Single Top and Higgs Production in e−pe^- p collisions

In this proceedings some studies on the prospects of single top production at the Large Hadron Electron Collider (LHeC) and double Higgs production at the Future Circular Hadron Electron Collider (FCC-he) shall be presented. In particular, we investigated the $tbW$ couplings via single top quark production with the introduction of possible anomalous Lorentz structures, and measured the sensitivity of the Higgs self coupling ($\lambda$) through double Higgs production. The studies are performed with 60 GeV electrons colliding with 7 (50) TeV protons for the LHeC (FCC-he). For the single top studies a parton level study has been performed, and we find the sensitivity of the anomalous coupling at a 95\% C.L, considering 10-1\% systematic errors. The double Higgs production has been studied with speculated detector parameters and the sensitivity of $\lambda$ estimated via the cross section study around the Standard Model Higgs self coupling strength ($\lambda_{SM}$) considering 5\% systematic error in signal and backgrounds. Effects of non-standard CP-even and CP-odd couplings for $hhh$, $hWW$ and $hhWW$ vertices have been studied and constrained at 95\% C.L.Comment: 7 pages, 2 figures, submitted to the proceedings of the HEPP 2015 worksho

Eigenvalue monotonicity of qq-Laplacians of trees along a poset

Let $T$ be a tree on $n$ vertices with $q$-Laplacian $L_{T}^{q}$. Let $GTS_n$ be the generalized tree shift poset on the set of unlabelled trees with $n$ vertices. We prove that for all $q \in R$, going up on $GTS_n$ has the following effect: the spectral radius and the second smallest eigenvalue of $L_{T}^{q}$ increase while the smallest eigenvalue of $L_{T}^{q}$ decreases. These generalize known results for eigenvalues of the Laplacian. As a corollary, we obtain consequences about the eigenvalues of $q,t$-Laplacians and exponential distance matrices of trees

Economic Implications of Peste des petits ruminants (PPR) Disease in Sheep and Goats: A Sample Analysis of District Pune, Maharastra

The paper has reported a cross-sectional sample survey conducted across six villages severely affected by peste des petits ruminants disease to assess the nature and extent of loss in small ruminants. The study is based on the data pertaining to disease incidence, production losses, costs incurred and impact on farm productivity collected though personal interview method. The incidence and mortality rate have been found slightly higher in sheep than goats. The total losses due to disease have been found to range between Rs 918 in sheep to Rs 945 in goats. Reduction in the market value of animals has been recorded as the major loss component as appearance of the animal changes drastically after the illness, costing Rs. 404 (44%) in sheep and Rs 408 (43%) in goat. It is followed by losses in production yield. Expenditure on medicine and infertility has been found to cause more than 80 per cent of the total cost, followed by veterinary and labour services. The study has suggested that timely vaccination could be the best and low-cost preventive measure to control such deadly disease outbreaks.Agricultural and Food Policy,

Effort estimation for object-oriented system using artificial intelligence techniques

Software effort estimation is a vital task in software engineering. The importance of effort estimation becomes critical during early stage of the software life cycle when the details of the software have not been revealed yet. The effort involved in developing a software product plays an important role in determining the success or failure. With the proliferation of software projects and the heterogeneity in their genre, there is a need for efficient effort estimation techniques to enable the project managers to perform proper planning of the Software Life Cycle activates. In the context of developing software using object-oriented methodologies, traditional methods and metrics were extended to help managers in effort estimation activity. There are basically some points approach, which are available for software effort estimation such as Function Point, Use Case Point, Class Point, Object Point, etc. In this thesis, the main goal is to estimate the effort of various software projects using Class Point Approach. The parameters are optimized using various artificial intelligence (AI) techniques such as Multi-Layer Perceptron (MLP), K-Nearest Neighbor Regression (KNN) and Radial Basis Function Network(RBFN), fuzzy logic with various clustering algorithms such as the Fuzzy C-means (FCM) algorithm, K-means clustering algorithm and Subtractive Clustering (SC) algorithm, such as to achieve better accuracy. Furthermore, a comparative analysis of software effort estimation using these various AI techniques has been provided. By estimating the software projects accurately, we can have software with acceptable quality within budget and on planned schedules