Social Deference and Hunger as Mechanisms for Starvation Avoidance in Cognitive Radio Societies, Proceedings of IWCMC 2016, Paphos Cyprus
Anna Wisniewska, Bilal Khan, Ala Al-Fuqaha, Kirk Dombrowski, Mohammad Al-Shattal
Wireless communication is an increasingly ubiquitous and important resource substrate of the digital ecosystem. In the face of the rapid growth in the population of Internet of Things (IoT), however, uncoordinated access to limited resources of radio spectrum is likely to lead to mass starvation. Here we put forward a new bio-social paradigm for cognitive radio, extending previous models in which the secondary users of spectrum alternate stochastically between foraging and consuming behaviors. In this paper, we ask and resolve two questions: (1) What costs and benefits does social deference to the group yield for each of the individuals therein? and (2) Can a notion of individual “hunger” form the basis of a distributed social deference scheme that is free of group coordination costs? Through a series of simulation experiments grounded in a well-specified formal model, we show that social deference improves both the fairness and the reliability of spectrum resource allocation, and moreover, that the concept of individual “hunger” can be used to implement social deference with minimal group coordination overhead. The results have consequences both in suggesting potential improvements for distributed spectrum access, and in understanding the evolutionary pressures on the behaviors of individual devices within emerging digital IoT societies.
“Creating a Community of Practice to Prevent Suicide Through Multiple Channels: Describing the Theoretical Foundations and Structured Learning of PC CARES.” International Quarterly of Community Health Education 36(2): 115–122.
Lisa Wexler, Diane McEachern, Gloria DiFulvio, Cristine Smith, Louis Graham, and Kirk Dombrowski
It is critical to develop practical, effective, ecological, and decolonizing approaches to indigenous suicide prevention and health promotion for the North American communities. The youth suicide rates in predominantly indigenous small, rural, and remote Northern communities are unacceptably high. This health disparity, however, is fairly recent, occurring over the last 50 to 100 years as communities experienced forced social, economic, and political change and intergenerational trauma. These conditions increase suicide risk and can reduce people’s access to shared protective factors and processes. In this context, it is imperative that suicide prevention includes—at its heart— decolonization, while also utilizing the “best practices” from research to effectively address the issue from multiple levels. This article describes such an approach: Promoting Community Conversations About Research to End Suicide (PC CARES). PC CARES uses popular education strategies to build a “community of practice” among local and regional service providers, friends, and families that fosters personal and collective learning about suicide prevention in order to spur practical action on multiple levels to prevent suicide and promote health. This article will discuss the theoretical underpinnings of the community intervention and describe the form that PC CARES takes to structure ongoing dialogue, learning, solidarity, and multilevel mobilization for suicide prevention.
“Understanding differences in HIV/HCV prevalence according to differentiated risk behaviors in a sample of PWID in rural Puerto Rico.” Journal of Harm Reduction 13 (10): 1-7.
Roberto Abadie, Melissa Welch-Lazoritz, Camila Gelpi-Acosta, Juan Carlos Reyes, Ric Curtis, Kirk Dombrowski
Blood contained in needles and injection equipment has been identified as a vector for HIV and HCV transmission among people who inject drugs (PWID). Yet, there is often a wide discrepancy in prevalence for both viruses. While microbiological differences between viruses influence prevalence, other variables associated with the way drugs are acquired and used, also play a role.
Respondent-driven sampling (RDS) methods recruited a sample of 315 current intravenous drug users in rural Puerto Rico. Information about type and frequency of use, HIV and HVC risk behaviors (sharing needles, cookers, cotton, and water), sexual behaviors, and alcohol use was collected. HIV and HCV statuses were assessed via rapid antibody tests. T tests compare means of participants who tested positive (reactive) to those who tested negative. Logistic regression analyses were used to validate the association of the risk factors involved.
Tests showed a significant difference in HIV (6 %) and HCV (78.4 %) prevalence among a population of current PWID. The main risk behaviors in HCV transmission are the sharing of injection “works”, (e.g., cookers, cotton, and water). Sharing works occurred more than twice as often as the sharing of needles, and HCV+ and HCV? individuals reported the same needle sharing habits.
“Improving the Network Scale-Up Estimator: Incorporating Means of Sums, Recursive Back Estimation, and Sampling Weights.” PLoSOne 10(12): e0143406.
Patrick Habecker, Kirk Dombrowski, and Bilal Khan
Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM) provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations) via traditional survey tools such as telephone or mail surveys—by asking a representative sample to estimate the number of people they know who are members of such a “hidden” subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation “trimming” to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights.
“Attractor-based obstructions to growth in homogenous cyclic Boolean automata.”Journal of Computer Science and System Biology 8(6): 341-353.
Bilal Khan, Yuri Kantor, Kirk Dombrowski,
We consider a synchronous Boolean organism consisting of N cells arranged in a circle, where each cell initially takes on an independently chosen Boolean value. During the lifetime of the organism, each cell updates its own value by responding to the presence (or absence) of diversity amongst its two neighbours’ values. We show that if all cells eventually take a value of 0 (irrespective of their initial values) then the organism necessarily has a cell count that is a power of 2. In addition, the converse is also proved: if the number of cells in the organism is a proper power of 2, then no matter what the initial values of the cells are, eventually all cells take on a value of 0 and then cease to change further. We argue that such an absence of structure in the dynamical properties of the organism implies a lack of adaptiveness, and so is evolutionarily disadvantageous. It follows that as the organism doubles in size (say from m to 2m) it will necessarily encounter an intermediate size that is a proper power of 2, and suffers from low adaptiveness. Finally we show, through computational experiments, that one way an organism can grow to more than twice its size and still avoid passing through intermediate sizes that lack structural dynamics, is for the organism to depart from assumptions of homogeneity at the cellular level.