Algorithm for Mesoscopic Advection-Diffusion

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

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

Investigating Associations between Health Behaviours, Constructs of the Job Demands-Resources Model, and Work-Related Outcomes

Health behaviours are important determinants of health, yet have received inadequate attention within the organisational behaviour literature. Three empirical studies were conducted to enhance conceptual and empirical understanding of the associations between employee wellbeing and a range of health behaviours. The findings of this research provide a valuable starting point for researchers interested in refining job demands-resources theory to take into account health behaviours, and may inform organisations seeking to enhance work well-being initiatives

Active Versus Passive: Receiver Model Transforms for Diffusive Molecular Communication

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

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

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

Impact of distributed generation mix on the effectiveness of islanded operation detection

Distributed generation can be understood as a process where large scale power generation is gradually replaced by smaller power generation facilities with reduced power yield, and mostly connected at the system distribution level. One of the most important requirements for interconnecting distributed generation to healthy power networks is the Loss of Mains (or Islanding) detection. During a Loss of Mains (LOM) event a part of the grid (including distributed generation) losses physical connection with rest of the grid. A condition like this should be detected and actions to disconnect distributed generation should be initiated, in order to protect life and property. A very common passive method used to detect an islanding event, is the Rate of Change of Frequency (ROCOF). Since distribution networks nowadays are accommodating a great amount converter-interfaced generation, there is a risk that such methods may fail to successfully operate or operate spuriously, putting system stability at risk. Most of the existing LOM protection performance studies, consider only a single generator within the islanded part of the network. While historically such approach was reasonable, rapidly increasing numbers of DG connections lead to high probability of islanding with more than one generator in the mix. Therefore, this paper, considers various mixes of generation to investigate how this impacts LOM detection performance. In particular studies are undertaken with a few identified most likely combinations of distributed generators