1,533 research outputs found
Containing epidemic outbreaks by message-passing techniques
The problem of targeted network immunization can be defined as the one of
finding a subset of nodes in a network to immunize or vaccinate in order to
minimize a tradeoff between the cost of vaccination and the final (stationary)
expected infection under a given epidemic model. Although computing the
expected infection is a hard computational problem, simple and efficient
mean-field approximations have been put forward in the literature in recent
years. The optimization problem can be recast into a constrained one in which
the constraints enforce local mean-field equations describing the average
stationary state of the epidemic process. For a wide class of epidemic models,
including the susceptible-infected-removed and the
susceptible-infected-susceptible models, we define a message-passing approach
to network immunization that allows us to study the statistical properties of
epidemic outbreaks in the presence of immunized nodes as well as to find
(nearly) optimal immunization sets for a given choice of parameters and costs.
The algorithm scales linearly with the size of the graph and it can be made
efficient even on large networks. We compare its performance with topologically
based heuristics, greedy methods, and simulated annealing
Flight of the dragonflies and damselflies
This work is a synthesis of our current understanding of the mechanics, aerodynamics and visually mediated control of dragonfly and damselfly flight, with the addition of new experimental and computational data in several key areas. These are: the diversity of dragonfly wing morphologies, the aerodynamics of gliding flight, force generation in flapping flight, aerodynamic efficiency, comparative flight performance and pursuit strategies during predatory and territorial flights. New data are set in context by brief reviews covering anatomy at several scales, insect aerodynamics, neuromechanics and behaviour. We achieve a new perspective by means of a diverse range of techniques, including laser-line mapping of wing topographies, computational fluid dynamics simulations of finely detailed wing geometries, quantitative imaging using particle image velocimetry of on-wing and wake flow patterns, classical aerodynamic theory, photography in the field, infrared motion capture and multi-camera optical tracking of free flight trajectories in laboratory environments. Our comprehensive approach enables a novel synthesis of datasets and subfields that integrates many aspects of flight from the neurobiology of the compound eye, through the aeromechanical interface with the surrounding fluid, to flight performance under cruising and higher-energy behavioural modes
Containing Epidemic Outbreaks by Message-Passing Techniques
The problem of targeted network immunization can be defined as the one of finding a subset of nodes in a network to immunize or vaccinate in order to minimize a tradeoff between the cost of vaccination and the final (stationary) expected infection under a given epidemic model. Although computing the expected infection is a hard computational problem, simple and efficient mean-field approximations have been put forward in the literature in recent years. The optimization problem can be recast into a constrained one in which the constraints enforce local mean-field equations describing the average stationary state of the epidemic process. For a wide class of epidemic models, including the susceptible-infected-removed and the susceptible-infected-susceptible models, we define a message-passing approach to network immunization that allows us to study the statistical properties of epidemic outbreaks in the presence of immunized nodes as well as to find (nearly) optimal immunization sets for a given choice of parameters and costs. The algorithm scales linearly with the size of the graph, and it can be made efficient even on large networks. We compare its performance with topologically based heuristics, greedy methods, and simulated annealing on both random graphs and real-world networks
Suppression of properties associated with malignancy in murine melanoma-melanocyte hybrid cells.
Murine and human melanoma cells differ relatively reliably from non-tumorigenic melanocytes in certain biological properties. When cultured at low pH, melanocytes tend to be pigmented and melanoma cells unpigmented. The growth of virtually all metastatic melanoma cells is inhibited by phorbol esters such as TPA (12-O-tetradecanoyl phorbol-13-acetate), which stimulate melanocyte growth. Melanocytes fail to grow in suspension culture or produce tumours when implanted in animals, while many melanoma lines can do both. Here we studied which of these properties were dominant in hybrid cells formed by fusion of drug-resistant murine B16-F10RR melanoma cells to melanocytes of the albino and brown lines, melan-c and melan-b. The albino melanocytes are unpigmented but well-differentiated, the brown melanocytes produce pale brown pigment and the melanoma cells are unpigmented under the conditions used. All hybrid colonies observed produced black pigment, except some melan-b/melanoma hybrids when growing sparsely with TPA. Thus pigmentation was generally dominant. 14/15 hybrid lines showed stimulation of proliferation by TPA, as do melanocytes. Most hybrid lines showed no or reduced capacity for growth in suspension, though some grew better in suspension when TPA was present. There was marked suppression of the tumorigenicity of the parental melanoma cells in 4/8 hybrids examined, and tumorigenicity was reduced in the others, despite considerable chromosome loss by the passage level tested. Thus most properties of the non-tumorigenic pigment cells were dominant, as often observed for other cell lineages, and providing further evidence for gene loss in the genesis of malignant melanoma
Open access megajournals: The publisher perspective (Part 2: Operational realities)
This paper is the second of two Learned Publishing articles in which we report the results of a series of interviews, with senior publishers and editors exploring open access megajournals (OAMJs). Megajournals (of which PLoS One is the best known example) represent a relatively new approach to scholarly communication and can be characterized as large, broad-scope, open access journals, which take an innovative approach to peer review, basing acceptance decisions solely on the technical or scientific soundness of the article. Based on interviews with 31 publishers and editors, this paper reports the perceived cultural, operational, and technical challenges associated with launching, growing, and maintaining a megajournal. We find that overcoming these challenges while delivering the societal benefits associated with OAMJs is seen to require significant investment in people and systems, as well as an ongoing commitment to the model
Open-access mega-journals
Purpose: Open-access mega-journals (OAMJs) represent an increasingly important part of the scholarly communication landscape. OAMJs, such as PLOS ONE, are large scale, broad scope journals that operate an open access business model (normally based on article-processing charges), and which employ a novel form of peer review, focusing on scientific ‘soundness’ and eschewing judgment of novelty or importance. This paper examines the discourses relating to OAMJs, and their place within scholarly publishing, and considers attitudes towards mega-journals within the academic community.
Design/methodology/approach: This paper presents a review of the literature of OAMJs structured around four defining characteristics: scale, disciplinary scope, peer review policy and economic model. The existing scholarly literature was augmented by searches of more informal outputs, such as blogs and email discussion lists, to capture the debate in its entirety.
Findings: While the academic literature relating specifically to OAMJs is relatively sparse, discussion in other fora is detailed and animated, with debates ranging from the sustainability and ethics of the mega-journal model, to the impact of soundness-only peer review on article quality and discoverability, and the potential for OAMJs to represent a paradigm-shifting development in scholarly publishing.
Originality/value: This article represents the first comprehensive review of the mega-journal phenomenon, drawing not only on the published academic literature, but also grey, professional and informal sources. The paper advances a number of ways in which the role of OAMJs in the scholarly communication environment can be conceptualised
Open access megajournals: The publisher perspective (Part 1: Motivations)
This paper is the first of two Learned Publishing articles in which we report the results of a series of interviews with senior publishers and editors exploring open access megajournals (OAMJs). Megajournals (of which PLoS One is the best known example) represent a relatively new approach to scholarly communication and can be characterized as large, broad-scope, open access journals that take an innovative approach to peer review, basing acceptance decisions solely on the technical or scientific soundness of the article. This model is often said to support the broader goals of the open science movement. Based on in-depth interviews with 31 publishers and editors representing 16 different organizations (10 of which publish a megajournal), this paper reports how the term ‘megajournal’ is understood and publishers’ rationale and motivations for launching (or not launching) an OAMJ. We find that while there is general agreement on the common characteristics of megajournals, there is not yet a consensus on their relative importance. We also find seven motivating factors that were said to drive the launch of an OAMJ and link each of these factors to potential societal and business benefits. These results suggest that the often polarized debate surrounding OAMJs is a consequence of the extent to which observers perceive publishers to be motivated by these societal or business benefits
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