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ARTICLE STUDY ON APPLICABILITY AND FEEDING PREFERENCES OF AQUATIC INSECTS
No full textAquatic macroinvertebrates play an important role in a wide range of ecological processes. Primary production, detritus decomposition, nutrient mineralization, and downstream spiralling are just some of the processes they have a significant impact on. The categorization of functional feeding groups (FFGs) was created to make it easier to include macroinvertebrates in aquatic ecosystems research. When macroinvertebrates consume resources, their physical properties (such as the specialisation of mouth parts) and behavioural processes (such as feeding strategy) are combined in this categorization. In spite of recent advancements in macroinvertebrate identification, there is still a lack of knowledge on the FFG assignment. FFG classification has also undergone considerable alteration because of a focus on gut content analysis, which is more suited for assigning trophic guilds than using the FFG classification alone. These objectives are to present an overview of the usefulness of utilising the FFG classification, synthesise known information on aquatic insects in Latin America using the FFG, and provide basic instructions on how to allocate species to their FFGs in this research. The purpose of FFGs is to show the impact organisms may have on their habitats and the resources they use. Groups such as scrapers, shredders, and collectorsgatherers use modified mouth parts to sieve or collect small particles (1mm) accumulating on the stream bottom, while filterers use special adaptations to remove particles from the water directly. Other groups include filterers, which remove particles directly from the water. The piercers that drink plant juices by cutting or puncturing the tissue with their mouth parts and feed on vascular plants are also covered in depth. A list of aquatic insect families in Latin America, with an initial assignment to FFGs, is also provided in this section When allocating FFGs based on the contents of one's stomach, we advised care
INDUCED ORDER STATISTICS AND THEIR CHARACTERIZATION FOR BIVARIATE KUMARSWAMY AND BIVARIATE PSEUDOKUMARSWAMY DISTRIBUTIONS
No full textIn this article two Bivariate distributions, namely, Bivariate Kumarswamy Distribution and Bivariate Pseudo-Kumaraswamy Distributions, as were derived from univariate Kumaraswamy Distribution and Pseudo-Kumaraswamy Distributions, have been considered. Using these Bivariate Distributions Induced Order Statistics have been obtained. Further, the probability density function of a single and joint induced statistics have been derived and to characterize them their moments and Entropy for order statistics have also been obtained
ANALYTICAL STUDIES OF CU(II),NI(II) AND PD(II) COMPLEX WITH 3- PHENYL-QUINAZOLIN-4(3H)-ONE-2-CARBOXALDEHYDOXIME
No full text3-Phenyl quinazolin-4-(3H)-one-2-carboxaldehydoxime forms water insoluble chelates with Cu(II), Ni(II) and Pd(II). It has been found to be a selective reagent for the gravimetric estimation of these metal ions in presence of many interfering ions. All the che lates have 1:2 (metal: ligand) stoichiometry as shown by Job's method of continuous variation and elemental analysis. Structures of the metal chelates have been established on the basis of magnetic measurements, visible and IR spectra
CHARACTERIZATION OF INDUCED ORDER STATISTICS FROM RAYLIEGH BIVARIATE DISTRIBUTION
No full textIn this paper, a new bivariate distribution, using the concept given by Mongestern (1956), has been derived from univariate Rayleigh distribution. This new bivariate Rayleigh distribution is then considered to obtain the Induced (concomitants) order statistics. We have finally derived the probability density function of a single and joint induced order statistics and have obtained their moments to characterize the distribution