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Abstract The rational utilization of energy is an important issue for sustainable development. Electrically coupled integrated energy systems can enhance energy utilization efficiency and reduce energy costs. However, traditional integrated energy system optimization has problems with local optima and slow convergence speed, which cannot fully utilize energy resources. Therefore, this study proposes an improved electrical coupling integrated energy system on the ground of particle swarm optimization algorithm. In response to the problems of local optima and slow convergence speed in traditional optimization algorithms, particle swarm optimization algorithm is introduced for system optimization. By combining PSO with simulated annealing algorithm, the possibility of PSO in global optimization is reduced. The local search ability of PSO and the global search ability of simulated annealing algorithm are used to find the optimal solution. The particle swarm optimization algorithm is used for preliminary search. When the particle falls into the local optimal, the simulated annealing algorithm is introduced for global search, and the particle is guided to jump out of the local optimal and continue searching. The experiment demonstrates that the improved algorithm has certain advantages in solving test functions. The variance, mean, and optimal values are 0.00125, 0.13874, and 0.105531, respectively, which are all better than the particle swarm optimization algorithm. The simulated annealing algorithm improved the particle swarm optimization algorithm with a high accuracy index, which eventually stabilized above 0.9, and the recall index also remained above 0.8. After 100 iterations, it had already fallen into a local optimal solution. By applying the improved hybrid optimization algorithm to the electrically-coupled integrated energy system, the distribution of various energy sources can be managed and optimized more effectively, and the overall performance of the system can be improved. Especially when dealing with complex energy scheduling and distribution problems, the algorithm can provide more stable, efficient and reliable solutions. This study can achieve efficient operation and optimized scheduling of integrated energy systems, reduce energy consumption and environmental pollution, and reduce energy costs. And it can improve the reliability and stability of energy supply, which has important application value and research significance.

This paper firstly establishes the mathematical models of electric networks, natural gas networks and electrically coupled equipment, respectively, and models them comprehensively to form the basic architecture of an electrically coupled integrated energy system. Based on this, an integrated energy system planning model based on the ARIMA-LSTM model is proposed, and the objective function is optimized. Among them, the ARIMA model is used to fix the order of the objective function, and the LSTM model is used to train the backpropagation of the error of the objective function. Finally, the effectiveness of electrical cost planning and CO2 emission planning is verified by simulation experiments under two scenarios. The results show that scenario 1 saves $79,799.8 in electricity cost and reduces 11,612 t of CO2 emissions compared with scenario 2, which is not configured with an electrically coupled integrated energy system. The research in this paper provides new ideas and methods for the planning of electrically coupled integrated energy systems, which have certain academic value and application prospects.

When systems experience a severe fault, splitting, as the final line of defense to ensure the stability of the power system, holds immense significance. The precise selection of splitting sections has become the current focal point of research. Addressing the challenges of a large search space and unclear splitting sections, this paper introduces a grid structure optimization algorithm based on electrical coupling degree. Firstly, employing the theory of slow coherency, a generalized characteristic analysis of the system is conducted, leading to an initial division of coherency groups. Subsequently, an electrical coupling degree index, taking into account the inertia of generators, is proposed. This index can reflect the clarity of grid splitting. Furthermore, a two-layer optimization model for grid structure is constructed, utilizing the Proximal Policy Optimization (PPO) algorithm to optimize the grid structure. This process reduces the size of the splitting space and mitigates the difficulty of acquiring splitting sections. Finally, simulation validation is performed using the IEEE-118-bus system to demonstrate the effectiveness of the proposed optimization algorithm.

In this study, the electrical characteristics and electrical coupling effect for monolithic 3-dimensional nonvolatile memory consisting of a feedback field-effect transistor (M3D-NVM-FBFET) were investigated using technology computer-aided design. The M3D-NVM-FBFET consists of an N-type FBFET with an oxide–nitride–oxide layer and a metal–oxide–semiconductor FET (MOSFET) in the top and bottom tiers, respectively. For the memory simulation, the programming and erasing voltages were applied at 18 and −18 V for 1 μs, respectively. The memory window of the M3D-NVM-FBFET was 1.98 V. As the retention simulation was conducted for 10 years, the memory window decreased from 1.98 to 0.83 V. For the M3D-NVM-FBFET, the electrical coupling that occurs through an electrical signal in the bottom-tier transistor was investigated. As the thickness of the interlayer dielectric (TILD) decreases from 100 to 10 nm, the change in the VTH increases from 0.16 to 0.87 V and from 0.15 to 0.84 V after the programming and erasing operations, respectively. M3D-NVM-FBFET circuits with a thin TILD of 50 nm or less need to be designed considering electrical coupling.

The effect of the work-function variation (WFV) of metal-oxide-semiconductor field-effect transistor (MOSFET) gates on a monolithic 3D inverter (M3DINV) structure is investigated in the current paper. The M3DINV has a structure in which MOSFETs are sequentially stacked. The WFV effect of the top- and bottom-tier gates on the M3DINV is investigated using technology computer-aided design (TCAD) and a Monte-Carlo sampling simulation of TCAD. When the interlayer dielectric thickness (TILD) changes from 5 to 100 nm, electrical parameters, such as the threshold voltage, subthreshold swing, on-current, and off-current of the top-tier N-MOSFET and the parameter changes by the change in gate voltage of the bottom-tier P-MOSFET, are investigated. As TILD decreases below about 30 nm, the means and standard deviations of the electrical parameters rapidly increase. This means that the coupling and its distribution are relatively large in the regime and thus should be well considered for M3D circuit simulation. In addition, due to the increase in standard deviation, the WFV effect of both the top- and bottom-tier MOSFET gates was observed to be greater than those of only the top-tier MOSFET gates and only the bottom-tier MOSFET gates.

A monolithic three-dimensional integrated static random access memory containing a feedback field effect transistor (M3D-FBFET-SRAM) was proposed. The M3D-FBFET-SRAM cell consists of one metal oxide semiconductor field effect transistor (MOSFET) and one FBFET, and each transistor is located on the top tier and one on the bottom tier in a monolithic 3D integration, respectively. The electrical characteristics and operation of the NFBFET in the M3D-FBFET-SRAM cell were investigated using a TCAD simulator. For SRAM operation, the optimum doping profile of the NFBFET was used for non-turn-off characteristics. For the M3D-FBFET-SRAM cell, the operation of the SRAM and electrical coupling occurring between the top and bottom tier transistor were investigated. As the thickness of interlayer dielectric decreases, the reading ‘ON’ current decreases. To prevent performance degradation, two ways to compensate for current level were suggested.

Electrical synaptic transmission relies on neuronal gap junctions containing channels constructed by Connexins. While at chemical synapses neurotransmitter-gated ion channels are critically supported by scaffolding proteins, it is unknown if channels at electrical synapses require similar scaffold support. Here, we investigated the functional relationship between neuronal Connexins and Zonula Occludens 1 (ZO1), an intracellular scaffolding protein localized to electrical synapses. Using model electrical synapses in zebrafish Mauthner cells, we demonstrated that ZO1 is required for robust synaptic Connexin localization, but Connexins are dispensable for ZO1 localization. Disrupting this hierarchical ZO1/Connexin relationship abolishes electrical transmission and disrupts Mauthner cell-initiated escape responses. We found that ZO1 is asymmetrically localized exclusively postsynaptically at neuronal contacts where it functions to assemble intercellular channels. Thus, forming functional neuronal gap junctions requires a postsynaptic scaffolding protein. The critical function of a scaffolding molecule reveals an unanticipated complexity of molecular and functional organization at electrical synapses.

Electrical transmission between neurons is largely mediated by gap junctions. These junctions allow the direct flow of electric current between neurons, and in mammals, they are mostly composed of the protein connexin36. Circuits of electrically coupled neurons are widespread in these animals. Plus, experimental and theoretical evidence supports the notion that, beyond synchronicity, these circuits are able to perform sophisticated operations such as lateral excitation and inhibition, noise reduction, as well as the ability to selectively respond upon coincident excitatory inputs. Although once considered stereotyped and unmodifiable, we now know that electrical synapses are subject to modulation and, by reconfiguring neural circuits, these modulations can alter relevant operations. The strength of electrical synapses depends on the gap junction resistance, as well as on its functional interaction with the electrophysiological properties of coupled neurons. In particular, voltage and ligand gated channels of the non-synaptic membrane critically determine the efficacy of transmission at these contacts. Consistently, modulatory actions on these channels have been shown to represent relevant mechanisms of plasticity of electrical synaptic transmission. Here, we review recent evidence on the regulation of electrical synapses of mammals, the underlying molecular mechanisms, and the possible ways in which they affect circuit function.

During the last decades it became increasingly evident that electrical synapses are capable of activity-dependent plasticity. However, measuring the actual strength of electrical transmission remains difficult. Usually changes in coupling strength can only be inferred indirectly from measures such as the coupling coefficient and the coupling conductance. Because these are affected by both junctional and non-junctional conductance, plastic changes can potentially be due to both components. Furthermore, these techniques also require the blocking of chemical transmission, so that processes that involve crosstalk between chemical and electrical synapses will be suppressed. To directly examine the magnitude of errors that can occur, we use dual whole-cell current- and voltage-clamp recordings from the soma of the pair of easily accessible, electrically coupled Retzius cells in the leech to simultaneously determine coupling coefficients, coupling conductances and directly measured gap junctional currents. We present the first direct and comparative analysis of gap junction conductance using all three methods and analyze how each method would characterize the response of gap junctions to serotonin. The traditional coupling coefficients showed severe deficits in assessing the symmetry and strength of electrical synapses. These were reduced when coupling conductances were determined and were absent in the direct method. Additionally, both coupling coefficient and coupling conductance caused large and systematic errors in assessing the size and time course of the serotonin-induced changes of gap junctional currents. Most importantly, both measurements can easily be misinterpreted as implying long-term gap junctional plasticity, although the direct measurements confirm its absence. We thus show directly that coupling coefficients and coupling conductances can severely confound plastic changes in membrane and junctional conductance. Wherever possible, voltage clamp measurements should be chosen to accurately characterize the timing and strength of plasticity of electrical synapses. However, we also demonstrate that coupling coefficients can still yield a qualitatively correct picture when amended by independent measurements of the course of membrane resistance during the experiments.

In this paper, we investigated the electrical coupling between the top and bottom transistors in a monolithic 3-dimensional (3D) inverter (M3INV) stacked vertically with junctionless field-effect transistor (JLFET), which is one of candidates to replace metal-oxide-semiconductor field-effect transistors (MOSFET). Currents, transconductances, and gate capacitances of the top N-type transistor at the different gate voltages of the bottom P-type transistor as a function of thickness of inter-layer dielectric (TILD) and gate channel length (Lg) are simulated using technology computer-aided-design (TCAD). In M3INV stacked vertically with MOSFET (M3INV-MOS) and JLFET (M3INV-JL), the variations of threshold voltage, transconductance, and capacitance increase as TILD decreases and they increase as Lg increases, and thus there is a strong coupling in M3INV at the range of TILD ≤ 30 nm. In M3INV, the coupling between stacked JLFETs in M3INV-JL is larger than that between MOSFETs in M3INV-MOS at the same TILD and Lg. The switching threshold voltage (Vm) and noise margins (NMs) of M3INV are calculated from the voltage transfer characteristics (VTC) simulated with TCAD mixed-mode. As the gate lengths of M3INV-MOS and M3INV-JL increase, the Vm variations increase and decrease, respectively. The smaller the gate lengths of M3INV-NOS and M3INV-JL, the larger and smaller the variation of Vm, respectively. The noise margin of M3INV-MOS is larger and better for inverter characteristics than one of M3INV-JL. M3INV-MOS has less electrical coupling than M3INV-JL.

The junctionless field-effect transistor (JLFET) compact model using the model parameters extracted from the LETI-UTSOI (version 2.1) model was proposed to perform circuit simulation considering the electrical coupling between the stacked JLFETs of a monolithic 3D integrated circuit (M3DIC) composed of JLFETs (M3DIC-JLFET). We validated the model by extracting the model parameters and comparing the simulation results of the technology computer-aided design and the Synopsys HSPICE circuit simulator. The performance of the M3DIC-JLFET was compared with that of the M3DIC composed of MOSFETs (M3DIC-MOSFET). The performance of a fan-out-3 ring oscillator with M3DIC-JLFET varied by less than 3% compared to that with M3DIC-MOSFET. The performances of ring oscillators of M3DIC-JLFET and M3DIC-MOSFET were almost the same. We simulated the performances of M3DICs such as an inverter, a NAND, a NOR, a 2 × 1 multiplexer, and a D flip-flop. The overall performance of the M3DIC-MOSFET was slightly better than that of the M3DIC-JLFET.

The Large Cell (LC) motor neurons of the crab cardiac ganglion have variable membrane conductance magnitudes even within the same individual, yet produce identical synchronized activity in the intact network. In a previous study we blocked a subset of K+ conductances across LCs, resulting in loss of synchronous activity (Lane et al., 2016). In this study, we hypothesized that this same variability of conductances makes LCs vulnerable to desynchronization during neuromodulation. We exposed the LCs to serotonin (5HT) and dopamine (DA) while recording simultaneously from multiple LCs. Both amines had distinct excitatory effects on LC output, but only 5HT caused desynchronized output. We further determined that DA rapidly increased gap junctional conductance. Co-application of both amines induced 5HT-like output, but waveforms remained synchronized. Furthermore, DA prevented desynchronization induced by the K+ channel blocker tetraethylammonium (TEA), suggesting that dopaminergic modulation of electrical coupling plays a protective role in maintaining network synchrony.

Evidence suggests that layer 5 pyramidal neurons can be divided into functional zones with unique afferent connectivity and membrane characteristics that allow for post-synaptic integration of feedforward and feedback inputs. To assess the existence of these zones and their interaction, we characterized the resonance properties of a biophysically-realistic compartmental model of a neocortical layer 5 pyramidal neuron. Consistent with recently published theoretical and empirical findings, our model was configured to have a “hot zone” in distal apical dendrite and apical tuft where both high- and low-threshold Ca2+ ionic conductances had densities 1–2 orders of magnitude higher than anywhere else in the apical dendrite. We simulated injection of broad spectrum sinusoidal currents with linearly increasing frequency to calculate the input impedance of individual compartments, the transfer impedance between the soma and key compartments within the dendritic tree, and a dimensionless term we introduce called resonance quality. We show that input resonance analysis distinguished at least four distinct zones within the model based on properties of their frequency preferences: basal dendrite which displayed little resonance; soma/proximal apical dendrite which displayed resonance at 5–23 Hz, strongest at 5–10 Hz and hyperpolarized/resting membrane potentials; distal apical dendrite which displayed resonance at 8–19 Hz, strongest at 10 Hz and depolarized membrane potentials; and apical tuft which displayed a weak resonance largely between 8 and 10 Hz across a wide range of membrane potentials. Transfer resonance analysis revealed that changes in subthreshold electrical coupling were found to modulate the transfer resonant frequency of signals transmitted from distal apical dendrite and apical tuft to the soma, which would impact the frequencies that individual neurons are expected to respond to and reinforce. Furthermore, eliminating the hot zone was found to reduce amplification of resonance within the model, which contributes to reduced excitability when perisomatic and distal apical regions receive coincident stimulating current injections. These results indicate that the interactions between different functional zones should be considered in a more complete understanding of neuronal integration. Resonance analysis may therefore be a useful tool for assessing the integration of inputs across the entire neuronal membrane.

This review highlights the most important discovery in the reticular activating system in the last 10 years, the manifestation of gamma band activity in cells of the reticular activating system (RAS), especially in the pedunculopontine nucleus, which is in charge of waking and rapid eye movement (REM) sleep. The identification of different cell groups manifesting P/Q-type Ca2+ channels that control waking vs. those that manifest N-type channels that control REM sleep provides novel avenues for the differential control of waking vs. REM sleep. Recent discoveries on the development of this system can help explain the developmental decrease in REM sleep and the basic rest-activity cycle.

In this study, fuel, oxidant supply and cooling systems with microcontroller units (MCU) are developed in a compact design to fit two 5 kW proton exchange membrane fuel cell (PEMFC) stacks. At the initial stage, the testing facility of the system has a large volume (2.0 m × 2.0 m × 1.5 m) with a longer pipeline and excessive control sensors for safe testing. After recognizing the performance and stability of stack, the system is redesigned to fit in a limited space (0.4 m × 0.5 m × 0.8 m). Furthermore, the stack performance is studied under different hydrogen recycling modes. Then, two similar 5 kW stacks are directly coupled with diodes to obtain a higher power output and safe operation. The result shows that the efficiency of the 5 kW stack is 43.46% with a purge period of 2 min with hydrogen recycling and that the hydrogen utilization rate µf is 66.31%. In addition, the maximum power output of the twin-coupled module (a power module with two stacks in electrical cascade/parallel arrangement) is 9.52 kW.

In order to simulate a circuit by applying various logic circuits and full chip using the HSPICE model, which can consider electrical coupling proposed in the previous research, it is investigated whether additional electrical coupling other than electrical coupling by top and bottom layer exists. Additional electrical coupling were verified through device simulation and confirmed to be blocked by heavily doped source/drain. Comparing the HSPICE circuit simulation results using the newly proposed monolithic 3D NAND (M3DNAND) structure in the technology computer-aided design (TCAD) mixed-mode and monolithic 3D inverter (M3DINV) unit cell model was once more verified. It is possible to simulate various logic circuits using the previously proposed M3DINV unit cell model. We simulated the operation and performances of M3DNAND, M3DNOR, 2 × 1 multiplexer (MUX), D flip-flop (D-FF), and static random access memry (SRAM).

We studied how a neuronal circuit composed of two neuron types connected by chemical and electrical synapses maintains constant its integrative capacities as neurons grow. For this we combined electrophysiological experiments with mathematical modeling in pairs of electrically-coupled Retzius neurons from postnatal to adult leeches. The electrically-coupled dendrites of both Retzius neurons receive a common chemical input, which produces excitatory postsynaptic potentials (EPSPs) with varying amplitudes. Each EPSP spreads to the soma, but also crosses the electrical synapse to arrive at the soma of the coupled neuron. The leak of synaptic current across the electrical synapse reduces the amplitude of the EPSPs in proportion to the coupling ratio. In addition, summation of EPSPs generated in both neurons generates the baseline action potentials of these serotonergic neurons. To study how integration is adjusted as neurons grow, we first studied the characteristics of the chemical and electrical connections onto the coupled dendrites of neuron pairs with soma diameters ranging from 21 to 75 μm. Then by feeding a mathematical model with the neuronal voltage responses to pseudorandom noise currents we obtained the values of the coupling ratio, the membrane resistance of the soma (rm) and dendrites (rdend), the space constant (λ) and the characteristic dendritic length (L = l/λ). We found that the EPSPs recorded from the somata were similar regardless on the neuron size. However, the amplitude of the EPSPs and the firing frequency of the neurons were inversely proportional to the coupling ratio of the neuron pair, which also was independent from the neuronal size. This data indicated that the integrative constancy relied on the passive membrane properties. We show that the growth of Retzius neurons was compensated by increasing the membrane resistance of the dendrites and therefore the λ value. By solely increasing the dendrite resistance this circuit maintains constant its integrative capacities as its neurons grow.

Normal heart rhythm (sinus rhythm) depends on regular activity of the sinoatrial node (SAN), a heterogeneous collection of specialized myocytes in the right atrium. SAN cells, in general, possess a unique electrophysiological profile that promotes spontaneous electrical activity (automaticity). However, while automaticity is required for normal pacemaking, it is not necessarily sufficient. Less appreciated is the importance of the elaborate structure of the SAN complex for proper pacemaker function. Here, we review the important structural features of the SAN with a focus on how these elements help manage a precarious balance between electrical charge generated by the SAN (source) and the charge needed to excite the surrounding atrial tissue (sink). We also discuss how compromised source-sink balance due, for example to fibrosis, may promote SAN dysfunction, characterized by slow and/or asynchronous pacemaker activity and even failure, in the setting of cardiovascular disease (e.g. heart failure, atrial fibrillation). Finally, we discuss implications of the source-sink balance in the SAN complex for cell and gene therapies aimed at creating a biological pacemaker as replacement or bridge to conventional electronic pacemakers.

Unapposed hemichannels formed by oligomerized hexamers of gap junction proteins are now known to be involved in various cellular processes under both physiological and pathological conditions. On the other hand, less is known regarding how disparities in the molecular composition of hemichannels impact electrical synaptic transmission between neurons when they form intercellular heterotypic gap junctions. Here we review data indicating that molecular differences between apposed hemichannels at electrical synapses are generally associated with rectification of electrical transmission. Furthermore, this association has been observed at both innexin and connexin based electrical synapses. We discuss the possible molecular mechanisms underlying electrical rectification, as well as the potential contribution of intracellular soluble factors to this phenomenon. Thus, asymmetries in molecular composition and sensitivity to cellular factors of each contributing hemichannel can profoundly influence the transmission of electrical signals, endowing electrical synapses with more complex functional properties.

The inferior olive (IO) is a neural network belonging to the olivo-cerebellar system whose neurons are coupled with electrical synapses and display subthreshold oscillations and spiking activity. The IO generates complex spatio-temporal patterns. The generation and modulation of coherent spiking activity in the IO is one key issue in cerebellar research. In this work, we build a large scale IO network model of electrically coupled conductance-based neurons to study the emerging spatio-temporal patterns of its transient neuronal activity. The main factors studied governing the collective dynamics of the IO network were: the degree of electrical coupling, the extent of the electrotonic connections, the presence of stimuli or regions with different excitability levels and the modulatory effect of an inhibitory loop. The spatio-temporal patterns were analyzed using a discrete wavelet transform to provide a quantitative characterization. Our results show that the electrotonic coupling produces quasi-synchronized subthreshold oscillations over a wide dynamical range. The synchronized oscillatory activity plays the role of a timer for a coordinated representation of spiking rhythms with different frequencies. The encoding and coexistence of several coordinated rhythms is related to the different clusterization and coherence of transient spatio-temporal patterns in the network, where the spiking activity is commensurate with the quasi-synchronized subthreshold oscillations. In the presence of stimuli, different rhythms are encoded in the spiking activity of IO neurons that nevertheless remains constrained to a commensurate value of the subthreshold frequency. The stimuli induced spatio-temporal patterns can reverberate for long periods, which contributes to the computational properties of the IO. We also show that the presence of regions with different excitability levels creates sinks and sources of coordinated activity which shape the propagation of spike wave fronts.

How is the cerebellum capable of efficient motor learning and control despite very low firing of the inferior olive inputs, which are postulated to carry errors needed for learning and contribute to on-line motor control? Inferior olive neurons form the largest electrically coupled network in the adult human brain. Here, we discuss how intermediate coupling strengths can lead to chaotic resonance and increase information transmission of the error signal despite the very low inferior olive firing rate. This increased information transmission can then lead to more efficient learning than with weak or strong coupling. In addition, we argue that a dynamic modulation of inferior olive electrical coupling via the Purkinje cell- deep cerebellar neurons – inferior olive triangle could speed up learning and improve on-line control. Initially strong coupling would allow transmission of large errors to multiple functionally related Purkinje cells, resulting in fast but coarse learning as well as significant effects on deep cerebellar nucleus and on-line motor control. In the late phase of learning decreased coupling would allow de-synchronized IO firing, allowing high-fidelity transmission of error, resulting in slower but fine learning, and little on-line motor control effects.

The spiking patterns of neocortical pyramidal neurons are shaped by the conductances in their apical dendrites. We have previously shown that the spiking patterns of layer 5 pyramidal neurons change with temperature, probably because temperature modulates the electrical coupling between somatic and dendritic compartments. Here we examine the effect of temperature on the spiking patterns of layer 2/3 and layer 6 pyramidal neurons in acute slices of mouse primary motor cortex. In both cell types, decreasing temperature led to more irregular spiking patterns. Our results indicate that a decrease in spiking regularity with decreasing temperature, probably mediated by increased electrical coupling between soma and dendrites, is common to all pyramidal neurons in motor cortex.