7,560 research outputs found
A tractable genotype-phenotype map for the self-assembly of protein quaternary structure
The mapping between biological genotypes and phenotypes is central to the
study of biological evolution. Here we introduce a rich, intuitive, and
biologically realistic genotype-phenotype (GP) map, that serves as a model of
self-assembling biological structures, such as protein complexes, and remains
computationally and analytically tractable. Our GP map arises naturally from
the self-assembly of polyomino structures on a 2D lattice and exhibits a number
of properties: (genotypes vastly outnumber phenotypes),
(genotypic redundancy varies greatly between
phenotypes), (phenotypes consist
of disconnected mutational networks) and (most
phenotypes can be reached in a small number of mutations). We also show that
the mutational robustness of phenotypes scales very roughly logarithmically
with phenotype redundancy and is positively correlated with phenotypic
evolvability. Although our GP map describes the assembly of disconnected
objects, it shares many properties with other popular GP maps for connected
units, such as models for RNA secondary structure or the HP lattice model for
protein tertiary structure. The remarkable fact that these important properties
similarly emerge from such different models suggests the possibility that
universal features underlie a much wider class of biologically realistic GP
maps.Comment: 12 pages, 6 figure
Instability of the massive Klein-Gordon field on the Kerr spacetime
We investigate the instability of the massive scalar field in the vicinity of
a rotating black hole. The instability arises from amplification caused by the
classical superradiance effect. The instability affects bound states: solutions
to the massive Klein-Gordon equation which tend to zero at infinity. We
calculate the spectrum of bound state frequencies on the Kerr background using
a continued fraction method, adapted from studies of quasinormal modes. We
demonstrate that the instability is most significant for the ,
state, for . For a fast rotating hole () we find
a maximum growth rate of ,
at . The physical implications are discussed.Comment: Added references. 27 pages, 7 figure
A framework for the construction of generative models for mesoscale structure in multilayer networks
Multilayer networks allow one to represent diverse and coupled connectivity patterns—such as time-dependence, multiple subsystems, or both—that arise in many applications and which are difficult or awkward to incorporate into standard network representations. In the study of multilayer networks, it is important to investigate mesoscale (i.e., intermediate-scale) structures, such as dense sets of nodes known as communities, to discover network features that are not apparent at the microscale or the macroscale. The ill-defined nature of mesoscale structure and its ubiquity in empirical networks make it crucial to develop generative models that can produce the features that one encounters in empirical networks. Key purposes of such models include generating synthetic networks with empirical properties of interest, benchmarking mesoscale-detection methods and algorithms, and inferring structure in empirical multilayer networks. In this paper, we introduce a framework for the construction of generative models for mesoscale structures in multilayer networks. Our framework provides a standardized set of generative models, together with an associated set of principles from which they are derived, for studies of mesoscale structures in multilayer networks. It unifies and generalizes many existing models for mesoscale structures in fully ordered (e.g., temporal) and unordered (e.g., multiplex) multilayer networks. One can also use it to construct generative models for mesoscale structures in partially ordered multilayer networks (e.g., networks that are both temporal and multiplex). Our framework has the ability to produce many features of empirical multilayer networks, and it explicitly incorporates a user-specified dependency structure between layers. We discuss the parameters and properties of our framework, and we illustrate examples of its use with benchmark models for community-detection methods and algorithms in multilayer networks
Strong correlation effects in single-wall carbon nanotubes
We present an overview of strong correlations in single-wall carbon
nanotubes, and an introduction to the techniques used to study them
theoretically. We concentrate on zigzag nanotubes, although universality
dictates that much ofthe theory can also be applied to armchair or chiral
nanotubes. We show how interaction effects lead to exotic low energy properties
and discuss future directions for studies on correlation effects in nanotubes
Customer mobility and congestion in supermarkets
The analysis and characterization of human mobility using population-level
mobility models is important for numerous applications, ranging from the
estimation of commuter flows in cities to modeling trade flows between
countries. However, almost all of these applications have focused on large
spatial scales, which typically range between intra-city scales to
inter-country scales. In this paper, we investigate population-level human
mobility models on a much smaller spatial scale by using them to estimate
customer mobility flow between supermarket zones. We use anonymized, ordered
customer-basket data to infer empirical mobility flow in supermarkets, and we
apply variants of the gravity and intervening-opportunities models to fit this
mobility flow and estimate the flow on unseen data. We find that a
doubly-constrained gravity model and an extended radiation model (which is a
type of intervening-opportunities model) can successfully estimate 65--70\% of
the flow inside supermarkets. Using a gravity model as a case study, we then
investigate how to reduce congestion in supermarkets using mobility models. We
model each supermarket zone as a queue, and we use a gravity model to identify
store layouts with low congestion, which we measure either by the maximum
number of visits to a zone or by the total mean queue size. We then use a
simulated-annealing algorithm to find store layouts with lower congestion than
a supermarket's original layout. In these optimized store layouts, we find that
popular zones are often in the perimeter of a store. Our research gives insight
both into how customers move in supermarkets and into how retailers can arrange
stores to reduce congestion. It also provides a case study of human mobility on
small spatial scales
Sds22 regulates aurora B activity and microtubule-kinetochore interactions at mitosis
Sds22 defines protein phosphatase 1 location and function at kinetochores and subsequent activity of aurora B in mitosis
Application of Edwards' statistical mechanics to high dimensional jammed sphere packings
The isostatic jamming limit of frictionless spherical particles from Edwards'
statistical mechanics [Song \emph{et al.}, Nature (London) {\bf 453}, 629
(2008)] is generalized to arbitrary dimension using a liquid-state
description. The asymptotic high-dimensional behavior of the self-consistent
relation is obtained by saddle-point evaluation and checked numerically. The
resulting random close packing density scaling is
consistent with that of other approaches, such as replica theory and density
functional theory. The validity of various structural approximations is
assessed by comparing with three- to six-dimensional isostatic packings
obtained from simulations. These numerical results support a growing accuracy
of the theoretical approach with dimension. The approach could thus serve as a
starting point to obtain a geometrical understanding of the higher-order
correlations present in jammed packings.Comment: 13 pages, 7 figure
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