Electric field mill network products to improve detection of the lightning hazard

NASA Technical Reports Server (NTRS)

Maier, Launa M.

1987-01-01

An electric field mill network has been used at Kennedy Space Center for over 10 years as part of the thunderstorm detection system. Several algorithms are currently available to improve the informational output of the electric field mill data. The charge distributions of roughly 50 percent of all lightning can be modeled as if they reduced the charged cloud by a point charge or a point dipole. Using these models, the spatial differences in the lightning induced electric field changes, and a least squares algorithm to obtain an optimum solution, the three-dimensional locations of the lightning charge centers can be located. During the lifetime of a thunderstorm, dynamically induced charging, modeled as a current source, can be located spatially with measurements of Maxwell current density. The electric field mills can be used to calculate the Maxwell current density at times when it is equal to the displacement current density. These improvements will produce more accurate assessments of the potential electrical activity, identify active cells, and forecast thunderstorm termination.

Network meta-analysis, electrical networks and graph theory.

PubMed

Rücker, Gerta

2012-12-01

Network meta-analysis is an active field of research in clinical biostatistics. It aims to combine information from all randomized comparisons among a set of treatments for a given medical condition. We show how graph-theoretical methods can be applied to network meta-analysis. A meta-analytic graph consists of vertices (treatments) and edges (randomized comparisons). We illustrate the correspondence between meta-analytic networks and electrical networks, where variance corresponds to resistance, treatment effects to voltage, and weighted treatment effects to current flows. Based thereon, we then show that graph-theoretical methods that have been routinely applied to electrical networks also work well in network meta-analysis. In more detail, the resulting consistent treatment effects induced in the edges can be estimated via the Moore-Penrose pseudoinverse of the Laplacian matrix. Moreover, the variances of the treatment effects are estimated in analogy to electrical effective resistances. It is shown that this method, being computationally simple, leads to the usual fixed effect model estimate when applied to pairwise meta-analysis and is consistent with published results when applied to network meta-analysis examples from the literature. Moreover, problems of heterogeneity and inconsistency, random effects modeling and including multi-armed trials are addressed. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks.

PubMed

Çakir, Yüksel

2016-01-01

Synchronization behaviors of bursting neurons coupled through electrical and dynamic chemical synapses are investigated. The Izhikevich model is used with random and small world network of bursting neurons. Various currents which consist of diffusive electrical and time-delayed dynamic chemical synapses are used in the simulations to investigate the influences of synaptic currents and couplings on synchronization behavior of bursting neurons. The effects of parameters, such as time delay, inhibitory synaptic strengths, and decay time on synchronization behavior are investigated. It is observed that in random networks with no delay, bursting synchrony is established with the electrical synapse alone, single spiking synchrony is observed with hybrid coupling. In small world network with no delay, periodic bursting behavior with multiple spikes is observed when only chemical and only electrical synapse exist. Single-spike and multiple-spike bursting are established with hybrid couplings. A decrease in the synchronization measure is observed with zero time delay, as the decay time is increased in random network. For synaptic delays which are above active phase period, synchronization measure increases with an increase in synaptic strength and time delay in small world network. However, in random network, it increases with only an increase in synaptic strength.

Computational model of electrically coupled, intrinsically distinct pacemaker neurons.

PubMed

Soto-Treviño, Cristina; Rabbah, Pascale; Marder, Eve; Nadim, Farzan

2005-07-01

Electrical coupling between neurons with similar properties is often studied. Nonetheless, the role of electrical coupling between neurons with widely different intrinsic properties also occurs, but is less well understood. Inspired by the pacemaker group of the crustacean pyloric network, we developed a multicompartment, conductance-based model of a small network of intrinsically distinct, electrically coupled neurons. In the pyloric network, a small intrinsically bursting neuron, through gap junctions, drives 2 larger, tonically spiking neurons to reliably burst in-phase with it. Each model neuron has 2 compartments, one responsible for spike generation and the other for producing a slow, large-amplitude oscillation. We illustrate how these compartments interact and determine the dynamics of the model neurons. Our model captures the dynamic oscillation range measured from the isolated and coupled biological neurons. At the network level, we explore the range of coupling strengths for which synchronous bursting oscillations are possible. The spatial segregation of ionic currents significantly enhances the ability of the 2 neurons to burst synchronously, and the oscillation range of the model pacemaker network depends not only on the strength of the electrical synapse but also on the identity of the neuron receiving inputs. We also compare the activity of the electrically coupled, distinct neurons with that of a network of coupled identical bursting neurons. For small to moderate coupling strengths, the network of identical elements, when receiving asymmetrical inputs, can have a smaller dynamic range of oscillation than that of its constituent neurons in isolation.

Towards Smart Grid Dynamic Ratings

NASA Astrophysics Data System (ADS)

Cheema, Jamal; Clark, Adrian; Kilimnik, Justin; Pavlovski, Chris; Redman, David; Vu, Maria

2011-08-01

The energy distribution industry is giving greater attention to smart grid solutions as a means for increasing the capabilities, efficiency and reliability of the electrical power network. The smart grid makes use of intelligent monitoring and control devices throughout the distribution network to report on electrical properties such as voltage, current and power, as well as raising network alarms and events. A further aspect of the smart grid embodies the dynamic rating of electrical assets of the network. This fundamentally involves a rating of the load current capacity of electrical assets including feeders, transformers and switches. The mainstream approach to rate assets is to apply the vendor plate rating, which often under utilizes assets, or in some cases over utilizes when environmental conditions reduce the effective rated capacity, potentially reducing lifetime. Using active intelligence we have developed a rating system that rates assets in real time based upon several events. This allows for a far more efficient and reliable electrical grid that is able to extend further the life and reliability of the electrical network. In this paper we describe our architecture, the observations made during development and live deployment of the solution into operation. We also illustrate how this solution blends with the smart grid by proposing a dynamic rating system for the smart grid.

Flowable Conducting Particle Networks in Redox-Active Electrolytes for Grid Energy Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hatzell, K. B.; Boota, M.; Kumbur, E. C.

2015-01-01

This study reports a new hybrid approach toward achieving high volumetric energy and power densities in an electrochemical flow capacitor for grid energy storage. The electrochemical flow capacitor suffers from high self-discharge and low energy density because charge storage is limited to the available surface area (electric double layer charge storage). Here, we examine two carbon materials as conducting particles in a flow battery electrolyte containing the VO2+/VO2+ redox couple. Highly porous activated carbon spheres (CSs) and multi-walled carbon nanotubes (MWCNTs) are investigated as conducting particle networks that facilitate both faradaic and electric double layer charge storage. Charge storage contributionsmore » (electric double layer and faradaic) are distinguished for flow-electrodes composed of MWCNTs and activated CSs. A MWCNT flow-electrode based in a redox-active electrolyte containing the VO2+/VO2+ redox couple demonstrates 18% less self-discharge, 10 X more energy density, and 20 X greater power densities (at 20 mV s-1) than one based on a non-redox active electrolyte. Furthermore, a MWCNT redox-active flow electrode demonstrates 80% capacitance retention, and >95% coulombic efficiency over 100 cycles, indicating the feasibility of utilizing conducting networks with redox chemistries for grid energy storage.« less

Flowable conducting particle networks in redox-active electrolytes for grid energy storage

DOE PAGES

Hatzell, K. B.; Boota, M.; Kumbur, E. C.; ...

2015-01-09

This paper reports a new hybrid approach toward achieving high volumetric energy and power densities in an electrochemical flow capacitor for grid energy storage. The electrochemical flow capacitor suffers from high self-discharge and low energy density because charge storage is limited to the available surface area (electric double layer charge storage). Here, we examine two carbon materials as conducting particles in a flow battery electrolyte containing the VO 2+/VO 2 + redox couple. Highly porous activated carbon spheres (CSs) and multi-walled carbon nanotubes (MWCNTs) are investigated as conducting particle networks that facilitate both faradaic and electric double layer charge storage.more » Charge storage contributions (electric double layer and faradaic) are distinguished for flow-electrodes composed of MWCNTs and activated CSs. A MWCNT flow-electrode based in a redox-active electrolyte containing the VO 2+/VO 2 + redox couple demonstrates 18% less self-discharge, 10 X more energy density, and 20 X greater power densities (at 20 mV s -1) than one based on a non-redox active electrolyte. Additionally, a MWCNT redox-active flow electrode demonstrates 80% capacitance retention, and >95% coulombic efficiency over 100 cycles, indicating the feasibility of utilizing conducting networks with redox chemistries for grid energy storage.« less

Thunderstorm Hypothesis Reasoner

NASA Technical Reports Server (NTRS)

Mulvehill, Alice M.

1994-01-01

THOR is a knowledge-based system which incorporates techniques from signal processing, pattern recognition, and artificial intelligence (AI) in order to determine the boundary of small thunderstorms which develop and dissipate over the area encompassed by KSC and the Cape Canaveral Air Force Station. THOR interprets electric field mill data (derived from a network of electric field mills) by using heuristics and algorithms about thunderstorms that have been obtained from several domain specialists. THOR generates two forms of output: contour plots which visually describe the electric field activity over the network and a verbal interpretation of the activity. THOR uses signal processing and pattern recognition to detect signatures associated with noise or thunderstorm behavior in a near real time fashion from over 31 electrical field mills. THOR's AI component generates hypotheses identifying areas which are under a threat from storm activity, such as lightning. THOR runs on a VAX/VMS at the Kennedy Space Center. Its software is a coupling of C and FORTRAN programs, several signal processing packages, and an expert system development shell.

Autonomous Optimization of Targeted Stimulation of Neuronal Networks

PubMed Central

Kumar, Sreedhar S.; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin

2016-01-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable ‘state’ to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers. PMID:27509295

Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

PubMed

Kumar, Sreedhar S; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin; Egert, Ulrich

2016-08-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable 'state' to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.

Multiple Factors-Aware Diffusion in Social Networks

DTIC Science & Technology

2015-05-22

Multiple Factors-Aware Diffusion in Social Networks Chung-Kuang Chou(B) and Ming-Syan Chen Department of Electrical Engineering, National Taiwan...propagates from nodes to nodes over a social network . The behavior that a node adopts an information piece in a social network can be affected by...Twitter dataset. Keywords: Social networks · Diffusion models 1 Introduction Information diffusion in social networks has been an active research field

Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled population.

PubMed

Wei, Xile; Zhang, Danhong; Lu, Meili; Wang, Jiang; Yu, Haitao; Che, Yanqiu

2015-01-01

This paper presents the endogenous electric field in chemical or electrical synaptic coupled networks, aiming to study the role of endogenous field feedback in the signal propagation in neural systems. It shows that the feedback of endogenous fields to network activities can reduce the required energy of the noise and enhance the transmission of input signals in hybrid coupled populations. As a common and important nonsynaptic interactive method among neurons, particularly, the endogenous filed feedback can not only promote the detectability of exogenous weak signal in hybrid coupled neural population but also enhance the robustness of the detectability against noise. Furthermore, with the increasing of field coupling strengths, the endogenous field feedback is conductive to the stochastic resonance by facilitating the transition of cluster activities from the no spiking to spiking regions. Distinct from synaptic coupling, the endogenous field feedback can play a role as internal driving force to boost the population activities, which is similar to the noise. Thus, it can help to transmit exogenous weak signals within the network in the absence of noise drive via the stochastic-like resonance.

Emergence of Critical Behavior in β-Cell Network

NASA Astrophysics Data System (ADS)

Westacott, Matthew; Hraha, Thomas; McClatchey, Mason; Pozzoli, Marina; Benninger, Richard

2014-03-01

The β-cell is a cell type located in the Islet of Langerhans, a micro-organ of the pancreas which maintains glucose homeostasis through secretion of insulin. An electrophysiological process governing insulin release occurs through initial uptake of blood glucose and generation of ATP which inhibits the ATP sensitive potassium channel (K-ATP) causing membrane depolarization (activation). Neighboring β-cells are electrically coupled through gap junctions which allow passage of cationic molecules, creating a network of coupled electrical oscillators. Cells exhibiting hyperpolzarized (inactive) membrane potential affect behavior of neighboring cells by electrically suppressing their depolarization. Here we observe critical behavior between global active-inactive states by increasing the number of inactive elements with the K-ATP inhibitor Diazoxide and a tunable ATP insensitive transgenic mouse model. We show this behavior occurs due to from cell-cell coupling as mice lacking β-cell gap junctions show no critical behavior. Also, a computational β-cell model was expanded to construct a coupled β-cell network and we show this model replicates the critical behavior seen in-vitro.While electrical activity of single β-cells is well studied these data highlight a newly defined characteristic of their emergent multicellular behavior within the Islet of Langerhans and may elucidate pathophysiology of Diabetes due to mutations in the K-ATP channel.

State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

PubMed

Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

2011-11-16

The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

Prediction of heart abnormality using MLP network

NASA Astrophysics Data System (ADS)

Hashim, Fakroul Ridzuan; Januar, Yulni; Mat, Muhammad Hadzren; Rizman, Zairi Ismael; Awang, Mat Kamil

2018-02-01

Heart abnormality does not choose gender, age and races when it strikes. With no warning signs or symptoms, it can result to a sudden death of the patient. Generally, heart's irregular electrical activity is defined as heart abnormality. Via implementation of Multilayer Perceptron (MLP) network, this paper tries to develop a program that allows the detection of heart abnormality activity. Utilizing several training algorithms with Purelin activation function, an amount of heartbeat signals received through the electrocardiogram (ECG) will be employed to condition the MLP network.

Tansig activation function (of MLP network) for cardiac abnormality detection

NASA Astrophysics Data System (ADS)

Adnan, Ja'afar; Daud, Nik Ghazali Nik; Ishak, Mohd Taufiq; Rizman, Zairi Ismael; Rahman, Muhammad Izzuddin Abd

2018-02-01

Heart abnormality often occurs regardless of gender, age and races. This problem sometimes does not show any symptoms and it can cause a sudden death to the patient. In general, heart abnormality is the irregular electrical activity of the heart. This paper attempts to develop a program that can detect heart abnormality activity through implementation of Multilayer Perceptron (MLP) network. A certain amount of data of the heartbeat signals from the electrocardiogram (ECG) will be used in this project to train the MLP network by using several training algorithms with Tansig activation function.

Developing a tissue-engineered neural-electrical relay using encapsulated neuronal constructs on conducting polymer fibers.

PubMed

Cullen, D Kacy; R Patel, Ankur; Doorish, John F; Smith, Douglas H; Pfister, Bryan J

2008-12-01

Neural-electrical interface platforms are being developed to extracellularly monitor neuronal population activity. Polyaniline-based electrically conducting polymer fibers are attractive substrates for sustained functional interfaces with neurons due to their flexibility, tailored geometry and controlled electro-conductive properties. In this study, we addressed the neurobiological considerations of utilizing small diameter (<400 microm) fibers consisting of a blend of electrically conductive polyaniline and polypropylene (PA-PP) as the backbone of encapsulated tissue-engineered neural-electrical relays. We devised new approaches to promote survival, adhesion and neurite outgrowth of primary dorsal root ganglion neurons on PA-PP fibers. We attained a greater than ten-fold increase in the density of viable neurons on fiber surfaces to approximately 700 neurons mm(-2) by manipulating surrounding surface charges to bias settling neuronal suspensions toward fibers coated with cell-adhesive ligands. This stark increase in neuronal density resulted in robust neuritic extension and network formation directly along the fibers. Additionally, we encapsulated these neuronal networks on PA-PP fibers using agarose to form a protective barrier while potentially facilitating network stability. Following encapsulation, the neuronal networks maintained integrity, high viability (>85%) and intimate adhesion to PA-PP fibers. These efforts accomplished key prerequisites for the establishment of functional electrical interfaces with neuronal populations using small diameter PA-PP fibers-specifically, improved neurocompatibility, high-density neuronal adhesion and neuritic network development directly on fiber surfaces.

Wireless Sensor Network for Radiometric Detection and Assessment of Partial Discharge in High-Voltage Equipment

NASA Astrophysics Data System (ADS)

Upton, D. W.; Saeed, B. I.; Mather, P. J.; Lazaridis, P. I.; Vieira, M. F. Q.; Atkinson, R. C.; Tachtatzis, C.; Garcia, M. S.; Judd, M. D.; Glover, I. A.

2018-03-01

Monitoring of partial discharge (PD) activity within high-voltage electrical environments is increasingly used for the assessment of insulation condition. Traditional measurement techniques employ technologies that either require off-line installation or have high power consumption and are hence costly. A wireless sensor network is proposed that utilizes only received signal strength to locate areas of PD activity within a high-voltage electricity substation. The network comprises low-power and low-cost radiometric sensor nodes which receive the radiation propagated from a source of PD. Results are reported from several empirical tests performed within a large indoor environment and a substation environment using a network of nine sensor nodes. A portable PD source emulator was placed at multiple locations within the network. Signal strength measured by the nodes is reported via WirelessHART to a data collection hub where it is processed using a location algorithm. The results obtained place the measured location within 2 m of the actual source location.

Defining toxicological tipping points in neuronal network development.

PubMed

Frank, Christopher L; Brown, Jasmine P; Wallace, Kathleen; Wambaugh, John F; Shah, Imran; Shafer, Timothy J

2018-02-02

Measuring electrical activity of neural networks by microelectrode array (MEA) has recently shown promise for screening level assessments of chemical toxicity on network development and function. Important aspects of interneuronal communication can be quantified from a single MEA recording, including individual firing rates, coordinated bursting, and measures of network synchrony, providing rich datasets to evaluate chemical effects. Further, multiple recordings can be made from the same network, including during the formation of these networks in vitro. The ability to perform multiple recording sessions over the in vitro development of network activity may provide further insight into developmental effects of neurotoxicants. In the current study, a recently described MEA-based screen of 86 compounds in primary rat cortical cultures over 12 days in vitro was revisited to establish a framework that integrates all available primary measures of electrical activity from MEA recordings into a composite metric for deviation from normal activity (total scalar perturbation). Examining scalar perturbations over time and increasing concentration of compound allowed for definition of critical concentrations or "tipping points" at which the neural networks switched from recovery to non-recovery trajectories for 42 compounds. These tipping point concentrations occurred at predominantly lower concentrations than those causing overt cell viability loss or disrupting individual network parameters, suggesting tipping points may be a more sensitive measure of network functional loss. Comparing tipping points for six compounds with plasma concentrations known to cause developmental neurotoxicity in vivo demonstrated strong concordance and suggests there is potential for using tipping points for chemical prioritization. Published by Elsevier Inc.

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

The Influence of Neuronal Density and Maturation on Network Activity of Hippocampal Cell Cultures: A Methodological Study

PubMed Central

Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm2 cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm2 cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm2 are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs. PMID:24386305

The influence of neuronal density and maturation on network activity of hippocampal cell cultures: a methodological study.

PubMed

Biffi, Emilia; Regalia, Giulia; Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm(2) cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm(2) cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm(2) are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs.

Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand.

PubMed

Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

2015-01-01

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers' peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers' location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual 'map' of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand

PubMed Central

Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

2015-01-01

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments. PMID:26226511

Impact of delays on the synchronization transitions of modular neuronal networks with hybrid synapses

NASA Astrophysics Data System (ADS)

Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

2013-09-01

The combined effects of the information transmission delay and the ratio of the electrical and chemical synapses on the synchronization transitions in the hybrid modular neuronal network are investigated in this paper. Numerical results show that the synchronization of neuron activities can be either promoted or destroyed as the information transmission delay increases, irrespective of the probability of electrical synapses in the hybrid-synaptic network. Interestingly, when the number of the electrical synapses exceeds a certain level, further increasing its proportion can obviously enhance the spatiotemporal synchronization transitions. Moreover, the coupling strength has a significant effect on the synchronization transition. The dominated type of the synapse always has a more profound effect on the emergency of the synchronous behaviors. Furthermore, the results of the modular neuronal network structures demonstrate that excessive partitioning of the modular network may result in the dramatic detriment of neuronal synchronization. Considering that information transmission delays are inevitable in intra- and inter-neuronal networks communication, the obtained results may have important implications for the exploration of the synchronization mechanism underlying several neural system diseases such as Parkinson's Disease.

Improvement of calculation method for electrical parameters of short network of ore-thermal furnaces

NASA Astrophysics Data System (ADS)

Aliferov, A. I.; Bikeev, R. A.; Goreva, L. P.

2017-10-01

The paper describes a new calculation method for active and inductive resistance of split interleaved current leads packages in ore-thermal electric furnaces. The method is developed on basis of regression analysis of dependencies of active and inductive resistances of the packages on their geometrical parameters, mutual disposition and interleaving pattern. These multi-parametric calculations have been performed with ANSYS software. The proposed method allows solving split current lead electrical parameters minimization and balancing problems for ore-thermal furnaces.

Effects of Increasing Neuromuscular Electrical Stimulation Current Intensity on Cortical Sensorimotor Network Activation: A Time Domain fNIRS Study

PubMed Central

Zucchelli, Lucia; Perrey, Stephane; Contini, Davide; Caffini, Matteo; Spinelli, Lorenzo; Kerr, Graham; Quaresima, Valentina; Ferrari, Marco; Torricelli, Alessandro

2015-01-01

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions. PMID:26158464

Effects of Increasing Neuromuscular Electrical Stimulation Current Intensity on Cortical Sensorimotor Network Activation: A Time Domain fNIRS Study.

PubMed

Muthalib, Makii; Re, Rebecca; Zucchelli, Lucia; Perrey, Stephane; Contini, Davide; Caffini, Matteo; Spinelli, Lorenzo; Kerr, Graham; Quaresima, Valentina; Ferrari, Marco; Torricelli, Alessandro

2015-01-01

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

Sensory Regulation of Network Components Underlying Ciliary Locomotion in Hermissenda

PubMed Central

Crow, Terry; Tian, Lian-Ming

2008-01-01

Ciliary locomotion in the nudibranch mollusk Hermissenda is modulated by the visual and graviceptive systems. Components of the neural network mediating ciliary locomotion have been identified including aggregates of polysensory interneurons that receive monosynaptic input from identified photoreceptors and efferent neurons that activate cilia. Illumination produces an inhibition of type Ii (off-cell) spike activity, excitation of type Ie (on-cell) spike activity, decreased spike activity in type IIIi inhibitory interneurons, and increased spike activity of ciliary efferent neurons. Here we show that pairs of type Ii interneurons and pairs of type Ie interneurons are electrically coupled. Neither electrical coupling or synaptic connections were observed between Ie and Ii interneurons. Coupling is effective in synchronizing dark-adapted spontaneous firing between pairs of Ie and pairs of Ii interneurons. Out-of-phase burst activity, occasionally observed in dark-adapted and light-adapted pairs of Ie and Ii interneurons, suggests that they receive synaptic input from a common presynaptic source or sources. Rhythmic activity is typically not a characteristic of dark-adapted, light-adapted, or light-evoked firing of type I interneurons. However, burst activity in Ie and Ii interneurons may be elicited by electrical stimulation of pedal nerves or generated at the offset of light. Our results indicate that type I interneurons can support the generation of both rhythmic activity and changes in tonic firing depending on sensory input. This suggests that the neural network supporting ciliary locomotion may be multifunctional. However, consistent with the nonmuscular and nonrhythmic characteristics of visually modulated ciliary locomotion, type I interneurons exhibit changes in tonic activity evoked by illumination. PMID:18768639

The impact of electric vehicles on the outlook of future energy system

NASA Astrophysics Data System (ADS)

Zhuk, A.; Buzoverov, E.

2018-02-01

Active promotion of electric vehicles (EVs) and technology of fast EV charging in the medium term may cause significant peak loads on the energy system, what necessitates making strategic decisions related to the development of generating capacities, distribution networks with EV charging infrastructure, and priorities in the development of battery electric vehicles and vehicles with electrochemical generators. The paper analyses one of the most significant aspects of joint development of electric transport system and energy system in the conditions of substantial growth of energy consumption by EVs. The assessments of per-unit-costs of operation and depreciation of EV power unit were made, taking into consideration the expenses of electric power supply. The calculations show that the choice of electricity buffering method for EV fast charging depends on the character of electricity infrastructure in the region where the electric transport is operating. In the conditions of high density of electricity network and a large number of EVs, the stationary storage facilities or the technology of distributed energy storage in EV batteries - vehicle-to-grid (V2G) technology may be used for buffering. In the conditions of low density and low capacity of electricity networks, the most economical solution could be usage of EVs with traction power units based on the combination of air-aluminum electrochemical generator and a buffer battery of small capacity.

Analysis and Synthesis of Adaptive Neural Elements and Assembles

DTIC Science & Technology

1992-02-17

effects of neuromodulators on electrically activity. Based on the simulations it appears that there are potentially novel mechanisms with which modulatory...and Byrne, J.H. A learning rule based on empirically-derived activity-dependent neuromodulation supports operant conditioning in a small network...dependent neuromodulation can support operant conditioning in a small oscillatory network". 2. Society for Neuroscience Short Course on Neural

Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials

NASA Astrophysics Data System (ADS)

Radivojevic, Milos; Jäckel, David; Altermatt, Michael; Müller, Jan; Viswam, Vijay; Hierlemann, Andreas; Bakkum, Douglas J.

2016-08-01

A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.

Why do electricity policy and competitive markets fail to use advanced PV systems to improve distribution power quality?

DOE Office of Scientific and Technical Information (OSTI.GOV)

McHenry, Mark P.; Johnson, Jay; Hightower, Mike

The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the networkmore » characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. As a result, we discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.« less

Why do electricity policy and competitive markets fail to use advanced PV systems to improve distribution power quality?

DOE PAGES

McHenry, Mark P.; Johnson, Jay; Hightower, Mike

2016-01-01

The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the networkmore » characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. As a result, we discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.« less

Local network assessment

NASA Astrophysics Data System (ADS)

Glen, D. V.

1985-04-01

Local networks, related standards activities of the Institute of Electrical and Electronics Engineers the American National Standards Institute and other elements are presented. These elements include: (1) technology choices such as topology, transmission media, and access protocols; (2) descriptions of standards for the 802 local area networks (LAN's); high speed local networks (HSLN's) and military specification local networks; and (3) intra- and internetworking using bridges and gateways with protocols Interconnection (OSI) reference model. The convergence of LAN/PBX technology is also described.

Rational modulation of neuronal processing with applied electric fields.

PubMed

Bikson, Marom; Radman, Thomas; Datta, Abhishek

2006-01-01

Traditional approaches to electrical stimulation, using trains of supra-threshold pulses to trigger action potentials, may be replaced or augmented by using 'rational' sub-threshold stimulation protocols that incorporate knowledge of single neuron geometry, inhomogeneous tissue properties, and nervous system information coding. Sub-threshold stimulation, at intensities (well) below those sufficient to trigger action potentials, may none-the-less exert a profound effect on brain function through modulation of concomitant neuronal activity. For example, small DC fields may coherently polarize a network of neurons and thus modulate the simultaneous processing of afferent synaptic input as well as resulting changes in synaptic plasticity. Through 'activity-dependent plasticity', sub-threshold fields may allow specific targeting of pathological networks and are thus particularly suitable to overcome the poor anatomical focus of noninvasive (transcranial) electrical stimulation. Additional approaches to improve targeting in transcranial stimulation using novel electrode configurations are also introduced.

Numerical investigation into blood clotting at the bone-dental implant interface in the presence of an electrical stimulus.

PubMed

Vanegas-Acosta, J C; Garzón-Alvarado, D A; Lancellotti, V

2013-12-01

The insertion of a dental implant activates a sequence of wound healing events ending with bone formation and implant osseointegration. This sequence starts with the blood coagulation process and the formation of a fibrin network that detains spilt blood. Fibrin formation can be simplified as the kinetic reaction between thrombin and fibrinogen preceding the conversion of fibrinogen into fibrin. Based on experimental observations of the electrical properties of these molecules, we present a hypothesis for the mechanism of a static electrical stimulus in controlling the formation of the blood clot. Specifically, the electrical stimulus increases the fibrin network formation in such a way that a preferential region of higher fibrin density is obtained. This hypothesis is validated by means of a numerical model for the blood clot formation at the bone-dental implant interface. Numerical results compare favorably to experimental observations for blood clotting with and without the static electrical stimulus. It is concluded that the density of the fibrin network depends on the strength of the static electrical stimulus, and that the blood clot formation has a preferential direction of formation in the presence of the electrical signal. © 2013 Published by Elsevier Ltd. All rights reserved.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

An EBIC study of dislocation networks in unprocessed and unprocessed web silicon ribbon. [for solar cells

NASA Technical Reports Server (NTRS)

Fieldler, F. S.; Ast, D.

1982-01-01

Experimental techniques for the preparation of electron beam induced current samples of Web-dentritic silicon are described. Both as grown and processed material were investigated. High density dislocation networks were found close to twin planes in the bulk of the material. The electrical activity of these networks is reduced in processed material.

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels†

PubMed Central

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L.; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J.; Hierlemann, Andreas

2017-01-01

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm2). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons. PMID:25973786

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels.

PubMed

Müller, Jan; Ballini, Marco; Livi, Paolo; Chen, Yihui; Radivojevic, Milos; Shadmani, Amir; Viswam, Vijay; Jones, Ian L; Fiscella, Michele; Diggelmann, Roland; Stettler, Alexander; Frey, Urs; Bakkum, Douglas J; Hierlemann, Andreas

2015-07-07

Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 μm) within a large overall sensing area (3.85 × 2.10 mm(2)). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.

77 FR 47828 - Amended Notice of Intent To Prepare the Hawai'i Clean Energy Programmatic Environmental Impact...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-10

... efficiency and renewable energy activities and technologies to be analyzed in the PEIS and, accordingly, has... Renewables, (4) Alternative Transportation Fuels and Modes, and (5) Electrical Transmission and Distribution... Kaua'i; electric vehicle public charging networks; efficient appliance rebates; solar water heating...

Three-dimensional micro-electrode array for recording dissociated neuronal cultures.

PubMed

Musick, Katherine; Khatami, David; Wheeler, Bruce C

2009-07-21

This work demonstrates the design, fabrication, packaging, characterization, and functionality of an electrically and fluidically active three-dimensional micro-electrode array (3D MEA) for use with neuronal cell cultures. The successful function of the device implies that this basic concept-construction of a 3D array with a layered approach-can be utilized as the basis for a new family of neural electrode arrays. The 3D MEA prototype consists of a stack of individually patterned thin films that form a cell chamber conducive to maintaining and recording the electrical activity of a long-term three-dimensional network of rat cortical neurons. Silicon electrode layers contain a polymer grid for neural branching, growth, and network formation. Along the walls of these electrode layers lie exposed gold electrodes which permit recording and stimulation of the neuronal electrical activity. Silicone elastomer micro-fluidic layers provide a means for loading dissociated neurons into the structure and serve as the artificial vasculature for nutrient supply and aeration. The fluidic layers also serve as insulation for the micro-electrodes. Cells have been shown to survive in the 3D MEA for up to 28 days, with spontaneous and evoked electrical recordings performed in that time. The micro-fluidic capability was demonstrated by flowing in the drug tetrotodoxin to influence the activity of the culture.

Fluid power network for centralized electricity generation in offshore wind farms

NASA Astrophysics Data System (ADS)

Jarquin-Laguna, A.

2014-06-01

An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network. Due to the stochastic nature of the wind and wake interaction effects between turbines, the operating parameters (i.e. pitch angle, rotor speed) of each turbine are different. Time domain simulations, including the main turbine dynamics and laminar transient flow in pipelines, are used to evaluate the efficiency and rotor speed stability of the hydraulic system. It is shown that a passive control of the rotor speed, as proposed in previous work for a single hydraulic turbine, has strong limitations in terms of performance for more than one turbine coupled to the same hydraulic network. It is concluded that in order to connect several turbines, a passive control strategy of the rotor speed is not sufficient and a hydraulic network with constant pressure is suggested. However, a constant pressure network requires the addition of active control at the hydraulic motors and spear valves, increasing the complexity of the initial concept. Further work needs to be done to incorporate an active control strategy and evaluate the feasibility of the constant pressure hydraulic network.

Will electrical cyber-physical interdependent networks undergo first-order transition under random attacks?

NASA Astrophysics Data System (ADS)

Ji, Xingpei; Wang, Bo; Liu, Dichen; Dong, Zhaoyang; Chen, Guo; Zhu, Zhenshan; Zhu, Xuedong; Wang, Xunting

2016-10-01

Whether the realistic electrical cyber-physical interdependent networks will undergo first-order transition under random failures still remains a question. To reflect the reality of Chinese electrical cyber-physical system, the "partial one-to-one correspondence" interdependent networks model is proposed and the connectivity vulnerabilities of three realistic electrical cyber-physical interdependent networks are analyzed. The simulation results show that due to the service demands of power system the topologies of power grid and its cyber network are highly inter-similar which can effectively avoid the first-order transition. By comparing the vulnerability curves between electrical cyber-physical interdependent networks and its single-layer network, we find that complex network theory is still useful in the vulnerability analysis of electrical cyber-physical interdependent networks.

The use of dendrograms to describe the electrical activity of motoneurons underlying behaviors in leeches

PubMed Central

Juárez-Hernández, León J.; Bisson, Giacomo; Torre, Vincent

2013-01-01

The present manuscript aims at identifying patterns of electrical activity recorded from neurons of the leech nervous system, characterizing specific behaviors. When leeches are at rest, the electrical activity of neurons and motoneurons is poorly correlated. When leeches move their head and/or tail, in contrast, action potential (AP) firing becomes highly correlated. When the head or tail suckers detach, specific patterns of electrical activity are detected. During elongation and contraction the electrical activity of motoneurons in the Medial Anterior and Dorsal Posterior nerves increase, respectively, and several motoneurons are activated both during elongation and contraction. During crawling, swimming, and pseudo-swimming patterns of electrical activity are better described by the dendrograms of cross-correlations of motoneurons pairs. Dendrograms obtained from different animals exhibiting the same behavior are similar and by averaging these dendrograms we obtained a template underlying a given behavior. By using this template, the corresponding behavior is reliably identified from the recorded electrical activity. The analysis of dendrograms during different leech behavior reveals the fine orchestration of motoneurons firing specific to each stereotyped behavior. Therefore, dendrograms capture the subtle changes in the correlation pattern of neuronal networks when they become involved in different tasks or functions. PMID:24098274

Channeling the Central Dogma

PubMed Central

Calabrese, Ronald L.

2014-01-01

How do neurons and networks achieve their characteristic electrical activity, regulate this activity homeostatically, and yet show population variability in expression? O'Leary et al. address some of these thorny questions in this theoretical analysis that starts with the Central Dogma. PMID:24853932

Nanoparticles Induce Changes of the Electrical Activity of Neuronal Networks on Microelectrode Array Neurochips

PubMed Central

Gramowski, Alexandra; Flossdorf, Juliane; Bhattacharya, Kunal; Jonas, Ludwig; Lantow, Margareta; Rahman, Qamar; Schiffmann, Dietmar; Weiss, Dieter G.; Dopp, Elke

2010-01-01

Background Nanomaterials are extensively used in industry and daily life, but little is known about possible health effects. An intensified research regarding toxicity of nanomaterials is urgently needed. Several studies have demonstrated that nanoparticles (NPs; diameter < 100 nm) can be transported to the central nervous system; however, interference of NPs with the electrical activity of neurons has not yet been shown. Objectives/methods We investigated the acute electrophysiological effects of carbon black (CB), hematite (Fe2O3), and titanium dioxide (TiO2) NPs in primary murine cortical networks on microelectrode array (MEA) neurochips. Uptake of NPs was studied by transmission electron microscopy (TEM), and intracellular formation of reactive oxygen species (ROS) was studied by flow cytometry. Results The multiparametric assessment of electrical activity changes caused by the NPs revealed an NP-specific and concentration-dependent inhibition of the firing patterns. The number of action potentials and the frequency of their patterns (spike and burst rates) showed a significant particle-dependent decrease and significant differences in potency. Further, we detected the uptake of CB, Fe2O3, and TiO2 into glial cells and neurons by TEM. Additionally, 24 hr exposure to TiO2 NPs caused intracellular formation of ROS in neuronal and glial cells, whereas exposure to CB and Fe2O3 NPs up to a concentration of 10 μg/cm2 did not induce significant changes in free radical levels. Conclusion NPs at low particle concentrations are able to exhibit a neurotoxic effect by disturbing the electrical activity of neuronal networks, but the underlying mechanisms depend on the particle type. PMID:20457553

Torsional vibration measurements on rotating shaft system using laser doppler vibrometer

NASA Astrophysics Data System (ADS)

Xiang, Ling; Yang, Shixi; Gan, Chunbiao

2012-11-01

In this work, a laser torsional vibrameter was used to measure the torsion vibration of a rotating shaft system under electrical network impact. Based on the principles of laser Doppler velocimetry, the laser torsional vibrometer (LTV) are non-contact measurement of torsional oscillation of rotating shafts, offering significant advantages over conventional techniques. Furthermore, a highly complex shafting system is analyzed by a modified Riccati torsional transfer matrix. The system is modeled as a chain consisting of an elastic spring with concentrated mass points, and the multi-segments lumped mass model is established for this shafting system. By the modified Riccati torsional transfer matrix method, an accumulated calculation is effectively eliminated to obtain the natural frequencies. The electrical network impacts can activize the torsional vibration of shaft system, and the activized torsion vibration frequencies contained the natural frequencies of shaft system. The torsional vibrations of the shaft system were measured under electrical network impacts in laser Doppler torsional vibrometer. By comparisons, the natural frequencies by measurement were consistent with the values by calculation. The results verify the instrument is robust, user friendly and can be calibrated in situ. The laser torsional vibrometer represents a significant step forward in rotating machinery diagnostics.

Automatic control in multidrive electrotechnical complexes with semiconductor converters

NASA Astrophysics Data System (ADS)

Vasilev, B. U.; Mardashov, D. V.

2017-01-01

The frequency convertor and the automatic control system, which can be used in the multi-drive electromechanical system with a few induction motions, are considered. The paper presents the structure of existing modern multi-drive electric drives inverters, namely, electric drives with a total frequency converter and few electric motions, and an electric drive, in which the converter is used for power supply and control of the independent frequency. It was shown that such technical solutions of frequency converters possess a number of drawbacks. The drawbacks are given. It was shown that the control of technological processes using the electric drive of this structure may be provided under very limited conditions, as the energy efficiency and the level of electromagnetic compatibility of electric drives is low. The authors proposed using a multi-inverter structure with an active rectifier in multidrive electric drives with induction motors frequency converters. The application of such frequency converter may solve the problem of electromagnetic compatibility, namely, consumption of sinusoidal currents from the network and the maintenance of a sinusoidal voltage and energy compatibility, namely, consumption of practically active energy from the network. Also, the paper proposes the use of the automatic control system, which by means of a multi-inverter frequency converter provides separate control of drive machines and flexible regulation of technological processes. The authors present oscillograms, which confirm the described characteristics of the developed electrical drive. The possible subsequent ways to improve the multi-motor drives are also described.

Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

NASA Astrophysics Data System (ADS)

Rodríguez, Ana R.; O'Neill, Kate M.; Swiatkowski, Przemyslaw; Patel, Mihir V.; Firestein, Bonnie L.

2018-02-01

Objective. This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks. Approach. We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ PSD-95 non-binding) expression cellularly and network-wide, respectively. Main results. Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity. Significance. Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

Inhibition Potentiates the Synchronizing Action of Electrical Synapses

PubMed Central

Pfeuty, Benjamin; Golomb, David; Mato, Germán; Hansel, David

2007-01-01

In vivo and in vitro experimental studies have found that blocking electrical interactions connecting GABAergic interneurons reduces oscillatory activity in the γ range in cortex. However, recent theoretical works have shown that the ability of electrical synapses to promote or impede synchrony, when alone, depends on their location on the dendritic tree of the neurons, the intrinsic properties of the neurons and the connectivity of the network. The goal of the present paper is to show that this versatility in the synchronizing ability of electrical synapses is greatly reduced when the neurons also interact via inhibition. To this end, we study a model network comprising two-compartment conductance-based neurons interacting with both types of synapses. We investigate the effect of electrical synapses on the dynamical state of the network as a function of the strength of the inhibition. We find that for weak inhibition, electrical synapses reinforce inhibition-generated synchrony only if they promote synchrony when they are alone. In contrast, when inhibition is sufficiently strong, electrical synapses improve synchrony even if when acting alone they would stabilize asynchronous firing. We clarify the mechanism underlying this cooperative interplay between electrical and inhibitory synapses. We show that it is relevant in two physiologically observed regimes: spike-to-spike synchrony, where neurons fire at almost every cycle of the population oscillations, and stochastic synchrony, where neurons fire irregularly and at a rate which is substantially lower than the frequency of the global population rhythm. PMID:18946530

Regulation of persistent sodium currents by glycogen synthase kinase 3 encodes daily rhythms of neuronal excitability

NASA Astrophysics Data System (ADS)

Paul, Jodi R.; Dewoskin, Daniel; McMeekin, Laura J.; Cowell, Rita M.; Forger, Daniel B.; Gamble, Karen L.

2016-11-01

How neurons encode intracellular biochemical signalling cascades into electrical signals is not fully understood. Neurons in the central circadian clock in mammals provide a model system to investigate electrical encoding of biochemical timing signals. Here, using experimental and modelling approaches, we show how the activation of glycogen synthase kinase 3 (GSK3) contributes to neuronal excitability through regulation of the persistent sodium current (INaP). INaP exhibits a day/night difference in peak magnitude and is regulated by GSK3. Using mathematical modelling, we predict and confirm that GSK3 activation of INaP affects the action potential afterhyperpolarization, which increases the spontaneous firing rate without affecting the resting membrane potential. Together, these results demonstrate a crucial link between the molecular circadian clock and electrical activity, providing examples of kinase regulation of electrical activity and the propagation of intracellular signals in neuronal networks.

Transportation and dynamic networks: Models, theory, and applications to supply chains, electric power, and financial networks

NASA Astrophysics Data System (ADS)

Liu, Zugang

Network systems, including transportation and logistic systems, electric power generation and distribution networks as well as financial networks, provide the critical infrastructure for the functioning of our societies and economies. The understanding of the dynamic behavior of such systems is also crucial to national security and prosperity. The identification of new connections between distinct network systems is the inspiration for the research in this dissertation. In particular, I answer two questions raised by Beckmann, McGuire, and Winsten (1956) and Copeland (1952) over half a century ago, which are, respectively, how are electric power flows related to transportation flows and does money flow like water or electricity? In addition, in this dissertation, I achieve the following: (1) I establish the relationships between transportation networks and three other classes of complex network systems: supply chain networks, electric power generation and transmission networks, and financial networks with intermediation. The establishment of such connections provides novel theoretical insights as well as new pricing mechanisms, and efficient computational methods. (2) I develop new modeling frameworks based on evolutionary variational inequality theory that capture the dynamics of such network systems in terms of the time-varying flows and incurred costs, prices, and, where applicable, profits. This dissertation studies the dynamics of such network systems by addressing both internal competition and/or cooperation, and external changes, such as varying costs and demands. (3) I focus, in depth, on electric power supply chains. By exploiting the relationships between transportation networks and electric power supply chains, I develop a large-scale network model that integrates electric power supply chains and fuel supply markets. The model captures both the economic transactions as well as the physical transmission constraints. The model is then applied to the New England electric power supply chain consisting of 6 states, 5 fuel types, 82 power generators, with a total of 573 generating units, and 10 demand markets. The empirical case study demonstrates that the regional electricity prices simulated by the model match very well the actual electricity prices in New England. I also utilize the model to study interactions between electric power supply chains and energy fuel markets.

Alternative Fuels Data Center: Electric Vehicle Charging Network Expands at

Science.gov Websites

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Report on the survey for electrostatic discharges on Mars using NASA's Deep Space Network (DSN)

NASA Astrophysics Data System (ADS)

Arabshahi, S.; Majid, W.; Geldzahler, B.; Kocz, J.; Schulter, T.; White, L.

2017-12-01

Mars atmosphere has strong dust activity. It is suggested that the larger regional storms are capable of producing electric fields large enough to initiate electrostatic discharges. The storms have charging process similar to terrestrial dust devils and have hot cores and complicated vortex winds similar to terrestrial thunderstorms. However, due to uncertainties in our understanding of the electrical environment of the storms and absence of related in-situ measurements, the existence (or non-existence) of such electrostatic discharges on the planet is yet to be confirmed. Knowing about the electrical activity on Mars is essential for future human explorations of the planet. We have recently launched a long-term monitoring campaign at NASA's Madrid Deep Space Communication Complex (MDSCC) to search for powerful discharges on Mars. The search occurs during routine tracking of Mars orbiting spacecraft by Deep Space Network (DSN) radio telescope. In this presentation, we will report on the result of processing and analysis of the data from the first six months of our campaign.

Basic Principles of Electrical Network Reliability Optimization in Liberalised Electricity Market

NASA Astrophysics Data System (ADS)

Oleinikova, I.; Krishans, Z.; Mutule, A.

2008-01-01

The authors propose to select long-term solutions to the reliability problems of electrical networks in the stage of development planning. The guide lines or basic principles of such optimization are: 1) its dynamical nature; 2) development sustainability; 3) integrated solution of the problems of network development and electricity supply reliability; 4) consideration of information uncertainty; 5) concurrent consideration of the network and generation development problems; 6) application of specialized information technologies; 7) definition of requirements for independent electricity producers. In the article, the major aspects of liberalized electricity market, its functions and tasks are reviewed, with emphasis placed on the optimization of electrical network development as a significant component of sustainable management of power systems.

Alternative Fuels Data Center: New York Broadens Network for Electric

Science.gov Websites

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Renewable Electricity Futures (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mai, T.

2012-08-01

This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented at the 2012 RE AMP Annual Meeting. RE-AMP is an active network of 144 nonprofits and foundations across eight Midwestern states working on climate change and energy policy with the goal of reducing global warming pollution economy-wide 80% by 2050.

Global Electricity Trade Network: Structures and Implications

PubMed Central

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions. PMID:27504825

Global Electricity Trade Network: Structures and Implications.

PubMed

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S F; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions.

Optimization of return electrodes in neurostimulating arrays

NASA Astrophysics Data System (ADS)

Flores, Thomas; Goetz, Georges; Lei, Xin; Palanker, Daniel

2016-06-01

Objective. High resolution visual prostheses require dense stimulating arrays with localized inputs of individual electrodes. We study the electric field produced by multielectrode arrays in electrolyte to determine an optimal configuration of return electrodes and activation sequence. Approach. To determine the boundary conditions for computation of the electric field in electrolyte, we assessed current dynamics using an equivalent circuit of a multielectrode array with interleaved return electrodes. The electric field modeled with two different boundary conditions derived from the equivalent circuit was then compared to measurements of electric potential in electrolyte. To assess the effect of return electrode configuration on retinal stimulation, we transformed the computed electric fields into retinal response using a model of neural network-mediated stimulation. Main results. Electric currents at the capacitive electrode-electrolyte interface redistribute over time, so that boundary conditions transition from equipotential surfaces at the beginning of the pulse to uniform current density in steady state. Experimental measurements confirmed that, in steady state, the boundary condition corresponds to a uniform current density on electrode surfaces. Arrays with local return electrodes exhibit improved field confinement and can elicit stronger network-mediated retinal response compared to those with a common remote return. Connecting local return electrodes enhances the field penetration depth and allows reducing the return electrode area. Sequential activation of the pixels in large monopolar arrays reduces electrical cross-talk and improves the contrast in pattern stimulation. Significance. Accurate modeling of multielectrode arrays helps optimize the electrode configuration to maximize the spatial resolution, contrast and dynamic range of retinal prostheses.

GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

PubMed Central

Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

2018-01-01

The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

Spatial Analysis of Slowly Oscillating Electric Activity in the Gut of Mice Using Low Impedance Arrayed Microelectrodes

PubMed Central

Taniguchi, Mizuki; Kajioka, Shunichi; Shozib, Habibul B.; Sawamura, Kenta; Nakayama, Shinsuke

2013-01-01

Smooth and elaborate gut motility is based on cellular cooperation, including smooth muscle, enteric neurons and special interstitial cells acting as pacemaker cells. Therefore, spatial characterization of electric activity in tissues containing these electric excitable cells is required for a precise understanding of gut motility. Furthermore, tools to evaluate spatial electric activity in a small area would be useful for the investigation of model animals. We thus employed a microelectrode array (MEA) system to simultaneously measure a set of 8×8 field potentials in a square area of ∼1 mm2. The size of each recording electrode was 50×50 µm2, however the surface area was increased by fixing platinum black particles. The impedance of microelectrode was sufficiently low to apply a high-pass filter of 0.1 Hz. Mapping of spectral power, and auto-correlation and cross-correlation parameters characterized the spatial properties of spontaneous electric activity in the ileum of wild-type (WT) and W/Wv mice, the latter serving as a model of impaired network of pacemaking interstitial cells. Namely, electric activities measured varied in both size and cooperativity in W/Wv mice, despite the small area. In the ileum of WT mice, procedures suppressing the excitability of smooth muscle and neurons altered the propagation of spontaneous electric activity, but had little change in the period of oscillations. In conclusion, MEA with low impedance electrodes enables to measure slowly oscillating electric activity, and is useful to evaluate both histological and functional changes in the spatio-temporal property of gut electric activity. PMID:24124480

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty.

PubMed

Fathollah Bayati, Mohsen; Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model.

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty

PubMed Central

Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model. PMID:28953900

Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model

PubMed Central

2017-01-01

Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors. PMID:28316842

Analysis of the error of the developed method of determination the active conductivity reducing the insulation level between one phase of the network and ground, and insulation parameters in a non-symmetric network with isolated neutral with voltage above 1000 V

NASA Astrophysics Data System (ADS)

Utegulov, B. B.

2018-02-01

In the work the study of the developed method was carried out for reliability by analyzing the error in indirect determination of the insulation parameters in an asymmetric network with an isolated neutral voltage above 1000 V. The conducted studies of the random relative mean square errors show that the accuracy of indirect measurements in the developed method can be effectively regulated not only by selecting a capacitive additional conductivity, which are connected between phases of the electrical network and the ground, but also by the selection of measuring instruments according to the accuracy class. When choosing meters with accuracy class of 0.5 with the correct selection of capacitive additional conductivity that are connected between the phases of the electrical network and the ground, the errors in measuring the insulation parameters will not exceed 10%.

High Efficiency, Transparent, Reusable, and Active PM2.5 Filters by Hierarchical Ag Nanowire Percolation Network.

PubMed

Jeong, Seongmin; Cho, Hyunmin; Han, Seonggeun; Won, Phillip; Lee, Habeom; Hong, Sukjoon; Yeo, Junyeob; Kwon, Jinhyeong; Ko, Seung Hwan

2017-07-12

Air quality has become a major public health issue in Asia including China, Korea, and India. Particulate matters are the major concern in air quality. We present the first environmental application demonstration of Ag nanowire percolation network for a novel, electrical type transparent, reusable, and active PM2.5 air filter although the Ag nanowire percolation network has been studied as a very promising transparent conductor in optoelectronics. Compared with previous particulate matter air filter study using relatively weaker short-range intermolecular force in polar polymeric nanofiber, Ag nanowire percolation network filters use stronger long-range electrostatic force to capture PM2.5, and they are highly efficient (>99.99%), transparent, working on an active mode, low power consumption, antibacterial, and reusable after simple washing. The proposed new particulate matter filter can be applied for a highly efficient, reusable, active and energy efficient filter for wearable electronics application.

Beyond Critical Exponents in Neuronal Avalanches

NASA Astrophysics Data System (ADS)

Friedman, Nir; Butler, Tom; Deville, Robert; Beggs, John; Dahmen, Karin

2011-03-01

Neurons form a complex network in the brain, where they interact with one another by firing electrical signals. Neurons firing can trigger other neurons to fire, potentially causing avalanches of activity in the network. In many cases these avalanches have been found to be scale independent, similar to critical phenomena in diverse systems such as magnets and earthquakes. We discuss models for neuronal activity that allow for the extraction of testable, statistical predictions. We compare these models to experimental results, and go beyond critical exponents.

Engineering highly organized and aligned single walled carbon nanotube networks for electronic device applications: Interconnects, chemical sensor, and optoelectronics

NASA Astrophysics Data System (ADS)

Kim, Young Lae

For 20 years, single walled carbon nanotubes (SWNTs) have been studied actively due to their unique one-dimensional nanostructure and superior electrical, thermal, and mechanical properties. For these reasons, they offer the potential to serve as building blocks for future electronic devices such as field effect transistors (FETs), electromechanical devices, and various sensors. In order to realize these applications, it is crucial to develop a simple, scalable, and reliable nanomanufacturing process that controllably places aligned SWNTs in desired locations, orientations, and dimensions. Also electronic properties (semiconducting/metallic) of SWNTs and their organized networks must be controlled for the desired performance of devices and systems. These fundamental challenges are significantly limiting the use of SWNTs for future electronic device applications. Here, we demonstrate a strategy to fabricate highly controlled micro/nanoscale SWNT network structures and present the related assembly mechanism to engineer the SWNT network topology and its electrical transport properties. A method designed to evaluate the electrical reliability of such nano- and microscale SWNT networks is also presented. Moreover, we develop and investigate a robust SWNT based multifunctional selective chemical sensor and a range of multifunctional optoelectronic switches, photo-transistors, optoelectronic logic gates and complex optoelectronic digital circuits.

Modeling of electrochemical flow capacitors using Stokesian dynamics

NASA Astrophysics Data System (ADS)

Karzar Jeddi, Mehdi; Luo, Haoxiang; Cummings, Peter; Hatzell, Kelsey

2017-11-01

Electrochemical flow capacitors (EFCs) are supercapacitors designed to store electrical energy in the form of electrical double layer (EDL) near the surface of porous carbon particles. During its operation, a slurry of activated carbon beads and smaller carbon black particles is pumped between two flat and parallel electrodes. In the charging phase, ions in the electrolyte diffuse to the EDL, and electrical charges percolate through the dynamic network of particles from the flat electrodes; during the discharging phase, the process is reversed with the ions released to the bulk fluid and electrical charges percolating back through the network. In these processes, the relative motion and contact of particle of different sizes affect not only the rheology of the slurry but also charge transfer of the percolation network. In this study, we use Stoekesian dynamics simulation to investigate the role of hydrodynamic interactions of packed carbon particles in the charging/discharging behaviors of EFCs. We derived mobility functions for polydisperse spheres near a no-slip wall. A code is implemented and validated, and a simple charging model has been incorporated to represent charge transfer. Theoretical formulation and results demonstration will be presented in this talk.

Region-specific network plasticity in simulated and living cortical networks: comparison of the center of activity trajectory (CAT) with other statistics

NASA Astrophysics Data System (ADS)

Chao, Zenas C.; Bakkum, Douglas J.; Potter, Steve M.

2007-09-01

Electrically interfaced cortical networks cultured in vitro can be used as a model for studying the network mechanisms of learning and memory. Lasting changes in functional connectivity have been difficult to detect with extracellular multi-electrode arrays using standard firing rate statistics. We used both simulated and living networks to compare the ability of various statistics to quantify functional plasticity at the network level. Using a simulated integrate-and-fire neural network, we compared five established statistical methods to one of our own design, called center of activity trajectory (CAT). CAT, which depicts dynamics of the location-weighted average of spatiotemporal patterns of action potentials across the physical space of the neuronal circuitry, was the most sensitive statistic for detecting tetanus-induced plasticity in both simulated and living networks. By reducing the dimensionality of multi-unit data while still including spatial information, CAT allows efficient real-time computation of spatiotemporal activity patterns. Thus, CAT will be useful for studies in vivo or in vitro in which the locations of recording sites on multi-electrode probes are important.

Multifunctional three-dimensional macroporous nanoelectronic networks for smart materials.

PubMed

Liu, Jia; Xie, Chong; Dai, Xiaochuan; Jin, Lihua; Zhou, Wei; Lieber, Charles M

2013-04-23

Seamless and minimally invasive integration of 3D electronic circuitry within host materials could enable the development of materials systems that are self-monitoring and allow for communication with external environments. Here, we report a general strategy for preparing ordered 3D interconnected and addressable macroporous nanoelectronic networks from ordered 2D nanowire nanoelectronic precursors, which are fabricated by conventional lithography. The 3D networks have porosities larger than 99%, contain approximately hundreds of addressable nanowire devices, and have feature sizes from the 10-μm scale (for electrical and structural interconnections) to the 10-nm scale (for device elements). The macroporous nanoelectronic networks were merged with organic gels and polymers to form hybrid materials in which the basic physical and chemical properties of the host were not substantially altered, and electrical measurements further showed a >90% yield of active devices in the hybrid materials. The positions of the nanowire devices were located within 3D hybrid materials with ∼14-nm resolution through simultaneous nanowire device photocurrent/confocal microscopy imaging measurements. In addition, we explored functional properties of these hybrid materials, including (i) mapping time-dependent pH changes throughout a nanowire network/agarose gel sample during external solution pH changes, and (ii) characterizing the strain field in a hybrid nanoelectronic elastomer structures subject to uniaxial and bending forces. The seamless incorporation of active nanoelectronic networks within 3D materials reveals a powerful approach to smart materials in which the capabilities of multifunctional nanoelectronics allow for active monitoring and control of host systems.

Anatomically realistic multiscale models of normal and abnormal gastrointestinal electrical activity

PubMed Central

Cheng, Leo K; Komuro, Rie; Austin, Travis M; Buist, Martin L; Pullan, Andrew J

2007-01-01

One of the major aims of the International Union of Physiological Sciences (IUPS) Physiome Project is to develop multiscale mathematical and computer models that can be used to help understand human health. We present here a small facet of this broad plan that applies to the gastrointestinal system. Specifically, we present an anatomically and physiologically based modelling framework that is capable of simulating normal and pathological electrical activity within the stomach and small intestine. The continuum models used within this framework have been created using anatomical information derived from common medical imaging modalities and data from the Visible Human Project. These models explicitly incorporate the various smooth muscle layers and networks of interstitial cells of Cajal (ICC) that are known to exist within the walls of the stomach and small bowel. Electrical activity within individual ICCs and smooth muscle cells is simulated using a previously published simplified representation of the cell level electrical activity. This simulated cell level activity is incorporated into a bidomain representation of the tissue, allowing electrical activity of the entire stomach or intestine to be simulated in the anatomically derived models. This electrical modelling framework successfully replicates many of the qualitative features of the slow wave activity within the stomach and intestine and has also been used to investigate activity associated with functional uncoupling of the stomach. PMID:17457969

Electrical Mapping of Silver Nanowire Networks: A Versatile Tool for Imaging Network Homogeneity and Degradation Dynamics during Failure.

PubMed

Sannicolo, Thomas; Charvin, Nicolas; Flandin, Lionel; Kraus, Silas; Papanastasiou, Dorina T; Celle, Caroline; Simonato, Jean-Pierre; Muñoz-Rojas, David; Jiménez, Carmen; Bellet, Daniel

2018-05-22

Electrical stability and homogeneity of silver nanowire (AgNW) networks are critical assets for increasing their robustness and reliability when integrated as transparent electrodes in devices. Our ability to distinguish defects, inhomogeneities, or inactive areas at the scale of the entire network is therefore a critical issue. We propose one-probe electrical mapping (1P-mapping) as a specific simple tool to study the electrical distribution in these discrete structures. 1P-mapping has allowed us to show that the tortuosity of the voltage equipotential lines of AgNW networks under bias decreases with increasing network density, leading to a better electrical homogeneity. The impact of the network fabrication technique on the electrical homogeneity of the resulting electrode has also been investigated. Then, by combining 1P-mapping with electrical resistance measurements and IR thermography, we propose a comprehensive analysis of the evolution of the electrical distribution in AgNW networks when subjected to increasing voltage stresses. We show that AgNW networks experience three distinctive stages: optimization, degradation, and breakdown. We also demonstrate that the failure dynamics of AgNW networks at high voltages occurs through a highly correlated and spatially localized mechanism. In particular the in situ formation of cracks could be clearly visualized. It consists of two steps: creation of a crack followed by propagation nearly parallel to the equipotential lines. Finally, we show that current can dynamically redistribute during failure, by following partially damaged secondary pathways through the crack.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Channeling the Central Dogma.

PubMed

Calabrese, Ronald L

2014-05-21

How do neurons and networks achieve their characteristic electrical activity, regulate this activity homeostatically, and yet show population variability in expression? In this issue of Neuron, O'Leary et al. (2014) address some of these thorny questions in this theoretical analysis that starts with the Central Dogma. Copyright © 2014 Elsevier Inc. All rights reserved.

Functional Magnetic Resonance Imaging Networks Induced by Intracranial Stimulation May Help Defining the Epileptogenic Zone

PubMed Central

Zhang, Myron; Avitsian, Rafi; Bhattacharyya, Pallab; Bulacio, Juan; Cendes, Fernando; Enatsu, Rei; Lowe, Mark; Najm, Imad; Nair, Dileep; Phillips, Michael; Gonzalez-Martinez, Jorge

2014-01-01

Abstract Patients with medically intractable epilepsy often undergo invasive evaluation and surgery, with a 50% success rate. The low success rate is likely due to poor identification of the epileptogenic zone (EZ), the brain area causing seizures. This work introduces a new method using functional magnetic resonance imaging (fMRI) with simultaneous direct electrical stimulation of the brain that could help localize the EZ, performed in five patients with medically intractable epilepsy undergoing invasive evaluation with intracranial depth electrodes. Stimulation occurred in a location near the hypothesized EZ and a location away. Electrical recordings in response to stimulation were recorded and compared to fMRI. Multiple stimulation parameters were varied, like current and frequency. The brain areas showing fMRI response were compared with the areas resected and the success of surgery. Robust fMRI maps of activation networks were easily produced, which also showed a significant but weak positive correlation between quantitative measures of blood-oxygen-level-dependent (BOLD) activity and measures of electrical activity in response to direct electrical stimulation (mean correlation coefficient of 0.38 for all acquisitions that produced a strong BOLD response). For four patients with outcome data at 6 months, successful surgical outcome is consistent with the resection of brain areas containing high local fMRI activity. In conclusion, this method demonstrates the feasibility of simultaneous direct electrical stimulation and fMRI in humans, which allows the study of brain connectivity with high resolution and full spatial coverage. This innovative technique could be used to better define the localization and extension of the EZ in intractable epilepsies, as well as for other functional neurosurgical procedures. PMID:24735069

Nanomolar Oxytocin Synergizes with Weak Electrical Afferent Stimulation to Activate the Locomotor CPG of the Rat Spinal Cord In Vitro

PubMed Central

Dose, Francesco; Zanon, Patrizia; Coslovich, Tamara; Taccola, Giuliano

2014-01-01

Synergizing the effect of afferent fibre stimulation with pharmacological interventions is a desirable goal to trigger spinal locomotor activity, especially after injury. Thus, to better understand the mechanisms to optimize this process, we studied the role of the neuropeptide oxytocin (previously shown to stimulate locomotor networks) on network and motoneuron properties using the isolated neonatal rat spinal cord. On motoneurons oxytocin (1 nM–1 μM) generated sporadic bursts with superimposed firing and dose-dependent depolarization. No desensitization was observed despite repeated applications. Tetrodotoxin completely blocked the effects of oxytocin, demonstrating the network origin of the responses. Recording motoneuron pool activity from lumbar ventral roots showed oxytocin mediated depolarization with synchronous bursts, and depression of reflex responses in a stimulus and peptide-concentration dependent fashion. Disinhibited bursting caused by strychnine and bicuculline was accelerated by oxytocin whose action was blocked by the oxytocin antagonist atosiban. Fictive locomotion appeared when subthreshold concentrations of NMDA plus 5HT were coapplied with oxytocin, an effect prevented after 24 h incubation with the inhibitor of 5HT synthesis, PCPA. When fictive locomotion was fully manifested, oxytocin did not change periodicity, although cycle amplitude became smaller. A novel protocol of electrical stimulation based on noisy waveforms and applied to one dorsal root evoked stereotypic fictive locomotion. Whenever the stimulus intensity was subthreshold, low doses of oxytocin triggered fictive locomotion although oxytocin per se did not affect primary afferent depolarization evoked by dorsal root pulses. Among the several functional targets for the action of oxytocin at lumbar spinal cord level, the present results highlight how small concentrations of this peptide could bring spinal networks to threshold for fictive locomotion in combination with other protocols, and delineate the use of oxytocin to strengthen the efficiency of electrical stimulation to activate locomotor circuits. PMID:24658101

Saccade Modulation by Optical and Electrical Stimulation in the Macaque Frontal Eye Field

PubMed Central

Grimaldi, Piercesare; Schweers, Nicole

2013-01-01

Recent studies have demonstrated that strong neural modulations can be evoked with optogenetic stimulation in macaque motor cortex without observing any evoked movements (Han et al., 2009, 2011; Diester et al., 2011). It remains unclear why such perturbations do not generate movements and if conditions exist under which they may evoke movements. In this study, we examine the effects of five optogenetic constructs in the macaque frontal eye field and use electrical microstimulation to assess whether optical perturbation of the local network leads to observable motor changes during optical, electrical, and combined stimulation. We report a significant increase in the probability of evoking saccadic eye movements when low current electrical stimulation is coupled to optical stimulation compared with when electrical stimulation is used alone. Experiments combining channelrhodopsin 2 (ChR2) and electrical stimulation with simultaneous fMRI revealed no discernible fMRI activity at the electrode tip with optical stimulation but strong activity with electrical stimulation. Our findings suggest that stimulation with current ChR2 optogenetic constructs generates subthreshold activity that contributes to the initiation of movements but, in most cases, is not sufficient to evoke a motor response. PMID:24133271

60-Hz electric and magnetic fields generated by a distribution network.

PubMed

Héroux, P

1987-01-01

From a mobile unit, 60-Hz electric and magnetic fields generated by Hydro-Québec's distribution network were measured. Nine runs, representative of various human environments, were investigated. Typical values were 32 V/m and 0.16 microT. The electrical distribution networks investigated were major contributors to the electric and magnetic environments.

Observations of Penetration Electric Fields and Sub-Auroral Ion Drifts With Mid-Latitude SuperDARN Radars

NASA Astrophysics Data System (ADS)

Baker, J. B.; Greenwald, R. A.; Yin, Y.; Ruohoniemi, J. M.; Clausen, L.; Frissell, N. A.; Ribeiro, A. J.

2009-12-01

The Super Dual Auroral Radar Network (SuperDARN) provides continuous Doppler measurements of ionospheric plasma convection over extended spatial scales with high temporal resolution. First generation SuperDARN radars were constructed at magnetic latitudes near 60 degrees to optimize coverage during periods of moderate geomagnetic activity. In recent years there has been an expansion of the network to middle latitudes to increase coverage during enhanced geomagnetic activity, such as during magnetic storms. In this paper we present measurements of prompt penetration electric fields and sub-auroral ion drift (SAID) events observed by the Wallops and Blackstone radars at middle latitudes. Together, these two radars provide a capability to continuously examine the temporal evolution of these features over an extended local time sector. We present case studies and statistical results showing that transient sub-auroral flow enhancements occur over a wide range of magnetospheric disturbance levels and are often highly correlated with activity at higher latitudes.

On the Dynamics of the Spontaneous Activity in Neuronal Networks

PubMed Central

Bonifazi, Paolo; Ruaro, Maria Elisabetta; Torre, Vincent

2007-01-01

Most neuronal networks, even in the absence of external stimuli, produce spontaneous bursts of spikes separated by periods of reduced activity. The origin and functional role of these neuronal events are still unclear. The present work shows that the spontaneous activity of two very different networks, intact leech ganglia and dissociated cultures of rat hippocampal neurons, share several features. Indeed, in both networks: i) the inter-spike intervals distribution of the spontaneous firing of single neurons is either regular or periodic or bursting, with the fraction of bursting neurons depending on the network activity; ii) bursts of spontaneous spikes have the same broad distributions of size and duration; iii) the degree of correlated activity increases with the bin width, and the power spectrum of the network firing rate has a 1/f behavior at low frequencies, indicating the existence of long-range temporal correlations; iv) the activity of excitatory synaptic pathways mediated by NMDA receptors is necessary for the onset of the long-range correlations and for the presence of large bursts; v) blockage of inhibitory synaptic pathways mediated by GABAA receptors causes instead an increase in the correlation among neurons and leads to a burst distribution composed only of very small and very large bursts. These results suggest that the spontaneous electrical activity in neuronal networks with different architectures and functions can have very similar properties and common dynamics. PMID:17502919

Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

NASA Astrophysics Data System (ADS)

Gollas, Frank; Tetzlaff, Ronald

2009-05-01

Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio-temporal autoregressive filter models are considered, for a prediction of EEG signal values. Thus Signal features values for successive, short, quasi stationary segments of brain electrical activity can be obtained, with the objective of detecting distinct changes prior to impending epileptic seizures. Furthermore long term recordings gained during presurgical diagnostics in temporal lobe epilepsy are analyzed and the predictive performance of the extracted features is evaluated statistically. Therefore a Receiver Operating Characteristic analysis is considered, assessing the distinguishability between distributions of supposed preictal and interictal periods.

Corticocortical evoked potentials reveal projectors and integrators in human brain networks.

PubMed

Keller, Corey J; Honey, Christopher J; Entz, Laszlo; Bickel, Stephan; Groppe, David M; Toth, Emilia; Ulbert, Istvan; Lado, Fred A; Mehta, Ashesh D

2014-07-02

The cerebral cortex is composed of subregions whose functional specialization is largely determined by their incoming and outgoing connections with each other. In the present study, we asked which cortical regions can exert the greatest influence over other regions and the cortical network as a whole. Previous research on this question has relied on coarse anatomy (mapping large fiber pathways) or functional connectivity (mapping inter-regional statistical dependencies in ongoing activity). Here we combined direct electrical stimulation with recordings from the cortical surface to provide a novel insight into directed, inter-regional influence within the cerebral cortex of awake humans. These networks of directed interaction were reproducible across strength thresholds and across subjects. Directed network properties included (1) a decrease in the reciprocity of connections with distance; (2) major projector nodes (sources of influence) were found in peri-Rolandic cortex and posterior, basal and polar regions of the temporal lobe; and (3) major receiver nodes (receivers of influence) were found in anterolateral frontal, superior parietal, and superior temporal regions. Connectivity maps derived from electrical stimulation and from resting electrocorticography (ECoG) correlations showed similar spatial distributions for the same source node. However, higher-level network topology analysis revealed differences between electrical stimulation and ECoG that were partially related to the reciprocity of connections. Together, these findings inform our understanding of large-scale corticocortical influence as well as the interpretation of functional connectivity networks. Copyright © 2014 the authors 0270-6474/14/349152-12$15.00/0.

[Changes of brain pain center and default mode network an electro acupuncture in Weizhong and Dachangshu acupoints: a task-fMRI study].

PubMed

Zhou, S; Cao, H X; Yu, L C; Jin, Y J; Jia, R H; Wen, Y R; Chen, X F

2016-02-23

To investigate the functional brain pain center and default mode network response to electro acupuncture stimulate in weizhong acupoints(BL40) and dachangshu acupoints(BL25). During January to February 2015, volunteers were enrolled in this study from the staff and student interns of Gansu Province Traditional Chinese Medicine Hospital. A total of 20 healthy, right-handed subjects, male 9, female 11, age (23±3) years, participated in this study. Block design task functional magnetic resonance imaging(fMRI) 3.0 T was performed in all subjects by electro acupuncture stimulating at BL40 and BL25 from the same experienced acupuncturist.The needle connected electric acupuncture apparatus through tow long coaxial-cable. A block design with five 120 s blocks of rest time (OFF block, electric acupuncture turn off ) interspersed between five 60 s blocks of stimulation (ON block, electric acupuncture turn on) fMRI scan. Magnetic resonance data of brain function was collected and FSL(fMRI Software Library) software was used to analyze the data. All subjects' data were analyzed except 2 cases whose head movement were more than 2 mm. Activated brain function regions by electro acupuncture stimulate included temporal lobe lateral sulcus, lobus insularis, thalamus, supramarginal gyrus, prefrontal medial frontal gyrus. Negative activated brain regions included middle frontal gyrus, parahippocampal gyrus, cingulate cortex abdominal segment, parietal cortex.The functional pain central and default mode network were changed when electro acupuncture stimulate in(BL40) and(BL25). There are several brain activation regions and negative activated brain regions when administering electro acupuncture stimulation at BL40 and BL25.

Etude et simulation de la MADA

NASA Astrophysics Data System (ADS)

Defontaines, Remi

Over the past ten years, the production of electric energy using wind turbines has increased eight times. This production of energy is in full expansion, and different means are now at the dispositions of researchers to finally explore it to the maximum. The DFIG is a type of wind turbine that has been the object of numerous studies over the past several years. This wind turbine functions with the speed of the wind. Its principle particularity is that it is constituted of an asynchronous machine, a wound-rotor and is capable of providing active power to the network by the stator and the rotor. This structure permits a good performance over a wide range of wind speeds, at a reasonable cost. It manages to be cost-effective because it uses weakly dimensioned power converters. Despite its advantages, there is a problem: its connection to the network. The electric network is not always stable; it regularly suffers voltage damage (low voltage, unbalance or overvoltage). This damage can result in fault from poor quality in the machine, and this damages or even destroys the power converters. To avoid this issue, the wind turbine disconnects from the network when it undergoes deterioration. The goal of this research is to find a strategy that allows the wind turbine to function even when the network voltage deteriorates, which in turn results in avoiding disconnection and therefore the loss of electrical power.

Deep brain stimulation mechanisms: beyond the concept of local functional inhibition.

PubMed

Deniau, Jean-Michel; Degos, Bertrand; Bosch, Clémentine; Maurice, Nicolas

2010-10-01

Deep brain electrical stimulation has become a recognized therapy in the treatment of a variety of motor disorders and has potentially promising applications in a wide range of neurological diseases including neuropsychiatry. Behavioural observation that electrical high-frequency stimulation of a given brain area induces an effect similar to a lesion suggested a mechanism of functional inhibition. In vitro and in vivo experiments as well as per operative recordings in patients have revealed a variety of effects involving local changes of neuronal excitability as well as widespread effects throughout the connected network resulting from activation of axons, including antidromic activation. Here we review current data regarding the local and network activity changes induced by high-frequency stimulation of the subthalamic nucleus and discuss this in the context of motor restoration in Parkinson's disease. Stressing the important functional consequences of axonal activation in deep brain stimulation mechanisms, we highlight the importance of developing anatomical knowledge concerning the fibre connections of the putative therapeutic targets. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Influence of graphene quantum dots on electrical properties of polymer composites

NASA Astrophysics Data System (ADS)

Arthisree, D.; Joshi, Girish M.

2017-07-01

We successfully prepared synthetic nanocomposite (SNC) by dispersing graphene quantum dots (GQD) in cellulose acetate (CA) polymer system. The dispersion and occupied network of GQD were foreseen by microscopic techniques. The variation of plane to crossed linked array network was observed by the polarizing optical microscopic (POM) technique. The scanning electron microscopy (SEM) revealed the leaves like impressions of GQD in host polymer system. The series network of GQD occupied in CA at higher resolution was confirmed by transmission electron microscopy (TEM). The two dimensional (2D) topographic images demonstrated an entangled polymer network to plane morphology. The variation in surface roughness was evaluated from the dimensional (3D) topography. The influence of temperature on AC conductivity with highest value (4  ×  10-5 S cm-1), contributes to the decrease in activation energy. The DC conductivity obeys the percolation criteria co-related to the GQD loading by weight fraction. Furthermore, this synthetic nanocomposite is feasible for the development of sensing and electrical applications.

The use of virtual ground to control transmembrane voltages and measure bilayer currents in serial arrays of droplet interface bilayers

NASA Astrophysics Data System (ADS)

Sarles, Stephen A.

2013-09-01

The droplet interface bilayer (DIB) is a simple technique for constructing a stable lipid bilayer at the interface of two lipid-encased water droplets submerged in oil. Networks of DIBs formed by connecting more than two droplets constitute a new form of modular biomolecular smart material, where the transduction properties of a single lipid bilayer can affect the actions performed at other interface bilayers in the network via diffusion through the aqueous environments of shared droplet connections. The passive electrical properties of a lipid bilayer and the arrangement of droplets that determine the paths for transport in the network require specific electrical control to stimulate and interrogate each bilayer. Here, we explore the use of virtual ground for electrodes inserted into specific droplets in the network and employ a multichannel patch clamp amplifier to characterize bilayer formation and ion-channel activity in a serial DIB array. Analysis of serial connections of DIBs is discussed to understand how assigning electrode connections to the measurement device can be used to measure activity across all lipid membranes within a network. Serial arrays of DIBs are assembled using the regulated attachment method within a multi-compartment flexible substrate, and wire-type electrodes inserted into each droplet compartment of the substrate enable the application of voltage and measurement of current in each droplet in the array.

Endocannabinoid Release Modulates Electrical Coupling between CCK Cells Connected via Chemical and Electrical Synapses in CA1

PubMed Central

Iball, Jonathan; Ali, Afia B.

2011-01-01

Electrical coupling between some subclasses of interneurons is thought to promote coordinated firing that generates rhythmic synchronous activity in cortical regions. Synaptic activity of cholecystokinin (CCK) interneurons which co-express cannabinoid type-1 (CB1) receptors are powerful modulators of network activity via the actions of endocannabinoids. We investigated the modulatory actions of endocannabinoids between chemically and electrically connected synapses of CCK cells using paired whole-cell recordings combined with biocytin and double immunofluorescence labeling in acute slices of rat hippocampus at P18–20 days. CA1 stratum radiatum CCK Schaffer collateral-associated cells were coupled electrically with each other as well as CCK basket cells and CCK cells with axonal projections expanding to dentate gyrus. Approximately 50% of electrically coupled cells received facilitating, asynchronously released inhibitory postsynaptic potential (IPSPs) that curtailed the steady-state coupling coefficient by 57%. Tonic CB1 receptor activity which reduces inhibition enhanced electrical coupling between cells that were connected via chemical and electrical synapses. Blocking CB1 receptors with antagonist, AM-251 (5 μM) resulted in the synchronized release of larger IPSPs and this enhanced inhibition further reduced the steady-state coupling coefficient by 85%. Depolarization induced suppression of inhibition (DSI), maintained the asynchronicity of IPSP latency, but reduced IPSP amplitudes by 95% and enhanced the steady-state coupling coefficient by 104% and IPSP duration by 200%. However, DSI did not did not enhance electrical coupling at purely electrical synapses. These data suggest that different morphological subclasses of CCK interneurons are interconnected via gap junctions. The synergy between the chemical and electrical coupling between CCK cells probably plays a role in activity-dependent endocannabinoid modulation of rhythmic synchronization. PMID:22125513

A Simple Rule for Dendritic Spine and Axonal Bouton Formation Can Account for Cortical Reorganization after Focal Retinal Lesions

PubMed Central

Butz, Markus; van Ooyen, Arjen

2013-01-01

Lasting alterations in sensory input trigger massive structural and functional adaptations in cortical networks. The principles governing these experience-dependent changes are, however, poorly understood. Here, we examine whether a simple rule based on the neurons' need for homeostasis in electrical activity may serve as driving force for cortical reorganization. According to this rule, a neuron creates new spines and boutons when its level of electrical activity is below a homeostatic set-point and decreases the number of spines and boutons when its activity exceeds this set-point. In addition, neurons need a minimum level of activity to form spines and boutons. Spine and bouton formation depends solely on the neuron's own activity level, and synapses are formed by merging spines and boutons independently of activity. Using a novel computational model, we show that this simple growth rule produces neuron and network changes as observed in the visual cortex after focal retinal lesions. In the model, as in the cortex, the turnover of dendritic spines was increased strongest in the center of the lesion projection zone, while axonal boutons displayed a marked overshoot followed by pruning. Moreover, the decrease in external input was compensated for by the formation of new horizontal connections, which caused a retinotopic remapping. Homeostatic regulation may provide a unifying framework for understanding cortical reorganization, including network repair in degenerative diseases or following focal stroke. PMID:24130472

Analysis of the energy efficiency of the implementation power electric generated modules in the CHS

NASA Astrophysics Data System (ADS)

Sukhikh, A. A.; Milyutin, V. A.; Lvova, A. M.

2017-11-01

Application on the Central heat source (CHS) local generation of electricity is primarily aimed at solving problems of own needs of electric energy that not only guarantees the independence of the work of the CHS from external electrical networks, but will prevent the stop of heat supply of consumers and defrosting heating networks in case of accidents in electrical networks caused by natural or anthropogenic factors. Open the prospects of electric power supply stand-alone objects, such commercial or industrial objects on the territory of a particular neighborhood.

ROLE OF THE NETWORK FORMER IN SEMICONDUCTING OXIDE GLASSES.

DTIC Science & Technology

SEMICONDUCTOR DEVICES, * GLASS ), (*ELECTRICAL NETWORKS, GLASS ), ELECTRICAL PROPERTIES, SEEBECK EFFECT, BORATES, PHOSPHATES, ELECTRICAL RESISTANCE, X RAY DIFFRACTION, ANNEALING, OXIDATION, OXIDES, ELECTRODES, VANADIUM

Three levels of neuroelectronic interfacing: silicon chips with ion channels, nerve cells, and brain tissue.

PubMed

Fromherz, Peter

2006-12-01

We consider the direct electrical interfacing of semiconductor chips with individual nerve cells and brain tissue. At first, the structure of the cell-chip contact is studied. Then we characterize the electrical coupling of ion channels--the electrical elements of nerve cells--with transistors and capacitors in silicon chips. On that basis it is possible to implement signal transmission between microelectronics and the microionics of nerve cells in both directions. Simple hybrid neuroelectronic systems are assembled with neuron pairs and with small neuronal networks. Finally, the interfacing with capacitors and transistors is extended to brain tissue cultured on silicon chips. The application of highly integrated silicon chips allows an imaging of neuronal activity with high spatiotemporal resolution. The goal of the work is an integration of neuronal network dynamics with digital electronics on a microscopic level with respect to experiments in brain research, medical prosthetics, and information technology.

Lead-acid batteries with polymer-structured electrodes for electric-vehicle applications

NASA Astrophysics Data System (ADS)

Soria, M. L.; Fullea, J.; Sáez, F.; Trinidad, F.

Some years ago a consortium of enterprises and a university from different European countries and industrial sectors was established to work together in the development of lighter lead-acid batteries for electrical and conventional vehicles with new innovative materials and process techniques, with the final goal of increasing the energy density by means of a battery weight reduction. Its main idea was to substitute the heavy lead alloy grids (mechanical support of the active masses and collectors of the current produced during the charge and discharge reactions) by lightweight metallised polymeric network structures (PNS) with reduced mesh dimensions in comparison to conventional grids. The network was then coated with conductive materials and corrosion resistant layers to conduct the current flow. In this paper, the electrode characteristics and the design features of the batteries prepared in the project will be described and their electrical performance presented.

Validation of long-term primary neuronal cultures and network activity through the integration of reversibly bonded microbioreactors and MEA substrates.

PubMed

Biffi, Emilia; Menegon, Andrea; Piraino, Francesco; Pedrocchi, Alessandra; Fiore, Gianfranco B; Rasponi, Marco

2012-01-01

In vitro recording of neuronal electrical activity is a widely used technique to understand brain functions and to study the effect of drugs on the central nervous system. The integration of microfluidic devices with microelectrode arrays (MEAs) enables the recording of networks activity in a controlled microenvironment. In this work, an integrated microfluidic system for neuronal cultures was developed, reversibly coupling a PDMS microfluidic device with a commercial flat MEA through magnetic forces. Neurons from mouse embryos were cultured in a 100 µm channel and their activity was followed up to 18 days in vitro. The maturation of the networks and their morphological and functional characteristics were comparable with those of networks cultured in macro-environments and described in literature. In this work, we successfully demonstrated the ability of long-term culturing of primary neuronal cells in a reversible bonded microfluidic device (based on magnetism) that will be fundamental for neuropharmacological studies. Copyright © 2011 Wiley Periodicals, Inc.

Computational exploration of neuron and neural network models in neurobiology.

PubMed

Prinz, Astrid A

2007-01-01

The electrical activity of individual neurons and neuronal networks is shaped by the complex interplay of a large number of non-linear processes, including the voltage-dependent gating of ion channels and the activation of synaptic receptors. These complex dynamics make it difficult to understand how individual neuron or network parameters-such as the number of ion channels of a given type in a neuron's membrane or the strength of a particular synapse-influence neural system function. Systematic exploration of cellular or network model parameter spaces by computational brute force can overcome this difficulty and generate comprehensive data sets that contain information about neuron or network behavior for many different combinations of parameters. Searching such data sets for parameter combinations that produce functional neuron or network output provides insights into how narrowly different neural system parameters have to be tuned to produce a desired behavior. This chapter describes the construction and analysis of databases of neuron or neuronal network models and describes some of the advantages and downsides of such exploration methods.

Analysis and Application of Microgrids

NASA Astrophysics Data System (ADS)

Yue, Lu

New trends of generating electricity locally and utilizing non-conventional or renewable energy sources have attracted increasing interests due to the gradual depletion of conventional fossil fuel energy sources. The new type of power generation is called Distributed Generation (DG) and the energy sources utilized by Distributed Generation are termed Distributed Energy Sources (DERs). With DGs embedded in the distribution networks, they evolve from passive distribution networks to active distribution networks enabling bidirectional power flows in the networks. Further incorporating flexible and intelligent controllers and employing future technologies, active distribution networks will turn to a Microgrid. A Microgrid is a small-scale, low voltage Combined with Heat and Power (CHP) supply network designed to supply electrical and heat loads for a small community. To further implement Microgrids, a sophisticated Microgrid Management System must be integrated. However, due to the fact that a Microgrid has multiple DERs integrated and is likely to be deregulated, the ability to perform real-time OPF and economic dispatch with fast speed advanced communication network is necessary. In this thesis, first, problems such as, power system modelling, power flow solving and power system optimization, are studied. Then, Distributed Generation and Microgrid are studied and reviewed, including a comprehensive review over current distributed generation technologies and Microgrid Management Systems, etc. Finally, a computer-based AC optimization method which minimizes the total transmission loss and generation cost of a Microgrid is proposed and a wireless communication scheme based on synchronized Code Division Multiple Access (sCDMA) is proposed. The algorithm is tested with a 6-bus power system and a 9-bus power system.

Electrically activated artificial muscles made with liquid crystal elastomers

NASA Astrophysics Data System (ADS)

Shahinpoor, Mohsen

2000-06-01

Composites of monodomain nematic liquid crystal elastomers and a conducting material distributed within their network are shown to exhibit large deformations, i.e. contraction, expansion, bending with strains of over 200% and appreciable force, by Joule heating through electrical activation. The electrical activation of the conducting material induces a rapid Joule heating in the sample leading to a nematic to isotropic phase transition where the elastomer of dimensions 32 mm x 7 mm x 0.4 mm contracted in less than a second. The cooling process, isotropic to nematic transition where the elastomer expands back to its original length, was slow and took 8 seconds. The material studied here is a highly novel liquid crystalline co-elastomer, invented and developed by Heino Finkelmann and co-workers at Albert-Ludwigs-Universitaet in Freiburg, Germany. The material is such that in which the mesogenic units are in both the side chains and the main chains of the elastomer. This co-elastomer was then mechanically loaded to induce a uniaxial network anisotropy before the cross-linking reaction was completed. These samples were then made into a composite with a conducting material such as dispersed silver particles or graphite fibers. The final samples was capable of undergoing more than 200% reversible strain in a few seconds.

An integrated multi-electrode-optrode array for in vitro optogenetics

PubMed Central

Welkenhuysen, Marleen; Hoffman, Luis; Luo, Zhengxiang; De Proft, Anabel; Van den Haute, Chris; Baekelandt, Veerle; Debyser, Zeger; Gielen, Georges; Puers, Robert; Braeken, Dries

2016-01-01

Modulation of a group of cells or tissue needs to be very precise in order to exercise effective control over the cell population under investigation. Optogenetic tools have already demonstrated to be of great value in the study of neuronal circuits and in neuromodulation. Ideally, they should permit very accurate resolution, preferably down to the single cell level. Further, to address a spatially distributed sample, independently addressable multiple optical outputs should be present. In current techniques, at least one of these requirements is not fulfilled. In addition to this, it is interesting to directly monitor feedback of the modulation by electrical registration of the activity of the stimulated cells. Here, we present the fabrication and characterization of a fully integrated silicon-based multi-electrode-optrode array (MEOA) for in vitro optogenetics. We demonstrate that this device allows for artifact-free electrical recording. Moreover, the MEOA was used to reliably elicit spiking activity from ChR2-transduced neurons. Thanks to the single cell resolution stimulation capability, we could determine spatial and temporal activation patterns and spike latencies of the neuronal network. This integrated approach to multi-site combined optical stimulation and electrical recording significantly advances today’s tool set for neuroscientists in their search to unravel neuronal network dynamics. PMID:26832455

Lightning and electrical activity during the Shiveluch volcano eruption on 16 November 2014

NASA Astrophysics Data System (ADS)

Shevtsov, Boris M.; Firstov, Pavel P.; Cherneva, Nina V.; Holzworth, Robert H.; Akbashev, Renat R.

2016-03-01

According to World Wide Lightning Location Network (WWLLN) data, a sequence of lightning discharges was detected which occurred in the area of the explosive eruption of Shiveluch volcano on 16 November 2014 in Kamchatka. Information on the ash cloud motion was confirmed by the measurements of atmospheric electricity, satellite observations and meteorological and seismic data. It was concluded that WWLLN resolution is enough to detect the earlier stage of volcanic explosive eruption when electrification processes develop the most intensively. The lightning method has the undeniable advantage for the fast remote sensing of volcanic electric activity anywhere in the world. There is a good opportunity for the development of WWLLN technology to observe explosive volcanic eruptions.

One-to-one neuron-electrode interfacing.

PubMed

Greenbaum, Alon; Anava, Sarit; Ayali, Amir; Shein, Mark; David-Pur, Moshe; Ben-Jacob, Eshel; Hanein, Yael

2009-09-15

The question of neuronal network development and organization is a principle one, which is closely related to aspects of neuronal and network form-function interactions. In-vitro two-dimensional neuronal cultures have proved to be an attractive and successful model for the study of these questions. Research is constraint however by the search for techniques aimed at culturing stable networks, whose electrical activity can be reliably and consistently monitored. A simple approach to form small interconnected neuronal circuits while achieving one-to-one neuron-electrode interfacing is presented. Locust neurons were cultured on a novel bio-chip consisting of carbon-nanotube multi-electrode-arrays. The cells self-organized to position themselves in close proximity to the bio-chip electrodes. The organization of the cells on the electrodes was analyzed using time lapse microscopy, fluorescence imaging and scanning electron microscopy. Electrical recordings from well identified cells is presented and discussed. The unique properties of the bio-chip and the specific neuron-nanotube interactions, together with the use of relatively large insect ganglion cells, allowed long-term stabilization (as long as 10 days) of predefined neural network topology as well as high fidelity electrical recording of individual neuron firing. This novel preparation opens ample opportunity for future investigation into key neurobiological questions and principles.

The application of the multi-alternative approach in active neural network models

NASA Astrophysics Data System (ADS)

Podvalny, S.; Vasiljev, E.

2017-02-01

The article refers to the construction of intelligent systems based artificial neuron networks are used. We discuss the basic properties of the non-compliance of artificial neuron networks and their biological prototypes. It is shown here that the main reason for these discrepancies is the structural immutability of the neuron network models in the learning process, that is, their passivity. Based on the modern understanding of the biological nervous system as a structured ensemble of nerve cells, it is proposed to abandon the attempts to simulate its work at the level of the elementary neurons functioning processes and proceed to the reproduction of the information structure of data storage and processing on the basis of the general enough evolutionary principles of multialternativity, i.e. the multi-level structural model, diversity and modularity. The implementation method of these principles is offered, using the faceted memory organization in the neuron network with the rearranging active structure. An example of the implementation of the active facet-type neuron network in the intellectual decision-making system in the conditions of critical events development in the electrical distribution system.

Distinctive time-lagged resting-state networks revealed by simultaneous EEG-fMRI.

PubMed

Feige, Bernd; Spiegelhalder, Kai; Kiemen, Andrea; Bosch, Oliver G; Tebartz van Elst, Ludger; Hennig, Jürgen; Seifritz, Erich; Riemann, Dieter

2017-01-15

Functional activation as evidenced by blood oxygen level-dependent (BOLD) functional MRI changes or event-related EEG is known to closely follow patterns of stimulation or self-paced action. Any lags are compatible with axonal conduction velocities and neural integration times. The important analysis of resting state networks is generally based on the assumption that these principles also hold for spontaneous fluctuations in brain activity. Previous observations using simultaneous EEG and fMRI indicate that slower processes, with delays in the seconds range, determine at least part of the relationship between spontaneous EEG and fMRI. To assess this relationship systematically, we used deconvolution analysis of EEG-fMRI during the resting state, assessing the relationship between EEG frequency bands and fMRI BOLD across the whole brain while allowing for time lags of up to 10.5s. Cluster analysis, identifying similar BOLD time courses in relation to EEG band power peaks, showed a clear segregation of functional subsystems of the brain. Our analysis shows that fMRI BOLD increases commonly precede EEG power increases by seconds. Most zero-lag correlations, on the other hand, were negative. This indicates two main distinct neuromodulatory mechanisms: an "idling" mechanism of simultaneous electric and metabolic network anticorrelation and a "regulatory" mechanism in which metabolic network activity precedes increased EEG power by some seconds. This has to be taken into consideration in further studies which address the causal and functional relationship of metabolic and electric brain activity patterns. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of Artificial Neural Networks in the Heart Electrical Axis Position Conclusion Modeling

NASA Astrophysics Data System (ADS)

Bakanovskaya, L. N.

2016-08-01

The article touches upon building of a heart electrical axis position conclusion model using an artificial neural network. The input signals of the neural network are the values of deflections Q, R and S; and the output signal is the value of the heart electrical axis position. Training of the network is carried out by the error propagation method. The test results allow concluding that the created neural network makes a conclusion with a high degree of accuracy.

Improved detection of electrical activity with a voltage probe based on a voltage-sensing phosphatase.

PubMed

Tsutsui, Hidekazu; Jinno, Yuka; Tomita, Akiko; Niino, Yusuke; Yamada, Yoshiyuki; Mikoshiba, Katsuhiko; Miyawaki, Atsushi; Okamura, Yasushi

2013-09-15

  One of the most awaited techniques in modern physiology is the sensitive detection of spatiotemporal electrical activity in a complex network of excitable cells. The use of genetically encoded voltage probes has been expected to enable such analysis. However, in spite of recent progress, existing probes still suffer from low signal amplitude and/or kinetics too slow to detect fast electrical activity. Here, we have developed an improved voltage probe named Mermaid2, which is based on the voltage-sensor domain of the voltage-sensing phosphatase from Ciona intestinalis and Förster energy transfer between a pair of fluorescent proteins. In mammalian cells, Mermaid2 permits ratiometric readouts of fractional changes of more than 50% over a physiologically relevant voltage range with fast kinetics, and it was used to follow a train of action potentials at frequencies of up to 150 Hz. Mermaid2 was also able to detect single action potentials and subthreshold voltage responses in hippocampal neurons in vitro, in addition to cortical electrical activity evoked by sound stimuli in single trials in living mice.

Electrical Stimulation Modulates High γ Activity and Human Memory Performance

PubMed Central

Berry, Brent M.; Miller, Laura R.; Khadjevand, Fatemeh; Ezzyat, Youssef; Wanda, Paul; Sperling, Michael R.; Lega, Bradley; Stead, S. Matt

2018-01-01

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62–118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with “poor” memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation. PMID:29404403

Virtual CO2 Emission Flows in the Global Electricity Trade Network.

PubMed

Qu, Shen; Li, Yun; Liang, Sai; Yuan, Jiahai; Xu, Ming

2018-06-05

Quantifying greenhouse gas emissions due to electricity consumption is crucial for climate mitigation in the electric power sector. Current practices primarily use production-based emission factors to quantify emissions for electricity consumption, assuming production and consumption of electricity take place within the same region. The increasingly intensified cross-border electricity trade complicates the accounting for emissions of electricity consumption. This study employs a network approach to account for the flows in the whole electricity trade network to estimate CO 2 emissions of electricity consumption for 137 major countries/regions in 2014. Results show that in some countries, especially those in Europe and Southern Africa, the impacts of electricity trade on the estimation of emission factors and embodied emissions are significant. The changes made to emission factors by considering intergrid electricity trade can have significant implications for emission accounting and climate mitigation when multiplied by total electricity consumption of the corresponding countries/regions.

Scientific Lightning Detection Network for Kazakhstan

NASA Astrophysics Data System (ADS)

Streltsov, A. V.; Lozbin, A.; Inchin, A.; Shpadi, Y.; Inchin, P.; Shpadi, M.; Ayazbayev, G.; Bykayev, R.; Mailibayeva, L.

2015-12-01

In the frame of grant financing of the scientific research in 2015-2017 the project "To Develop Electromagnetic System for lightning location and atmosphere-lithosphere coupling research" was found. The project was start in January, 2015 and should be done during 3 years. The purpose is to create a system of electromagnetic measurements for lightning location and atmosphere-lithosphere coupling research consisting of a network of electric and magnetic sensors and the dedicated complex for data processing and transfer to the end user. The main tasks are to set several points for electromagnetic measurements with 100-200 km distance between them, to develop equipment for these points, to develop the techniques and software for lightning location (Time-of-arrival and Direction Finding (TOA+DF)) and provide a lightning activity research in North Tien-Shan region with respect to seismicity and other natural and manmade activities. Also, it is planned to use lightning data for Global Electric Circuit (GEC) investigation. Currently, there are lightning detection networks in many countries. In Kazakhstan we have only separate units in airports. So, we don't have full lightning information for our region. It is planned, to setup 8-10 measurement points with magnetic and electric filed antennas for VLF range. The final data set should be including each stroke location, time, type (CG+, CG-, CC+ or CC-) and waveform from each station. As the magnetic field lightning antenna the ferrite rod VLF antenna will be used. As the electric field antenna the wide range antenna with specific frequencies filters will be used. For true event detection TOA and DF methods needs detected stroke from minimum 4 stations. In this case we can get location accuracy about 2-3 km and better.

Spontaneous and electrically modulated spatiotemporal dynamics of the neocortical slow oscillation and associated local fast activity.

PubMed

Greenberg, Anastasia; Dickson, Clayton T

2013-12-01

The neocortical slow oscillation (SO; ~1Hz) of non-REM sleep and anesthesia reflects synchronized network activity composed of alternating active and silent (ON/OFF) phases at the local network and cellular level. The SO itself shows self-organized spatiotemporal dynamics as it appears to originate at unique foci on each cycle and then propagates across the cortical surface. During sleep, this rhythm is relevant for neuroplastic processes mediating memory consolidation especially since its enhancement by slow, rhythmic electrical fields improves subsequent recall. However, the neurobiological mechanism by which spontaneous or enhanced SO activity might operate on memory traces is unknown. Here we show a series of original results, using cycle to cycle tracking across multiple neocortical sites in urethane anesthetized rats: The spontaneous spatiotemporal dynamics of the SO are complex, showing interfering propagation patterns in the anterior-to-posterior plane. These patterns compete for expression and tend to alternate following phase resets that take place during the silent OFF phase of the SO. Applying sinusoidal electrical field stimulation to the anterior pole of the cerebral cortex progressively entrained local field, gamma, and multi-unit activity at all sites, while disrupting the coordination of endogenous SO activity. Field stimulation also biased propagation in the anterior-to-posterior direction and more notably, enhanced the long-range gamma synchrony between cortical regions. These results are the first to show that changes to slow wave dynamics cause enhancements in high frequency cortico-cortical communication and provide mechanistic clues into how the SO is relevant for sleep-dependent memory consolidation. © 2013.

Construction of a cardiac conduction system subject to extracellular stimulation.

PubMed

Clements, Clyde; Vigmond, Edward

2005-01-01

Proper electrical excitation of the heart is dependent on the specialized conduction system that coordinates the electrical activity from the atria to the ventricles. This paper describes the construction of a conduction system as a branching network of Purkinje fibers on the endocardial surface. Endocardial surfaces were extracted from an FEM model of the ventricles and transformed to 2D. A Purkinje network was drawn on top and the inverse transform performed. The underlying mathematics utilized one dimensional cubic Hermite finite elements. Compared to linear elements, the cubic Hermite solution was found to have a much smaller RMS error. Furthermore, this method has the advantage of enforcing current conservation at bifurcation and unification points, and allows for discrete coupling resistances.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Posse, Christian

2005-09-15

The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabási-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using other methods and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Posse, Christian

2005-09-15

The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabasi-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using standard power engineering methods, and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas (Conference Presentation)

NASA Astrophysics Data System (ADS)

De Angelis, Francesco

2017-06-01

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas Michele Dipalo, Valeria Caprettini, Anbrea Barbaglia, Laura Lovato, Francesco De Angelis e-mail: francesco.deangelis@iit.it Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova Biological systems are analysed mainly by optical, chemical or electrical methods. Normally each of these techniques provides only partial information about the environment, while combined investigations could reveal new phenomena occurring in complex systems such as in-vitro neuronal networks. Aiming at the merging of optical and electrical investigations of biological samples, we introduced three-dimensional plasmonic nanoantennas on CMOS-based electrical sensors [1]. The overall device is then capable of enhanced Raman Analysis of cultured cells combined with electrical recording of neuronal activity. The Raman measurements show a much higher sensitivity when performed on the tip of the nanoantenna in respect to the flat substrate [2]; this effect is a combination of the high plasmonic field enhancement and of the tight adhesion of cells on the nanoantenna tip. Furthermore, when plasmonic opto-poration is exploited [3] the 3D nanoelectrodes are able to penetrate through the cell membrane thus accessing the intracellular environment. Our latest results (unpublished) show that the technique is completely non-invasive and solves many problems related to state-of-the-art intracellular recording approaches on large neuronal networks. This research received funding from ERC-IDEAS Program: "Neuro-Plasmonics" [Grant n. 616213]. References: [1] M. Dipalo, G. C. Messina, H. Amin, R. La Rocca, V. Shalabaeva, A. Simi, A. Maccione, P. Zilio, L. Berdondini, F. De Angelis, Nanoscale 2015, 7, 3703. [2] R. La Rocca, G. C. Messina, M. Dipalo, V. Shalabaeva, F. De Angelis, Small 2015, 11, 4632. [3] G. C. Messina et al., Spatially, Temporally, and Quantitatively Controlled Delivery of Broad Range of Molecules into Selected Cells through Plasmonic Nanotubes. Advanced Materials 2015.

Advanced information society(5)

NASA Astrophysics Data System (ADS)

Tanizawa, Ippei

Based on the advancement of information network technology information communication forms informationalized society giving significant impact on business activities and life style in it. The information network has been backed up technologically by development of computer technology and has got great contribution by enhanced computer technology and communication equipments. Information is transferred by digital and analog methods. Technical development which has brought out multifunctioned modems of communication equipments in analog mode, and construction of advanced information communication network which has come out by joint work of computer and communication under digital technique, are described. The trend in institutional matter and standardization of electrical communication is also described showing some examples of value-added network (VAN).

Differences of brain electrical activity between moderate and severe obstructive sleep apneic patients: a LORETA study.

PubMed

Toth, Marton; Kondakor, Istvan; Faludi, Bela

2016-10-01

The effects of initiation of continuous positive airway pressure (CPAP) therapy on electroencephalographic (EEG) background activity were investigated in patients exhibiting both moderate (n = 13) and severe (n = 12) obstructive sleep apnea syndromes in the testing of the potential differences of alterations of brain electrical activity caused by chronic hypoxia between these two groups. A normal control group (n = 14) was also examined. Two EEG examinations were achieved in each group: before and after first-time CPAP therapy. Low-resolution electromagnetic tomography (LORETA) was implemented towards localizing the generators of EEG activity in separate frequency bands. Prior to CPAP treatment, as a common direction of change, analysis with LORETA demonstrated increased activity in comparison with the patient and control groups. In the moderate group, significant changes were detected in the alpha2 band in the posterior cingulate cortex as well as in the beta1 band in the right posterior parietal cortex and the left supramarginal gyrus. In the severe group, significant changes were found in theta and alpha1 bands in the posterior cingulate cortex. Following CPAP treatment, these significant differences vanished in the severe group. In the moderate group, significantly decreased activity was seen in the beta3 band in the right fusiform gyrus. These findings potentially suggest a normalizing effect of CPAP therapy on EEG background activity in both groups of obstructive sleep apnea syndrome patients. Compensatory alterations of brain electrical activity in regions associated with influencing successful memory retrieval, emotional perception, default mode network, anorexia and fear network caused by chronic intermittent hypoxia could possibly be reversed with the use of CPAP therapy. © 2016 European Sleep Research Society.

Prefrontal cortical network activity: Opposite effects of psychedelic hallucinogens and D1/D5 dopamine receptor activation

PubMed Central

Lambe, Evelyn K.; Aghajanian, George K.

2007-01-01

The fine-tuning of network activity provides a modulating influence on how information is processed and interpreted in the brain. Here, we use brain slices of rat prefrontal cortex to study how recurrent network activity is affected by neuromodulators known to alter normal cortical function. We previously determined that glutamate spillover and stimulation of extrasynaptic NMDA receptors are required to support hallucinogen-induced cortical network activity. Since microdialysis studies suggest that psychedelic hallucinogens and dopamine D1/D5 receptor agonists have opposite effects on extracellular glutamate in prefrontal cortex, we hypothesized that these two families of psychoactive drugs would have opposite effects on cortical network activity. We found that network activity can be enhanced by DOI (a psychedelic hallucinogen that is a partial agonist of serotonin 5-HT2A/2C receptors) and suppressed by the selective D1/D5 agonist SKF 38393. This suppression could be mimicked by direct activation of adenylyl cyclase with forskolin or by addition of a cAMP analog. These findings are consistent with previous work showing that activation of adenylyl cyclase can upregulate neuronal glutamate transporters, thereby decreasing synaptic spillover of glutamate. Consistent with this hypothesis, a low concentration of the glutamate transporter inhibitor TBOA restored electrically-evoked recurrent activity in the presence of a selective D1/D5 agonist, whereas recurrent activity in the presence of a low level of the GABAA antagonist bicuculline was not resistant to suppression by the D1/D5 agonist. The tempering of network UP states by D1/D5 receptor activation may have implications for the proposed use of D1/D5 agonists in the treatment of schizophrenia. PMID:17293055

Design of pressure-driven microfluidic networks using electric circuit analogy.

PubMed

Oh, Kwang W; Lee, Kangsun; Ahn, Byungwook; Furlani, Edward P

2012-02-07

This article reviews the application of electric circuit methods for the analysis of pressure-driven microfluidic networks with an emphasis on concentration- and flow-dependent systems. The application of circuit methods to microfluidics is based on the analogous behaviour of hydraulic and electric circuits with correlations of pressure to voltage, volumetric flow rate to current, and hydraulic to electric resistance. Circuit analysis enables rapid predictions of pressure-driven laminar flow in microchannels and is very useful for designing complex microfluidic networks in advance of fabrication. This article provides a comprehensive overview of the physics of pressure-driven laminar flow, the formal analogy between electric and hydraulic circuits, applications of circuit theory to microfluidic network-based devices, recent development and applications of concentration- and flow-dependent microfluidic networks, and promising future applications. The lab-on-a-chip (LOC) and microfluidics community will gain insightful ideas and practical design strategies for developing unique microfluidic network-based devices to address a broad range of biological, chemical, pharmaceutical, and other scientific and technical challenges.

Dynamic range in the C. elegans brain network

NASA Astrophysics Data System (ADS)

Antonopoulos, Chris G.

2016-01-01

We study external electrical perturbations and their responses in the brain dynamic network of the Caenorhabditis elegans soil worm, given by the connectome of its large somatic nervous system. Our analysis is inspired by a realistic experiment where one stimulates externally specific parts of the brain and studies the persistent neural activity triggered in other cortical regions. In this work, we perturb groups of neurons that form communities, identified by the walktrap community detection method, by trains of stereotypical electrical Poissonian impulses and study the propagation of neural activity to other communities by measuring the corresponding dynamic ranges and Steven law exponents. We show that when one perturbs specific communities, keeping the rest unperturbed, the external stimulations are able to propagate to some of them but not to all. There are also perturbations that do not trigger any response. We found that this depends on the initially perturbed community. Finally, we relate our findings for the former cases with low neural synchronization, self-criticality, and large information flow capacity, and interpret them as the ability of the brain network to respond to external perturbations when it works at criticality and its information flow capacity becomes maximal.

Recruitment of local inhibitory networks by horizontal connections in layer 2/3 of ferret visual cortex.

PubMed

Tucker, Thomas R; Katz, Lawrence C

2003-01-01

To investigate how neurons in cortical layer 2/3 integrate horizontal inputs arising from widely distributed sites, we combined intracellular recording and voltage-sensitive dye imaging to visualize the spatiotemporal dynamics of neuronal activity evoked by electrical stimulation of multiple sites in visual cortex. Individual stimuli evoked characteristic patterns of optical activity, while delivering stimuli at multiple sites generated interacting patterns in the regions of overlap. We observed that neurons in overlapping regions received convergent horizontal activation that generated nonlinear responses due to the emergence of large inhibitory potentials. The results indicate that co-activation of multiple sets of horizontal connections recruit strong inhibition from local inhibitory networks, causing marked deviations from simple linear integration.

Self-assembled tunable networks of sticky colloidal particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demortiere, Arnaud; Snezhko, Oleksiy Alexey; Sapozhnikov, Maksim

Self-assembled tunable networks of microscopic polymer fibers ranging from wavy colloidal "fur" to highly interconnected networks are created from polymer systems and an applied electric field. The networks emerge via dynamic self-assembly in an alternating (ac) electric field from a non-aqueous suspension of "sticky" polymeric colloidal particles with a controlled degree of polymerization. The resulting architectures are tuned by the frequency and amplitude of the electric field and surface properties of the particles.

Stochastic resonance enhancement of small-world neural networks by hybrid synapses and time delay

NASA Astrophysics Data System (ADS)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang

2017-01-01

The synergistic effect of hybrid electrical-chemical synapses and information transmission delay on the stochastic response behavior in small-world neuronal networks is investigated. Numerical results show that, the stochastic response behavior can be regulated by moderate noise intensity to track the rhythm of subthreshold pacemaker, indicating the occurrence of stochastic resonance (SR) in the considered neural system. Inheriting the characteristics of two types of synapses-electrical and chemical ones, neural networks with hybrid electrical-chemical synapses are of great improvement in neuron communication. Particularly, chemical synapses are conducive to increase the network detectability by lowering the resonance noise intensity, while the information is better transmitted through the networks via electrical coupling. Moreover, time delay is able to enhance or destroy the periodic stochastic response behavior intermittently. In the time-delayed small-world neuronal networks, the introduction of electrical synapses can significantly improve the signal detection capability by widening the range of optimal noise intensity for the subthreshold signal, and the efficiency of SR is largely amplified in the case of pure chemical couplings. In addition, the stochastic response behavior is also profoundly influenced by the network topology. Increasing the rewiring probability in pure chemically coupled networks can always enhance the effect of SR, which is slightly influenced by information transmission delay. On the other hand, the capacity of information communication is robust to the network topology within the time-delayed neuronal systems including electrical couplings.

A Phase-Locked Loop Epilepsy Network Emulator.

PubMed

Watson, P D; Horecka, K M; Cohen, N J; Ratnam, R

2016-10-15

Most seizure forecasting employs statistical learning techniques that lack a representation of the network interactions that give rise to seizures. We present an epilepsy network emulator (ENE) that uses a network of interconnected phase-locked loops (PLLs) to model synchronous, circuit-level oscillations between electrocorticography (ECoG) electrodes. Using ECoG data from a canine-epilepsy model (Davis et al. 2011) and a physiological entropy measure (approximate entropy or ApEn, Pincus 1995), we demonstrate the entropy of the emulator phases increases dramatically during ictal periods across all ECoG recording sites and across all animals in the sample. Further, this increase precedes the observable voltage spikes that characterize seizure activity in the ECoG data. These results suggest that the ENE is sensitive to phase-domain information in the neural circuits measured by ECoG and that an increase in the entropy of this measure coincides with increasing likelihood of seizure activity. Understanding this unpredictable phase-domain electrical activity present in ECoG recordings may provide a target for seizure detection and feedback control.

Defects formation and spiral waves in a network of neurons in presence of electromagnetic induction.

PubMed

Rostami, Zahra; Jafari, Sajad

2018-04-01

Complex anatomical and physiological structure of an excitable tissue (e.g., cardiac tissue) in the body can represent different electrical activities through normal or abnormal behavior. Abnormalities of the excitable tissue coming from different biological reasons can lead to formation of some defects. Such defects can cause some successive waves that may end up to some additional reorganizing beating behaviors like spiral waves or target waves. In this study, formation of defects and the resulting emitted waves in an excitable tissue are investigated. We have considered a square array network of neurons with nearest-neighbor connections to describe the excitable tissue. Fundamentally, electrophysiological properties of ion currents in the body are responsible for exhibition of electrical spatiotemporal patterns. More precisely, fluctuation of accumulated ions inside and outside of cell causes variable electrical and magnetic field. Considering undeniable mutual effects of electrical field and magnetic field, we have proposed the new Hindmarsh-Rose (HR) neuronal model for the local dynamics of each individual neuron in the network. In this new neuronal model, the influence of magnetic flow on membrane potential is defined. This improved model holds more bifurcation parameters. Moreover, the dynamical behavior of the tissue is investigated in different states of quiescent, spiking, bursting and even chaotic state. The resulting spatiotemporal patterns are represented and the time series of some sampled neurons are displayed, as well.

A functional magnetic resonance imaging study of human brain in pain-related areas induced by electrical stimulation with different intensities.

PubMed

Yuan, Wang; Ming, Zhang; Rana, Netra; Hai, Liu; Chen-wang, Jin; Shao-hui, Ma

2010-01-01

Pain-related studies have mainly been performed through traditional methods, which lack the rigorous analysis of anatomical locations. Functional magnetic resonance imaging (fMRI) is a noninvasive method detecting neural activity, and has the ability to precisely locate related activations in vivo. Moreover, few studies have used painful stimulation of changed intensity to investigate relevant functioning nuclei in the human brain. This study mainly focused on the pain-related activations induced by electrical stimulation with different intensities using fMRI. Furthermore, the electrophysiological characteristics of different pain-susceptible-neurons were analyzed to construct the pain modulatory network, which was corresponding to painful stimulus of changed intensity. Twelve volunteers underwent functional scanning receiving different electrical stimulation. The data were collected and analyzed to generate the corresponding functional activation maps and response time curves related to pain. The common activations were mainly located in several specific regions, including the secondary somatosensory cortex (SII), insula, anterior cingulate cortex (ACC), thalamus, and other cerebral regions. Moreover, innocuous electrical stimulation primarily activated the lateral portions of SII and thalamus, as well as the posterior insula, anterior ACC, whereas noxious electrical stimulation primarily activated the medial portions of SII and thalamus, as well as the anterior insula, the posterior ACC, with larger extensions and greater intensities. Several specified cerebral regions displayed different response patterns during electrical stimulation by means of fMRI, which implied that the corresponding pain-susceptible-neurons might process specific aspects of pain. Elucidation of functions on pain-related regions will help to understand the delicate pain modulation of human brain.

The active control strategy on the output power for photovoltaic-storage systems based on extended PQ-QV-PV Node

NASA Astrophysics Data System (ADS)

Xu, Chen; Zhou, Bao-Rong; Zhai, Jian-Wei; Zhang, Yong-Jun; Yi, Ying-Qi

2017-05-01

In order to solve the problem of voltage exceeding specified limits and improve the penetration of photovoltaic in distribution network, we can make full use of the active power regulation ability of energy storage(ES) and the reactive power regulation ability of grid-connected photovoltaic inverter to provide support of active power and reactive power for distribution network. A strategy of actively controlling the output power for photovoltaic-storage system based on extended PQ-QV-PV node by analyzing the voltage regulating mechanism of point of commom coupling(PCC) of photovoltaic with energy storage(PVES) by controlling photovoltaic inverter and energy storage. The strategy set a small wave range of voltage to every photovoltaic by making the type of PCC convert among PQ, PV and QV. The simulation results indicate that the active control method can provide a better solution to the problem of voltage exceeding specified limits when photovoltaic is connectted to electric distribution network.

Characteristic changes in brain electrical activity due to chronic hypoxia in patients with obstructive sleep apnea syndrome (OSAS): a combined EEG study using LORETA and omega complexity.

PubMed

Toth, Marton; Faludi, Bela; Wackermann, Jiri; Czopf, Jozsef; Kondakor, Istvan

2009-11-01

EEG background activity of patients with obstructive sleep apnea syndrome (OSAS, N = 25) was compared to that of normal controls (N = 14) to reflect alterations of brain electrical activity caused by chronic intermittent hypoxia in OSAS. Global and regional (left vs. right, anterior vs. posterior) measures of spatial complexity (Omega) were used to characterize the degree of spatial synchrony of EEG. Low resolution electromagnetic tomography (LORETA) was used to localize generators of EEG activity in separate frequency bands. Comparing patients to controls, lower Omega complexity was found globally and in the right hemisphere. Using LORETA, an increased medium frequency activity was seen bilaterally in the precuneus, paracentral and posterior cingulate cortex. These findings indicate that alterations caused by chronic hypoxia in brain electrical activity in regions associated with influencing emotional regulation, long-term memory and the default mode network. Global synchronization (lower Omega complexity) may indicate a significantly reduced number of relatively independent, parallel neural processes due to chronic global hypoxic state in apneic patients as well as over the right hemisphere.

Prediction of Industrial Electric Energy Consumption in Anhui Province Based on GA-BP Neural Network

NASA Astrophysics Data System (ADS)

Zhang, Jiajing; Yin, Guodong; Ni, Youcong; Chen, Jinlan

2018-01-01

In order to improve the prediction accuracy of industrial electrical energy consumption, a prediction model of industrial electrical energy consumption was proposed based on genetic algorithm and neural network. The model use genetic algorithm to optimize the weights and thresholds of BP neural network, and the model is used to predict the energy consumption of industrial power in Anhui Province, to improve the prediction accuracy of industrial electric energy consumption in Anhui province. By comparing experiment of GA-BP prediction model and BP neural network model, the GA-BP model is more accurate with smaller number of neurons in the hidden layer.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

PubMed

Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

PubMed Central

Grooms, Joshua K.; Thompson, Garth J.; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H.; Epstein, Charles M.

2017-01-01

Abstract A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies. PMID:28462586

Synchronization and coordination of sequences in two neural ensembles

NASA Astrophysics Data System (ADS)

Venaille, Antoine; Varona, Pablo; Rabinovich, Mikhail I.

2005-06-01

There are many types of neural networks involved in the sequential motor behavior of animals. For high species, the control and coordination of the network dynamics is a function of the higher levels of the central nervous system, in particular the cerebellum. However, in many cases, especially for invertebrates, such coordination is the result of direct synaptic connections between small circuits. We show here that even the chaotic sequential activity of small model networks can be coordinated by electrotonic synapses connecting one or several pairs of neurons that belong to two different networks. As an example, we analyzed the coordination and synchronization of the sequential activity of two statocyst model networks of the marine mollusk Clione. The statocysts are gravity sensory organs that play a key role in postural control of the animal and the generation of a complex hunting motor program. Each statocyst network was modeled by a small ensemble of neurons with Lotka-Volterra type dynamics and nonsymmetric inhibitory interactions. We studied how two such networks were synchronized by electrical coupling in the presence of an external signal which lead to winnerless competition among the neurons. We found that as a function of the number and the strength of connections between the two networks, it is possible to coordinate and synchronize the sequences that each network generates with its own chaotic dynamics. In spite of the chaoticity, the coordination of the signals is established through an activation sequence lock for those neurons that are active at a particular instant of time.

Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim.

PubMed

Parasuram, Harilal; Nair, Bipin; D'Angelo, Egidio; Hines, Michael; Naldi, Giovanni; Diwakar, Shyam

2016-01-01

Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals.

Defects formation and wave emitting from defects in excitable media

NASA Astrophysics Data System (ADS)

Ma, Jun; Xu, Ying; Tang, Jun; Wang, Chunni

2016-05-01

Abnormal electrical activities in neuronal system could be associated with some neuronal diseases. Indeed, external forcing can cause breakdown even collapse in nervous system under appropriate condition. The excitable media sometimes could be described by neuronal network with different topologies. The collective behaviors of neurons can show complex spatiotemporal dynamical properties and spatial distribution for electrical activities due to self-organization even from the regulating from central nervous system. Defects in the nervous system can emit continuous waves or pulses, and pacemaker-like source is generated to perturb the normal signal propagation in nervous system. How these defects are developed? In this paper, a network of neurons is designed in two-dimensional square array with nearest-neighbor connection type; the formation mechanism of defects is investigated by detecting the wave propagation induced by external forcing. It is found that defects could be induced under external periodical forcing under the boundary, and then the wave emitted from the defects can keep balance with the waves excited from external forcing.

Analysis of the variation of atmospheric electric field during solar events

NASA Astrophysics Data System (ADS)

Tacza, J.; Raulin, J. P.

2016-12-01

We present the capability of a new network of electric field mill sensors to monitor the atmospheric electric field at various locations in South America. The first task is to obtain a diurnal curve of atmospheric electric field variations under fair weather conditions, which we will consider as a reference curve. To accomplish this, we made daily, monthly, seasonal and annual averages. For all sensor location, the results show significant similarities with the Carnegie curve. The Carnegie curve is the characteristic curve in universal time of atmospheric electric field in fair weather and one thinks it is related to the currents flowing in the global atmospheric electric circuit. Ultimately, we pretend to study departures of the daily observations from the standard curve. This difference can be caused by solar, geophysical and atmospheric phenomena such as the solar activity cycle, solar flares and energetic charged particles, galactic cosmic rays, seismic activity and/or specific meteorological events. As an illustration we investigate solar effects on the atmospheric electric field observed at CASLEO (Lat. 31.798°S, Long. 69.295°W, Altitude: 2552 masl) by the method of superposed epoch analysis, between January 2010 and December 2015.

Robustness of a multimodal piezoelectric damping involving the electrical analogue of a plate

NASA Astrophysics Data System (ADS)

Lossouarn, Boris; Cunefare, Kenneth A.; Aucejo, Mathieu; Deü, Jean-François

2016-04-01

Multimodal passive damping of a mechanical structure can be implemented by a coupling to a secondary structure exhibiting similar modal properties. When considering a piezoelectric coupling, the secondary structure is an electrical network. A suitable topology for such a network can be obtained by a finite difference formulation of the mechanical equations, followed by a direct electromechanical analogy. This procedure is applied to the Kirchhoff-Love theory in order to find the electrical analogue of a clamped plate. The passive electrical network is implemented with inductors, transformers and the inherent capacitance of the piezoelectric patches. The electrical resonances are tuned to approach those of several mechanical modes simultaneously. This yields a broadband reduction of the plate vibrations through the array of interconnected piezoelectric patches. The robustness of the control strategy is evaluated by introducing perturbations in the mechanical or electrical designs. A non-optimal tuning is considered by way of a uniform variation of the network inductance. Then, the effect of local or boundary modifications of the electromechanical system is observed experimentally. In the end, the use of an analogous electrical network appears as an efficient and robust solution for the multimodal control of a plate.

Effect of gap junctions on the firing patterns and synchrony for different external inputs in the striatal fast-spiking neuron network.

PubMed

Zhang, Mingming; Zhao, Zongya; He, Ping; Wang, Jue

2014-01-01

Gap junctions are the mechanism for striatal fast-spiking interneurons (FSIs) to interconnect with each other and play an important role in determining the physiological functioning of the FSIs. To investigate the effect of gap junctions on the firing activities and synchronization of the network for different external inputs, a simple network with least connections and a Newman-Watts small-world network were constructed. Our research shows that both properties of neural networks are related to the conductance of the gap junctions, as well as the frequency and correlation of the external inputs. The effect of gap junctions on the synchronization of network is different for inputs with different frequencies and correlations. The addition of gap junctions can promote the network synchrony in some conditions but suppress it in others, and they can inhibit the firing activities in most cases. Both the firing rate and synchronization of the network increase along with the increase of the electrical coupling strength for inputs with low frequency and high correlation. Thus, the network of coupled FSIs can act as a detector for synchronous synaptic input from cortex and thalamus.

Response of Cultured Neuronal Network Activity After High-Intensity Power Frequency Magnetic Field Exposure

PubMed Central

Saito, Atsushi; Takahashi, Masayuki; Makino, Kei; Suzuki, Yukihisa; Jimbo, Yasuhiko; Nakasono, Satoshi

2018-01-01

High-intensity and low frequency (1–100 kHz) time-varying electromagnetic fields stimulate the human body through excitation of the nervous system. In power frequency range (50/60 Hz), a frequency-dependent threshold of the external electric field-induced neuronal modulation in cultured neuronal networks was used as one of the biological indicator in international guidelines; however, the threshold of the magnetic field-induced neuronal modulation has not been elucidated. In this study, we exposed rat brain-derived neuronal networks to a high-intensity power frequency magnetic field (hPF-MF), and evaluated the modulation of synchronized bursting activity using a multi-electrode array (MEA)-based extracellular recording technique. As a result of short-term hPF-MF exposure (50–400 mT root-mean-square (rms), 50 Hz, sinusoidal wave, 6 s), the synchronized bursting activity was increased in the 400 mT-exposed group. On the other hand, no change was observed in the 50–200 mT-exposed groups. In order to clarify the mechanisms of the 400 mT hPF-MF exposure-induced neuronal response, we evaluated it after blocking inhibitory synapses using bicuculline methiodide (BMI); subsequently, increase in bursting activity was observed with BMI application, and the response of 400 mT hPF-MF exposure disappeared. Therefore, it was suggested that the response of hPF-MF exposure was involved in the inhibitory input. Next, we screened the inhibitory pacemaker-like neuronal activity which showed autonomous 4–10 Hz firing with CNQX and D-AP5 application, and it was confirmed that the activity was reduced after 400 mT hPF-MF exposure. Comparison of these experimental results with estimated values of the induced electric field (E-field) in the culture medium revealed that the change in synchronized bursting activity occurred over 0.3 V/m, which was equivalent to the findings of a previous study that used the external electric fields. In addition, the results suggested that the potentiation of neuronal activity after 400 mT hPF-MF exposure was related to the depression of autonomous activity of pacemaker-like neurons. Our results indicated that the synchronized bursting activity was increased by hPF-MF exposure (E-field: >0.3 V/m), and the response was due to reduced inhibitory pacemaker-like neuronal activity. PMID:29662453

Neural signal registration and analysis of axons grown in microchannels

NASA Astrophysics Data System (ADS)

Pigareva, Y.; Malishev, E.; Gladkov, A.; Kolpakov, V.; Bukatin, A.; Mukhina, I.; Kazantsev, V.; Pimashkin, A.

2016-08-01

Registration of neuronal bioelectrical signals remains one of the main physical tools to study fundamental mechanisms of signal processing in the brain. Neurons generate spiking patterns which propagate through complex map of neural network connectivity. Extracellular recording of isolated axons grown in microchannels provides amplification of the signal for detailed study of spike propagation. In this study we used neuronal hippocampal cultures grown in microfluidic devices combined with microelectrode arrays to investigate a changes of electrical activity during neural network development. We found that after 5 days in vitro after culture plating the spiking activity appears first in microchannels and on the next 2-3 days appears on the electrodes of overall neural network. We conclude that such approach provides a convenient method to study neural signal processing and functional structure development on a single cell and network level of the neuronal culture.

Multimodal vibration damping of a plate by piezoelectric coupling to its analogous electrical network

NASA Astrophysics Data System (ADS)

Lossouarn, B.; Deü, J.-F.; Aucejo, M.; Cunefare, K. A.

2016-11-01

Multimodal damping can be achieved by coupling a mechanical structure to an electrical network exhibiting similar modal properties. Focusing on a plate, a new topology for such an electrical analogue is found from a finite difference approximation of the Kirchhoff-Love theory and the use of the direct electromechanical analogy. Discrete models based on element dynamic stiffness matrices are proposed to simulate square plate unit cells coupled to their electrical analogues through two-dimensional piezoelectric transducers. A setup made of a clamped plate covered with an array of piezoelectric patches is built in order to validate the control strategy and the numerical models. The analogous electrical network is implemented with passive components as inductors, transformers and the inherent capacitance of the piezoelectric patches. The effect of the piezoelectric coupling on the dynamics of the clamped plate is significant as it creates the equivalent of a multimodal tuned mass damping. An adequate tuning of the network then yields a broadband vibration reduction. In the end, the use of an analogous electrical network appears as an efficient solution for the multimodal control of a plate.

Non-contact measurement of electrical activity in neurons using magnified image spatial spectrum (MISS) microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Lee, Young J.; Best-Popescu, Catherine; Popescu, Gabriel; Jang, Sung-Soo; Chung, Hee Jung

2017-02-01

Traditionally the measurement of electrical activity in neurons has been carried out using microelectrode arrays that require the conducting elements to be in contact with the neuronal network. This method, also referred to as "electrophysiology", while being excellent in terms of temporal resolution is limited in spatial resolution and is invasive. An optical microscopy method for measuring electrical activity is thus highly desired. Common-path quantitative phase imaging (QPI) systems are good candidates for such investigations as they provide high sensitivity (on the order of nanometers) to the plasma membrane fluctuations that can be linked to electrical activity in a neuronal circuit. In this work we measured electrical activity in a culture of rat cortical neurons using MISS microscopy, a high-speed common-path QPI technique having an axial resolution of around 1 nm in optical path-length, which we introduced at PW BIOS 2016. Specifically, we measured the vesicular cycling (endocytosis and exocytosis) occurring at axon terminals of the neurons due to electrical activity caused by adding a high K+ solution to the cell culture. The axon terminals were localized using a micro-fluidic device that separated them from the rest of the culture. Stacks of images of these terminals were acquired at 826 fps both before and after K+ excitation and the temporal standard deviation maps for the two cases were compared to measure the membrane fluctuations. Concurrently, the existence of vesicular cycling was confirmed through fluorescent tagging and imaging of the vesicles at and around the axon terminals.

Cardiac abnormality prediction using HMLP network

NASA Astrophysics Data System (ADS)

Adnan, Ja'afar; Ahmad, K. A.; Mat, Muhamad Hadzren; Rizman, Zairi Ismael; Ahmad, Shahril

2018-02-01

Cardiac abnormality often occurs regardless of gender, age and races but depends on the lifestyle. This problem sometimes does not show any symptoms and usually detected once it already critical which lead to a sudden death to the patient. Basically, cardiac abnormality is the irregular electrical signal that generate by the pacemaker of the heart. This paper attempts to develop a program that can detect cardiac abnormality activity through implementation of Hybrid Multilayer Perceptron (HMLP) network. A certain amount of data of the heartbeat signals from the electrocardiogram (ECG) will be used in this project to train the MLP and HMLP network by using Modified Recursive Prediction Error (MRPE) algorithm and to test the network performance.

Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise

PubMed Central

Zhan, Feibiao; Liu, Shenquan

2017-01-01

Electrical activities are ubiquitous neuronal bioelectric phenomena, which have many different modes to encode the expression of biological information, and constitute the whole process of signal propagation between neurons. Therefore, we focus on the electrical activities of neurons, which is also causing widespread concern among neuroscientists. In this paper, we mainly investigate the electrical activities of the Morris-Lecar (M-L) model with electromagnetic radiation or Gaussian white noise, which can restore the authenticity of neurons in realistic neural network. First, we explore dynamical response of the whole system with electromagnetic induction (EMI) and Gaussian white noise. We find that there are slight differences in the discharge behaviors via comparing the response of original system with that of improved system, and electromagnetic induction can transform bursting or spiking state to quiescent state and vice versa. Furthermore, we research bursting transition mode and the corresponding periodic solution mechanism for the isolated neuron model with electromagnetic induction by using one-parameter and bi-parameters bifurcation analysis. Finally, we analyze the effects of Gaussian white noise on the original system and coupled system, which is conducive to understand the actual discharge properties of realistic neurons. PMID:29209192

Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise.

PubMed

Zhan, Feibiao; Liu, Shenquan

2017-01-01

Electrical activities are ubiquitous neuronal bioelectric phenomena, which have many different modes to encode the expression of biological information, and constitute the whole process of signal propagation between neurons. Therefore, we focus on the electrical activities of neurons, which is also causing widespread concern among neuroscientists. In this paper, we mainly investigate the electrical activities of the Morris-Lecar (M-L) model with electromagnetic radiation or Gaussian white noise, which can restore the authenticity of neurons in realistic neural network. First, we explore dynamical response of the whole system with electromagnetic induction (EMI) and Gaussian white noise. We find that there are slight differences in the discharge behaviors via comparing the response of original system with that of improved system, and electromagnetic induction can transform bursting or spiking state to quiescent state and vice versa. Furthermore, we research bursting transition mode and the corresponding periodic solution mechanism for the isolated neuron model with electromagnetic induction by using one-parameter and bi-parameters bifurcation analysis. Finally, we analyze the effects of Gaussian white noise on the original system and coupled system, which is conducive to understand the actual discharge properties of realistic neurons.

Development of coherent neuronal activity patterns in mammalian cortical networks: common principles and local hetereogeneity.

PubMed

Egorov, Alexei V; Draguhn, Andreas

2013-01-01

Many mammals are born in a very immature state and develop their rich repertoire of behavioral and cognitive functions postnatally. This development goes in parallel with changes in the anatomical and functional organization of cortical structures which are involved in most complex activities. The emerging spatiotemporal activity patterns in multi-neuronal cortical networks may indeed form a direct neuronal correlate of systemic functions like perception, sensorimotor integration, decision making or memory formation. During recent years, several studies--mostly in rodents--have shed light on the ontogenesis of such highly organized patterns of network activity. While each local network has its own peculiar properties, some general rules can be derived. We therefore review and compare data from the developing hippocampus, neocortex and--as an intermediate region--entorhinal cortex. All cortices seem to follow a characteristic sequence starting with uncorrelated activity in uncoupled single neurons where transient activity seems to have mostly trophic effects. In rodents, before and shortly after birth, cortical networks develop weakly coordinated multineuronal discharges which have been termed synchronous plateau assemblies (SPAs). While these patterns rely mostly on electrical coupling by gap junctions, the subsequent increase in number and maturation of chemical synapses leads to the generation of large-scale coherent discharges. These patterns have been termed giant depolarizing potentials (GDPs) for predominantly GABA-induced events or early network oscillations (ENOs) for mostly glutamatergic bursts, respectively. During the third to fourth postnatal week, cortical areas reach their final activity patterns with distinct network oscillations and highly specific neuronal discharge sequences which support adult behavior. While some of the mechanisms underlying maturation of network activity have been elucidated much work remains to be done in order to fully understand the rules governing transition from immature to mature patterns of network activity. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Distinct Spatiotemporal Activation Patterns of the Perirhinal-Entorhinal Network in Response to Cortical and Amygdala Input

PubMed Central

Willems, Janske G. P.; Wadman, Wytse J.; Cappaert, Natalie L. M.

2016-01-01

The perirhinal (PER) and entorhinal cortex (EC) receive input from the agranular insular cortex (AiP) and the subcortical lateral amygdala (LA) and the main output area is the hippocampus. Information transfer through the PER/EC network however, is not always guaranteed. It is hypothesized that this network actively regulates the (sub)cortical activity transfer to the hippocampal network and that the inhibitory system is involved in this function. This study determined the recruitment by the AiP and LA afferents in PER/EC network with the use of voltage sensitive dye (VSD) imaging in horizontal mouse brain slices. Electrical stimulation (500 μA) of the AiP induced activity that gradually propagated predominantly in the rostro-caudal direction: from the PER to the lateral EC (LEC). In the presence of 1 μM of the competitive γ-aminobutyric acid (GABAA) receptor antagonist bicuculline, AiP stimulation recruited the medial EC (MEC) as well. In contrast, LA stimulation (500 μA) only induced activity in the deep layers of the PER. In the presence of bicuculline, the initial population activity in the PER propagated further towards the superficial layers and the EC after a delay. The latency of evoked responses decreased with increasing stimulus intensities (50–500 μA) for both the AiP and LA stimuli. The stimulation threshold for evoking responses in the PER/EC network was higher for the LA than for the AiP. This study showed that the extent of the PER/EC network activation depends on release of inhibition. When GABAA dependent inhibition is reduced, both the AiP and the LA activate spatially overlapping regions, although in a distinct spatiotemporal fashion. It is therefore hypothesized that the inhibitory network regulates excitatory activity from both cortical and subcortical areas that has to be transmitted through the PER/EC network. PMID:27378860

Hydropower in the Southeast: Balancing Lakeview and Production Optimization

NASA Astrophysics Data System (ADS)

Engstrom, J.

2017-12-01

Hydropower is the most important source of renewable electricity in Southeastern U.S. However, the region is repeatedly struck by droughts, and there are many conflicting interests in the limited water resource. This study takes a historical perspective and investigates how hydropower production patterns have changed over time, considering both natural drivers and human dimensions. Hydropower production is strongly tied to the natural variability of large-scale atmospheric drivers (teleconnections) as they affect the water availability in the whole river system and partly also the market demand. To balance the water resource between different interests is a complex task, and the conflicting interests vary by basin, sometimes over a relatively small geographic area. Here road networks adjacent to the hydropower reservoirs are used as an indicator of human development and recreational activities. Through a network analysis of the historical development of road networks surrounding the reservoir, the local and regional conflicting interests are identified and the influence on renewable electricity production quantified.

Neural networks applied to discriminate botanical origin of honeys.

PubMed

Anjos, Ofélia; Iglesias, Carla; Peres, Fátima; Martínez, Javier; García, Ángela; Taboada, Javier

2015-05-15

The aim of this work is develop a tool based on neural networks to predict the botanical origin of honeys using physical and chemical parameters. The managed database consists of 49 honey samples of 2 different classes: monofloral (almond, holm oak, sweet chestnut, eucalyptus, orange, rosemary, lavender, strawberry trees, thyme, heather, sunflower) and multifloral. The moisture content, electrical conductivity, water activity, ashes content, pH, free acidity, colorimetric coordinates in CIELAB space (L(∗), a(∗), b(∗)) and total phenols content of the honey samples were evaluated. Those properties were considered as input variables of the predictive model. The neural network is optimised through several tests with different numbers of neurons in the hidden layer and also with different input variables. The reduced error rates (5%) allow us to conclude that the botanical origin of honey can be reliably and quickly known from the colorimetric information and the electrical conductivity of honey. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fabrication and electrical characterization of silicon nanowires based resistors

NASA Astrophysics Data System (ADS)

Ni, L.; Demami, F.; Rogel, R.; Salaün, A. C.; Pichon, L.

2009-11-01

Silicon nanowires (SiNWs) are synthesized via the Vapor-Liquid-Solid (VLS) mechanism using gold (Au) as metal catalyst and silane (SiH4) as precursor gas. Au nanoparticles are employed as liquid droplets catalysis during the SiNWs growth performed in a hot wall LPCVD reactor at 480°C and 40 Pa. SiNWs local synthesis at micron scale is demonstrated using classical optical photolithography process. SiNWs grow with high density anchored at the dedicated catalyst islands. This resulting network is used to interconnect two heavily doped polysilicon interdigitated electrodes leading to the formation of electrical resistors in a coplanar structure. Current-voltage (I-V) characteristics highlight a symmetric shape. The temperature dependence of the electrical resistance is activated, with activation energy of 0.47 eV at temperatures greater than 300K.

Vertically oriented graphene bridging active-layer/current-collector interface for ultrahigh rate supercapacitors.

PubMed

Bo, Zheng; Zhu, Weiguang; Ma, Wei; Wen, Zhenhai; Shuai, Xiaorui; Chen, Junhong; Yan, Jianhua; Wang, Zhihua; Cen, Kefa; Feng, Xinliang

2013-10-25

Dense networks of graphene nanosheets standing vertically on a current collector can work as numerous electrically conductive bridges to facilitate charge transport and mitigate the constriction/spreading resistance at the interface between the active material and the current collector. The vertically oriented graphene-bridged supercapacitors present excellent rate and power capabilities. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CO2 Emissions Embodied in Interprovincial Electricity Transmissions in China.

PubMed

Qu, Shen; Liang, Sai; Xu, Ming

2017-09-19

Existing studies on the evaluation of CO 2 emissions due to electricity consumption in China are inaccurate and incomplete. This study uses a network approach to calculate CO 2 emissions of purchased electricity in Chinese provinces. The CO 2 emission factors of purchased electricity range from 265 g/kWh in Sichuan to 947 g/kWh in Inner Mongolia. We find that emission factors of purchased electricity in many provinces are quite different from the emission factors of electricity generation. This indicates the importance of the network approach in accurately reflecting embodied emissions. We also observe substantial variations of emissions factors of purchased electricity within subnational grids: the provincial emission factors deviate from the corresponding subnational-grid averages from -58% to 44%. This implies that using subnational-grid averages as required by Chinese government agencies can be quite inaccurate for reporting indirect CO 2 emissions of enterprises' purchased electricity. The network approach can improve the accuracy of the quantification of embodied emissions in purchased electricity and emission flows embodied in electricity transmission.

The variation of the ground electric field associated with the Mei-Nung earthquake on Feb. 6, 2016

NASA Astrophysics Data System (ADS)

Bing-Chih Chen, Alfred; Yeh, Er-Chun; Chuang, Chia-Wen

2017-04-01

Recent studies show that a strong coupling exists between lithosphere, atmosphere and extending up to the ionosphere. Natural phenomena on the ground surface such as oceans variation, volcanic and seismic activities such as earthquakes, and lightning possibly generate significant impacts at ionosphere immediately by electrodynamic processes. The electric field near the ground is one of the potential quantities to explore this coupling process, especially caused by earthquake. Unfortunately, thunderstorm, dust storm or human activities also affect the measured electric field at ground. To investigate the feasibility of a network to monitor the variation of the ground electric field driven by the lightning and earthquake, a filed mill has been deployed in the NCKU campus since Dec. 2015, and luckily experienced the earthquake with a moment magnitude of 6.4 struck 28 km on 6 Feb. 2016. The recorded ground electric field deceased steadily since 1.5 days before the earthquake, and returned to normal level gradually. Moreover, this special feature can not be identified in the other period of the field test. The detail analysis is reported in this presentation.

Optical sensors for electrical elements of a medium voltage distribution network

NASA Astrophysics Data System (ADS)

De Maria, Letizia; Bartalesi, Daniele; Serragli, Paolo; Paladino, Domenico

2012-04-01

The aging of most of the components of the National transmission and distribution system can potentially influence the reliability of power supply in a Medium Voltage (MV) network. In order to prevent possible dangerous situations, selected diagnostic indicators on electrical parts exploiting reliable and potentially low-cost sensors are required. This paper presents results concerning two main research activities regarding the development and application of innovative optical sensors for the diagnostic of MV electrical components. The first concerns a multi-sensor prototype for the detection of pre-discharges in MV switchboards: it is the combination of three different types of sensors operating simultaneously to detect incipient failure and to reduce the occurrence of false alarms. The system is real-time controlled by an embedded computer through a LabView interface. The second activity refers to a diagnostic tool to provide significant real-time information about early aging of MV/Low Voltage (LV) transformers by means of its vibration fingerprint. A miniaturized Optical Micro-Electro-Mechanical System (MEMS) based unit has been assembled for vibration measurements, wireless connected to a remote computer and controlled via LabView interface. Preliminary comparative tests were carried out with standard piezoelectric accelerometers on a conventional MV/LV test transformer under open circuit and in short-circuited configuration.

An Energy Efficient Technique Using Electric Active Shielding for Capacitive Coupling Intra-Body Communication

PubMed Central

Ma, Chao; Huang, Zhonghua; Wang, Zhiqi; Zhou, Linxuan; Li, Yinlin

2017-01-01

Capacitive coupling intra-body communication (CC-IBC) has become one of the candidates for healthcare sensor networks due to its positive prevailing features of energy efficiency, transmission rate and security. Under the CC-IBC scheme, some of the electric field emitted from signal (SIG) electrode of the transmitter will couple directly to the ground (GND) electrode, acting equivalently as an internal impedance of the signal source and inducing considerable energy losses. However, none of the previous works have fully studied the problem. In this paper, the underlying theory of such energy loss is investigated and quantitatively evaluated using conventional parameters. Accordingly, a method of electric active shielding is proposed to reduce the displacement current across the SIG-GND electrodes, leading to less power loss. In addition, the variation of such loss in regard to frequency range and positions on human body was also considered. The theory was validated by finite element method simulation and experimental measurement. The prototype result shows that the receiving power has been improved by approximate 5.5 dBm while the total power consumption is maximally 9 mW less using the proposed technique, providing an energy efficient option in physical layer for wearable and implantable healthcare sensor networks. PMID:28885546

Review Of E-Beam Electrical Test Techniques

NASA Astrophysics Data System (ADS)

Hohn, Fritz J.

1987-09-01

Electron beams as a viable technique for contactless testing of electrical functions and electrical integrity of different active devices in VLSI-chips has been demonstrated over the past years. This method of testing electronic networks, most widely used in the laboratory environment, is based on an electron probe which is deflected from point to point in the network. A current of secondary electrons emitted in response to the impingement of the electron probe is converted to a signal indicating the presence of a voltage or varying potential at the different points. Voltage contrast, electron beam induced current, dual potential approach, stroboscopic techniques and other methods have been developed and are used to detect different functional failures in devices. Besides the VLSI application, the contactless testing of three dimensional conductor networks of a 10cm x 10cm x .8cm multilayer ceramic module poses a different and new application for the electron beam test technique. A dual potential electron beam test system allows to generate electron beam induced voltage contrast. The same system at a different potential is used to detect this voltage contrast over the large area without moving the substrate and thus test for the electrical integrity of the networks. Less attention in most of the applications has been paid to the electron optical environment, mostly SEM's were upgraded or converted to do the job of a "voltage contrast" machine. This by no means will satisfy all requirements and more thoughts have to be given to aspects such as: low voltage electron guns: thermal emitter, Schottky emitter, field emitter, low voltage electron optics, two lens systems, different means of detection, signal processing - storage and others. This paper will review available E-beam test techniques, specific applications and some critical components.

Nanostructured CuS networks composed of interconnected nanoparticles for asymmetric supercapacitors.

PubMed

Fu, Wenbin; Han, Weihua; Zha, Heming; Mei, Junfeng; Li, Yunxia; Zhang, Zemin; Xie, Erqing

2016-09-21

Nanostructured metal sulfides with excellent electrochemical activity and electrical conductivity are particularly promising for applications in high-performance energy storage devices. Here, we report on the facile synthesis of nanostructured CuS networks composed of interconnected nanoparticles as novel battery-type materials for asymmetric supercapacitors. We find that the CuS networks exhibit a high specific capacity of 49.8 mA g(-1) at a current density of 1 A g(-1), good rate capability and cycle stability. The superior performance could be attributed to the interconnected nanoparticles of CuS networks, which can facilitate electrolyte diffusion and provide fast electron pathways. Furthermore, an aqueous asymmetric supercapacitor has been assembled by using the CuS networks as the positive electrode and activated carbon as the negative electrode. The assembled device can work at a high operating voltage of 1.6 V and show a maximum energy density of 17.7 W h kg(-1) at a power density of 504 W kg(-1). This study indicates that the CuS networks have great potential for supercapacitor applications.

Research on the full life cycle management system of smart electric energy meter

NASA Astrophysics Data System (ADS)

Chen, Xiangqun; Huang, Rui; Shen, Liman; Guo, Dingying; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Renheng, Xu

2018-02-01

At present, China’s smart electric energy meter life management is started from the procurement and acceptance. The related monitoring and management of the manufacturing sector has not yet been carried out. This article applies RFID technology and network cloud platform to full life cycle management system of smart electric energy meters, builds this full life cycle management system including design and manufacturing, process control, measurement and calibration testing, storage management, user acceptance, site operation, maintenance scrap and other aspects. Exploring smart electric energy meters on-line and off-line communication by the application of active RFID communication functions, and the actual functional application such as local data exchange and instrument calibration. This system provides technical supports on power demand side management and the improvement of smart electric energy meter reliability evaluation system.

Ionic messengers in development and cancer.

PubMed

Moreau, Marc; Leclerc, Catherine

2015-01-01

The idea that electrical fields can influence the development of an organism is not new. Electrical fields in cells are mainly due to the presence of channels which are permeable and selective for different ions and transporters. Modulation of their activities can affect cell cycle properties, proliferation and differentiation.Electrical fields are important for embryonic patterning, regeneration and tumour development. Membrane potential is a permanent signal which allows communication between cells, tissues and organs and has to be considered to have the same importance as biochemical signals. The activity of ion channels and pumps which maintain the electrical fields can now be dissected and visualized with new tools involving fluorescent reporters.Despite the fact that our understanding, at the molecular level, of the role of bioelectric signaling pathways, ion currents, voltage and pH gradients in developmental biology and tumor progression is increasing, therapeutic applications of this knowledge still appears to be far away. For the moment, research priorities seem to be on establishing the links between biochemical events, genetic regulation, and network interactions.

Electrotonic potentials in Aloe vera L.: Effects of intercellular and external electrodes arrangement.

PubMed

Volkov, Alexander G; Nyasani, Eunice K; Tuckett, Clayton; Scott, Jessenia M; Jackson, Mariah M Z; Greeman, Esther A; Greenidge, Ariane S; Cohen, Devin O; Volkova, Maia I; Shtessel, Yuri B

2017-02-01

Electrostimulation of plants can induce plant movements, activation of ion channels, ion transport, gene expression, enzymatic systems activation, electrical signaling, plant-cell damage, enhanced wound healing, and influence plant growth. Here we found that electrical networks in plant tissues have electrical differentiators. The amplitude of electrical responses decreases along a leaf and increases by decreasing the distance between polarizing Pt-electrodes. Intercellular Ag/AgCl electrodes inserted in a leaf and extracellular Ag/AgCl electrodes attached to the leaf surface were used to detect the electrotonic potential propagation along a leaf of Aloe vera. There is a difference in duration and amplitude of electrical potentials measured by electrodes inserted in a leaf and those attached to a leaf's surface. If the external reference electrode is located in the soil near the root, it changes the amplitude and duration of electrotonic potentials due to existence of additional resistance, capacitance, ion channels and ion pumps in the root. The information gained from this study can be used to elucidate extracellular and intercellular communication in the form of electrical signals within plants. Copyright © 2016 Elsevier B.V. All rights reserved.

Connexin-Dependent Neuroglial Networking as a New Therapeutic Target.

PubMed

Charvériat, Mathieu; Naus, Christian C; Leybaert, Luc; Sáez, Juan C; Giaume, Christian

2017-01-01

Astrocytes and neurons dynamically interact during physiological processes, and it is now widely accepted that they are both organized in plastic and tightly regulated networks. Astrocytes are connected through connexin-based gap junction channels, with brain region specificities, and those networks modulate neuronal activities, such as those involved in sleep-wake cycle, cognitive, or sensory functions. Additionally, astrocyte domains have been involved in neurogenesis and neuronal differentiation during development; they participate in the "tripartite synapse" with both pre-synaptic and post-synaptic neurons by tuning down or up neuronal activities through the control of neuronal synaptic strength. Connexin-based hemichannels are also involved in those regulations of neuronal activities, however, this feature will not be considered in the present review. Furthermore, neuronal processes, transmitting electrical signals to chemical synapses, stringently control astroglial connexin expression, and channel functions. Long-range energy trafficking toward neurons through connexin-coupled astrocytes and plasticity of those networks are hence largely dependent on neuronal activity. Such reciprocal interactions between neurons and astrocyte networks involve neurotransmitters, cytokines, endogenous lipids, and peptides released by neurons but also other brain cell types, including microglial and endothelial cells. Over the past 10 years, knowledge about neuroglial interactions has widened and now includes effects of CNS-targeting drugs such as antidepressants, antipsychotics, psychostimulants, or sedatives drugs as potential modulators of connexin function and thus astrocyte networking activity. In physiological situations, neuroglial networking is consequently resulting from a two-way interaction between astrocyte gap junction-mediated networks and those made by neurons. As both cell types are modulated by CNS drugs we postulate that neuroglial networking may emerge as new therapeutic targets in neurological and psychiatric disorders.

Neuromodulation: Selected approaches and challenges

PubMed Central

Parpura, Vladimir; Silva, Gabriel A.; Tass, Peter A.; Bennet, Kevin E.; Meyyappan, Meyya; Koehne, Jessica; Lee, Kendall H.; Andrews, Russell J.

2012-01-01

The brain operates through complex interactions in the flow of information and signal processing within neural networks. The “wiring” of such networks, being neuronal or glial, can physically and/or functionally go rogue in various pathological states. Neuromodulation, as a multidisciplinary venture, attempts to correct such faulty nets. In this review, selected approaches and challenges in neuromoduation are discussed. The use of water-dispersible carbon nanotubes have proven effective in modulation of neurite outgrowth in culture as well as in aiding regeneration after spinal cord injury in vivo. Studying neural circuits using computational biology and analytical engineering approaches brings to light geometrical mapping of dynamics within neural networks, much needed information for stimulation interventions in medical practice. Indeed, sophisticated desynchronization approaches used for brain stimulation have been successful in coaxing “misfiring” neuronal circuits to resume productive firing patterns in various human disorders. Devices have been developed for the real time measurement of various neurotransmitters as well as electrical activity in the human brain during electrical deep brain stimulation. Such devices can establish the dynamics of electrochemical changes in the brain during stimulation. With increasing application of nanomaterials in devices for electrical and chemical recording and stimulating in the brain, the era of cellular, and even intracellular, precision neuromodulation will soon be upon us. PMID:23190025

Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities.

PubMed

Ostojic, Srdjan; Brunel, Nicolas; Hakim, Vincent

2009-06-01

We investigate how synchrony can be generated or induced in networks of electrically coupled integrate-and-fire neurons subject to noisy and heterogeneous inputs. Using analytical tools, we find that in a network under constant external inputs, synchrony can appear via a Hopf bifurcation from the asynchronous state to an oscillatory state. In a homogeneous net work, in the oscillatory state all neurons fire in synchrony, while in a heterogeneous network synchrony is looser, many neurons skipping cycles of the oscillation. If the transmission of action potentials via the electrical synapses is effectively excitatory, the Hopf bifurcation is supercritical, while effectively inhibitory transmission due to pronounced hyperpolarization leads to a subcritical bifurcation. In the latter case, the network exhibits bistability between an asynchronous state and an oscillatory state where all the neurons fire in synchrony. Finally we show that for time-varying external inputs, electrical coupling enhances the synchronization in an asynchronous network via a resonance at the firing-rate frequency.

Modelling of piezoelectric actuator dynamics for active structural control

NASA Technical Reports Server (NTRS)

Hagood, Nesbitt W.; Chung, Walter H.; Von Flotow, Andreas

1990-01-01

The paper models the effects of dynamic coupling between a structure and an electrical network through the piezoelectric effect. The coupled equations of motion of an arbitrary elastic structure with piezoelectric elements and passive electronics are derived. State space models are developed for three important cases: direct voltage driven electrodes, direct charge driven electrodes, and an indirect drive case where the piezoelectric electrodes are connected to an arbitrary electrical circuit with embedded voltage and current sources. The equations are applied to the case of a cantilevered beam with surface mounted piezoceramics and indirect voltage and current drive. The theoretical derivations are validated experimentally on an actively controlled cantilevered beam test article with indirect voltage drive.

Gross domestic product estimation based on electricity utilization by artificial neural network

NASA Astrophysics Data System (ADS)

Stevanović, Mirjana; Vujičić, Slađana; Gajić, Aleksandar M.

2018-01-01

The main goal of the paper was to estimate gross domestic product (GDP) based on electricity estimation by artificial neural network (ANN). The electricity utilization was analyzed based on different sources like renewable, coal and nuclear sources. The ANN network was trained with two training algorithms namely extreme learning method and back-propagation algorithm in order to produce the best prediction results of the GDP. According to the results it can be concluded that the ANN model with extreme learning method could produce the acceptable prediction of the GDP based on the electricity utilization.

Development of network-based multichannel neuromuscular electrical stimulation system for stroke rehabilitation.

PubMed

Qu, Hongen; Xie, Yongji; Liu, Xiaoxuan; He, Xin; Hao, Manzhao; Bao, Yong; Xie, Qing; Lan, Ning

2016-01-01

Neuromuscular electrical stimulation (NMES) is a promising assistive technology for stroke rehabilitation. Here we present the design and development of a multimuscle stimulation system as an emerging therapy for people with paretic stroke. A network-based multichannel NMES system was integrated based on dual bus architecture of communication and an H-bridge current regulator with a power booster. The structure of the system was a body area network embedded with multiple stimulators and a communication protocol of controlled area network to transmit muscle stimulation parameter information to individual stimulators. A graphical user interface was designed to allow clinicians to specify temporal patterns and muscle stimulation parameters. We completed and tested a prototype of the hardware and communication software modules of the multichannel NMES system. The prototype system was first verified in nondisabled subjects for safety, and then tested in subjects with stroke for feasibility with assisting multijoint movements. Results showed that synergistic stimulation of multiple muscles in subjects with stroke improved performance of multijoint movements with more natural velocity profiles at elbow and shoulder and reduced acromion excursion due to compensatory trunk rotation. The network-based NMES system may provide an innovative solution that allows more physiological activation of multiple muscles in multijoint task training for patients with stroke.

Coordination of locomotor and cardiorespiratory networks of Lymnaea stagnalis by a pair of identified interneurones.

PubMed

Syed, N I; Winlow, W

1991-07-01

1. The morphology and electrophysiology of a newly identified bilateral pair of interneurones in the central nervous system of the pulmonate pond snail Lymnaea stagnalis is described. 2. These interneurones, identified as left and right pedal dorsal 11 (L/RPeD11), are electrically coupled to each other as well as to a large number of foot and body wall motoneurones, forming a fast-acting neural network which coordinates the activities of foot and body wall muscles. 3. The left and right sides of the body wall of Lymnaea are innervated by left and right cerebral A cluster neurones. Although these motoneurones have only ipsilateral projections, they are indirectly electrically coupled to their contralateral homologues via their connections with L/RPeD11. Similarly, the activities of left and right pedal G cluster neurones, which are known to be involved in locomotion, are also coordinated by L/RPeD11. 4. Selective ablation of both neurones PeD11 results in the loss of coordination between the bilateral cerebral A clusters. 5. Interneurones L/RPeD11 are multifunctional. In addition to coordinating motoneuronal activity, they make chemical excitatory connections with heart motoneurones. They also synapse upon respiratory motoneurones, hyperpolarizing those involved in pneumostome opening (expiration) and depolarizing those involved in pneumostome closure (inspiration). 6. An identified respiratory interneurone involved in pneumostome closure (visceral dorsal 4) inhibits L/RPeD11 together with all their electrically coupled follower cells. 7. Both L/RPeD11 have strong excitatory effects on another pair of electrically coupled neurones, visceral dorsal 1 and right parietal dorsal 2, which have previously been shown to be sensitive to changes in the partial pressure of environmental oxygen (PO2). 8. Although L/RPeD11 participate in whole-body withdrawal responses, electrical stimulation applied directly to these neurones was not sufficient to induce this behaviour.

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer’s Disease

PubMed Central

Dulla, Chris G.; Coulter, Douglas A.; Ziburkus, Jokubas

2015-01-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer’s disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. PMID:25948650

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer's Disease.

PubMed

Dulla, Chris G; Coulter, Douglas A; Ziburkus, Jokubas

2016-06-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer's disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. © The Author(s) 2015.

Electrical Properties of an m × n Hammock Network

NASA Astrophysics Data System (ADS)

Tan, Zhen; Tan, Zhi-Zhong; Zhou, Ling

2018-05-01

Electrical property is an important problem in the field of natural science and physics, which usually involves potential, current and resistance in the electric circuit. We investigate the electrical properties of an arbitrary hammock network, which has not been resolved before, and propose the exact potential formula of an arbitrary m × n hammock network by means of the Recursion-Transform method with current parameters (RT-I) pioneered by one of us [Z. Z. Tan, Phys. Rev. E 91 (2015) 052122], and the branch currents and equivalent resistance of the network are derived naturally. Our key technique is to setting up matrix equations and making matrix transformation, the potential formula derived is a meaningful discovery, which deduces many novel applications. The discovery of potential formula of the hammock network provides new theoretical tools and techniques for related scientific research. Supported by the Natural Science Foundation of Jiangsu Province under Grant No. BK20161278

EMMNet: sensor networking for electricity meter monitoring.

PubMed

Lin, Zhi-Ting; Zheng, Jie; Ji, Yu-Sheng; Zhao, Bao-Hua; Qu, Yu-Gui; Huang, Xu-Dong; Jiang, Xiu-Fang

2010-01-01

Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters.

EMMNet: Sensor Networking for Electricity Meter Monitoring

PubMed Central

Lin, Zhi-Ting; Zheng, Jie; Ji, Yu-Sheng; Zhao, Bao-Hua; Qu, Yu-Gui; Huang, Xu-Dong; Jiang, Xiu-Fang

2010-01-01

Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters. PMID:22163551

The Influence of Cold Temperature on Cellular Excitability of Hippocampal Networks

PubMed Central

Vara, Hugo; Caires, Rebeca; Ballesta, Juan J.; Belmonte, Carlos; Viana, Felix

2012-01-01

The hippocampus plays an important role in short term memory, learning and spatial navigation. A characteristic feature of the hippocampal region is its expression of different electrical population rhythms and activities during different brain states. Physiological fluctuations in brain temperature affect the activity patterns in hippocampus, but the underlying cellular mechanisms are poorly understood. In this work, we investigated the thermal modulation of hippocampal activity at the cellular network level. Primary cell cultures of mouse E17 hippocampus displayed robust network activation upon light cooling of the extracellular solution from baseline physiological temperatures. The activity generated was dependent on action potential firing and excitatory glutamatergic synaptic transmission. Involvement of thermosensitive channels from the transient receptor potential (TRP) family in network activation by temperature changes was ruled out, whereas pharmacological and immunochemical experiments strongly pointed towards the involvement of temperature-sensitive two-pore-domain potassium channels (K2P), TREK/TRAAK family. In hippocampal slices we could show an increase in evoked and spontaneous synaptic activity produced by mild cooling in the physiological range that was prevented by chloroform, a K2P channel opener. We propose that cold-induced closure of background TREK/TRAAK family channels increases the excitability of some hippocampal neurons, acting as a temperature-sensitive gate of network activation. Our findings in the hippocampus open the possibility that small temperature variations in the brain in vivo, associated with metabolism or blood flow oscillations, act as a switch mechanism of neuronal activity and determination of firing patterns through regulation of thermosensitive background potassium channel activity. PMID:23300680

VHF discharges in storm cells producing microbursts

NASA Technical Reports Server (NTRS)

Laroche, P.; Malherbe, C.; Bondiou, A.; Weber, M.; Engholm, C.; Coel, V.

1991-01-01

An experiment was carried out in which 3-D mapping of VHF sources was compared to a 3-D description of the reflectivity and dynamics of associated cloud cells observed by a radar network. Data from 61 microbursts were analyzed and it was found that, in 93 pct. of the cases, electrical activity precedes outflow development. The results confirm that the peak in intracloud activity precedes the maximum value of the outflow.

System and method for islanding detection and prevention in distributed generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhowmik, Shibashis; Mazhari, Iman; Parkhideh, Babak

Various examples are directed to systems and methods for detecting an islanding condition at an inverter configured to couple a distributed generation system to an electrical grid network. A controller may determine a command frequency and a command frequency variation. The controller may determine that the command frequency variation indicates a potential islanding condition and send to the inverter an instruction to disconnect the distributed generation system from the electrical grid network. When the distributed generation system is disconnected from the electrical grid network, the controller may determine whether the grid network is valid.

A Phase-Locked Loop Epilepsy Network Emulator

PubMed Central

Watson, P.D.; Horecka, K. M.; Cohen, N.J.; Ratnam, R.

2015-01-01

Most seizure forecasting employs statistical learning techniques that lack a representation of the network interactions that give rise to seizures. We present an epilepsy network emulator (ENE) that uses a network of interconnected phase-locked loops (PLLs) to model synchronous, circuit-level oscillations between electrocorticography (ECoG) electrodes. Using ECoG data from a canine-epilepsy model (Davis et al. 2011) and a physiological entropy measure (approximate entropy or ApEn, Pincus 1995), we demonstrate the entropy of the emulator phases increases dramatically during ictal periods across all ECoG recording sites and across all animals in the sample. Further, this increase precedes the observable voltage spikes that characterize seizure activity in the ECoG data. These results suggest that the ENE is sensitive to phase-domain information in the neural circuits measured by ECoG and that an increase in the entropy of this measure coincides with increasing likelihood of seizure activity. Understanding this unpredictable phase-domain electrical activity present in ECoG recordings may provide a target for seizure detection and feedback control. PMID:26664133

Electric Field and Lightning Observations in the Core of Category 5 Hurricane Emily

NASA Technical Reports Server (NTRS)

Blakeslee, Richard; Mach, Doug M.; Bateman, Monte G.; Bailey, Jeff C.

2007-01-01

Significant electric fields and lightning activity associated with Hurricane Emily were observed from a NASA high-altitude ER-2 aircraft on July 17, 2005 while this storm developed as a compact but intense category 5 hurricane in the Caribbean south of Cuba. The electrical measurements were acquired as part of the NASA sponsored Tropical Cloud Systems and Processes (TCSP) experiment. In addition to the electrical measurements, the aircraft's remote sensing instrument complement also included active radars, passive microwave, visible and infrared radiometers, and a temperature sounder providing details on the dynamical, microphysical, and environmental structure, characteristics and development of this intense storm. Cloud-to-ground lightning location data from Vaisala's long range lightning detection network were also acquired and displayed in real-time along with electric fields measured at the aircraft. These data and associated display also supported aircraft guidance and vectoring during the mission. During the observing period, flash rates in excess of 3 to 5 flashes per minute, as well as large electric field and field change values were observed as the storm appeared to undergo periods of intensification, especially in the northwest quadrant in the core eyewall regions. This is in contrast to most hurricanes that tend to be characterized by weak electrification and little or no lightning activity except in the outer rain bands. It should be noted that this storm also had significant lightning associated with its rain bands.

Bio-inspired nanocatalysts for the oxygen reduction reaction.

PubMed

Grumelli, Doris; Wurster, Benjamin; Stepanow, Sebastian; Kern, Klaus

2013-01-01

Electrochemical conversions at fuel cell electrodes are complex processes. In particular, the oxygen reduction reaction has substantial overpotential limiting the electrical power output efficiency. Effective and inexpensive catalytic interfaces are therefore essential for increased performance. Taking inspiration from enzymes, earth-abundant metal centres embedded in organic environments present remarkable catalytic active sites. Here we show that these enzyme-inspired centres can be effectively mimicked in two-dimensional metal-organic coordination networks self-assembled on electrode surfaces. Networks consisting of trimesic acid and bis-pyridyl-bispyrimidine coordinating to single iron and manganese atoms on Au(111) effectively catalyse the oxygen reduction and reveal distinctive catalytic activity in alkaline media. These results demonstrate the potential of surface-engineered metal-organic networks for electrocatalytic conversions. Specifically designed coordination complexes at surfaces inspired by enzyme cofactors represent a new class of nanocatalysts with promising applications in electrocatalysis.

Multicellular automaticity of cardiac cell monolayers: effects of density and spatial distribution of pacemaker cells

NASA Astrophysics Data System (ADS)

Elber Duverger, James; Boudreau-Béland, Jonathan; Le, Minh Duc; Comtois, Philippe

2014-11-01

Self-organization of pacemaker (PM) activity of interconnected elements is important to the general theory of reaction-diffusion systems as well as for applications such as PM activity in cardiac tissue to initiate beating of the heart. Monolayer cultures of neonatal rat ventricular myocytes (NRVMs) are often used as experimental models in studies on cardiac electrophysiology. These monolayers exhibit automaticity (spontaneous activation) of their electrical activity. At low plated density, cells usually show a heterogeneous population consisting of PM and quiescent excitable cells (QECs). It is therefore highly probable that monolayers of NRVMs consist of a heterogeneous network of the two cell types. However, the effects of density and spatial distribution of the PM cells on spontaneous activity of monolayers remain unknown. Thus, a simple stochastic pattern formation algorithm was implemented to distribute PM and QECs in a binary-like 2D network. A FitzHugh-Nagumo excitable medium was used to simulate electrical spontaneous and propagating activity. Simulations showed a clear nonlinear dependency of spontaneous activity (occurrence and amplitude of spontaneous period) on the spatial patterns of PM cells. In most simulations, the first initiation sites were found to be located near the substrate boundaries. Comparison with experimental data obtained from cardiomyocyte monolayers shows important similarities in the position of initiation site activity. However, limitations in the model that do not reflect the complex beat-to-beat variation found in experiments indicate the need for a more realistic cardiomyocyte representation.

Improved actuation strain of PDMS-based DEA materials chemically modified with softening agents

NASA Astrophysics Data System (ADS)

Biedermann, Miriam; Blümke, Martin; Wegener, Michael; Krüger, Hartmut

2015-04-01

Dielectric elastomer actuators (DEAs) are smart materials that gained much in interest particularly in recent years. One active field of research is the improvement of their properties by modification of their structural framework. The object of this work is to improve the actuation properties of polydimethylsiloxane (PDMS)-based DEAs by covalent incorporation of mono-vinyl-terminated low-molecular PDMS chains into the PDMS network. These low-molecular units act as a kind of softener within the PDMS network. The loose chain ends interfere with the network formation and lower the network's density. PDMS films with up to 50wt% of low-molecular PDMS additives were manufactured and the chemical, mechanical, electrical, and electromechanical properties of these novel materials were investigated.

Settlement of reactive power compensation in the light of white certificates

NASA Astrophysics Data System (ADS)

Zajkowski, Konrad

2017-10-01

The article discusses the problem of the determination of savings on active energy as a result of a reactive power compensation. Statutory guidance on the required energy audit to obtain white certificates in the European Union was followed. The analysis was made on the basis of the Polish Law. The paper presents a detailed analytical method and an estimation method taking into account the impact on the line, the transformer and the generator. According to the relevant guidelines in the European Union, the reduction of CO2 emissions by calculating the saving of active power should be determined. The detailed method and an estimation method proposed for the determination of savings on active energy as a result of the reactive power compensation carried out possess some errors and inconvenience. The detailed method requires knowledge of the network topology and a determination of reactive power Q at each point of the network. The estimation method of analysis is easy in execution, especially if the consumer of energy is the main or the most significant purchaser of electricity in the network. Unfortunately, this latter method can be used only for activities that do not require high computational accuracy. The results obtained by this method are approximate values that can be used for the calculation of economic indicators. The estimation method is suitable for determining the number of white certificates when a power audit concerns a recipient of electricity, the structure of which is a large number of divisions scattered at many different locations in the power system.

Within-Day Recharge of Plug-In Hybrid Electric Vehicles: Energy Impact of Public Charging Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Jing; Lin, Zhenhong

2012-01-01

This paper studies the role of public charging infrastructure in increasing PHEV s share of driving on electricity and the resulting petroleum use reduction. Using vehicle activity data obtained from the GPS-tracking household travel survey in Austin, Texas, gasoline and electricity consumptions of PHEVs in real world driving context are estimated. Driver s within-day recharging behavior, constrained by travel activities and public charger network, is modeled as a boundedly rational decision and incorporated in the energy use estimation. The key findings from the Austin dataset include: (1) public charging infrastructure makes PHEV a competitive vehicle choice for consumers without amore » home charger; (2) providing sufficient public charging service is expected to significantly reduce petroleum consumption of PHEVs; and (3) public charging opportunities offer greater benefits for PHEVs with a smaller battery pack, as within-day recharges compensate battery capacity.« less

Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans

PubMed Central

Devauchelle, Anne-Dominique; Béranger, Benoît; Tallon-Baudry, Catherine

2018-01-01

Resting-state networks offer a unique window into the brain’s functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics. PMID:29561263

Magneto-electric nano-particles for non-invasive brain stimulation.

PubMed

Yue, Kun; Guduru, Rakesh; Hong, Jeongmin; Liang, Ping; Nair, Madhavan; Khizroev, Sakhrat

2012-01-01

This paper for the first time discusses a computational study of using magneto-electric (ME) nanoparticles to artificially stimulate the neural activity deep in the brain. The new technology provides a unique way to couple electric signals in the neural network to the magnetic dipoles in the nanoparticles with the purpose to enable a non-invasive approach. Simulations of the effect of ME nanoparticles for non-invasively stimulating the brain of a patient with Parkinson's Disease to bring the pulsed sequences of the electric field to the levels comparable to those of healthy people show that the optimized values for the concentration of the 20-nm nanoparticles (with the magneto-electric (ME) coefficient of 100 V cm(-1) Oe(-1) in the aqueous solution) is 3 × 10(6) particles/cc, and the frequency of the externally applied 300-Oe magnetic field is 80 Hz.

Swelling characteristics of acrylic acid polyelectrolyte hydrogel in a dc electric field

NASA Astrophysics Data System (ADS)

Jabbari, Esmaiel; Tavakoli, Javad; Sarvestani, Alireza S.

2007-10-01

A novel application of environmentally sensitive polyelectrolytes is in the fabrication of BioMEMS devices as sensors and actuators. Poly(acrylic acid) (PAA) gels are anionic polyelectrolyte networks that exhibit volume expansion in aqueous physiological environments. When an electric field is applied to PAA polyelectrolyte gels, the fixed anionic polyelectrolyte charges and the requirement of electro-neutrality in the network generate an osmotic pressure, above that in the absence of the electric field, to expand the network. The objective of this research was to investigate the effect of an externally applied dc electric field on the volume expansion of the PAA polyelectrolyte gel in a simulated physiological solution of phosphate buffer saline (PBS). For swelling studies in the electric field, two platinum-coated plates, as electrodes, were wrapped in a polyethylene sheet to protect the plates from corrosion and placed vertically in a vessel filled with PBS. The plates were placed on a rail such that the distance between the two plates could be adjusted. The PAA gel was synthesized by free radical crosslinking of acrylic acid monomer with ethylene glycol dimethacrylate (EGDMA) crosslinker. Our results demonstrate that volume expansion depends on the intensity of the electric field, the PAA network density, network homogeneity, and the position of the gel in the field relative to positive/negative electrodes. Our model predictions for PAA volume expansion, based on the dilute electrolyte concentration in the gel network, is in excellent agreement with the experimental findings in the high-electric-field regime (250-300 Newton/Coulomb).

Further Evaluation of DNT Hazard Screening using Neural Networks from Rat Cortical Neurons on Multi-well Microelectrode Arrays

EPA Science Inventory

Thousands of chemicals have not been characterized for their DNT potential. Due to the need for DNT hazard identification, efforts to develop screening assays for DNT potential is a high priority. Multi-well microelectrode arrays (MEA) measure the spontaneous activity of electr...

Atmospheric electricity/meteorology analysis

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard; Buechler, Dennis

1993-01-01

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies.

Localized electrical stimulation of in vitro neurons using an array of sub-cellular sized electrodes.

PubMed

Braeken, Dries; Huys, Roeland; Loo, Josine; Bartic, Carmen; Borghs, Gustaaf; Callewaert, Geert; Eberle, Wolfgang

2010-12-15

The investigation of single-neuron parameters is of great interest because many aspects in the behavior and communication of neuronal networks still remain unidentified. However, the present available techniques for single-cell measurements are slow and do not allow for a high-throughput approach. We present here a CMOS compatible microelectrode array with 84 electrodes (with diameters ranging from 1.2 to 4.2 μm) that are smaller than the size of cell, thereby supporting single-cell addressability. We show controllable electroporation of a single cell by an underlying electrode while monitoring changes in the intracellular membrane potential. Further, by applying a localized electrical field between two electrodes close to a neuron while recording changes in the intracellular calcium concentration, we demonstrate activation of a single cell (∼270%, DF/F(0)), followed by a network response of the neighboring cells. The technology can be easily scaled up to larger electrode arrays (theoretically up to 137,000 electrodes/mm(2)) with active CMOS electronics integration able to perform high-throughput measurements on single cells. Copyright © 2010 Elsevier B.V. All rights reserved.

Memory scrutinized through electrical brain stimulation: A review of 80 years of experiential phenomena.

PubMed

Curot, Jonathan; Busigny, Thomas; Valton, Luc; Denuelle, Marie; Vignal, Jean-Pierre; Maillard, Louis; Chauvel, Patrick; Pariente, Jérémie; Trebuchon, Agnès; Bartolomei, Fabrice; Barbeau, Emmanuel J

2017-07-01

Electrical brain stimulations (EBS) sometimes induce reminiscences, but it is largely unknown what type of memories they can trigger. We reviewed 80 years of literature on reminiscences induced by EBS and added our own database. We classified them according to modern conceptions of memory. We observed a surprisingly large variety of reminiscences covering all aspects of declarative memory. However, most were poorly detailed and only a few were episodic. This result does not support theories of a highly stable and detailed memory, as initially postulated, and still widely believed as true by the general public. Moreover, memory networks could only be activated by some of their nodes: 94.1% of EBS were temporal, although the parietal and frontal lobes, also involved in memory networks, were stimulated. The qualitative nature of memories largely depended on the site of stimulation: EBS to rhinal cortex mostly induced personal semantic reminiscences, while only hippocampal EBS induced episodic memories. This result supports the view that EBS can activate memory in predictable ways in humans. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks.

PubMed

de Araújo, Paulo Régis C; Filho, Raimir Holanda; Rodrigues, Joel J P C; Oliveira, João P C M; Braga, Stephanie A

2018-04-24

At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks

PubMed Central

de Araújo, Paulo Régis C.; Filho, Raimir Holanda; Oliveira, João P. C. M.; Braga, Stephanie A.

2018-01-01

At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations. PMID:29695099

Monitoring the development of volcanic eruptions through volcanic lightning - Using a lightning mapping array, seismic and infrasound array, and visual plume analysis

NASA Astrophysics Data System (ADS)

Smith, C. M.; Thompson, G.; McNutt, S. R.; Behnke, S. A.; Edens, H. E.; Van Eaton, A. R.; Gaudin, D.; Thomas, R. J.

2017-12-01

The period of 28 May - 7 June 2015 at Sakurajima Volcano, Japan witnessed a multitude of Vulcanian eruptive events, which resulted in plumes reaching 500-3000m above the vent. These plumes varied from white, gas-rich plumes to dark grey and black ash-rich plumes, and were recorded on lowlight and infrared cameras. A nine-station lightning mapping array (LMA) was deployed to locate sources of VHF (67-73 MHz) radiation produced by lightning flashes and other types of electrical activity such as `continuous RF (radio frequency)'. Two Nanometrics Trillium broadband seismometers and six BSU infrasound sensors were deployed. Over this ten day period we recorded 1556 events that consisted of both seismic and infrasound signals, indicating explosive activity. There are an additional 1222 events that were recorded as only seismic or infrasound signals, which may be a result of precursory seismic signals or noise contamination. Plume discharge types included both distinct lightning flashes and `continuous RF'. The LMA ran continuously for the duration of the experiment. On 30 May 2015 at least seven lightning flashes were also detected by the Vaisala Global Lightning Detection 360 network, which detects VLF (3-30 kHz) radiation. However the University of Washington's World Wide Lightning Location Network, which also detects VLF radiation, detected no volcanic lightning flashes in this time period. This indicates that the electrical activity in Sakurajima's plume occurs near the lower limits of the VLF detection threshold. We investigate relationships between the plume dynamics, the geophysical signal and the corresponding electrical activity through: plume velocity and height; event waveform cross-correlation; volcano acoustic-seismic ratios; overall geophysical energy; RSAM records; and VHF sources detected by the LMA. By investigating these relationships we hope to determine the seismic/infrasound energy threshold required to generate measurable electrical activity. Seismic and infrasound are two of the most common volcanic monitoring methods. By developing the relationships between plume electrification and these geophysical methods we hope to expand the use of lightning for active volcano monitoring.

Time series prediction in the case of nonlinear loads by using ADALINE and NAR neural networks

NASA Astrophysics Data System (ADS)

Ghiormez, L.; Panoiu, M.; Panoiu, C.; Tirian, O.

2018-01-01

This paper presents a study regarding the time series prediction in the case of an electric arc furnace. The considered furnace is a three phase load and it is used to melt scrap in order to obtain liquid steel. The furnace is powered by a three-phase electrical supply and therefore has three graphite electrodes. The furnace is a nonlinear load that can influence the equipment connected to the same electrical power supply network. The nonlinearity is given by the electric arc that appears at the furnace between the graphite electrode and the scrap. Because of the disturbances caused by the electric arc furnace during the elaboration process of steel it is very useful to predict the current of the electric arc and the voltage from the measuring point in the secondary side of the furnace transformer. In order to make the predictions were used ADALINE and NAR neural networks. To train the networks and to make the predictions were used data acquired from the real technological plant.

Functional connectivity and dynamics of cortical-thalamic networks co-cultured in a dual compartment device

NASA Astrophysics Data System (ADS)

Kanagasabapathi, Thirukumaran T.; Massobrio, Paolo; Barone, Rocco Andrea; Tedesco, Mariateresa; Martinoia, Sergio; Wadman, Wytse J.; Decré, Michel M. J.

2012-06-01

Co-cultures containing dissociated cortical and thalamic cells may provide a unique model for understanding the pathophysiology in the respective neuronal sub-circuitry. In addition, developing an in vitro dissociated co-culture model offers the possibility of studying the system without influence from other neuronal sub-populations. Here we demonstrate a dual compartment system coupled to microelectrode arrays (MEAs) for co-culturing and recording spontaneous activities from neuronal sub-populations. Propagation of electrical activities between cortical and thalamic regions and their interdependence in connectivity is verified by means of a cross-correlation algorithm. We found that burst events originate in the cortical region and drive the entire cortical-thalamic network bursting behavior while mutually weak thalamic connections play a relevant role in sustaining longer burst events in cortical cells. To support these experimental findings, a neuronal network model was developed and used to investigate the interplay between network dynamics and connectivity in the cortical-thalamic system.

Macroscopic and microscopic spectral properties of brain networks during local and global synchronization

NASA Astrophysics Data System (ADS)

Maksimenko, Vladimir A.; Lüttjohann, Annika; Makarov, Vladimir V.; Goremyko, Mikhail V.; Koronovskii, Alexey A.; Nedaivozov, Vladimir; Runnova, Anastasia E.; van Luijtelaar, Gilles; Hramov, Alexander E.; Boccaletti, Stefano

2017-07-01

We introduce a practical and computationally not demanding technique for inferring interactions at various microscopic levels between the units of a network from the measurements and the processing of macroscopic signals. Starting from a network model of Kuramoto phase oscillators, which evolve adaptively according to homophilic and homeostatic adaptive principles, we give evidence that the increase of synchronization within groups of nodes (and the corresponding formation of synchronous clusters) causes also the defragmentation of the wavelet energy spectrum of the macroscopic signal. Our methodology is then applied to getting a glance into the microscopic interactions occurring in a neurophysiological system, namely, in the thalamocortical neural network of an epileptic brain of a rat, where the group electrical activity is registered by means of multichannel EEG. We demonstrate that it is possible to infer the degree of interaction between the interconnected regions of the brain during different types of brain activities and to estimate the regions' participation in the generation of the different levels of consciousness.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barone, C., E-mail: cbarone@unisa.it; Mauro, C.; Pagano, S.

Carbon nanotubes added to polymer and epoxy matrices are compounds of interest for applications in electronics and aerospace. The realization of high-performance devices based on these materials can profit from the investigation of their electric noise properties, as this gives a more detailed insight of the basic charge carriers transport mechanisms at work. The dc and electrical noise characteristics of different polymer/carbon nanotubes composites have been analyzed from 10 to 300 K. The results suggest that all these systems can be regarded as random resistive networks of tunnel junctions formed by adjacent carbon nanotubes. However, in the high-temperature regime, contributions derivingmore » from other possible mechanisms cannot be separated using dc information alone. A transition from a fluctuation-induced tunneling process to a thermally activated regime is instead revealed by electric noise spectroscopy. In particular, a crossover is found from a two-level tunneling mechanism, operating at low temperatures, to resistance fluctuations of a percolative network, in the high-temperature region. The observed behavior of 1/f noise seems to be a general feature for highly conductive samples, independent on the type of polymer matrix and on the nanotube density.« less

Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity.

PubMed

Han, Fang; Wiercigroch, Marian; Fang, Jian-An; Wang, Zhijie

2011-10-01

Excitement and synchronization of electrically and chemically coupled Newman-Watts (NW) small-world neuronal networks with a short-term synaptic plasticity described by a modified Oja learning rule are investigated. For each type of neuronal network, the variation properties of synaptic weights are examined first. Then the effects of the learning rate, the coupling strength and the shortcut-adding probability on excitement and synchronization of the neuronal network are studied. It is shown that the synaptic learning suppresses the over-excitement, helps synchronization for the electrically coupled network but impairs synchronization for the chemically coupled one. Both the introduction of shortcuts and the increase of the coupling strength improve synchronization and they are helpful in increasing the excitement for the chemically coupled network, but have little effect on the excitement of the electrically coupled one.

Reconfigurable engineered motile semiconductor microparticles.

PubMed

Ohiri, Ugonna; Shields, C Wyatt; Han, Koohee; Tyler, Talmage; Velev, Orlin D; Jokerst, Nan

2018-05-03

Locally energized particles form the basis for emerging classes of active matter. The design of active particles has led to their controlled locomotion and assembly. The next generation of particles should demonstrate robust control over their active assembly, disassembly, and reconfiguration. Here we introduce a class of semiconductor microparticles that can be comprehensively designed (in size, shape, electric polarizability, and patterned coatings) using standard microfabrication tools. These custom silicon particles draw energy from external electric fields to actively propel, while interacting hydrodynamically, and sequentially assemble and disassemble on demand. We show that a number of electrokinetic effects, such as dielectrophoresis, induced charge electrophoresis, and diode propulsion, can selectively power the microparticle motions and interactions. The ability to achieve on-demand locomotion, tractable fluid flows, synchronized motility, and reversible assembly using engineered silicon microparticles may enable advanced applications that include remotely powered microsensors, artificial muscles, reconfigurable neural networks and computational systems.

Ergonomics principles to design clothing work for electrical workers in Colombia.

PubMed

Castillo, Juan; Cubillos, A

2012-01-01

The recent development of the Colombian legislation, have been identified the need to develop protective clothing to work according to specifications from the work done and in compliance with international standards. These involve the development and design of new strategies and measures for work clothing design. In this study we analyzes the activities of the workers in the electrical sector, the method analyzes the risks activity data in various activities, that activities include power generation plants, local facilities, industrial facilities and maintenance of urban and rural networks. The analyses method is focused on ergonomic approach, risk analysis is done, we evaluate the role of security expert and we use a design algorithm developed for this purpose. The result of this study is the identification of constraints and variables that contribute to the development of a model of analysis that leads to the development the work protective clothes.

Social representations of electricity network technologies: exploring processes of anchoring and objectification through the use of visual research methods.

PubMed

Devine-Wright, Hannah; Devine-Wright, Patrick

2009-06-01

The aim of this study was to explore everyday thinking about the UK electricity network, in light of government policy to increase the generation of electricity from renewable energy sources. Existing literature on public perceptions of electricity network technologies was broadened by adopting a more socially embedded conception of the construction of knowledge using the theory of social representations (SRT) to explore symbolic associations with network technologies. Drawing and association tasks were administered within nine discussion groups held in two places: a Scottish town where significant upgrades to the local transmission network were planned and an English city with no such plans. Our results illustrate the ways in which network technologies, such as high voltage (HV) pylons, are objectified in talk and drawings. These invoked positive as well as negative symbolic and affective associations, both at the level of specific pylons, and the 'National Grid' as a whole and are anchored in understanding of other networks such as mobile telecommunications. We conclude that visual methods are especially useful for exploring beliefs about technologies that are widespread, proximal to our everyday experience but nevertheless unfamiliar topics of everyday conversation.

Label-free optical detection of action potential in mammalian neurons (Conference Presentation)

NASA Astrophysics Data System (ADS)

Batabyal, Subrata; Satpathy, Sarmishtha; Bui, Loan; Kim, Young-Tae; Mohanty, Samarendra K.; Davé, Digant P.

2017-02-01

Electrophysiology techniques are the gold standard in neuroscience for studying functionality of a single neuron to a complex neuronal network. However, electrophysiology techniques are not flawless, they are invasive nature, procedures are cumbersome to implement with limited capability of being used as a high-throughput recording system. Also, long term studies of neuronal functionality with aid of electrophysiology is not feasible. Non-invasive stimulation and detection of neuronal electrical activity has been a long standing goal in neuroscience. Introduction of optogenetics has ushered in the era of non-invasive optical stimulation of neurons, which is revolutionizing neuroscience research. Optical detection of neuronal activity that is comparable to electro-physiology is still elusive. A number of optical techniques have been reported recording of neuronal electrical activity but none is capable of reliably measuring action potential spikes that is comparable to electro-physiology. Optical detection of action potential with voltage sensitive fluorescent reporters are potential alternatives to electrophysiology techniques. The heavily rely on secondary reporters, which are often toxic in nature with background fluorescence, with slow response and low SNR making them far from ideal. The detection of one shot (without averaging)-single action potential in a true label-free way has been elusive so far. In this report, we demonstrate the optical detection of single neuronal spike in a cultured mammalian neuronal network without using any exogenous labels. To the best of our knowledge, this is the first demonstration of label free optical detection of single action potentials in a mammalian neuronal network, which was achieved using a high-speed phase sensitive interferometer. We have carried out stimulation and inhibition of neuronal firing using Glutamate and Tetrodotoxin respectively to demonstrate the different outcome (stimulation and inhibition) revealed in optical signal. We hypothesize that the interrogating optical beam is modulated during neuronal firing by electro-motility driven membrane fluctuation in conjunction with electrical wave propagation in cellular system.

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

NASA Astrophysics Data System (ADS)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

Light-weight free-standing carbon nanotube-silicon films for anodes of lithium ion batteries.

PubMed

Cui, Li-Feng; Hu, Liangbing; Choi, Jang Wook; Cui, Yi

2010-07-27

Silicon is an attractive alloy-type anode material because of its highest known capacity (4200 mAh/g). However, lithium insertion into and extraction from silicon are accompanied by a huge volume change, up to 300%, which induces a strong strain on silicon and causes pulverization and rapid capacity fading due to the loss of the electrical contact between part of silicon and current collector. Si nanostructures such as nanowires, which are chemically and electrically bonded to the current collector, can overcome the pulverization problem, however, the heavy metal current collectors in these systems are larger in weight than Si active material. Herein we report a novel anode structure free of heavy metal current collectors by integrating a flexible, conductive carbon nanotube (CNT) network into a Si anode. The composite film is free-standing and has a structure similar to the steel bar reinforced concrete, where the infiltrated CNT network functions as both mechanical support and electrical conductor and Si as a high capacity anode material for Li-ion battery. Such free-standing film has a low sheet resistance of approximately 30 Ohm/sq. It shows a high specific charge storage capacity (approximately 2000 mAh/g) and a good cycling life, superior to pure sputtered-on silicon films with similar thicknesses. Scanning electron micrographs show that Si is still connected by the CNT network even when small breaking or cracks appear in the film after cycling. The film can also "ripple up" to release the strain of a large volume change during lithium intercalation. The conductive composite film can function as both anode active material and current collector. It offers approximately 10 times improvement in specific capacity compared with widely used graphite/copper anode sheets.

Self-organizing intelligent network of smart electrical heating devices as an alternative to traditional ways of heating

NASA Astrophysics Data System (ADS)

Zaslavsky, Aleksander M.; Tkachov, Viktor V.; Protsenko, Stanislav M.; Bublikov, Andrii V.; Suleimenov, Batyrbek; Orshubekov, Nurbek; Gromaszek, Konrad

2017-08-01

The paper considers the problem of automated decentralized distribution of the electric energy among unlimited-power electric heaters providing the given temperature distribution within the zones of monitored object heating in the context of maximum use of electric power which limiting level is time-dependent randomly. Principles of collective selforganization automata for solving the problem are analyzed. It has been shown that after all the automata make decision, equilibrium of Nash type is attained when unused power within the electric network is not more than a power of any non-energized electric heater.

Ecohydrologic Investigations of Shallow Lateral Subsurface Flow in Tropical Soils using Time-Lapse Surface Electrical Resistivity Tomography

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Mojica, A.; Abebe, N. A.; Smithsonian Tropical Research Institute, Panama Canal Watershed Experiment, Agua Salud Project

2010-12-01

The hydrologic effects of deforestation and aforestation in the tropics remain an area of active research. Hydrologic predictions of land-use change effects remain elusive. One of the unique features of catchment hydrology in the tropics is the effect of intense, continuous biological activity by insects, shrubs, trees, and small mammals. Sapprolitic soils derived from weathered bedrock cover widespread areas. These soils have low matrix permeabilities on the order of 1 mm/h, are 10 to 20 m in thickness and have relatively low activity because they have been depleted of light cations by annual rainfall over 2000 mm. As part of the Smithsonian Tropical Research Institute, Panama Canal Watershed Experiment, Agua Salud Project, we have observed shallow subsurface flow in tropical soils in central Panama using an introduced salinity contrast and surface electrical resistivity tomography (ERT). In 2009 and 2010, experiments were conducted in a 30 year-old secondary succession forest, and in two former pasture sites that were planted with native timber species and teak, respectively, in 2008. At each site, saline water (NaCl tagged with LiBr) was introduced to the soil using two different methods: soil pits and ponded surface applications. Results showed the strongest response in the case of ponded surface applications with observed changes in resistivity between -50% and 50%. In soil pit applications, the change in electrical resistivity varied from -10% to 10%. Results suggest that in the case of surface application, a transient perched water table is created near the bottom of the bioturbation layer that activates the downslope macropore network and results in bulk flow velocities that are significantly higher than observed soil matrix permeabilities. When heavy rainfall occurred during tests, increased mobility of the salinity contrast more clearly showed the active layer where most flow occurred. Time-series ERT observations enabled measurements of downslope bulk flow velocities over 1 m/h, presumably due to the existing downslope macroporosity network. These observations are being used to estimate macroporosity network properties and constrain hydrologic model parameters in different land uses. These results show that these non-invasive tests are a useful tool to determine the distribution of downslope lateral flow generated from pit and surface-applied saline solutions. ERT experimental results from a hillslope-scale experiment in central Panama, showing change in electrical conductivity from 30-minutes to 330-minutes after continuous injection of salinity contrast at x=0.

Modelling the Effects of Electrical Coupling between Unmyelinated Axons of Brainstem Neurons Controlling Rhythmic Activity

PubMed Central

Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan

2015-01-01

Gap junctions between fine unmyelinated axons can electrically couple groups of brain neurons to synchronise firing and contribute to rhythmic activity. To explore the distribution and significance of electrical coupling, we modelled a well analysed, small population of brainstem neurons which drive swimming in young frog tadpoles. A passive network of 30 multicompartmental neurons with unmyelinated axons was used to infer that: axon-axon gap junctions close to the soma gave the best match to experimentally measured coupling coefficients; axon diameter had a strong influence on coupling; most neurons were coupled indirectly via the axons of other neurons. When active channels were added, gap junctions could make action potential propagation along the thin axons unreliable. Increased sodium and decreased potassium channel densities in the initial axon segment improved action potential propagation. Modelling suggested that the single spike firing to step current injection observed in whole-cell recordings is not a cellular property but a dynamic consequence of shunting resulting from electrical coupling. Without electrical coupling, firing of the population during depolarising current was unsynchronised; with coupling, the population showed synchronous recruitment and rhythmic firing. When activated instead by increasing levels of modelled sensory pathway input, the population without electrical coupling was recruited incrementally to unpatterned activity. However, when coupled, the population was recruited all-or-none at threshold into a rhythmic swimming pattern: the tadpole “decided” to swim. Modelling emphasises uncertainties about fine unmyelinated axon physiology but, when informed by biological data, makes general predictions about gap junctions: locations close to the soma; relatively small numbers; many indirect connections between neurons; cause of action potential propagation failure in fine axons; misleading alteration of intrinsic firing properties. Modelling also indicates that electrical coupling within a population can synchronize recruitment of neurons and their pacemaker firing during rhythmic activity. PMID:25954930

Statistical patterns in the location of natural lightning

NASA Astrophysics Data System (ADS)

Zoghzoghy, F. G.; Cohen, M. B.; Said, R. K.; Inan, U. S.

2013-01-01

Lightning discharges are nature's way of neutralizing the electrical buildup in thunderclouds. Thus, if an individual discharge destroys a substantial fraction of the cloud charge, the probability of a subsequent flash is reduced until the cloud charge separation rebuilds. The temporal pattern of lightning activity in a localized region may thus inherently be a proxy measure of the corresponding timescales for charge separation and electric field buildup processes. We present a statistical technique to bring out this effect (as well as the subsequent recovery) using lightning geo-location data, in this case with data from the National Lightning Detection Network (NLDN) and from the GLD360 Network. We use this statistical method to show that a lightning flash can remove an appreciable fraction of the built up charge, affecting the neighboring lightning activity for tens of seconds within a ˜ 10 km radius. We find that our results correlate with timescales of electric field buildup in storms and suggest that the proposed statistical tool could be used to study the electrification of storms on a global scale. We find that this flash suppression effect is a strong function of flash type, flash polarity, cloud-to-ground flash multiplicity, the geographic location of lightning, and is proportional to NLDN model-derived peak stroke current. We characterize the spatial and temporal extent of the suppression effect as a function of these parameters and discuss various applications of our findings.

Understanding Actions of Others: The Electrodynamics of the Left and Right Hemispheres. A High-Density EEG Neuroimaging Study

PubMed Central

Ortigue, Stephanie; Sinigaglia, Corrado; Rizzolatti, Giacomo; Grafton, Scott T.

2010-01-01

Background When we observe an individual performing a motor act (e.g. grasping a cup) we get two types of information on the basis of how the motor act is done and the context: what the agent is doing (i.e. grasping) and the intention underlying it (i.e. grasping for drinking). Here we examined the temporal dynamics of the brain activations that follow the observation of a motor act and underlie the observer's capacity to understand what the agent is doing and why. Methodology/Principal Findings Volunteers were presented with two-frame video-clips. The first frame (T0) showed an object with or without context; the second frame (T1) showed a hand interacting with the object. The volunteers were instructed to understand the intention of the observed actions while their brain activity was recorded with a high-density 128-channel EEG system. Visual event-related potentials (VEPs) were recorded time-locked with the frame showing the hand-object interaction (T1). The data were analyzed by using electrical neuroimaging, which combines a cluster analysis performed on the group-averaged VEPs with the localization of the cortical sources that give rise to different spatio-temporal states of the global electrical field. Electrical neuroimaging results revealed four major steps: 1) bilateral posterior cortical activations; 2) a strong activation of the left posterior temporal and inferior parietal cortices with almost a complete disappearance of activations in the right hemisphere; 3) a significant increase of the activations of the right temporo-parietal region with simultaneously co-active left hemispheric sources, and 4) a significant global decrease of cortical activity accompanied by the appearance of activation of the orbito-frontal cortex. Conclusions/Significance We conclude that the early striking left hemisphere involvement is due to the activation of a lateralized action-observation/action execution network. The activation of this lateralized network mediates the understanding of the goal of object-directed motor acts (mirror mechanism). The successive right hemisphere activation indicates that this hemisphere plays an important role in understanding the intention of others. PMID:20730095

Resting state electrical brain activity and connectivity in fibromyalgia

PubMed Central

Vanneste, Sven; Ost, Jan; Van Havenbergh, Tony; De Ridder, Dirk

2017-01-01

The exact mechanism underlying fibromyalgia is unknown, but increased facilitatory modulation and/or dysfunctional descending inhibitory pathway activity are posited as possible mechanisms contributing to sensitization of the central nervous system. The primary goal of this study is to identify a fibromyalgia neural circuit that can account for these abnormalities in central pain. The second goal is to gain a better understanding of the functional connectivity between the default and the executive attention network (salience network plus dorsal lateral prefrontal cortex) in fibromyalgia. We examine neural activity associated with fibromyalgia (N = 44) and compare these with healthy controls (N = 44) using resting state source localized EEG. Our data support an important role of the pregenual anterior cingulate cortex but also suggest that the degree of activation and the degree of integration between different brain areas is important. The inhibition of the connectivity between the dorsal lateral prefrontal cortex and the posterior cingulate cortex on the pain inhibitory pathway seems to be limited by decreased functional connectivity with the pregenual anterior cingulate cortex. Our data highlight the functional dynamics of brain regions integrated in brain networks in fibromyalgia patients. PMID:28650974

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)

Nanoscale Control over the Mixing Behavior of Surface-Confined Bicomponent Supramolecular Networks Using an Oriented External Electric Field

PubMed Central

2017-01-01

Strong electric fields are known to influence the properties of molecules as well as materials. Here we show that by changing the orientation of an externally applied electric field, one can locally control the mixing behavior of two molecules physisorbed on a solid surface. Whether the starting two-component network evolves into an ordered two-dimensional (2D) cocrystal, yields an amorphous network where the two components phase separate, or shows preferential adsorption of only one component depends on the solution stoichiometry. The experiments are carried out by changing the orientation of the strong electric field that exists between the tip of a scanning tunneling microscope and a solid substrate. The structure of the two-component network typically changes from open porous at negative substrate bias to relatively compact when the polarity of the applied bias is reversed. The electric-field-induced mixing behavior is reversible, and the supramolecular system exhibits excellent stability and good response efficiency. When molecular guests are adsorbed in the porous networks, the field-induced switching behavior was found to be completely different. Plausible reasons behind the field-induced mixing behavior are discussed. PMID:29112378

Synchronization behaviors of coupled neurons under electromagnetic radiation

NASA Astrophysics Data System (ADS)

Ma, Jun; Wu, Fuqiang; Wang, Chunni

2017-01-01

Based on an improved neuronal model, in which the effect of magnetic flux is considered during the fluctuation and change of ion concentration in cells, the transition of synchronization is investigated by imposing external electromagnetic radiation on the coupled neurons, and networks, respectively. It is found that the synchronization degree depends on the coupling intensity and the intensity of external electromagnetic radiation. Indeed, appropriate intensity of electromagnetic radiation could be effective to realize intermittent synchronization, while stronger intensity of electromagnetic radiation can induce disorder of coupled neurons and network. Neurons show rhythm synchronization in the electrical activities by increasing the coupling intensity under electromagnetic radiation, and spatial patterns can be formed in the network under smaller factor of synchronization.

Robert Hare's Theory of Galvanism: A Study of Heat and Electricity in Early Nineteenth-Century American Chemistry.

PubMed

Fisher, Amy

2018-04-09

As a professor of chemistry at the University of Pennsylvania, Robert Hare actively shaped early American science. He participated in a large network of scholars, including Joseph Henry, François Arago, and Jacob Berzelius, and experimented with and wrote extensively about electricity and its associated chemical and thermal phenomena. In the early nineteenth century, prominent chemists such as Berzelius and Humphry Davy proclaimed that a revolution had occurred in chemistry through electrical research. Examining Robert Hare's contributions to this discourse, this paper analyzes how Hare's study of electricity and the caloric theory of heat led him to propose a new theory of galvanism. It also examines the reception of Hare's work in America and Great Britain, highlighting the contributions of early American chemists to the development of electrochemistry.

A novel environmental chamber for neuronal network multisite recordings.

PubMed

Biffi, E; Regalia, G; Ghezzi, D; De Ceglia, R; Menegon, A; Ferrigno, G; Fiore, G B; Pedrocchi, A

2012-10-01

Environmental stability is a critical issue for neuronal networks in vitro. Hence, the ability to control the physical and chemical environment of cell cultures during electrophysiological measurements is an important requirement in the experimental design. In this work, we describe the development and the experimental verification of a closed chamber for multisite electrophysiology and optical monitoring. The chamber provides stable temperature, pH and humidity and guarantees cell viability comparable to standard incubators. Besides, it integrates the electronics for long-term neuronal activity recording. The system is portable and adaptable for multiple network housings, which allows performing parallel experiments in the same environment. Our results show that this device can be a solution for long-term electrophysiology, for dual network experiments and for coupled optical and electrical measurements. Copyright © 2012 Wiley Periodicals, Inc.

Evaluating the electricity intensity of evolving water supply mixes: the case of California’s water network

NASA Astrophysics Data System (ADS)

Stokes-Draut, Jennifer; Taptich, Michael; Kavvada, Olga; Horvath, Arpad

2017-11-01

Climate change is making water supply less predictable, even unreliable, in parts of the world. Urban water providers, especially in already arid areas, will need to diversify their water resources by switching to alternative sources and negotiating trading agreements to create more resilient and interdependent networks. The increasing complexity of these networks will likely require more operational electricity. The ability to document, visualize, and analyze water-energy relationships will be critical to future water planning, especially as data needed to conduct the analyses become increasingly available. We have developed a network model and decision-support tool, WESTNet, to perform these tasks. Herein, WESTNet was used to analyze a model of California’s 2010 urban water network as well as the projected system for 2020 and 2030. Results for California’s ten hydrologic regions show that the average number of water sources per utility and total electricity consumption for supplying water will increase in spite of decreasing per-capita water consumption. Electricity intensity (kWh m-3) will increase in arid regions of the state due to shifts to alternative water sources such as indirect potable water reuse, desalination, and water transfers. In wetter, typically less populated, regions, reduced water demand for electricity-intensive supplies will decrease the electricity intensity of the water supply mix, though total electricity consumption will increase due to urban population growth. The results of this study provide a baseline for comparing current and potential innovations to California’s water system. The WESTNet tool can be applied to diverse water systems in any geographic region at a variety of scales to evaluate an array of network-dependent water-energy parameters.

Electromagnetic compatibility of PLC adapters for in-home/domestic networks

NASA Astrophysics Data System (ADS)

Potisk, Lukas; Hallon, Jozef; Orgon, Milos; Fujdiak, Radek

2018-01-01

The use of programable logic controllers (PLC) technology in electrical networks 230 V causes electromagnetic radiation that interferes with other electrical equipment connected to the network [1-4]. Therefore, this article describes the issues of electromagnetic compatibility (EMC) of new PLC adapters used in IP broadband services in a multi-user environment. The measurements of disturbing electromagnetic field originated in PLC adapters were made in a certified laboratory EMC (laboratory of electromagnetic compatibility) in the Institute of Electrical Engineering at Faculty of Electrical Engineering and Information Technology of the Slovak University of Technology in Bratislava. The measured spectra of the radiated electromagnetic field will be compared with the results obtained when testing older PLC modems [5].

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EPA Pesticide Factsheets

Thousands of compounds in the environment have not been characterized for developmental neurotoxicity (DNT) hazard. To address this issue, methods to screen compounds rapidly for DNT hazard evaluation are necessary and are being developed for key neurodevelopmental processes. In order to develop an assay for network formation, the current study evaluated effects of a training set of chemicals on network ontogeny by measuring spontaneous electrical activity in neural networks grown on microelectrode arrays (MEA). Rat (0-24 h old) primary cortical cells were plated in 48 well MEA plates and exposed to six compounds: acetaminophen, bisindolylmaleimide-1 (Bis-1), domoic acid, mevastatin, sodium orthovanadate, and loperamide for a period of 12 days. Spontaneous network activity was recorded on days 2, 5, 7, 9, and 12 and viability was assessed using the Cell Titer Blue® assay on day 12. Network activity (e.g. mean firing rate (MFR), burst rate (BR), etc), increased between days 5 and 12. Random Forest analysis indicated that across all compounds and times, temporal correlation of firing patterns (r), MFR, BR, #of active electrodes and % of spikes in a burst were the most influential parameters in separating control from treated wells. All compounds except acetaminophen (≤ 30 µM) caused concentration-related effects on one or more of these parameters. Domoic acid and sodium orthovanadate altered several of these parameters in the absence of cytotoxicity. Although

Conductive network formation of carbon nanotubes in elastic polymer microfibers and its effect on the electrical conductance: Experiment and simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, Hyun Woo; Kim, Jeongmin; Sung, Bong June, E-mail: jjpark@chonnam.ac.kr, E-mail: bjsung@sogang.ac.kr

We investigate how the electrical conductance of microfibers (made of polymers and conductive nanofillers) decreases upon uniaxial deformation by performing both experiments and simulations. Even though various elastic conductors have been developed due to promising applications for deformable electronic devices, the mechanism at a molecular level for electrical conductance change has remained elusive. Previous studies proposed that the decrease in electrical conductance would result from changes in either distances or contact numbers between conductive fillers. In this work, we prepare microfibers of single walled carbon nanotubes (SWCNTs)/polyvinyl alcohol composites and investigate the electrical conductance and the orientation of SWCNTs uponmore » uniaxial deformation. We also perform extensive Monte Carlo simulations, which reproduce experimental results for the relative decrease in conductance and the SWCNTs orientation. We investigate the electrical networks of SWCNTs in microfibers and find that the decrease in the electrical conductance upon uniaxial deformation should be attributed to a subtle change in the topological structure of the electrical network.« less

Homeostatic structural plasticity can account for topology changes following deafferentation and focal stroke.

PubMed

Butz, Markus; Steenbuck, Ines D; van Ooyen, Arjen

2014-01-01

After brain lesions caused by tumors or stroke, or after lasting loss of input (deafferentation), inter- and intra-regional brain networks respond with complex changes in topology. Not only areas directly affected by the lesion but also regions remote from the lesion may alter their connectivity-a phenomenon known as diaschisis. Changes in network topology after brain lesions can lead to cognitive decline and increasing functional disability. However, the principles governing changes in network topology are poorly understood. Here, we investigated whether homeostatic structural plasticity can account for changes in network topology after deafferentation and brain lesions. Homeostatic structural plasticity postulates that neurons aim to maintain a desired level of electrical activity by deleting synapses when neuronal activity is too high and by providing new synaptic contacts when activity is too low. Using our Model of Structural Plasticity, we explored how local changes in connectivity induced by a focal loss of input affected global network topology. In accordance with experimental and clinical data, we found that after partial deafferentation, the network as a whole became more random, although it maintained its small-world topology, while deafferentated neurons increased their betweenness centrality as they rewired and returned to the homeostatic range of activity. Furthermore, deafferentated neurons increased their global but decreased their local efficiency and got longer tailed degree distributions, indicating the emergence of hub neurons. Together, our results suggest that homeostatic structural plasticity may be an important driving force for lesion-induced network reorganization and that the increase in betweenness centrality of deafferentated areas may hold as a biomarker for brain repair.

Networks: How Energy Links People, Goods and Services, Grades 4, 5. Interdisciplinary Student/Teacher Materials in Energy, the Environment, and the Economy.

ERIC Educational Resources Information Center

Johnson, Bette; Swinton, Olivia

The purpose of this unit is to investigate a simple energy network and to make an analogy with similar mutually supporting networks in the natural and man-made worlds. The lessons in this unit develop the network idea around a simple electrical distribution system that we depend on and also into further consideration of electrical energy itself.…

Interdisciplinary Student/Teacher Materials in Energy, the Environment, and the Economy. Networks: How Energy Links People, Goods and Services, Grades 4, 5.

ERIC Educational Resources Information Center

Johnson, Bette; Swinton, Olivia

The purpose of this unit is to investigate a simple energy network and to make an analogy with similar mutually supporting networks in the natural and man-made worlds. The lessons in this unit develop the network idea around a simple electrical distribution system that we depend on and also into further consideration of electrical energy itself.…

Micro-economic analysis of the physical constrained markets: game theory application to competitive electricity markets

NASA Astrophysics Data System (ADS)

Bompard, E.; Ma, Y. C.; Ragazzi, E.

2006-03-01

Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower price, leading to higher market efficiency. Electricity markets are pretty different from other commodities mainly due to the physical constraints related to the network structure that may impact the market performance. The network structure of the system on which the economic transactions need to be undertaken poses strict physical and operational constraints. Strategic interactions among producers that game the market with the objective of maximizing their producer surplus must be taken into account when modeling competitive electricity markets. The physical constraints, specific of the electricity markets, provide additional opportunity of gaming to the market players. Game theory provides a tool to model such a context. This paper discussed the application of game theory to physical constrained electricity markets with the goal of providing tools for assessing the market performance and pinpointing the critical network constraints that may impact the market efficiency. The basic models of game theory specifically designed to represent the electricity markets will be presented. IEEE30 bus test system of the constrained electricity market will be discussed to show the network impacts on the market performances in presence of strategic bidding behavior of the producers.

Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadat Hayatshahi, Sayyed Hamed; Abdolmaleki, Parviz; Safarian, Shahrokh

2005-12-16

Logistic regression and artificial neural networks have been developed as two non-linear models to establish quantitative structure-activity relationships between structural descriptors and biochemical activity of adenosine based competitive inhibitors, toward adenosine deaminase. The training set included 24 compounds with known k {sub i} values. The models were trained to solve two-class problems. Unlike the previous work in which multiple linear regression was used, the highest of positive charge on the molecules was recognized to be in close relation with their inhibition activity, while the electric charge on atom N1 of adenosine was found to be a poor descriptor. Consequently, themore » previously developed equation was improved and the newly formed one could predict the class of 91.66% of compounds correctly. Also optimized 2-3-1 and 3-4-1 neural networks could increase this rate to 95.83%.« less

Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits.

PubMed

Wimmer, Klaus; Ramon, Marc; Pasternak, Tatiana; Compte, Albert

2016-01-13

Neuronal activity in the lateral prefrontal cortex (LPFC) reflects the structure and cognitive demands of memory-guided sensory discrimination tasks. However, we still do not know how neuronal activity articulates in network states involved in perceiving, remembering, and comparing sensory information during such tasks. Oscillations in local field potentials (LFPs) provide fingerprints of such network dynamics. Here, we examined LFPs recorded from LPFC of macaques while they compared the directions or the speeds of two moving random-dot patterns, S1 and S2, separated by a delay. LFP activity in the theta, beta, and gamma bands tracked consecutive components of the task. In response to motion stimuli, LFP theta and gamma power increased, and beta power decreased, but showed only weak motion selectivity. In the delay, LFP beta power modulation anticipated the onset of S2 and encoded the task-relevant S1 feature, suggesting network dynamics associated with memory maintenance. After S2 onset the difference between the current stimulus S2 and the remembered S1 was strongly reflected in broadband LFP activity, with an early sensory-related component proportional to stimulus difference and a later choice-related component reflecting the behavioral decision buildup. Our results demonstrate that individual LFP bands reflect both sensory and cognitive processes engaged independently during different stages of the task. This activation pattern suggests that during elementary cognitive tasks, the prefrontal network transitions dynamically between states and that these transitions are characterized by the conjunction of LFP rhythms rather than by single LFP bands. Neurons in the brain communicate through electrical impulses and coordinate this activity in ensembles that pulsate rhythmically, very much like musical instruments in an orchestra. These rhythms change with "brain state," from sleep to waking, but also signal with different oscillation frequencies rapid changes between sensory and cognitive processing. Here, we studied rhythmic electrical activity in the monkey prefrontal cortex, an area implicated in working memory, decision making, and executive control. Monkeys had to identify and remember a visual motion pattern and compare it to a second pattern. We found orderly transitions between rhythmic activity where the same frequency channels were active in all ongoing prefrontal computations. This supports prefrontal circuit dynamics that transitions rapidly between complex rhythmic patterns during structured cognitive tasks. Copyright © 2016 the authors 0270-6474/16/360489-17$15.00/0.

Cerebral energy metabolism and the brain's functional network architecture: an integrative review.

PubMed

Lord, Louis-David; Expert, Paul; Huckins, Jeremy F; Turkheimer, Federico E

2013-09-01

Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.

Ca2+-induced uncoupling of Aplysia bag cell neurons.

PubMed

Dargaei, Zahra; Standage, Dominic; Groten, Christopher J; Blohm, Gunnar; Magoski, Neil S

2015-02-01

Electrical transmission is a dynamically regulated form of communication and key to synchronizing neuronal activity. The bag cell neurons of Aplysia are a group of electrically coupled neuroendocrine cells that initiate ovulation by secreting egg-laying hormone during a prolonged period of synchronous firing called the afterdischarge. Accompanying the afterdischarge is an increase in intracellular Ca2+ and the activation of protein kinase C (PKC). We used whole cell recording from paired cultured bag cell neurons to demonstrate that electrical coupling is regulated by both Ca2+ and PKC. Elevating Ca2+ with a train of voltage steps, mimicking the onset of the afterdischarge, decreased junctional current for up to 30 min. Inhibition was most effective when Ca2+ entry occurred in both neurons. Depletion of Ca2+ from the mitochondria, but not the endoplasmic reticulum, also attenuated the electrical synapse. Buffering Ca2+ with high intracellular EGTA or inhibiting calmodulin kinase prevented uncoupling. Furthermore, activating PKC produced a small but clear decrease in junctional current, while triggering both Ca2+ influx and PKC inhibited the electrical synapse to a greater extent than Ca2+ alone. Finally, the amplitude and time course of the postsynaptic electrotonic response were attenuated after Ca2+ influx. A mathematical model of electrically connected neurons showed that excessive coupling reduced recruitment of the cells to fire, whereas less coupling led to spiking of essentially all neurons. Thus a decrease in electrical synapses could promote the afterdischarge by ensuring prompt recovery of electrotonic potentials or making the neurons more responsive to current spreading through the network. Copyright © 2015 the American Physiological Society.

Co-percolation to tune conductive behaviour in dynamical metallic nanowire networks.

PubMed

Fairfield, J A; Rocha, C G; O'Callaghan, C; Ferreira, M S; Boland, J J

2016-11-03

Nanowire networks act as self-healing smart materials, whose sheet resistance can be tuned via an externally applied voltage stimulus. This memristive response occurs due to modification of junction resistances to form a connectivity path across the lowest barrier junctions in the network. While most network studies have been performed on expensive noble metal nanowires like silver, networks of inexpensive nickel nanowires with a nickel oxide coating can also demonstrate resistive switching, a common feature of metal oxides with filamentary conduction. However, networks made from solely nickel nanowires have high operation voltages which prohibit large-scale material applications. Here we show, using both experiment and simulation, that a heterogeneous network of nickel and silver nanowires allows optimization of the activation voltage, as well as tuning of the conduction behavior to be either resistive switching, memristive, or a combination of both. Small percentages of silver nanowires, below the percolation threshold, induce these changes in electrical behaviour, even for low area coverage and hence very transparent films. Silver nanowires act as current concentrators, amplifying conductivity locally as shown in our computational dynamical activation framework for networks of junctions. These results demonstrate that a heterogeneous nanowire network can act as a cost-effective adaptive material with minimal use of noble metal nanowires, without losing memristive behaviour that is essential for smart sensing and neuromorphic applications.

Modeling Geoelectric Fields and Geomagnetically Induced Currents Around New Zealand to Explore GIC in the South Island's Electrical Transmission Network

NASA Astrophysics Data System (ADS)

Divett, T.; Ingham, M.; Beggan, C. D.; Richardson, G. S.; Rodger, C. J.; Thomson, A. W. P.; Dalzell, M.

2017-10-01

Transformers in New Zealand's South Island electrical transmission network have been impacted by geomagnetically induced currents (GIC) during geomagnetic storms. We explore the impact of GIC on this network by developing a thin-sheet conductance (TSC) model for the region, a geoelectric field model, and a GIC network model. (The TSC is composed of a thin-sheet conductance map with underlying layered resistivity structure.) Using modeling approaches that have been successfully used in the United Kingdom and Ireland, we applied a thin-sheet model to calculate the electric field as a function of magnetic field and ground conductance. We developed a TSC model based on magnetotelluric surveys, geology, and bathymetry, modified to account for offshore sediments. Using this representation, the thin sheet model gave good agreement with measured impedance vectors. Driven by a spatially uniform magnetic field variation, the thin-sheet model results in electric fields dominated by the ocean-land boundary with effects due to the deep ocean and steep terrain. There is a strong tendency for the electric field to align northwest-southeast, irrespective of the direction of the magnetic field. Applying this electric field to a GIC network model, we show that modeled GIC are dominated by northwest-southeast transmission lines rather than east-west lines usually assumed to dominate.

Reduction technique of drop voltage and power losses to improve power quality using ETAP Power Station simulation model

NASA Astrophysics Data System (ADS)

Satrio, Reza Indra; Subiyanto

2018-03-01

The effect of electric loads growth emerged direct impact in power systems distribution. Drop voltage and power losses one of the important things in power systems distribution. This paper presents modelling approach used to restructrure electrical network configuration, reduce drop voltage, reduce power losses and add new distribution transformer to enhance reliability of power systems distribution. Restructrure electrical network was aimed to analyse and investigate electric loads of a distribution transformer. Measurement of real voltage and real current were finished two times for each consumer, that were morning period and night period or when peak load. Design and simulation were conduct by using ETAP Power Station Software. Based on result of simulation and real measurement precentage of drop voltage and total power losses were mismatch with SPLN (Standard PLN) 72:1987. After added a new distribution transformer and restructrured electricity network configuration, the result of simulation could reduce drop voltage from 1.3 % - 31.3 % to 8.1 % - 9.6 % and power losses from 646.7 watt to 233.29 watt. Result showed, restructrure electricity network configuration and added new distribution transformer can be applied as an effective method to reduce drop voltage and reduce power losses.

Acoustic Network Localization and Interpretation of Infrasonic Pulses from Lightning

NASA Astrophysics Data System (ADS)

Arechiga, R. O.; Johnson, J. B.; Badillo, E.; Michnovicz, J. C.; Thomas, R. J.; Edens, H. E.; Rison, W.

2011-12-01

We improve on the localization accuracy of thunder sources and identify infrasonic pulses that are correlated across a network of acoustic arrays. We attribute these pulses to electrostatic charge relaxation (collapse of the electric field) and attempt to model their spatial extent and acoustic source strength. Toward this objective we have developed a single audio range (20-15,000 Hz) acoustic array and a 4-station network of broadband (0.01-500 Hz) microphone arrays with aperture of ~45 m. The network has an aperture of 1700 m and was installed during the summers of 2009-2011 in the Magdalena mountains of New Mexico, an area that is subject to frequent lightning activity. We are exploring a new technique based on inverse theory that integrates information from the audio range and the network of broadband acoustic arrays to locate thunder sources more accurately than can be achieved with a single array. We evaluate the performance of the technique by comparing the location of thunder sources with RF sources located by the lightning mapping array (LMA) of Langmuir Laboratory at New Mexico Tech. We will show results of this technique for lightning flashes that occurred in the vicinity of our network of acoustic arrays and over the LMA. We will use acoustic network detection of infrasonic pulses together with LMA data and electric field measurements to estimate the spatial distribution of the charge (within the cloud) that is used to produce a lightning flash, and will try to quantify volumetric charges (charge magnitude) within clouds.

Nanoscale Design of Nano-Sized Particles in Shape-Memory Polymer Nanocomposites Driven by Electricity

PubMed Central

Lu, Haibao; Huang, Wei Min; Liang, Fei; Yu, Kai

2013-01-01

In the last few years, we have witnessed significant progress in developing high performance shape memory polymer (SMP) nanocomposites, in particular, for shape recovery activated by indirect heating in the presence of electricity, magnetism, light, radio frequency, microwave and radiation, etc. In this paper, we critically review recent findings in Joule heating of SMP nanocomposites incorporated with nanosized conductive electromagnetic particles by means of nanoscale control via applying an electro- and/or magnetic field. A few different nanoscale design principles to form one-/two-/three- dimensional conductive networks are discussed. PMID:28788303

Carbon nanotube active-matrix backplanes for conformal electronics and sensors.

PubMed

Takahashi, Toshitake; Takei, Kuniharu; Gillies, Andrew G; Fearing, Ronald S; Javey, Ali

2011-12-14

In this paper, we report a promising approach for fabricating large-scale flexible and stretchable electronics using a semiconductor-enriched carbon nanotube solution. Uniform semiconducting nanotube networks with superb electrical properties (mobility of ∼20 cm2 V(-1) s(-1) and ION/IOFF of ∼10(4)) are obtained on polyimide substrates. The substrate is made stretchable by laser cutting a honeycomb mesh structure, which combined with nanotube-network transistors enables highly robust conformal electronic devices with minimal device-to-device stochastic variations. The utility of this device concept is demonstrated by fabricating an active-matrix backplane (12×8 pixels, physical size of 6×4 cm2) for pressure mapping using a pressure sensitive rubber as the sensor element.

The structural role of weak and strong links in a financial market network

NASA Astrophysics Data System (ADS)

Garas, A.; Argyrakis, P.; Havlin, S.

2008-05-01

We investigate the properties of correlation based networks originating from economic complex systems, such as the network of stocks traded at the New York Stock Exchange (NYSE). The weaker links (low correlation) of the system are found to contribute to the overall connectivity of the network significantly more than the strong links (high correlation). We find that nodes connected through strong links form well defined communities. These communities are clustered together in more complex ways compared to the widely used classification according to the economic activity. We find that some companies, such as General Electric (GE), Coca Cola (KO), and others, can be involved in different communities. The communities are found to be quite stable over time. Similar results were obtained by investigating markets completely different in size and properties, such as the Athens Stock Exchange (ASE). The present method may be also useful for other networks generated through correlations.

Storage of electric and magnetic energy in passive nonreciprocal networks

NASA Technical Reports Server (NTRS)

Smith, W. E.

1969-01-01

Examination of the relation of stored electric and magnetic energy within a system to the terminal behavior of nonreciprocal passive networks shows both similarities and important differences between wholly reciprocal systems and systems containing nonreciprocal elements.

Redox-Active Supramolecular Polymer Binders for Lithium–Sulfur Batteries That Adapt Their Transport Properties in Operando

DOE PAGES

Frischmann, Peter D.; Hwa, Yoon; Cairns, Elton J.; ...

2016-10-25

π-Stacked perylene bisimide (PBI) molecules are implemented here as highly networked, redox-active supramolecular polymer binders in sulfur cathodes for lightweight and energy-dense Li-S batteries. We show that the in operando reduction and lithiation of these PBI binders sustainably reduces Li-S cell impedance relative to nonredox active conventional polymer binders. This lower impedance enables high-rate cycling in Li-S cells with excellent durability, a critical step toward unlocking the full potential of Li-S batteries for electric vehicles and aviation.

A network thermodynamic method for numerical solution of the Nernst-Planck and Poisson equation system with application to ionic transport through membranes.

PubMed

Horno, J; González-Caballero, F; González-Fernández, C F

1990-01-01

Simple techniques of network thermodynamics are used to obtain the numerical solution of the Nernst-Planck and Poisson equation system. A network model for a particular physical situation, namely ionic transport through a thin membrane with simultaneous diffusion, convection and electric current, is proposed. Concentration and electric field profiles across the membrane, as well as diffusion potential, have been simulated using the electric circuit simulation program, SPICE. The method is quite general and extremely efficient, permitting treatments of multi-ion systems whatever the boundary and experimental conditions may be.

Neural network based short-term load forecasting using weather compensation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chow, T.W.S.; Leung, C.T.

This paper presents a novel technique for electric load forecasting based on neural weather compensation. The proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. The weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.

An electrical-heating and self-sensing shape memory polymer composite incorporated with carbon fiber felt

NASA Astrophysics Data System (ADS)

Gong, Xiaobo; Liu, Liwu; Liu, Yanju; Leng, Jinsong

2016-03-01

Shape memory polymers (SMPs) have the ability to adjust their stiffness, lock a temporary shape, and recover the permanent shape upon imposing an appropriate stimulus. They have found their way into the field of morphing structures. The electrically Joule resistive heating of the conductive composite can be a desirable stimulus to activate the shape memory effect of SMPs without external heating equipment. Electro-induced SMP composites incorporated with carbon fiber felt (CFF) were explored in this work. The CFF is an excellent conductive filler which can easily spread throughout the composite. It has a huge advantage in terms of low cost, simple manufacturing process, and uniform and tunable temperature distribution while heating. A continuous and compact conductive network made of carbon fibers and the overlap joints among them was observed from the microscopy images, and this network contributes to the high conductive properties of the CFF/SMP composites. The CFF/SMP composites can be electrical-heated rapidly and uniformly, and its’ shape recovery effect can be actuated by the electrical resistance Joule heating of the CFF without an external heater. The CFF/SMP composite get higher modulus and higher strength than the pure SMP without losing any strain recovery property. The high dependence of temperature and strain on the electrical resistance also make the composite a good self-sensing material. In general, the CFF/SMP composite shows great prospects as a potential material for the future morphing structures.

Modulation and detection of single neuron activity using spin transfer nano-oscillators

NASA Astrophysics Data System (ADS)

Algarin, Jose Miguel; Ramaswamy, Bharath; Venuti, Lucy; Swierzbinski, Matthew; Villar, Pablo; Chen, Yu-Jin; Krivorotov, Ilya; Weinberg, Irving N.; Herberholz, Jens; Araneda, Ricardo; Shapiro, Benjamin; Waks, Edo

2017-09-01

The brain is a complex network of interconnected circuits that exchange electrical signals with each other. These electrical signals provide insight on how neural circuits code information, and give rise to sensations, thoughts, emotions and actions. Currents methods to detect and modulate these electrical signals use implanted electrodes or optical fields with light sensitive dyes in the brain. These techniques require complex surgeries or suffer low resolution. In this talk we explore a new method to both image and stimulate single neurons using spintronics. We propose using a Spin Transfer Nano-Oscillators (STNOs) as a nanoscale sensor that converts neuronal action potentials to microwave field oscillations that can be detected wirelessly by magnetic induction. We will describe our recent proof-of-concept demonstration of both detection and wireless modulation of neuronal activity using STNOs. For detection we use electrodes to connect a STNO to a lateral giant crayfish neuron. When we stimulate the neuron, the STNO responds to the neuronal activity with a corresponding microwave signal. For modulation, we stimulate the STNOs wirelessly using an inductively coupled solenoid. The STNO rectifies the induced microwave signal to produce a direct voltage. This direct voltage from the STNO, when applied in the vicinity of a mammalian neuron, changes the frequency of electrical signals produced by the neuron.

Electrical innovations, authority and consulting expertise in late Victorian Britain

PubMed Central

Arapostathis, Stathis

2013-01-01

In this article I examine the practices of electrical engineering experts, with special reference to their role in the implementation of innovations in late Victorian electrical networks. I focus on the consulting work of two leading figures in the scientific and engineering world of the period, Alexander Kennedy and William Preece. Both were Fellows of the Royal Society and both developed large-scale consulting activities in the emerging electrical industry of light and power. At the core of the study I place the issues of trust and authority, and the bearing of these on the engineering expertise of consultants in late Victorian Britain. I argue that the ascription of expertise to these engineers and the trust placed in their advice were products of power relations on the local scale. The study seeks to unravel both the technical and the social reasons for authoritative patterns of consulting expertise. PMID:24686584

Evaluating conducting network based transparent electrodes from geometrical considerations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Ankush; Kulkarni, G. U., E-mail: guk@cens.res.in

2016-01-07

Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained frommore » conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in predicting the properties of a network simply from image analysis and will be helpful in improvisation and comparison of various TEs and better understanding of electrical percolation.« less

Evaluating conducting network based transparent electrodes from geometrical considerations

NASA Astrophysics Data System (ADS)

Kumar, Ankush; Kulkarni, G. U.

2016-01-01

Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained from conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in predicting the properties of a network simply from image analysis and will be helpful in improvisation and comparison of various TEs and better understanding of electrical percolation.

On the Synchronization of EEG Spindle Waves

NASA Astrophysics Data System (ADS)

Long, Wen; Zhang, ChengFu; Zhao, SiLan; Shi, RuiHong

2000-06-01

Based on recently sleeping cellular substrates, a network model synaptically coupled by N three-cell circuits is provided. Simulation results show that: (i) the dynamic behavior of every circuit is chaotic; (ii) the synchronization of the network is incomplete; (iii) the incomplete synchronization can integrate burst firings of cortical cells into waxing-and-wanning EEG spindle waves. These results enlighten us that this kind of incomplete synchronization may integrate microscopic, electrical activities of neurons in billions into macroscopic, functional states in human brain. In addition, the effects of coupling strength, connectional mode and noise to the synchronization are discussed.

The Study on the Communication Network of Wide Area Measurement System in Electricity Grid

NASA Astrophysics Data System (ADS)

Xiaorong, Cheng; Ying, Wang; Yangdan, Ni

Wide area measurement system(WAMS) is a fundamental part of security defense in Smart Grid, and the communication system of WAMS is an important part of Electric power communication network. For a large regional network is concerned, the real-time data which is transferred in the communication network of WAMS will affect the safe operation of the power grid directly. Therefore, WAMS raised higher requirements for real-time, reliability and security to its communication network. In this paper, the architecture of WASM communication network was studied according to the seven layers model of the open systems interconnection(OSI), and the network architecture was researched from all levels. We explored the media of WAMS communication network, the network communication protocol and network technology. Finally, the delay of the network were analyzed.

Carbon-based supercapacitors produced by activation of graphene.

PubMed

Zhu, Yanwu; Murali, Shanthi; Stoller, Meryl D; Ganesh, K J; Cai, Weiwei; Ferreira, Paulo J; Pirkle, Adam; Wallace, Robert M; Cychosz, Katie A; Thommes, Matthias; Su, Dong; Stach, Eric A; Ruoff, Rodney S

2011-06-24

Supercapacitors, also called ultracapacitors or electrochemical capacitors, store electrical charge on high-surface-area conducting materials. Their widespread use is limited by their low energy storage density and relatively high effective series resistance. Using chemical activation of exfoliated graphite oxide, we synthesized a porous carbon with a Brunauer-Emmett-Teller surface area of up to 3100 square meters per gram, a high electrical conductivity, and a low oxygen and hydrogen content. This sp(2)-bonded carbon has a continuous three-dimensional network of highly curved, atom-thick walls that form primarily 0.6- to 5-nanometer-width pores. Two-electrode supercapacitor cells constructed with this carbon yielded high values of gravimetric capacitance and energy density with organic and ionic liquid electrolytes. The processes used to make this carbon are readily scalable to industrial levels.

Carbon-Based Supercapacitors Produced by Activation of Graphene

NASA Astrophysics Data System (ADS)

Zhu, Yanwu; Murali, Shanthi; Stoller, Meryl D.; Ganesh, K. J.; Cai, Weiwei; Ferreira, Paulo J.; Pirkle, Adam; Wallace, Robert M.; Cychosz, Katie A.; Thommes, Matthias; Su, Dong; Stach, Eric A.; Ruoff, Rodney S.

2011-06-01

Supercapacitors, also called ultracapacitors or electrochemical capacitors, store electrical charge on high-surface-area conducting materials. Their widespread use is limited by their low energy storage density and relatively high effective series resistance. Using chemical activation of exfoliated graphite oxide, we synthesized a porous carbon with a Brunauer-Emmett-Teller surface area of up to 3100 square meters per gram, a high electrical conductivity, and a low oxygen and hydrogen content. This sp2-bonded carbon has a continuous three-dimensional network of highly curved, atom-thick walls that form primarily 0.6- to 5-nanometer-width pores. Two-electrode supercapacitor cells constructed with this carbon yielded high values of gravimetric capacitance and energy density with organic and ionic liquid electrolytes. The processes used to make this carbon are readily scalable to industrial levels.

Voltage management of distribution networks with high penetration of distributed photovoltaic generation sources

NASA Astrophysics Data System (ADS)

Alyami, Saeed

Installation of photovoltaic (PV) units could lead to great challenges to the existing electrical systems. Issues such as voltage rise, protection coordination, islanding detection, harmonics, increased or changed short-circuit levels, etc., need to be carefully addressed before we can see a wide adoption of this environmentally friendly technology. Voltage rise or overvoltage issues are of particular importance to be addressed for deploying more PV systems to distribution networks. This dissertation proposes a comprehensive solution to deal with the voltage violations in distribution networks, from controlling PV power outputs and electricity consumption of smart appliances in real time to optimal placement of PVs at the planning stage. The dissertation is composed of three parts: the literature review, the work that has already been done and the future research tasks. An overview on renewable energy generation and its challenges are given in Chapter 1. The overall literature survey, motivation and the scope of study are also outlined in the chapter. Detailed literature reviews are given in the rest of chapters. The overvoltage and undervoltage phenomena in typical distribution networks with integration of PVs are further explained in Chapter 2. Possible approaches for voltage quality control are also discussed in this chapter, followed by the discussion on the importance of the load management for PHEVs and appliances and its benefits to electric utilities and end users. A new real power capping method is presented in Chapter 3 to prevent overvoltage by adaptively setting the power caps for PV inverters in real time. The proposed method can maintain voltage profiles below a pre-set upper limit while maximizing the PV generation and fairly distributing the real power curtailments among all the PV systems in the network. As a result, each of the PV systems in the network has equal opportunity to generate electricity and shares the responsibility of voltage regulation. The method does not require global information and can be implemented either under a centralized supervisory control scheme or in a distributed way via consensus control. Chapter 4 investigates autonomous operation schedules for three types of intelligent appliances (or residential controllable loads) without receiving external signals for cost saving and for assisting the management of possible photovoltaic generation systems installed in the same distribution network. The three types of controllable loads studied in the chapter are electric water heaters, refrigerators deicing loads, and dishwashers, respectively. Chapter 5 investigates the method to mitigate overvoltage issues at the planning stage. A probabilistic method is presented in the chapter to evaluate the overvoltage risk in a distribution network with different PV capacity sizes under different load levels. Kolmogorov--Smirnov test (K--S test) is used to identify the most proper probability distributions for solar irradiance in different months. To increase accuracy, an iterative process is used to obtain the maximum allowable injection of active power from PVs. Conclusion and discussions on future work are given in Chapter 6.

Mechanical and Electrical Characterization of Entangled Networks of Carbon Nanofibers

PubMed Central

Mousavi, Arash K.; Atwater, Mark A.; Mousavi, Behnam K.; Jalalpour, Mohammad; Taha, Mahmoud Reda; Leseman, Zayd C.

2014-01-01

Entangled networks of carbon nanofibers are characterized both mechanically and electrically. Results for both tensile and compressive loadings of the entangled networks are presented for various densities. Mechanically, the nanofiber ensembles follow the micromechanical model originally proposed by van Wyk nearly 70 years ago. Interpretations are given on the mechanisms occurring during loading and unloading of the carbon nanofiber components. PMID:28788709

Comparative Analysis of Human and Rodent Brain Primary Neuronal Culture Spontaneous Activity Using Micro-Electrode Array Technology.

PubMed

Napoli, Alessandro; Obeid, Iyad

2016-03-01

Electrical activity in embryonic brain tissue has typically been studied using Micro Electrode Array (MEA) technology to make dozens of simultaneous recordings from dissociated neuronal cultures, brain stem cell progenitors, or brain slices from fetal rodents. Although these rodent neuronal primary culture electrical properties are mostly investigated, it has not been yet established to what extent the electrical characteristics of rodent brain neuronal cultures can be generalized to those of humans. A direct comparison of spontaneous spiking activity between rodent and human primary neurons grown under the same in vitro conditions using MEA technology has never been carried out before and will be described in the present study. Human and rodent dissociated fetal brain neuronal cultures were established in-vitro by culturing on a glass grid of 60 planar microelectrodes neurons under identical conditions. Three different cultures of human neurons were produced from tissue sourced from a single aborted fetus (at 16-18 gestational weeks) and these were compared with seven different cultures of embryonic rat neurons (at 18 gestational days) originally isolated from a single rat. The results show that the human and rodent cultures behaved significantly differently. Whereas the rodent cultures demonstrated robust spontaneous activation and network activity after only 10 days, the human cultures required nearly 40 days to achieve a substantially weaker level of electrical function. These results suggest that rat neuron preparations may yield inferences that do not necessarily transfer to humans. © 2015 Wiley Periodicals, Inc.

Electrical Activity in Martian Dust Storms

NASA Astrophysics Data System (ADS)

Majid, W.; Arabshahi, S.; Kocz, J.

2016-12-01

Dust storms on Mars are predicted to be capable of producing electrostatic fields and discharges, even larger than those in dust storms on Earth. Such electrical activity poses serious risks to any Human exploration of the planet and the lack of sufficient data to characterize any such activity has been identified by NASA's MEPAG as a key human safety knowledge gap. There are three key elements in the characterization of Martian electrostatic discharges: dependence on Martian environmental conditions, frequency of occurrence, and the strength of the generated electric fields. We will describe a recently deployed detection engine using NASA's Deep Space Network (DSN) to carry out a long term monitoring campaign to search for and characterize the entire Mars hemisphere for powerful discharges during routine tracking of spacecraft at Mars on an entirely non-interfering basis. The resulting knowledge of Mars electrical activity would allow NASA to plan risk mitigation measures to ensure human safety during Mars exploration. In addition, these measurements will also allow us to place limits on presence of oxidants such as H2O2 that may be produced by such discharges, providing another measurement point for models describing Martian atmospheric chemistry and habitability. Because of the continuous Mars telecommunication needs of NASA's Mars-based assets, the DSN is the only instrument in the world that combines long term, high cadence, observing opportunities with large sensitive telescopes, making it a unique asset worldwide in searching for and characterizing electrostatic activity at Mars from the ground.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Spiral Wave in Small-World Networks of Hodgkin-Huxley Neurons

NASA Astrophysics Data System (ADS)

Ma, Jun; Yang, Li-Jian; Wu, Ying; Zhang, Cai-Rong

2010-09-01

The effect of small-world connection and noise on the formation and transition of spiral wave in the networks of Hodgkin-Huxley neurons are investigated in detail. Some interesting results are found in our numerical studies. i) The quiescent neurons are activated to propagate electric signal to others by generating and developing spiral wave from spiral seed in small area. ii) A statistical factor is defined to describe the collective properties and phase transition induced by the topology of networks and noise. iii) Stable rotating spiral wave can be generated and keeps robust when the rewiring probability is below certain threshold, otherwise, spiral wave can not be developed from the spiral seed and spiral wave breakup occurs for a stable rotating spiral wave. iv) Gaussian white noise is introduced on the membrane of neurons to study the noise-induced phase transition on spiral wave in small-world networks of neurons. It is confirmed that Gaussian white noise plays active role in supporting and developing spiral wave in the networks of neurons, and appearance of smaller factor of synchronization indicates high possibility to induce spiral wave.

Numerical approximation of the electromechanical coupling in the left ventricle with inclusion of the Purkinje network.

PubMed

Landajuela, Mikel; Vergara, Christian; Gerbi, Antonello; Dedé, Luca; Formaggia, Luca; Quarteroni, Alfio

2018-03-25

In this work, we consider the numerical approximation of the electromechanical coupling in the left ventricle with inclusion of the Purkinje network. The mathematical model couples the 3D elastodynamics and bidomain equations for the electrophysiology in the myocardium with the 1D monodomain equation in the Purkinje network. For the numerical solution of the coupled problem, we consider a fixed-point iterative algorithm that enables a partitioned solution of the myocardium and Purkinje network problems. Different levels of myocardium-Purkinje network splitting are considered and analyzed. The results are compared with those obtained using standard strategies proposed in the literature to trigger the electrical activation. Finally, we present a numerical study that, although performed in an idealized computational domain, features all the physiological issues that characterize a heartbeat simulation, including the initiation of the signal in the Purkinje network and the systolic and diastolic phases. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Identifying Hydrologic Flowpaths on Arctic Hillslopes Using Electrical Resistivity and Self Potential

NASA Astrophysics Data System (ADS)

Voytek, E.; Rushlow, C. R.; Godsey, S.; Singha, K.

2015-12-01

Shallow subsurface flow is a dominant process controlling hillslope runoff generation, soil development, and solute reaction and transport. Despite their importance, the location and geometry of flowpaths are difficult to determine. In arctic environments, shallow subsurface flowpaths are limited to a thin zone of seasonal thaw above continuous permafrost, which is traditionally assumed to mimic to surface topography. Here we use a combined approach of electrical resistivity imaging (ERI) and self-potential measurements (SP) to map shallow subsurface flowpaths in and around water tracks, drainage features common to arctic hillslopes. ERI measurements delineate thawed zones in the subsurface that control flowpaths, while SP is sensitive to groundwater flow. We find that areas of low electrical resistivity in the water tracks are deeper than manual thaw depth estimates and variations from surface topography. This finding suggests that traditional techniques significantly underestimate active layer thaw and the extent of the flowpath network on arctic hillslopes. SP measurements identify complex 3-D flowpaths in the thawed zone. Our results lay the groundwork for investigations into the seasonal dynamics, hydrologic connectivity, and climate sensitivity of spatially distributed flowpath networks on arctic hillslopes.

Autapse-Induced Spiral Wave in Network of Neurons under Noise

PubMed Central

Qin, Huixin; Ma, Jun; Wang, Chunni; Wu, Ying

2014-01-01

Autapse plays an important role in regulating the electric activity of neuron by feedbacking time-delayed current on the membrane of neuron. Autapses are considered in a local area of regular network of neurons to investigate the development of spatiotemporal pattern, and emergence of spiral wave is observed while it fails to grow up and occupy the network completely. It is found that spiral wave can be induced to occupy more area in the network under optimized noise on the network with periodical or no-flux boundary condition being used. The developed spiral wave with self-sustained property can regulate the collective behaviors of neurons as a pacemaker. To detect the collective behaviors, a statistical factor of synchronization is calculated to investigate the emergence of ordered state in the network. The network keeps ordered state when self-sustained spiral wave is formed under noise and autapse in local area of network, and it independent of the selection of periodical or no-flux boundary condition. The developed stable spiral wave could be helpful for memory due to the distinct self-sustained property. PMID:24967577

Autapse-induced spiral wave in network of neurons under noise.

PubMed

Qin, Huixin; Ma, Jun; Wang, Chunni; Wu, Ying

2014-01-01

Autapse plays an important role in regulating the electric activity of neuron by feedbacking time-delayed current on the membrane of neuron. Autapses are considered in a local area of regular network of neurons to investigate the development of spatiotemporal pattern, and emergence of spiral wave is observed while it fails to grow up and occupy the network completely. It is found that spiral wave can be induced to occupy more area in the network under optimized noise on the network with periodical or no-flux boundary condition being used. The developed spiral wave with self-sustained property can regulate the collective behaviors of neurons as a pacemaker. To detect the collective behaviors, a statistical factor of synchronization is calculated to investigate the emergence of ordered state in the network. The network keeps ordered state when self-sustained spiral wave is formed under noise and autapse in local area of network, and it independent of the selection of periodical or no-flux boundary condition. The developed stable spiral wave could be helpful for memory due to the distinct self-sustained property.

Chimeras in leaky integrate-and-fire neural networks: effects of reflecting connectivities

NASA Astrophysics Data System (ADS)

Tsigkri-DeSmedt, Nefeli Dimitra; Hizanidis, Johanne; Schöll, Eckehard; Hövel, Philipp; Provata, Astero

2017-07-01

The effects of attracting-nonlocal and reflecting connectivity are investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which model the exchange of electrical signals between neurons. Earlier investigations have demonstrated that repulsive-nonlocal and hierarchical network connectivity can induce complex synchronization patterns and chimera states in systems of coupled oscillators. In the LIF system we show that if the elements are nonlocally linked with positive diffusive coupling on a ring network, the system splits into a number of alternating domains. Half of these domains contain elements whose potential stays near the threshold and they are interrupted by active domains where the elements perform regular LIF oscillations. The active domains travel along the ring with constant velocity, depending on the system parameters. When we introduce reflecting coupling in LIF networks unexpected complex spatio-temporal structures arise. For relatively extensive ranges of parameter values, the system splits into two coexisting domains: one where all elements stay near the threshold and one where incoherent states develop, characterized by multi-leveled mean phase velocity profiles.

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Werley, Kenneth Alan; Mccown, Andrew William

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. Thismore » third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.« less

Gestion de stockage d'energie thermique d'un parc de chauffe-eaux par une commande a champ moyen

NASA Astrophysics Data System (ADS)

Bourdel, Benoit

In today's energy transition, smart grids and electrical load control are very active research fields. This master's thesis is an offshoot of the SmartDesc project which aims at using energy storage capability of electric household appliances, such as water heaters and electric heaters to mitigate the fluctuations of system loads and renewable generation. The smartDESC project aims at demonstrating that the mean field game theory (MFG), as new mathematical theory, can be used to convert and control water heaters (and possibly space heater) into smart thermal capacities. Thus, a set of "modules" has been developed. These modules are used to generate the optimal control and locally interpret it, to simulate the water-heater thermophysics or water draw event, or to virtualize a telecommunication mesh network. The different aspects of the project have been first studied and developed separately. During the course of this master's research, the modules have been integrated, tested, interfaced and tuned in a common simulator. This simulator is designed to make complete electrical network simulations with a multi-scale approach (from individual water heater to global electric load and production). Firstly, the modules are precisely described theoretically and practically. Then, different types of control are applied to an uniform population of houses fitted with water heaters and controllers. The results of these controls are analysed and compared in order to understand their strengths and weaknesses. Finally, a study was conducted to analyse the resilience of a mean field control. This report demonstrates that mean field game theory in coordination with a system level aggregate model based optimization program, is able to effectively control a large population of water heaters to smooth the overall electrical load. This control offers good resilience to unforeseen circumstances that can disrupt the network. It is also demonstrated that a mean field control is able to absorb fluctuations due to wind power production. Thus, by reducing the variability of the residential sector's electrical charge, the mean field control plays a role in increasing power system stability in the face of high levels of renewable energy penetration. The next stage of smartDESC project is now to set up an intelligent electric water heater prototype. This prototype, in progress since January 2016 at Ecole Polytechnique in Montreal, is aimed at proving concretely the theories developed in the project.

Design of the smart home system based on the optimal routing algorithm and ZigBee network.

PubMed

Jiang, Dengying; Yu, Ling; Wang, Fei; Xie, Xiaoxia; Yu, Yongsheng

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system.

Design of the smart home system based on the optimal routing algorithm and ZigBee network

PubMed Central

Xie, Xiaoxia

2017-01-01

To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system. PMID:29131868

The effects of high-frequency oscillations in hippocampal electrical activities on the classification of epileptiform events using artificial neural networks

NASA Astrophysics Data System (ADS)

Chiu, Alan W. L.; Jahromi, Shokrollah S.; Khosravani, Houman; Carlen, Peter L.; Bardakjian, Berj L.

2006-03-01

The existence of hippocampal high-frequency electrical activities (greater than 100 Hz) during the progression of seizure episodes in both human and animal experimental models of epilepsy has been well documented (Bragin A, Engel J, Wilson C L, Fried I and Buzsáki G 1999 Hippocampus 9 137-42 Khosravani H, Pinnegar C R, Mitchell J R, Bardakjian B L, Federico P and Carlen P L 2005 Epilepsia 46 1-10). However, this information has not been studied between successive seizure episodes or utilized in the application of seizure classification. In this study, we examine the dynamical changes of an in vitro low Mg2+ rat hippocampal slice model of epilepsy at different frequency bands using wavelet transforms and artificial neural networks. By dividing the time-frequency spectrum of each seizure-like event (SLE) into frequency bins, we can analyze their burst-to-burst variations within individual SLEs as well as between successive SLE episodes. Wavelet energy and wavelet entropy are estimated for intracellular and extracellular electrical recordings using sufficiently high sampling rates (10 kHz). We demonstrate that the activities of high-frequency oscillations in the 100-400 Hz range increase as the slice approaches SLE onsets and in later episodes of SLEs. Utilizing the time-dependent relationship between different frequency bands, we can achieve frequency-dependent state classification. We demonstrate that activities in the frequency range 100-400 Hz are critical for the accurate classification of the different states of electrographic seizure-like episodes (containing interictal, preictal and ictal states) in brain slices undergoing recurrent spontaneous SLEs. While preictal activities can be classified with an average accuracy of 77.4 ± 6.7% utilizing the frequency spectrum in the range 0-400 Hz, we can also achieve a similar level of accuracy by using a nonlinear relationship between 100-400 Hz and <4 Hz frequency bands only.

Sleep, consciousness and the spontaneous and evoked electrical activity of the brain. Is there a cortical integrating mechanism?

PubMed

Evans, B M

2003-02-01

The physiological mechanisms that underlie consciousness and unconsciousness are the sleep/wake mechanisms. Deep sleep is a state of physiological reversible unconsciousness. The change from that state to wakefulness is mediated by the reticular activating mechanism. The reverse change from wakefulness to sleep is also an active process effected by an arousal inhibitory mechanism based on a partial blockade of the thalamus and upper brain stem, associated with thalamic sleep spindles and also with cortical sub-delta activity (<1 Hz). The deactivation of the thalamus has been demonstrated both electrically and by positron emission tomography during deep sleep. Normally, wakefulness is associated with instant awareness (defined as the ability to integrate all sensory information from the external environment and the internal environment of the body). Awareness may be a function of the thalamo-cortical network in the cerebral hemispheres, which forms the final path of the sleep/wake mechanism. Anatomical and physiological studies suggest that there may be a double thalamo-cortical network; one relating to cortical and thalamic areas with specific functions and the other global, involving all cortical areas and so-called 'non-specific' thalamic nuclei. The global system might function as a cortical integrating mechanism permitting the spread of information between the specific cortical areas and thus underlying awareness. The global system may also be responsible for much of the spontaneous and evoked electrical activity of the brain. The cognitive change between sleep and wakefulness is accompanied by changes in the autonomic system, the cerebral blood flow and cerebral metabolism. Awareness is an essential component of total consciousness (defined as continuous awareness of the external and internal environment, both past and present, together with the emotions arising from it). In addition to awareness, full consciousness requires short-term and explicit memory and intact emotional responses.

Electrical properties of a liquid crystal dispersed in an electrospun cellulose acetate network

PubMed Central

Danila, Octavian; Ganea, Constantin Paul

2018-01-01

Electro-optical devices that work in a similar fashion as PDLCs (polymer-dispersed liquid crystals), produced from cellulose acetate (CA) electrospun fibers deposited onto indium tin oxide coated glass and a nematic liquid crystal (E7), were studied. CA and the CA/liquid crystal composite were characterized by multiple investigation techniques, such as polarized optical microscopy, dielectric spectroscopy and impedance measurements. Dielectric constant and electric energy loss were studied as a function of frequency and temperature. The activation energy was evaluated and the relaxation time was obtained by fitting the spectra of the dielectric loss with the Havriliak–Negami functions. To determine the electrical characteristics of the studied samples, impedance measurements results were treated using the Cole–Cole diagram and the three-element equivalent model. PMID:29441261

Electrical properties of a liquid crystal dispersed in an electrospun cellulose acetate network.

PubMed

Maximean, Doina Manaila; Danila, Octavian; Almeida, Pedro L; Ganea, Constantin Paul

2018-01-01

Electro-optical devices that work in a similar fashion as PDLCs (polymer-dispersed liquid crystals), produced from cellulose acetate (CA) electrospun fibers deposited onto indium tin oxide coated glass and a nematic liquid crystal (E7), were studied. CA and the CA/liquid crystal composite were characterized by multiple investigation techniques, such as polarized optical microscopy, dielectric spectroscopy and impedance measurements. Dielectric constant and electric energy loss were studied as a function of frequency and temperature. The activation energy was evaluated and the relaxation time was obtained by fitting the spectra of the dielectric loss with the Havriliak-Negami functions. To determine the electrical characteristics of the studied samples, impedance measurements results were treated using the Cole-Cole diagram and the three-element equivalent model.

Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

NASA Astrophysics Data System (ADS)

Schäfer, Mirko; Tranberg, Bo; Hempel, Sabrina; Schramm, Stefan; Greiner, Martin

2017-08-01

The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

Investigating brain functional evolution and plasticity using microelectrode array technology.

PubMed

Napoli, Alessandro; Obeid, Iyad

2015-10-01

The aim of this work was to investigate long and short-term plasticity responsible for memory formation in dissociated neuronal networks. In order to address this issue, a set of experiments was designed and implemented in which the microelectrode array electrode grid was divided into four quadrants, two of which were chronically stimulated, every two days for one hour with a stimulation paradigm that varied over time. Overall network and quadrant responses were then analyzed to quantify what level of plasticity took place in the network and how this was due to the stimulation interruption. The results demonstrate that there were no spatial differences in the stimulus-evoked activity within quadrants. Furthermore, the implemented stimulation protocol induced depression effects in the neuronal networks as demonstrated by the consistently lower network activity following stimulation sessions. Finally, the analysis demonstrated that the inhibitory effects of the stimulation decreased over time, thus suggesting a habituation phenomenon. These findings are sufficient to conclude that electrical stimulation is an important tool to interact with dissociated neuronal cultures, but localized stimuli are not enough to drive spatial synaptic potentiation or depression. On the contrary, the ability to modulate synaptic temporal plasticity was a feasible task to achieve by chronic network stimulation. Copyright © 2015 Elsevier Inc. All rights reserved.

The Neural Correlates of Long-Term Carryover following Functional Electrical Stimulation for Stroke.

PubMed

Gandolla, Marta; Ward, Nick S; Molteni, Franco; Guanziroli, Eleonora; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2016-01-01

Neurorehabilitation effective delivery for stroke is likely to be improved by establishing a mechanistic understanding of how to enhance adaptive plasticity. Functional electrical stimulation is effective at reducing poststroke foot drop; in some patients, the effect persists after therapy has finished with an unknown mechanism. We used fMRI to examine neural correlates of functional electrical stimulation key elements, volitional intent to move and concurrent stimulation, in a group of chronic stroke patients receiving functional electrical stimulation for foot-drop correction. Patients exhibited task-related activation in a complex network, sharing bilateral sensorimotor and supplementary motor activation with age-matched controls. We observed consistent separation of patients with and without carryover effect on the basis of brain responses. Patients who experienced the carryover effect had responses in supplementary motor area that correspond to healthy controls; the interaction between experimental factors in contralateral angular gyrus was seen only in those without carryover. We suggest that the functional electrical stimulation carryover mechanism of action is based on movement prediction and sense of agency/body ownership-the ability of a patient to plan the movement and to perceive the stimulation as a part of his/her own control loop is important for carryover effect to take place.

Synchronization of Lienard-Type Oscillators in Uniform Electrical Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sinha, Mohit; Dorfler, Florian; Johnson, Brian B.

2016-08-01

This paper presents a condition for global asymptotic synchronization of Lienard-type nonlinear oscillators in uniform LTI electrical networks with series R-L circuits modeling interconnections. By uniform electrical networks, we mean that the per-unit-length impedances are identical for the interconnecting lines. We derive conditions for global asymptotic synchronization for a particular feedback architecture where the derivative of the oscillator output current supplements the innate current feedback induced by simply interconnecting the oscillator to the network. Our proof leverages a coordinate transformation to a set of differential coordinates that emphasizes signal differences and the particular form of feedback permits the formulation ofmore » a quadratic Lyapunov function for this class of networks. This approach is particularly interesting since synchronization conditions are difficult to obtain by means of quadratic Lyapunov functions when only current feedback is used and for networks composed of series R-L circuits. Our synchronization condition depends on the algebraic connectivity of the underlying network, and reiterates the conventional wisdom from Lyapunov- and passivity-based arguments that strong coupling is required to ensure synchronization.« less

Three essays on "making" electric power markets

NASA Astrophysics Data System (ADS)

Kench, Brian Thomas

2000-10-01

Technological change over the past three decades has altered most of the basic conditions in the electric power industry. Because of technical progress, the dominant paradigm has shifted from the provision of electric power by regulated and vertically integrated local natural monopolies to competition and vertical separation. In the first essay I provide a historical context of the electric industry's power current deregulation debate. Then a dynamic model of induced institutional change is used to investigate how endogenous technological advancements have induced radical institutional change in the generation and transmission segments of the electric power industry. Because the Federal Energy Regulatory Commission (FERC) ordered regulated utilities to provide open access to their transmission networks and to separate their generation and transmission functions, transmission networks have been used more intensively and in much different ways then in the past. The second essay tests experimentally the predictions of neoclassical theory for a radial electric power market under two alternative deregulated transmission institutions: financial transmission rights and physical transmission rights. Experimental evidence presented there demonstrates that an electric power market with physical transmission rights governing its transmission network generates more "right" market signals relative to a transmission network governed by financial transmission rights. The move to a greater reliance on markets for electric power is an idea that has animated sweeping and dramatic changes in the traditional business of electric power. The third essay examines two of the most innovative and complex initiatives of making electric power markets in the United States: California and PJM. As those markets mature and others are made, they must revise their governance mechanisms to eliminate rules that create inefficiency and adopt rules that work efficiently elsewhere. I argue that restructured electric power markets in the United States we should consider adopting an integrated procurement approach for electric power and ancillary services, binding forward markets for those commodities, and a market for physical transmission rights.

Electricity storage: Friend or foe of the networks?

NASA Astrophysics Data System (ADS)

Jamasb, Tooraj

2017-06-01

As storage technology progresses it offers a range of solutions and services to users and the electricity industry. A new study explores whether or not this will eventually lead to self-sufficient consumers and spell the end of the networks as we know them.

Network based management for multiplexed electric vehicle charging

DOEpatents

Gadh, Rajit; Chung, Ching Yen; Qui, Li

2017-04-11

A system for multiplexing charging of electric vehicles, comprising a server coupled to a plurality of charging control modules over a network. Each of said charging modules being connected to a voltage source such that each charging control module is configured to regulate distribution of voltage from the voltage source to an electric vehicle coupled to the charging control module. Data collection and control software is provided on the server for identifying a plurality of electric vehicles coupled to the plurality of charging control modules and selectively distributing charging of the plurality of charging control modules to multiplex distribution of voltage to the plurality of electric vehicles.

Neural network control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Harmon, Frederick G.

2005-11-01

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster-monitoring missions. The benefits, due to the hybrid and electric-only modes, include increased time-on-station and greater range as compared to electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. This dissertation contributes to the research fields of small unmanned aerial vehicles, hybrid-electric propulsion system control, and intelligent control. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system is provided. The UAV is intended for intelligence, surveillance, and reconnaissance (ISR) missions. A conceptual design reveals the trade-offs that must be considered to take advantage of the hybrid-electric propulsion system. The resulting hybrid-electric propulsion system is a two-point design that includes an engine primarily sized for cruise speed and an electric motor and battery pack that are primarily sized for a slower endurance speed. The electric motor provides additional power for take-off, climbing, and acceleration and also serves as a generator during charge-sustaining operation or regeneration. The intelligent control of the hybrid-electric propulsion system is based on an instantaneous optimization algorithm that generates a hyper-plane from the nonlinear efficiency maps for the internal combustion engine, electric motor, and lithium-ion battery pack. The hyper-plane incorporates charge-depletion and charge-sustaining strategies. The optimization algorithm is flexible and allows the operator/user to assign relative importance between the use of gasoline, electricity, and recharging depending on the intended mission. A MATLAB/Simulink model was developed to test the control algorithms. The Cerebellar Model Arithmetic Computer (CMAC) associative memory neural network is applied to the control of the UAVs parallel hybrid-electric propulsion system. The CMAC neural network approximates the hyper-plane generated from the instantaneous optimization algorithm and produces torque commands for the internal combustion engine and electric motor. The CMAC neural network controller saves on the required memory as compared to a large look-up table by two orders of magnitude. The CMAC controller also prevents the need to compute a hyper-plane or complex logic every time step.

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

NASA Technical Reports Server (NTRS)

Knox, W. Bradley; Mengshoel, Ole

2009-01-01

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Simulation electromagnetic scattering on bodies through integral equation and neural networks methods

NASA Astrophysics Data System (ADS)

Lvovich, I. Ya; Preobrazhenskiy, A. P.; Choporov, O. N.

2018-05-01

The paper deals with the issue of electromagnetic scattering on a perfectly conducting diffractive body of a complex shape. Performance calculation of the body scattering is carried out through the integral equation method. Fredholm equation of the second time was used for calculating electric current density. While solving the integral equation through the moments method, the authors have properly described the core singularity. The authors determined piecewise constant functions as basic functions. The chosen equation was solved through the moments method. Within the Kirchhoff integral approach it is possible to define the scattered electromagnetic field, in some way related to obtained electrical currents. The observation angles sector belongs to the area of the front hemisphere of the diffractive body. To improve characteristics of the diffractive body, the authors used a neural network. All the neurons contained a logsigmoid activation function and weighted sums as discriminant functions. The paper presents the matrix of weighting factors of the connectionist model, as well as the results of the optimized dimensions of the diffractive body. The paper also presents some basic steps in calculation technique of the diffractive bodies, based on the combination of integral equation and neural networks methods.

Detection of Frauds and Other Non-technical Losses in Power Utilities using Smart Meters: A Review

NASA Astrophysics Data System (ADS)

Ahmad, Tanveer; Ul Hasan, Qadeer

2016-06-01

Analysis of losses in power distribution system and techniques to mitigate these are two active areas of research especially in energy scarce countries like Pakistan to increase the availability of power without installing new generation. Since total energy losses account for both technical losses (TL) as well as non-technical losses (NTLs). Utility companies in developing countries are incurring of major financial losses due to non-technical losses. NTLs lead to a series of additional losses, such as damage to the network (infrastructure and the reduction of network reliability) etc. The purpose of this paper is to perform an introductory investigation of non-technical losses in power distribution systems. Additionally, analysis of NTLs using consumer energy consumption data with the help of Linear Regression Analysis has been carried out. This data focuses on the Low Voltage (LV) distribution network, which includes: residential, commercial, agricultural and industrial consumers by using the monthly kWh interval data acquired over a period (one month) of time using smart meters. In this research different prevention techniques are also discussed to prevent illegal use of electricity in the distribution of electrical power system.

Energy-aware virtual network embedding in flexi-grid networks.

PubMed

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng

2017-11-27

Network virtualization technology has been proposed to allow multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network, which increases the utilization of the substrate network. Efficiently mapping VNs on the substrate network is a major challenge on account of the VN embedding (VNE) problem. Meanwhile, energy efficiency has been widely considered in the network design in terms of operation expenses and the ecological awareness. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the electricity cost of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low electricity cost. Numerical results show that the heuristic algorithm performs closely to the ILP for a small size network, and we also demonstrate its applicability to larger networks.

Electrical activity controls area-specific expression of neuronal apoptosis in the mouse developing cerebral cortex.

PubMed

Blanquie, Oriane; Yang, Jenq-Wei; Kilb, Werner; Sharopov, Salim; Sinning, Anne; Luhmann, Heiko J

2017-08-21

Programmed cell death widely but heterogeneously affects the developing brain, causing the loss of up to 50% of neurons in rodents. However, whether this heterogeneity originates from neuronal identity and/or network-dependent processes is unknown. Here, we report that the primary motor cortex (M1) and primary somatosensory cortex (S1), two adjacent but functionally distinct areas, display striking differences in density of apoptotic neurons during the early postnatal period. These differences in rate of apoptosis negatively correlate with region-dependent levels of activity. Disrupting this activity either pharmacologically or by electrical stimulation alters the spatial pattern of apoptosis and sensory deprivation leads to exacerbated amounts of apoptotic neurons in the corresponding functional area of the neocortex. Thus, our data demonstrate that spontaneous and periphery-driven activity patterns are important for the structural and functional maturation of the neocortex by refining the final number of cortical neurons in a region-dependent manner.

Brain plasticity and functionality explored by nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Sacconi, L.; Allegra, L.; Buffelli, M.; Cesare, P.; D'Angelo, E.; Gandolfi, D.; Grasselli, G.; Lotti, J.; Mapelli, J.; Strata, P.; Pavone, F. S.

2010-02-01

In combination with fluorescent protein (XFP) expression techniques, two-photon microscopy has become an indispensable tool to image cortical plasticity in living mice. In parallel to its application in imaging, multi-photon absorption has also been used as a tool for the dissection of single neurites with submicrometric precision without causing any visible collateral damage to the surrounding neuronal structures. In this work, multi-photon nanosurgery is applied to dissect single climbing fibers expressing GFP in the cerebellar cortex. The morphological consequences are then characterized with time lapse 3-dimensional two-photon imaging over a period of minutes to days after the procedure. Preliminary investigations show that the laser induced fiber dissection recalls a regenerative process in the fiber itself over a period of days. These results show the possibility of this innovative technique to investigate regenerative processes in adult brain. In parallel with imaging and manipulation technique, non-linear microscopy offers the opportunity to optically record electrical activity in intact neuronal networks. In this work, we combined the advantages of second-harmonic generation (SHG) with a random access (RA) excitation scheme to realize a new microscope (RASH) capable of optically recording fast membrane potential events occurring in a wide-field of view. The RASH microscope, in combination with bulk loading of tissue with FM4-64 dye, was used to simultaneously record electrical activity from clusters of Purkinje cells in acute cerebellar slices. Complex spikes, both synchronous and asynchronous, were optically recorded simultaneously across a given population of neurons. Spontaneous electrical activity was also monitored simultaneously in pairs of neurons, where action potentials were recorded without averaging across trials. These results show the strength of this technique in describing the temporal dynamics of neuronal assemblies, opening promising perspectives in understanding the computations of neuronal networks.

ELECTRIC VEHICLE CONVERSIONS USING ALTERNATIVE ENERGY TO DRIVE ALASKAN RURAL COMMUNITIES

EPA Science Inventory

This proposal concerns sustainable transportation in rural Alaskan communities which are not part of a road or electrical network (off grid). In most off-grid communities, the road networks generally are less than 50 square miles, so transportation needs are limited. This limi...

Managing Ongoing EVSE Costs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Cabell

The costs associated with EVSE begin with picking the best location and unit for the job, but they continue with electricity and network charges through the life of your vehicle. This presentation tells how to balance electricity demand charges and network management costs through smart planning at your program's inception.

Heating the sun's lower transition region with fine-scale electric currents

NASA Technical Reports Server (NTRS)

Rabin, D.; Moore, R.

1984-01-01

Analytical and observational data are presented to show that the lower transition zone, a 100 km thick region at 10,000-200,000 K between the solar chromosphere and corona, is heated by local electric currents. The study was spurred by correlations between the enhanced atmospheric heating and magnetospheric flux in the chromospheric network and active regions. Field aligned current heated flux loops are asserted to mainly reside in and make up most of the transition region. It is shown that thermal conduction from the sides of hot gas columns generated by the current dissipation is the source of the observed temperature distribution in the transition regions.

Soft Multifunctional Composites and Emulsions with Liquid Metals.

PubMed

Kazem, Navid; Hellebrekers, Tess; Majidi, Carmel

2017-07-01

Binary mixtures of liquid metal (LM) or low-melting-point alloy (LMPA) in an elastomeric or fluidic carrier medium can exhibit unique combinations of electrical, thermal, and mechanical properties. This emerging class of soft multifunctional composites have potential applications in wearable computing, bio-inspired robotics, and shape-programmable architectures. The dispersion phase can range from dilute droplets to connected networks that support electrical conductivity. In contrast to deterministically patterned LM microfluidics, LMPA- and LM-embedded elastomer (LMEE) composites are statistically homogenous and exhibit effective bulk properties. Eutectic Ga-In (EGaIn) and Ga-In-Sn (Galinstan) alloys are typically used due to their high conductivity, low viscosity, negligible nontoxicity, and ability to wet to nonmetallic materials. Because they are liquid-phase, these alloys can alter the electrical and thermal properties of the composite while preserving the mechanics of the surrounding medium. For composites with LMPA inclusions (e.g., Field's metal, Pb-based solder), mechanical rigidity can be actively tuned with external heating or electrical activation. This progress report, reviews recent experimental and theoretical studies of this emerging class of soft material architectures and identifies current technical challenges and opportunities for further advancement. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A strip chart recorder pattern recognition tool kit for Shuttle operations

NASA Technical Reports Server (NTRS)

Hammen, David G.; Moebes, Travis A.; Shelton, Robert O.; Savely, Robert T.

1993-01-01

During Space Shuttle operations, Mission Control personnel monitor numerous mission-critical systems such as electrical power; guidance, navigation, and control; and propulsion by means of paper strip chart recorders. For example, electrical power controllers monitor strip chart recorder pen traces to identify onboard electrical equipment activations and deactivations. Recent developments in pattern recognition technologies coupled with new capabilities that distribute real-time Shuttle telemetry data to engineering workstations make it possible to develop computer applications that perform some of the low-level monitoring now performed by controllers. The number of opportunities for such applications suggests a need to build a pattern recognition tool kit to reduce software development effort through software reuse. We are building pattern recognition applications while keeping such a tool kit in mind. We demonstrated the initial prototype application, which identifies electrical equipment activations, during three recent Shuttle flights. This prototype was developed to test the viability of the basic system architecture, to evaluate the performance of several pattern recognition techniques including those based on cross-correlation, neural networks, and statistical methods, to understand the interplay between an advanced automation application and human controllers to enhance utility, and to identify capabilities needed in a more general-purpose tool kit.

Differential neural circuitry and self-interest in real vs hypothetical moral decisions

PubMed Central

Dalgleish, Tim; Thompson, Russell; Evans, Davy; Schweizer, Susanne; Mobbs, Dean

2012-01-01

Classic social psychology studies demonstrate that people can behave in ways that contradict their intentions—especially within the moral domain. We measured brain activity while subjects decided between financial self-benefit (earning money) and preventing physical harm (applying an electric shock) to a confederate under both real and hypothetical conditions. We found a shared neural network associated with empathic concern for both types of decisions. However, hypothetical and real moral decisions also recruited distinct neural circuitry: hypothetical moral decisions mapped closely onto the imagination network, while real moral decisions elicited activity in the bilateral amygdala and anterior cingulate—areas essential for social and affective processes. Moreover, during real moral decision-making, distinct regions of the prefrontal cortex (PFC) determined whether subjects make selfish or pro-social moral choices. Together, these results reveal not only differential neural mechanisms for real and hypothetical moral decisions but also that the nature of real moral decisions can be predicted by dissociable networks within the PFC. PMID:22711879

Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks

NASA Astrophysics Data System (ADS)

Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut; Perc, Matjaž

2016-02-01

We study the effects of an autapse, which is mathematically described as a self-feedback loop, on the propagation of weak, localized pacemaker activity across a Newman-Watts small-world network consisting of stochastic Hodgkin-Huxley neurons. We consider that only the pacemaker neuron, which is stimulated by a subthreshold periodic signal, has an electrical autapse that is characterized by a coupling strength and a delay time. We focus on the impact of the coupling strength, the network structure, the properties of the weak periodic stimulus, and the properties of the autapse on the transmission of localized pacemaker activity. Obtained results indicate the existence of optimal channel noise intensity for the propagation of the localized rhythm. Under optimal conditions, the autapse can significantly improve the propagation of pacemaker activity, but only for a specific range of the autaptic coupling strength. Moreover, the autaptic delay time has to be equal to the intrinsic oscillation period of the Hodgkin-Huxley neuron or its integer multiples. We analyze the inter-spike interval histogram and show that the autapse enhances or suppresses the propagation of the localized rhythm by increasing or decreasing the phase locking between the spiking of the pacemaker neuron and the weak periodic signal. In particular, when the autaptic delay time is equal to the intrinsic period of oscillations an optimal phase locking takes place, resulting in a dominant time scale of the spiking activity. We also investigate the effects of the network structure and the coupling strength on the propagation of pacemaker activity. We find that there exist an optimal coupling strength and an optimal network structure that together warrant an optimal propagation of the localized rhythm.

Relationships between cortical myeloarchitecture and electrophysiological networks

PubMed Central

Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Mougin, Olivier E.; Geades, Nicolas; Singh, Krish D.; Morris, Peter G.; Gowland, Penny A.; Brookes, Matthew J.

2016-01-01

The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poorly understood. Recent animal work has demonstrated that electrical activity promotes myelination. Inspired by this, we test a hypothesis that gray-matter myelin is related to electrophysiological connectivity. Using ultra-high field MRI and the principle of structural covariance, we derive a structural network showing how myelin density differs across cortical regions and how separate regions can exhibit similar myeloarchitecture. Building upon recent evidence that neural oscillations mediate connectivity, we use magnetoencephalography to elucidate networks that represent the major electrophysiological pathways of communication in the brain. Finally, we show that a significant relationship exists between our functional and structural networks; this relationship differs as a function of neural oscillatory frequency and becomes stronger when integrating oscillations over frequency bands. Our study sheds light on the way in which cortical microstructure supports functional networks. Further, it paves the way for future investigations of the gray-matter structure/function relationship and its breakdown in pathology. PMID:27830650

The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

NASA Astrophysics Data System (ADS)

Ivanin, O. A.; Direktor, L. B.

2018-05-01

The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

Investigating the functional neuroanatomy of concrete and abstract word processing through direct electric stimulation (DES) during awake surgery.

PubMed

Orena, E F; Caldiroli, D; Acerbi, F; Barazzetta, I; Papagno, C

2018-06-05

Neuropsychological, neuroimaging and electrophysiological studies demonstrate that abstract and concrete word processing relies not only on the activity of a common bilateral network but also on dedicated networks. The neuropsychological literature has shown that a selective sparing of abstract relative to concrete words can be documented in lesions of the left anterior temporal regions. We investigated concrete and abstract word processing in 10 patients undergoing direct electrical stimulation (DES) for brain mapping during awake surgery in the left hemisphere. A lexical decision and a concreteness judgment task were added to the neuropsychological assessment during intra-operative monitoring. On the concreteness judgment, DES delivered over the inferior frontal gyrus significantly decreased abstract word accuracy while accuracy for concrete words decreased when the anterior temporal cortex was stimulated. These results are consistent with a lexical-semantic model that distinguishes between concrete and abstract words related to different neural substrates in the left hemisphere.

Optimal operation management of fuel cell/wind/photovoltaic power sources connected to distribution networks

NASA Astrophysics Data System (ADS)

Niknam, Taher; Kavousifard, Abdollah; Tabatabaei, Sajad; Aghaei, Jamshid

2011-10-01

In this paper a new multiobjective modified honey bee mating optimization (MHBMO) algorithm is presented to investigate the distribution feeder reconfiguration (DFR) problem considering renewable energy sources (RESs) (photovoltaics, fuel cell and wind energy) connected to the distribution network. The objective functions of the problem to be minimized are the electrical active power losses, the voltage deviations, the total electrical energy costs and the total emissions of RESs and substations. During the optimization process, the proposed algorithm finds a set of non-dominated (Pareto) optimal solutions which are stored in an external memory called repository. Since the objective functions investigated are not the same, a fuzzy clustering algorithm is utilized to handle the size of the repository in the specified limits. Moreover, a fuzzy-based decision maker is adopted to select the 'best' compromised solution among the non-dominated optimal solutions of multiobjective optimization problem. In order to see the feasibility and effectiveness of the proposed algorithm, two standard distribution test systems are used as case studies.

Broadband electrical impedance matching for piezoelectric ultrasound transducers.

PubMed

Huang, Haiying; Paramo, Daniel

2011-12-01

This paper presents a systematic method for designing broadband electrical impedance matching networks for piezoelectric ultrasound transducers. The design process involves three steps: 1) determine the equivalent circuit of the unmatched piezoelectric transducer based on its measured admittance; 2) design a set of impedance matching networks using a computerized Smith chart; and 3) establish the simulation model of the matched transducer to evaluate the gain and bandwidth of the impedance matching networks. The effectiveness of the presented approach is demonstrated through the design, implementation, and characterization of impedance matching networks for a broadband acoustic emission sensor. The impedance matching network improved the power of the acquired signal by 9 times.

Short-term depression of gap junctional coupling in reticular thalamic neurons of absence epileptic rats.

PubMed

Kohmann, Denise; Lüttjohann, Annika; Seidenbecher, Thomas; Coulon, Philippe; Pape, Hans-Christian

2016-10-01

Gap junctional electrical coupling between neurons of the reticular thalamic nucleus (RTN) is critical for hypersynchrony in the thalamo-cortical network. This study investigates the role of electrical coupling in pathological rhythmogenesis in RTN neurons in a rat model of absence epilepsy. Rhythmic activation resulted in a Ca(2+) -dependent short-term depression (STD) of electrical coupling between pairs of RTN neurons in epileptic rats, but not in RTN of a non-epileptic control strain. Pharmacological blockade of gap junctions in RTN in vivo induced a depression of seizure activity. The STD of electrical coupling represents a mechanism of Ca(2+) homeostasis in RTN aimed to counteract excessive synchronization. Neurons in the reticular thalamic nucleus (RTN) are coupled by electrical synapses, which play a major role in regulating synchronous activity. This study investigates electrical coupling in RTN neurons from a rat model of childhood absence epilepsy, genetic absence epilepsy rats from Strasbourg (GAERS), compared with a non-epileptic control (NEC) strain, to assess the impact on pathophysiological rhythmogenesis. Whole-cell recordings were obtained from pairs of RTN neurons of GAERS and NEC in vitro. Coupling was determined by injection of hyperpolarizing current steps in one cell and monitoring evoked voltage responses in both activated and coupled cell. The coupling coefficient (cc) was compared under resting condition, during pharmacological interventions and repeated activation using a series of current injections. The effect of gap junctional coupling on seizure expression was investigated by application of gap junctional blockers into RTN of GAERS in vivo. At resting conditions, cc did not differ between GAERS and NEC. During repeated activation, cc declined in GAERS but not in NEC. This depression in cc was restored within 25 s and was prevented by intracellular presence of BAPTA in the activated but not in the coupled cell. Local application of gap junctional blockers into RTN of GAERS in vivo resulted in a decrease of spike wave discharge (SWD) activity. Repeated activation results in a short-term depression (STD) of gap junctional coupling in RTN neurons of GAERS, depending on intracellular Ca(2+) mechanisms in the activated cell. As blockage of gap junctions in vivo results in a decrease of SWD activity, the STD observed in GAERS is considered a compensatory mechanism, aimed to dampen SWD activity. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Delivering key signals to the machine: seeking the electric signal that muscles emanate

NASA Astrophysics Data System (ADS)

Bani Hashim, A. Y.; Maslan, M. N.; Izamshah, R.; Mohamad, I. S.

2014-11-01

Due to the limitation of electric power generation in the human body, present human-machine interfaces have not been successful because of the nature of standard electronics circuit designs, which do not consider the specifications of signals that resulted from the skin. In general, the outcomes and applications of human-machine interfaces are limited to custom-designed subsystems, such as neuroprosthesis. We seek to model the bio dynamical of sub skin into equivalent mathematical definitions, descriptions, and theorems. Within the human skin, there are networks of nerves that permit the skin to function as a multi dimension transducer. We investigate the nature of structural skin. Apart from multiple networks of nerves, there are other segments within the skin such as minute muscles. We identify the segments that are active when there is an electromyography activity. When the nervous system is firing signals, the muscle is being stimulated. We evaluate the phenomena of biodynamic of the muscles that is concerned with the electromyography activity of the nervous system. In effect, we design a relationship between the human somatosensory and synthetic systems sensory as the union of a complete set of the new domain of the functional system. This classifies electromyogram waveforms linked to intent thought of an operator. The system will become the basis for delivering key signals to machine such that the machine is under operator's intent, hence slavery.

Drive Control Scheme of Electric Power Assisted Wheelchair Based on Neural Network Learning of Human Wheelchair Operation Characteristics

NASA Astrophysics Data System (ADS)

Tanohata, Naoki; Seki, Hirokazu

This paper describes a novel drive control scheme of electric power assisted wheelchairs based on neural network learning of human wheelchair operation characteristics. “Electric power assisted wheelchair” which enhances the drive force of the operator by employing electric motors is expected to be widely used as a mobility support system for elderly and disabled people. However, some handicapped people with paralysis of the muscles of one side of the body cannot maneuver the wheelchair as desired because of the difference in the right and left input force. Therefore, this study proposes a neural network learning system of such human wheelchair operation characteristics and a drive control scheme with variable distribution and assistance ratios. Some driving experiments will be performed to confirm the effectiveness of the proposed control system.

Electrical and Optical Activation of Mesoscale Neural Circuits with Implications for Coding.

PubMed

Millard, Daniel C; Whitmire, Clarissa J; Gollnick, Clare A; Rozell, Christopher J; Stanley, Garrett B

2015-11-25

Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery of circuit function and for engineered approaches to alleviate various disorders of the nervous system. However, evidence suggests that neural activity generated by artificial stimuli differs dramatically from normal circuit function, in terms of both the local neuronal population activity at the site of activation and the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. Here, we used voltage-sensitive dye imaging of primary somatosensory cortex in the anesthetized rat in response to deflections of the facial vibrissae and electrical or optogenetic stimulation of thalamic neurons that project directly to the somatosensory cortex. Although the different inputs produced responses that were similar in terms of the average cortical activation, the variability of the cortical response was strikingly different for artificial versus sensory inputs. Furthermore, electrical microstimulation resulted in highly unnatural spatial activation of cortex, whereas optical input resulted in spatial cortical activation that was similar to that induced by sensory inputs. A thalamocortical network model suggested that observed differences could be explained by differences in the way in which artificial and natural inputs modulate the magnitude and synchrony of population activity. Finally, the variability structure in the response for each case strongly influenced the optimal inputs for driving the pathway from the perspective of an ideal observer of cortical activation when considered in the context of information transmission. Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery and clinical translation. However, neural activity generated by these artificial means differs dramatically from normal circuit function, both locally and in the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. The significance of this work is in quantifying the differences, elucidating likely mechanisms underlying the differences, and determining the implications for information processing. Copyright © 2015 the authors 0270-6474/15/3515702-14$15.00/0.

Optimal Resource Allocation in Electrical Network Defense

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yao, Y; Edmunds, T; Papageorgiou, D

2004-01-15

Infrastructure networks supplying electricity, natural gas, water, and other commodities are at risk of disruption due to well-engineered and coordinated terrorist attacks. Countermeasures such as hardening targets, acquisition of spare critical components, and surveillance can be undertaken to detect and deter these attacks. Allocation of available countermeasures resources to sites or activities in a manner that maximizes their effectiveness is a challenging problem. This allocation must take into account the adversary's response after the countermeasure assets are in place and consequence mitigation measures the infrastructure operation can undertake after the attack. The adversary may simply switch strategies to avoid countermeasuresmore » when executing the attack. Stockpiling spares of critical energy infrastructure components has been identified as a key element of a grid infrastructure defense strategy in a recent National Academy of Sciences report [1]. Consider a scenario where an attacker attempts to interrupt the service of an electrical network by disabling some of its facilities while a defender wants to prevent or minimize the effectiveness of any attack. The interaction between the attacker and the defender can be described in three stages: (1) The defender deploys countermeasures, (2) The attacker disrupts the network, and (3) The defender responds to the attack by rerouting power to maintain service while trying to repair damage. In the first stage, the defender considers all possible attack scenarios and deploys countermeasures to defend against the worst scenarios. Countermeasures can include hardening targets, acquiring spare critical components, and installing surveillance devices. In the second stage, the attacker, with full knowledge of the deployed countermeasures, attempts to disable some nodes or links in the network to inflict the greatest loss on the defender. In the third stage, the defender re-dispatches power and restores disabled nodes or links to minimize the loss. The loss can be measured in costs, including the costs of using more expensive generators and the economic losses that can be attributed to loss of load. The defender's goal is to minimize the loss while the attacker wants to maximize it. Assuming some level of budget constraint, each side can only defend or attack a limited number of network elements. When an element is attacked, it is assumed that it will be totally disabled. It is assumed that when an element is defended it cannot be disabled, which may mean that it will be restored in a very short time after being attacked. The rest of the paper is organized as follows. Section 2 will briefly review literature related to multilevel programming and network defense. Section 3 presents a mathematical formulation of the electrical network defense problem. Section 4 describes the solution algorithms. Section 5 discusses computational results. Finally, Sec. 6 explores future research directions.« less

An integrated eVoucher mechanism for flexible loads in real-time retail electricity market

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Tao; Pourbabak, Hajir; Liang, Zheming

This study proposes an innovative economic and engineering coupled framework to encourage typical flexible loads or load aggregators, such as parking lots with high penetration of electric vehicles, to participate directly in the real-time retail electricity market based on an integrated eVoucher program. The integrated eVoucher program entails demand side management, either in the positive or negative direction, following a popular customer-centric design principle. It provides the extra economic benefit to end-users and reduces the risk associated with the wholesale electricity market for electric distribution companies (EDCs), meanwhile improving the potential resilience of the distribution networks with consideration for frequencymore » deviations. When implemented, the eVoucher program allows typical flexible loads, such as electric vehicle parking lots, to adjust their demand and consumption behavior according to financial incentives from an EDC. A distribution system operator (DSO) works as a third party to hasten negotiations between such parking lots and EDCs, as well as the price clearing process. Eventually, both electricity retailers and power system operators will benefit from the active participation of the flexible loads and energy customers.« less

An integrated eVoucher mechanism for flexible loads in real-time retail electricity market

DOE PAGES

Chen, Tao; Pourbabak, Hajir; Liang, Zheming; ...

2017-01-26

This study proposes an innovative economic and engineering coupled framework to encourage typical flexible loads or load aggregators, such as parking lots with high penetration of electric vehicles, to participate directly in the real-time retail electricity market based on an integrated eVoucher program. The integrated eVoucher program entails demand side management, either in the positive or negative direction, following a popular customer-centric design principle. It provides the extra economic benefit to end-users and reduces the risk associated with the wholesale electricity market for electric distribution companies (EDCs), meanwhile improving the potential resilience of the distribution networks with consideration for frequencymore » deviations. When implemented, the eVoucher program allows typical flexible loads, such as electric vehicle parking lots, to adjust their demand and consumption behavior according to financial incentives from an EDC. A distribution system operator (DSO) works as a third party to hasten negotiations between such parking lots and EDCs, as well as the price clearing process. Eventually, both electricity retailers and power system operators will benefit from the active participation of the flexible loads and energy customers.« less

Memristors in the electrical network of Aloe vera L.

PubMed Central

Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tucket, Clayton; Forde-Tuckett, Victoria; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

2014-01-01

A memristor is a resistor with memory, which is a non-linear passive two-terminal electrical element relating magnetic flux linkage and electrical charge. Here we found that memristors exist in vivo. The electrostimulation of the Aloe vera by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar periodic sinusoidal or triangle electrostimulating waves. Memristive behavior of an electrical network in the Aloe vera is linked to the properties of voltage gated ion channels: the K+ channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K+ channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants. PMID:25763487

Social networks among Indigenous peoples in Mexico.

PubMed

Skoufias, Emmanuel; Lunde, Trine; Patrinos, Harry Anthony

2010-01-01

We examine the extent to which social networks among indigenous peoples in Mexico have a significant effect on a variety of human capital investment and economic activities, such as school attendance and work among teenage boys and girls, and migration, welfare participation, employment status, occupation, and sector of employment among adult males and females. Using data from the 10 percent population sample of the 2000 Population and Housing Census of Mexico and the empirical strategy that Bertrand, Luttmer, and Mullainathan (2000) propose, which allows us to take into account the role of municipality and language group fixed effects, we confirm empirically that social network effects play an important role in the economic decisions of indigenous people, especially in rural areas. Our analysis also provides evidence that better access to basic services such as water and electricity increases the size and strength of network effects in rural areas.

Early alterations of social brain networks in young children with autism

PubMed Central

Kojovic, Nada; Rihs, Tonia Anahi; Jan, Reem Kais; Franchini, Martina; Plomp, Gijs; Vulliemoz, Serge; Eliez, Stephan; Michel, Christoph Martin; Schaer, Marie

2018-01-01

Social impairments are a hallmark of Autism Spectrum Disorders (ASD), but empirical evidence for early brain network alterations in response to social stimuli is scant in ASD. We recorded the gaze patterns and brain activity of toddlers with ASD and their typically developing peers while they explored dynamic social scenes. Directed functional connectivity analyses based on electrical source imaging revealed frequency specific network atypicalities in the theta and alpha frequency bands, manifesting as alterations in both the driving and the connections from key nodes of the social brain associated with autism. Analyses of brain-behavioural relationships within the ASD group suggested that compensatory mechanisms from dorsomedial frontal, inferior temporal and insular cortical regions were associated with less atypical gaze patterns and lower clinical impairment. Our results provide strong evidence that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD. PMID:29482718

Surface dynamics of voltage-gated ion channels.

PubMed

Heine, Martin; Ciuraszkiewicz, Anna; Voigt, Andreas; Heck, Jennifer; Bikbaev, Arthur

2016-07-03

Neurons encode information in fast changes of the membrane potential, and thus electrical membrane properties are critically important for the integration and processing of synaptic inputs by a neuron. These electrical properties are largely determined by ion channels embedded in the membrane. The distribution of most ion channels in the membrane is not spatially uniform: they undergo activity-driven changes in the range of minutes to days. Even in the range of milliseconds, the composition and topology of ion channels are not static but engage in highly dynamic processes including stochastic or activity-dependent transient association of the pore-forming and auxiliary subunits, lateral diffusion, as well as clustering of different channels. In this review we briefly discuss the potential impact of mobile sodium, calcium and potassium ion channels and the functional significance of this for individual neurons and neuronal networks.

Surface dynamics of voltage-gated ion channels

PubMed Central

Heine, Martin; Ciuraszkiewicz, Anna; Voigt, Andreas; Heck, Jennifer; Bikbaev, Arthur

2016-01-01

ABSTRACT Neurons encode information in fast changes of the membrane potential, and thus electrical membrane properties are critically important for the integration and processing of synaptic inputs by a neuron. These electrical properties are largely determined by ion channels embedded in the membrane. The distribution of most ion channels in the membrane is not spatially uniform: they undergo activity-driven changes in the range of minutes to days. Even in the range of milliseconds, the composition and topology of ion channels are not static but engage in highly dynamic processes including stochastic or activity-dependent transient association of the pore-forming and auxiliary subunits, lateral diffusion, as well as clustering of different channels. In this review we briefly discuss the potential impact of mobile sodium, calcium and potassium ion channels and the functional significance of this for individual neurons and neuronal networks. PMID:26891382

Activated carbon fiber composite as a new material for electrical and electrochemical applications

NASA Astrophysics Data System (ADS)

Nasr, Mohamed Fathy

Activated carbon fiber (ACF) is a microporous material consisting of three-dimensional network of micrographitic layers. The micrographitic edges have a considerable amount of active functional groups (such as -COOH, -OH, -CO-, -O-) and dangling bonds. The huge specific surface area (up to 3000 m2/g) is another important property of ACF. Exploitation of the high surface area and the reactivity of the functional groups of ACF, through incorporating or doping ACF with transition metal salts (M) and/or binder (B), was used to enhance the electrical properties of ACF. Such treatments created new interfaces such as (ACF/M, ACF/M/B, and ACF/B/M) through which an extra charge can be localized, transferred, or stored. This process can be of great benefit in energy storage devices such as supercapacitors for computer memory backup. In this work, activated carbon fiber nonwoven fabrics have been impregnated with different concentrations of organometallic Cu and Zn salts, a carbonaceous sot binder, or mixtures of both, followed by thermal treatment over a temperature range 300°C--900°C under an inert atmosphere. The use of carbonaceous sot as a binder has used in the study, is novel. Electrical measurements, current-voltage characterization, current-time relationship, as well as the relative permittivity and impedance of ACF composites, have been conducted. The electric double-layer capacitance of the as-received and the ACF composites were also evaluated.

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems 12/8/06 to 12/31/09

DTIC Science & Technology

2010-01-01

8/06 to 12/31/09. Qilian Liang Department of Electrical Engineering 416 Yates Street, Room 518 University of Texas at Arlington Arlington, TX 76019...Modeling in Foliage Environment Jing Liang and Qilian Liang, Senior Member, IEEE Department of Electrical Engineering University of Texas at Arlington E...32 46 of 816 NEW: Network-enabled Electronic Warfare for Target Recognition Qilian Liang Xiuzhen Cheng Sherwood W. Samn Dept of Electrical

Multiple mechanisms switch an electrically coupled, synaptically inhibited neuron between competing rhythmic oscillators.

PubMed

Gutierrez, Gabrielle J; O'Leary, Timothy; Marder, Eve

2013-03-06

Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patterns of coordination shown in the network as a function of the electrical coupling and inhibitory synapse strengths with the help of a novel visualization method that we call the "parameterscape." The hub neuron can be switched between the fast and slow oscillators by multiple network mechanisms, indicating that a given change in network state can be achieved by degenerate cellular mechanisms. These results have importance for interpreting experiments employing optogenetic, genetic, and pharmacological manipulations to understand circuit dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.

Electrical Coupling between the Myenteric Interstitial Cells of Cajal and Adjacent Muscle Layers in the Guinea-Pig Gastric Antrum

PubMed Central

Cousins, H M; Edwards, F R; Hickey, H; Hill, C E; Hirst, G D S

2003-01-01

Intracellular recordings were made from short segments of the muscular wall of the guinea-pig gastric antrum. Preparations were impaled using two independent microelectrodes, one positioned in the circular layer and the other either in the longitudinal layer, in the network of myenteric interstitial cells of Cajal (ICCmy) or in the circular layer. Cells in each layer displayed characteristic patterns of rhythmical activity, with the largest signals being generated by ICCmy. Current pulses injected into the circular muscle layer produced electrotonic potentials in each cell layer, indicating that the layers are electrically interconnected. The amplitudes of these electrotonic potentials were largest in the circular layer and smallest in the longitudinal layer. An analysis of electrical coupling between the three layers suggests that although the cells in each layer are well coupled to neighbouring cells, the coupling between either muscle layer and the network of ICCmy is relatively poor. The electrical connections between ICCmy and the circular layer did not rectify. In parallel immunohistochemical studies, the distribution of the connexins Cx40, Cx43 and Cx45 within the antral wall was determined. Only Cx43 was detected; it was widely distributed on ICCmy and throughout the circular smooth muscle layer, being concentrated around ICCIM, but was less abundant in the circular muscle layer immediately adjacent to ICCmy. Although the electrophysiological studies indicate that smooth muscle cells in the longitudinal muscle layer are electrically coupled to each other, none of the connexins examined were detected in this layer. PMID:12844505

Clean Cities 2015 Annual Metrics Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Caley; Singer, Mark

2016-12-01

The U.S. Department of Energy's (DOE's) Clean Cities program advances the nation's economic, environmental, and energy security by supporting local actions to cut petroleum use and greenhouse gas (GHG) emissions in transportation. A national network of nearly 100 Clean Cities coalitions, whose territory covers 80% of the U.S. population, brings together stakeholders in the public and private sectors to deploy alternative and renewable fuels, idle-reduction (IR) measures, fuel economy improvements, and new transportation technologies as they emerge. Each year, DOE asks Clean Cities coordinators to submit annual reports of their activities and accomplishments for the previous calendar year. Progress reportsmore » and information are submitted online as a function of the Alternative Fuels Data Center (AFDC) at the National Renewable Energy Laboratory (NREL). Coordinators report a range of information that characterize the membership, funding, projects, and activities of their coalitions. They also document activities in their region related to the development of refueling/charging infrastructure, sales of alternative fuels; deployment of alternative fuel vehicles (AFVs), plug-in electric vehicles (PEVs), hybrid electric vehicles (HEVs), and plug-in hybrid electric vehicles (PHEVs); idle reduction initiatives; fuel economy improvement activities; and programs to reduce vehicle miles traveled (VMT). NREL analyzes the data and translates them into petroleum-use and GHG emission reduction impacts, which are summarized in this report.« less

From cognitive networks to seizures: Stimulus evoked dynamics in a coupled cortical network

NASA Astrophysics Data System (ADS)

Lee, Jaejin; Ermentrout, Bard; Bodner, Mark

2013-12-01

Epilepsy is one of the most common neuropathologies worldwide. Seizures arising in epilepsy or in seizure disorders are characterized generally by uncontrolled spread of excitation and electrical activity to a limited region or even over the entire cortex. While it is generally accepted that abnormal excessive firing and synchronization of neuron populations lead to seizures, little is known about the precise mechanisms underlying human epileptic seizures, the mechanisms of transitions from normal to paroxysmal activity, or about how seizures spread. Further complication arises in that seizures do not occur with a single type of dynamics but as many different phenotypes and genotypes with a range of patterns, synchronous oscillations, and time courses. The concept of preventing, terminating, or modulating seizures and/or paroxysmal activity through stimulation of brain has also received considerable attention. The ability of such stimulation to prevent or modulate such pathological activity may depend on identifiable parameters. In this work, firing rate networks with inhibitory and excitatory populations were modeled. Network parameters were chosen to model normal working memory behaviors. Two different models of cognitive activity were developed. The first model consists of a single network corresponding to a local area of the brain. The second incorporates two networks connected through sparser recurrent excitatory connectivity with transmission delays ranging from approximately 3 ms within local populations to 15 ms between populations residing in different cortical areas. The effect of excitatory stimulation to activate working memory behavior through selective persistent activation of populations is examined in the models, and the conditions and transition mechanisms through which that selective activation breaks down producing spreading paroxysmal activity and seizure states are characterized. Specifically, we determine critical parameters and architectural changes that produce the different seizure dynamics in the networks. This provides possible mechanisms for seizure generation. Because seizures arise as attractors in a multi-state system, the system may possibly be returned to its baseline state through some particular stimulation. The ability of stimulation to terminate seizure dynamics in the local and distributed models is studied. We systematically examine when this may occur and the form of the stimulation necessary for the range of seizure dynamics. In both the local and distributed network models, termination is possible for all seizure types observed by stimulation possessing some particular configuration of spatial and temporal characteristics.

Long-lasting desynchronization in rat hippocampal slice induced by coordinated reset stimulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tass, P. A.; Barnikol, U. B.; Department of Stereotaxic and Functional Neurosurgery, University of Cologne, D-50931 Cologne

2009-07-15

In computational models it has been shown that appropriate stimulation protocols may reshape the connectivity pattern of neural or oscillator networks with synaptic plasticity in a way that the network learns or unlearns strong synchronization. The underlying mechanism is that a network is shifted from one attractor to another, so that long-lasting stimulation effects are caused which persist after the cessation of stimulation. Here we study long-lasting effects of multisite electrical stimulation in a rat hippocampal slice rendered epileptic by magnesium withdrawal. We show that desynchronizing coordinated reset stimulation causes a long-lasting desynchronization between hippocampal neuronal populations together with amore » widespread decrease in the amplitude of the epileptiform activity. In contrast, periodic stimulation induces a long-lasting increase in both synchronization and amplitude.« less

A multi-criteria decision aid methodology to design electric vehicles public charging networks

NASA Astrophysics Data System (ADS)

Raposo, João; Rodrigues, Ana; Silva, Carlos; Dentinho, Tomaz

2015-05-01

This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city's urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE's characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

Passive Responses Resembling Action Potentials: A Device for the Classroom

ERIC Educational Resources Information Center

Newman, Ian A.; Pickard, Barbara G.

1975-01-01

Describes the construction and operation of a network of entirely passive electrical components that gives a response to an electrical shock similar to an action potential. The network of resistors, capacitors, and diodes was developed to produce responses that would mimic those observed, for example, when a dark-grown pea epicotyl is shocked…

Transient Analysis Generator /TAG/ simulates behavior of large class of electrical networks

NASA Technical Reports Server (NTRS)

Thomas, W. J.

1967-01-01

Transient Analysis Generator program simulates both transient and dc steady-state behavior of a large class of electrical networks. It generates a special analysis program for each circuit described in an easily understood and manipulated programming language. A generator or preprocessor and a simulation system make up the TAG system.

Analysis of electrical tomography sensitive field based on multi-terminal network and electric field

NASA Astrophysics Data System (ADS)

He, Yongbo; Su, Xingguo; Xu, Meng; Wang, Huaxiang

2010-08-01

Electrical tomography (ET) aims at the study of the conductivity/permittivity distribution of the interested field non-intrusively via the boundary voltage/current. The sensor is usually regarded as an electric field, and finite element method (FEM) is commonly used to calculate the sensitivity matrix and to optimize the sensor architecture. However, only the lumped circuit parameters can be measured by the data acquisition electronics, it's very meaningful to treat the sensor as a multi terminal network. Two types of multi terminal network with common node and common loop topologies are introduced. Getting more independent measurements and making more uniform current distribution are the two main ways to minimize the inherent ill-posed effect. By exploring the relationships of network matrixes, a general formula is proposed for the first time to calculate the number of the independent measurements. Additionally, the sensitivity distribution is analyzed with FEM. As a result, quasi opposite mode, an optimal single source excitation mode, that has the advantages of more uniform sensitivity distribution and more independent measurements, is proposed.

Application of neural network for real-time measurement of electrical resistivity in cold crucible

NASA Astrophysics Data System (ADS)

Votava, Pavel; Poznyak, Igor

2017-08-01

The article describes use of an Induction furnace with cold crucible as a tool for real-time measurement of a melted material electrical resistivity. The measurement is based on an inverse problem solution of a 2D mathematical model, possibly implementable in a microcontroller or a FPGA in a form of a neural network. The 2D mathematical model results has been provided as a training set for the neural network. At the end, the implementation results are discussed together with uncertainty of measurement, which is done by the neural network implementation itself.

Noise-assisted energy transport in electrical oscillator networks with off-diagonal dynamical disorder.

PubMed

León-Montiel, Roberto de J; Quiroz-Juárez, Mario A; Quintero-Torres, Rafael; Domínguez-Juárez, Jorge L; Moya-Cessa, Héctor M; Torres, Juan P; Aragón, José L

2015-11-27

Noise is generally thought as detrimental for energy transport in coupled oscillator networks. However, it has been shown that for certain coherently evolving systems, the presence of noise can enhance, somehow unexpectedly, their transport efficiency; a phenomenon called environment-assisted quantum transport (ENAQT) or dephasing-assisted transport. Here, we report on the experimental observation of such effect in a network of coupled electrical oscillators. We demonstrate that by introducing stochastic fluctuations in one of the couplings of the network, a relative enhancement in the energy transport efficiency of 22.5 ± 3.6% can be observed.

Transparent, conformable, active multielectrode array using organic electrochemical transistors.

PubMed

Lee, Wonryung; Kim, Dongmin; Matsuhisa, Naoji; Nagase, Masae; Sekino, Masaki; Malliaras, George G; Yokota, Tomoyuki; Someya, Takao

2017-10-03

Mechanically flexible active multielectrode arrays (MEA) have been developed for local signal amplification and high spatial resolution. However, their opaqueness limited optical observation and light stimulation during use. Here, we show a transparent, ultraflexible, and active MEA, which consists of transparent organic electrochemical transistors (OECTs) and transparent Au grid wirings. The transparent OECT is made of Au grid electrodes and has shown comparable performance with OECTs with nontransparent electrodes/wirings. The transparent active MEA realizes the spatial mapping of electrocorticogram electrical signals from an optogenetic rat with 1-mm spacing and shows lower light artifacts than noise level. Our active MEA would open up the possibility of precise investigation of a neural network system with direct light stimulation.

Introduction of a new opto-electrical phase-locked loop in CMOS technology: the PMD-PLL

NASA Astrophysics Data System (ADS)

Ringbeck, Thorsten; Schwarte, Rudolf; Buxbaum, Bernd

1999-12-01

The huge and increasing need of information in the industrial world demands an enormous potential of bandwidth in telecommunication systems. Optical communication provides all participants with the whole spectrum of digital services like videophone, cable TV, video conferencing and online services. Especially fast and low cost opto-electrical receivers are badly needed in order to expand fiber networks to every home (FTTH--fiber to the home or FTTD--fiber to the desk, respectively). This paper proposes a new receiver structure which is designed to receiver optical data which are encoded by code division multiple access techniques (CDMA). For data recovery in such CDMA networks phase locked loops (PLL) are needed, which synchronize the local oscillator with the incoming clock. In optical code division multiple access networks these PLLs could be realized either with an electrical PLL after opto-electrical converting or directly in the optical path with a pure optical PLL.

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less

The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

DOE PAGES

Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

2016-11-12

Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less

A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

PubMed

Mailloux, Shay; Halámek, Jan; Katz, Evgeny

2014-03-07

A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

Electrical network method for the thermal or structural characterization of a conducting material sample or structure

DOEpatents

Ortiz, Marco G.

1993-01-01

A method for modeling a conducting material sample or structure system, as an electrical network of resistances in which each resistance of the network is representative of a specific physical region of the system. The method encompasses measuring a resistance between two external leads and using this measurement in a series of equations describing the network to solve for the network resistances for a specified region and temperature. A calibration system is then developed using the calculated resistances at specified temperatures. This allows for the translation of the calculated resistances to a region temperature. The method can also be used to detect and quantify structural defects in the system.

Electrical network method for the thermal or structural characterization of a conducting material sample or structure

DOEpatents

Ortiz, M.G.

1993-06-08

A method for modeling a conducting material sample or structure system, as an electrical network of resistances in which each resistance of the network is representative of a specific physical region of the system. The method encompasses measuring a resistance between two external leads and using this measurement in a series of equations describing the network to solve for the network resistances for a specified region and temperature. A calibration system is then developed using the calculated resistances at specified temperatures. This allows for the translation of the calculated resistances to a region temperature. The method can also be used to detect and quantify structural defects in the system.

Solvated dissipative electro-elastic network model of hydrated proteins

NASA Astrophysics Data System (ADS)

Martin, Daniel

2013-03-01

Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the a the active site.

Solvated dissipative electro-elastic network model of hydrated proteins

NASA Astrophysics Data System (ADS)

Martin, Daniel R.; Matyushov, Dmitry V.

2012-10-01

Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the active site of the protein.

All Optical Solution for Free Space Optics Point to Point Links

NASA Astrophysics Data System (ADS)

Hirayama, Daigo

Optical network systems are quickly replacing electrical network systems. Optical systems provide better bandwidth, faster data rates, better security to networks, and are less susceptible to noise. Free Space Optics (systems) still rely on numerous electrical systems such as the modulation and demodulation systems to convert optical signals to electrical signals for the transmitting laser. As the concept of the entirely optical network becomes more realizable, the electrical components of the FSO system will become a hindrance to communications. The focus of this thesis is to eliminate the electrical devices for the FSO point to point links by replacing them with optical devices. The concept is similar to an extended beam connector. However, where an extended beam connector deals with a gap of a few millimeters, my focus looks at distances from 100 meters to one kilometer. The aim is to achieve a detectable signal of 1nW at a distance of 500 meters at a wavelength of 1500-1600nm. This leads to application in building to building links and mobile networks. The research examines the design of the system in terms of generating the wave, the properties of the fiber feeding the wave, and the power necessary to achieve a usable distance. The simulation is executed in Code V by Synopsys, which is an industry standard to analyze optical systems. A usable device with a range of around 500m was achieved with an input power of 1mW. The approximations of the phase function resulted in some aberrations to the profile of the beam, but were not very detrimental to the function of the device. The removal of electrical devices from a FSO point to point link decreased the power used to establish the link and decreased the cost.

Functional Connectivity in Islets of Langerhans from Mouse Pancreas Tissue Slices

PubMed Central

Stožer, Andraž; Gosak, Marko; Dolenšek, Jurij; Perc, Matjaž; Marhl, Marko; Rupnik, Marjan Slak; Korošak, Dean

2013-01-01

We propose a network representation of electrically coupled beta cells in islets of Langerhans. Beta cells are functionally connected on the basis of correlations between calcium dynamics of individual cells, obtained by means of confocal laser-scanning calcium imaging in islets from acute mouse pancreas tissue slices. Obtained functional networks are analyzed in the light of known structural and physiological properties of islets. Focusing on the temporal evolution of the network under stimulation with glucose, we show that the dynamics are more correlated under stimulation than under non-stimulated conditions and that the highest overall correlation, largely independent of Euclidean distances between cells, is observed in the activation and deactivation phases when cells are driven by the external stimulus. Moreover, we find that the range of interactions in networks during activity shows a clear dependence on the Euclidean distance, lending support to previous observations that beta cells are synchronized via calcium waves spreading throughout islets. Most interestingly, the functional connectivity patterns between beta cells exhibit small-world properties, suggesting that beta cells do not form a homogeneous geometric network but are connected in a functionally more efficient way. Presented results provide support for the existing knowledge of beta cell physiology from a network perspective and shed important new light on the functional organization of beta cell syncitia whose structural topology is probably not as trivial as believed so far. PMID:23468610

Gap junctions between interneurons are required for normal spatial coding in the hippocampus and short-term spatial memory

PubMed Central

Allen, Kevin; Fuchs, Elke C.; Jaschonek, Hannah; Bannerman, David M.; Monyer, Hannah

2011-01-01

Gap junctions containing connexin-36 (Cx36) electrically couple interneurons in many brain regions and synchronize their activity. We used Cx36 knockout mice (Cx36−/−) to study the importance of electrical coupling between interneurons for spatial coding in the hippocampus and for different forms of hippocampus-dependent spatial memory. Recordings in behaving mice revealed that the spatial selectivity of hippocampal pyramidal neurons was reduced and less stable in Cx36−/− mice. Altered network activity was reflected in slower theta oscillations in the mutants. Temporal coding, assessed by determining the presence and characteristics of theta phase precession, had different dynamics in Cx36−/− mice compared to controls. At the behavioral level, Cx36−/− mice displayed impaired short-term spatial memory but normal spatial reference memory. These results highlight the functional role of electrically coupled interneurons for spatial coding and cognition. Moreover, they suggest that the precise spatial selectivity of place cells is not essential for normal performance on spatial tasks assessing associative long-term memory. PMID:21525295

Lithium conductivity in glasses of the Li2O-Al2O3-SiO2 system.

PubMed

Ross, Sebastian; Welsch, Anna-Maria; Behrens, Harald

2015-01-07

To improve the understanding of Li-dynamics in oxide glasses, i.e. the effect of [AlO4](-) tetrahedra and non-bridging oxygens on the potential landscape, electrical conductivity of seven fully polymerized and partly depolymerized lithium aluminosilicate glasses was investigated using impedance spectroscopy (IS). Lithium is the only mobile particle in these materials. Data derived from IS, i.e. activation energies, pre-exponential factors and diffusivities for lithium, are interpreted in light of Raman spectroscopic analyses of local structures in order to identify building units, which are crucial for lithium dynamics and migration. In polymerized glasses (compositional join LiAlSiO4-LiAlSi4O10) the direct current (DC) electrical conductivity continuously increases with increasing lithium content while lithium diffusivity is not affected by the Al/Si ratio in the glasses. Hence, the increase in electrical conductivity can be solely assigned to lithium concentration in the glasses. An excess of Li with respect to Al, i.e. the introduction of non-bridging oxygen into the network, causes a decrease in lithium mobility in the glasses. Activation energies in polymerized glasses (66 to 70 kJ mol(-1)) are significantly lower than those in depolymerized networks (76 to 78 kJ mol(-1)) while pre-exponential factors are nearly constant across all compositions. Comparison of the data with results for lithium silicates from the literature indicates a minimum in lithium diffusivity for glasses containing both aluminium tetrahedra and non-bridging oxygens. The findings allow a prediction of DC conductivity for a large variety of lithium aluminosilicate glass compositions.

Accelerated reliability testing of highly aligned single-walled carbon nanotube networks subjected to DC electrical stressing.

PubMed

Strus, Mark C; Chiaramonti, Ann N; Kim, Young Lae; Jung, Yung Joon; Keller, Robert R

2011-07-01

We investigate the electrical reliability of nanoscale lines of highly aligned, networked, metallic/semiconducting single-walled carbon nanotubes (SWCNTs) fabricated through a template-based fluidic assembly process. We find that these SWCNT networks can withstand DC current densities larger than 10 MA cm(-2) for several hours and, in some cases, several days. We develop test methods that show that the degradation rate, failure predictability and total device lifetime can be linked to the initial resistance. Scanning electron and transmission electron microscopy suggest that fabrication variability plays a critical role in the rate of degradation, and we offer an empirical method of quickly determining the long-term performance of a network. We find that well-fabricated lines subject to constant electrical stress show a linear accumulation of damage reminiscent of electromigration in metallic interconnects, and we explore the underlying physical mechanisms that could cause such behavior.

High-performance, polymer-based direct cellular interfaces for electrical stimulation and recording

NASA Astrophysics Data System (ADS)

Kim, Seong-Min; Kim, Nara; Kim, Youngseok; Baik, Min-Seo; Yoo, Minsu; Kim, Dongyoon; Lee, Won-June; Kang, Dong-Hee; Kim, Sohee; Lee, Kwanghee; Yoon, Myung-Han

2018-04-01

Due to the trade-off between their electrical/electrochemical performance and underwater stability, realizing polymer-based, high-performance direct cellular interfaces for electrical stimulation and recording has been very challenging. Herein, we developed transparent and conductive direct cellular interfaces based on a water-stable, high-performance poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) film via solvent-assisted crystallization. The crystallized PEDOT:PSS on a polyethylene terephthalate (PET) substrate exhibited excellent electrical/electrochemical/optical characteristics, long-term underwater stability without film dissolution/delamination, and good viability for primarily cultured cardiomyocytes and neurons over several weeks. Furthermore, the highly crystallized, nanofibrillar PEDOT:PSS networks enabled dramatically enlarged surface areas and electrochemical activities, which were successfully employed to modulate cardiomyocyte beating via direct electrical stimulation. Finally, the high-performance PEDOT:PSS layer was seamlessly incorporated into transparent microelectrode arrays for efficient, real-time recording of cardiomyocyte action potentials with a high signal fidelity. All these results demonstrate the strong potential of crystallized PEDOT:PSS as a crucial component for a variety of versatile bioelectronic interfaces.

Functional Evaluation of Biological Neurotoxins in Networked Cultures of Stem Cell-derived Central Nervous System Neurons

PubMed Central

Hubbard, Kyle; Beske, Phillip; Lyman, Megan; McNutt, Patrick

2015-01-01

Therapeutic and mechanistic studies of the presynaptically targeted clostridial neurotoxins (CNTs) have been limited by the need for a scalable, cell-based model that produces functioning synapses and undergoes physiological responses to intoxication. Here we describe a simple and robust method to efficiently differentiate murine embryonic stem cells (ESCs) into defined lineages of synaptically active, networked neurons. Following an 8 day differentiation protocol, mouse embryonic stem cell-derived neurons (ESNs) rapidly express and compartmentalize neurotypic proteins, form neuronal morphologies and develop intrinsic electrical responses. By 18 days after differentiation (DIV 18), ESNs exhibit active glutamatergic and γ-aminobutyric acid (GABA)ergic synapses and emergent network behaviors characterized by an excitatory:inhibitory balance. To determine whether intoxication with CNTs functionally antagonizes synaptic neurotransmission, thereby replicating the in vivo pathophysiology that is responsible for clinical manifestations of botulism or tetanus, whole-cell patch clamp electrophysiology was used to quantify spontaneous miniature excitatory post-synaptic currents (mEPSCs) in ESNs exposed to tetanus neurotoxin (TeNT) or botulinum neurotoxin (BoNT) serotypes /A-/G. In all cases, ESNs exhibited near-complete loss of synaptic activity within 20 hr. Intoxicated neurons remained viable, as demonstrated by unchanged resting membrane potentials and intrinsic electrical responses. To further characterize the sensitivity of this approach, dose-dependent effects of intoxication on synaptic activity were measured 20 hr after addition of BoNT/A. Intoxication with 0.005 pM BoNT/A resulted in a significant decrement in mEPSCs, with a median inhibitory concentration (IC50) of 0.013 pM. Comparisons of median doses indicate that functional measurements of synaptic inhibition are faster, more specific and more sensitive than SNARE cleavage assays or the mouse lethality assay. These data validate the use of synaptically coupled, stem cell-derived neurons for the highly specific and sensitive detection of CNTs. PMID:25742030

Proceedings of the Workshop on Mobility and Control in Challenging Environments

DTIC Science & Technology

2007-09-20

1.18 h (V) -3.48 Electronic Nervous Systems Activating Nitinol With Electronic Neurons Controlling Walking With EN Networks ele dep prot ret forward...command backward command Myomorphic Actuators •Artificial Muscle Nitinol : 50/50 Alloy of Nickel and Titanium. • Two stable crystalline states • State...an electrical current through it causing conversion to austenite and shorteningText Kevlar “Tendon” Crimp Connector Teflon Coated Nitinol Current

Computer-Assisted Monitoring Of A Complex System

NASA Technical Reports Server (NTRS)

Beil, Bob J.; Mickelson, Eric M.; Sterritt, John M.; Costantino, Rob W.; Houvener, Bob C.; Super, Mike A.

1995-01-01

Propulsion System Advisor (PSA) computer-based system assists engineers and technicians in analyzing masses of sensory data indicative of operating conditions of space shuttle propulsion system during pre-launch and launch activities. Designed solely for monitoring; does not perform any control functions. Although PSA developed for highly specialized application, serves as prototype of noncontrolling, computer-based subsystems for monitoring other complex systems like electric-power-distribution networks and factories.

[Electrical burns suffered by copper thieves].

PubMed

Belmir, R; Fejjal, N; Achbouk, H; El Mazouz, S; Gharib, N; Abassi, A; Belmahi, A

2011-06-30

Thefts of copper appear to have been on the increase for some time owing to its high resale price. This has led to an increase in the number of high-voltage electrical accidents (HVEA). Such accidents are very serious because they cause deep burns along the neurovascular axis. A report is presented describing a series of nine patients presenting HVEA admitted to the Ibn Sina Hospital Plastic Surgery and Burns Division in Rabat, Morocco, with a study of the epidemiological, clinical, and therapeutic aspects. The patients all belonged to the young and active sector of the population. The burns were secondary to contact with high-voltage cables occurring during the attempted stealing of copper by stripping electric conductors in transformers (67% of the cases) and in attempts to cut overhead lines supplying electric trains on the railway network (33%). Electrothermal treatment of the lesions required repeated surgery with amputation and disarticulation of necrotic limb segments (67% of the cases), the consequences of which were marked by disabling functional sequelae. Preventing this type of HVEA remains fundamental.

Development of superconducting power devices in Europe

NASA Astrophysics Data System (ADS)

Tixador, Pascal

2010-11-01

Europe celebrated last year (2008) the 100-year anniversary of the first liquefaction of helium by H. Kammerling Onnes in Leiden. It led to the discovery of superconductivity in 1911. Europe is still active in the development of superconducting (SC) devices. The discovery of high critical temperature materials in 1986, again in Europe, has opened a lot of opportunities for SC devices by broking the 4 K cryogenic bottleneck. Electric networks experience deep changes due to the emergence of dispersed generation (renewable among other) and to the advances in ICT (Information Communication Technologies). The networks of the future will be "smart grids". Superconductivity will offer "smart" devices for these grids like FCL (Fault Current Limiter) or VLI (Very Low Inductance) cable and would certainly play an important part. Superconductivity also will participate to the required sustainable development by lowering the losses and enhancing the mass specific powers. Different SC projects in Europe will be presented (Cable, FCL, SMES, Flywheel and Electrical Machine) but the description is not exhaustive. Nexans has commercialized the first two FCLs without public funds in the European grid (UK and Germany). The Amsterdam HTS cable is an exciting challenge in term of losses for long SC cables. European companies (Nexans, Air Liquide, Siemens, Converteam, …) are also very active for projects outside Europe (LIPA, DOE FCL, …).

Electrification processes and lightning generation in volcanic plumes—observations from recent eruptions

NASA Astrophysics Data System (ADS)

Van Eaton, A. R.; Smith, C. M.; Schneider, D. J.

2017-12-01

Lightning in volcanic plumes provides a promising way to monitor ash-producing eruptions and investigate their dynamics. Among the many methods of lightning detection are global networks of sensors that detect electromagnetic radiation in the very low frequency band (3-30 kHz), including the World Wide Lightning Location Network. These radio waves propagate thousands of kilometers at the speed of light, providing an opportunity for rapid detection of explosive volcanism anywhere in the world. Lightning is particularly valuable as a near real-time indicator of ash-rich plumes that are hazardous to aviation. Yet many fundamental questions remain. Under what conditions does electrical activity in volcanic plumes become powerful, detectable lightning? And conversely, can we use lightning to illuminate eruption processes and hazards? This study highlights recent observations from the eruptions of Redoubt (Alaska, 2009), Kelud (Indonesia, 2014), Calbuco (Chile, 2015), and Bogoslof (Alaska, 2017) to examine volcanic lighting from a range of eruption styles (Surtseyan to Plinian) and mass eruption rates from 10^5 to 10^8 kg/s. It is clear that lightning stroke-rates do not scale in a simple way with mass eruption rate or plume height across different eruptions. However, relative changes in electrical activity through individual eruptions relate to changes in eruptive intensity, ice content, and volcanic plume processes (fall vs. flow).

Forecasting of the electrical actuators condition using stator’s current signals

NASA Astrophysics Data System (ADS)

Kruglova, T. N.; Yaroshenko, I. V.; Rabotalov, N. N.; Melnikov, M. A.

2017-02-01

This article describes a forecasting method for electrical actuators realized through the combination of Fourier transformation and neural network techniques. The method allows finding the value of diagnostic functions in the iterating operating cycle and the number of operational cycles in time before the BLDC actuator fails. For forecasting of the condition of the actuator, we propose a hierarchical structure of the neural network aiming to reduce the training time of the neural network and improve estimation accuracy.

An introduction to neural networks surgery, a field of neuromodulation which is based on advances in neural networks science and digitised brain imaging.

PubMed

Sakas, D E; Panourias, I G; Simpson, B A

2007-01-01

Operative Neuromodulation is the field of altering electrically or chemically the signal transmission in the nervous system by implanted devices in order to excite, inhibit or tune the activities of neurons or neural networks and produce therapeutic effects. The present article reviews relevant literature on procedures or devices applied either in contact with the cerebral cortex or cranial nerves or in deep sites inside the brain in order to treat various refractory neurological conditions such as: a) chronic pain (facial, somatic, deafferentation, phantom limb), b) movement disorders (Parkinson's disease, dystonia, Tourette syndrome), c) epilepsy, d) psychiatric disease, e) hearing deficits, and f) visual loss. These data indicate that in operative neuromodulation, a new field emerges that is based on neural networks research and on advances in digitised stereometric brain imaging which allow precise localisation of cerebral neural networks and their relay stations; this field can be described as Neural networks surgery because it aims to act extrinsically or intrinsically on neural networks and to alter therapeutically the neural signal transmission with the use of implantable electrical or electronic devices. The authors also review neurotechnology literature relevant to neuroengineering, nanotechnologies, brain computer interfaces, hybrid cultured probes, neuromimetics, neuroinformatics, neurocomputation, and computational neuromodulation; the latter field is dedicated to the study of the biophysical and mathematical characteristics of electrochemical neuromodulation. The article also brings forward particularly interesting lines of research such as the carbon nanofibers electrode arrays for simultaneous electrochemical recording and stimulation, closed-loop systems for responsive neuromodulation, and the intracortical electrodes for restoring hearing or vision. The present review of cerebral neuromodulatory procedures highlights the transition from the conventional neurosurgery of resective or ablative techniques to a highly selective "surgery of networks". The dynamics of the convergence of the above biomedical and technological fields with biological restorative approaches have important implications for patients with severe neurological disorders.

Chronotype and seasonality: morningness is associated with lower seasonal mood and behavior changes in the Old Order Amish.

PubMed

Zhang, Layan; Evans, Daniel S; Raheja, Uttam K; Stephens, Sarah H; Stiller, John W; Reeves, Gloria M; Johnson, Mary; Ryan, Kathleen A; Weizel, Nancy; Vaswani, Dipika; McLain, Hassan; Shuldiner, Alan R; Mitchell, Braxton D; Hsueh, Wen-Chi; Snitker, Soren; Postolache, Teodor T

2015-03-15

Several studies documented that lower scores on the Morningness-Eveningness Questionnaire (MEQ) are associated with a higher global seasonality of mood (GSS). As for the Modern Man artificial lighting predominantly extends evening activity and exposure to light, and as evening bright light phase is known to delay circadian rhythms, this chronic exposure could potentially lead to both lower Morningness as well as higher GSS. The aim of the study was to investigate if the MEQ-GSS relationship holds in the Old Order Amish of Lancaster County, PA, a population that does not use network electrical light. 489 Old Order Amish adults (47.6% women), with average (SD) age of 49.7 (14.2) years, completed both the Seasonal Pattern Assessment Questionnaire (SPAQ) for the assessment of GSS, and MEQ. Associations between GSS scores and MEQ scores were analyzed using linear models, accounting for age, gender and relatedness by including the relationship matrix in the model as a random effect. GSS was inversely associated with MEQ scores (p=0.006, adjusted). include a potential recall bias associated with self-report questionnaires and no actual light exposure measurements. We confirmed the previously reported inverse association between MEQ scores and lower seasonality of mood, for the first time in a population that does not use home network electrical lighting. This result suggests that the association is not a byproduct of exposure to network electric light, and calls for additional research to investigate mechanisms by which Morningness is negatively associated with seasonality. Published by Elsevier B.V.

The response of thunderstorms and lightning to smoke from Amazonian fires

NASA Astrophysics Data System (ADS)

Altaratz, Orit; Koren, Ilan; Yair, Yoav; Price, Colin

2010-05-01

The effects of man-made aerosols on clouds are long believed to be a key component for model predictions of climate change, yet are one of the least understood. High aerosol concentrations can change the convection intensity and hence the electrical activity of thunderclouds. Focusing on the Amazon dry season in Brazil, where thousands of man-made forest fires inject smoke into the atmosphere, we studied the aerosol effects on thunderclouds and lightning. We used the ground-based World-Wide Lightning Location Network (WWLLN) measurements together with Aqua-MODIS remotely-sensed aerosol and cloud data to study the relationship between aerosol loading and lightning flash occurrence. We present evidence for the transition between two regimes, representing opposing effects of aerosols on clouds. The first is the microphysical effect which is manifested in an increase in convective intensity (and therefore in electrical activity), followed by the radiative effect that becomes dominant with the increase in aerosol loading leading to a decrease in convective intensity, manifested in lower lightning activity.

Stability Enhancement of Silver Nanowire Networks with Conformal ZnO Coatings Deposited by Atmospheric Pressure Spatial Atomic Layer Deposition.

PubMed

Khan, Afzal; Nguyen, Viet Huong; Muñoz-Rojas, David; Aghazadehchors, Sara; Jiménez, Carmen; Nguyen, Ngoc Duy; Bellet, Daniel

2018-06-06

Silver nanowire (AgNW) networks offer excellent electrical and optical properties and have emerged as one of the most attractive alternatives to transparent conductive oxides to be used in flexible optoelectronic applications. However, AgNW networks still suffer from chemical, thermal, and electrical instabilities, which in some cases can hinder their efficient integration as transparent electrodes in devices such as solar cells, transparent heaters, touch screens, and organic light emitting diodes. We have used atmospheric pressure spatial atomic layer deposition (AP-SALD) to fabricate hybrid transparent electrode materials in which the AgNW network is protected by a conformal thin layer of zinc oxide. The choice of AP-SALD allows us to maintain the low-cost and scalable processing of AgNW-based transparent electrodes. The effects of the ZnO coating thickness on the physical properties of AgNW networks are presented. The composite electrodes show a drastic enhancement of both thermal and electrical stabilities. We found that bare AgNWs were stable only up to 300 °C when subjected to thermal ramps, whereas the ZnO coating improved the stability up to 500 °C. Similarly, ZnO-coated AgNWs exhibited an increase of 100% in electrical stability with respect to bare networks, withstanding up to 18 V. A simple physical model shows that the origin of the stability improvement is the result of hindered silver atomic diffusion thanks to the presence of the thin oxide layer and the quality of the interfaces of hybrid electrodes. The effects of ZnO coating on both the network adhesion and optical transparency are also discussed. Finally, we show that the AP-SALD ZnO-coated AgNW networks can be effectively used as very stable transparent heaters.

An electric-analog simulation of elliptic partial differential equations using finite element theory

USGS Publications Warehouse

Franke, O.L.; Pinder, G.F.; Patten, E.P.

1982-01-01

Elliptic partial differential equations can be solved using the Galerkin-finite element method to generate the approximating algebraic equations, and an electrical network to solve the resulting matrices. Some element configurations require the use of networks containing negative resistances which, while physically realizable, are more expensive and time-consuming to construct. ?? 1982.

Control of a solar-energy-supplied electrical-power system without intermediate circuitry

NASA Astrophysics Data System (ADS)

Leistner, K.

A computer control system is developed for electric-power systems comprising solar cells and small numbers of users with individual centrally controlled converters (and storage facilities when needed). Typical system structures are reviewed; the advantages of systems without an intermediate network are outlined; the demands on a control system in such a network (optimizing generator working point and power distribution) are defined; and a flexible modular prototype system is described in detail. A charging station for lead batteries used in electric automobiles is analyzed as an example. The power requirements of the control system (30 W for generator control and 50 W for communications and distribution control) are found to limit its use to larger networks.

Motorized CPM/CAM physiotherapy device with sliding-mode Fuzzy Neural Network control loop.

PubMed

Ho, Hung-Jung; Chen, Tien-Chi

2009-11-01

Continuous passive motion (CPM) and controllable active motion (CAM) physiotherapy devices promote rehabilitation of damaged joints. This paper presents a computerized CPM/CAM system that obviates the need for mechanical resistance devices such as springs. The system is controlled by a computer which performs sliding-mode Fuzzy Neural Network (FNN) calculations online. CAM-type resistance force is generated by the active performance of an electric motor which is controlled so as to oppose the motion of the patient's leg. A force sensor under the patient's foot on the device pedal provides data for feedback in a sliding-mode FNN control loop built around the motor. Via an active impedance control feedback system, the controller drives the motor to behave similarly to a damped spring by generating and controlling the amplitude and direction of the pedal force in relation to the patient's leg. Experiments demonstrate the high sensitivity and speed of the device. The PC-based feedback nature of the control loop means that sophisticated auto-adaptable CPM/CAM custom-designed physiotherapy becomes possible. The computer base also allows extensive data recording, data analysis and network-connected remote patient monitoring.

A microfluidic platform for controlled biochemical stimulation of twin neuronal networks.

PubMed

Biffi, Emilia; Piraino, Francesco; Pedrocchi, Alessandra; Fiore, Gianfranco B; Ferrigno, Giancarlo; Redaelli, Alberto; Menegon, Andrea; Rasponi, Marco

2012-06-01

Spatially and temporally resolved delivery of soluble factors is a key feature for pharmacological applications. In this framework, microfluidics coupled to multisite electrophysiology offers great advantages in neuropharmacology and toxicology. In this work, a microfluidic device for biochemical stimulation of neuronal networks was developed. A micro-chamber for cell culturing, previously developed and tested for long term neuronal growth by our group, was provided with a thin wall, which partially divided the cell culture region in two sub-compartments. The device was reversibly coupled to a flat micro electrode array and used to culture primary neurons in the same microenvironment. We demonstrated that the two fluidically connected compartments were able to originate two parallel neuronal networks with similar electrophysiological activity but functionally independent. Furthermore, the device allowed to connect the outlet port to a syringe pump and to transform the static culture chamber in a perfused one. At 14 days invitro, sub-networks were independently stimulated with a test molecule, tetrodotoxin, a neurotoxin known to block action potentials, by means of continuous delivery. Electrical activity recordings proved the ability of the device configuration to selectively stimulate each neuronal network individually. The proposed microfluidic approach represents an innovative methodology to perform biological, pharmacological, and electrophysiological experiments on neuronal networks. Indeed, it allows for controlled delivery of substances to cells, and it overcomes the limitations due to standard drug stimulation techniques. Finally, the twin network configuration reduces biological variability, which has important outcomes on pharmacological and drug screening.

The Local Structure of Globalization. The Network Dynamics of Foreign Direct Investments in the International Electricity Industry

NASA Astrophysics Data System (ADS)

Koskinen, Johan; Lomi, Alessandro

2013-05-01

We study the evolution of the network of foreign direct investment (FDI) in the international electricity industry during the period 1994-2003. We assume that the ties in the network of investment relations between countries are created and deleted in continuous time, according to a conditional Gibbs distribution. This assumption allows us to take simultaneously into account the aggregate predictions of the well-established gravity model of international trade as well as local dependencies between network ties connecting the countries in our sample. According to the modified version of the gravity model that we specify, the probability of observing an investment tie between two countries depends on the mass of the economies involved, their physical distance, and the tendency of the network to self-organize into local configurations of network ties. While the limiting distribution of the data generating process is an exponential random graph model, we do not assume the system to be in equilibrium. We find evidence of the effects of the standard gravity model of international trade on evolution of the global FDI network. However, we also provide evidence of significant dyadic and extra-dyadic dependencies between investment ties that are typically ignored in available research. We show that local dependencies between national electricity industries are sufficient for explaining global properties of the network of foreign direct investments. We also show, however, that network dependencies vary significantly over time giving rise to a time-heterogeneous localized process of network evolution.

Effect of the mechanical deformation on the electrical properties of the polymer/CNT fiber

NASA Astrophysics Data System (ADS)

Cho, Hyun Woo; Sung, Bong June; Nano-Bio Computational Chemistry Laboratory Team

2014-03-01

We elucidate the effect of the mechanical deformation on the electrical properties of the polymer/CNT fiber. The conductive polymer fiber has drawn a great attention for its potential application to a stretchable electronics such as wearable devices and artificial muscles, etc. However, the electrical conductivity of the polymer-based stretchable electronics decreases significantly during the deformation, which may limit the applicability of the polymer/CNT fiber for the stretchable electronics. Moreover, its physical origin for the decrease in electrical conductivity has not been explained clearly. In this work, we employ a coarse-grained model for the polymer/CNT fiber, and we calculate the electric conductivity using global tunneling network (GTN) model. We show that the electric conductivity decreases during the elongation of the polymer/CNT fiber. We also find using critical path approximation (CPA) that the structure of the electrical network of the CNTs changes collectively during the elongation of the fiber, which is strongly responsible for the reduction of the electrical conductivity of the polymer/CNT fiber.

Plasticity of Neuron-Glial Transmission: Equipping Glia for Long-Term Integration of Network Activity.

PubMed

Croft, Wayne; Dobson, Katharine L; Bellamy, Tomas C

2015-01-01

The capacity of synaptic networks to express activity-dependent changes in strength and connectivity is essential for learning and memory processes. In recent years, glial cells (most notably astrocytes) have been recognized as active participants in the modulation of synaptic transmission and synaptic plasticity, implicating these electrically nonexcitable cells in information processing in the brain. While the concept of bidirectional communication between neurons and glia and the mechanisms by which gliotransmission can modulate neuronal function are well established, less attention has been focussed on the computational potential of neuron-glial transmission itself. In particular, whether neuron-glial transmission is itself subject to activity-dependent plasticity and what the computational properties of such plasticity might be has not been explored in detail. In this review, we summarize current examples of plasticity in neuron-glial transmission, in many brain regions and neurotransmitter pathways. We argue that induction of glial plasticity typically requires repetitive neuronal firing over long time periods (minutes-hours) rather than the short-lived, stereotyped trigger typical of canonical long-term potentiation. We speculate that this equips glia with a mechanism for monitoring average firing rates in the synaptic network, which is suited to the longer term roles proposed for astrocytes in neurophysiology.

Functional electrical stimulation controlled by artificial neural networks: pilot experiments with simple movements are promising for rehabilitation applications.

PubMed

Ferrante, Simona; Pedrocchi, Alessandra; Iannò, Marco; De Momi, Elena; Ferrarin, Maurizio; Ferrigno, Giancarlo

2004-01-01

This study falls within the ambit of research on functional electrical stimulation for the design of rehabilitation training for spinal cord injured patients. In this context, a crucial issue is the control of the stimulation parameters in order to optimize the patterns of muscle activation and to increase the duration of the exercises. An adaptive control system (NEURADAPT) based on artificial neural networks (ANNs) was developed to control the knee joint in accordance with desired trajectories by stimulating quadriceps muscles. This strategy includes an inverse neural model of the stimulated limb in the feedforward line and a neural network trained on-line in the feedback loop. NEURADAPT was compared with a linear closed-loop proportional integrative derivative (PID) controller and with a model-based neural controller (NEUROPID). Experiments on two subjects (one healthy and one paraplegic) show the good performance of NEURADAPT, which is able to reduce the time lag introduced by the PID controller. In addition, control systems based on ANN techniques do not require complicated calibration procedures at the beginning of each experimental session. After the initial learning phase, the ANN, thanks to its generalization capacity, is able to cope with a certain range of variability of skeletal muscle properties.

Electricity exchange and the valuation of transnational transmission access: A case study of intra-regional integration of the electric industries of Argentina and Chile

NASA Astrophysics Data System (ADS)

Brereton, Beverly Ann

The interconnection of neighboring electricity networks provides opportunities for the realization of synergies between electricity systems. Examples of the synergies to be realized are the rationalized management of the electricity networks whose fuel source domination differs, and the exploitation of non-coincident system peak demands. These factors allow technology diversity in the satisfaction of electricity demand, the coordination of planning and maintenance schedules between the networks by exploiting the cost differences in the pool of generation assets and the load configuration differences in the neighboring locations. The interconnection decision studied in this dissertation focused on the electricity networks of Argentina and Chile whose electricity systems operate in isolation at the current time. The cooperative game-theoretic framework was applied in the analysis of the decision facing the two countries and the net surplus to be derived from interconnection was evaluated. Measurement of the net gains from interconnection used in this study were reflected in changes in generating costs under the assumption that demand is fixed under all scenarios. With the demand for electricity assumed perfectly inelastic, passive or aggressive bidding strategies were considered under the scenarios for the generators in the two countries. The interconnection decision was modeled using a linear power flow model which utilizes linear programming techniques to reflect dispatch procedures based on generation bids. Results of the study indicate that the current interconnection project between Argentina and Chile will not result in positive net surplus under a variety of scenarios. Only under significantly reduced interconnection cost will the venture prove attractive. Possible sharing mechanisms were also explored in the research and a symmetric distribution of the net surplus to be derived under the reduced interconnection cost scenario was recommended to preserve equity in the allocation of the interconnection gains.

Dynamics of global supply chain and electric power networks: Models, pricing analysis, and computations

NASA Astrophysics Data System (ADS)

Matsypura, Dmytro

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following coauthored papers: Nagurney, Cruz, and Matsypura (2003), Nagurney and Matsypura (2004, 2005, 2006), Matsypura and Nagurney (2005), Matsypura, Nagurney, and Liu (2006).

AC Electric Field Communication for Human-Area Networking

NASA Astrophysics Data System (ADS)

Kado, Yuichi; Shinagawa, Mitsuru

We have proposed a human-area networking technology that uses the surface of the human body as a data transmission path and uses an AC electric field signal below the resonant frequency of the human body. This technology aims to achieve a “touch and connect” intuitive form of communication by using the electric field signal that propagates along the surface of the human body, while suppressing both the electric field radiating from the human body and mutual interference. To suppress the radiation field, the frequency of the AC signal that excites the transmitter electrode must be lowered, and the sensitivity of the receiver must be raised while reducing transmission power to its minimally required level. We describe how we are developing AC electric field communication technologies to promote the further evolution of a human-area network in support of ubiquitous services, focusing on three main characteristics, enabling-transceiver technique, application-scenario modeling, and communications quality evaluation. Special attention is paid to the relationship between electro-magnetic compatibility evaluation and regulations for extremely low-power radio stations based on Japan's Radio Law.

ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

PubMed

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-08-15

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

PubMed Central

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-01-01

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

On a simulation study for reliable and secured smart grid communications

NASA Astrophysics Data System (ADS)

Mallapuram, Sriharsha; Moulema, Paul; Yu, Wei

2015-05-01

Demand response is one of key smart grid applications that aims to reduce power generation at peak hours and maintain a balance between supply and demand. With the support of communication networks, energy consumers can become active actors in the energy management process by adjusting or rescheduling their electricity usage during peak hours based on utilities pricing incentives. Nonetheless, the integration of communication networks expose the smart grid to cyber-attacks. In this paper, we developed a smart grid simulation test-bed and designed evaluation scenarios. By leveraging the capabilities of Matlab and ns-3 simulation tools, we conducted a simulation study to evaluate the impact of cyber-attacks on demand response application. Our data shows that cyber-attacks could seriously disrupt smart grid operations, thus confirming the need of secure and resilient communication networks for supporting smart grid operations.

Noise-assisted energy transport in electrical oscillator networks with off-diagonal dynamical disorder

PubMed Central

León-Montiel, Roberto de J.; Quiroz-Juárez, Mario A.; Quintero-Torres, Rafael; Domínguez-Juárez, Jorge L.; Moya-Cessa, Héctor M.; Torres, Juan P.; Aragón, José L.

2015-01-01

Noise is generally thought as detrimental for energy transport in coupled oscillator networks. However, it has been shown that for certain coherently evolving systems, the presence of noise can enhance, somehow unexpectedly, their transport efficiency; a phenomenon called environment-assisted quantum transport (ENAQT) or dephasing-assisted transport. Here, we report on the experimental observation of such effect in a network of coupled electrical oscillators. We demonstrate that by introducing stochastic fluctuations in one of the couplings of the network, a relative enhancement in the energy transport efficiency of 22.5 ± 3.6% can be observed. PMID:26610864

Transitions to Synchrony in Coupled Bursting Neurons

NASA Astrophysics Data System (ADS)

Dhamala, Mukeshwar; Jirsa, Viktor K.; Ding, Mingzhou

2004-01-01

Certain cells in the brain, for example, thalamic neurons during sleep, show spike-burst activity. We study such spike-burst neural activity and the transitions to a synchronized state using a model of coupled bursting neurons. In an electrically coupled network, we show that the increase of coupling strength increases incoherence first and then induces two different transitions to synchronized states, one associated with bursts and the other with spikes. These sequential transitions to synchronized states are determined by the zero crossings of the maximum transverse Lyapunov exponents. These results suggest that synchronization of spike-burst activity is a multi-time-scale phenomenon and burst synchrony is a precursor to spike synchrony.

Node-node correlations and transport properties in scale-free networks

NASA Astrophysics Data System (ADS)

Obregon, Bibiana; Guzman, Lev

2011-03-01

We study some transport properties of complex networks. We focus our attention on transport properties of scale-free and small-world networks and compare two types of transport: Electric and max-flow cases. In particular, we construct scale-free networks, with a given degree sequence, to estimate the distribution of conductances for different values of assortative/dissortative mixing. For the electric case we find that the distributions of conductances are affect ed by the assortative mixing of the network whereas for the max-flow case, the distributions almost do not show changes when node-node correlations are altered. Finally, we compare local and global transport in terms of the average conductance for the small-world (Watts-Strogatz) model

Modeling the resilience of critical infrastructure: the role of network dependencies.

PubMed

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2016-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities' well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure.

Modeling the resilience of critical infrastructure: the role of network dependencies

PubMed Central

Guidotti, Roberto; Chmielewski, Hana; Unnikrishnan, Vipin; Gardoni, Paolo; McAllister, Therese; van de Lindt, John

2017-01-01

Water and wastewater network, electric power network, transportation network, communication network, and information technology network are among the critical infrastructure in our communities; their disruption during and after hazard events greatly affects communities’ well-being, economic security, social welfare, and public health. In addition, a disruption in one network may cause disruption to other networks and lead to their reduced functionality. This paper presents a unified theoretical methodology for the modeling of dependent/interdependent infrastructure networks and incorporates it in a six-step probabilistic procedure to assess their resilience. Both the methodology and the procedure are general, can be applied to any infrastructure network and hazard, and can model different types of dependencies between networks. As an illustration, the paper models the direct effects of seismic events on the functionality of a potable water distribution network and the cascading effects of the damage of the electric power network (EPN) on the potable water distribution network (WN). The results quantify the loss of functionality and delay in the recovery process due to dependency of the WN on the EPN. The results show the importance of capturing the dependency between networks in modeling the resilience of critical infrastructure. PMID:28825037

Should the next standby power target be 0-watt?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meier, Alan; Siderius, Hans-Paul

The standby power use of appliances continues to consume large amounts of electricity. Considerable success has been made in reducing each device’s use, but these savings have been offset by a huge increase in the number of products using standby power and new power requirements for maintaining network connections. Current strategies to reduce standby have limitations and may not be most appropriate for emerging energy consumption trends. A new strategy for further reductions in standby, the “Standzero” option, encourages electrical products to be designed to operate for short periods without relying on mains-supplied electricity. Energy savings are achieved through enhancedmore » efficiency and by harvesting ambient energy. A sensitivity analysis suggests many appliances could be designed to operate for at least an hour without relying on mains power and, in some cases, may be able to operate indefinitely at zero watts until activated.« less

Topological properties of a self-assembled electrical network via ab initio calculation

NASA Astrophysics Data System (ADS)

Stephenson, C.; Lyon, D.; Hübler, A.

2017-02-01

Interacting electrical conductors self-assemble to form tree like networks in the presence of applied voltages or currents. Experiments have shown that the degree distribution of the steady state networks are identical over a wide range of network sizes. In this work we develop a new model of the self-assembly process starting from the underlying physical interaction between conductors. In agreement with experimental results we find that for steady state networks, our model predicts that the fraction of endpoints is a constant of 0.252, and the fraction of branch points is 0.237. We find that our model predicts that these scaling properties also hold for the network during the approach to the steady state as well. In addition, we also reproduce the experimental distribution of nodes with a given Strahler number for all steady state networks studied.

Teaching Structured Design of Network Algorithms in Enhanced Versions of SQL

ERIC Educational Resources Information Center

de Brock, Bert

2004-01-01

From time to time developers of (database) applications will encounter, explicitly or implicitly, structures such as trees, graphs, and networks. Such applications can, for instance, relate to bills of material, organization charts, networks of (rail)roads, networks of conduit pipes (e.g., plumbing, electricity), telecom networks, and data…

Robust Long-Range Coordination of Spontaneous Neural Activity in Waking, Sleep and Anesthesia.

PubMed

Liu, Xiao; Yanagawa, Toru; Leopold, David A; Fujii, Naotaka; Duyn, Jeff H

2015-09-01

Although the emerging field of functional connectomics relies increasingly on the analysis of spontaneous fMRI signal covariation to infer the spatial fingerprint of the brain's large-scale functional networks, the nature of the underlying neuro-electrical activity remains incompletely understood. In part, this lack in understanding owes to the invasiveness of electrophysiological acquisition, the difficulty in their simultaneous recording over large cortical areas, and the absence of fully established methods for unbiased extraction of network information from these data. Here, we demonstrate a novel, data-driven approach to analyze spontaneous signal variations in electrocorticographic (ECoG) recordings from nearly entire hemispheres of macaque monkeys. Based on both broadband analysis and analysis of specific frequency bands, the ECoG signals were found to co-vary in patterns that resembled the fMRI networks reported in previous studies. The extracted patterns were robust against changes in consciousness associated with sleep and anesthesia, despite profound changes in intrinsic characteristics of the raw signals, including their spectral signatures. These results suggest that the spatial organization of large-scale brain networks results from neural activity with a broadband spectral feature and is a core aspect of the brain's physiology that does not depend on the state of consciousness. Published by Oxford University Press 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Enhancement of electrical signaling in neural networks on graphene films.

PubMed

Tang, Mingliang; Song, Qin; Li, Ning; Jiang, Ziyun; Huang, Rong; Cheng, Guosheng

2013-09-01

One of the key challenges for neural tissue engineering is to exploit supporting materials with robust functionalities not only to govern cell-specific behaviors, but also to form functional neural network. The unique electrical and mechanical properties of graphene imply it as a promising candidate for neural interfaces, but little is known about the details of neural network formation on graphene as a scaffold material for tissue engineering. Therapeutic regenerative strategies aim to guide and enhance the intrinsic capacity of the neurons to reorganize by promoting plasticity mechanisms in a controllable manner. Here, we investigated the impact of graphene on the formation and performance in the assembly of neural networks in neural stem cell (NSC) culture. Using calcium imaging and electrophysiological recordings, we demonstrate the capabilities of graphene to support the growth of functional neural circuits, and improve neural performance and electrical signaling in the network. These results offer a better understanding of interactions between graphene and NSCs, also they clearly present the great potentials of graphene as neural interface in tissue engineering. Copyright © 2013 Elsevier Ltd. All rights reserved.

Value Creation Through Integrated Networks and Convergence

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Martini, Paul; Taft, Jeffrey D.

2015-04-01

Customer adoption of distributed energy resources and public policies are driving changes in the uses of the distribution system. A system originally designed and built for one-way energy flows from central generating facilities to end-use customers is now experiencing injections of energy from customers anywhere on the grid and frequent reversals in the direction of energy flow. In response, regulators and utilities are re-thinking the design and operations of the grid to create more open and transactive electric networks. This evolution has the opportunity to unlock significant value for customers and utilities. Alternatively, failure to seize this potential may insteadmore » lead to an erosion of value if customers seek to defect and disconnect from the system. This paper will discuss how current grid modernization investments may be leveraged to create open networks that increase value through the interaction of intelligent devices on the grid and prosumerization of customers. Moreover, even greater value can be realized through the synergistic effects of convergence of multiple networks. This paper will highlight examples of the emerging nexus of non-electric networks with electricity.« less

Membrane Capacitive Memory Alters Spiking in Neurons Described by the Fractional-Order Hodgkin-Huxley Model

PubMed Central

Weinberg, Seth H.

2015-01-01

Excitable cells and cell membranes are often modeled by the simple yet elegant parallel resistor-capacitor circuit. However, studies have shown that the passive properties of membranes may be more appropriately modeled with a non-ideal capacitor, in which the current-voltage relationship is given by a fractional-order derivative. Fractional-order membrane potential dynamics introduce capacitive memory effects, i.e., dynamics are influenced by a weighted sum of the membrane potential prior history. However, it is not clear to what extent fractional-order dynamics may alter the properties of active excitable cells. In this study, we investigate the spiking properties of the neuronal membrane patch, nerve axon, and neural networks described by the fractional-order Hodgkin-Huxley neuron model. We find that in the membrane patch model, as fractional-order decreases, i.e., a greater influence of membrane potential memory, peak sodium and potassium currents are altered, and spike frequency and amplitude are generally reduced. In the nerve axon, the velocity of spike propagation increases as fractional-order decreases, while in a neural network, electrical activity is more likely to cease for smaller fractional-order. Importantly, we demonstrate that the modulation of the peak ionic currents that occurs for reduced fractional-order alone fails to reproduce many of the key alterations in spiking properties, suggesting that membrane capacitive memory and fractional-order membrane potential dynamics are important and necessary to reproduce neuronal electrical activity. PMID:25970534

Microfluidic device for unidirectional axon growth

NASA Astrophysics Data System (ADS)

Malishev, E.; Pimashkin, A.; Gladkov, A.; Pigareva, Y.; Bukatin, A.; Kazantsev, V.; Mukhina, I.; Dubina, M.

2015-11-01

In order to better understand the communication and connectivity development of neuron networks, we designed microfluidic devices with several chambers for growing dissociated neuronal cultures from mice fetal hippocampus (E18). The chambers were connected with microchannels providing unidirectional axonal growth between “Source” and “Target” neural sub-networks. Experiments were performed in a hippocampal cultures plated in a poly-dimethylsiloxane (PDMS) microfluidic chip, aligned with a 60 microelectrode array (MEA). Axonal growth through microchannels was observed with brightfield, phase-contrast and fluorescence microscopy, and after 7 days in vitro electrical activity was recorded. Visual inspection and spike propagation analysis showed the predominant axonal growth in microchannels in a direction from “Source” to “Target”.

Application of Student Book Based On Integrated Learning Model Of Networked Type With Heart Electrical Activity Theme For Junior High School

NASA Astrophysics Data System (ADS)

Gusnedi, G.; Ratnawulan, R.; Triana, L.

2018-04-01

The purpose of this study is to determine the effect of the use of Integrated Science IPA books Using Networked Learning Model of knowledge competence through improved learning outcomes obtained. The experimental design used is one group pre test post test design to know the results before and after being treated. The number of samples used is one class that is divided into two categories of initial ability to see the improvement of knowledge competence. The sample used was taken from the students of grade VIII SMPN 2 Sawahlunto, Indonesia. The results of this study indicate that most students have increased knowledge competence.

Using a Conflict Map as an Instructional Tool To Change Student Conceptions in Simple Series Electric-Circuits.

ERIC Educational Resources Information Center

Tsai, Chin-Chung

2003-01-01

Examines the effects of using a conflict map on 8th grade students' conceptual change and ideational networks about simple series electric circuits. Analyzes student interview data through a flow map method. Shows that the use of conflict maps could help students construct greater, richer, and more integrated ideational networks about electric…

Memory elements in the electrical network of Mimosa pudica L.

PubMed Central

Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tuckett, Clayton; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

2014-01-01

The fourth basic circuit element, a memristor, is a resistor with memory that was postulated by Chua in 1971. Here we found that memristors exist in vivo. The electrostimulation of the Mimosa pudica by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar sinusoidal or triangle periodic electrostimulating waves. Memristive behavior of an electrical network in the Mimosa pudica is linked to the properties of voltage gated ion channels: the channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K+ channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants. PMID:25482796

Memory elements in the electrical network of Mimosa pudica L.

PubMed

Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tuckett, Clayton; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

2014-01-01

The fourth basic circuit element, a memristor, is a resistor with memory that was postulated by Chua in 1971. Here we found that memristors exist in vivo. The electrostimulation of the Mimosa pudica by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar sinusoidal or triangle periodic electrostimulating waves. Memristive behavior of an electrical network in the Mimosa pudica is linked to the properties of voltage gated ion channels: the channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K(+) channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants.

The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network.

PubMed

Harmon, Frederick G; Frank, Andrew A; Joshi, Sanjay S

2005-01-01

A Simulink model, a propulsion energy optimization algorithm, and a CMAC controller were developed for a small parallel hybrid-electric unmanned aerial vehicle (UAV). The hybrid-electric UAV is intended for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, and reconnaissance (ISR). The Simulink model is a forward-facing simulation program used to test different control strategies. The flexible energy optimization algorithm for the propulsion system allows relative importance to be assigned between the use of gasoline, electricity, and recharging. A cerebellar model arithmetic computer (CMAC) neural network approximates the energy optimization results and is used to control the parallel hybrid-electric propulsion system. The hybrid-electric UAV with the CMAC controller uses 67.3% less energy than a two-stroke gasoline-powered UAV during a 1-h ISR mission and 37.8% less energy during a longer 3-h ISR mission.

Simulation Tools and Techniques for Analyzing the Impacts of Photovoltaic System Integration

NASA Astrophysics Data System (ADS)

Hariri, Ali

Solar photovoltaic (PV) energy integration in distribution networks is one of the fastest growing sectors of distributed energy integration. The growth in solar PV integration is incentivized by various clean power policies, global interest in solar energy, and reduction in manufacturing and installation costs of solar energy systems. The increase in solar PV integration has raised a number of concerns regarding the potential impacts that might arise as a result of high PV penetration. Some impacts have already been recorded in networks with high PV penetration such as in China, Germany, and USA (Hawaii and California). Therefore, network planning is becoming more intricate as new technologies are integrated into the existing electric grid. The integrated new technologies pose certain compatibility concerns regarding the existing electric grid infrastructure. Therefore, PV integration impact studies are becoming more essential in order to have a better understanding of how to advance the solar PV integration efforts without introducing adverse impacts into the network. PV impact studies are important for understanding the nature of the new introduced phenomena. Understanding the nature of the potential impacts is a key factor for mitigating and accommodating for said impacts. Traditionally, electric power utilities relied on phasor-based power flow simulations for planning their electric networks. However, the conventional, commercially available, phasor-based simulation tools do not provide proper visibility across a wide spectrum of electric phenomena. Moreover, different types of simulation approaches are suitable for specific types of studies. For instance, power flow software cannot be used for studying time varying phenomena. At the same time, it is not practical to use electromagnetic transient (EMT) tools to perform power flow solutions. Therefore, some electric phenomena caused by the variability of PV generation are not visible using the conventional utility simulation software. On the other hand, EMT simulation tools provide high accuracy and visibility over a wide bandwidth of frequencies at the expense of larger processing and memory requirements, limited network size, and long simulation time. Therefore, there is a gap in simulation tools and techniques that can efficiently and effectively identify potential PV impact. New planning simulation tools are needed in order to accommodate for the simulation requirements of new integrated technologies in the electric grid. The dissertation at hand starts by identifying some of the potential impacts that are caused by high PV penetration. A phasor-based quasi-static time series (QSTS) analysis tool is developed in order to study the slow dynamics that are caused by the variations in the PV generation that lead to voltage fluctuations. Moreover, some EMT simulations are performed in order to study the impacts of PV systems on the electric network harmonic levels. These studies provide insights into the type and duration of certain impacts, as well as the conditions that may lead to adverse phenomena. In addition these studies present an idea about the type of simulation tools that are sufficient for each type of study. After identifying some of the potential impacts, certain planning tools and techniques are proposed. The potential PV impacts may cause certain utilities to refrain from integrating PV systems into their networks. However, each electric network has a certain limit beyond which the impacts become substantial and may adversely interfere with the system operation and the equipment along the feeder; this limit is referred to as the hosting limit (or hosting capacity). Therefore, it is important for utilities to identify the PV hosting limit on a specific electric network in order to safely and confidently integrate the maximum possible PV systems. In the following dissertation, two approaches have been proposed for identifying the hosing limit: 1. Analytical approach: this is a theoretical mathematical approach that demonstrated the understanding of the fundamentals of electric power system operation. It provides an easy way to estimate the maximum amount of PV power that can be injected at each node in the network. This approach has been tested and validated. 2. Stochastic simulation software approach: this approach provides a comprehensive simulation software that can be used in order to identify the PV hosting limit. The software performs a large number of stochastic simulation while varying the PV system size and location. The collected data is then analyzed for violations in the voltage levels, voltage fluctuations and reverse power flow. (Abstract shortened by ProQuest.).

Nanocarbon networks for advanced rechargeable lithium batteries.

PubMed

Xin, Sen; Guo, Yu-Guo; Wan, Li-Jun

2012-10-16

Carbon is one of the essential elements in energy storage. In rechargeable lithium batteries, researchers have considered many types of nanostructured carbons, such as carbon nanoparticles, carbon nanotubes, graphene, and nanoporous carbon, as anode materials and, especially, as key components for building advanced composite electrode materials. Nanocarbons can form efficient three-dimensional conducting networks that improve the performance of electrode materials suffering from the limited kinetics of lithium storage. Although the porous structure guarantees a fast migration of Li ions, the nanocarbon network can serve as an effective matrix for dispersing the active materials to prevent them from agglomerating. The nanocarbon network also affords an efficient electron pathway to provide better electrical contacts. Because of their structural stability and flexibility, nanocarbon networks can alleviate the stress and volume changes that occur in active materials during the Li insertion/extraction process. Through the elegant design of hierarchical electrode materials with nanocarbon networks, researchers can improve both the kinetic performance and the structural stability of the electrode material, which leads to optimal battery capacity, cycling stability, and rate capability. This Account summarizes recent progress in the structural design, chemical synthesis, and characterization of the electrochemical properties of nanocarbon networks for Li-ion batteries. In such systems, storage occurs primarily in the non-carbon components, while carbon acts as the conductor and as the structural buffer. We emphasize representative nanocarbon networks including those that use carbon nanotubes and graphene. We discuss the role of carbon in enhancing the performance of various electrode materials in areas such as Li storage, Li ion and electron transport, and structural stability during cycling. We especially highlight the use of graphene to construct the carbon conducting network for alloy anodes, such as Si and Ge, to accelerate electron transport, alleviate volume change, and prevent the agglomeration of active nanoparticles. Finally, we describe the power of nanocarbon networks for the next generation rechargeable lithium batteries, including Li-S, Li-O(2), and Li-organic batteries, and provide insights into the design of ideal nanocarbon networks for these devices. In addition, we address the ways in which nanocarbon networks can expand the applications of rechargeable lithium batteries into the emerging fields of stationary energy storage and transportation.

Effect of Transcranial Magnetic Stimulation on Neuronal Networks

NASA Astrophysics Data System (ADS)

Unsal, Ahmet; Hadimani, Ravi; Jiles, David

2013-03-01

The human brain contains around 100 billion nerve cells controlling our day to day activities. Consequently, brain disorders often result in impairments such as paralysis, loss of coordination and seizure. It has been said that 1 in 5 Americans suffer some diagnosable mental disorder. There is an urgent need to understand the disorders, prevent them and if possible, develop permanent cure for them. As a result, a significant amount of research activities is being directed towards brain research. Transcranial Magnetic Stimulation (TMS) is a promising tool for diagnosing and treating brain disorders. It is a non-invasive treatment method that produces a current flow in the brain which excites the neurons. Even though TMS has been verified to have advantageous effects on various brain related disorders, there have not been enough studies on the impact of TMS on cells. In this study, we are investigating the electrophysiological effects of TMS on one dimensional neuronal culture grown in a circular pathway. Electrical currents are produced on the neuronal networks depending on the directionality of the applied field. This aids in understanding how neuronal networks react under TMS treatment.

Functional Stem Cell Integration into Neural Networks Assessed by Organotypic Slice Cultures.

PubMed

Forsberg, David; Thonabulsombat, Charoensri; Jäderstad, Johan; Jäderstad, Linda Maria; Olivius, Petri; Herlenius, Eric

2017-08-14

Re-formation or preservation of functional, electrically active neural networks has been proffered as one of the goals of stem cell-mediated neural therapeutics. A primary issue for a cell therapy approach is the formation of functional contacts between the implanted cells and the host tissue. Therefore, it is of fundamental interest to establish protocols that allow us to delineate a detailed time course of grafted stem cell survival, migration, differentiation, integration, and functional interaction with the host. One option for in vitro studies is to examine the integration of exogenous stem cells into an existing active neural network in ex vivo organotypic cultures. Organotypic cultures leave the structural integrity essentially intact while still allowing the microenvironment to be carefully controlled. This allows detailed studies over time of cellular responses and cell-cell interactions, which are not readily performed in vivo. This unit describes procedures for using organotypic slice cultures as ex vivo model systems for studying neural stem cell and embryonic stem cell engraftment and communication with CNS host tissue. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

This CD contains files that support the talk (see CASI ID 20100021404). There are 24 models that relate to the ADAPT system and 1 Excel worksheet. In the paper an investigation into the use of Bayesian networks to construct large-scale diagnostic systems is described. The high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems are described in the talk. The data in the CD are the models of the 24 different power systems.

Fiber-Optic Distribution Of Pulsed Power To Multiple Sensors

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1996-01-01

Optoelectronic systems designed according to time-sharing scheme distribute optical power to multiple integrated-circuit-based sensors in fiber-optic networks. Networks combine flexibility of electronic sensing circuits with advantage of electrical isolation afforded by use of optical fibers instead of electrical conductors to transmit both signals and power. Fiber optics resist corrosion and immune to electromagnetic interference. Sensor networks of this type useful in variety of applications; for example, in monitoring strains in aircraft, buildings, and bridges, and in monitoring and controlling shapes of flexible structures.

Radio Emissions from Electrical Activity in Martian Dust Storms

NASA Astrophysics Data System (ADS)

Majid, W.; Arabshahi, S.; Kocz, J.; Schulter, T.; White, L.

2017-12-01

Dust storms on Mars are predicted to be capable of producing electrostatic fields and discharges, even larger than those in dust storms on Earth. There are three key elements in the characterization of Martian electrostatic discharges: dependence on Martian environmental conditions, event rate, and the strength of the generated electric fields. The detection and characterization of electric activity in Martian dust storms has important implications for habitability, and preparations for human exploration of the red planet. Furthermore, electrostatic discharges may be linked to local chemistry and plays an important role in the predicted global electrical circuit. Because of the continuous Mars telecommunication needs of NASA's Mars-based assets, the Deep Space Network (DSN) is the only facility in the world that combines long term, high cadence, observing opportunities with large sensitive telescopes, making it a unique asset worldwide in searching for and characterizing electrostatic activity from large scale convective dust storms at Mars. We will describe a newly inaugurated program at NASA's Madrid Deep Space Communication Complex to carry out a long-term monitoring campaign to search for and characterize the entire Mars hemisphere for powerful discharges during routine tracking of spacecraft at Mars on an entirely non-interfering basis. The ground-based detections will also have important implications for the design of a future instrument that could make similar in-situ measurements from orbit or from the surface of Mars, with far greater sensitivity and duty cycle, opening up a new window in our understanding of the Martian environment.

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE PAGES

Buitrago, Jaime; Asfour, Shihab

2017-01-01

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Micro-grid platform based on NODE.JS architecture, implemented in electrical network instrumentation

NASA Astrophysics Data System (ADS)

Duque, M.; Cando, E.; Aguinaga, A.; Llulluna, F.; Jara, N.; Moreno, T.

2016-05-01

In this document, I propose a theory about the impact of systems based on microgrids in non-industrialized countries that have the goal to improve energy exploitation through alternatives methods of a clean and renewable energy generation and the creation of the app to manage the behavior of the micro-grids based on the NodeJS, Django and IOJS technologies. The micro-grids allow the optimal way to manage energy flow by electric injection directly in electric network small urban's cells in a low cost and available way. In difference from conventional systems, micro-grids can communicate between them to carry energy to places that have higher demand in accurate moments. This system does not require energy storage, so, costs are lower than conventional systems like fuel cells, solar panels or else; even though micro-grids are independent systems, they are not isolated. The impact that this analysis will generate, is the improvement of the electrical network without having greater control than an intelligent network (SMART-GRID); this leads to move to a 20% increase in energy use in a specified network; that suggest there are others sources of energy generation; but for today's needs, we need to standardize methods and remain in place to support all future technologies and the best option are the Smart Grids and Micro-Grids.

Short-term forecasting of electric loads using nonlinear autoregressive artificial neural networks with exogenous vector inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buitrago, Jaime; Asfour, Shihab

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN) with exogenous multi-variable input (NARX). The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input.more » Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. Finally, the New England electrical load data are used to train and validate the forecast prediction.« less

Transparent, conformable, active multielectrode array using organic electrochemical transistors

PubMed Central

Lee, Wonryung; Kim, Dongmin; Matsuhisa, Naoji; Nagase, Masae; Sekino, Masaki; Malliaras, George G.; Yokota, Tomoyuki; Someya, Takao

2017-01-01

Mechanically flexible active multielectrode arrays (MEA) have been developed for local signal amplification and high spatial resolution. However, their opaqueness limited optical observation and light stimulation during use. Here, we show a transparent, ultraflexible, and active MEA, which consists of transparent organic electrochemical transistors (OECTs) and transparent Au grid wirings. The transparent OECT is made of Au grid electrodes and has shown comparable performance with OECTs with nontransparent electrodes/wirings. The transparent active MEA realizes the spatial mapping of electrocorticogram electrical signals from an optogenetic rat with 1-mm spacing and shows lower light artifacts than noise level. Our active MEA would open up the possibility of precise investigation of a neural network system with direct light stimulation. PMID:28923928

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trinklei, Eddy; Parker, Gordon; Weaver, Wayne

This report presents a scoping study for networked microgrids which are defined as "Interoperable groups of multiple Advanced Microgrids that become an integral part of the electricity grid while providing enhanced resiliency through self-healing, aggregated ancillary services, and real-time communication." They result in optimal electrical system configurations and controls whether grid-connected or in islanded modes and enable high penetrations of distributed and renewable energy resources. The vision for the purpose of this document is: "Networked microgrids seamlessly integrate with the electricity grid or other Electric Power Sources (EPS) providing cost effective, high quality, reliable, resilient, self-healing power delivery systems." Scopingmore » Study: Networked Microgrids September 4, 2014 Eddy Trinklein, Michigan Technological University Gordon Parker, Michigan Technological University Wayne Weaver, Michigan Technological University Rush Robinett, Michigan Technological University Lucia Gauchia Babe, Michigan Technological University Chee-Wooi Ten, Michigan Technological University Ward Bower, Ward Bower Innovations LLC Steve Glover, Sandia National Laboratories Steve Bukowski, Sandia National Laboratories Prepared by Michigan Technological University Houghton, Michigan 49931 Michigan Technological University« less

A fast stimulability screening protocol for neuronal cultures on microelectrode arrays.

PubMed

Kapucu, Fikret E; Tanskanen, Jarno M A; Yuan, Yuting; Hyttinen, Jari A K

2015-01-01

Microelectrode arrays (MEAs) are used to study the electrical activity in brain slices and neuronal cultures. MEA experiments for the analysis of electrical stimulation responses require the tissue or culture to be prone to stimulation. For brain slices, potential stimulation sites may be directly visible in microscope, in which case the determination of stimulability at those locations is sufficient. In unstructured neuronal cultures, potential stimulation sites may not be known a priori, and spatial stimulability screening should be performed. Considering, e.g., 59 microelectrode sites, each to be stimulated several times, may result in long screening times, unacceptable with a MEA system without an integrated CO2 incubator, or in high stimulation effects on the networks. Here, we describe an implementation of a fast stimulation protocol employing pseudorandom stimulation site switching aiming at alleviating the network effects of the stimulability screening. In this paper, we show the usability of the proposed protocol by first detecting stimulable locations and subsequently apply repeated stimulation on the identified potentially stimulable locations to observe an exemplary neuronal pathway.

Nonlinear electronic transport and enhanced catalytic behavior caused by native oxides on Cu nanowires

NASA Astrophysics Data System (ADS)

Hajimammadov, Rashad; Csendes, Zita; Ojakoski, Juha-Matti; Lorite, Gabriela Simone; Mohl, Melinda; Kordas, Krisztian

2017-09-01

Electrical transport properties of individual nanowires (both in axial and transversal directions) and their random networks suggest rapid oxidation when Cu is exposed to ambient conditions. The oxidation process is elucidated by thorough XRD, XPS and Raman analyzes conducted for a period of 30 days. Based on the obtained experimental data, we may conclude that first, cuprous oxide and copper hydroxide form that finally transform to cupric oxide. In electrical applications, oxidation of copper is not a true problem as long as thin films or bulk metal is concerned. However, as highlighted in our work, this is not the case for nanowires, since the oxidized surface plays quite important role in the contact formation and also in the conduction of percolated nanowire networks. On the other hand, by taking advantage of the mixed surface oxide states present on the nanowires along with their large specific surface area, we tested and found excellent catalytic activity of the oxidized nanowires in phenol oxidation, which suggests further applications of these materials in catalysis.

The contribution of raised intraneuronal chloride to epileptic network activity.

PubMed

Alfonsa, Hannah; Merricks, Edward M; Codadu, Neela K; Cunningham, Mark O; Deisseroth, Karl; Racca, Claudia; Trevelyan, Andrew J

2015-05-20

Altered inhibitory function is an important facet of epileptic pathology. A key concept is that GABAergic activity can become excitatory if intraneuronal chloride rises. However, it has proved difficult to separate the role of raised chloride from other contributory factors in complex network phenomena, such as epileptic pathology. Therefore, we asked what patterns of activity are associated with chloride dysregulation by making novel use of Halorhodopsin to load clusters of mouse pyramidal cells artificially with Cl(-). Brief (1-10 s) activation of Halorhodopsin caused substantial positive shifts in the GABAergic reversal potential that were proportional to the charge transfer during the illumination and in adult neocortical pyramidal neurons decayed with a time constant of τ = 8.0 ± 2.8s. At the network level, these positive shifts in EGABA produced a transient rise in network excitability, with many distinctive features of epileptic foci, including high-frequency oscillations with evidence of out-of-phase firing (Ibarz et al., 2010). We show how such firing patterns can arise from quite small shifts in the mean intracellular Cl(-) level, within heterogeneous neuronal populations. Notably, however, chloride loading by itself did not trigger full ictal events, even with additional electrical stimulation to the underlying white matter. In contrast, when performed in combination with low, subepileptic levels of 4-aminopyridine, Halorhodopsin activation rapidly induced full ictal activity. These results suggest that chloride loading has at most an adjunctive role in ictogenesis. Our simulations also show how chloride loading can affect the jitter of action potential timing associated with imminent recruitment to an ictal event (Netoff and Schiff, 2002). Copyright © 2015 Alfonsa et al.

Towards more Global Coordination of Atmospheric Electricity Measurements (GloCAEM)

NASA Astrophysics Data System (ADS)

Nicoll, Keri; Harrison, Giles

2017-04-01

Earth's atmospheric electrical environment has been studied since the 1750s but its more recent applications to science questions around clouds and climate highlight the incompleteness of our understanding, in part due to lack of suitable global measurements. The Global Electric Circuit (GEC) sustains the near-surface fair weather (FW) electric field, which is present globally in regions which are not strongly electrically disturbed by weather or pollution. It can be measured routinely at the surface using well established instrumentation such as electric field mills. Despite the central role of lightning as a weather hazard and the potentially widespread importance of charge for atmospheric processes, research is hampered by the fragmented nature of surface atmospheric electricity measurements. This makes anything other than local studies in fortuitous fair weather conditions difficult. In contrast to detection of global lightning using satellite measurements and ground-based radio networks, the FW electric field and GEC cannot be measured by remote sensing and no similar measurement networks exist for its study. This presents an opportunity as many researchers worldwide now make high temporal resolution measurements of the FW electric field routinely, which is neither coordinated nor exploited. The GLOCAEM (Global Coordination of Atmospheric Electricity Measurements) project is currently bringing some of these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring. A specific objective of the project is to establish the first modern archive of international FW atmospheric electric field data in close to real time to allow global studies of atmospheric electricity to be straightforwardly and robustly performed. Data will be archived through the UK Centre for Environmental Data Analysis (CEDA) and will be available for download by users from early 2018. Both 1 second and 1 minute electric field data will be archived, along with meteorological measurements (if available) for ease of interpretation of electrical measurements. Although the primary aim of the project is to provide a close to real time electric field database, archiving of existing historical electric field datasets is also planned to extend the range of studies possible. This presentation will provide a summary of progress with the GLOCAEM project.

Real-Time-Simulation of IEEE-5-Bus Network on OPAL-RT-OP4510 Simulator

NASA Astrophysics Data System (ADS)

Atul Bhandakkar, Anjali; Mathew, Lini, Dr.

2018-03-01

The Real-Time Simulator tools have high computing technologies, improved performance. They are widely used for design and improvement of electrical systems. The advancement of the software tools like MATLAB/SIMULINK with its Real-Time Workshop (RTW) and Real-Time Windows Target (RTWT), real-time simulators are used extensively in many engineering fields, such as industry, education, and research institutions. OPAL-RT-OP4510 is a Real-Time Simulator which is used in both industry and academia. In this paper, the real-time simulation of IEEE-5-Bus network is carried out by means of OPAL-RT-OP4510 with CRO and other hardware. The performance of the network is observed with the introduction of fault at various locations. The waveforms of voltage, current, active and reactive power are observed in the MATLAB simulation environment and on the CRO. Also, Load Flow Analysis (LFA) of IEEE-5-Bus network is computed using MATLAB/Simulink power-gui load flow tool.

A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons.

PubMed

Beim Graben, Peter; Rodrigues, Serafim

2012-01-01

We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement.

Regulation of distribution network business

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roman, J.; Gomez, T.; Munoz, A.

1999-04-01

The traditional distribution function actually comprises two separate activities: distribution network and retailing. Retailing, which is also termed supply, consists of trading electricity at the wholesale level and selling it to the end users. The distribution network business, or merely distribution, is a natural monopoly and it must be regulated. Increasing attention is presently being paid to the regulation of distribution pricing. Distribution pricing, comprises two major tasks: global remuneration of the distribution utility and tariff setting by allocation of the total costs among all the users of the network services. In this paper, the basic concepts for establishing themore » global remuneration of a distribution utility are presented. A remuneration scheme which recognizes adequate investment and operation costs, promotes losses reduction and incentivates the control of the quality of service level is proposed. Efficient investment and operation costs are calculated by using different types of strategic planning and regression analysis models. Application examples that have been used during the distribution regulation process in Spain are also presented.« less

A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons

PubMed Central

beim Graben, Peter; Rodrigues, Serafim

2013-01-01

We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the “open-field” configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement. PMID:23316157

Recovery of neuronal and network excitability after spinal cord injury and implications for spasticity

PubMed Central

D'Amico, Jessica M.; Condliffe, Elizabeth G.; Martins, Karen J. B.; Bennett, David J.; Gorassini, Monica A.

2014-01-01

The state of areflexia and muscle weakness that immediately follows a spinal cord injury (SCI) is gradually replaced by the recovery of neuronal and network excitability, leading to both improvements in residual motor function and the development of spasticity. In this review we summarize recent animal and human studies that describe how motoneurons and their activation by sensory pathways become hyperexcitable to compensate for the reduction of functional activation of the spinal cord and the eventual impact on the muscle. Specifically, decreases in the inhibitory control of sensory transmission and increases in intrinsic motoneuron excitability are described. We present the idea that replacing lost patterned activation of the spinal cord by activating synaptic inputs via assisted movements, pharmacology or electrical stimulation may help to recover lost spinal inhibition. This may lead to a reduction of uncontrolled activation of the spinal cord and thus, improve its controlled activation by synaptic inputs to ultimately normalize circuit function. Increasing the excitation of the spinal cord with spared descending and/or peripheral inputs by facilitating movement, instead of suppressing it pharmacologically, may provide the best avenue to improve residual motor function and manage spasticity after SCI. PMID:24860447

Critical behaviour in charging of electric vehicles

NASA Astrophysics Data System (ADS)

Carvalho, Rui; Buzna, Lubos; Gibbens, Richard; Kelly, Frank

2015-09-01

The increasing penetration of electric vehicles over the coming decades, taken together with the high cost to upgrade local distribution networks and consumer demand for home charging, suggest that managing congestion on low voltage networks will be a crucial component of the electric vehicle revolution and the move away from fossil fuels in transportation. Here, we model the max-flow and proportional fairness protocols for the control of congestion caused by a fleet of vehicles charging on two real-world distribution networks. We show that the system undergoes a continuous phase transition to a congested state as a function of the rate of vehicles plugging to the network to charge. We focus on the order parameter and its fluctuations close to the phase transition, and show that the critical point depends on the choice of congestion protocol. Finally, we analyse the inequality in the charging times as the vehicle arrival rate increases, and show that charging times are considerably more equitable in proportional fairness than in max-flow.

Oscillations emerging from noise-driven steady state in networks with electrical synapses and subthreshold resonance

PubMed Central

Tchumatchenko, Tatjana; Clopath, Claudia

2014-01-01

Oscillations play a critical role in cognitive phenomena and have been observed in many brain regions. Experimental evidence indicates that classes of neurons exhibit properties that could promote oscillations, such as subthreshold resonance and electrical gap junctions. Typically, these two properties are studied separately but it is not clear which is the dominant determinant of global network rhythms. Our aim is to provide an analytical understanding of how these two effects destabilize the fluctuation-driven state, in which neurons fire irregularly, and lead to an emergence of global synchronous oscillations. Here we show how the oscillation frequency is shaped by single neuron resonance, electrical and chemical synapses.The presence of both gap junctions and subthreshold resonance are necessary for the emergence of oscillations. Our results are in agreement with several experimental observations such as network responses to oscillatory inputs and offer a much-needed conceptual link connecting a collection of disparate effects observed in networks. PMID:25405458

The quantum CP-violating kaon system reproduced in the electronic laboratory

NASA Astrophysics Data System (ADS)

Caruso, M.; Fanchiotti, H.; García Canal, C. A.; Mayosky, M.; Veiga, A.

2016-11-01

The equivalence between the Schrödinger dynamics of a quantum system with a finite number of basis states and a classical dynamics is realized in terms of electric networks. The isomorphism that connects in a univocal way both dynamical systems was applied to the case of neutral mesons, kaons in particular, and the class of electric networks univocally related to the quantum system was analysed. Moreover, under CPT invariance, the relevant ɛ parameter that measures CP violation in the kaon system is reinterpreted in terms of network parameters. All these results were explicitly shown by means of both a numerical simulation of the implied networks and by constructing the corresponding circuits.

Forecasting Electric Power Generation of Photovoltaic Power System for Energy Network

NASA Astrophysics Data System (ADS)

Kudo, Mitsuru; Takeuchi, Akira; Nozaki, Yousuke; Endo, Hisahito; Sumita, Jiro

Recently, there has been an increase in concern about the global environment. Interest is growing in developing an energy network by which new energy systems such as photovoltaic and fuel cells generate power locally and electric power and heat are controlled with a communications network. We developed the power generation forecast method for photovoltaic power systems in an energy network. The method makes use of weather information and regression analysis. We carried out forecasting power output of the photovoltaic power system installed in Expo 2005, Aichi Japan. As a result of comparing measurements with a prediction values, the average prediction error per day was about 26% of the measured power.

Energy regeneration model of self-consistent field of electron beams into electric power*

NASA Astrophysics Data System (ADS)

Kazmin, B. N.; Ryzhov, D. R.; Trifanov, I. V.; Snezhko, A. A.; Savelyeva, M. V.

2016-04-01

We consider physic-mathematical models of electric processes in electron beams, conversion of beam parameters into electric power values and their transformation into users’ electric power grid (onboard spacecraft network). We perform computer simulation validating high energy efficiency of the studied processes to be applied in the electric power technology to produce the power as well as electric power plants and propulsion installation in the spacecraft.

Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

NASA Astrophysics Data System (ADS)

Zhang, Xianjun

The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical output and recovered thermal output, which are affected by multiple factors and thus analyzed in different case studies. The results indicate that the designed typical gas system is capable of supplying sufficient natural gas for the DG normal operation, while the present water system cannot support the complete recovery of the exhaust heat from the DG units.

Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation

PubMed Central

Li, Luozheng; Mi, Yuanyuan; Zhang, Wenhao; Wang, Da-Hui; Wu, Si

2018-01-01

Adaptation refers to the general phenomenon that the neural system dynamically adjusts its response property according to the statistics of external inputs. In response to an invariant stimulation, neuronal firing rates first increase dramatically and then decrease gradually to a low level close to the background activity. This prompts a question: during the adaptation, how does the neural system encode the repeated stimulation with attenuated firing rates? It has been suggested that the neural system may employ a dynamical encoding strategy during the adaptation, the information of stimulus is mainly encoded by the strong independent spiking of neurons at the early stage of the adaptation; while the weak but synchronized activity of neurons encodes the stimulus information at the later stage of the adaptation. The previous study demonstrated that short-term facilitation (STF) of electrical synapses, which increases the synchronization between neurons, can provide a mechanism to realize dynamical encoding. In the present study, we further explore whether short-term plasticity (STP) of chemical synapses, an interaction form more common than electrical synapse in the cortex, can support dynamical encoding. We build a large-size network with chemical synapses between neurons. Notably, facilitation of chemical synapses only enhances pair-wise correlations between neurons mildly, but its effect on increasing synchronization of the network can be significant, and hence it can serve as a mechanism to convey the stimulus information. To read-out the stimulus information, we consider that a downstream neuron receives balanced excitatory and inhibitory inputs from the network, so that the downstream neuron only responds to synchronized firings of the network. Therefore, the response of the downstream neuron indicates the presence of the repeated stimulation. Overall, our study demonstrates that STP of chemical synapse can serve as a mechanism to realize dynamical neural encoding. We believe that our study shed lights on the mechanism underlying the efficient neural information processing via adaptation. PMID:29636675

Electric Vehicles in Colorado: Anticipating Consumer Demand for Direct Current Fast Charging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wood, Eric W.; Rames, Clement L.

To support the State of Colorado in planning for growth in direct current fast charging (DCFC) for electric vehicles, the National Renewable Energy Laboratory (NREL) has partnered with the Regional Air Quality Council (RAQC) and the Colorado Department of Transportation (CDOT) to analyze a number of DCFC investment scenarios. NREL analyzed existing electric vehicle registration data from IHS Markit (IHS) to highlight early trends in the electric vehicle market, which were compared with sales forecasts predicting large growth in the Colorado electric vehicle market. Electric vehicle forecasts were then used to develop future DCFC scenarios to be evaluated in amore » simulation environment to estimate consumer benefits of the hypothetical DCFC networks in terms of increased driving range and electric vehicle miles traveled (eVMT). Simulated utilization of the hypothetical DCFC networks was analyzed for geographic trends, particularly for correlations with vehicle electric range. Finally, a subset of simulations is presented for consumers with potentially inconsistent access to charging at their home location and presumably greater reliance on public DCFC infrastructure.« less

Biophysics of olfaction

NASA Astrophysics Data System (ADS)

Marques Simoes de Souza, Fabio; Antunes, Gabriela

2007-03-01

The majority of the biophysical models of olfaction have been focused on the electrical properties of the system, which is justified by the relative facility of recording the electrical activity of the olfactory cells. However, depending on the level of detail utilized, a biophysical model can explore molecular, cellular and network phenomena. This review presents the state of the art of the biophysical approach to understanding olfaction. The reader is introduced to the principal problems involving the study of olfaction and guided gradually to comprehend why it is important to develop biophysical models to investigate olfaction. A large number of representative biophysical efforts in olfaction, their main contributions, the trends for the next generations of biophysical models and the improvements that may be explored by future biophysicists of olfaction have been reviewed.

Assessment of critical path analyses of the relationship between permeability and electrical conductivity of pore networks

NASA Astrophysics Data System (ADS)

Skaggs, Todd H.

2011-10-01

Critical path analysis (CPA) is a method for estimating macroscopic transport coefficients of heterogeneous materials that are highly disordered at the micro-scale. Developed originally to model conduction in semiconductors, numerous researchers have noted that CPA might also have relevance to flow and transport processes in porous media. However, the results of several numerical investigations of critical path analysis on pore network models raise questions about the applicability of CPA to porous media. Among other things, these studies found that (i) in well-connected 3D networks, CPA predictions were inaccurate and became worse when heterogeneity was increased; and (ii) CPA could not fully explain the transport properties of 2D networks. To better understand the applicability of CPA to porous media, we made numerical computations of permeability and electrical conductivity on 2D and 3D networks with differing pore-size distributions and geometries. A new CPA model for the relationship between the permeability and electrical conductivity was found to be in good agreement with numerical data, and to be a significant improvement over a classical CPA model. In sufficiently disordered 3D networks, the new CPA prediction was within ±20% of the true value, and was nearly optimal in terms of minimizing the squared prediction errors across differing network configurations. The agreement of CPA predictions with 2D network computations was similarly good, although 2D networks are in general not well-suited for evaluating CPA. Numerical transport coefficients derived for regular 3D networks of slit-shaped pores were found to be in better agreement with experimental data from rock samples than were coefficients derived for networks of cylindrical pores.

Teaching Network Security with IP Darkspace Data

ERIC Educational Resources Information Center

Zseby, Tanja; Iglesias Vázquez, Félix; King, Alistair; Claffy, K. C.

2016-01-01

This paper presents a network security laboratory project for teaching network traffic anomaly detection methods to electrical engineering students. The project design follows a research-oriented teaching principle, enabling students to make their own discoveries in real network traffic, using data captured from a large IP darkspace monitor…

An electrical description of the generation of slow waves in the antrum of the guinea-pig

PubMed Central

Edwards, FR; Hirst, GDS

2005-01-01

This paper provides an electrical description of the generation of slow waves in the guinea-pig gastric antrum. A short segment of a circular smooth muscle bundle with an attached network of myenteric interstitial cells of Cajal (ICC-MY) and longitudinal muscle sheet was modelled as three electrical compartments with resistive connexions between the ICC-MY compartment and each of the smooth muscle compartments. The circular smooth muscle layer contains a proportion of intramuscular interstitial cells of Cajal (ICC-IM), responsible for the regenerative component of the slow wave. Hence the equivalent cell representing the circular muscle layer incorporated a mechanism, modelled as a two stage reaction, which produces an intracellular messenger. The first stage of the reaction is proposed to be activated in a voltage-dependent manner as described by Hodgkin and Huxley. A similar mechanism was incorporated into the equivalent cell describing the ICC-MY network. Spontaneous discrete transient depolarizations, termed unitary potentials, are detected in records taken from either bundles of circular smooth muscle containing ICC-IM or from ICC-MY. In the simulation the mean rate of discharge of unitary potentials was allowed to vary with the concentration of messenger according to a conventional dose–effect relationship. Such a mechanism, which describes regenerative potentials generated by the circular muscle layer, also simulated the plateau component of the pacemaker potential in the ICC-MY network. A voltage-sensitive membrane conductance was included in the ICC-MY compartment; this was used to describe the primary component of the pacemaker potential. The model generates a range of membrane potential changes with properties similar to those generated by the three cell types present in the intact tissue. PMID:15613372

Mechanisms for pattern specificity of deep-brain stimulation in Parkinson’s disease

PubMed Central

Mato, Germán; Dellavale, Damián

2017-01-01

Deep brain stimulation (DBS) has become a widely used technique for treating advanced stages of neurological and psychiatric illness. In the case of motor disorders related to basal ganglia (BG) dysfunction, several mechanisms of action for the DBS therapy have been identified which might be involved simultaneously or in sequence. However, the identification of a common key mechanism underlying the clinical relevant DBS configurations has remained elusive due to the inherent complexity related to the interaction between the electrical stimulation and the neural tissue, and the intricate circuital structure of the BG-thalamocortical network. In this work, it is shown that the clinically relevant range for both, the frequency and intensity of the electrical stimulation pattern, is an emergent property of the BG anatomy at the system-level that can be addressed using mean-field descriptive models of the BG network. Moreover, it is shown that the activity resetting mechanism elicited by electrical stimulation provides a natural explanation to the ineffectiveness of irregular (i.e., aperiodic) stimulation patterns, which has been commonly observed in previously reported pathophysiology models of Parkinson’s disease. Using analytical and numerical techniques, these results have been reproduced in both cases: 1) a reduced mean-field model that can be thought as an elementary building block capable to capture the underlying fundamentals of the relevant loops constituting the BG-thalamocortical network, and 2) a detailed model constituted by the direct and hyperdirect loops including one-dimensional spatial structure of the BG nuclei. We found that the optimal ranges for the essential parameters of the stimulation patterns can be understood without taking into account biophysical details of the relevant structures. PMID:28813460

Stability and chaos of Rulkov map-based neuron network with electrical synapse

NASA Astrophysics Data System (ADS)

Wang, Caixia; Cao, Hongjun

2015-02-01

In this paper, stability and chaos of a simple system consisting of two identical Rulkov map-based neurons with the bidirectional electrical synapse are investigated in detail. On the one hand, as a function of control parameters and electrical coupling strengthes, the conditions for stability of fixed points of this system are obtained by using the qualitative analysis. On the other hand, chaos in the sense of Marotto is proved by a strict mathematical way. These results could be useful for building-up large-scale neurons networks with specific dynamics and rich biophysical phenomena.

Large-size, high-uniformity, random silver nanowire networks as transparent electrodes for crystalline silicon wafer solar cells.

PubMed

Xie, Shouyi; Ouyang, Zi; Jia, Baohua; Gu, Min

2013-05-06

Metal nanowire networks are emerging as next generation transparent electrodes for photovoltaic devices. We demonstrate the application of random silver nanowire networks as the top electrode on crystalline silicon wafer solar cells. The dependence of transmittance and sheet resistance on the surface coverage is measured. Superior optical and electrical properties are observed due to the large-size, highly-uniform nature of these networks. When applying the nanowire networks on the solar cells with an optimized two-step annealing process, we achieved as large as 19% enhancement on the energy conversion efficiency. The detailed analysis reveals that the enhancement is mainly caused by the improved electrical properties of the solar cells due to the silver nanowire networks. Our result reveals that this technology is a promising alternative transparent electrode technology for crystalline silicon wafer solar cells.

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

NASA Astrophysics Data System (ADS)

Hattam, Laura; Greetham, Danica Vukadinović

2018-01-01

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes' model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes' equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined.

Causal relationships between neurons of the nucleus incertus and the hippocampal theta activity in the rat.

PubMed

Martínez-Bellver, Sergio; Cervera-Ferri, Ana; Luque-García, Aina; Martínez-Ricós, Joana; Valverde-Navarro, Alfonso; Bataller, Manuel; Guerrero, Juan; Teruel-Marti, Vicent

2017-03-01

The nucleus incertus is a key node of the brainstem circuitry involved in hippocampal theta rhythmicity. Synchronisation exists between the nucleus incertus and hippocampal activities during theta periods. By the Granger causality analysis, we demonstrated a directional information flow between theta rhythmical neurons in the nucleus incertus and the hippocampus in theta-on states. The electrical stimulation of the nucleus incertus is also able to evoke a phase reset of the hippocampal theta wave. Our data suggest that the nucleus incertus is a key node of theta generation and the modulation network. In recent years, a body of evidence has shown that the nucleus incertus (NI), in the dorsal tegmental pons, is a key node of the brainstem circuitry involved in hippocampal theta rhythmicity. Ascending reticular brainstem system activation evokes hippocampal theta rhythm with coupled neuronal activity in the NI. In a recent paper, we showed three populations of neurons in the NI with differential firing during hippocampal theta activation. The objective of this work was to better evaluate the causal relationship between the activity of NI neurons and the hippocampus during theta activation in order to further understand the role of the NI in the theta network. A Granger causality analysis was run to determine whether hippocampal theta activity with sensory-evoked theta depends on the neuronal activity of the NI, or vice versa. The analysis showed causal interdependence between the NI and the hippocampus during theta activity, whose directional flow depended on the different neuronal assemblies of the NI. Whereas type I and II NI neurons mainly acted as receptors of hippocampal information, type III neuronal activity was the predominant source of flow between the NI and the hippocampus in theta states. We further determined that the electrical activation of the NI was able to reset hippocampal waves with enhanced theta-band power, depending on the septal area. Collectively, these data suggest that hippocampal theta oscillations after sensory activation show dependence on NI neuron activity, which could play a key role in establishing optimal conditions for memory encoding. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

PubMed

Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adeli, Hojjat

2017-09-27

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epileptiform abnormalities. This technique can be time-consuming, limited by technical artifact, provides variable results secondary to reader expertise level, and is limited in identifying abnormalities. Therefore, it is essential to develop a computer-aided diagnosis (CAD) system to automatically distinguish the class of these EEG signals using machine learning techniques. This is the first study to employ the convolutional neural network (CNN) for analysis of EEG signals. In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes. The proposed technique achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Graph Theory at the Service of Electroencephalograms.

PubMed

Iakovidou, Nantia D

2017-04-01

The brain is one of the largest and most complex organs in the human body and EEG is a noninvasive electrophysiological monitoring method that is used to record the electrical activity of the brain. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using EEG signals. This means that the brain is studied as a connected system where nodes, or units, represent different specialized brain regions and links, or connections, represent communication pathways between the nodes. Graph theory and theory of complex networks provide a variety of measures, methods, and tools that can be useful to efficiently model, analyze, and study EEG networks. This article is addressed to computer scientists who wish to be acquainted and deal with the study of EEG data and also to neuroscientists who would like to become familiar with graph theoretic approaches and tools to analyze EEG data.

Effect of Morphologic Features of Neurons on the Extracellular Electric Potential: A Simulation Study Using Cable Theory and Electro-Quasi-Static Equations.

PubMed

Bestel, R; Appali, R; van Rienen, U; Thielemann, C

2017-11-01

Microelectrode arrays serve as an indispensable tool in electro-physiological research to study the electrical activity of neural cells, enabling measurements of single cell as well as network communication analysis. Recent experimental studies have reported that the neuronal geometry has an influence on electrical signaling and extracellular recordings. However, the corresponding mechanisms are not yet fully understood and require further investigation. Allowing systematic parameter studies, computational modeling provides the opportunity to examine the underlying effects that influence extracellular potentials. In this letter, we present an in silico single cell model to analyze the effect of geometrical variability on the extracellular electric potentials. We describe finite element models of a single neuron with varying geometric complexity in three-dimensional space. The electric potential generation of the neuron is modeled using Hodgkin-Huxley equations. The signal propagation is described with electro-quasi-static equations, and results are compared with corresponding cable equation descriptions. Our results show that both the geometric dimensions and the distribution of ion channels of a neuron are critical factors that significantly influence both the amplitude and shape of extracellular potentials.

Applying the Network Simulation Method for testing chaos in a resistively and capacitively shunted Josephson junction model

NASA Astrophysics Data System (ADS)

Bellver, Fernando Gimeno; Garratón, Manuel Caravaca; Soto Meca, Antonio; López, Juan Antonio Vera; Guirao, Juan L. G.; Fernández-Martínez, Manuel

In this paper, we explore the chaotic behavior of resistively and capacitively shunted Josephson junctions via the so-called Network Simulation Method. Such a numerical approach establishes a formal equivalence among physical transport processes and electrical networks, and hence, it can be applied to efficiently deal with a wide range of differential systems. The generality underlying that electrical equivalence allows to apply the circuit theory to several scientific and technological problems. In this work, the Fast Fourier Transform has been applied for chaos detection purposes and the calculations have been carried out in PSpice, an electrical circuit software. Overall, it holds that such a numerical approach leads to quickly computationally solve Josephson differential models. An empirical application regarding the study of the Josephson model completes the paper.

The Use of Generating Sets with ING Gas Engines in "Shore to Ship" Systems

NASA Astrophysics Data System (ADS)

Tarnapowicz, Dariusz; German-Galkin, Sergiej

2016-09-01

The main sources of air pollution in ports are ships, on which electrical energy is produced in the autonomous generating sets Diesel-Generator. The most effective way to reduce harmful exhaust emissions from ships is to exclude marine generating sets and provide the shore-side electricity in "Shore to Ship" system. The main problem in the implementation of power supply for ships from land is connected with matching parameters of voltage in onshore network with marine network. Currently, the recommended solution is to supply ships from the onshore electricity network with the use of power electronic converters. This article presents an analysis of the "Shore to Ship" system with the use of generating sets with LNG gas engines. It shows topologies with LNG - Generator sets, environmental benefits of such a solution, advantages and disadvantages.

Biophysical Model of Cortical Network Activity and the Influence of Electrical Stimulation

DTIC Science & Technology

2015-11-13

dynamics of seizure propagation across micro domains in the vicinity of the seizure onset zone, Journal of Neural Engineering, (08 2015): 46016. doi...field potential (lfp) in a large scalesimulation of cerebral cortex , Society for Neuroscience. 19-OCT-15, . : , TOTAL: 2 Number of Peer-Reviewed...of graduating undergraduates who achieved a 3.5 GPA to 4.0 (4.0 max scale ): Number of graduating undergraduates funded by a DoD funded Center of

Fabrication of electric papers of graphene nanosheet shelled cellulose fibres by dispersion and infiltration as flexible electrodes for energy storage

NASA Astrophysics Data System (ADS)

Kang, Yan-Ru; Li, Ya-Li; Hou, Feng; Wen, Yang-Yang; Su, Dong

2012-05-01

An electrically conductive and electrochemically active composite paper of graphene nanosheet (GNS) coated cellulose fibres was fabricated via a simple paper-making process of dispersing chemically synthesized GNS into a cellulose pulp, followed by infiltration. The GNS nanosheet was deposited onto the cellulose fibers, forming a coating, during infiltration. It forms a continuous network through a bridge of interconnected cellulose fibres at small GNS loadings (3.2 wt%). The GNS/cellulose paper is as flexible and mechanically tough as the pure cellulose paper. The electrical measurements show the composite paper has a sheet resistance of 1063 Ω □-1 and a conductivity of 11.6 S m-1. The application of the composite paper as a flexible double layer supercapacitor in an organic electrolyte (LiPF6) displays a high capacity of 252 F g-1 at a current density of 1 A g-1 with respect to GNS. Moreover, the paper can be used as the anode in a lithium battery, showing distinct charge and discharge performances. The simple process for synthesising the GNS functionalized cellulose papers is attractive for the development of high performance papers for electrical, electrochemical and multifunctional applications.An electrically conductive and electrochemically active composite paper of graphene nanosheet (GNS) coated cellulose fibres was fabricated via a simple paper-making process of dispersing chemically synthesized GNS into a cellulose pulp, followed by infiltration. The GNS nanosheet was deposited onto the cellulose fibers, forming a coating, during infiltration. It forms a continuous network through a bridge of interconnected cellulose fibres at small GNS loadings (3.2 wt%). The GNS/cellulose paper is as flexible and mechanically tough as the pure cellulose paper. The electrical measurements show the composite paper has a sheet resistance of 1063 Ω □-1 and a conductivity of 11.6 S m-1. The application of the composite paper as a flexible double layer supercapacitor in an organic electrolyte (LiPF6) displays a high capacity of 252 F g-1 at a current density of 1 A g-1 with respect to GNS. Moreover, the paper can be used as the anode in a lithium battery, showing distinct charge and discharge performances. The simple process for synthesising the GNS functionalized cellulose papers is attractive for the development of high performance papers for electrical, electrochemical and multifunctional applications. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr30318c

Cortical network reorganization guided by sensory input features.

PubMed

Kilgard, Michael P; Pandya, Pritesh K; Engineer, Navzer D; Moucha, Raluca

2002-12-01

Sensory experience alters the functional organization of cortical networks. Previous studies using behavioral training motivated by aversive or rewarding stimuli have demonstrated that cortical plasticity is specific to salient inputs in the sensory environment. Sensory experience associated with electrical activation of the basal forebrain (BasF) generates similar input specific plasticity. By directly engaging plasticity mechanisms and avoiding extensive behavioral training, BasF stimulation makes it possible to efficiently explore how specific sensory features contribute to cortical plasticity. This review summarizes our observations that cortical networks employ a variety of strategies to improve the representation of the sensory environment. Different combinations of receptive-field, temporal, and spectrotemporal plasticity were generated in primary auditory cortex neurons depending on the pitch, modulation rate, and order of sounds paired with BasF stimulation. Simple tones led to map expansion, while modulated tones altered the maximum cortical following rate. Exposure to complex acoustic sequences led to the development of combination-sensitive responses. This remodeling of cortical response characteristics may reflect changes in intrinsic cellular mechanisms, synaptic efficacy, and local neuronal connectivity. The intricate relationship between the pattern of sensory activation and cortical plasticity suggests that network-level rules alter the functional organization of the cortex to generate the most behaviorally useful representation of the sensory environment.

Optogenetic stimulation of multiwell MEA plates for neural and cardiac applications

NASA Astrophysics Data System (ADS)

Clements, Isaac P.; Millard, Daniel C.; Nicolini, Anthony M.; Preyer, Amanda J.; Grier, Robert; Heckerling, Andrew; Blum, Richard A.; Tyler, Phillip; McSweeney, K. M.; Lu, Yi-Fan; Hall, Diana; Ross, James D.

2016-03-01

Microelectrode array (MEA) technology enables advanced drug screening and "disease-in-a-dish" modeling by measuring the electrical activity of cultured networks of neural or cardiac cells. Recent developments in human stem cell technologies, advancements in genetic models, and regulatory initiatives for drug screening have increased the demand for MEA-based assays. In response, Axion Biosystems previously developed a multiwell MEA platform, providing up to 96 MEA culture wells arrayed into a standard microplate format. Multiwell MEA-based assays would be further enhanced by optogenetic stimulation, which enables selective excitation and inhibition of targeted cell types. This capability for selective control over cell culture states would allow finer pacing and probing of cell networks for more reliable and complete characterization of complex network dynamics. Here we describe a system for independent optogenetic stimulation of each well of a 48-well MEA plate. The system enables finely graded control of light delivery during simultaneous recording of network activity in each well. Using human induced pluripotent stem cell (hiPSC) derived cardiomyocytes and rodent primary neuronal cultures, we demonstrate high channel-count light-based excitation and suppression in several proof-of-concept experimental models. Our findings demonstrate advantages of combining multiwell optical stimulation and MEA recording for applications including cardiac safety screening, neural toxicity assessment, and advanced characterization of complex neuronal diseases.

Programmability of nanowire networks

NASA Astrophysics Data System (ADS)

Bellew, A. T.; Bell, A. P.; McCarthy, E. K.; Fairfield, J. A.; Boland, J. J.

2014-07-01

Electrical connectivity in networks of nanoscale junctions must be better understood if nanowire devices are to be scaled up from single wires to functional material systems. We show that the natural connectivity behaviour found in random nanowire networks presents a new paradigm for creating multi-functional, programmable materials. In devices made from networks of Ni/NiO core-shell nanowires at different length scales, we discover the emergence of distinct behavioural regimes when networks are electrically stressed. We show that a small network, with few nanowire-nanowire junctions, acts as a unipolar resistive switch, demonstrating very high ON/OFF current ratios (>105). However, large networks of nanowires distribute an applied bias across a large number of junctions, and thus respond not by switching but instead by evolving connectivity. We demonstrate that these emergent properties lead to fault-tolerant materials whose resistance may be tuned, and which are capable of adaptively reconfiguring under stress. By combining these two behavioural regimes, we demonstrate that the same nanowire network may be programmed to act both as a metallic interconnect, and a resistive switch device with high ON/OFF ratio. These results enable the fabrication of programmable, multi-functional materials from random nanowire networks.Electrical connectivity in networks of nanoscale junctions must be better understood if nanowire devices are to be scaled up from single wires to functional material systems. We show that the natural connectivity behaviour found in random nanowire networks presents a new paradigm for creating multi-functional, programmable materials. In devices made from networks of Ni/NiO core-shell nanowires at different length scales, we discover the emergence of distinct behavioural regimes when networks are electrically stressed. We show that a small network, with few nanowire-nanowire junctions, acts as a unipolar resistive switch, demonstrating very high ON/OFF current ratios (>105). However, large networks of nanowires distribute an applied bias across a large number of junctions, and thus respond not by switching but instead by evolving connectivity. We demonstrate that these emergent properties lead to fault-tolerant materials whose resistance may be tuned, and which are capable of adaptively reconfiguring under stress. By combining these two behavioural regimes, we demonstrate that the same nanowire network may be programmed to act both as a metallic interconnect, and a resistive switch device with high ON/OFF ratio. These results enable the fabrication of programmable, multi-functional materials from random nanowire networks. Electronic supplementary information (ESI) available: Nanowire statistics (length, diameter statistics, and oxide thickness) are provided. Forming curves for single junctions and networks. Passive voltage contrast image demonstrating selectivity of conductive pathways in 100 μm network. See DOI: 10.1039/c4nr02338b

PV water pumping: NEOS Corporation recent PV water pumping activities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lane, C.

1995-11-01

NEOS Corporation has been very active in PV-powered water pumping, particularly with respect to electric utilities. Most of the recent activity has been through the Photovoltaic Services Network (PSN). The PSN is an independent, not-for-profit organization comprised of all types of electric utilities: rural electric coops, public power districts, investor-owned utilities, and power marketing agencies. The PSN`s mission is to work pro-actively to promote utility involvement in PV through education and training. PV information is distributed by the PSN in three primary forms: (1) consultation with PSN technical service representatives: (2) literature generated by the PSN; and (3) literature publishedmore » by other organizations. The PSN can also provide assistance to members in developing PV customer service programs. The PSN`s product support activities include consolidation of information on existing packaged PV systems and facilitation of the development of new PV product packages that meet utility-defined specifications for cost performance, and reliability. The PSN`s initial product support efforts will be focused on commercially available packaged PV systems for a variety of off-grid applications. In parallel with this effort, if no products exist that meet the PSN`s functional specifications, the PSN will initiate the second phase of product development support process by encouraging the development of new packaged systems. Through these services and product support activities, the PSN anticipates engaging all segments for the PV industry, thus providing benefits to PV systems suppliers as well as local PV service contractors.This paper describes field testing of pv power systems for water pumping.« less

Study on key technologies of vehicle networking system platform for electric automobiles based on micro-service

NASA Astrophysics Data System (ADS)

Ye, Fei

2018-04-01

With the rapid increase of electric automobiles and charging piles, the elastic expansion and online rapid upgrade were required for the vehicle networking system platform (system platform for short). At present, it is difficult to meet the operation needs due to the traditional huge rock architecture used by the system platform. This paper studied the system platform technology architecture based on "cloud platform +micro-service" to obtain a new generation of vehicle networking system platform with the combination of elastic expansion and application, thus significantly improving the service operation ability of system.

Flexible transparent conductors based on metal nanowire networks

DOE PAGES

Guo, Chuan Fei; Ren, Zhifeng

2015-04-01

Few conductors are transparent and flexible. Metals have the best electrical conductivity, but they are opaque and stiff in bulk form. However, metals can be transparent and flexible when they are very thin or properly arranged on the nanoscale. This review focuses on the flexible transparent conductors based on percolating networks of metal. Specifically, we discuss the fabrication, the means to improve the electrical conductivity, the large stretchability and its mechanism, and the applications of these metal networks. We also suggest some criteria for evaluating flexible transparent conductors and propose some new research directions in this emerging field.

Models for the modern power grid

NASA Astrophysics Data System (ADS)

Nardelli, Pedro H. J.; Rubido, Nicolas; Wang, Chengwei; Baptista, Murilo S.; Pomalaza-Raez, Carlos; Cardieri, Paulo; Latva-aho, Matti

2014-10-01

This article reviews different kinds of models for the electric power grid that can be used to understand the modern power system, the smart grid. From the physical network to abstract energy markets, we identify in the literature different aspects that co-determine the spatio-temporal multilayer dynamics of power system. We start our review by showing how the generation, transmission and distribution characteristics of the traditional power grids are already subject to complex behaviour appearing as a result of the the interplay between dynamics of the nodes and topology, namely synchronisation and cascade effects. When dealing with smart grids, the system complexity increases even more: on top of the physical network of power lines and controllable sources of electricity, the modernisation brings information networks, renewable intermittent generation, market liberalisation, prosumers, among other aspects. In this case, we forecast a dynamical co-evolution of the smart grid and other kind of networked systems that cannot be understood isolated. This review compiles recent results that model electric power grids as complex systems, going beyond pure technological aspects. From this perspective, we then indicate possible ways to incorporate the diverse co-evolving systems into the smart grid model using, for example, network theory and multi-agent simulation.

Simulation studies of multiple large wind turbine generators on a utility network

NASA Technical Reports Server (NTRS)

Gilbert, L. J.; Triezenberg, D. M.

1979-01-01

The potential electrical problems that may be inherent in the inertia of clusters of wind turbine generators and an electric utility network were investigated. Preliminary and limited results of an analog simulation of two MOD-2 wind generators tied to an infinite bus indicate little interaction between the generators and between the generators and the bus. The system demonstrated transient stability for the conditions considered.

Nonvolatile Ionic Two-Terminal Memory Device

NASA Technical Reports Server (NTRS)

Williams, Roger M.

1990-01-01

Conceptual solid-state memory device nonvolatile and erasable and has only two terminals. Proposed device based on two effects: thermal phase transition and reversible intercalation of ions. Transfer of sodium ions between source of ions and electrical switching element increases or decreases electrical conductance of element, turning switch "on" or "off". Used in digital computers and neural-network computers. In neural networks, many small, densely packed switches function as erasable, nonvolatile synaptic elements.

Electro-migration of impurities in TlBr

NASA Astrophysics Data System (ADS)

Kim, Ki Hyun; Kim, Eunlim; Kim, H.; Tappero, R.; Bolotnikov, A. E.; Camarda, G. S.; Hossain, A.; Cirignano, L.; James, R. B.

2013-10-01

We observed the electro-migration of Cu, Ag, and Au impurities that exist in positive-ion states in TlBr detectors under electric field strengths typically used for device operation. The migration occurred predominantly through bulk- and specific-channels, which are presumed to be a network of grain and sub-grain boundaries. The electro-migration velocity of Cu, Ag, and Au in TlBr is about 4-8 × 10-8 cm/s at room temperature under an electric field of 500-800 V/mm. The instability and polarization effects of TlBr detectors might well be correlated with the electro-migration of residual impurities in TlBr, which alters the internal electric field over time. The effect may also have been due to migration of the electrode material itself, which would allow for the possibility of a better choice for contact material and for depositing an effective diffusion barrier. From our findings, we suggest that applying our electro-migration technique for purifying material is a promising new way to remove electrically active metallic impurities in TlBr crystals, as well as other materials.

Regulation and competition without privatization: Norway`s experience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moen, J.; Hamrin, J.

The competitive market for the hydro-based Norwegian electricity system is working well, with end-user prices only slightly above the wholesale market. Pool prices are reflecting only weather-related variations, and no market power abuses are evident. The challenge now is to restructure ownership of the wires and retail suppliers to lower wheeling costs and avoid cross-subsidization. Since the Norwegian Energy Act came into effect in 1991, the electricity industry in Norway has operated as one of the most deregulated electricity industries in the world. The Energy Act introduced third party access to the retail market and competition in electricity production. Themore » generation, sale and purchase of electricity is now highly competitive, with customers free to buy electricity from any generator, trader or the electricity Pool. Transmission pricing was separated from power purchasing arrangements, so that the buying and selling of electricity as a product is distinct from the transmission of electricity as a service. Transmission and distribution networks continue to maintain natural monopolies, with network owners providing wheeling service across their networks to customers who are connected to them. These monopoly sectors of the industry are subject to regulation by the government-appointed regulatory body, Norwegian Water Resources and Energy Administration (NVE). Regulation is on a cost-of-service basis, with the revenue allowance determined by NVE. The main force behind the Norwegian reform was the desire for efficiency gains to be achieved through a total restructure of the commercial character of the energy service industry (ESI). Unlike the U.K., in Norway the monopoly franchise for both generation and retail supply was removed in one step without any transition period, and the old pool was reformed to provide the needed structure for this new competitive energy market.« less

Highly Adaptive Solid-Liquid Interfacing Triboelectric Nanogenerator for Harvesting Diverse Water Wave Energy.

PubMed

Zhao, Xue Jiao; Kuang, Shuang Yang; Wang, Zhong Lin; Zhu, Guang

2018-05-22

Harvesting water wave energy presents a significantly practical route to energy supply for self-powered wireless sensing networks. Here we report a networked integrated triboelectric nanogenerator (NI-TENG) as a highly adaptive means of harvesting energy from interfacing interactions with various types of water waves. Having an arrayed networking structure, the NI-TENG can accommodate diverse water wave motions and generate stable electric output regardless of how random the water wave is. Nanoscaled surface morphology consisting of dense nanowire arrays is the key for obtaining high electric output. A NI-TENG having an area of 100 × 70 mm 2 can produce a stable short-circuit current of 13.5 μA and corresponding electric power of 1.03 mW at a water wave height of 12 cm. This merit promises practical applications of the NI-TENG in real circumstances, where water waves are highly variable and unpredictable. After energy storage, the generated electric energy can drive wireless sensing by autonomously transmitting data at a period less than 1 min. This work proposes a viable solution for powering individual standalone nodes in a wireless sensor network. Potential applications include but are not limited to long-term environment monitoring, marine surveillance, and off-shore navigation.

Selected Topics on Decision Making for Electric Vehicles

NASA Astrophysics Data System (ADS)

Sweda, Timothy Matthew

Electric vehicles (EVs) are an attractive alternative to conventional gasoline-powered vehicles due to their lower emissions, fuel costs, and maintenance costs. Range anxiety, or the fear of running out of charge prior to reaching one's destination, remains a significant concern, however. In this dissertation, we address the issue of range anxiety by developing a set of decision support tools for both charging infrastructure providers and EV drivers. In Chapter 1, we present an agent-based information system for identifying patterns in residential EV ownership and driving activities to enable strategic deployment of new charging infrastructure. Driver agents consider their own driving activities within the simulated environment, in addition to the presence of charging stations and the vehicle ownership of others in their social networks, when purchasing a new vehicle. The Chicagoland area is used as a case study to demonstrate the model, and several deployment scenarios are analyzed. In Chapter 2, we address the problem of finding an optimal recharging policy for an EV along a given path. The path consists of a sequence of nodes, each representing a charging station, and the driver must decide where to stop and how much to recharge at each stop. We present efficient algorithms for finding an optimal policy in general instances with deterministic travel costs and homogeneous charging stations, and also for two specialized cases. In addition, we develop two heuristic procedures that we characterize analytically and explore empirically. We further analyze and test our solution methods on model variations that include stochastic travel costs and nonhomogeneous charging stations. In Chapter 3, we study the problem of finding an optimal routing and recharging policy for an electric vehicle in a grid network. Each node in the network represents a charging station and has an associated probability of being available at any point in time or occupied by another vehicle. We present an efficient algorithm for finding an optimal a priori route and recharging policy as well as heuristic methods for finding adaptive policies. We conduct numerical experiments to demonstrate the empirical performance of our solutions.

A dual-scale metal nanowire network transparent conductor for highly efficient and flexible organic light emitting diodes.

PubMed

Lee, Jinhwan; An, Kunsik; Won, Phillip; Ka, Yoonseok; Hwang, Hyejin; Moon, Hyunjin; Kwon, Yongwon; Hong, Sukjoon; Kim, Changsoon; Lee, Changhee; Ko, Seung Hwan

2017-02-02

Although solution processed metal nanowire (NW) percolation networks are a strong candidate to replace commercial indium tin oxide, their performance is limited in thin film device applications due to reduced effective electrical areas arising from the dimple structure and percolative voids that single size metal NW percolation networks inevitably possess. Here, we present a transparent electrode based on a dual-scale silver nanowire (AgNW) percolation network embedded in a flexible substrate to demonstrate a significant enhancement in the effective electrical area by filling the large percolative voids present in a long/thick AgNW network with short/thin AgNWs. As a proof of concept, the performance enhancement of a flexible phosphorescent OLED is demonstrated with the dual-scale AgNW percolation network compared to the previous mono-scale AgNWs. Moreover, we report that mechanical and oxidative robustness, which are critical for flexible OLEDs, are greatly increased by embedding the dual-scale AgNW network in a resin layer.

Evaluation and prediction of solar radiation for energy management based on neural networks

NASA Astrophysics Data System (ADS)

Aldoshina, O. V.; Van Tai, Dinh

2017-08-01

Currently, there is a high rate of distribution of renewable energy sources and distributed power generation based on intelligent networks; therefore, meteorological forecasts are particularly useful for planning and managing the energy system in order to increase its overall efficiency and productivity. The application of artificial neural networks (ANN) in the field of photovoltaic energy is presented in this article. Implemented in this study, two periodically repeating dynamic ANS, that are the concentration of the time delay of a neural network (CTDNN) and the non-linear autoregression of a network with exogenous inputs of the NAEI, are used in the development of a model for estimating and daily forecasting of solar radiation. ANN show good productivity, as reliable and accurate models of daily solar radiation are obtained. This allows to successfully predict the photovoltaic output power for this installation. The potential of the proposed method for controlling the energy of the electrical network is shown using the example of the application of the NAEI network for predicting the electric load.

Cell-cell bioelectrical interactions and local heterogeneities in genetic networks: a model for the stabilization of single-cell states and multicellular oscillations.

PubMed

Cervera, Javier; Manzanares, José A; Mafe, Salvador

2018-04-04

Genetic networks operate in the presence of local heterogeneities in single-cell transcription and translation rates. Bioelectrical networks and spatio-temporal maps of cell electric potentials can influence multicellular ensembles. Could cell-cell bioelectrical interactions mediated by intercellular gap junctions contribute to the stabilization of multicellular states against local genetic heterogeneities? We theoretically analyze this question on the basis of two well-established experimental facts: (i) the membrane potential is a reliable read-out of the single-cell electrical state and (ii) when the cells are coupled together, their individual cell potentials can be influenced by ensemble-averaged electrical potentials. We propose a minimal biophysical model for the coupling between genetic and bioelectrical networks that associates the local changes occurring in the transcription and translation rates of an ion channel protein with abnormally low (depolarized) cell potentials. We then analyze the conditions under which the depolarization of a small region (patch) in a multicellular ensemble can be reverted by its bioelectrical coupling with the (normally polarized) neighboring cells. We show also that the coupling between genetic and bioelectric networks of non-excitable cells, modulated by average electric potentials at the multicellular ensemble level, can produce oscillatory phenomena. The simulations show the importance of single-cell potentials characteristic of polarized and depolarized states, the relative sizes of the abnormally polarized patch and the rest of the normally polarized ensemble, and intercellular coupling.

Electrical conductivity modeling and experimental study of densely packed SWCNT networks.

PubMed

Jack, D A; Yeh, C-S; Liang, Z; Li, S; Park, J G; Fielding, J C

2010-05-14

Single-walled carbon nanotube (SWCNT) networks have become a subject of interest due to their ability to support structural, thermal and electrical loadings, but to date their application has been hindered due, in large part, to the inability to model macroscopic responses in an industrial product with any reasonable confidence. This paper seeks to address the relationship between macroscale electrical conductivity and the nanostructure of a dense network composed of SWCNTs and presents a uniquely formulated physics-based computational model for electrical conductivity predictions. The proposed model incorporates physics-based stochastic parameters for the individual nanotubes to construct the nanostructure such as: an experimentally obtained orientation distribution function, experimentally derived length and diameter distributions, and assumed distributions of chirality and registry of individual CNTs. Case studies are presented to investigate the relationship between macroscale conductivity and nanostructured variations in the bulk stochastic length, diameter and orientation distributions. Simulation results correspond nicely with those available in the literature for case studies of conductivity versus length and conductivity versus diameter. In addition, predictions for the increasing anisotropy of the bulk conductivity as a function of the tube orientation distribution are in reasonable agreement with our experimental results. Examples are presented to demonstrate the importance of incorporating various stochastic characteristics in bulk conductivity predictions. Finally, a design consideration for industrial applications is discussed based on localized network power emission considerations and may lend insight to the design engineer to better predict network failure under high current loading applications.

Statistical analysis of storm electrical discharges reconstituted from a lightning mapping system, a lightning location system, and an acoustic array

NASA Astrophysics Data System (ADS)

Gallin, Louis-Jonardan; Farges, Thomas; Marchiano, Régis; Coulouvrat, François; Defer, Eric; Rison, William; Schulz, Wolfgang; Nuret, Mathieu

2016-04-01

In the framework of the European Hydrological Cycle in the Mediterranean Experiment project, a field campaign devoted to the study of electrical activity during storms took place in the south of France in 2012. An acoustic station composed of four microphones and four microbarometers was deployed within the coverage of a Lightning Mapping Array network. On the 26 October 2012, a thunderstorm passed just over the acoustic station. Fifty-six natural thunder events, due to cloud-to-ground and intracloud flashes, were recorded. This paper studies the acoustic reconstruction, in the low frequency range from 1 to 40 Hz, of the recorded flashes and their comparison with detections from electromagnetic networks. Concurrent detections from the European Cooperation for Lightning Detection lightning location system were also used. Some case studies show clearly that acoustic signal from thunder comes from the return stroke but also from the horizontal discharges which occur inside the clouds. The huge amount of observation data leads to a statistical analysis of lightning discharges acoustically recorded. Especially, the distributions of altitudes of reconstructed acoustic detections are explored in detail. The impact of the distance to the source on these distributions is established. The capacity of the acoustic method to describe precisely the lower part of nearby cloud-to-ground discharges, where the Lightning Mapping Array network is not effective, is also highlighted.

CMOS nanoelectrode array for all-electrical intracellular electrophysiological imaging

NASA Astrophysics Data System (ADS)

Abbott, Jeffrey; Ye, Tianyang; Qin, Ling; Jorgolli, Marsela; Gertner, Rona S.; Ham, Donhee; Park, Hongkun

2017-05-01

Developing a new tool capable of high-precision electrophysiological recording of a large network of electrogenic cells has long been an outstanding challenge in neurobiology and cardiology. Here, we combine nanoscale intracellular electrodes with complementary metal-oxide-semiconductor (CMOS) integrated circuits to realize a high-fidelity all-electrical electrophysiological imager for parallel intracellular recording at the network level. Our CMOS nanoelectrode array has 1,024 recording/stimulation 'pixels' equipped with vertical nanoelectrodes, and can simultaneously record intracellular membrane potentials from hundreds of connected in vitro neonatal rat ventricular cardiomyocytes. We demonstrate that this network-level intracellular recording capability can be used to examine the effect of pharmaceuticals on the delicate dynamics of a cardiomyocyte network, thus opening up new opportunities in tissue-based pharmacological screening for cardiac and neuronal diseases as well as fundamental studies of electrogenic cells and their networks.

Monitoring groundwater and river interaction along the Hanford reach of the Columbia River

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, M.D.

1994-04-01

As an adjunct to efficient Hanford Site characterization and remediation of groundwater contamination, an automatic monitor network has been used to measure Columbia River and adjacent groundwater levels in several areas of the Hanford Site since 1991. Water levels, temperatures, and electrical conductivity measured by the automatic monitor network provided an initial database with which to calibrate models and from which to infer ground and river water interactions for site characterization and remediation activities. Measurements of the dynamic river/aquifer system have been simultaneous at 1-hr intervals, with a quality suitable for hydrologic modeling and for computer model calibration and testing.more » This report describes the equipment, procedures, and results from measurements done in 1993.« less

Microcontroller - Based System for Electrogastrography Monitoring Through Wireless Transmission

NASA Astrophysics Data System (ADS)

Haddab, S.; Laghrouche, M.

2009-01-01

Electrogastrography (EGG) is a non-invasive method for recording the electrical activity of the stomach. This paper presents a system designed for monitoring the EGG physiological variables of a patient outside the hospital environment. The signal acquisition is achieved by means of an ambulatory system carried by the patient and connected to him through skin electrodes. The acquired signal is transmitted via the Bluetooth to a mobile phone where the data are stored into the memory and then transferred via the GSM network to the processing and diagnostic unit in the hospital. EGG is usually contaminated by artefacts and other signals, which are sometimes difficult to remove. We have used a neural network method for motion artefacts removal and biological signal separation.

Self-triggering superconducting fault current limiter

DOEpatents

Yuan, Xing [Albany, NY; Tekletsadik, Kasegn [Rexford, NY

2008-10-21

A modular and scaleable Matrix Fault Current Limiter (MFCL) that functions as a "variable impedance" device in an electric power network, using components made of superconducting and non-superconducting electrically conductive materials. The matrix fault current limiter comprises a fault current limiter module that includes a superconductor which is electrically coupled in parallel with a trigger coil, wherein the trigger coil is magnetically coupled to the superconductor. The current surge doing a fault within the electrical power network will cause the superconductor to transition to its resistive state and also generate a uniform magnetic field in the trigger coil and simultaneously limit the voltage developed across the superconductor. This results in fast and uniform quenching of the superconductors, significantly reduces the burnout risk associated with non-uniformity often existing within the volume of superconductor materials. The fault current limiter modules may be electrically coupled together to form various "n" (rows).times."m" (columns) matrix configurations.

Global potential for wind-generated electricity

PubMed Central

Lu, Xi; McElroy, Michael B.; Kiviluoma, Juha

2009-01-01

The potential of wind power as a global source of electricity is assessed by using winds derived through assimilation of data from a variety of meteorological sources. The analysis indicates that a network of land-based 2.5-megawatt (MW) turbines restricted to nonforested, ice-free, nonurban areas operating at as little as 20% of their rated capacity could supply >40 times current worldwide consumption of electricity, >5 times total global use of energy in all forms. Resources in the contiguous United States, specifically in the central plain states, could accommodate as much as 16 times total current demand for electricity in the United States. Estimates are given also for quantities of electricity that could be obtained by using a network of 3.6-MW turbines deployed in ocean waters with depths <200 m within 50 nautical miles (92.6 km) of closest coastlines. PMID:19549865

Design process of a photonics network for military platforms

NASA Astrophysics Data System (ADS)

Nelson, George F.; Rao, Nagarajan M.; Krawczak, John A.; Stevens, Rick C.

1999-02-01

Technology development in photonics is rapidly progressing. The concept of a Unified Network will provide re- configurable network access to platform sensors, Vehicle Management Systems, Stores and avionics. The re-configurable taps into the network will accommodate present interface standards and provide scaleability for the insertion of future interfaces. Significant to this development is the design and test of the Optical Backplane Interconnect System funded by Naval Air Systems Command and developed by Lockheed Martin Tactical Defense Systems - Eagan. OBIS results in the merging of the electrical backplane and the optical backplane, with interconnect fabric and card edge connectors finally providing adequate electrical and optical card access. Presently OBIS will support 1.2 Gb/s per fiber over multiples of 12 fibers per ribbon cable.

Smart Grid Communications System Blueprint

NASA Astrophysics Data System (ADS)

Clark, Adrian; Pavlovski, Chris

2010-10-01

Telecommunications operators are well versed in deploying 2G and 3G wireless networks. These networks presently support the mobile business user and/or retail consumer wishing to place conventional voice calls and data connections. The electrical power industry has recently commenced transformation of its distribution networks by deploying smart monitoring and control devices throughout their networks. This evolution of the network into a `smart grid' has also motivated the need to deploy wireless technologies that bridge the communication gap between the smart devices and information technology systems. The requirements of these networks differ from traditional wireless networks that communications operators have deployed, which have thus far forced energy companies to consider deploying their own wireless networks. We present our experience in deploying wireless networks to support the smart grid and highlight the key properties of these networks. These characteristics include application awareness, support for large numbers of simultaneous cell connections, high service coverage and prioritized routing of data. We also outline our target blueprint architecture that may be useful to the industry in building wireless and fixed networks to support the smart grid. By observing our experiences, telecommunications operators and equipment manufacturers will be able to augment their current networks and products in a way that accommodates the needs of the emerging industry of smart grids and intelligent electrical networks.

SIDON: A simulator of radio-frequency networks. Application to WEST ICRF launchers

NASA Astrophysics Data System (ADS)

Helou, Walid; Dumortier, Pierre; Durodié, Frédéric; Goniche, Marc; Hillairet, Julien; Mollard, Patrick; Berger-By, Gilles; Bernard, Jean-Michel; Colas, Laurent; Lombard, Gilles; Maggiora, Riccardo; Magne, Roland; Milanesio, Daniele; Moreau, Didier

2015-12-01

SIDON (SImulator of raDiO-frequency Networks) is an in-house developed Radio-Frequency (RF) network solver that has been implemented to cross-validate the design of WEST ICRF launchers and simulate their impedance matching algorithm while considering all mutual couplings and asymmetries. In this paper, the authors illustrate the theory of SIDON as well as results of its calculations. The authors have built time-varying plasma scenarios (a sequence of launchers front-faces L-mode and H-mode Z-matrices), where at each time step (1 millisecond here), SIDON solves the RF network. At the same time, when activated, the impedance matching algorithm controls the matching elements (vacuum capacitors) and thus their corresponding S-matrices. Typically a 1-second pulse requires around 10 seconds of computational time on a desktop computer. These tasks can be hardly handled by commercial RF software. This innovative work allows identifying strategies for the launchers future operation while insuring the limitations on the currents, voltages and electric fields, matching and Load-Resilience, as well as the required straps voltage amplitude/phase balance. In this paper, a particular attention is paid to the simulation of the launchers behavior when arcs appear at several locations of their circuits using SIDON calculator. This latter work shall confirm or identify strategies for the arc detection using various RF electrical signals. One shall note that the use of such solvers in not limited to ICRF launchers simulations but can be employed, in principle, to any linear or linearized RF problem.

Abnormal salience signaling in schizophrenia: The role of integrative beta oscillations.

PubMed

Liddle, Elizabeth B; Price, Darren; Palaniyappan, Lena; Brookes, Matthew J; Robson, Siân E; Hall, Emma L; Morris, Peter G; Liddle, Peter F

2016-04-01

Aberrant salience attribution and cerebral dysconnectivity both have strong evidential support as core dysfunctions in schizophrenia. Aberrant salience arising from an excess of dopamine activity has been implicated in delusions and hallucinations, exaggerating the significance of everyday occurrences and thus leading to perceptual distortions and delusional causal inferences. Meanwhile, abnormalities in key nodes of a salience brain network have been implicated in other characteristic symptoms, including the disorganization and impoverishment of mental activity. A substantial body of literature reports disruption to brain network connectivity in schizophrenia. Electrical oscillations likely play a key role in the coordination of brain activity at spatially remote sites, and evidence implicates beta band oscillations in long-range integrative processes. We used magnetoencephalography and a task designed to disambiguate responses to relevant from irrelevant stimuli to investigate beta oscillations in nodes of a network implicated in salience detection and previously shown to be structurally and functionally abnormal in schizophrenia. Healthy participants, as expected, produced an enhanced beta synchronization to behaviorally relevant, as compared to irrelevant, stimuli, while patients with schizophrenia showed the reverse pattern: a greater beta synchronization in response to irrelevant than to relevant stimuli. These findings not only support both the aberrant salience and disconnectivity hypotheses, but indicate a common mechanism that allows us to integrate them into a single framework for understanding schizophrenia in terms of disrupted recruitment of contextually appropriate brain networks. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Abnormal salience signaling in schizophrenia: The role of integrative beta oscillations

PubMed Central

Liddle, Elizabeth B.; Price, Darren; Palaniyappan, Lena; Brookes, Matthew J.; Robson, Siân E.; Hall, Emma L.; Morris, Peter G.

2016-01-01

Abstract Aberrant salience attribution and cerebral dysconnectivity both have strong evidential support as core dysfunctions in schizophrenia. Aberrant salience arising from an excess of dopamine activity has been implicated in delusions and hallucinations, exaggerating the significance of everyday occurrences and thus leading to perceptual distortions and delusional causal inferences. Meanwhile, abnormalities in key nodes of a salience brain network have been implicated in other characteristic symptoms, including the disorganization and impoverishment of mental activity. A substantial body of literature reports disruption to brain network connectivity in schizophrenia. Electrical oscillations likely play a key role in the coordination of brain activity at spatially remote sites, and evidence implicates beta band oscillations in long‐range integrative processes. We used magnetoencephalography and a task designed to disambiguate responses to relevant from irrelevant stimuli to investigate beta oscillations in nodes of a network implicated in salience detection and previously shown to be structurally and functionally abnormal in schizophrenia. Healthy participants, as expected, produced an enhanced beta synchronization to behaviorally relevant, as compared to irrelevant, stimuli, while patients with schizophrenia showed the reverse pattern: a greater beta synchronization in response to irrelevant than to relevant stimuli. These findings not only support both the aberrant salience and disconnectivity hypotheses, but indicate a common mechanism that allows us to integrate them into a single framework for understanding schizophrenia in terms of disrupted recruitment of contextually appropriate brain networks. Hum Brain Mapp 37:1361‐1374, 2016. © 2016 Wiley Periodicals, Inc. PMID:26853904

Modification of electrical properties of silicon dioxide through intrinsic nano-patterns

NASA Astrophysics Data System (ADS)

Majee, Subimal; Barshilia, Devesh; Banerjee, Debashree; Kumar, Sanjeev; Mishra, Prabhash; Akhtar, Jamil

2018-05-01

The inherent network of nanopores and voids in silicon dioxide (SiO2) is generally undesirable for aspects of film quality, electrical insulation and dielectric performance. However, if we view these pores as natural nano-patterns embedded in a dielectric matrix then that opens up new vistas for exploration. The nano-pattern platform can be used to tailor electrical, optical, magnetic and mechanical properties of the carrier film. In this article we report the tunable electrical properties of thermal SiO2 thin-film achieved through utilization of the metal-nanopore network where the pores are filled with metallic Titanium (Ti). Without any intentional chemical doping, we have shown that the electrical resistivity of the oxide film can be controlled through physical filling up of the intrinsic oxide nanopores with Ti. The electrical resistivity of the composite film remains constant even after complete removal of the metal from the film surface except the pores. Careful morphological, electrical and structural analyses are carried out to establish that the presence of Ti in the nanopores play a crucial role in the observed conductive nature of the nanoporous film.

Neurodynamic oscillators

NASA Technical Reports Server (NTRS)

Espinosa, Ismael; Gonzalez, Hortensia; Quiza, Jorge; Gonazalez, J. Jesus; Arroyo, Ruben; Lara, Ritaluz

1995-01-01

Oscillation of electrical activity has been found in many nervous systems, from invertebrates to vertebrates including man. There exists experimental evidence of very simple circuits with the capability of oscillation. Neurons with intrinsic oscillation have been found and also neural circuits where oscillation is a property of the network. These two types of oscillations coexist in many instances. It is nowadays hypothesized that behind synchronization and oscillation there is a system of coupled oscillators responsible for activities that range from locomotion and feature binding in vision to control of sleep and circadian rhythms. The huge knowledge that has been acquired on oscillators from the times of Lord Rayleigh has made the simulation of neural oscillators a very active endeavor. This has been enhanced with more recent physiological findings about small neural circuits by means of intracellular and extracellular recordings as well as imaging methods. The future of this interdisciplinary field looks very promising; some researchers are going into quantum mechanics with the idea of trying to provide a quantum description of the brain. In this work we describe some simulations using neuron models by means of which we form simple neural networks that have the capability of oscillation. We analyze the oscillatory activity with root locus method, cross-correlation histograms, and phase planes. In the more complicated neural network models there is the possibility of chaotic oscillatory activity and we study that by means of Lyapunov exponents. The companion paper shows an example of that kind.

Studies of stimulus parameters for seizure disruption using neural network simulations.

PubMed

Anderson, William S; Kudela, Pawel; Cho, Jounhong; Bergey, Gregory K; Franaszczuk, Piotr J

2007-08-01

A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic modality. The model consists of an approximately 800 mum x 800 mum region of simulated cortex, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. The cell dynamics are governed by a modified version of the Hodgkin-Huxley equations in single compartment format. Axonal connections are patterned after histological data and published models of local cortical wiring. Stimulation induced action potentials take place at the axon initial segments, according to threshold requirements on the applied electric field distribution. Stimulation induced action potentials in horizontal axonal branches are also separately simulated. The calculations are performed on a 16 node distributed 32-bit processor system. Clear differences in seizure evolution are presented for stimulated versus the undisturbed rhythmic activity. Data is provided for frequency dependent stimulation effects demonstrating a plateau effect of stimulation efficacy as the applied frequency is increased from 60 to 200 Hz. Timing of the stimulation with respect to the underlying rhythmic activity demonstrates a phase dependent sensitivity. Electrode height and position effects are also presented. Using a dipole stimulation electrode arrangement, clear orientation effects of the dipole with respect to the model connectivity is also demonstrated. A sensitivity analysis of these results as a function of the stimulation threshold is also provided.

Bioprinting: Functional droplet networks

NASA Astrophysics Data System (ADS)

Durmus, Naside Gozde; Tasoglu, Savas; Demirci, Utkan

2013-06-01

Tissue-mimicking printed networks of droplets separated by lipid bilayers that can be functionalized with membrane proteins are able to spontaneously fold and transmit electrical currents along predefined paths.

Multi-label spacecraft electrical signal classification method based on DBN and random forest

PubMed Central

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data. PMID:28486479

Multi-label spacecraft electrical signal classification method based on DBN and random forest.

PubMed

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data.

Prediction of the Seizure Suppression Effect by Electrical Stimulation via a Computational Modeling Approach.

PubMed

Ahn, Sora; Jo, Sumin; Jun, Sang Beom; Lee, Hyang Woon; Lee, Seungjun

2017-01-01

In this paper, we identified factors that can affect seizure suppression via electrical stimulation by an integrative study based on experimental and computational approach. Preferentially, we analyzed the characteristics of seizure-like events (SLEs) using our previous in vitro experimental data. The results were analyzed in two groups classified according to the size of the effective region, in which the SLE was able to be completely suppressed by local stimulation. However, no significant differences were found between these two groups in terms of signal features or propagation characteristics (i.e., propagation delays, frequency spectrum, and phase synchrony). Thus, we further investigated important factors using a computational model that was capable of evaluating specific influences on effective region size. In the proposed model, signal transmission between neurons was based on two different mechanisms: synaptic transmission and the electrical field effect. We were able to induce SLEs having similar characteristics with differentially weighted adjustments for the two transmission methods in various noise environments. Although the SLEs had similar characteristics, their suppression effects differed. First of all, the suppression effect occurred only locally where directly received the stimulation effect in the high noise environment, but it occurred in the entire network in the low noise environment. Interestingly, in the same noise environment, the suppression effect was different depending on SLE propagation mechanism; only a local suppression effect was observed when the influence of the electrical field transmission was very weak, whereas a global effect was observed with a stronger electrical field effect. These results indicate that neuronal activities synchronized by a strong electrical field effect respond more sensitively to partial changes in the entire network. In addition, the proposed model was able to predict that stimulation of a seizure focus region is more effective for suppression. In conclusion, we confirmed the possibility of a computational model as a simulation tool to analyze the efficacy of deep brain stimulation (DBS) and investigated the key factors that determine the size of an effective region in seizure suppression via electrical stimulation.

Tagging and tracking individual networks within a complex mitochondrial web with photoactivatable GFP.

PubMed

Twig, Gilad; Graf, Solomon A; Wikstrom, Jakob D; Mohamed, Hibo; Haigh, Sarah E; Elorza, Alvaro; Deutsch, Motti; Zurgil, Naomi; Reynolds, Nicole; Shirihai, Orian S

2006-07-01

Assembly of mitochondria into networks supports fuel metabolism and calcium transport and is involved in the cellular response to apoptotic stimuli. A mitochondrial network is defined as a continuous matrix lumen whose boundaries limit molecular diffusion. Observation of individual networks has proven challenging in live cells that possess dense populations of mitochondria. Investigation into the electrical and morphological properties of mitochondrial networks has therefore not yielded consistent conclusions. In this study we used matrix-targeted, photoactivatable green fluorescent protein to tag single mitochondrial networks. This approach, coupled with real-time monitoring of mitochondrial membrane potential, permitted the examination of matrix lumen continuity and fusion and fission events over time. We found that adjacent and intertwined mitochondrial structures often represent a collection of distinct networks. We additionally found that all areas of a single network are invariably equipotential, suggesting that a heterogeneous pattern of membrane potential within a cell's mitochondria represents differences between discrete networks. Interestingly, fission events frequently occurred without any gross morphological changes and particularly without fragmentation. These events, which are invisible under standard confocal microscopy, redefine the mitochondrial network boundaries and result in electrically disconnected daughter units.

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

A Design of a Network Model to the Electric Power Trading System Using Web Services

NASA Astrophysics Data System (ADS)

Maruo, Tomoaki; Matsumoto, Keinosuke; Mori, Naoki; Kitayama, Masashi; Izumi, Yoshio

Web services are regarded as a new application paradigm in the world of the Internet. On the other hand, many business models of a power trading system has been proposed to aim at load reduction by consumers cooperating with electric power suppliers in an electric power market. Then, we propose a network model of power trading system using Web service in this paper. The adaptability of Web services to power trading system was checked in the prototype of our network model and we got good results for it. Each server provides functions as a SOAP server, and it is coupled loosely with each other through SOAP. Storing SOAP message in HTTP packet can establish the penetration communication way that is not conscious of a firewall. Switching of a dynamic server is possible by means of rewriting the server point information on WSDL at the time of obstacle generating.

Tickling the retina: integration of subthreshold electrical pulses can activate retinal neurons

NASA Astrophysics Data System (ADS)

Sekhar, S.; Jalligampala, A.; Zrenner, E.; Rathbun, D. L.

2016-08-01

Objective. The field of retinal prosthetics has made major progress over the last decade, restoring visual percepts to people suffering from retinitis pigmentosa. The stimulation pulses used by present implants are suprathreshold, meaning individual pulses are designed to activate the retina. In this paper we explore subthreshold pulse sequences as an alternate stimulation paradigm. Subthreshold pulses have the potential to address important open problems such as fading of visual percepts when patients are stimulated at moderate pulse repetition rates and the difficulty in preferentially stimulating different retinal pathways. Approach. As a first step in addressing these issues we used Gaussian white noise electrical stimulation combined with spike-triggered averaging to interrogate whether a subthreshold sequence of pulses can be used to activate the mouse retina. Main results. We demonstrate that the retinal network can integrate multiple subthreshold electrical stimuli under an experimental paradigm immediately relevant to retinal prostheses. Furthermore, these characteristic stimulus sequences varied in their shape and integration window length across the population of retinal ganglion cells. Significance. Because the subthreshold sequences activate the retina at stimulation rates that would typically induce strong fading (25 Hz), such retinal ‘tickling’ has the potential to minimize the fading problem. Furthermore, the diversity found across the cell population in characteristic pulse sequences suggests that these sequences could be used to selectively address the different retinal pathways (e.g. ON versus OFF). Both of these outcomes may significantly improve visual perception in retinal implant patients.

Intrinsic Neuronal Properties Switch the Mode of Information Transmission in Networks

PubMed Central

Gjorgjieva, Julijana; Mease, Rebecca A.; Moody, William J.; Fairhall, Adrienne L.

2014-01-01

Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission. PMID:25474701

Platonic Relationships among Resistors

ERIC Educational Resources Information Center

Allen, Bradley; Liu, Tongtian

2015-01-01

Calculating the effective resistance of an electrical network is a common problem in introductory physics courses. Such calculations are typically restricted to two-dimensional networks, though even such networks can become increasingly complex, leading to several studies on their properties. Furthermore, several authors have used advanced…

Power processing

NASA Technical Reports Server (NTRS)

Schwarz, F. C.

1971-01-01

Processing of electric power has been presented as a discipline that draws on almost every field of electrical engineering, including system and control theory, communications theory, electronic network design, and power component technology. The cost of power processing equipment, which often equals that of expensive, sophisticated, and unconventional sources of electrical energy, such as solar batteries, is a significant consideration in the choice of electric power systems.

Porous mesocarbon microbeads with graphitic shells: constructing a high-rate, high-capacity cathode for hybrid supercapacitor

PubMed Central

Lei, Yu; Huang, Zheng-Hong; Yang, Ying; Shen, Wanci; Zheng, Yongping; Sun, Hongyu; Kang, Feiyu

2013-01-01

Li4Ti5O12/activated carbon hybrid supercapacitor can combine the advantages of both lithium-ion battery and supercapacitor, which may meet the requirements for developing high-performance hybrid electric vehicles. Here we proposed a novel “core-shell” porous graphitic carbon (PGC) to replace conventional activated carbon for achieving excellent cell performance. In this PGC structure made from mesocarbon microbead (MCMB), the inner core is composed of porous amorphous carbon, while the outer shell is graphitic carbon. The abundant porosity and the high surface area not only offer sufficient reaction sites to store electrical charge physically, but also can accelerate the liquid electrolyte to penetrate the electrode and the ions to reach the reacting sites. Meanwhile, the outer graphitic shells of the porous carbon microbeads contribute to a conductive network which will remarkably facilitate the electron transportation, and thus can be used to construct a high-rate, high-capacity cathode for hybrid supercapacitor, especially at high current densities. PMID:23963328

On the watch for geomagnetic storms

USGS Publications Warehouse

Green, Arthur W.; Brown, William M.

1997-01-01

Geomagnetic storms, induced by solar activity, pose significant hazards to satellites, electrical power distribution systems, radio communications, navigation, and geophysical surveys. Strong storms can expose astronauts and crews of high-flying aircraft to dangerous levels of radiation. Economic losses from recent geomagnetic storms have run into hundreds of millions of dollars. With the U.S. Geological Survey (USGS) as the lead agency, an international network of geomagnetic observatories monitors the onset of solar-induced storms and gives warnings that help diminish losses to military and commercial operations and facilities.

David Palchak | NREL

Science.gov Websites

Electrical load forecasting with artificial neural networks Demand-side management optimization with Matlab -58491. D. Palchak, S. Suryanarayanan, and D. Zimmerle. "An Artificial Neural Network in Short-Term

Investigation of a generator system for generating electrical power, to supply directly to the public network, using a windmill

NASA Technical Reports Server (NTRS)

Tromp, C.

1979-01-01

A windpowered generator system is described which uses a windmill to convert mechanical energy to electrical energy for a three phase (network) voltage of constant amplitude and frequency. The generator system controls the windmill by the number of revolutions so that the power drawn from the wind for a given wind velocity is maximum. A generator revolution which is proportional to wind velocity is achieved. The stator of the generator is linked directly to the network and a feed converter at the rotor takes care of constant voltage and frequency at the stator.

Cellular computational platform and neurally inspired elements thereof

DOEpatents

Okandan, Murat

2016-11-22

A cellular computational platform is disclosed that includes a multiplicity of functionally identical, repeating computational hardware units that are interconnected electrically and optically. Each computational hardware unit includes a reprogrammable local memory and has interconnections to other such units that have reconfigurable weights. Each computational hardware unit is configured to transmit signals into the network for broadcast in a protocol-less manner to other such units in the network, and to respond to protocol-less broadcast messages that it receives from the network. Each computational hardware unit is further configured to reprogram the local memory in response to incoming electrical and/or optical signals.

Towards a magnetoresistive platform for neural signal recording

NASA Astrophysics Data System (ADS)

Sharma, P. P.; Gervasoni, G.; Albisetti, E.; D'Ercoli, F.; Monticelli, M.; Moretti, D.; Forte, N.; Rocchi, A.; Ferrari, G.; Baldelli, P.; Sampietro, M.; Benfenati, F.; Bertacco, R.; Petti, D.

2017-05-01

A promising strategy to get deeper insight on brain functionalities relies on the investigation of neural activities at the cellular and sub-cellular level. In this framework, methods for recording neuron electrical activity have gained interest over the years. Main technological challenges are associated to finding highly sensitive detection schemes, providing considerable spatial and temporal resolution. Moreover, the possibility to perform non-invasive assays would constitute a noteworthy benefit. In this work, we present a magnetoresistive platform for the detection of the action potential propagation in neural cells. Such platform allows, in perspective, the in vitro recording of neural signals arising from single neurons, neural networks and brain slices.

The Combined Release and Radiation Effects Satellite program (CRRES): A unique series of scientific experiments

NASA Technical Reports Server (NTRS)

1991-01-01

CRRES is a program to study the space environment which surrounds Earth and the effects of space radiation on modern satellite electronic systems. The satellite will carry an array of active experiments including chemical releases and a complement of sophisticated scientific instruments to accomplish these objectives. Other chemical release active experiments will be performed with suborbital rocket probes. These chemical releases will paint the magnetic and electric fields in Earthspace with clouds of glowing ions. Earthspace will be a laboratory, and the releases will be studied with an extensive network of ground-, aircraft-, and satellite-based diagnostic instruments.

Effective Connectivity Reveals Largely Independent Parallel Networks of Face and Body Patches.

PubMed

Premereur, Elsie; Taubert, Jessica; Janssen, Peter; Vogels, Rufin; Vanduffel, Wim

2016-12-19

The primate brain processes objects in the ventral visual pathway. One object category, faces, is processed in a hierarchical network of interconnected areas along this pathway. It remains unknown whether such an interconnected network is specific for faces or whether there are similar networks for other object classes. For example, the primate inferotemporal cortex also contains a set of body-selective patches, adjacent to the face-selective patches, but it is not known whether these body-selective patches form a similar discretely connected network or whether cross-talk exists between the face- and body-processing systems. To address these questions, we combined fMRI with electrical microstimulation to determine the effective connectivity of fMRI-defined face and body patches. We found that microstimulation of face patches caused increased fMRI activation throughout the face-processing system; microstimulation of the body patches gave similar results restricted to the body-processing system. Critically, our results revealed largely segregated connectivity patterns for the body and face patches. These results suggest that face and body patches form two interconnected hierarchical networks that are largely separated within the monkey inferotemporal cortex. Only a restricted number of voxels were activated by stimulation of both the body and face patches. The latter regions may be important for the integration of face and body information. Our findings are not only essential to advance our understanding of the neural circuits that enable social cognition, but they also provide further insights into the organizing principles of the inferotemporal cortex. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization based on benefit of regional energy suppliers of distributed generation in active distribution network

NASA Astrophysics Data System (ADS)

Huo, Xianxu; Li, Guodong; Jiang, Ling; Wang, Xudong

2017-08-01

With the development of electricity market, distributed generation (DG) technology and related policies, regional energy suppliers are encouraged to build DG. Under this background, the concept of active distribution network (ADN) is put forward. In this paper, a bi-level model of intermittent DG considering benefit of regional energy suppliers is proposed. The objective of the upper level is the maximization of benefit of regional energy suppliers. On this basis, the lower level is optimized for each scene. The uncertainties of DG output and load of users, as well as four active management measures, which include demand-side management, curtailing the output power of DG, regulating reactive power compensation capacity and regulating the on-load tap changer, are considered. Harmony search algorithm and particle swarm optimization are combined as a hybrid strategy to solve the model. This model and strategy are tested with IEEE-33 node system, and results of case study indicate that the model and strategy successfully increase the capacity of DG and benefit of regional energy suppliers.

In Vitro Studies of Neuronal Networks and Synaptic Plasticity in Invertebrates and in Mammals Using Multielectrode Arrays

PubMed Central

Tessadori, Jacopo; Ghirardi, Mirella

2015-01-01

Brain functions are strictly dependent on neural connections formed during development and modified during life. The cellular and molecular mechanisms underlying synaptogenesis and plastic changes involved in learning and memory have been analyzed in detail in simple animals such as invertebrates and in circuits of mammalian brains mainly by intracellular recordings of neuronal activity. In the last decades, the evolution of techniques such as microelectrode arrays (MEAs) that allow simultaneous, long-lasting, noninvasive, extracellular recordings from a large number of neurons has proven very useful to study long-term processes in neuronal networks in vivo and in vitro. In this work, we start off by briefly reviewing the microelectrode array technology and the optimization of the coupling between neurons and microtransducers to detect subthreshold synaptic signals. Then, we report MEA studies of circuit formation and activity in invertebrate models such as Lymnaea, Aplysia, and Helix. In the following sections, we analyze plasticity and connectivity in cultures of mammalian dissociated neurons, focusing on spontaneous activity and electrical stimulation. We conclude by discussing plasticity in closed-loop experiments. PMID:25866681

Analysis of large power systems

NASA Technical Reports Server (NTRS)

Dommel, H. W.

1975-01-01

Computer-oriented power systems analysis procedures in the electric utilities are surveyed. The growth of electric power systems is discussed along with the solution of sparse network equations, power flow, and stability studies.

Distribution and Network of Basal Temporal Language Areas: A Study of the Combination of Electric Cortical Stimulation and Diffusion Tensor Imaging.

PubMed

Enatsu, Rei; Kanno, Aya; Ookawa, Satoshi; Ochi, Satoko; Ishiai, Sumio; Nagamine, Takashi; Mikuni, Nobuhiro

2017-10-01

The basal temporal language area (BTLA) is considered to have several functions in language processing; however, its brain network is still unknown. This study investigated the distribution and networks of the BTLA using a combination of electric cortical stimulation and diffusion tensor imaging (DTI). 10 patients with intractable focal epilepsy who underwent presurgical evaluation with subdural electrodes were enrolled in this study (language dominant side: 6 patients, language nondominant side: 4 patients). Electric stimulation at 50 Hz was applied to the electrodes during Japanese sentence reading, morphograms (kanji) reading, and syllabograms (kana) reading tasks to identify the BTLA. DTI was used to identify the subcortical fibers originating from the BTLA found by electric stimulation. The BTLA was found in 6 patients who underwent implantation of the subdural electrodes in the dominant hemisphere. The BTLA was located anywhere between 20 mm and 56 mm posterior to the temporal tips. In 3 patients, electric stimulation of some or all areas within the BTLA induced disturbance in reading of kanji words only. DTI detected the inferior longitudinal fasciculus (ILF) in all patients and the uncinate fasciculus (UF) in 1 patient, originating from the BTLA. ILF was detected from both kanji-specific areas and kanji-nonspecific areas. This study indicates that the network of the BTLA is a part of a ventral stream and is mainly composed of the ILF, which acts as a critical structure for lexical retrieval. ILF is also associated with the specific processing of kanji words. Copyright © 2017 Elsevier Inc. All rights reserved.

Resting state functional connectivity: its physiological basis and application in neuropharmacology.

PubMed

Lu, Hanbing; Stein, Elliot A

2014-09-01

Brain structures do not work in isolation; they work in concert to produce sensory perception, motivation and behavior. Systems-level network activity can be investigated by resting state magnetic resonance imaging (rsMRI), an emerging neuroimaging technique that assesses the synchrony of the brain's ongoing spontaneous activity. Converging evidence reveals that rsMRI is able to consistently identify distinct spatiotemporal patterns of large-scale brain networks. Dysregulation within and between these networks has been implicated in a number of neurodegenerative and neuropsychiatric disorders, including Alzheimer's disease and drug addiction. Despite wide application of this approach in systems neuroscience, the physiological basis of these fluctuations remains incompletely understood. Here we review physiological studies in electrical, metabolic and hemodynamic fluctuations that are most pertinent to the rsMRI signal. We also review recent applications to neuropharmacology - specifically drug effects on resting state fluctuations. We speculate that the mechanisms governing spontaneous fluctuations in regional oxygenation availability likely give rise to the observed rsMRI signal. We conclude by identifying several open questions surrounding this technique. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Published by Elsevier Ltd.

Skeleton-supported stochastic networks of organic memristive devices: Adaptations and learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erokhina, Svetlana; Sorokin, Vladimir; Erokhin, Victor, E-mail: victor.erokhin@fis.unipr.it

Stochastic networks of memristive devices were fabricated using a sponge as a skeleton material. Cyclic voltage-current characteristics, measured on the network, revealed properties, similar to the organic memristive device with deterministic architecture. Application of the external training resulted in the adaptation of the network electrical properties. The system revealed an improved stability with respect to the networks, composed from polymer fibers.

Airborne Network Optimization with Dynamic Network Update

DTIC Science & Technology

2015-03-26

Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University...Member Dr. Barry E. Mullins Member AFIT-ENG-MS-15-M-030 Abstract Modern networks employ congestion and routing management algorithms that can perform...airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The

A Planning Guide for Instructional Networks, Part II.

ERIC Educational Resources Information Center

Daly, Kevin F.

1994-01-01

This second in a series of articles on planning for instructional computer networks focuses on site preparation, installation, service, and support. Highlights include an implementation schedule; classroom and computer lab layouts; electrical power needs; workstations; network cable; telephones; furniture; climate control; and security. (LRW)

Multiscaling statistics of high frequency global solar radiation data in the Guadeloupean Archipelago

NASA Astrophysics Data System (ADS)

Calif, R.; Schmitt, F. G.; Huang, Y.; Soubdhan, T.

2013-12-01

The part of the solar power production from photovoltaiccs systems is constantly increasing in the electric grids. Solar energy converter devices such as photovoltaic cells are very sensitive to instantaneous solar radiation fluctuations. Thus rapid variation of solar radiation due to changes in the local meteorological condition can induce large amplitude fluctuations of the produced electrical power and reduce the overall efficiency of the system. When large amount of photovoltaic electricity is send into a weak or small electricity network such as island network, the electric grid security can be in jeopardy due to these power fluctuations. The integration of this energy into the electrical network remains a major challenge, due to the high variability of solar radiation in time and space. To palliate these difficulties, it is essential to identify the characteristic of these fluctuations in order to anticipate the eventuality of power shortage or power surge. A good knowledge of the intermittency of global solar radiation is crucial for selecting the location of a solar power plant and predicting the generation of electricity. This work presents a multifractal analysis study of 367 daily global solar radiation sequences measured with a sampling rate of 1 Hz over one year at Guadeloupean Archipelago (French West Indies) located at 16o15'N latitude and 60o30'W longitude. The mean power spectrum computed follows a power law behaviour close to the Kolmogorov spectrum. The intermittent and multifractal properties of global solar radiation data are investigated using several methods. Under this basis, a characterization for each day using three multifractal parameters is proposed.

Study on Fuel Cell Network System Considering Reduction in Fuel Cell Capacity Using Load Leveling and Heat Release Loss

NASA Astrophysics Data System (ADS)

Obara, Shin'ya; Kudo, Kazuhiko

Reduction in fuel cell capacity linked to a fuel cell network system is considered. When the power demand of the whole network is small, some of the electric power generated by the fuel cell is supplied to a water electrolysis device, and hydrogen and oxygen gases are generated. Both gases are compressed with each compressor and they are stored in cylinders. When the electric demand of the whole network is large, both gases are supplied to the network, and fuel cells are operated by these hydrogen and oxygen gases. Furthermore, an optimization plan is made to minimize the quantity of heat release of the hot water piping that connects each building. Such an energy network is analyzed assuming connection of individual houses, a hospital, a hotel, a convenience store, an office building, and a factory. Consequently, compared with the conventional system, a reduction of 46% of fuel cell capacity is expected.

Fault detection and classification in electrical power transmission system using artificial neural network.

PubMed

Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

2015-01-01

This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.

The effect of learning on bursting.

PubMed

Stegenga, Jan; Le Feber, Joost; Marani, Enrico; Rutten, Wim L C

2009-04-01

We have studied the effect that learning a new stimulus-response (SR) relationship had within a neuronal network cultured on a multielectrode array. For training, we applied repetitive focal electrical stimulation delivered at a low rate (<1/s). Stimulation was withdrawn when a desired SR success ratio was achieved. It has been shown elsewhere, and we verified that this training algorithm, named conditional repetitive stimulation (CRS), can be used to strengthen an initially weak SR. So far, it remained unclear what the role of the rest of the network during learning was. We therefore studied the effect of CRS on spontaneously occurring network bursts. To this end, we made profiles of the firing rates within network bursts. We have earlier shown that these profiles change shape on a time base of several hours during spontaneous development. We show here that profiles of summed activity, called burst profiles, changed shape at an increased rate during CRS. This suggests that the whole network was involved in making the changes necessary to incorporate the desired SR relationship. However, a local (path-specific) component to learning was also found by analyzing profiles of single-electrode-activity phase profiles. Phase profiles that were not part of the SR relationship changed far less during CRS than the phase profiles of the electrodes that were part of the SR relationship. Finally, the manner in which phase profiles changed shape varied and could not be linked to the SR relationship.