Rethinking of risk communication: lessons from the decision sciences

Risk communication involves three primary elements: process, content and intent. Much has been written about the first two. Much is known, for example, about the guiding principles that should be considered during the design of a risk communication. Likewise, many studies have been conducted about how best to establish the technical and informational content of a risk communication. Very little attention, by contrast, has been devoted to the intent of risk communication, which is to inform decision making for risk management. While appropriate information upon which to base risk management decisions is important, so to is an understanding of how people instinctively approach decision making under conditions of risk. Work in the decision sciences provides this often-missing perspective for many risk communication efforts and is, therefore, the focus of this paper.

Information transfer in moving animal groups

Moving animal groups provide some of the most intriguing and difficult to characterise examples of collective behaviour. We review some recent (and not so recent) empirical research on the motion of animal groups, including fish, locusts and homing pigeons. An important concept which unifies our understanding of these groups is that of transfer of directional information. Individuals which change their direction of travel in response to the direction taken by their near neighbours can quickly transfer information about the presence of a predatory threat or food source. We show that such information transfer is optimised when the density of individuals in a group is close to that at which a phase transition occurs between random and ordered motion. Similarly, we show that even relatively small differences in information possessed by group members can lead to strong collective-level decisions for one of two options. By combining the use of self-propelled particle and social force models of collective motion with thinking about the evolution of flocking we aim to better understand how complexity arises within these groups.

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Anonymous communications in the Internet

With the growth and acceptance of the Internet, there has been increased interest in maintaining anonymity in the network. By using traffic analysis, it is possible to infer who is talking to whom over the Internet. We present a novel approach to hide the senders and the receivers of messages. Routes are chosen and frames traverse these routes. Each frame consists of a token and a node can send a message through a frame only when the corresponding token is free. The advantage of our protocol is that it poses limited bandwidth overhead when there is at least some traffic, while posing minimal bandwidth overhead when there is no traffic at all.

Objects limit human comprehension

This paper demonstrates that the human visual system, the primary sensory conduit for primates, processes ambient energy in a way that obligatorily constructs the objects that we ineluctably perceive. And since our perceptual apparatus processes information only in terms of objects (along with the properties and movements of objects), we are limited in our ability to comprehend ‘what is’ when we move beyond our ordinary world of midsize objects—as, for example, when we address the micro microworld of quantum physics.

Negotiating Values: Narrative and Exposition

In this paper I focus on the limits of narrative by asking what kinds of things narratives do, and what kinds of texts do related things in other ways. In particular I focus on how narrative genres organise time in relation to value, drawing on functional linguistic models of temporality and evaluation. From a linguistic perspective, the various narrative genres negotiate different kinds of solidarity with listeners, and so the limits of narrative materialise various possibilities for communing in a culture, alongside the potentialities for construing community through related and other genres of discourse—since in general, the limits/possibilities of our language (and attendant modalities of communication) are the limits/possibilities of our social world.

Mobile location estimation using density-based clustering technique for NLoS environments

Mobile location technologies have drawn much attention to cope with the mass demands of wireless communication services. Although clustering spatial data is viewed as an effective way to access the objects located in a physical space, little has been done in estimating mobile location. In wireless communication, one of the main problems with accurate location is nonline of sight (NLoS) propagation. To solve the problem, we present a new location algorithm with clustering technique by utilizing the geometrical feature of cell layout, time of arrival range measurements, and three base stations. The mobile location is estimated by solving the optimal solution of the objective function based on the high density cluster. Furthermore, our proposed algorithm only needs three range measurements and does not distinguish between NLoS and LoS environments. Simulations study was conducted to evaluate the performance of the algorithm for different NLoS error distributions and various upper bound of NLoS error. The results of our experiments demonstrate that the proposed algorithm is significantly more effective in location accuracy than range scaling algorithm, linear lines of position algorithm, and Taylor series algorithm, and also satisfies the location accuracy demand of E-911.

Hierarchical analysis of piecewise affine models of gene regulatory networks

A key point in the analysis of dynamical models of biological systems is to handle systems of relatively high dimensions. In the present paper we propose a method to hierarchically organize a certain type of piecewise affine (PWA) differential systems. This specific class of systems has been extensively studied for the past few years, as it provides a good framework to model gene regulatory networks. The method, shown on several examples, allows a qualitative analysis of the asymptotic behavior of a PWA system, decomposing it into several smaller subsystems. This technique, based on the well-known strongly connected components decomposition, is not new. However, its adaptation to the non-smooth PWA differential equations turns out to be quite relevant because of the strong discrete structure underlying these equations. Its biological relevance is shown on a 7-dimensional PWA system modeling the gene network responsible for the carbon starvation response in Escherichia coli.

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The Behavioral Ecology of Shellfish Gathering in Western Kiribati,Micronesia 1: Prey Choice

Focusing on contemporary shellfish exploitation among several atoll communities in Kiribati, Micronesia, this paper examines the relationship between human foragers and their invertebrate prey via the prey choice or diet breadth model derived from optimal foraging theory. Shellfish, like many other reef organisms, are relatively sedentary and predictable, but these characteristics make them susceptible to over-harvesting. The research reveals that shellfish gatherers are foraging in a manner that matches the predictions of optimal foraging theory. The work adds to our understanding of optimal foraging decisions in atoll settings by critically evaluating the depiction of atoll dwellers as conservationists.

Leitlinien zur molekulargenetischen Diagnostik: Fragiles-X und Fragiles-X assoziiertes Tremor/Ataxie Syndrom

Ohne Zusammenfassung

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Benchmarking the effects of operating system interference on extreme-scale parallel machines

We investigate operating system noise, which we identify as one of the main reasons for a lack of synchronicity in parallel applications. Using a microbenchmark, we measure the noise on several contemporary platforms and find that, even with a general-purpose operating system, noise can be limited if certain precautions are taken. We then inject artificially generated noise into a massively parallel system and measure its influence on the performance of collective operations. Our experiments indicate that on extreme-scale platforms, the performance is correlated with the largest interruption to the application, even if the probability of such an interruption on a single process is extremely small. We demonstrate that synchronizing the noise can significantly reduce its negative influence.

Social Capital,Collective Action and Group Formation: Developmental Trajectories in Post-socialist Mongolia

Group formation, social capital and collective action have been the focus of much recent attention amongst donors and policy makers. Optimistic scenarios highlight their contributions to poverty reduction and effective natural resource management. However, recent critiques have focused on the exclusionary potential or ‘dark side’ of groups and social capital. Not only are their longer term livelihood impacts unclear, but lacunae persist in our understanding of how social capital, especially trust, is built. This paper presents a longitudinal evaluation of trust, collective action and cooperation among herders in post-Soviet Mongolia in the context of recent donor projects. Results highlight the important catalytic effect of external interventions in overcoming a lack of trust and promoting formalised collective action, but only in the context of a particular conjunction of circumstances. Indications for livelihood outcomes confirm the differentiated benefits, exclusionary potential and fragility of social capital and new institutional forms.

A finite volume method for stochastic integrate-and-fire models

The stochastic integrate and fire neuron is one of the most commonly used stochastic models in neuroscience. Although some cases are analytically tractable, a full analysis typically calls for numerical simulations. We present a fast and accurate finite volume method to approximate the solution of the associated Fokker-Planck equation. The discretization of the boundary conditions offers a particular challenge, as standard operator splitting approaches cannot be applied without modification. We demonstrate the method using stationary and time dependent inputs, and compare them with Monte Carlo simulations. Such simulations are relatively easy to implement, but can suffer from convergence difficulties and long run times. In comparison, our method offers improved accuracy, and decreases computation times by several orders of magnitude. The method can easily be extended to two and three dimensional Fokker-Planck equations.

Individual variability of behavioural responses by Wandering Albatrosses (Diomedea exulans) to human disturbance

Sub-Antarctic Marion Island has had a permanent research station for 50 years and the islands Wandering Albatrosses have been intensively studied for 20 years. The reactions of breeding birds to approaches by a human on foot were recorded. Three response variables were calculated: intensity of vocal reaction (IVR), intensity of non-vocal reaction (INR) and overall response index (ORI). At 5 m from the nest, twice as many birds stood and/or vocalised as at 15 m. Nearest neighbour distance, age and gender did not explain individual variability of responses. Study colony birds had higher IVR scores than non-study colony birds; birds at colonies closest to the station had the highest ORI scores. A better breeding record was associated with lower IVR and ORI scores, but a causative relationship remains to be demonstrated. A minimum viewing distance of 25 m is recommended for breeding Wandering Albatrosses.

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XenLoop: a transparent high performance inter-VM network loopback

Advances in virtualization technology have focused mainly on strengthening the isolation barrier between virtual machines (VMs) that are co-resident within a single physical machine. At the same time, a large category of communication intensive distributed applications and software components exist, such as web services, high performance grid applications, transaction processing, and graphics rendering, that often wish to communicate across this isolation barrier with other endpoints on co-resident VMs. State of the art inter-VM communication mechanisms do not adequately address the requirements of such applications. TCP/UDP based network communication tends to perform poorly when used between co-resident VMs, but has the advantage of being transparent to user applications. Other solutions exploit inter-domain shared memory mechanisms to improve communication latency and bandwidth, but require applications or user libraries to be rewritten against customized APIs—something not practical for a large majority of distributed applications. In this paper, we present the design and implementation of a fully transparent and high performance inter-VM network loopback channel, called XenLoop, in the Xen virtual machine environment. XenLoop does not sacrifice user-level transparency and yet achieves high communication performance between co-resident guest VMs. XenLoop intercepts outgoing network packets beneath the network layer and shepherds the packets destined to co-resident VMs through a high-speed inter-VM shared memory channel that bypasses the virtualized network interface. Guest VMs using XenLoop can migrate transparently across machines without disrupting ongoing network communications, and seamlessly switch between the standard network path and the XenLoop channel. In our evaluation using a number of unmodified benchmarks, we observe that XenLoop can reduce the inter-VM round trip latency by up to a factor of 5 and increase bandwidth by a up to a factor of 6.

An introduction to the Freshwater Animal Diversity Assessment (FADA) project

The Freshwater Animal Diversity Assessment (FADA) project aims at compiling an overview of genus- and species-level diversity of animals in the continental, aquatic ecosystems of the world. It is a collective effort of 163 experts, and presents 59 articles treating the diversity and endemism of different animal taxa, ranging from microscopic worms to mammals, at global and regional scales. Given their structural importance, an article on macrophytes is also added. Here, we give an overview of the project’s history, and outline the common framework of the various articles, as well as the conventions the experts agreed to adhere to in their treatises. Furthermore, we briefly introduce future prospects.

Predictive performance modelling of parallel component compositions

Large-scale scientific computing applications frequently make use of closely-coupled distributed parallel components. The performance of such applications is therefore dependent on the component parts and their interaction at run-time. This paper describes a methodology for predictive performance modelling and evaluation of parallel applications composed of multiple interacting components. In this paper, the fundamental steps and required operations involved in the modelling and evaluation process are identified—including component decomposition, component model combination, M×N communication modelling, dataflow analysis and overall performance evaluation. A case study is presented to illustrate the modelling process and the methodology is verified through experimental analysis.

The problem of adaptive individual choice in cultural evolution

This paper tries to explain how individuals manage adaptive individual choice (i.e., the decision to acquire a fitter than average behavior or idea rapidly and tractably) in cultural evolution, despite the fact that acquiring fitness information is very difficult. I argue that the means of solving this problem suggested in the cultural evolution literature largely are various types of decision rules employing representations of fitness correlated properties or states of affairs. I argue that the problem of adaptive individual choice is best solved where some of these learning rule representations are socially transmitted and some are biologically transmitted.

Individual optimization efforts and population dynamics: a mathematical model for the evolution of resource allocation strategies, with applications to reproductive and mating systems

We develop a formal framework for the optimal allocation of limited resources that includes and clarifies the interplay between individual optimization and the resulting effects at the population level. As an example, in regard to the evolution of sexual recombination, the paradox of the twofold cost of sex is avoided by distinguishing between the evolution of recombination and the subsequent emergence and stability of different mating types as a result of individual optimization within a population that benefits from recombination.

The Cauchy problem for one-dimensional spiking neuron models

I consider spiking neuron models defined by a one-dimensional differential equation and a reset—i.e., neuron models of the integrate-and-fire type. I address the question of the existence and uniqueness of a solution on for a given initial condition. It turns out that the reset introduces a countable and ordered set of backward solutions for a given initial condition. I discuss the implications of these mathematical results in terms of neural coding and spike timing precision.