51 research outputs found

    Algorithm for Mesoscopic Advection-Diffusion

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    In this paper, an algorithm is presented to calculate the transition rates between adjacent mesoscopic subvolumes in the presence of flow and diffusion. These rates can be integrated in stochastic simulations of reaction-diffusion systems that follow a mesoscopic approach, i.e., that partition the environment into homogeneous subvolumes and apply the spatial stochastic simulation algorithm (spatial SSA). The rates are derived by integrating Fick's second law over a single subvolume in one dimension (1D), and are also shown to apply in three dimensions (3D). The proposed algorithm corrects the derived rates to ensure that they are physically meaningful and it is implemented in the AcCoRD simulator (Actor-based Communication via Reaction-Diffusion). Simulations using the proposed method are compared with a naive mesoscopic approach, microscopic simulations that track every molecule, and analytical results that are exact in 1D and an approximation in 3D. By choosing subvolumes that are sufficiently small, such that the Peclet number associated with a subvolume is sufficiently less than 2, the accuracy of the proposed method is comparable with the microscopic method, thus enabling the simulation of advection-reaction-diffusion systems with the spatial SSA.Comment: 12 pages, 9 figures. Submitted to IEEE Transactions on NanoBioscienc

    Root Mean Square Error of Neural Spike Train Sequence Matching with Optogenetics

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    Optogenetics is an emerging field of neuroscience where neurons are genetically modified to express light-sensitive receptors that enable external control over when the neurons fire. Given the prominence of neuronal signaling within the brain and throughout the body, optogenetics has significant potential to improve the understanding of the nervous system and to develop treatments for neurological diseases. This paper uses a simple optogenetic model to compare the timing distortion between a randomly-generated target spike sequence and an externally-stimulated neuron spike sequence. The distortion is measured by filtering each sequence and finding the root mean square error between the two filter outputs. The expected distortion is derived in closed form when the target sequence generation rate is sufficiently low. Derivations are verified via simulations.Comment: 6 pages, 5 figures. Will be presented at IEEE Global Communications Conference (IEEE GLOBECOM 2017) in December 201

    Active Versus Passive: Receiver Model Transforms for Diffusive Molecular Communication

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    This paper presents an analytical comparison of active and passive receiver models in diffusive molecular communication. In the active model, molecules are absorbed when they collide with the receiver surface. In the passive model, the receiver is a virtual boundary that does not affect molecule behavior. Two approaches are presented to derive transforms between the receiver signals. As an example, two models for an unbounded diffusion-only molecular communication system with a spherical receiver are unified. As time increases in the three-dimensional system, the transform functions have constant scaling factors, such that the receiver models are effectively equivalent. Methods are presented to enable the transformation of stochastic simulations, which are used to verify the transforms and demonstrate that transforming the simulation of a passive receiver can be more efficient and more accurate than the direct simulation of an absorbing receiver.Comment: 6 pages, 3 figures, 3 tables. Will be presented at IEEE Globecom 201

    Modeling Interference-Free Neuron Spikes with Optogenetic Stimulation

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    This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a cortical neuron's membrane potential and its firing times. The external control is a simple optogenetic model represented by an illumination source that stimulates a saturating or decaying membrane current. This paper considers firing frequencies that are sufficiently low for the membrane potential to return to its resting potential after it fires. The time required for the neuron to charge and for the neuron to recover to the resting potential are numerically fitted to functions of the Izhikevich neuron model parameters and the peak input current. Results show that simple functions of the model parameters and maximum input current can be used to predict the charging and recovery times, even when there are deviations in the actual parameter values. Furthermore, the predictions lead to lower bounds on the firing frequency that can be achieved without significant distortion.Comment: 12 pages, 11 figures, 7 tables. Submitted for publication. Portions of this work appeared previously as arXiv:1710.11569, which is the conference version of this articl

    Timing Control of Single Neuron Spikes with Optogenetic Stimulation

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    This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a cortical neuron's membrane potential and its firing times. The external control is a simple optogenetic model represented by a constant current source that can be turned on or off. This paper considers a firing frequency that is sufficiently low for the membrane potential to return to its resting potential after it fires. The time required for the neuron to charge and for the neuron to recover to the resting potential are fitted to functions of the Izhikevich neuron model parameters. Results show that linear functions of the model parameters can be used to predict the charging times with some accuracy and are sufficient to estimate the highest firing frequency achievable without interspike interference.Comment: 6 pages, 8 figures, 3 tables. To be presented at the 2018 IEEE International Conference on Communications (IEEE ICC 2018) in May 201

    Effect of Local Population Uncertainty on Cooperation in Bacteria

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    Bacteria populations rely on mechanisms such as quorum sensing to coordinate complex tasks that cannot be achieved by a single bacterium. Quorum sensing is used to measure the local bacteria population density, and it controls cooperation by ensuring that a bacterium only commits the resources for cooperation when it expects its neighbors to reciprocate. This paper proposes a simple model for sharing a resource in a bacterial environment, where knowledge of the population influences each bacterium's behavior. Game theory is used to model the behavioral dynamics, where the net payoff (i.e., utility) for each bacterium is a function of its current behavior and that of the other bacteria. The game is first evaluated with perfect knowledge of the population. Then, the unreliability of diffusion introduces uncertainty in the local population estimate and changes the perceived payoffs. The results demonstrate the sensitivity to the system parameters and how population uncertainty can overcome a lack of explicit coordination.Comment: 5 pages, 6 figures. Will be presented as an invited paper at the 2017 IEEE Information Theory Workshop in November 2017 in Kaohsiung, Taiwa

    SurvSec: A New Security Architecture for Reliable Network Recovery from Base Station Failure of Surveillance WSN

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    AbstractSecuring surveillance wireless sensor networks (WSNs) in hostile environments such as borders, perimeters and battlefields during Base Station (BS) failure is challenging. Surveillance WSNs are highly vulnerable to BS failure. The attackers can render the network useless by only destroying the BS as the needed efforts to destroy the BS is much less than that is needed to destroy the network. This attack scenario will give the attackers the best chance to compromise many legitimate nodes. Previous works have tackled BS failure by deploying a mobile BS or by using multiple BSs. Despite the best electronic countermeasures, intrusion tolerance and anti-traffic analysis strategies to protect the BSs, an adversary still can destroy them. This paper proposes a novel security architecture called Surveillance Security (SurvSec) for reliable network recovery from single BS failure of surveillance WSN with single BS. SurvSec relies on a set of sensor nodes serve as Security Managers for management and storage of the security related data of all sensor nodes. SurvSec security architecture provides methodologies for choosing and changing the security managers of the surveillance WSN. SurvSec has three components: (1) Sensor nodes serve as Security Managers, (2) Data Storage System, (3) Data Recovery System. Furthermore, both the frame format of the stored data is carefully built and the security threats are encoded to allow minimum overheads for SurvSec security architecture. In this paper, we provide detailed specifications of SurvSec security architecture. We evaluate our designed security architecture for reliable network recovery from BS failure. Our evaluation shows that the proposed new security architecture can meet all the desired specifications and our analysis shows that the provided Security Managers are capable of network recovery from BS failure

    Vascular Endothelial Growth Factor and Placenta Growth Factor in Intrauterine Growth-Restricted Fetuses and Neonates

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    The angiogenic factors vascular endothelial growth factor (VEGF) and placenta growth factor (PlGF) are respectively up- and downregulated by hypoxia. We aimed to study circulating levels of the above factors in intrauterine growth restriction (IUGR) and to correlate their levels with the customized centiles of the infants. The study included 25 IUGR and 25 appropriate for gestational age (AGA) full-term, singleton infants and their mothers. Maternal (MS), fetal (UC), and neonatal day 1 (N1) and 4 (N4) blood was examined. MS and N1 PlGF, as well as UC VEGF levels correlated with the customized centiles of the infants (r = 0.39, P = .007, r = 0.34, P = .01, and r = −0.41, P = .004, resp). Furthermore, UC, N1, and N4 VEGF levels were higher in girls (r = 0.36, P = .01, r = 0.33, P = .02, and r = 0.41, P = .005 resp). In conclusion, positive and negative correlations of examined factors with the customized centiles of the infant could rely on placental function and intrauterine oxygen concentrations—both being usually lower in IUGR cases—while higher VEGF levels in girls should possibly be attributed to the stimulating action of estrogens
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