Do Planetary Transits Predict Synchronicity Experience?

Synchronicity involves the experience of personal meaning entangled with ambiguous coincidences in time. Ambiguity results from incomplete information about the chances of various events occurring. The problem that this study addresses is the lack of empirical research on synchronicity. This study sought to address this problem by exploring the astrological hypothesis that planetary transits predict synchronicity events. Synchronicities were compared with the probability distributions of planetary transits. In comparison with the base rate prediction, planetary transits were not a significant predictor of synchronicity events. The findings of this study provide new insight into the complex, multifaceted, and ambiguous phenomenon of synchronicity. The concept of ambiguity tolerance plays a significant role in synchronicity research since ambiguity cannot be completely eliminated.

The Usage of “xiaojie (小姐)” in Contem porary Chinese: Synchronic Differences in Distribution and Possibilities for Diachronic Change

xiaojie(小姐， miss) is a popular form of address in contemporary Chinese; generally speaking, it is defined as a title for ―unmarried girl. This form has multiple connotations,. Given recent changes in society, some think that, xiaojie (小姐） will become a widely-used form of address, while others think that young females will come to consider the title repulsive. None can have the final say, this is because the synchronic language differences are not only the result of the synchronic change but also possibly its sign. Since synchronic differences could not only be a result of diachronic change but also could herald further change, it is not clear what direction xiaojie (小姐） will take. In the language conflicts, When two language varieties conflict, the more common variety usually influences the less common. A field investigation in large cities throughout China thus allows us not only to draw A Distributional Map of Pragmatic Features of the Title xiaojie(小姐) ,but also enables us to see its diachronic possibilities.

Fibonacci Harmonics: A New Mathematical Model of Synchronicity

This article aims to provide a brief overview of the relevance of new findings about the Fibonacci Life Chart Method (FLCM) for understanding synchronicity. The FLCM is reviewed first, including an exposition of the golden section model, and elaboration of a new harmonic model. The two models are then compared to illuminate several strengths and weaknesses in connection with the following four major criteria regarding synchronicity: explanatory adequacy;predictability of future synchronicities;simplicity of the model;and generalizability to other branches of knowledge. The review indicates that both models appear capable of simulating nonlinear and fractal dynamics. Hybrid approaches that combine both models are feasible and necessary for projects that aim to experimentally address synchronicity.

Compensation：A Synchronic Dynamic Mechanism in Language

In this paper, compensation mechanism—a synchronic dynamic rule in language is postulated and theorized. The rule raises the acceptability of clauses by effecting the positive side of some variations with exceptional expression and offsetting their negative side. This mechanism is determined by the instrumentality and systematicality of language so that its basic principle should be applicable to all exceptional expressions for particular positive effects and thus universal synchronically.

On the Jefimenko’s Non-Einsteinian Clocks and Synchronicity of Moving Clocks

In this work we analyze the concept of time dilation in its application to the rate of moving clocks. The rates of two equiform elementary electromagnetic clocks of different orientations relative to their direction of motion are computed on the basis of relativistic transformations of force and coordinates for the case when the clocks are at rest in a stationary reference frame and for the case when they are moving at constant speed relative to the stationary reference frame. It is shown that, although both clocks run slower when they are moving than when they are at rest, the rate of the moving clocks is affected by their orientation relative to their direction of motion, rather than by the kinematic (relativistic) time dilation as it is now generally assumed. The implication of this result for the experimental proofs of the existence of the kinematic the dilation is discussed.

The capital market spillover effect of product market advertising:Evidence from stock price synchronicity

We analyze whether product market advertising has a spillover effect on stock price synchronicity by transmitting firm-specific information to the capital market and attracting more investor attention.Using a sample of Chinese listed firms from 2009 to 2017,we find that firms with greater advertising expenditures have lower stock price synchronicity.The results are robust after we address endogeneity concerns.In accord with our hypothesis that product market advertising increases the amount of firm-level information capitalized into stock prices through the information channel,we find that the impact of advertising on synchronicity is more pronounced for firms with a higher degree of information asymmetry and firms in the consumer-product industry.Further tests show that product market advertising enhances the ability of current period returns to reflect future earnings,and thus rules out that the negative relationship between advertising and synchronicity is driven by noise trading.Our results imply that product market advertising plays an informative role and improves information efficiency in a capital market.

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each other.The memory characteristic of memristors makes them suitable for simulating neuronal synapses with plasticity.In this paper,a memristor is used to simulate a synapse,a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is explored.We explore the influence of system parameters on the dynamical behaviors of the discrete small-world network,and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameterαis changed.The results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network,and the higher the reconnection probability and number of the nearest neurons,the more significant the synchronization state of the neurons.In addition,by increasing the coupling strength of memristor synapses,synchronization performance is promoted.The results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

Chimera states of phase oscillator populations with nonlocal higher-order couplings

The chimera states underlying many realistic dynamical processes have attracted ample attention in the area of dynamical systems.Here, we generalize the Kuramoto model with nonlocal coupling incorporating higher-order interactions encoded with simplicial complexes.Previous works have shown that higher-order interactions promote coherent states.However, we uncover the fact that the introduced higher-order couplings can significantly enhance the emergence of the incoherent state.Remarkably, we identify that the chimera states arise as a result of multi-attractors in dynamic states.Importantly, we review that the increasing higher-order interactions can significantly shape the emergent probability of chimera states.All the observed results can be well described in terms of the dimension reduction method.This study is a step forward in highlighting the importance of nonlocal higher-order couplings, which might provide control strategies for the occurrence of spatial-temporal patterns in networked systems.

Dynamics and synchronization in a memristor-coupled discrete heterogeneous neuron network considering noise

Research on discrete memristor-based neural networks has received much attention.However,current research mainly focuses on memristor–based discrete homogeneous neuron networks,while memristor-coupled discrete heterogeneous neuron networks are rarely reported.In this study,a new four-stable discrete locally active memristor is proposed and its nonvolatile and locally active properties are verified by its power-off plot and DC V–I diagram.Based on two-dimensional(2D)discrete Izhikevich neuron and 2D discrete Chialvo neuron,a heterogeneous discrete neuron network is constructed by using the proposed discrete memristor as a coupling synapse connecting the two heterogeneous neurons.Considering the coupling strength as the control parameter,chaotic firing,periodic firing,and hyperchaotic firing patterns are revealed.In particular,multiple coexisting firing patterns are observed,which are induced by different initial values of the memristor.Phase synchronization between the two heterogeneous neurons is discussed and it is found that they can achieve perfect synchronous at large coupling strength.Furthermore,the effect of Gaussian white noise on synchronization behaviors is also explored.We demonstrate that the presence of noise not only leads to the transition of firing patterns,but also achieves the phase synchronization between two heterogeneous neurons under low coupling strength.

Quantum synchronization with correlated baths

We study quantum synchronization under the nonequilibrium reservoirs.We consider a two-qubit XXZ chain coupled independently to their own reservoirs modeled by the collisional model.Two reservoir particles,initially prepared in a thermal state or a state with coherence,are correlated through a unitary transformation and afterward interact locally with the two quantum subsystems.We study the quantum effect of reservoir on synchronous dynamics of system.By preparing different reservoir initial states or manipulating the reservoir particles coupling and the temperature gradient,we find that quantum entanglement of reservoir is the key to control quantum synchronization of system qubits.

Dynamical behavior of memristor-coupled heterogeneous discrete neural networks with synaptic crosstalk

Synaptic crosstalk is a prevalent phenomenon among neuronal synapses,playing a crucial role in the transmission of neural signals.Therefore,considering synaptic crosstalk behavior and investigating the dynamical behavior of discrete neural networks are highly necessary.In this paper,we propose a heterogeneous discrete neural network(HDNN)consisting of a three-dimensional KTz discrete neuron and a Chialvo discrete neuron.These two neurons are coupled mutually by two discrete memristors and the synaptic crosstalk is considered.The impact of crosstalk strength on the firing behavior of the HDNN is explored through bifurcation diagrams and Lyapunov exponents.It is observed that the HDNN exhibits different coexisting attractors under varying crosstalk strengths.Furthermore,the influence of different crosstalk strengths on the synchronized firing of the HDNN is investigated,revealing a gradual attainment of phase synchronization between the two discrete neurons as the crosstalk strength decreases.

A step to the decentralized real-time timekeeping network

The composite time scale(CTS) provides an accurate and stable time-frequency reference for modern science and technology. Conventional CTS always features a centralized network topology, which means that the CTS is accompanied by a local master clock. This largely restricts the stability and reliability of the CTS. We simulate the restriction and analyze the influence of the master clock on the CTS. It proves that the CTS's long-term stability is also positively related to that of the master clock, until the region dominated by the frequency drift of the H-maser(averaging time longer than ~10~5s).Aiming at this restriction, a real-time clock network is utilized. Based on the network, a real-time CTS referenced by a stable remote master clock is achieved. The experiment comparing two real-time CTSs referenced by a local and a remote master clock respectively reveals that under open-loop steering, the stability of the CTS is improved by referencing to a remote and more stable master clock instead of a local and less stable master clock. In this way, with the help of the proposed scheme, the CTS can be referenced to the most stable master clock within the network in real time, no matter whether it is local or remote, making democratic polycentric timekeeping possible.

On the functions of astrocyte-mediated neuronal slow inward currents

Slow inward currents are known as neuronal excitatory currents mediated by glutamate release and activation of neuronal extra synaptic N-met hyl-D-aspartate receptors with the contribution of astrocytes.These events are significantly slower than the excitatory postsynaptic currents.Parameters of slow inward currents are determined by seve ral factors including the mechanisms of astrocytic activation and glutamate release,as well as the diffusion pathways from the release site towards the extra synaptic recepto rs.Astrocytes are stimulated by neuronal network activity,which in turn excite neurons,forming an astrocyte-neuron feedback loop.Mostly as a consequence of brain edema,astrocytic swelling can also induce slow inward currents under pathological conditions.There is a growing body of evidence on the roles of slow inward currents on a single neuron or local network level.These events often occur in synchro ny on neurons located in the same astrocytic domain.Besides synchronization of neuronal excitability,slow inward currents also set synaptic strength via eliciting timing-dependent synaptic plasticity.In addition,slow inward currents are also subject to non-synaptic plasticity triggered by long-la sting stimulation of the excitatory inputs.Of note,there might be important regionspecific differences in the roles and actions triggering slow inward currents.In greater networks,the pathophysiological roles of slow inward currents can be better understood than physiological ones.Slow inward currents are identified in the pathophysiological background of autism,as slow inward currents drive early hypersynchrony of the neural networks.Slow inward currents are significant contributors to paroxysmal depolarizational shifts/interictal spikes.These events are related to epilepsy,but also found in Alzheimer's disease,Parkinson's disease,and stroke,leading to the decline of cognitive functions.Events with features overlapping with slow inward currents(excitatory,N-methyl-Daspartate-receptor mediated currents with astrocytic contribution) as ischemic currents and spreading depolarization also have a well-known pathophysiological role in worsening consequences of stroke,traumatic brain injury,or epilepsy.One might assume that slow inward currents occurring with low frequency under physiological conditions might contribute to synaptic plasticity and memory formation.However,to state this,more experimental evidence from greater neuronal networks or the level of the individual is needed.In this review,I aimed to summarize findings on slow inward currents and to speculate on the potential functions of it.

A Synchronization Acquisition Algorithm Based on the Frequency Hopping Pulses Combining

As modern electromagnetic environments are more and more complex,the anti-interference performance of the synchronization acquisition is becoming vital in wireless communications.With the rapid development of the digital signal processing technologies,some synchronization acquisition algorithms for hybrid direct-sequence(DS)/frequency hopping(FH)spread spectrum communications have been proposed.However,these algorithms do not focus on the analysis and the design of the synchronization acquisition under typical interferences.In this paper,a synchronization acquisition algorithm based on the frequency hopping pulses combining(FHPC)is proposed.Specifically,the proposed algorithm is composed of two modules:an adaptive interference suppression(IS)module and an adaptive combining decision module.The adaptive IS module mitigates the effect of the interfered samples in the time-domain or the frequencydomain,and the adaptive combining decision module can utilize each frequency hopping pulse to construct an anti-interference decision metric and generate an adaptive acquisition decision threshold to complete the acquisition.Theory and simulation demonstrate that the proposed algorithm significantly enhances the antiinterference and anti-noise performances of the synchronization acquisition for hybrid DS/FH communications.

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.

Improved Particle Swarm Optimization for Parameter Identification of Permanent Magnet Synchronous Motor

In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness.

Localization method of subsynchronous oscillation source based on high-resolution time-frequency distribution image and CNN

The penetration of new energy sources such as wind power is increasing,which consequently increases the occurrence rate of subsynchronous oscillation events.However,existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features,such as frequency drift,caused by the random volatility of wind farms when oscillations occur.This paper proposes a subsynchronous oscillation sourcelocalization method that involves an enhanced short-time Fourier transform and a convolutional neural network(CNN).First,an enhanced STFT is performed to secure high-resolution time-frequency distribution(TFD)images from the measured data of the generation unit ports.Next,these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model.Ultimately,the trained CNN model realizes the online localization of subsynchronous oscillation sources.The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform.Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms,thus providing a foundation for oscillation suppression in practical engineering scenarios.

Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor(PMSM)speed control systems with conventional linear active disturbance rejection control(CLADRC)strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances.In order to address these issues,this paper proposes an improved two-degree-of-freedom LADRC(TDOF-LADRC)strategy,which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning.PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately.Moreover,to evaluate the control performance of the TDOF-LADRC strategy,its stability is proven,and the influence of each controller parameter on the system control performance is analyzed.Based on it,a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances.Finally,experiments are performed on a 750 W PMSM experimental platform,and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

Harmonics in the Squirrel Cage Induction Motor Analytic Calculation Part III: Influence on the Torque-speed Characteristic

The harmonics that appear in the squirrel cage asynchronous machine have been discussed in great detail in the literature for a long time. However, the systematization of the phenomenon is still pending, so we made an attempt to fill this gap in the previous parts of our study by elaborating formulas for calculation of parasitic torques. It was a general demand among those who work in this field towards the author to verify his formulas with measurements. In the literature, it seems,only one detailed, purposeful series of measurements has been published so far, the purpose of which was to investigate the effect of the number of rotor slots on the torque-speed characteristic curve of the machine. The main goal of this study is to verify the correctness of the formulas by comparing them with the referred series of measurements. Relying on this, the expected synchronous parasitic torques were developed for the frequently used rotor slot numbers-as a design guide for the engineer.Thus, together with our complete table for radial magnetic pull published in our previous work, the designer has all the principles, data and formulas available for the right number of rotor slots for his given machine and for the drive system. This brings this series of papers to an end.

Synchronous gastric and colon cancers:Important to consider hereditary syndromes and chronic inflammatory disease associations

In this editorial we comment on the manuscript,describing management and surveillance strategies in synchronous and metachronous,gastric and colon cancers.Synchronous or metachronous primary malignancies at different sites of the gastrointestinal tract pose a unique diagnostic and therapeutic challenge.Multidisciplinary services and strategies are required for the management of multiple site primary malignancies,to provide the best oncological outcomes.Although this study highlights the dual cancers in 76 sporadic cases,the authors excluded 55 patients due to combination of factors which includes;incomplete clinical data,genetic syndrome,gastric stump cancers.In addition,the authors did not elaborate if any patients presented with signet ring cell morphology,E-cadherin mutations or presence of inflammatory bowel disease.Genetic and mutational errors and epithelial field defects from chronic inflammatory diseases of the gastrointestinal tract are important when considering synchronous gastric and colonic cancers.We will briefly discuss these in this editorial.