Precise measurements of the anisotropies in the cosmic microwave background enable us to do an accurate study on the form of the primordial power spectrum for a given set of cosmological parameters. In a previous paper [1], we implemented an improved (error sensitive) Richardson-Lucy deconvolution algorithm on the measured angular power spectrum from the first year of WMAP data to determine the primordial power spectrum assuming a concordance cosmological model. This recovered spectrum has a likelihood far better than a scale invariant, or, 'best fit' scale free spectra (∆ ln L ≈ 25 w.r.t. Harrison Zeldovich, and, ∆ ln L ≈ 11 w.r.t. power law with ns = 0.95). In this paper we use Discrete Wavelet Transform (DWT) to decompose the local features of the recovered spectrum individually to study their effect and significance on the recovered angular power spectrum and hence the likelihood. We show that besides the infra-red cut off at the horizon scale, the associated features of the primordial power spectrum around the horizon have a significant effect on improving the likelihood. The strong features are localized at the horizon scale.

We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multi-fractal behavior. [6,7,8] and its variants [9,10,11]. The difficulty in characterizing the scaling property stems from the fact that, the observed time series is very often nonstationary. Hence, it is essential to define fluctuations in a manner which takes proper account of non-stationarity.In this note, we propose a new method, based on discrete wavelet transform [12], to separate the trend in the time series from the fluctuations. The method is direct and suggests itself naturally from the basic concepts underlying wavelet decomposition, apart from being supplementary to the detrended fluctuation analysis. The fact that the so called low-pass coefficients represent a coarse grained version of the data in wavelet transform and the built-in ability of the wavelets to have variable window sizes for coarse graining, makes it a natural tool for identifying fluctuations around trends at various scales. We use this method to examine scaling behavior of a time series. For the purpose of checking the efficacy of our procedure and comparison with multifractal detrended fluctuation analysis (MF-DFA), we consider time series generated (10 6 data points) from the binomial multifractal model [2], for which the scaling exponent is analytically calculable. The method has also been checked on Gaussian random noise. We then analyzed the time series of average spin densities (9x10 5 data points) in a simulation of the 2D Ising model on a 256 x 256 lattice at the critical temperature T c , where each update of the system in the simulation is taken as one time step [16,17]. These computer generated time series are shown in Fig.

The cultivation of rice (Oryza sativa L.), a major food crop, requires ample water (30 % of the fresh water available worldwide), and its productivity is greatly affected by drought, the most significant environmental factor. Much research has focussed on identifying quantitative trait loci, stress-regulated genes and transcription factors that will contribute towards the development of climate-resilient/tolerant crop plants in general and rice in particular. The transcription factor DREB1A, identified from the model plant Arabidopsis thaliana, has been reported to enhance stress tolerance against drought stress. We developed transgenic rice plants with AtDREB1A in the background of indica rice cultivar Samba Mahsuri through Agrobacterium-mediated transformation. The AtDREB1A gene was stably inherited and expressed in T1 and T2 plants and in subsequent generations, as indicated by the results of PCR, Southern blot and RT-PCR analyses. Expression of AtDREB1A was induced by drought stress in transgenic rice lines, which were highly tolerant to severe water deficit stress in both the vegetative and reproductive stages without affecting their morphological or agronomic traits. The physiological studies revealed that the expression of AtDREB1A was associated with an increased accumulation of the osmotic substance proline, maintenance of chlorophyll, increased relative water content and decreased ion leakage under drought stress. Most of the homozygous lines were highly tolerant to drought stress and showed significantly a higher grain yield and spikelet fertility relative to the nontransgenic control plants under both stressed and unstressed conditions. The improvement in drought stress tolerance in combination with agronomic traits is very essential in high premium indica rice cultivars, such as Samba Mahsuri, so that farmers can benefit in times of seasonal droughts and water scarcity.Electronic supplementary materialThe online version of this article (doi:10.1007/s11248-013-9776-6) contains supplementary material, which is available to authorized users.

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Nuclear factor Y (NF-Y) is a heterotrimeric transcription factor with three distinct NF-YA, NF-YB and NF-YC subunits. It plays important roles in plant growth, development and stress responses. We have reported earlier on development of gain-of-function mutants in an indica rice cultivar, BPT-5204. Now, we screened 927 seeds from 70 Ac/Ds plants for salinity tolerance and identified one activation-tagged salt tolerant DS plant (DS-16, T3 generation) that showed enhanced expression of a novel ‘histone-like transcription factor’ belonging to rice NF-Y subfamily C and was named as OsNF-YC13. Localization studies using GFP-fusion showed that the protein is localized to nucleus and cytoplasm. Real time expression analysis confirmed upregulation of transcript levels of OsNF-YC13 during salt treatment in a tissue specific manner. Biochemical and physiological characterization of the DS-16 revealed enhanced K+/Na+ ratio, proline content, chlorophyll content, enzymes with antioxidant activity etc. DS-16 also showed transcriptional up-regulation of genes that are involved in salinity tolerance. In-silico analysis of OsNF-YC13 promoter region evidenced the presence of various key stress-responsive cis-regulatory elements. OsNF-YC13 subunit alone does not appear to have the capacity for direct transcription activation, but appears to interact with the B- subunits in the process of transactivation.