Inclusion of Taxaceae in a separate order, Taxales

This article does not have an abstract

Epidermal structure and development of stomata in Ephedra foliata Boiss.

The epidermal structure of the leaf and stem of Ephedra foliata Boiss. is described. The epidermis of internodes and leaves shows longitudinal rows of cells and stomata. In the nodes and the leaf bases the stomata are irregularly orientated. The subsidiary cells are perigene and the development of stomata is typically haplocheilic

The effects of transients on photospheric and chromospheric power distributions

We have observed a quiet Sun region with the Swedish 1-meter Solar Telescope (SST) equipped with CRISP Imaging SpectroPolarimeter. High-resolution, high-cadence, H$\alpha$ line scanning images were taken to observe different layers of the solar atmosphere from the photosphere to upper chromosphere. We study the distribution of power in different period-bands at different heights. Power maps of the upper photosphere and the lower chromosphere show suppressed power surrounding the magnetic-network elements, known as "magnetic shadows". These also show enhanced power close to the photosphere, traditionally referred to as "power halos". The interaction between acoustic waves and inclined magnetic fields is generally believed to be responsible for these two effects. In this study we explore if small-scale transients can influence the distribution of power at different heights. We show that the presence of transients, like mottles, Rapid Blueshifted Excursions (RBEs) and Rapid Redshifted Excursions (RREs), can strongly influence the power-maps. The short and finite lifetime of these events strongly affects all powermaps, potentially influencing the observed power distribution. We show that Doppler-shifted transients like RBEs and RREs that occur ubiquitously, can have a dominant effect on the formation of the power halos in the quiet Sun. For magnetic shadows, transients like mottles do not seem to have a significant effect in the power suppression around 3 minutes and wave interaction may play a key role here. Our high cadence observations reveal that flows, waves and shocks manifest in presence of magnetic fields to form a non-linear magnetohydrodynamic system.Comment: 11 pages, 11 Figures, 4 movies (will be available online in ApJ). ApJ (accepted

The ion-aerosol interactions from the ion mobility and aerosol particle size distribution measurements on January 17 and February 18, 2005 at Maitri, Antarctica - A case study

A case study for the ion–aerosol interactions is presented from the simultaneous measurements of mobility spectra of atmospheric ions in the mobility range of 2.29 to 2.98 × 10 − 4 cm2 V − 1 s −1 (diameter range 0.41–109 nm) and of size distribution of atmospheric aerosol particles in the size ranges of 4.4–700 nm and 500–20,000 nm diameters made at Maitri (70°45′52′ ′S, 11°44′2.7′ ′E; 130 m above mean sea level), Antarctica, on two days January 17 and February 18, 2005, with contrasting meteorological conditions. In contrast to January 17, on February 18, winds were stronger from the morning to noon and lower from the noon to evening, atmospheric pressure was lower, cloudiness was more, the land surface remained snow-covered after a blizzard on February 16 and 17 and the airmass over Maitri, descended from an altitude of ~3 km after an excursion over ocean. On these days mobility spectra showed two modes, corresponding to intermediate ions and light large ions and an indication of additional one/two maxima for small/cluster ions and heavy large ions. The small ions generated by cosmic rays, and the nucleation mode particles generated probably by photochemical reactions grew in size by condensation of volatile trace gases on them and produced the cluster and intermediate ion modes and the Aitken particle mode in ion/particle spectra. Particles in the size range of 9–26 nm have been estimated to grow at the rate of 1.9 nm h − 1 on February 18, 2005. Both, ions and aerosol particles show bimodal size distributions in the 16–107 nm size range, and comparison of the two size distributions suggests the formation of multiple charged ions. Attachment of small ions to particles in this bimodal distribution of Aitken particles together with the formation of multiple charged ions are proposed to result in the light and heavy large ion modes. Growth of the nucleation mode particles on February 18, 2005 is associated with the passage of the airmass over ocean. In contrast, though the ion size distributions were not much different, the aerosol size distributions did not show a dominant peak for the formation and growth of nucleation mode particles on January 17. More measurements are needed before the conclusion of this case study is generalized

A Doubling Technique for the Power Method Transformations

Power method polynomials are used for simulating non-normal distributions with specified product moments or L-moments. The power method is capable of producing distributions with extreme values of skew (L-skew) and kurtosis (L-kurtosis). However, these distributions can be extremely peaked and thus not representative of real-world data. To obviate this problem, two families of distributions are introduced based on a doubling technique with symmetric standard normal and logistic power method distributions. The primary focus of the methodology is in the context of L-moment theory. As such, L-moment based systems of equations are derived for simulating univariate and multivariate non-normal distributions with specified values of L-skew, L-kurtosis, and L-correlation. Evaluation of the proposed doubling technique indicates that estimates of L-skew, L-kurtosis, and L-correlation are superior to conventional product-moments in terms of relative bias and relative efficiency when extreme non-normal distributions are of concern

An L-Moment Based Characterization of the Family of Dagum Distributions

This paper introduces a method for simulating univariate and multivariate Dagum distributions through the method of L-moments and L-correlation. A method is developed for characterizing non-normal Dagum distributions with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of contexts such as statistical modeling (e.g., income distribution, personal wealth distributions, etc.) and Monte Carlo or simulation studies. Numerical examples are provided to demonstrate that -moment-based Dagum distributions are superior to their conventional moment-based analogs in terms of estimation and distribution fitting. Evaluation of the proposed method also demonstrates that the estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to their conventional product-moment based counterparts of skew, kurtosis, and Pearson correlation in terms of relative bias and relative efficiency–most notably in the context of heavy-tailed distributions

Design of dimensional model for clinical data storage and analysis

Current research in the field of Life and Medical Sciences is generating chunk of data on daily basis. It has thus become a necessity to find solutions for efficient storage of this data, trying to correlate and extract knowledge from it. Clinical data generated in Hospitals, Clinics & Diagnostics centers is falling under a similar paradigm. Patient’s records in various hospitals are increasing at an exponential rate, thus adding to the problem of data management and storage. Major problem being faced corresponding to storage, is the varied dimensionality of the data, ranging from images to numerical form. Therefore there is a need for development of efficient data model which can handle this multi-dimensionality data issue and store the data with historical aspect. For the stated problem lying in façade of clinical informatics we propose a clinical dimensional model design which can be used for development of a clinical data mart. The model has been designed keeping in consideration temporal storage of patient's data with respect to all possible clinical parameters which can include both textual and image based data. Availability of said data for each patient can be then used for application of data mining techniques for finding the correlation of all the parameters at the level of individual and population