Feeding stimulatory effects of Cyperus rotundus tuber on Cirrhinus mrigala

Traditionally tubers of cyperus (Cyperus rotundus) and its extracts have been used for alluring fish during harvesting in India. An experiment was conducted to evaluate its feeding stimulatory activity and effect on the growth of a commercially important freshwater fish, Cirrhinus mrigala. Three isonitrogenous and isocaloric formulated diets viz. plant ingredient based control and control supplemented with cyperus tuber (CS) at 1% and 5% levels were fed to the fingerlings of mrigal, C. mrigala (2.68+0.20 g) for a period of 45 days. The growth performance and the activity of metabolic enzymes, aspartate aminotransferase (AST) and alanine aminotransferase (ALT), in liver, gill and muscle tissues of mrigal were studied during every 15 days interval. Highest relative growth (72.28%) was obtained in the mrigal fed with the diet containing 5% cyperus (5% CS), while the relative growths were 66.18% and 43.40% for the fish fed with the 1% CS diet and control respectively. The activities of AST and ALT were significantly higher (p<0.01) in both 1% and 5% CS diets as compared to the control in all the tissues studied. Higher aminotransferase activities were observed in the tissues of 5% CS group than in those of 1% CS group throughout the experimental period. The observed higher enzymatic activity was concomitant with the higher growth rate in fish. The results suggested that cyperus tuber supplementation increased feed palatability and growth

Unifying Parsimonious Tree Reconciliation

Evolution is a process that is influenced by various environmental factors, e.g. the interactions between different species, genes, and biogeographical properties. Hence, it is interesting to study the combined evolutionary history of multiple species, their genes, and the environment they live in. A common approach to address this research problem is to describe each individual evolution as a phylogenetic tree and construct a tree reconciliation which is parsimonious with respect to a given event model. Unfortunately, most of the previous approaches are designed only either for host-parasite systems, for gene tree/species tree reconciliation, or biogeography. Hence, a method is desirable, which addresses the general problem of mapping phylogenetic trees and covering all varieties of coevolving systems, including e.g., predator-prey and symbiotic relationships. To overcome this gap, we introduce a generalized cophylogenetic event model considering the combinatorial complete set of local coevolutionary events. We give a dynamic programming based heuristic for solving the maximum parsimony reconciliation problem in time O(n^2), for two phylogenies each with at most n leaves. Furthermore, we present an exact branch-and-bound algorithm which uses the results from the dynamic programming heuristic for discarding partial reconciliations. The approach has been implemented as a Java application which is freely available from http://pacosy.informatik.uni-leipzig.de/coresym.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

Relative Abundance of Transcripts (RATs):Identifying differential isoform abundance from RNA-seq [version 1; referees: 1 approved, 2 approved with reservations]

The biological importance of changes in RNA expression is reflected by the wide variety of tools available to characterise these changes from RNA-seq data. Several tools exist for detecting differential transcript isoform usage (DTU) from aligned or assembled RNA-seq data, but few exist for DTU detection from alignment-free RNA-seq quantifications. We present the RATs, an R package that identifies DTU transcriptome-wide directly from transcript abundance estimates. RATs is unique in applying bootstrapping to estimate the reliability of detected DTU events and shows good performance at all replication levels (median false positive fraction < 0.05). We compare RATs to two existing DTU tools, DRIM-Seq & SUPPA2, using two publicly available simulated RNA-seq datasets and a published human RNA-seq dataset, in which 248 genes have been previously identified as displaying significant DTU. RATs with default threshold values on the simulated Human data has a sensitivity of 0.55, a Matthews correlation coefficient of 0.71 and a false discovery rate (FDR) of 0.04, outperforming both other tools. Applying the same thresholds for SUPPA2 results in a higher sensitivity (0.61) but poorer FDR performance (0.33). RATs and DRIM-seq use different methods for measuring DTU effect-sizes complicating the comparison of results between these tools, however, for a likelihood-ratio threshold of 30, DRIM-Seq has similar FDR performance to RATs (0.06), but worse sensitivity (0.47). These differences persist for the simulated drosophila dataset. On the published human RNA-seq dataset the greatest agreement between the tools tested is 53%, observed between RATs and SUPPA2. The bootstrapping quality filter in RATs is responsible for removing the majority of DTU events called by SUPPA2 that are not reported by RATs. All methods, including the previously published qRT-PCR of three of the 248 detected DTU events, were found to be sensitive to annotation differences between Ensembl v60 and v87

Application of Liquid Membrane in Removal of Dyes

Textile industries are major sources of residual dyes and organic pollutants that are released into natural water resources. Treatment of this waste water and its recycling is essential because of higher grades of impurities for example pigments, auxiliary chemicals and heavy metals,etc.). Dyeing process causes a loss of 10-25% of the textile dyes,out of which 2-20% are removed as aqueous effluents causing harm to environment. Removal of effluents constituting dyes inside water bodies are unwanted due to their color,& because many of them breakdown into products which are poisonous. To re-use the materials obtained from the waste products,Liquid membrane techniques evolved over other separation techniques due to its high selectivity,recovery,increased fluxes,and reduced investment and operating cost. It combines extraction and stripping in a single unit operation. Removal of dyes by liquid membranes using organic solvents was found to be toxic and costlier. So vegetables oils are used instead of organic solvents in liquid membranes for extraction of different types of dyes and different parameters are optimized based on the extraction percentage. This thesis focuses on the extraction of Methylene Blue using bulk liquid membrane from its aqueous phase. The feed phase was aqueous solution of Methylene Blue and the strip phase was sulfuric acid solution. Solvent was Sunflower Oil for the liquid membrane phase and phenol acted as carrier. 95% MB extraction was achieved from feed phase to organic phase whereas only 90% of MB was recovered from organic phase to the receiving phase. Optimum value for strip phase concentration parameter was 1.25 N and similarly for carrier concentration 1M of carrier is most favorable for the transport process when optimum 12 pH of feed phase if maintained increases the efficiency. Even stirring speed conditions affects the extraction and recovery to great extent and when all the three phase are stirred at 300 rpm it gives the best results

A Certain Class of Statistical Deferred Weighted A-summability Based on (p; q)-integers and Associated Approximation Theorems

Statistical summability has recently enhanced researchers’ substantial awareness since it is more broad than the traditional (ordinary) convergence. The basic concept of statistical weighted A- summability was introduced by Mohiuddine (2016). In this investigation, we introduce the (presumably new) concept of statistical deferred weighted A-summability and deferred weighted A- statistical convergence with respect to the difference sequence of order r involving (p; q)-integers and establish an inclusion relation between them. Furthermore, based upon the proposed methods, we intend to approximate the rate of convergence and to demonstrate a Korovkin type approximation theorem for functions of two variables defined on a Banach space CB(D). Finally, several illustrative examples are presented in light of our definitions and outcomes established in this paper

Limits of Quantum Speed-Ups for Computational Geometry and Other Problems: Fine-Grained Complexity via Quantum Walks

Many computational problems are subject to a quantum speed-up: one might find that a problem having an Opn3q-time or Opn2q-time classic algorithm can be solved by a known Opn1.5q-time or Opnq-time quantum algorithm. The question naturally arises: how much quantum speed-up is possible? The area of fine-grained complexity allows us to prove optimal lower-bounds on the complexity of various computational problems, based on the conjectured hardness of certain natural, well-studied problems. This theory has recently been extended to the quantum setting, in two independent papers by Buhrman, Patro and Speelman [7], and by Aaronson, Chia, Lin, Wang, and Zhang [1]. In this paper, we further extend the theory of fine-grained complexity to the quantum setting. A fundamental conjecture in the classical setting states that the 3SUM problem cannot be solved by (classical) algorithms in time Opn2´εq, for any ε ą 0. We formulate an analogous conjecture, the Quantum-3SUM-Conjecture, which states that there exist no sublinear Opn1´εq-time quantum algorithms for the 3SUM problem. Based on the Quantum-3SUM-Conjecture, we show new lower-bounds on the time complexity of quantum algorithms for several computational problems. Most of our lower-bounds are optimal, in that they match known upper-bounds, and hence they imply tight limits on the quantum speedup that is possible for these problems. These results are proven by adapting to the quantum setting known classical fine-grained reductions from the 3SUM problem. This adaptation is not trivial, however, since the original classical reductions require pre-processing the input in various ways, e.g. by sorting it according to some order, and this pre-processing (provably) cannot be done in sublinear quantum time. We overcome this bottleneck by combining a quantum walk with a classical dynamic data-structure having a certain “history-independence” property. This type of construction has been used in the past to prove upper bounds, and here we use it for the first time as part of a reduction. This general proof strategy allows us to prove tight lower bounds on several computational-geometry problems, on Convolution-3SUM and on the 0-Edge-Weight-Triangle problem, conditional on the Quantum-3SUM-Conjecture. We believe this proof strategy will be useful in proving tight (conditional) lower-bounds, and limits on quantum speed-ups, for many other problems

EXPERIMENTAL EVALUATION OF ANTIDEPRESSANT ACTIVITY OF AQUEOUS AND CHLOROFORM LEAF AND SHOOT EXTRACTS OF EICCHORNIA CRASSIPES LINN IN MICE

Objective: To investigate antidepressant activity of aqueous and chloroform extract of Eicchornia crassipes plant leaves and shoots in mice.Methods: The antidepressant activity of aqueous and chloroform extract of Eicchornia crassipes plant leaves and shoots were tested by forced swimtest (FST) and tail suspension test (TST) in albino mice and the results were compared for the both extracts. Imipramine was used as the standardrug for comparison. Results: Phytochemical screening showed presence of carbohydrates, alkaloids, flavanoids, steroids, saponins, amino acids, gums and mucilage.aqueous extract of Eicchornea crassipes (AEEC) and chloroform extract of E. crassipes (CEEC) did not produce any lethal effect even upto 2000 mg/kp.o during acute oral toxicity study. In FST and TST, CEEC showed diminution of duration of immobility time in 200 mg/kg but not in 100 mg/kg. Conclusion: From the above finding concluding that, shortening of immobility time in the FST and TST indicating, CEEC showed more antidepressantactivity acting either by the enhancement of central 5-HT or catecholamine neurotransmission compared to AEEC in mice.Keywords: Eicchornia crassipes, Aqueous extract of Eicchornia crassipes, Chloroform extract of Eicchornia crassipes, Forced swim test,Tail suspension test

Nucleation of the electroactive γ phase and enhancement of the optical transparency in low filler content poly(vinylidene)/clay nanocomposites

Poly(vinylidene fluoride), PVDF, based nanocomposites with different clays structures have been processed by solvent casting and melt crystallisation. Depending on the melting temperature of the polymer, the nanocomposite recrystalises in the electroactive or non electroactive β-phase of the polymer. This fact is related to the thermal behaviour of the clay. For montmorillonite clay, the full crystallisation of the electroactiveγ-phase occurs for clay contents lower than 0.5 wt%, allowing the nanocomposites to maintain the mechanical properties of the polymer matrix. The electroactivity of the material has been proven by measuring the piezoelectric d33 response of the material. The obtained value of d33 is -7 pC/N, lower than in β-PVDF obtained by mechanical stretching, but still among the largest coefficients obtained for polymers. Further, the optical transmittance in the visible range is strongly enhanced with respect to the transmittance of the pure polymer. Finally, it is demonstrated that the nucleation of the β-phase can be also obtained in other clays, such as in kaolinite and laponite.Fundação para a Ciência e a Tecnologia (FCT) - NANO/NMed-SD/0156/2007, PTDC/CTM/69316/2006, PTDC/CTM-NAN/112574/2009, SFRH/BD/62507/2009.FEDER funds through the "Programa Operacional Factores de Competitividade – COMPETECOST Action MP1003, the ‘European Scientific Network for Artificial Muscles’ (ESNAM)

Early and Accurate Prediction of Heart Disease Using Machine Learning Model

Heart disease is one of the critical health issues and many people across the world are suffering with this disease. It is important to identify this disease in early stages to save many lives. The purpose of this article is to design a model to predict the heart diseases using machine learning techniques. This model is developed using classification algorithms, as they play important role in prediction. The model is developed using different classification algorithms which include Logistic Regression, Random Forest, Support vector machine, Gaussian Naïve Bayes, Gradient boosting, K-nearest neighbours, Multinomial Naïve bayes and Decision trees. Cleveland data repository is used to train and test the classifiers. In addition to this, feature selection algorithm named chi square is used to select key features from the input data set, which will decrease the execution time and increases the performance of the classifiers. Out of all the classifiers evaluated using performance metrics, Random forest is giving good accuracy. So, the model built using Random forest is efficient and feasible solution in identifying heart diseases and it can be implemented in healthcare which plays key role in the stream of cardiology. &nbsp

Barley <i>SIX-ROWED SPIKE3</i> encodes a putative Jumonji C-type H3K9me2/me3 demethylase that represses lateral spikelet fertility

The VRS genes of barley control the fertility of the lateral spikelets on the barley inflorescence. Here, Bull et al. show that VRS3 encodes a putative Jumonji C-type histone demethylase that regulates expression of other VRS genes, and genes involved in stress, hormone and sugar metabolism