1,420 research outputs found
First report of groundnut ringspot orthotospovirus infecting field pea (Pisum sativum L.) crop in Brazil.
Field pea (Pisum sativum L.) cultivar Axé with symptoms of orthotospovirus infection (~5% incidence) were collected under open field conditions in Brasília-DF, Central Brazil. Ten leaf samples displaying apical chlorosis, necrosis, and deformation were evaluated via serology (ELISA) using antisera (produced at Embrapa Vegetable Crops) specific to the nucleocapsid (N) protein of three Orthotospovirus species: Tomato chlorotic spot orthotospovirus (TCSV), Tomato spotted wilt orthotospovirus (TSWV), and Groundnut ringspot orthotospovirus (GRSV)
Exceptional Times for the Dynamical Discrete Web
The dynamical discrete web (DyDW),introduced in recent work of Howitt and
Warren, is a system of coalescing simple symmetric one-dimensional random walks
which evolve in an extra continuous dynamical time parameter \tau. The
evolution is by independent updating of the underlying Bernoulli variables
indexed by discrete space-time that define the discrete web at any fixed \tau.
In this paper, we study the existence of exceptional (random) values of \tau
where the paths of the web do not behave like usual random walks and the
Hausdorff dimension of the set of exceptional such \tau. Our results are
motivated by those about exceptional times for dynamical percolation in high
dimension by H\"{a}ggstrom, Peres and Steif, and in dimension two by Schramm
and Steif. The exceptional behavior of the walks in the DyDW is rather
different from the situation for the dynamical random walks of Benjamini,
H\"{a}ggstrom, Peres and Steif. For example, we prove that the walk from the
origin S^\tau_0 violates the law of the iterated logarithm (LIL) on a set of
\tau of Hausdorff dimension one. We also discuss how these and other results
extend to the dynamical Brownian web, the natural scaling limit of the DyDW
Special section on biological control.
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Strategies supporting the prevention and control of neglected tropical diseases during and beyond the COVID-19 pandemic
Emerging and re-emerging zoonotic diseases represent a public health challenge of international concern. They include a large group of neglected tropical diseases (NTDs), many of which are of zoonotic nature. Coronavirus disease 2019 (COVID-19), another emerging zoonotic disease, has just increased the stakes exponentially. Most NTDs are subject to the impact of some of the very same human-related activities triggering other emerging and re-emerging diseases, including COVID-19, severe acute respiratory syndrome (SARS), bird flu and swine flu. It is conceivable that COVID-19 will exacerbate the NTDs, as it will divert much needed financial and human resources. There is considerable concern that recent progress achieved with control and elimination efforts will be reverted. Future potential strategies will need to reconsider the determinants of health in NTDs in order to galvanize efforts and come up with a comprehensive, well defined programme that will set the stage for an effective multi-sectorial approach. In this Commentary, we propose areas of potential synergies between the COVID-19 pandemic control efforts, other health and non-health sector initiatives and NTD control and elimination programmes
Majority Dynamics and Aggregation of Information in Social Networks
Consider n individuals who, by popular vote, choose among q >= 2
alternatives, one of which is "better" than the others. Assume that each
individual votes independently at random, and that the probability of voting
for the better alternative is larger than the probability of voting for any
other. It follows from the law of large numbers that a plurality vote among the
n individuals would result in the correct outcome, with probability approaching
one exponentially quickly as n tends to infinity. Our interest in this paper is
in a variant of the process above where, after forming their initial opinions,
the voters update their decisions based on some interaction with their
neighbors in a social network. Our main example is "majority dynamics", in
which each voter adopts the most popular opinion among its friends. The
interaction repeats for some number of rounds and is then followed by a
population-wide plurality vote.
The question we tackle is that of "efficient aggregation of information": in
which cases is the better alternative chosen with probability approaching one
as n tends to infinity? Conversely, for which sequences of growing graphs does
aggregation fail, so that the wrong alternative gets chosen with probability
bounded away from zero? We construct a family of examples in which interaction
prevents efficient aggregation of information, and give a condition on the
social network which ensures that aggregation occurs. For the case of majority
dynamics we also investigate the question of unanimity in the limit. In
particular, if the voters' social network is an expander graph, we show that if
the initial population is sufficiently biased towards a particular alternative
then that alternative will eventually become the unanimous preference of the
entire population.Comment: 22 page
Thermal phase diagrams of columnar liquid crystals
In order to understand the possible sequence of transitions from the
disordered columnar phase to the helical phase in hexa(hexylthio)triphenylene
(HHTT), we study a three-dimensional planar model with octupolar interactions
inscribed on a triangular lattice of columns. We obtain thermal phase diagrams
using a mean-field approximation and Monte Carlo simulations. These two
approaches give similar results, namely, in the quasi one-dimensional regime,
as the temperature is lowered, the columns order with a linear polarization,
whereas helical phases develop at lower temperatures. The helicity patterns of
the helical phases are determined by the exact nature of the frustration in the
system, itself related to the octupolar nature of the molecules.Comment: 12 pages, 9 figures, ReVTe
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