scholarly journals A Model for Evolutionary Structural Plasticity and Synchronization of a Network of Neurons

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Gualberto Solís-Perales ◽  
Jairo Sánchez Estrada
Keyword(s):  
Membrane Potential ◽  
Network Structure ◽  
Structural Plasticity ◽  
Adaptive Controller ◽  
Adaptive Change ◽  
Time Dependent ◽  
Neuron Networks ◽  
Proposed Model ◽  
Structural Network ◽  
Coupling Force

A model of time-dependent structural plasticity for the synchronization of neuron networks is presented. It is known that synchronized oscillations reproduce structured communities, and this synchronization is transient since it can be enhanced or suppressed, and the proposed model reproduces this characteristic. The evolutionary behavior of the couplings is comparable to those of a network of biological neurons. In the structural network, the physical connections of axons and dendrites between neurons are modeled, and the evolution in the connections depends on the neurons’ potential. Moreover, it is shown that the coupling force’s function behaves as an adaptive controller that leads the neurons in the network to synchronization. The change in the node’s degree shows that the network exhibits time-dependent structural plasticity, achieved through the evolutionary or adaptive change of the coupling force between the nodes. The coupling force function is based on the computed magnitude of the membrane potential deviations with its neighbors and a threshold that determines the neuron’s connections. These rule the functional network structure along the time.

Noise in Integrate-and-Fire Neurons: From Stochastic Input to Escape Rates

2000 ◽  
Vol 12 (2) ◽  
pp. 367-384 ◽  
Author(s):  
Hans E. Plesser ◽  
Wulfram Gerstner
Keyword(s):  
Membrane Potential ◽  
Diffusion Approximation ◽  
Hazard Function ◽  
Time Dependent ◽  
Integrate And Fire ◽  
Probability Current ◽  
Periodic Input ◽  
Stochastic Input ◽  
Free Membrane ◽  
Noise Models

We analyze the effect of noise in integrate-and-fire neurons driven by time-dependent input and compare the diffusion approximation for the membrane potential to escape noise. It is shown that for time-dependent subthreshold input, diffusive noise can be replaced by escape noise with a hazard function that has a gaussian dependence on the distance between the (noise-free) membrane voltage and threshold. The approximation is improved if we add to the hazard function a probability current proportional to the derivative of the voltage. Stochastic resonance in response to periodic input occurs in both noise models and exhibits similar characteristics.

scholarly journals Crack-Considered Elastic Net Monitoring Model of Concrete Dam Displacement

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jiingmei Zhang ◽  
Chongshi Gu
Keyword(s):  
Water Pressure ◽  
Elastic Net ◽  
Arch Dam ◽  
Time Dependent ◽  
Concrete Dams ◽  
Displacement Monitoring ◽  
Concrete Dam ◽  
Monitoring Model ◽  
Proposed Model ◽  
Dependent Component

Displacement monitoring data modeling is important for evaluating the performance and health conditions of concrete dams. Conventional displacement monitoring models of concrete dams decompose the total displacement into the water pressure component, temperature component, and time-dependent component. And the crack-induced displacement is generally incorporated into the time-dependent component, thus weakening the interpretability of the model. In the practical engineering modeling, some significant explaining variables are selected while the others are eliminated by applying commonly used regression methods which occasionally show instability. This paper proposes a crack-considered elastic net monitoring model of concrete dam displacement to improve the interpretability and stability. In this model, the mathematical expression of the crack-induced displacement component is derived through the analysis of large surface crack’s effect on the concrete dam displacement to improve the interpretability of the model. Moreover, the elastic net method with better stability is used to solve the crack-considered displacement monitoring model. Sequentially, the proposed model is applied to analyze the radial displacement of a gravity arch dam. The results demonstrate that the proposed model contributes to more reasonable explaining variables’ selection and better coefficients’ estimation and also indicate better interpretability and higher predictive precision.

A transportation network evolution model based on link prediction

2021 ◽  
Author(s):  
Shuang Gu ◽  
Keping Li ◽  
Yan Liang ◽  
Dongyang Yan
Keyword(s):  
Network Structure ◽  
Link Prediction ◽  
Transportation Networks ◽  
Network Evolution ◽  
Evolution Model ◽  
Civil Aviation ◽  
Node Degree ◽  
Network Efficiency ◽  
Evolution Mechanism ◽  
Proposed Model

An effective and reliable evolution model can provide strong support for the planning and design of transportation networks. As a network evolution mechanism, link prediction plays an important role in the expansion of transportation networks. Most of the previous algorithms mainly took node degree or common neighbors into account in calculating link probability between two nodes, and the structure characteristics which can enhance global network efficiency are rarely considered. To address these issues, we propose a new evolution mechanism of transportation networks from the aspect of link prediction. Specifically, node degree, distance, path, expected network structure, relevance, population and GDP are comprehensively considered according to the characteristics and requirements of the transportation networks. Numerical experiments are done with China’s high-speed railway network, China’s highway network and China’s inland civil aviation network. We compare receiver operating characteristic curve and network efficiency in different models and explore the degree and hubs of networks generated by the proposed model. The results show that the proposed model has better prediction performance and can effectively optimize the network structure compared with other baseline link prediction methods.

scholarly journals Group Scheduling Problems with Time-Dependent and Position-Dependent DeJong’s Learning Effect

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li Sun ◽  
Lei Ning ◽  
Jia-zhen Huo
Keyword(s):  
Polynomial Time ◽  
Completion Time ◽  
Learning Effect ◽  
Time Dependent ◽  
Total Weighted Completion Time ◽  
Group Scheduling ◽  
Scheduling Problems ◽  
Scheduling Model ◽  
Proposed Model ◽  
Weighted Completion Time

In this paper, we introduce a group scheduling model with time-dependent and position-dependent DeJong’s learning effect. The objectives of scheduling problems are to minimize makespan, the total completion time, and the total weighted completion time, respectively. We show that the problems remain solvable in polynomial time under the proposed model.

Ca2+-activated Cl− current in cultured myenteric neurons from murine proximal colon

2003 ◽  
Vol 284 (4) ◽  
pp. C839-C847 ◽  
Author(s):  
Sok Han Kang ◽  
Pieter Vanden Berghe ◽  
Terence K. Smith
Keyword(s):  
Membrane Potential ◽  
Channel Blocker ◽  
Reversal Potential ◽  
Outward Current ◽  
Proximal Colon ◽  
Time Dependent ◽  
Equilibrium Potential ◽  
Resting Membrane Potential ◽  
Myenteric Neurons ◽  
Whole Cell Patch Clamp

Whole cell patch-clamp recordings were made from cultured myenteric neurons taken from murine proximal colon. The micropipette contained Cs+ to remove K+ currents. Depolarization elicited a slowly activating time-dependent outward current ( I tdo), whereas repolarization was followed by a slowly deactivating tail current ( I tail). I tdo and I tail were present in ∼70% of neurons. We identified these currents as Cl− currents ( I Cl), because changing the transmembrane Cl− gradient altered the measured reversal potential ( E rev) of both I tdo and I tail with that for I tailshifted close to the calculated Cl− equilibrium potential ( E Cl). I Cl are Ca2+-activated Cl− current [ I Cl(Ca)] because they were Ca2+dependent. E Cl, which was measured from the E rev of I Cl(Ca) using a gramicidin perforated patch, was −33 mV. This value is more positive than the resting membrane potential (−56.3 ± 2.7 mV), suggesting myenteric neurons accumulate intracellular Cl−. ω-Conotoxin GIVA [0.3 μM; N-type Ca2+ channel blocker] and niflumic acid [10 μM; known I Cl(Ca) blocker], decreased the I Cl(Ca). In conclusion, these neurons have I Cl(Ca) that are activated by Ca2+entry through N-type Ca2+ channels. These currents likely regulate postspike frequency adaptation.

scholarly journals A Modified k – ε Turbulence Model for a Wave Breaking Simulation

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2282
Author(s):  
Giovanni Cannata ◽  
Federica Palleschi ◽  
Benedetta Iele ◽  
Francesco Gallerano
Keyword(s):  
Energy Dissipation ◽  
Turbulence Model ◽  
Wave Breaking ◽  
A Priori ◽  
Time Dependent ◽  
Breaking Wave ◽  
Vertical Coordinate ◽  
Initial Wave ◽  
Proposed Model ◽  
Curvilinear Coordinate

We propose a two-equation turbulence model based on modification of the k − ε standard model, for simulation of a breaking wave. The proposed model is able to adequately simulate the energy dissipation due to the wave breaking and does not require any “a priori” criterion to locate the initial wave breaking point and the region in which the turbulence model has to be activated. In order to numerically simulate the wave propagation from deep water to the shoreline and the wave breaking, we use a model in which vector and tensor quantities are expressed in terms of Cartesian components, where only the vertical coordinate is expressed as a function of a time-dependent curvilinear coordinate that follows the free surface movements. A laboratory test is numerically reproduced with the aim of validating the turbulence modified k − ε model. The numerical results compared with the experimental measurements show that the proposed turbulence model is capable of correctly estimating the energy dissipation induced by the wave breaking, in order to avoid any underestimation of the wave height.

scholarly journals Evolution of Network Structure and Mechanical Properties in Autonomous-Strengthening Dental Adhesive

Polymers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2076 ◽  
Author(s):  
Rizacan Sarikaya ◽  
Linyong Song ◽  
Qiang Ye ◽  
Anil Misra ◽  
Candan Tamerler ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Network Structure ◽  
Permanent Deformation ◽  
Hydrolytic Stability ◽  
Time Dependent ◽  
Rational Approach ◽  
Aqueous Environment ◽  
Experimental Sample ◽  
Dental Resins ◽  
By Products

The inherent degradation property of most dental resins in the mouth leads to the long-term release of degradation by-products at the adhesive/tooth interface. The by-products increase the virulence of cariogenic bacteria, provoking a degradative positive-feedback loop that leads to physicochemical and mechanical failure. Photoinduced free-radical polymerization and sol‒gel reactions have been coupled to produce a novel autonomous-strengthening adhesive with enhanced hydrolytic stability. This paper investigates the effect of network structure on time-dependent mechanical properties in adhesives with and without autonomous strengthening. Stress relaxation was conducted under 0.2% strain for 8 h followed by 40 h recovery in water. The stress‒time relationship is analyzed by nonlinear least-squares data-fitting. The fitted Prony series predicts the sample’s history under monotonic loading. Results showed that the control failed after the first loading‒unloading‒recovery cycle with permanent deformation. While for the experimental sample, the displacement was almost completely recovered and the Young’s modulus increased significantly after the first test cycle. The experimental polymer exhibited higher degree of conversion, lower leachate, and time-dependent stiffening characteristics. The autonomous-strengthening reaction persists in the aqueous environment leading to a network with enhanced resistance to deformation. The results illustrate a rational approach for tuning the viscoelasticity of durable dental adhesives.

Characterization of the Time-Dependent Rheological Behavior of Fluids for Electronics Packaging

2003 ◽  
Author(s):  
X. B. Chen ◽  
W. J. Zhang ◽  
G. Schoenau ◽  
B. W. Surgenor
Keyword(s):  
Rheological Behavior ◽  
Flow Behavior ◽  
Electronics Packaging ◽  
Structural Theory ◽  
Time Dependent ◽  
Fluid Behavior ◽  
Proposed Model ◽  
Key Issues

To effectively control the dispensing process by which fluids are delivered onto substrates in electronics packaging, one of the key issues is to understand and characterize the flow behavior of the fluids being dispensed. However, this task has proven to be a demanding one as the fluids used for electronics packaging usually exhibit the time-dependent rheological behavior, which has not been well documented in the literature. In this paper, the characterization of time-dependent rheological behavior of fluids is studied. In particular, a model using the structural theory is proposed and applied to the characterization of the decay and recovery of fluid behavior, which are typically encountered in a dispensing process. Experiments are conducted to validate the proposed model.

Protective effect of the dimer of 16,16-diMePGB1 against KCN-induced mitochondrial failure in hepatocytes

1992 ◽  
Vol 263 (2) ◽  
pp. C405-C411 ◽  
Author(s):  
Y. Park ◽  
T. M. Devlin ◽  
D. P. Jones
Keyword(s):  
Membrane Potential ◽  
Protective Effect ◽  
Ion Transport ◽  
Mitochondrial Membrane Potential ◽  
Mitochondrial Function ◽  
Mitochondrial Membrane ◽  
Time Dependent ◽  
Dependent Manner ◽  
Protective Effects ◽  
Cellular Swelling

The dimer and trimer of 16,16-dimethyl-15-dehydroprostaglandin B1 (16,16-diMePGB1) previously have been shown to have protective effects on mitochondrial function. To examine the potential mechanisms involved in protection against mitochondrial failure, we have studied the effects of the dimer of 16,16-diMe-PGB1 (dicalciphor) on mitochondrial function in hepatocytes exposed to KCN. Addition of micromolar concentrations of dicalciphor provided substantial protection against KCN-induced toxicity in a concentration- and time-dependent manner. Dicalciphor, however, had no effect on total or mitochondrial ATP losses in KCN-treated cells. The dimer prevented the marked loss of mitochondrial membrane potential (delta psi) and delta pH that occurs as a result of KCN treatment and prevented KCN-induced loading of phosphate in mitochondria. Furthermore, the dimer of 16,16-diMePGB1 also prevented KCN-induced mitochondrial and cellular swelling. These results demonstrate that dicalciphor protects against KCN-induced damage and that this protection is associated with regulation of specific mitochondrial ion transport functions.

scholarly journals Aerodynamic Modeling of Multistage Compressor Flowfields: Part 2 — Modeling Deterministic Stresses

1997 ◽  
Author(s):  
Edward J. Hall
Keyword(s):  
Test Data ◽  
Axial Flow ◽  
Time Dependent ◽  
State University ◽  
Turbine Engine ◽  
Prediction Scheme ◽  
Proposed Model ◽  
Multistage Compressors ◽  
Multistage Compressor ◽  
Flow Compressor

The primary purpose of this study was to investigate improved numerical techniques for predicting flows through multistage compressors. The vehicle chosen for this study was the Pennsylvania State University Research Compressor (PSRC). The PSRC facility consists of a 3-1/2 stage axial flow compressor which shares design features which are consistent with embedded stages of modern gas turbine engine axial flow compressors. In Part 2 of this two part paper, time-dependent predictions of rotor/stator/rotor aerodynamic interactions were employed to quantify the levels and distribution of deterministic stresses resulting from the average-passage flowfield description. Details of the spanwise and blade-to-blade distributions of the velocity correlations are examined and compared with results based on physical deterministic flow structures such as blade wakes and clearance flows. The predicted “apparent” wake profile decay resulting from the interaction of the wake through a downstream blade row is presented and compared with test data. This “apparent” wake profile decay is employed to define a simplified model for deterministic stress correlations in a steady state flowfield prediction scheme which retains the “mixing plane” methodology. Calculations based on this proposed model are described and predicted results are compared with both time-dependent predictions and test data. The resulting prediction strategy is both computational efficient and contains sufficient physical realism to permit its use in design studies.

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