193 research outputs found
A concentration phenomenon for semilinear elliptic equations
For a domain \Omega\subset\dR^N we consider the equation -\Delta u +
V(x)u = Q_n(x)\abs{u}^{p-2}u with zero Dirichlet boundary conditions and
. Here and are bounded functions that are positive
in a region contained in and negative outside, and such that the sets
shrink to a point as . We show that if
is a nontrivial solution corresponding to , then the sequence
concentrates at with respect to the and certain
-norms. We also show that if the sets shrink to two points and
are ground state solutions, then they concentrate at one of these points
Global bifurcation for asymptotically linear Schr\"odinger equations
We prove global asymptotic bifurcation for a very general class of
asymptotically linear Schr\"odinger equations \begin{equation}\label{1}
\{{array}{lr} \D u + f(x,u)u = \lam u \quad \text{in} \ {\mathbb R}^N, u \in
H^1({\mathbb R}^N)\setmimus\{0\}, \quad N \ge 1. {array}. \end{equation} The
method is topological, based on recent developments of degree theory. We use
the inversion in an appropriate Sobolev space
, and we first obtain bifurcation from the line of
trivial solutions for an auxiliary problem in the variables (\lambda,v) \in
{\mathbb R} \x X. This problem has a lack of compactness and of regularity,
requiring a truncation procedure. Going back to the original problem, we obtain
global branches of positive/negative solutions 'bifurcating from infinity'. We
believe that, for the values of covered by our bifurcation approach,
the existence result we obtain for positive solutions of \eqref{1} is the most
general so fa
Homoeologous chromosomal location of the genes encoding thionins in wheat and rye
Thionins are high sulphur basic polypeptides present in the endosperm of Gramineae. In wheat there are three thionins encoded by genes located in the long arms of chromosomes 1A, 1B and 1D. Rye has one thionin encoded by a gene which has been assigned to chromosome 1R after analysis of the Imperial-Chinese Spring rye-wheat disomic addition lines. Commercial varieties and experimental stocks with a 1B/1R substitution carry the thionin from rye ( R) instead of the B thionin from wheat. The R thionin gene is not located in the large chromosomal segment representing most of the short arm of chromosome 1R
Ulcerative Colitis Physician Team-Work in the Treatment
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68011/2/10.1177_000992286400300203.pd
Reptiles as food: Predation of Australian reptiles by introduced red foxes compounds and complements predation by cats
Context: Invasive species are a major cause of biodiversity loss across much of the world, and a key threat to Australia’s diverse reptile fauna. There has been no previous comprehensive analysis of the potential impact of the introduced European red fox, Vulpes vulpes, on Australian reptiles.
Aims: We seek to provide an inventory of all Australian reptile species known to be consumed by the fox, and identify characteristics of squamate species associated with such predation. We also compare these tallies and characteristics with reptile species known to be consumed by the domestic cat, Felis catus, to examine whether predation by these two introduced species is compounded (i.e. affecting much the same set of species) or complementary (affecting different groups of species).
Methods: We collated records of Australian reptiles consumed by foxes in Australia, with most records deriving from fox dietary studies (tallying >35 000 samples). We modelled presence or absence of fox predation records against a set of biological and other traits, and population trends, for squamate species.
Key results: In total, 108 reptile species (~11% of Australia’s terrestrial reptile fauna) have been recorded as consumed by foxes, fewer than that reported for cats (263 species). Eighty-six species have been reported to be eaten by both predators. More Australian turtle species have been reported as consumed by foxes than by cats, including many that suffer high levels of predation on egg clutches. Twenty threatened reptile species have been reported as consumed by foxes, and 15 by cats. Squamate species consumed by foxes are more likely to be undergoing population decline than those not known to be consumed by foxes. The likelihood of predation by foxes increased with squamate species’ adult body mass, in contrast to the relationship for predation by cats, which peaked at ~217 g. Foxes, but not cats, were also less likely to consume venomous snakes.
Conclusions: The two introduced, and now widespread, predators have both compounding and complementary impacts on the Australian reptile fauna.
Implications: Enhanced and integrated management of the two introduced predators is likely to provide substantial conservation benefits to much of the Australian reptile fauna
Counting the bodies: Estimating the numbers and spatial variation of Australian reptiles, birds and mammals killed by two invasive mesopredators
Aim
Introduced predators negatively impact biodiversity globally, with insular fauna often most severely affected. Here, we assess spatial variation in the number of terrestrial vertebrates (excluding amphibians) killed by two mammalian mesopredators introduced to Australia, the red fox (Vulpes vulpes) and feral cat (Felis catus). We aim to identify prey groups that suffer especially high rates of predation, and regions where losses to foxes and/or cats are most substantial.
Location
Australia.
Methods
We draw information on the spatial variation in tallies of reptiles, birds and mammals killed by cats in Australia from published studies. We derive tallies for fox predation by (i) modelling continental-scale spatial variation in fox density, (ii) modelling spatial variation in the frequency of occurrence of prey groups in fox diet, (iii) analysing the number of prey individuals within dietary samples and (iv) discounting animals taken as carrion. We derive point estimates of the numbers of individuals killed annually by foxes and by cats and map spatial variation in these tallies.
Results
Foxes kill more reptiles, birds and mammals (peaking at 1071 km−2 year−1) than cats (55 km−2 year−1) across most of the unmodified temperate and forested areas of mainland Australia, reflecting the generally higher density of foxes than cats in these environments. However, across most of the continent – mainly the arid central and tropical northern regions (and on most Australian islands) – cats kill more animals than foxes. We estimate that foxes and cats together kill 697 million reptiles annually in Australia, 510 million birds and 1435 million mammals.
Main conclusions
This continental-scale analysis demonstrates that predation by two introduced species takes a substantial and ongoing toll on Australian reptiles, birds and mammals. Continuing population declines and potential extinctions of some of these species threatens to further compound Australia's poor contemporary conservation record
Towards Machine Wald
The past century has seen a steady increase in the need of estimating and
predicting complex systems and making (possibly critical) decisions with
limited information. Although computers have made possible the numerical
evaluation of sophisticated statistical models, these models are still designed
\emph{by humans} because there is currently no known recipe or algorithm for
dividing the design of a statistical model into a sequence of arithmetic
operations. Indeed enabling computers to \emph{think} as \emph{humans} have the
ability to do when faced with uncertainty is challenging in several major ways:
(1) Finding optimal statistical models remains to be formulated as a well posed
problem when information on the system of interest is incomplete and comes in
the form of a complex combination of sample data, partial knowledge of
constitutive relations and a limited description of the distribution of input
random variables. (2) The space of admissible scenarios along with the space of
relevant information, assumptions, and/or beliefs, tend to be infinite
dimensional, whereas calculus on a computer is necessarily discrete and finite.
With this purpose, this paper explores the foundations of a rigorous framework
for the scientific computation of optimal statistical estimators/models and
reviews their connections with Decision Theory, Machine Learning, Bayesian
Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty
Quantification and Information Based Complexity.Comment: 37 page
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