14,169 research outputs found
Sign-time distributions for interface growth
We apply the recently introduced distribution of sign-times (DST) to
non-equilibrium interface growth dynamics. We are able to treat within a
unified picture the persistence properties of a large class of relaxational and
noisy linear growth processes, and prove the existence of a non-trivial scaling
relation. A new critical dimension is found, relating to the persistence
properties of these systems. We also illustrate, by means of numerical
simulations, the different types of DST to be expected in both linear and
non-linear growth mechanisms.Comment: 4 pages, 5 ps figs, replaced misprint in authors nam
On the optimality of gluing over scales
We show that for every , there exist -point metric spaces
(X,d) where every "scale" admits a Euclidean embedding with distortion at most
, but the whole space requires distortion at least . This shows that the scale-gluing lemma [Lee, SODA 2005] is tight,
and disproves a conjecture stated there. This matching upper bound was known to
be tight at both endpoints, i.e. when and , but nowhere in between.
More specifically, we exhibit -point spaces with doubling constant
requiring Euclidean distortion ,
which also shows that the technique of "measured descent" [Krauthgamer, et.
al., Geometric and Functional Analysis] is optimal. We extend this to obtain a
similar tight result for spaces with .Comment: minor revision
An ultrametric state space with a dense discrete overlap distribution: Paperfolding sequences
We compute the Parisi overlap distribution for paperfolding sequences. It
turns out to be discrete, and to live on the dyadic rationals. Hence it is a
pure point measure whose support is the full interval [-1; +1]. The space of
paperfolding sequences has an ultrametric structure. Our example provides an
illustration of some properties which were suggested to occur for pure states
in spin glass models
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Prevalence and determinants of anxiety and depression in end stage renal disease (ESRD). A comparison between ESRD patients with and without coexisting diabetes mellitus
Objective: To compare anxiety and/or depressive symptoms between patients with end-stage renal disease with and without comorbid diabetes and identify factors associated with symptoms of distress in this population.
Methods: Data from two studies (conducted between 2010 and 2014) were pooled. A total of 526 patients on hemodialysis (68.8% with diabetes) completed the Hospital Anxiety and Depression Scale (HADS). Elevated symptoms were defined as HADS-Anxiety or HADS-Depression ≥ 8. Univariate and multivariate logistic regressions were used to estimate associations between diabetic status, and other socio-demographic and clinical factors with baseline clinical anxiety and depression.
Results: A total of 233 (45.4%) reported elevated anxiety symptoms and 256 (49.9%) reported elevated depressive symptoms sufficient for caseness. Rates were not different between patients with and without diabetes. Risk for clinical depression was higher in patients who were single/unpartnered (OR = 1.828), Chinese vs. Malay (OR = 2.05), or had lower albumin levels (OR = 0.932). None of the parameters were associated with anxiety caseness.
Conclusion: Sociocultural factors rather than comorbid burden may help identify patients at risk for depression. The high rates of anxiety and depression underlie the importance for monitoring and intervention in dialysis care
Link-space formalism for network analysis
We introduce the link-space formalism for analyzing network models with
degree-degree correlations. The formalism is based on a statistical description
of the fraction of links l_{i,j} connecting nodes of degrees i and j. To
demonstrate its use, we apply the framework to some pedagogical network models,
namely, random-attachment, Barabasi-Albert preferential attachment and the
classical Erdos and Renyi random graph. For these three models the link-space
matrix can be solved analytically. We apply the formalism to a simple
one-parameter growing network model whose numerical solution exemplifies the
effect of degree-degree correlations for the resulting degree distribution. We
also employ the formalism to derive the degree distributions of two very simple
network decay models, more specifically, that of random link deletion and
random node deletion. The formalism allows detailed analysis of the
correlations within networks and we also employ it to derive the form of a
perfectly non-assortative network for arbitrary degree distribution.Comment: This updated version has been expanded to include a number of new
results. 19 pages, 11 figures. Minor Typos correcte
Sandpiles on multiplex networks
We introduce the sandpile model on multiplex networks with more than one type
of edge and investigate its scaling and dynamical behaviors. We find that the
introduction of multiplexity does not alter the scaling behavior of avalanche
dynamics; the system is critical with an asymptotic power-law avalanche size
distribution with an exponent on duplex random networks. The
detailed cascade dynamics, however, is affected by the multiplex coupling. For
example, higher-degree nodes such as hubs in scale-free networks fail more
often in the multiplex dynamics than in the simplex network counterpart in
which different types of edges are simply aggregated. Our results suggest that
multiplex modeling would be necessary in order to gain a better understanding
of cascading failure phenomena of real-world multiplex complex systems, such as
the global economic crisis.Comment: 7 pages, 7 figure
Diffusive persistence and the `sign-time' distribution
We present a new method for extracting the persistence exponent theta for the
diffusion equation, based on the distribution P of `sign-times'. With the aid
of a numerically verified Ansatz for P we derive an exact formula for theta in
arbitrary spatial dimension d. Our results are in excellent agreement with
previous numerical studies. Furthermore, our results indicate a qualitative
change in P above d ~ 36, signalling the existence of a sharp change in the
ergodic properties of the diffusion field.Comment: 5 pages, 2 tar gzip figures (Latex), subm. to PRE (Rapid Comm), new
reference adde
Transport of multiple users in complex networks
We study the transport properties of model networks such as scale-free and
Erd\H{o}s-R\'{e}nyi networks as well as a real network. We consider the
conductance between two arbitrarily chosen nodes where each link has the
same unit resistance. Our theoretical analysis for scale-free networks predicts
a broad range of values of , with a power-law tail distribution , where , and is the decay
exponent for the scale-free network degree distribution. We confirm our
predictions by large scale simulations. The power-law tail in leads to large values of , thereby significantly improving the
transport in scale-free networks, compared to Erd\H{o}s-R\'{e}nyi networks
where the tail of the conductivity distribution decays exponentially. We
develop a simple physical picture of the transport to account for the results.
We study another model for transport, the \emph{max-flow} model, where
conductance is defined as the number of link-independent paths between the two
nodes, and find that a similar picture holds. The effects of distance on the
value of conductance are considered for both models, and some differences
emerge. We then extend our study to the case of multiple sources, where the
transport is define between two \emph{groups} of nodes. We find a fundamental
difference between the two forms of flow when considering the quality of the
transport with respect to the number of sources, and find an optimal number of
sources, or users, for the max-flow case. A qualitative (and partially
quantitative) explanation is also given
Evolution of scale-free random graphs: Potts model formulation
We study the bond percolation problem in random graphs of weighted
vertices, where each vertex has a prescribed weight and an edge can
connect vertices and with rate . The problem is solved by the
limit of the -state Potts model with inhomogeneous interactions for
all pairs of spins. We apply this approach to the static model having
so that the resulting graph is scale-free with
the degree exponent . The number of loops as well as the giant
cluster size and the mean cluster size are obtained in the thermodynamic limit
as a function of the edge density, and their associated critical exponents are
also obtained. Finite-size scaling behaviors are derived using the largest
cluster size in the critical regime, which is calculated from the cluster size
distribution, and checked against numerical simulation results. We find that
the process of forming the giant cluster is qualitatively different between the
cases of and . While for the former, the giant
cluster forms abruptly at the percolation transition, for the latter, however,
the formation of the giant cluster is gradual and the mean cluster size for
finite shows double peaks.Comment: 34 pages, 9 figures, elsart.cls, final version appeared in NP
Assessing Authentically – Learnings From Marketing Educators
This paper demonstrates the importance and role of authentic assessments, that replicate industry practice, within Higher Education marketing programmes. We answer the call from employers, that students need to gain much-needed employability skills, and we illustrate how such assessments can be created to enable the development of employability skills. We provide an overview of four case studies, to illustrate different forms of authentic assessments, the theory which was used to underpin the designs, the skills developed during the assessments, and the outcomes of the assessments. As we emerge from the COVID-19 pandemic, which forced a move to online assessments, it is timely that we reflect on the value of authentic assessments and adjust our practice
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