270 research outputs found
Impact of Globalization on Production and Export of Turmeric in India – An Economic Analysis
India is a major supplier of turmeric to the world with more than 60 per cent share in turmeric trade. The production and export performance of turmeric in India have been examined using secondary data for the period from 1974-75 to 2007-08 and exponential form of growth function has been used for the analysis. The growth in production and export of turmeric has been reported significant, because of the high demand coupled with inflation. Instability index has been worked for the production and export for preliberalization and post-liberalization periods. Instability has been observed high for production, export and prices of domestic and international markets and domestic and international prices have shown high integration. For the assessment of direction of trade, the Markov chain model has been used. The data regarding country-wise export of turmeric has shown that the previous export share retention for Indian turmeric has been high in minor importing countries (pooled under others category) (87 %), followed by UAE (49 %), Iran (41 %) and UK (35 %). The countries such as USA and Japan have not been the stable importers of Indian turmeric. The plans for export may be oriented towards these two countries and also plans should be formulated for stabilizing the export of turmeric to other countries. The farmers should be provided training on production of a quality product.Turmeric, Export of turmeric, Indian turmeric, Markov chain model, Agricultural and Food Policy, Q13, Q17,
On the shape of the mass-function of dense clumps in the Hi-GAL fields. II. Using Bayesian inference to study the clump mass function
Context. Stars form in dense, dusty clumps of molecular clouds, but little is
known about their origin, their evolution and their detailed physical
properties. In particular, the relationship between the mass distribution of
these clumps (also known as the "clump mass function", or CMF) and the stellar
initial mass function (IMF), is still poorly understood. Aims. In order to
better understand how the CMF evolve toward the IMF, and to discern the "true"
shape of the CMF, large samples of bona-fide pre- and proto-stellar clumps are
required. Two such datasets obtained from the Herschel infrared GALactic Plane
Survey (Hi-GAL) have been described in paper I. Robust statistical methods are
needed in order to infer the parameters describing the models used to fit the
CMF, and to compare the competing models themselves. Methods. In this paper we
apply Bayesian inference to the analysis of the CMF of the two regions
discussed in Paper I. First, we determine the Bayesian posterior probability
distribution for each of the fitted parameters. Then, we carry out a
quantitative comparison of the models used to fit the CMF. Results. We have
compared the results from several methods implementing Bayesian inference, and
we have also analyzed the impact of the choice of priors and the influence of
various constraints on the statistical conclusions for the preferred values of
the parameters. We find that both parameter estimation and model comparison
depend on the choice of parameter priors. Conclusions. Our results confirm our
earlier conclusion that the CMFs of the two Hi-GAL regions studied here have
very similar shapes but different mass scales. Furthermore, the lognormal model
appears to better describe the CMF measured in the two Hi-GAL regions studied
here. However, this preliminary conclusion is dependent on the choice of
parameters priors.Comment: Submitted for publication to A&A on November 12, 2013. This paper
contains 11 pages and 7 figure
Context-Free Path Queries on RDF Graphs
Navigational graph queries are an important class of queries that canextract
implicit binary relations over the nodes of input graphs. Most of the
navigational query languages used in the RDF community, e.g. property paths in
W3C SPARQL 1.1 and nested regular expressions in nSPARQL, are based on the
regular expressions. It is known that regular expressions have limited
expressivity; for instance, some natural queries, like same generation-queries,
are not expressible with regular expressions. To overcome this limitation, in
this paper, we present cfSPARQL, an extension of SPARQL query language equipped
with context-free grammars. The cfSPARQL language is strictly more expressive
than property paths and nested expressions. The additional expressivity can be
used for modelling graph similarities, graph summarization and ontology
alignment. Despite the increasing expressivity, we show that cfSPARQL still
enjoys a low computational complexity and can be evaluated efficiently.Comment: 25 page
On the nature of the phase transition in the three-dimensional random field Ising model
A brief survey of the theoretical, numerical and experimental studies of the
random field Ising model during last three decades is given. Nature of the
phase transition in the three-dimensional RFIM with Gaussian random fields is
discussed. Using simple scaling arguments it is shown that if the strength of
the random fields is not too small (bigger than a certain threshold value) the
finite temperature phase transition in this system is equivalent to the
low-temperature order-disorder transition which takes place at variations of
the strength of the random fields. Detailed study of the zero-temperature phase
transition in terms of simple probabilistic arguments and modified mean-field
approach (which take into account nearest-neighbors spin-spin correlations) is
given. It is shown that if all thermally activated processes are suppressed the
ferromagnetic order parameter m(h) as the function of the strength of the
random fields becomes history dependent. In particular, the behavior of the
magnetization curves m(h) for increasing and for decreasing reveals the
hysteresis loop.Comment: 22 pages, 12 figure
Ground state numerical study of the three-dimensional random field Ising model
The random field Ising model in three dimensions with Gaussian random fields
is studied at zero temperature for system sizes up to 60^3. For each
realization of the normalized random fields, the strength of the random field,
Delta and a uniform external, H is adjusted to find the finite-size critical
point. The finite-size critical point is identified as the point in the H-Delta
plane where three degenerate ground states have the largest discontinuities in
the magnetization. The discontinuities in the magnetization and bond energy
between these ground states are used to calculate the magnetization and
specific heat critical exponents and both exponents are found to be near zero.Comment: 10 pages, 6 figures; new references and small changes to tex
Spontaneous magnetization of the Ising model on the Sierpinski carpet fractal, a rigorous result
We give a rigorous proof of the existence of spontaneous magnetization at
finite temperature for the Ising spin model defined on the Sierpinski carpet
fractal. The theorem is inspired by the classical Peierls argument for the two
dimensional lattice. Therefore, this exact result proves the existence of
spontaneous magnetization for the Ising model in low dimensional structures,
i.e. structures with dimension smaller than 2.Comment: 14 pages, 8 figure
Multifractals of Normalized First Passage Time in Sierpinski Gasket
The multifractal behavior of the normalized first passage time is
investigated on the two dimensional Sierpinski gasket with both absorbing and
reflecting barriers. The normalized first passage time for Sinai model and the
logistic model to arrive at the absorbing barrier after starting from an
arbitrary site, especially obtained by the calculation via the Monte Carlo
simulation, is discussed numerically. The generalized dimension and the
spectrum are also estimated from the distribution of the normalized first
passage time, and compared with the results on the finitely square lattice.Comment: 10 pages, Latex, with 3 figures and 1 table. to be published in J.
Phys. Soc. Jpn. Vol.67(1998
Predicting the impact of feedback on matter clustering with machine learning in CAMELS
Extracting information from the total matter power spectrum with the
precision needed for upcoming cosmological surveys requires unraveling the
complex effects of galaxy formation processes on the distribution of matter. We
investigate the impact of baryonic physics on matter clustering at using
a library of power spectra from the Cosmology and Astrophysics with MachinE
Learning Simulations (CAMELS) project, containing thousands of volume realizations with varying cosmology, initial random field,
stellar and AGN feedback strength and sub-grid model implementation methods. We
show that baryonic physics affects matter clustering on scales and the magnitude of this effect is dependent on the
details of the galaxy formation implementation and variations of cosmological
and astrophysical parameters. Increasing AGN feedback strength decreases halo
baryon fractions and yields stronger suppression of power relative to N-body
simulations, while stronger stellar feedback often results in weaker effects by
suppressing black hole growth and therefore the impact of AGN feedback. We find
a broad correlation between mean baryon fraction of massive halos (\,\Msun) and suppression of matter clustering but with
significant scatter compared to previous work owing to wider exploration of
feedback parameters and cosmic variance effects. We show that a random forest
regressor trained on the baryon content and abundance of halos across the full
mass range \Msun can predict the
effect of galaxy formation on the matter power spectrum on scales --20.0\,
Domestic pig prioritized in One Health action against fascioliasis in human endemic areas : experimental assessment of transmission capacity and epidemiological evaluation of reservoir role.
The Northern Bolivian Altiplano is the human fascioliasis hyperendemic area where the highest prevalences and intensities in humans have been reported. Preventive chemotherapy was implemented in the last ten years. Surveillance showed high human infection and re-infection rates in between the annual triclabendazole monodose treatments. A complementary One Health control action was launched to decrease the infection risk. Among the multidisciplinary axes, there is the need to establish animal reservoir species priorities for a more efficient control. Laboratory and field studies were performed for the first time to assess the Fasciola hepatica transmission capacity of the pig and its potential reservoir role. The experimental follow-up of altiplanic pig isolates through altiplanic Galba truncatula snail vector isolates were performed at different miracidial doses and different day/ night temperatures. Experiments included egg embryonation, miracidial infectivity, lymnaeid snail infection, intramolluscan larval development, cercarial production, chronobiology of the cercarial shedding, vector survival to infection, metacercarial infectivity of mammal host, and adult stage development. Surveys included the assessment of prevalence, intensity, egg measurements and egg shedding rates in nature. Pig contribution was evaluated by comparing with the main altiplanic reservoirs sheep and cattle. Results demonstrated that the pig assures the whole F. hepatica life cycle and participates in its transmission in this area. The fast egg embryonation, high cercarial production, long multi-wave shedding chronobiological pattern in monomiracidial infections at permanent 20 ◦C temperature, and the high daily egg outputs per pig are worth mentioning. The high infection risk suggests early infection of freely running piglets and evolutionary long-term adaptation of the liver fluke to this omnivorous mammal, despite its previously evoked resistance or non-suitability. Genetic, physiological and immune similarities with humans may also underlie the parasite adaptation to humans in this area. The pig should be accordingly included for appropriate control measures within a One Health action against human fascioliasis. The pig should henceforth be considered in epidemiological studies and control initiatives not only in fascioliasis endemic areas with human infection risk on other Andean countries, but also in rural areas of Latin America, Africa and Asia where domestic pigs are allowed to run freely
On large deviation properties of Erdos-Renyi random graphs
We show that large deviation properties of Erd\"os-R\'enyi random graphs can
be derived from the free energy of the -state Potts model of statistical
mechanics. More precisely the Legendre transform of the Potts free energy with
respect to is related to the component generating function of the graph
ensemble. This generalizes the well-known mapping between typical properties of
random graphs and the limit of the Potts free energy. For
exponentially rare graphs we explicitly calculate the number of components, the
size of the giant component, the degree distributions inside and outside the
giant component, and the distribution of small component sizes. We also perform
numerical simulations which are in very good agreement with our analytical
work. Finally we demonstrate how the same results can be derived by studying
the evolution of random graphs under the insertion of new vertices and edges,
without recourse to the thermodynamics of the Potts model.Comment: 38 pages, 9 figures, Latex2e, corrected and extended version
including numerical simulation result
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