EVALUATION OF COST EFFECTIVE ORGANIC FERTILIZERS

Organic farming/products are becoming very necessary in today’s world to control ecosystem health and to impart related human health benefits, world over there is growing demand for organic produce. A field experiment was conducted at the research farm of Kilpest India Ltd., Bhopal, during 2009 on rice using BGA Chlorella pyrenoidosa and Nostoc muscorum and biological hydrolysate of Soybean .These treatments were compared with recommended dose of Fytozyme. Currently, fytozyme (40% chemically hydrolysed protein solution) is being used as organic fertilizer world over which was taken as positive control. Cost of all the organic amendments were considered and kept at par with the Fytozyme. Results revealed a significant increase in growth parameters and straw yield in plot treated with Chlorella pyrenoidosa. Grain yield was also higher in C. pyrenoidosa (3.35 t/ha) followed by Fytozyme (3.05 t/ha) and Nostoc as well as biological Soy hydrolysate (both 2.81 t/ha). Thus concluding a better viable organic product

The Vanishing Role of Money in the Macroeconomy - An Empirical Investigation Based On Spectral and Wavelet Analysis

The recent de-emphasizing of the role of money in both theoretical macroeconomics as well as in the practical conduct of monetary policy sits uneasily with the idea that inflation is a monetary phenomenon. Empirical evidence has, however, been accumulating, pointing to an important leading indicator role for money and credit aggregates with respect to long term inflationary trends. Such a role could arise from monetary aggregates furnishing a nominal anchor for inflationary expectations, from their influence on the term structure of interest rates and from their affecting transactions costs in markets. Our paper attempts to assess the informational content role of money in the Indian economy by a separation of these effects across time scales and frequency bands, using the techniques of wavelet analysis and band spectral analysis respectively. Our results indicate variability of causal relations across frequency ranges and time scales, as also occasional causal reversals.Money, inflation, Cointegration, Causality, Decomposition, band spectra, wavelets

FogGIS: Fog Computing for Geospatial Big Data Analytics

Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog-based framework named Fog GIS for mining analytics from geospatial data. We built a prototype using Intel Edison, an embedded microprocessor. We validated the FogGIS by doing preliminary analysis. including compression, and overlay analysis. Results showed that Fog computing hold a great promise for analysis of geospatial data. We used several open source compression techniques for reducing the transmission to the cloud.Comment: 6 pages, 4 figures, 1 table, 3rd IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (09-11 December, 2016) Indian Institute of Technology (Banaras Hindu University) Varanasi, Indi

Prevalence and co-infection of Toxoplasma gondii and Neospora caninum in Apodemus sylvaticus in an area relatively free of cats

The protozoan parasite Toxoplasma gondii is prevalent worldwide and can infect a remarkably wide range of hosts despite felids being the only definitive host. As cats play a major role in transmission to secondary mammalian hosts, the interaction between cats and these hosts should be a major factor determining final prevalence in the secondary host. This study investigates the prevalence of T. gondii in a natural population of Apodemus sylvaticus collected from an area with low cat density (<2·5 cats/km2). A surprisingly high prevalence of 40·78% (95% CI: 34·07%–47·79%) was observed despite this. A comparable level of prevalence was observed in a previously published study using the same approaches where a prevalence of 59% (95% CI: 50·13%–67·87%) was observed in a natural population of Mus domesticus from an area with high cat density (>500 cats/km2). Detection of infected foetuses frompregnant dams in both populations suggests that congenital transmission may enable persistence of infection in the absence of cats. The prevalences of the related parasite, Neospora caninum were found to be low in both populations (A. sylvaticus: 3·39% (95% CI: 0·12%–6·66%); M. domesticus: 3·08% (95% CI: 0·11%–6·05%)). These results suggest that cat density may have a lower than expected effect on final prevalence in these ecosystems

Editorial: Biomechatronics: Harmonizing Mechatronic Systems With Human Beings.

There has been a growing body of research in the recent years on human-robot interactions, human-machine interfaces and intelligent devices that are centered around human application, however, these works by and large lacked in focus on how to harmonize the interactions between mechatronic systems and users in the loop. This is one of the key areas for evaluating the success of any mechatronic system implementation on human. The collection of papers in this volume is touching upon the frontiers of this research area as to how the efficacy of such biomechatronic systems could be evaluated and improved. There are a total of 19 papers looking into various aspects of human-machine interfaces (HMIs) using electromyography (EMG) and electroencephalography (EEG), tactile feedback, external devices such as exoskeletons and prosthetic devices for assistance and rehabilitation, novel techniques like machine learning and intelligent computation, and experimental evaluation or validation. The following paragraphs aim to give a glimpse of the contents presented in this eBook. Specifically, these are categorized under three distinct headings: (A) Novel exoskeletons for assistance and training, (B) Advanced human-machine interfaces in biomechatronics, and (C) Experimental outcomes and validation

Inverse problem of photoelastic fringe mapping using neural networks

This paper presents an enhanced technique for inverse analysis of photoelastic fringes using neural networks to determine the applied load. The technique may be useful in whole-field analysis of photoelastic images obtained due to external loading, which may find application in a variety of specialized areas including robotics and biomedical engineering. The presented technique is easy to implement, does not require much computation and can cope well within slight experimental variations. The technique requires image acquisition, filtering and data extraction, which is then fed to the neural network to provide load as output. This technique can be efficiently implemented for determining the applied load in applications where repeated loading is one of the main considerations. The results presented in this paper demonstrate the novelty of this technique to solve the inverse problem from direct image data. It has been shown that the presented technique offers better result for the inverse photoelastic problems than previously published works

False-Name Manipulation in Weighted Voting Games is Hard for Probabilistic Polynomial Time

False-name manipulation refers to the question of whether a player in a weighted voting game can increase her power by splitting into several players and distributing her weight among these false identities. Analogously to this splitting problem, the beneficial merging problem asks whether a coalition of players can increase their power in a weighted voting game by merging their weights. Aziz et al. [ABEP11] analyze the problem of whether merging or splitting players in weighted voting games is beneficial in terms of the Shapley-Shubik and the normalized Banzhaf index, and so do Rey and Rothe [RR10] for the probabilistic Banzhaf index. All these results provide merely NP-hardness lower bounds for these problems, leaving the question about their exact complexity open. For the Shapley--Shubik and the probabilistic Banzhaf index, we raise these lower bounds to hardness for PP, "probabilistic polynomial time", and provide matching upper bounds for beneficial merging and, whenever the number of false identities is fixed, also for beneficial splitting, thus resolving previous conjectures in the affirmative. It follows from our results that beneficial merging and splitting for these two power indices cannot be solved in NP, unless the polynomial hierarchy collapses, which is considered highly unlikely

Recovering Grammar Relationships for the Java Language Specification

Grammar convergence is a method that helps discovering relationships between different grammars of the same language or different language versions. The key element of the method is the operational, transformation-based representation of those relationships. Given input grammars for convergence, they are transformed until they are structurally equal. The transformations are composed from primitive operators; properties of these operators and the composed chains provide quantitative and qualitative insight into the relationships between the grammars at hand. We describe a refined method for grammar convergence, and we use it in a major study, where we recover the relationships between all the grammars that occur in the different versions of the Java Language Specification (JLS). The relationships are represented as grammar transformation chains that capture all accidental or intended differences between the JLS grammars. This method is mechanized and driven by nominal and structural differences between pairs of grammars that are subject to asymmetric, binary convergence steps. We present the underlying operator suite for grammar transformation in detail, and we illustrate the suite with many examples of transformations on the JLS grammars. We also describe the extraction effort, which was needed to make the JLS grammars amenable to automated processing. We include substantial metadata about the convergence process for the JLS so that the effort becomes reproducible and transparent

The approach to typicality in many-body quantum systems

The recent discovery that for large Hilbert spaces, almost all (that is, typical) Hamiltonians have eigenstates that place small subsystems in thermal equilibrium, has shed much light on the origins of irreversibility and thermalization. Here we give numerical evidence that many-body lattice systems generically approach typicality as the number of subsystems is increased, and thus provide further support for the eigenstate thermalization hypothesis. Our results indicate that the deviation of many-body systems from typicality decreases exponentially with the number of systems. Further, by averaging over a number of randomly-selected nearest-neighbor interactions, we obtain a power-law for the atypicality as a function of the Hilbert space dimension, distinct from the power-law possessed by random Hamiltonians.Comment: 6 pages, 2 png figures, revtex