151 research outputs found

    Sub-Weyl strength bounds for twisted GL(2)GL(2) short character sums

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    Let S(N)=βˆ‘n∼Nsmooth λf(n) χ(n),S(N) = \sum_{n \sim N}^{\text{smooth}} \, \lambda_{f}(n) \, \chi(n), where Ξ»f(n)\lambda_{f}(n)'s are Fourier coefficients of Hecke-eigen form, and Ο‡\chi is a primitive character of conductor prp^{r}. In this article we prove a sub-Weyl strength bounds for S(N)S(N). Indeed, we obtain S(N)β‰ͺ N59Β p13r45,S(N) \ll \, N^{\frac{5}{9}} \ p^{\frac{13r}{45}}, provided that p13r/20≀N≀p4r/5 p^{13r/20} \leq N \leq p^{4r/5}. Note that the above bound for S(N)S(N) is non-trivial if Nβ‰₯(pr)23βˆ’160N\geq \left(p^{r}\right)^{\frac{2}{3}-\frac{1}{60}}.Comment: First draf

    Hybrid method for achieving Pareto front on economic emission dispatch

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    In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multi-objective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II

    Morpho-physiological changes in oil palm (Elaeis guineensis Jacq.) tenera hybrid seedlings raised under different shade levels

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    Climatic conditions prevailing in oil palm growing states of India indicate the need for shade during primary stage of oil palm nursery for optimum growth and vigour of seedlings. Experiments were conducted to standardize the shade requirement based on growth/quality of oil palm seedlings in summer, rainy and winter seasons by providing 25%, 50% and 75% ultra violet stabilized high density poly ethylene (HDPE) shade nets. Results were found significant among the treatments for most of the growth parameters studied over the seasons. Highergrowth for key characters like seedling height, leaf area, collar girth and dry matter production were recorded at 75% shade level. Similarly, higher chlorophyll content, photosynthetic rate, transpiration rate, stomatal conductance and inter cellular CO2 concentration were observed at 75% shade. Among the season, seedling growth was vigorous in rainy season followed by summer and winter seasons. Hence, provision of 75% shade found to be ideal for raising seedlings during primary stage of nursery in oil palm

    Sub-convexity bound for GL(3)Γ—GL(2)GL(3) \times GL(2) LL-functions: GL(3)GL(3)-spectral aspect

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    Let Ο•\phi be a Hecke-Maass cusp form for SL(3,Z)SL(3, \mathbb{Z}) with Langlands parameters (ti)i=13({\bf t}_{i})_{i=1}^{3} satisfying ∣t3βˆ’t2βˆ£β‰€T1βˆ’ΞΎβˆ’Ο΅, tiβ‰ˆT,  i=1,2,3|{\bf t}_{3} - {\bf t}_{2}| \leq T^{1-\xi -\epsilon}, \quad \, {\bf t}_{i} \approx T, \quad \, \, i=1,2,3 with 1/201/2 0. Let ff be a holomorphic or Maass Hecke eigenform for SL(2,Z)SL(2,\mathbb{Z}). In this article, we prove a sub-convexity bound L(ϕ×f,12)β‰ͺmax⁑{T32βˆ’ΞΎ4+Ο΅,T32βˆ’1βˆ’2ΞΎ4+Ο΅}L(\phi \times f, \frac{1}{2}) \ll \max \{ T^{\frac{3}{2}-\frac{\xi}{4}+\epsilon} , T^{\frac{3}{2}-\frac{1-2 \xi}{4}+\epsilon} \} for the central values L(ϕ×f,12)L(\phi \times f, \frac{1}{2}) of the Rankin-Selberg LL-function of Ο•\phi and ff, where the implied constants may depend on ff and Ο΅\epsilon. Conditionally, we also obtain a subconvexity bound for L(ϕ×f,12)L(\phi \times f, \frac{1}{2}) when the spectral parameters of Ο•\phi are in generic position, that is tiβˆ’tjβ‰ˆT, for iβ‰ j, tiβ‰ˆT,  i=1,2,3.{\bf t}_{i} - {\bf t}_{j} \approx T, \quad \, \text{for} \, i \neq j, \quad \, {\bf t}_{i} \approx T , \, \, i=1,2,3.Comment: First draf
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