Sequential pattern formation governed by signaling gradients

Rhythmic and sequential segmentation of the embryonic body plan is a vital developmental patterning process in all vertebrate species. However, a theoretical framework capturing the emergence of dynamic patterns of gene expression from the interplay of cell oscillations with tissue elongation and shortening and with signaling gradients, is still missing. Here we show that a set of coupled genetic oscillators in an elongating tissue that is regulated by diffusing and advected signaling molecules can account for segmentation as a self-organized patterning process. This system can form a finite number of segments and the dynamics of segmentation and the total number of segments formed depend strongly on kinetic parameters describing tissue elongation and signaling molecules. The model accounts for existing experimental perturbations to signaling gradients, and makes testable predictions about novel perturbations. The variety of different patterns formed in our model can account for the variability of segmentation between different animal species.Comment: 12 pages, 5 figure

Epidemics on random intersection graphs

In this paper we consider a model for the spread of a stochastic SIR (Susceptible $\to$ Infectious $\to$ Recovered) epidemic on a network of individuals described by a random intersection graph. Individuals belong to a random number of cliques, each of random size, and infection can be transmitted between two individuals if and only if there is a clique they both belong to. Both the clique sizes and the number of cliques an individual belongs to follow mixed Poisson distributions. An infinite-type branching process approximation (with type being given by the length of an individual's infectious period) for the early stages of an epidemic is developed and made fully rigorous by proving an associated limit theorem as the population size tends to infinity. This leads to a threshold parameter $R_*$, so that in a large population an epidemic with few initial infectives can give rise to a large outbreak if and only if $R_*>1$. A functional equation for the survival probability of the approximating infinite-type branching process is determined; if $R_*\le1$, this equation has no nonzero solution, while if $R_*>1$, it is shown to have precisely one nonzero solution. A law of large numbers for the size of such a large outbreak is proved by exploiting a single-type branching process that approximates the size of the susceptibility set of a typical individual.Comment: Published in at http://dx.doi.org/10.1214/13-AAP942 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Star tracker operation in a high density proton field

Algorithms that reject transient signals due to proton effects on charge coupled device (CCD) sensors have been implemented in the HDOS ASTRA-l Star Trackers to be flown on the TOPEX mission scheduled for launch in July 1992. A unique technique for simulating a proton-rich environment to test trackers is described, as well as the test results obtained. Solar flares or an orbit that passes through the South Atlantic Anomaly can subject the vehicle to very high proton flux levels. There are three ways in which spurious proton generated signals can impact tracker performance: the many false signals can prevent or extend the time to acquire a star; a proton-generated signal can compromise the accuracy of the star's reported magnitude and position; and the tracked star can be lost, requiring reacquisition. Tests simulating a proton-rich environment were performed on two ASTRA-1 Star Trackers utilizing these new algorithms. There were no false acquisitions, no lost stars, and a significant reduction in reported position errors due to these improvements

A Flexible Network Approach to Privacy of Blockchain Transactions

For preserving privacy, blockchains can be equipped with dedicated mechanisms to anonymize participants. However, these mechanism often take only the abstraction layer of blockchains into account whereas observations of the underlying network traffic can reveal the originator of a transaction request. Previous solutions either provide topological privacy that can be broken by attackers controlling a large number of nodes, or offer strong and cryptographic privacy but are inefficient up to practical unusability. Further, there is no flexible way to trade privacy against efficiency to adjust to practical needs. We propose a novel approach that combines existing mechanisms to have quantifiable and adjustable cryptographic privacy which is further improved by augmented statistical measures that prevent frequent attacks with lower resources. This approach achieves flexibility for privacy and efficency requirements of different blockchain use cases.Comment: 6 pages, 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS

Scarring of Florida’s seagrasses: assessment and management options

Management programs that address scarring of seagrasses should be based on an approach that involves (1) education, (2) channel marking, (3) increased enforcement, and (4) limited-motoring zones. Aerial monitoring and photography of the managed area are essential in evaluating the effectiveness of a program. Management programs that use this multifaceted approach have been instituted by a few local governments and at several state parks. Initial results of the programs indicate that in some areas seagrass scarring has been reduced but that in other areas emphasis may need to be increased on one or more of the components of the four-point approach. A statewide management plan is needed to address the most egregious scarring over large areas that may be difficult to regulate at the local-government level

Sharing science, building bridges, and enhancing impact: Public-Private Partnerships in the CGIAR

"This study, which examines the role of public–private partnerships in international agricultural research, is intended to provide policymakers, research managers, and business decisionmakers with an understanding of how such partnerships operate and how they potentially contribute to food security and poverty reduction in developing countries. The study examines public–private partnerships in light of persistent market failure, institutional constraints, and systemic weaknesses, which impede the exchange of potentially pro-poor knowledge and technology. The study focuses on three key issues: whether public–private partnerships contribute to reducing the cost of research, whether they add value to research by facilitating innovation, and whether they enhance the impact of research on smallholders and other marginalized groups in developing-country agriculture. The study examines 75 projects undertaken by the research centers and programs of the Consultative Group on International Agricultural Research (CGIAR) in partnership with various types of private firms. Data and information were obtained through document analysis, semi-structured interviews with key informants, and an email survey of CGIAR centers. The resulting analysis provides a characterization of public–private partnerships in the CGIAR and describes the factors that contribute to their success. These finding are important to improving both public policy and organizational practices in the international agricultural research system." - from authors' abstract.Agricultural R&D, CGIAR, Innovation, Public-private partnerships,

Household epidemic models with varying infection response

This paper is concerned with SIR (susceptible--infected--removed) household epidemic models in which the infection response may be either mild or severe, with the type of response also affecting the infectiousness of an individual. Two different models are analysed. In the first model, the infection status of an individual is predetermined, perhaps due to partial immunity, and in the second, the infection status of an individual depends on the infection status of its infector and on whether the individual was infected by a within- or between-household contact. The first scenario may be modelled using a multitype household epidemic model, and the second scenario by a model we denote by the infector-dependent-severity household epidemic model. Large population results of the two models are derived, with the focus being on the distribution of the total numbers of mild and severe cases in a typical household, of any given size, in the event that the epidemic becomes established. The aim of the paper is to investigate whether it is possible to determine which of the two underlying explanations is causing the varying response when given final size household outbreak data containing mild and severe cases. We conduct numerical studies which show that, given data on sufficiently many households, it is generally possible to discriminate between the two models by comparing the Kullback-Leibler divergence for the two fitted models to these data