt, 2D-Fok, and Kostiakov-Lewis infiltration equations. Performance of the sediment transport model was evaluated for bare and cropped furrow fields. The results indicated that the sediment transport model can predict the initial sediment rate adequately, but the simulated sediment rate was less accurate for the later part of the irrigation event. Sensitivity analysis of the parameters of the sediment module showed that the soil erodibility coefficient was the most influential parameter for determining sediment load in furrow irrigation. The developed modeling tool can be used as a water management tool for mitigating sediment loss from the surface irrigated fields

Fingerprints Indicating Superior Properties of Internal Interfaces in Cu(In,Ga)Se2 Thin-Film Solar Cells

Growth of Cu(In,Ga)Se2 (CIGS) absorbers under Cu-poor conditions gives rise to incorporation of numerous defects into the bulk, whereas the same absorber grown under Cu-rich conditions leads to a stoichiometric bulk with minimum defects. This suggests that CIGS absorbers grown under Cu-rich conditions are more suitable for solar cell applications. However, the CIGS solar cell devices with record efficiencies have all been fabricated under Cu-poor conditions, despite the expectations. Therefore, in the present work, both Cu-poor and Cu-rich CIGS cells are investigated, and the superior properties of the internal interfaces of the Cu-poor CIGS cells, such as the p-n junction and grain boundaries, which always makes them the record-efficiency devices, are shown. More precisely, by employing a correlative microscopy approach, the typical fingerprints for superior properties of internal interfaces necessary for maintaining a lower recombination activity in the cell is discovered. These are a Cu-depleted and Cd-enriched CIGS absorber surface, near the p-n junction, as well as a negative Cu factor (∆β) and high Na content (>1.5 at%) at the grain boundaries. Thus, this work provides key factors governing the device performance (efficiency), which can be considered in the design of next-generation solar cells

Smooth deuterated cellulose films for the visualisation of adsorbed bio-macromolecules.

Novel thin and smooth deuterated cellulose films were synthesised to visualize adsorbed bio-macromolecules using contrast variation neutron reflectivity (NR) measurements. Incorporation of varying degrees of deuteration into cellulose was achieved by growing Gluconacetobacter xylinus in deuterated glycerol as carbon source dissolved in growth media containing D2O. The derivative of deuterated cellulose was prepared by trimethylsilylation(TMS) in ionic liquid(1-butyl-3-methylimidazolium chloride). The TMS derivative was dissolved in toluene for thin film preparation by spin-coating. The resulting film was regenerated into deuterated cellulose by exposure to acidic vapour. A common enzyme, horseradish peroxidase (HRP), was adsorbed from solution onto the deuterated cellulose films and visualized by NR. The scattering length density contrast of the deuterated cellulose enabled accurate visualization and quantification of the adsorbed HRP, which would have been impossible to achieve with non-deuterated cellulose. The procedure described enables preparing deuterated cellulose films that allows differentiation of cellulose and non-deuterated bio-macromolecules using NR