1,061 research outputs found
Impromptu Deployment of Wireless Relay Networks: Experiences Along a Forest Trail
We are motivated by the problem of impromptu or as- you-go deployment of
wireless sensor networks. As an application example, a person, starting from a
sink node, walks along a forest trail, makes link quality measurements (with
the previously placed nodes) at equally spaced locations, and deploys relays at
some of these locations, so as to connect a sensor placed at some a priori
unknown point on the trail with the sink node. In this paper, we report our
experimental experiences with some as-you-go deployment algorithms. Two
algorithms are based on Markov decision process (MDP) formulations; these
require a radio propagation model. We also study purely measurement based
strategies: one heuristic that is motivated by our MDP formulations, one
asymptotically optimal learning algorithm, and one inspired by a popular
heuristic. We extract a statistical model of the propagation along a forest
trail from raw measurement data, implement the algorithms experimentally in the
forest, and compare them. The results provide useful insights regarding the
choice of the deployment algorithm and its parameters, and also demonstrate the
necessity of a proper theoretical formulation.Comment: 7 pages, accepted in IEEE MASS 201
Propagation on networks: an exact alternative perspective
By generating the specifics of a network structure only when needed
(on-the-fly), we derive a simple stochastic process that exactly models the
time evolution of susceptible-infectious dynamics on finite-size networks. The
small number of dynamical variables of this birth-death Markov process greatly
simplifies analytical calculations. We show how a dual analytical description,
treating large scale epidemics with a Gaussian approximations and small
outbreaks with a branching process, provides an accurate approximation of the
distribution even for rather small networks. The approach also offers important
computational advantages and generalizes to a vast class of systems.Comment: 8 pages, 4 figure
Epidemics on contact networks: a general stochastic approach
Dynamics on networks is considered from the perspective of Markov stochastic
processes. We partially describe the state of the system through network motifs
and infer any missing data using the available information. This versatile
approach is especially well adapted for modelling spreading processes and/or
population dynamics. In particular, the generality of our systematic framework
and the fact that its assumptions are explicitly stated suggests that it could
be used as a common ground for comparing existing epidemics models too complex
for direct comparison, such as agent-based computer simulations. We provide
many examples for the special cases of susceptible-infectious-susceptible (SIS)
and susceptible-infectious-removed (SIR) dynamics (e.g., epidemics propagation)
and we observe multiple situations where accurate results may be obtained at
low computational cost. Our perspective reveals a subtle balance between the
complex requirements of a realistic model and its basic assumptions.Comment: Main document: 16 pages, 7 figures. Electronic Supplementary Material
(included): 6 pages, 1 tabl
Evaluating risk effects of industrial features on woodland caribou habitat selection in west central Alberta using agent-based modelling
AbstractAlberta woodland caribou (Rangifer tarandus) are classified as threatened in Canada, and a local population in the west-central region, the Little Smoky herd, is at immediate risk of extirpation due, in part, to anthropogenic activities such as oil, gas, and forestry that have altered the ecosystem dynamics. To investigate these impacts, we have developed a spatially explicit, agent-based model (ABM) to simulate winter habitat selection and use of woodland caribou, and to determine the relative impacts of different industrial features on caribou habitat-selection strategies. The ABM model is composed of cognitive caribou agents possessing memory and decision-making heuristics that act to optimize tradeoffs between energy acquisition and disturbance. A set of environmental data layers was used to develop a virtual grid representing the landscape over which caribou move. This grid contained forage-availability, energy-content, and predation-risk values. The model was calibrated using GPS data from caribou radio collars (n = 13) deployed over six months from 2004 to 2005, representing caribou winter activities. Additional simulations were conducted on caribou habitat-selection strategies by assigning industrial features (i.e., roads, seismic lines, pipelines, well sites, cutblocks and burns) different levels of disturbance depending on their type, age, and density. Differences in disturbance effects between industry features were confirmed by verifying which resultant simulations of caribou movement patterns most closely match actual caribou distributions and other patterns extracted from the GPS data. The results elucidate the degree to which caribou perceive different industry features as disturbance, and the differential energetic costs associated with each, thus offering insight into why caribou are choosing the habitats they use, and consequently, the level and type of industry most likely to affect their bioenergetics and fitness
Interactions between Genetic, Prenatal, Cortisol, and Parenting Influences on Adolescent Substance Use and Frequency:A TRAILS Study
INTRODUCTION: Dynamic relations between genetic, hormone, and pre- and postnatal environments are theorized as critically important for adolescent substance use but are rarely tested in multifactorial models. This study assessed the impact of interactions of genetic risk and cortisol reactivity with prenatal and parenting influences on both any and frequency of adolescent substance use. METHODS: Data are from the TRacking Adolescents' Individual Lives Survey (TRAILS), a prospective longitudinal, multi-rater study of 2,230 Dutch adolescents. Genetic risk was assessed via 3 substance-specific polygenic scores. Mothers retrospectively reported prenatal risk when adolescents were 11 years old. Adolescents rated their parents' warmth and hostility at age 11. Salivary cortisol reactivity was measured in response to a social stress task at age 16. Adolescents' self-reported cigarette, alcohol, and cannabis use frequency at age 16. RESULTS: A multivariate hurdle regression model showed that polygenic risk for smoking, alcohol, and cannabis predicted any use of each substance, respectively, but predicted more frequent use only for smoking. Blunted cortisol reactivity predicted any use and more frequent use for all 3 outcomes. There were 2 interactions: blunted cortisol reactivity exacerbated the association of polygenic risk with any smoking and the association of prenatal risk with any alcohol use. CONCLUSION: Polygenic risk seems of importance for early use but less so for frequency of use, whereas blunted cortisol reactivity was correlated with both. Blunted cortisol reactivity may also catalyze early risks for substance use, though to a limited degree. Gene-environment interactions play no role in the context of this multifactorial model
Maternal Smoking During Pregnancy and Offspring Birth Weight: A Genetically-Informed Approach Comparing Multiple Raters
Maternal smoking during pregnancy (SDP) is a significant public health concern with adverse consequences to the health and well-being of the fetus. There is considerable debate about the best method of assessing SDP, including birth/medical records, timeline follow-back approaches, multiple reporters, and biological verification (e.g., cotinine). This is particularly salient for genetically-informed approaches where it is not always possible or practical to do a prospective study starting during the prenatal period when concurrent biological specimen samples can be collected with ease. In a sample of families (N = 173) specifically selected for sibling pairs discordant for prenatal smoking exposure, we: (1) compare rates of agreement across different types of report—maternal report of SDP, paternal report of maternal SDP, and SDP contained on birth records from the Department of Vital Statistics; (2) examine whether SDP is predictive of birth weight outcomes using our best SDP report as identified via step (1); and (3) use a sibling-comparison approach that controls for genetic and familial influences that siblings share in order to assess the effects of SDP on birth weight. Results show high agreement between reporters and support the utility of retrospective report of SDP. Further, we replicate a causal association between SDP and birth weight, wherein SDP results in reduced birth weight even when accounting for genetic and familial confounding factors via a sibling comparison approac
Stellar-to-halo mass relation of cluster galaxies
In the hierarchical formation model, galaxy clusters grow by accretion of
smaller groups or isolated galaxies. During the infall into the centre of a
cluster, the properties of accreted galaxies change. In particular, both
observations and numerical simulations suggest that its dark matter halo is
stripped by the tidal forces of the host.
We use galaxy-galaxy weak lensing to measure the average mass of dark matter
haloes of satellite galaxies as a function of projected distance to the centre
of the host, for different stellar mass bins. Assuming that the stellar
component of the galaxy is less disrupted by tidal stripping, stellar mass can
be used as a proxy of the infall mass. We study the stellar to halo mass
relation of satellites as a function of the cluster-centric distance to measure
tidal stripping.
We use the shear catalogues of the DES science verification archive, the
CFHTLenS and the CFHT Stripe 82 (CS82) surveys, and we select satellites from
the redMaPPer catalogue of clusters. For galaxies located in the outskirts of
clusters, we find a stellar to halo mass relation in good agreement with the
theoretical expectations from \citet{moster2013} for central galaxies. In the
centre of the cluster, we find that this relation is shifted to smaller halo
mass for a given stellar mass. We interpret this finding as further evidence
for tidal stripping of dark matter haloes in high density environments.Comment: 15 pages, 14 figure
Missouri mothers and their children: A family study of the effects of genetics and the prenatal environment
The Missouri Mothers and Their Children Study was specifically designed to critically investigate prenatal environmental influences on child attention problems and associated learning and cognitive deficits. The project began as a pilot study in 2004 and was formally launched in 2008. Participants in the study were initially identified via the Department of Vital Statistics birth record database. Interview and lab-based data were obtained from (1) mothers of Missouri-born children (born 1998–2005), who smoked during one pregnancy but not during another pregnancy, (2) biological fathers when available, and (3) the children [i.e., full sibling pairs discordant for exposure to maternal smoking during pregnancy (SDP)]. This within-mother, between-pregnancy contrast provides the best possible methodological control for many stable maternal and familial confounding factors (e.g., heritable and socio-demographic characteristics of the mother that predict increased probability of SDP). It also controls for differences between mothers who do and do not smoke during pregnancy, and their partners, that might otherwise artifactually create, or alternatively mask, associations between SDP and child outcomes. Such a design will therefore provide opportunities to determine less biased effect sizes while also allowing us to investigate (on a preliminary basis) the possible contribution of paternal or other second-hand smoke exposure during the pre-, peri- and postnatal periods to offspring outcome. This protocol has developed a cohort that can be followed longitudinally through periods typically associated with increased externalizing symptoms and substance use initiation
Passive \u3cem\u3er\u3c/em\u3eGE or Developmental Gene-Environment Cascade? An Investigation of the Role of Xenobiotic Metabolism Genes in the Association Between Smoke Exposure During Pregnancy and Child Birth Weight
There is considerable evidence that smoke exposure during pregnancy (SDP) environmentally influences birth weight after controlling for genetic influences and maternal characteristics. However, maternal smoking during pregnancy—the behavior that leads to smoke exposure during pregnancy—is also genetically-influenced, indicating the potential role of passive gene-environment correlation. An alternative to passive gene-SDP correlation is a cascading effect whereby maternal and child genetic influences are causally linked to prenatal exposures, which then have an ‘environmental’ effect on the development of the child’s biology and behavior. We describe and demonstrate a conceptual framework for disentangling passive rGE from this cascading GE effect using a systems-based polygenic scoring approach comprised of genes shown to be important in the xenobiotic (substances foreign to the body) metabolism pathway. Data were drawn from 5044 families from the Avon Longitudinal Study of Parents and Children with information on maternal SDP, birth weight, and genetic polymorphisms in the xenobiotic pathway. Within a k-fold cross-validation approach (k = 5), we created weighted maternal and child polygenic scores using 18 polymorphisms from 10 genes that have been implicated in the xenobiotic metabolism pathway. Mothers and children shared variation in xenobiotic metabolism genes. Amongst mothers who smoked during pregnancy, neither maternal nor child xenobiotic metabolism polygenic scores were associated with a higher likelihood of smoke exposure during pregnancy, or the severity of smoke exposure during pregnancy (and therefore, neither proposed mechanism was supported), or with child birth weight. SDP was consistently associated with lower child birth weight controlling for the polygenic scores, maternal educational attainment, social class, psychiatric problems, and age. Limitations of the study design and the potential of the framework using other designs are discussed
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