9 research outputs found
Dual giant gravitons in AdS Y (Sasaki-Einstein)
We consider BPS motion of dual giant gravitons on Ad where
represents a five-dimensional Sasaki-Einstein manifold. We find that the
phase space for the BPS dual giant gravitons is symplectically isomorphic to
the Calabi-Yau cone over , with the K\"{a}hler form identified with the
symplectic form. The quantization of the dual giants therefore coincides with
the K\"{a}hler quantization of the cone which leads to an explicit
correspondence between holomorphic wavefunctions of dual giants and
gauge-invariant operators of the boundary theory. We extend the discussion to
dual giants in where is a seven-dimensional
Sasaki-Einstein manifold; for special motions the phase space of the dual
giants is symplectically isomorphic to the eight-dimensional Calabi-Yau cone.Comment: 14 pages. (v2) typo's corrected; factors of AdS radius reinstated for
clarity; remarks about dual giant wavefunctions in T^{1,1} expanded and put
in a new subsectio
Counting 1/8-BPS Dual-Giants
We count 1/8-BPS states in type IIB string theory on AdS_5 x S^5 background
which carry three independent angular momenta on S^5. These states can be
counted by considering configurations of multiple dual-giant gravitons up to N
in number which share at least four supersymmetries. We map this counting
problem to that of counting the energy eigen states of a system of N bosons in
a 3-dimensional harmonic oscillator. We also count 1/8-BPS states with two
independent non-zero spins in AdS_5 and one non-zero angular momentum on S^5 by
considering configurations of arbitrary number of giant gravitons that share at
least four supersymmetries.Comment: 19 page
Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution
We compare and contrast the long-time dynamical properties of two
individual-based models of biological coevolution. Selection occurs via
multispecies, stochastic population dynamics with reproduction probabilities
that depend nonlinearly on the population densities of all species resident in
the community. New species are introduced through mutation. Both models are
amenable to exact linear stability analysis, and we compare the analytic
results with large-scale kinetic Monte Carlo simulations, obtaining the
population size as a function of an average interspecies interaction strength.
Over time, the models self-optimize through mutation and selection to
approximately maximize a community fitness function, subject only to
constraints internal to the particular model. If the interspecies interactions
are randomly distributed on an interval including positive values, the system
evolves toward self-sustaining, mutualistic communities. In contrast, for the
predator-prey case the matrix of interactions is antisymmetric, and a nonzero
population size must be sustained by an external resource. Time series of the
diversity and population size for both models show approximate 1/f noise and
power-law distributions for the lifetimes of communities and species. For the
mutualistic model, these two lifetime distributions have the same exponent,
while their exponents are different for the predator-prey model. The difference
is probably due to greater resilience toward mass extinctions in the food-web
like communities produced by the predator-prey model.Comment: 26 pages, 12 figures. Discussion of early-time dynamics added. J.
Math. Biol., in pres
Divergência genética de milho transgênico em relação à produtividade de grãos e à qualidade nutricional
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease