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Smart nonlinear circuits can be tamed to reproduce the main dynamical properties in neural activities and thus neural circuits are built to estimate the occurrence of multiple modes in electric activities. In the presence of electromagnetic radiation, the cardiac tissue, brain and neural circuits are influenced because field energy is injected and captured when induction field and current are generated in the media and system. In this paper, an isolated Chua circuit is exposed to external electromagnetic field and energy capturing is estimated for nonlinear analysis from physical viewpoint. Furthermore, two Chua circuits without direct variable coupling are exposed to the same electromagnetic field for energy capturing. Periodical and noise-like radiations are imposed on the Chua circuits which can capture the magnetic field energy via the induction coil. It is found that the two Chua circuits (periodical or chaotic) can reach phase synchronization and phase lock in the presence of periodical radiation. On the other hand, noise-like radiation can realize complete synchronization between two chaotic Chua circuits while phase lock occurs between two Chua circuits in periodical oscillation. It gives some important clues to control the collective behaviors of neural activities under external field. [ABSTRACT FROM AUTHOR]

The survival and occurrence of chaos are much dependent on the intrinsic nonlinearity and parameters region for deterministic nonlinear systems, which are often represented by ordinary differential equations and maps. When nonlinear circuits are mapped into dimensional dynamical systems for further nonlinear analysis, the physical parameters of electric components, e.g. capacitor, inductor, resistance, memristor, can also be replaced by dynamical parameters for possible adjustment. Slight change for some bifurcation parameters can induce distinct mode transition and dynamics change in the chaotic systems only when the parameter is adjustable and controllable. In this paper, a thermistor is included into the chaotic Chua circuit and the temperature effect is considered by investigating the mode transition in oscillation and the dependence of Hamilton energy on parameters setting in thermistor. Furthermore, the temperature of thermistor is adjusted for finding possible synchronization between two chaotic Chua circuits connected by a thermistor. When the coupling channel via thermistor connection is activated, two identical Chua circuits (periodical or chaotic oscillation) can reach complete synchronization. In particular, two periodical Chua circuits can be coupled to present chaotic synchronization by taming parameters in thermistor of coupling channel. However, phase synchronization is reached while complete synchronization becomes difficult when the coupling channel is activated to coupling a periodical Chua circuit and a chaotic Chua circuit. It can give guidance for further control of firing behaviors in neural circuits when the thermistor can capture the heat effectively. [ABSTRACT FROM AUTHOR]

Played as an important nonlinear electric device, memristor is often used to build a variety of nonlinear circuits, which can produce a variety of modes in oscillation. Due to the memory effect, the dynamics of nonlinear circuits involved with memristor can show distinct transition in oscillation between periodic and chaotic states when the initial values are changed. As a result, a generic initial-dependent dynamical system is built and its memory on initial setting is explained. The physical properties and potential mechanism for resistor-based voltage coupling, memristor coupling, capacitor-based and inductor-based field coupling are explained, respectively. In this review, scale transformation, application of memristor on neurodynamics, time delay, synchronization pattern, particularly, electromagnetic induction and radiation, neuron model setting under field effect, field coupling on signal propagation between nonlinear circuits and neurons are summarized for readers' extensive investigation. [ABSTRACT FROM AUTHOR]

Nervous system has distinct anisotropy and some intrinsic biophysical properties enable neurons present various firing modes in neural activities. In presence of realistic electromagnetic fields, non-uniform radiation activates these neurons with energy diversity. By using a feasible model, energy function is obtained to predict the growth of synaptic connections of these neurons. Distribution of average value of the Hamilton energy function vs. intensity of noisy disturbance can predict the occurrence of coherence resonance, which the neural activities show high regularity by applying noisy disturbance with moderate intensity. From physical viewpoint, the average energy value has similar role average power for the neuron. Non-uniform spatial disturbance is applied and energy is injected into the neural network, statistical synchronization factor is calculated to predict the network synchronization stability and wave propagation. The intensity for field coupling is adaptively controlled by energy diversity between adjacent neurons. Local energy balance will terminate further growth of the coupling intensity; otherwise, heterogeneity is formed in the network due to energy diversity. Furthermore, memristive channel current is introduced into the neuron model for perceiving the effect of electromagnetic induction and radiation, and a memristive neuron is obtained. The circuit implement of memristive circuit depends on the connection to a magnetic flux-controlled memristor into the mentioned neural circuit in an additive branch circuit. The connection and activation of this memristive neural network are controlled under external spatial electromagnetic radiation by capturing enough field energy. Continuous energy collection and exchange generate energy diversity and synaptic connection is created to regulate the synchronous firing patterns and energy balance. • A feasible memristive neuron is proposed and its physical property is clarified. • Average Hamilton energy is effective to predict coherence resonance under noisy disturbance. • Non-uniform radiation is applied on the neural network with adaptive coupling. • Energy level controls the growth of synaptic connections. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman spectroscopy (SERS) sandwich biosensors have received tremendous attention in early diagnosis of bacterial infections. However, efficiently engineering nanoscale plasmonic hots pots (HS) towards ultrasensitive SERS detection still remains challenging. Herein, we propose a bioinspired synergistic HS engineering strategy to construct ultrasensitive SERS sandwich bacterial sensor (named USSB), by coupling bioinspired signal module and plasmonic enrichment module to synergistically boost the number and intensity of HS. The bioinspired signal module is based on dendritic mesoporous silica nanocarrier (DMSN) loaded with plasmonic nanoparticles and SERS tag, while magnetic Fe 3 O 4 nanoparticles coated with Au shell are employed in plasmonic enrichment module. We demonstrate that DMSN effectively shrank nanogaps between plasmonic nanoparticles to improve HS intensity. Meanwhile, plasmonic enrichment module contributed to plenty of additional HS inside and outside individual "sandwich". Ascribing to the boosted number and intensity of HS, the constructed USSB sensor exhibits ultrahigh detection sensitivity (7 CFU/mL) and selectivity towards model pathogenic bacteria of Staphylococcus aureus. Remarkably, the USSB sensor enables fast and accurate bacterial detection in real blood samples of septic mice, achieving early diagnosis of bacterial sepsis. The proposed bioinspired synergistic HS engineering strategy opens up a new direction for constructing ultrasensitive SERS sandwich biosensors, and may promote their advancing applications in the early diagnosis and prognosis of devastating diseases. [ABSTRACT FROM AUTHOR]

Reliable neural circuits provide feasible ways to estimate the information encoding and signal exchange between neurons so that more physical effects can be considered and explained. Electrical synapse benefits signal propagation and neurons can give rapid response selection under an external stimulus. Chemical synapse plays a standing biological function by the continuous release of neurotransmitter. Gap junction coupling can estimate the effect of electrical synapse coupling as resistor-based voltage coupling while chemical synapse coupling shows a complex form in synapse currents. In this paper, two FitzHugh–Nagumo neuron circuits are connected by resistor and induction coil, and thus field coupling is activated to realize synchronization. It gives possible guidance to explain the synapse function from physical view. These circuit equations are obtained and scale transformation is applied to get the dimensionless dynamical systems. Furthermore, the same scheme is used to discuss synchronization realization between Hindmarsh–Rose neuron models. It is found that synchronization can be suppressed when the coupling resistor is in series with the induction coil in which only one coupling channel is open. However, complete synchronization can be enhanced when the coupling resistor is paralleled with the induction coil because two coupling channels are activated simultaneously. As a result, appropriate adjustment and selection for the coupling electric devices can induce transition from synchronization to desynchronization between neural circuits, which indicates the self-adaption of synapse when two types of synapse are activated together. [ABSTRACT FROM AUTHOR]

The exchange of charged ions across membrane can generate fluctuation of membrane potential and also complex effect of electromagnetic induction. Diversity in excitability of neurons induces different modes selection and dynamical responses to external stimuli. Based on a neuron model with electromagnetic induction, which is described by magnetic flux and memristor, a two-layer network is proposed to discuss the pattern control and wave propagation in the network. In each layer, gap junction coupling is applied to connect the neurons, while field coupling is considered between two layers of the network. The field coupling is approached by using coupling of magnetic flux, which is associated with distribution of electromagnetic field. It is found that appropriate intensity of field coupling can enhance wave propagation from one layer to another one, and beautiful spatial patterns are formed. The developed target wave in the second layer shows some difference from target wave triggered in the first layer of the network when two layers are considered by different excitabilities. The potential mechanism could be pacemaker-like driving from the first layer will be encoded by the second layer. [ABSTRACT FROM AUTHOR]

Pattern estimation and selection in media can give important clues to understand the collective response to external stimulus by detecting the observable variables. Both reaction-diffusion systems (RDs) and neuronal networks can be treated as multi-agent systems from molecular level, intrinsic cooperation, competition. An external stimulus or attack can cause collapse of spatial order and distribution, while appropriate noise can enhance the consensus in the spatiotemporal systems. Pattern formation and synchronization stability can bridge isolated oscillators and the network by coupling these nodes with appropriate connection types. As a result, the dynamical behaviors can be detected and discussed by developing different spatial patterns and realizing network synchronization. Indeed, the collective response of network and multi-agent system depends on the local kinetics of nodes and cells. It is better to know the standard bifurcation analysis and stability control schemes before dealing with network problems. In this review, dynamics discussion and synchronization control on low-dimensional systems, pattern formation and synchronization stability on network, wave stability in RDs and neuronal network are summarized. Finally, possible guidance is presented when some physical effects such as polarization field and electromagnetic induction are considered. [ABSTRACT FROM AUTHOR]

Complex electrical activities in neuron can induce time-varying electromagnetic field and the effect of various electromagnetic inductions should be considered in dealing with electrical activities of neuron. Based on an improved neuron model, the effect of electromagnetic induction is described by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. Furthermore, additive phase noise is imposed on the neuron to detect the dynamical response of neuron and phase transition in modes. The dynamical properties of electrical activities are detected and discussed, and double coherence resonance behavior is observed, respectively. Furthermore, multiple modes of electrical activities can be observed in the sampled time series for membrane potential of the neuron model. [ABSTRACT FROM AUTHOR]

Signal propagation can be blocked when the axon is injured or ion channels are blocked by certain drug, and thus signal communication between neurons can be interrupted. It is found that defects could be induced in the injured area of the axon, and the local heterogeneity can emit continuous pulses or wave fronts. In this paper, a weak electric field is imposed on the neuron to suppress the blocking of the defects on signal propagation. It is found that appropriate electric field can help signal propagate along the axon even the electric field is imposed on a local area. Its potential mechanism could be that the local electric field can suppress the wave emitting from the defects and thus the injured area can be bridged to transmit the blocked signals by adding gradient forcing along the axon. [ABSTRACT FROM AUTHOR]

Appropriate noise can enhance the regularity in electrical activity of neuron, and stochastic resonance emerges when periodic forcing is imposed on the neuron and/or neuronal network. In this paper, periodic forcing is imposed on some neurons of a two-dimensional square lattice with nearest-neighbor connection (the boundary of one side in the network of neurons), which the local kinetics of node is described by Hindmarsh-Rose neuron, while noise is imposed on another side of the two-dimensional lattice. Indeed, spiral waves can be developed in the side of the network driven by appropriate noise intensity while the another side is occupied by plane wave. A statistical factor of synchronization is defined to discern the occurrence of regularity induced by local noise and local pacing. The emitted plane wave from one side of network can be suppressed by noise and disordered state emerges with stronger noise being used on all nodes of the network, furthermore, spiral wave is induced in the network under appropriate noise intensity. The network shows spatial regularity when spiral wave is developed and it is interesting to find spiral wave can coexist with plane wave in the network. Stochastic resonance-like behavior could be observed in the two-dimensional lattice composed of neurons even if noise and periodic forcing are imposed on different areas of the network. The occurrence of spatial regularity under coherence could rely on the competition between noise driving-induced segments and wave fronts induced by periodic forcing. [ABSTRACT FROM AUTHOR]

Because of functional differentiation of biological neurons, more functional regions have been developed and formed in the brain and the neurons with the same biophysical function are connected in a specific region. Many neural circuits can be improved to exit specific functions by incorporating special electric components into the branch circuits, and they can be connected to simulate the cooperation of neurons with different biophysical properties. In this paper, three kinds of functional neural circuits are connected to develop a functional network for detecting external illumination, temperature changes and acoustic wave synchronously. The synchronous stability between neurons are much dependent on the intrinsic properties of the synaptic connection along the coupling channels. Electric synapse connection, capacitor-connection and induction coil connection are applied to trigger voltage, electric field and magnetic field couplings along the links in the neural network, respectively. Indeed, the field coupling induced by capacitive and inductive coupling can be controllable under external field by injecting energy continuously. The results indicate that the phase lock of the neural network can be stabilized by taming the coupling intensity carefully, and it can be further enhanced and switched by involving the noise. The Hamilton energy is estimated and in line with the phase synchronization. These results are helpful to know potential biophysical mechanism of synchronous firing and mode selection in the functional network. • A neural network is constructed by a light-dependent, a temperature-dependent and a piezoelectric neural circuit. • Resistor, inductor and capacitor are applied to bridge the connection between two different neural circuits. • Phase lock can be achieved in the functional network with the ability of detecting the light, temperature and sound. • The results threw light on the exploring the biophysical mechanism of synchronous firing in the functional network. [ABSTRACT FROM AUTHOR]

A temperature-dependent nonlinear circuit can be mapped into an equivalent thermosensitive neuron model and then the main dynamical properties of neural activities can be reproduced. A thermistor is connected to different branch circuits of the FHN (FitzHugh–Nagumo) neural circuit, and different thermosensitive neuron models are obtained by applying scale transformation on the parameters and physical variables. The dynamics of the thermosensitive neurons is dependent on the temperature greatly, and synchronization stability between these neurons is investigated by selecting different kinds coupling channels. The reliability of this coupling scheme is mainly controlled by the physical properties of the electronic components in the coupling channels. A capacitor (and induction coil) can be used to connect nonlinear circuits and field coupling is activated to pump field energy for realizing synchronization. This kind of field coupling shows some advantage than the known voltage coupling via resistor connection because of no consumption of Joule heat and the coupling channel is adjustable. The results confirmed that two identical temperature-sensitive neurons can be coupled to reach complete synchronization by regulating the physical parameters in the coupling channel, and energy pumping along the coupling channel is decreased to zero under complete synchronization. For two thermosensitive neurons with parameter mismatch and diversity in temperature, synchronization approach becomes difficult and the energy pumping in the coupling channel is continued under phase lock. Its biophysical significance is that diversity in excitability and difference in channels makes thermosensitive neurons become much different, and the occurrence of bursting synchronization and seizure can be prevented completely. [ABSTRACT FROM AUTHOR]

Spatiotemporal systems can emerge some regular spatial patterns due to self organization or under external periodical pacing while external attack or intrinsic collapse can destroy the regularity in the spatial system. For an example, the electrical activities of neurons in nervous system show regular spatial distribution under appropriate coupling and connection. It is believed that distinct regularity could be induced in the media by appropriate forcing or feedback, while a diffusive collapse induced by continuous destruction can cause breakdown of the media. In this paper, the collapse of ordered spatial distribution is investigated in a regular network of neurons (Morris–Lecar, Hindmarsh–Rose) in two-dimensional array. A stable target wave is developed regular spatial distribution emerges by imposing appropriate external forcing with diversity, or generating heterogeneity (parameter diversity in space). The diffusive invasion could be produced by continuous parameter collapse or switch in local area, e.g, the diffusive poisoning in ion channels of potassium in Morris–Lecar neurons causes breakdown in conductance of channels. It is found that target wave-dominated regularity can be suppressed when the collapsed area is diffused in random. Statistical correlation functions for sampled nodes (neurons) are defined to detect the collapse of ordered state by series analysis. [ABSTRACT FROM AUTHOR]

The dynamics of a memristive system is dependent on the initial values and thus the threshold of coupling intensity for synchronization approach becomes unknown and unpredictable. Joule heat is consumed before reaching complete synchronization when variable coupling is applied for triggering voltage coupling via resistor connection. In this paper, a capacitor is used to couple two memristive circuits and the coupling intensity is increased in exponential way until the two memristive systems reach energy balance adaptively. The regulation of coupling intensity is controlled by using the Heaviside function when the Hamilton energy functions for the memristive systems are available. It is confirmed that two memristive systems can reach complete synchronization, phase lock when the coupling intensity is regulated in an adaptive way. It also explains why energy diversity enables creation of channel connection and coupling between nonlinear circuits, and then the coupling channel is tamed to realize energy balance between memristive systems without confirming exact threshold for coupling intensity. The scheme shows distinct self-adaptive property because the coupling intensity is controlled by the energy flow along the coupling channel. In particular, this kind of field coupling is controllable and external energy injection is helpful to regulate the coupling channel adaptively. [ABSTRACT FROM AUTHOR]

The Hodgkin-Huxley neuron model is used to describe the local dynamics of nodes in a two-dimensional regular network with nearest-neighbor connections. Multi-armed spiral waves emerge when a group of spiral waves rotate the same core synchronously. Here we have numerically investigated how multi-armed spiral waves are formed in such a system. Under the appropriate conditions, multi-armed spiral waves were able to develop as a result of adjusting the conductance of ion channels of particular neurons in the network. In a realistic neuron model, it can be practiced by blocking potassium of ion channels embedded in the membrane of neurons. For example, decreasing the potassium channel conductance in some neurons with a certain transient period can lead to the development of a group of double spirals in a localized area of the network. Furthermore, decreasing the excitability and the external forcing current to zero led to the growth of these double spirals and the formation of a stable multi-armed spiral wave that occupied the network under inhomogeneity. [ABSTRACT FROM AUTHOR]

Background: The CRAFITY score serves as a simple and effective predictive model for individuals diagnosed with hepatocellular carcinoma (HCC) and subjected to treatment with atezolizumab and bevacizumab (Atez/Bev). However, no large sample size studies have reported the application of the CRAFITY score among HCC patients undergoing transarterial chemoembolization (TACE) in conjunction with lenvatinib. This research aims to assess the prognostic role of the CRAFITY score in the context of individuals with HCC receiving TACE in combination with lenvatinib. Methods: This retrospective analysis encompassed 314 individuals diagnosed with HCC who underwent the combination of TACE and lenvatinib at two medical facilities in China from August 2019 to August 2022 (comprising a training cohort of n = 172 and a validation cohort of n = 142). We investigated the prognostic values of overall survival (OS), progression‐free survival (PFS), disease control rate, and objective response rate in the training cohort based on the CRAFITY scores. Furthermore, the predictive capacity of the model was corroborated through validation using an external cohort. Results: We included 174 and 142 patients treated with TACE plus lenvatinib in the training and validation cohorts, correspondingly. PFS and OS differed across all three groups in all training and validation cohorts, based on the CRAFITY score (p < 0.001). In both cohorts, the CRAFITY score effectively predicted tumor response (p < 0.001). Moreover, among the 121 patients who received TACE, lenvatinib, and immunotherapy, the CRAFITY score showed promising predictive efficacy in PFS and OS. Conclusions: The CRAFITY score, utilizing C‐reactive protein and alpha‐fetoprotein values, emerges as a dependable and pragmatic instrument for forecasting the effectiveness of TACE plus lenvatinib in individuals with unresectable HCC. This scoring system holds the potential to assist oncologists in making informed clinical decisions. [ABSTRACT FROM AUTHOR]

Background: Chemotherapy combined with immune checkpoint inhibitors (IC), bevacizumab (BC), or both (IBC) is the preferred first-line therapy for PD-L1-negative and oncogenic-driver wild-type metastatic lung adenocarcinoma. However, the optimal strategy is still undetermined. Methods: This retrospective study enrolled PD-L1-negative metastatic lung adenocarcinoma patients from four cancer centers between January 1, 2018 and June 30, 2022. All the patients received IC, BC, or IBC as the first-line therapies. The efficacy and safety were evaluated. Results: A total of 205 patients were included, with 60, 83, and 62 patients in IC, BC, and IBC groups, respectively. The baseline characteristics among three groups were well balanced. Patients treated with IBC had the highest objective response rate (ORR) (43.5%) and disease control rate (DCR) (100%) relative to those treated with IC (40.4%, 84.2%) or BC (40.5%, 96.2%) (ORR: P = 0.919, DCR: P < 0.01). Compared with the IC (6.74 m) or BC (8.28 m), IBC treatment significantly improved median progression-free survival (mPFS) (9.53 m, P = 0.005). However, no difference in overall survival (OS) was observed. When stratified by different clinical and molecular information, we found that male gender, ever smoking, wild-type genes mutations, and adrenal metastasis predict superior PFS benefit when treated with IBC. In patients with liver metastasis, IBC or BC treatment displayed better PFS compared with IC. No additional adverse reactions were observed in IBC group compared with other two groups. Conclusion: Combined IBC treatment achieved superior DCR and PFS compared with IC or BC in patients with PD-L1-negative metastatic lung adenocarcinoma, while did not increase the adverse events. [ABSTRACT FROM AUTHOR]

Abstract Local periodic stimulus can trigger stable pulse and target wave in the excitable media, the potential mechanism is that each cell is activated by continuous driving to keep pace with the external forcing. Indeed, local diversity in excitability and heterogeneity are induced when external forcing with diversity is applied on the media. When target wave is formed and propagated, the media will be modulated, e.g. it can emit electric signal from sinoatrial node and develops target wave in the cardiac tissue, and then the heartbeat is controlled completely. In fact, the distribution of electromagnetic field in the media is changed when external electric stimulus is applied on the media; therefore, the effect of electromagnetic induction becomes important during the information encoding and signal propagation. In this paper, the Morris–Lecar model is used to describe the local kinetic of the media and an induction current is considered thus the effect of electromagnetic induction can be described. Then the artificial heterogeneity is triggered to investigate the formation and development of target waves in the excitable media with electromagnetic induction and even radiation, which is described by using Gaussian white noise. Diversity in excitability and conductance of ion channels is considered, respectively, thus different kinds of artificial heterogeneity are developed to find the stability of target waves. It is found that the target wave encounters breakup with increasing of the intensity of electromagnetic radiation. Highlights • Biological neuron model is improved to consider the effect of electromagnetic induction. • Heterogeneity formation is explained on conductance and excitability diversity. • Electromagnetic radiation can suppress propagation of target wave. • Breakup of target wave can be induced by electromagnetic radiation. [ABSTRACT FROM AUTHOR]

Based on a class of chaotic system composed of hidden attractors, in which the equilibrium points are described by a circular function, complete synchronization between two identical systems, pattern formation and synchronization of network is investigated, respectively. A statistical factor of synchronization is defined and calculated by using the mean field theory, the dependence of synchronization on bifurcation parameters discussed in numerical way. By setting a chain network, which local kinetic is described by hidden attractors, synchronization approach is investigated. It is found that the synchronization and pattern formation are dependent on the coupling intensity and also the selection of coupling variables. In the end, open problems are proposed for readers' extensive guidance and investigation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Regular spatial patterns could be observed in spatiotemporal systems far from equilibrium states. Artificial networks with different topologies are often designed to reproduce the collective behaviors of nodes (or neurons) which the local kinetics of node is described by kinds of oscillator models. It is believed that the self-organization of network much depends on the bifurcation parameters and topology connection type. Indeed, the boundary effect is every important on the pattern formation of network. In this paper, a regular network of Hindmarsh–Rose neurons is designed in a two-dimensional square array with nearest-neighbor connection type. The neurons on the boundary are excited with random stimulus. It is found that spiral waves, even a pair of spiral waves could be developed in the network under appropriate coupling intensity. Otherwise, the spatial distribution of network shows irregular states. A statistical variable is defined to detect the collective behavior by using mean field theory. It is confirmed that regular pattern could be developed when the synchronization degree is low. The potential mechanism could be that random perturbation on the boundary could induce coherence resonance-like behavior thus spiral wave could be developed in the network. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Phototube can capture and transmit external illumination with high frequency into photocurrent in the nonlinear circuit, which can be tamed to produce the main dynamical properties of biological neurons. In fact, the involvement of functional electronic components can enhance the biophysical function of artificial neural circuits. In this paper, a photocell is connected to FitzHugh-Nagumo neural circuits, which can be excited by the photocurrent generated from the photocell. Furthermore, a memristor is proposed to couple two light-dependent neural circuits and the synchronization stability is investigated on the coupled dynamical systems by using standard scale transformation on the physical variables and parameters. It is found that phase synchronization and complete synchronization can be obtained by regulating the coupling channel connected by the memristor. The propagation and pumping of field energy are also calculated to predict the occurrence of synchronization. [ABSTRACT FROM AUTHOR]

A variety of electric components can be used to bridge connection to the nonlinear circuits, and continuous pumping and consumption of energy are critical for voltage balance between the output end. The realization and stability of synchronization are mainly dependent on the physical properties of coupling channel, which can be built by using different electric components such as resistor, capacitor, induction coil and even memristor. In this paper, a memristive nonlinear circuit developed from Chua circuit is presented for investigation of synchronization, and capacitor, induction coil are jointed with resistor for building artificial synapse which connects one output of two identical memristive circuits. The capacitance and inductance of the coupling channel are carefully adjusted with slight step increase to estimate the threshold of coupling intensity supporting complete synchronization. As a result, the saturation gain method applied to realize the synchronization between chaotic circuits and physical mechanism is presented. [ABSTRACT FROM AUTHOR]

Hydrogen storage capacity on Titanium (Ti) decorated porous graphene (PG) has been investigated using density functional theory simulations with generalized gradient approximation method. The possible adsorption sites of Ti atom on PG and electronic properties of Ti-PG system are also discussed.The results show a Ti atom prefers to strongly adsorb on the center site above the C hexagon with the binding energy of 3.65 eV, and the polarization and the hybridization mechanisms both contribute to the Ti atom adsorption on PG. To avoid a tendency of clustering among Ti atoms, the single side of the PG unit cell should only contain one Ti atom. For the single side of PG, four H 2 molecules can be adsorbed around Ti atom, and the adsorption mechanism of H 2 molecules come from not only the polarization mechanism between Ti and H atoms but also the orbital hybridization among Ti atom, H 2 molecules and C atoms. For the case of double sides of PG, eight H 2 molecules can be adsorbed on Ti-decorated PG unit cell with the average adsorption energy of −0.457 eV, and the gravimetric hydrogen storage capacity is 6.11 wt.%. Furthermore, ab inito molecular-dynaics simulation result shows that six H 2 molecules can be adsorbed on double sides of unit cell of Ti-PG system and the configuration of Ti-PG is very stable at 300 K and without external pressure, which indicates Ti-decorated PG could be considered as a potential hydrogen storage medium at ambient conditions. [ABSTRACT FROM AUTHOR]

In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities. [ABSTRACT FROM AUTHOR]

Based on first-principles method, the electron structure of porous graphene (PG) and adsorption ability of H 2 molecular on Y-decorated porous graphene are investigated using CASTEP code. It is found that the bridge of C–C bond which connects two C hexagons is favorable site for a Y atom adsorbed on the single side of PG, and six H 2 molecules can be absorbed around a Y atom with average adsorption energy of −0.297 eV/H 2 computed by GGA-PBE functional. Though two Y atoms can be stably adsorbed on the same side of one unit cell of PG, there isn’t sufficient space for H 2 absorbing around each Y atom. To improve capability of hydrogen storage, the unit cell of PG with single side should only contain one Y atom. For the case of double side of porous graphene, two Y atoms are preferably located above the center of the different C hexagon. Fourteen H 2 molecules can be absorbed on both sides of PG, and the gravimetric hydrogen storage capacity is 7.87 wt.% with the average adsorption energy of −0.23 eV/H 2 . [ABSTRACT FROM AUTHOR]

The electric activities of neurons can be modulated when autapses are connected to neurons. A forward feedback neuronal network in chain type is designed, which the local kinetics for each node is described by Hindmarsh–Rose neuron, and the autaptic forcing-induced wave propagation along the chain network is investigated. It is found that stable pulse can be induced by the local autaptic forcing in positive feedback type, and the wave begins to disappear when the autaptic modulation stops. It indicates that autapse excitation plays an important role in regulating the collective behaviors of neurons as a pacemaker. The sampled time series for membrane potential of the neuron driven by autapse are detected, and the rhythm predicates whether continuous pulse can be developed or propagated in the chain network. Furthermore, the emitted pulse can be blocked by artificial defects, and thus the wave propagation depends on the property of the network. [ABSTRACT FROM AUTHOR]