Asymmetric vibration of polar orthotropic annular circular plates of quadratically varying thickness with same boundary conditions

In the present paper, asymmetric vibration of polar orthotropic annular circular plates of quadratically varying thickness resting on Winkler elastic foundation is studied by using boundary characteristic orthonormal polynomials in Rayleigh-Ritz method. Convergence of the results is tested and comparison is made with results already available in the existing literature. Numerical results for the first ten frequencies for various values of parameters describing width of annular plate, thickness profile, material orthotropy and foundation constant for all three possible combinations of clamped, simply supported and free edge conditions are shown and discussed. It is found that (a) higher elastic property in circumferential direction leads to higher stiffness against lateral vibration; (b) Lateral vibration characteristics of F-F plates is more sensitive towards parametric changes in material orthotropy and foundation stiffness thanC-C and S-S plates; (c) Effect of quadratical thickness variation on fundamental frequency is more significant in cases of C-C and S-S plates than that of F-F plates. Thickness profile which is convex relative to plate center-line tends to result in higher stiffness of annular plates against lateral vibration than the one which is concave and (d) Fundamental mode of vibration of C-C and S-S plates is axisymmetrical while that of F-F plates is asymmetrical

Gyrothrix sagarensis SP. NOV.: A NOVEL HYPHOMYCETOUS FUNGUS ON MEDICINAL PLANT Gardenia latifolia AITON FROM CENTRAL INDIA

Gardenia latifolia is commonly known as Indian boxwood or Ceylon boxwood. Various parts of this plant are utilized to treat several cases of inflammatory pain, skin diseases, caries in humans, snake bite, stomachache, haemorrhage along with the ephemeral fever in live stocks. During the routine survey of Dr. Harisingh Gour Vishwavidyalaya Campus, Sagar for mycotaxonomic evaluation of terrestrial plants an interesting fungal specimen was encountered on G. latifolia Aiton which upon detailed morphological observations and mycotaxonomic treatment, proved to be a novel fungal species Gyrothrix sagarensis. It is also noteworthy that most of the species of this genus Gyrothrix (Corda) Corda, are reported on dead plant parts while the present novel species was collected and examined on living plant parts (i.e. on twig) of G. latifolia

A QUALITATIVE STUDY OF MENTAL PERSEVERANCE AND MENTAL CONCENTRATION AMONG ELITE AND SUB-ELITE WRESTLERS

Sports itself is a stressor and it demands a high level of resolutions, unflagging eagerness and obstinate persistence from its participants. It is believed that athletes having strong mental hardiness, concentration and optimum skill level do have a dominant hand upon the psychological weaker opponents. In sports, right from the motor acquisition stage to the highest competitive performance level, concentration plays an exceptionally vital role. It is a psycho-physiological process, an intense function of mind which is carried out through cognitive abilities and supplemented by emotional and conational factors. This research is an attempt to examine the dimensions of mental toughness and concentration abilities among wrestlers performing at national and international levels. It also attempts to find the interrelationship between these two parameters. The subjects (N=80) were wrestlers performing at two different levels i.e. national (N=40) and international (N=40). The subjects were asked to complete the Mental Toughness Questionnaire and to work on the Concentration Grid Exercise against time. The data was statistically analyzed. The results indicate that the international level wrestlers possessed significantly higher level of mental toughness as compared to the national level wrestlers. Female wrestlers have been found to possess significantly higher level of concentration abilities. No significant correlation was, however, observed between these two parameters

India’s energy and emissions future: an interpretive analysis of model scenarios

As a significant emitter of greenhouse gases, but also as a developing country starting from a low emissions base, India is an important actor in global climate change mitigation. However, perceptions of India vary widely, from an energy-hungry climate deal-breaker to a forerunner of a low carbon future. Developing clarity on India's energy and emissions future is challenged by the uncertainties of India's development transitions, including its pathway through a demographic and urban transition within a rapidly changing policy context. Model-based scenario analyses provide widely varying projections, in part because they make differing assumptions, often implicit, about these transitions. To address the uncertainty in India's energy and emissions future, this Letter applies a novel interpretive approach to existing scenario studies. First, we make explicit the implied development, technology and policy assumptions underlying model-based analysis in order to cluster and interpret results. In a second step, we analyse India's current policy landscape and use that as a benchmark against which to judge scenario assumptions and results. Using this interpretive approach, we conclude that, based on current policies, a doubling of India's CO2 energy-related emissions from 2012 levels is a likely upper bound for its 2030 emissions and that this trajectory is consistent with meeting India's Paris emissions intensity pledge. Because of its low emissions starting point, even after a doubling, India's 2030 per capita emissions will be below today's global average and absolute emissions will be less than half of China's 2015 emissions from the same sources. The analysis of recent policy trends further suggests a lower than expected electricity demand and a faster than expected transition from coal to renewable electricity. The Letter concludes by making an argument for interpretive approaches as a necessary complement to scenario analysis, particularly in rapidly changing development contexts

Isolation and Screening of Azo Dyes Tolerant Bacteria in Semi-Scale Industrial Effluents

Dyes are organic compound have colouring properties of the object which used in industrial application. Huge effluent are releasing by industrial processing, where the microorganism may naturally adopted against particular problems. Present work focused over the selection and screening few best native candidates from diverse bacteria from semi-skilled dye industrial effluent. From eleven isolated bacterial colonies only two are found resistant against azo dyes (Methyl orange and Trypan blue). During the screening it observed that isolates of bacteria (VN1 and VN2) were tolerates and decolorize azo dye up to 500 ppm. These bacterial strain can be used efficientlyremoval of dyes contamina-tion from ex-situ and in-situ

Lie group analysis of nanofluid slip flow with Stefan Blowing effect via modified Buongiorno’s Model : entropy generation analysis

This article presents a detailed theoretical and computational analysis of alumina and titania-water nanofluid flow from a horizontal stretching sheet. At the boundary of the sheet (wall), velocity slip, thermal slip and Stefan blowing effects are considered. The Pak-Cho viscosity and thermal conductivity model is employed together with the non-homogeneous Buongiorno nanofluid model. The equations for mass, momentum, energy and nanoparticle species conservation are transformed via Lie-group transformations into a dimensionless system. The partial differential boundary value problem is therefore rendered into nonlinear ordinary differential form. With appropriate boundary conditions, the emerging normalized equations are solved with the semi-numerical homotopy analysis method (HAM). To consider entropy generation affects a second law thermodynamic analysis is also carried out. The impact of some physical parameters on the skin friction, Nusselt number, velocity, temperature and entropy generation number (EGM) are represented graphically. This analysis shows that diffusion parameter is a key factor to retards the friction and rate of heat transfer at the surface. Further, temperature of fluid decreases for the higher value of thermal slip parameter. In addition, entropy generation number enhances with nanoparticles ambient concentration and Reynolds number. A numerical validation of HAM results is also included. The computations are relevant to thermodynamic optimization of nano-material processing operations

Angiogenesis-dependent and independent phases of intimal hyperplasia.

BACKGROUND: Neointimal vascular smooth muscle cell (VSMC) proliferation is a primary cause of occlusive vascular disease, including atherosclerosis, restenosis after percutaneous interventions, and bypass graft stenosis. Angiogenesis is implicated in the progression of early atheromatous lesions in animal models, but its role in neointimal VSMC proliferation is undefined. Because percutaneous coronary interventions result in induction of periadventitial angiogenesis, we analyzed the role of this process in neointima formation. METHODS AND RESULTS: Local injury to the arterial wall in 2 different animal models induced periadventitial angiogenesis and neointima formation. Application of angiogenesis stimulators vascular endothelial growth factor (VEGF-A165) or a proline/arginine-rich peptide (PR39) to the adventitia of the injured artery induced a marked increase in neointimal thickening beyond that seen with injury alone in both in vivo models. Inhibition of either VEGF (with soluble VEGF receptor 1 [sFlt1]) or fibroblast growth factor (FGF) (with a dominant=negative form of FGF receptor 1 [FGF-R1DN]), respectively, signaling reduced adventitial thickening induced by VEGF and PR39 to the level seen with mechanical arterial injury alone. However, neither inhibitor was effective in preventing neointimal thickening after mechanical injury when administered in the absence of angiogenic growth factor. CONCLUSIONS: Our findings indicate that adventitial angiogenesis stimulates intimal thickening but does not initiate it

Preventing anaemia in pregnancy - need for intensive IEC Activities

A Study to know the compliance rale of IFA tablets in respect of collection and consumption was carried out in three districts of Himachal Pradesh covering 90 clusters. Out of total women interviewed with childless than one year, only 94.8% had collected IFA tablets. 41.9% and 10% women had consumed these tablets for 60 and 100 days respectively. Majority of women did not consume these tablets with the reason that medicine is taken on ly during illness and as such they don't require these tablets. Intrusive Information, Education and Communication activities are stressed in the paper

Unsupervised Early Exit in DNNs with Multiple Exits

Deep Neural Networks (DNNs) are generally designed as sequentially cascaded differentiable blocks/layers with a prediction module connected only to its last layer. DNNs can be attached with prediction modules at multiple points along the backbone where inference can stop at an intermediary stage without passing through all the modules. The last exit point may offer a better prediction error but also involves more computational resources and latency. An exit point that is `optimal' in terms of both prediction error and cost is desirable. The optimal exit point may depend on the latent distribution of the tasks and may change from one task type to another. During neural inference, the ground truth of instances may not be available and error rates at each exit point cannot be estimated. Hence one is faced with the problem of selecting the optimal exit in an unsupervised setting. Prior works tackled this problem in an offline supervised setting assuming that enough labeled data is available to estimate the error rate at each exit point and tune the parameters for better accuracy. However, pre-trained DNNs are often deployed in new domains for which a large amount of ground truth may not be available. We model the problem of exit selection as an unsupervised online learning problem and use bandit theory to identify the optimal exit point. Specifically, we focus on Elastic BERT, a pre-trained multi-exit DNN to demonstrate that it `nearly' satisfies the Strong Dominance (SD) property making it possible to learn the optimal exit in an online setup without knowing the ground truth labels. We develop upper confidence bound (UCB) based algorithm named UEE-UCB that provably achieves sub-linear regret under the SD property. Thus our method provides a means to adaptively learn domain-specific optimal exit points in multi-exit DNNs. We empirically validate our algorithm on IMDb and Yelp datasets.Comment: To be presented at International conference on AI-ML system