Mutual Triggering Research Articles

The Temporal Relationship between Depressive Symptoms and Loneliness: The Moderating Role of Self-Compassion.

Loneliness and depression are significant mental health challenges among college students; however, the intricate relationship between these phenomena remains unclear, particularly in the context of self-compassion. In this comprehensive study, we employ a cross-lagged panel network (CLPN) analysis to investigate the symptom-level association between depression and loneliness while exploring the potential moderating influence of self-compassion. Our sample consisted of 2785 college students, who were categorized into high- and low-self-compassion groups based on scores from the Self-Compassion Scale. Depressive symptoms were assessed using the Patient Health Questionnaire-9, while the UCLA Loneliness Scale-8 measured loneliness expressions. Our findings indicate that self-compassion plays a crucial role in the relationship between depression and loneliness. Specifically, we observed distinctive patterns within the high and low-self-compassion groups. In the low-self-compassion group, "energy" emerged as the most influential symptom, whereas "motor function" exhibited the highest influence in the high-self-compassion group. Furthermore, among individuals with high self-compassion, the pathway from depression to loneliness was characterized by "guilt-being alone when desired," while the reverse path from loneliness to depression encompassed "left out-feeling sad" and "left out-anhedonia." Conversely, in the low-self-compassion group, depression and loneliness demonstrated a more intricate mutual triggering relationship, suggesting that self-compassion effectively moderates the association between these variables. This study provides valuable insights into the underlying mechanisms driving the interplay between depression and loneliness, shedding light on the pivotal role of self-compassion in this intricate dynamic.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Comorbidities: Linked by Vascular Pathomechanisms and Vasoactive Mediators?

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is often associated with various other syndromes or conditions including mast cell activation (MCA), dysmenorrhea and endometriosis, postural tachycardia (POTS) and small fiber neuropathy (SFN). The causes of these syndromes and the reason for their frequent association are not yet fully understood. We previously published a comprehensive hypothesis of the ME/CFS pathophysiology that explains the majority of symptoms, findings and chronicity of the disease. We wondered whether some of the identified key pathomechanisms in ME/CFS are also operative in MCA, endometriosis and dysmenorrhea, POTS, decreased cerebral blood flow and SFN, and possibly may provide clues on their causes and frequent co-occurrence. Our analysis indeed provides strong arguments in favor of this assumption, and we conclude that the main pathomechanisms responsible for this association are excessive generation and spillover into the systemic circulation of inflammatory and vasoactive tissue mediators, dysfunctional β2AdR, and the mutual triggering of symptomatology and disease initiation. Overall, vascular dysfunction appears to be a strong common denominator in these linkages.

Tri‐transformer Hawkes process via dot‐product attention operations with event type and temporal encoding

AbstractAsynchronous event sequences widely exist in the real world, such as social networks, electronic medical records, financial data, and genome analysis. For modeling asynchronous event sequences in the continuous time domain, point process has become the underpinning. In the initial research stage, Hawkes process is widely used because it can capture the self‐triggering and mutual triggering modes between different events in a variety of point process functions. In recent years, due to the development of neural networks, deep point process (also known as neural point process) can learn models with the stronger fitting ability and reduce the dependence on prior knowledge by using the powerful capacity of neural networks. The proposal of the transformer Hawkes process (THP) has led to a huge performance improvement, so a new climax of the transformer‐based deep Hawkes process is set off. However, THP does not make full use of the event and temporal information underlying the asynchronous event sequence, meanwhile, if we simply take the event type encoding and temporal encoding as the sequence encoding, a single transformer may suffer from learning bias. In order to circumvent these problems, we propose a tri‐transformer Hawkes process model (TTHP), in which the event and temporal information are introduced to the dot‐product attention operations as auxiliary information to form different multihead attention, respectively, and are utilized to build three heterogeneous learners. A series of well‐designed experiments on synthetic and real‐world datasets validate the effectiveness of the proposed TTHP.

BatRack: An open‐source multi‐sensor device for wildlife research

Abstract Bats represent a highly diverse group of mammals and are essential for ecosystem functioning. However, knowledge about their behaviour, ecology and conservation status is limited. Direct observation of marked individuals (commonly applied to birds) is not possible for bats due to their small size, rapid movement and nocturnal lifestyle, while neither popular observation methods such as camera traps nor conventional tracking technologies sufficiently capture the behaviour of individuals. The combination and networking of different sensors in a single system can overcome these limitations, but this potential has been explored only to a limited extent. We present BatRack, a multi‐sensor device that combines ultrasonic audio recordings, automatic radio telemetry and video camera recordings in a single modular unit. BatRack facilitates the individual or combined scheduling of sensors and includes a mutual triggering mode. It consists of off‐the‐shelf hardware and both its hardware blueprints and the required software have been published under an open license to allow scientists and practitioners to replicate the system. We tested the suitability of radio telemetry and audio sensors as camera triggers and evaluated the detection of individuals in video recordings compared to radio telemetry signals. Specifically, BatRack was used to monitor the individual swarming behaviour of six members of a maternity colony of Bechstein's bat. Preliminary anecdotal results indicate that swarming intensity is related to reproductive state and roost switching. BatRack allows researchers to recognize individual bats and monitor their behavioural patterns using an easily deployed and scalable system. BatRack is thus a promising approach to obtaining detailed insights into the behavioural ecology of bats.

A Stochastic Model of Cascading Failure Dynamics in Cyber-Physical Power Systems

Uncertain events such as renewable generation and load fluctuation will introduce uncertainties into the grid that might severely affect the system's robustness against cascading failure. A stochastic model for studying the cascading failure dynamics of cyber-physical power systems is proposed, the aim being to examine the impacts of uncertainties on the system's vulnerability to cascading failure. This model retains the structural and operating characteristics of cyber-physical power systems. Topological failure and communication operational failure described by data traffic model are considered as being deterministic, whereas grid operational failure described by probabilistic load flow model is considered as being stochastic. Stochastic methods are used to select the failure-prone components and to determine the time of failure of each selected component. Moreover, the effects of load uncertainty and heavy load demands on the system's vulnerability to cascading failure are studied. Simulation results indicate that the failure propagation of a cyber-physical power system is the result of repeated mutual triggering between the power network and the coupled communication network. In addition, the increased load uncertainty can cause cascading failure, and the higher the load uncertainty the more severe the blackouts. Moreover, higher load demand makes the coupled system more vulnerable to cascading failure.

Variable spatio-temporal clustering of microseismicity in the Hellenic Subduction Zone as possible indicator for fluid migration

This study investigates the variability of spatio-temporal microseismicity clustering and the occurrence of mutual triggering of events along the subduction interface in south-eastern Aegean as indication for fluid flow along and above the plate interface. We quantify spatial, temporal and spatio-temporal microseismicity clustering from the outer to the inner forearc and at intermediate depths. Waveform similarity indicates a decreasing of spatially clustered events from the outer and central towards the inner forearc and at intermediate depths. Highly similar events (cross-correlation >0.9), used as proxy for spatial clustering, decrease from the outer (30.2%) and central forearc (34.9%), towards the inner forearc (20.5%) and at intermediate depth (6.9%). Such highly similar events show increasing median inter-event times from the outer and central towards the inner forearc and at intermediate depth: 0.35, 0.34, 16.45, and 70 days, respectively. The Epidemic-Type-Aftershock-Sequences (ETAS) model, employed to investigate microseismicity temporal clustering, indicates an increase of the percentage of independent events from the outer (32%) and central (46%) forearc, to the inner forearc (93%) and at intermediate depth (93%). Hence, ETAS results suggest that mutual triggering of events is significant in the outer and central forearc, and it is almost absent in the inner forearc and at intermediate depths. Autocorrelation analysis, investigating spatio-temporal clustering, shows the tendency of earthquakes to occur close in space and time in the outer and central forearc, while in the inner forearc, and especially at intermediate depth, earthquakes are more homogeneously and randomly distributed. Combining the results from spatial, temporal and spatio-temporal analysis, we suggest that the different spatio-temporal patterns hint at systematic variations in the presence of migrating fluids on active faults close to failure. Triggering of seismicity is significant in the outer and central forearc, indicating fluid flow from the subduction interface, and it is diminishing towards the inner forearc. At intermediate depths, the nearly complete absence of mutual triggering of earthquakes indicates that there is little evidence for migration of fluids on active faults close to failure. Because intermediate depth seismicity in the Hellenic subduction zone occurs at P-T conditions where dehydration reactions are expected, fluids released by dehydration reactions within the slab are very likely migrating directly into the overlying mantle without triggering earthquakes.

Do Financial Companies Communicate to One Another in the News? (Application of Multivariate Hawkes Graphs to Uncover Granger Causality of Financial News)

A considerable amount of current research in financial business addresses the influence of news and social media on stock returns and volatility. Although news data are used in many applications, the mutual relationship among public announcements remains unclear. Moreover, the majority of studies are conducted using aggregated data, which are less effective in detecting causal links than observations of higher frequency. This paper provides evidence of self and mutual triggering of news announcements in the financial sector. It is proposed that the news arrival times be modelled as a multivariate Hawkes process to test the Granger causality of company-specific news and to detect the most influential companies. Based on this information, a novel method of constructing a composite news intensity index (NII) is presented. The NII demonstrates the ability to timeously describe the uncertainty in financial markets. The proposed measure Granger causes VIX at 6-month lag and can therefore be used to diagnose the health of a financial system.

Generating functions and stability study of multivariate self-excited epidemic processes

We present a stability study of the class of multivariate self-excited Hawkes point processes, that can model natural and social systems, including earthquakes, epileptic seizures and the dynamics of neuron assemblies, bursts of exchanges in social communities, interactions between Internet bloggers, bank network fragility and cascading of failures, national sovereign default contagion, and so on. We present the general theory of multivariate generating functions to derive the number of events over all generations of various types that are triggered by a mother event of a given type. We obtain the stability domains of various systems, as a function of the topological structure of the mutual excitations across different event types. We find that mutual triggering tends to provide a significant extension of the stability (or subcritical) domain compared with the case where event types are decoupled, that is, when an event of a given type can only trigger events of the same type.

Compile-time and runtime analysis of active behaviors

Active rules may interact in complex and sometimes unpredictable ways, thus possibly yielding infinite rule executions by triggering each other indefinitely. This paper presents analysis techniques focused on detecting termination of rule execution. We describe an approach which combines static analysis of a rule set at compile-time and detection of endless loops during rule processing at runtime. The compile-time analysis technique is based on the distinction between mutual triggering and mutual activation of rules. This distinction motivates the introduction of two graphs defining rule interaction, called Triggering and Activation Graphs, respectively. This analysis technique allows us to identify reactive behaviors which are guaranteed to terminate and reactive behaviors which may lead to infinite rule processing. When termination cannot be guaranteed at compile-time, it is crucial to detect infinite rule executions at runtime. We propose a technique for identifying loops which is based on recognizing that a given situation has already occurred in the past and, therefore, will occur an infinite number of times in the future. This technique is potentially very expensive, therefore, we explain how it can be implemented in practice with limited computational effort. A particular use of this technique allows us to develop cycle monitors, which check that critical rule sequences, detected at compile time, do not repeat forever We bridge compile-time analysis to runtime monitoring by showing techniques, based on the result of rule analysis, for the identification of rule sets that can be independently monitored and for the optimal selection of cycle monitors.

Temporal precision in circadian systems: a reliable neuronal clock from unreliable components?

Mutual coupling among oscillators of an ensemble has been proposed to explain the precision of some circadian rhythms. Reciprocal triggering is one of the most familiar forms of mutual coupling in nervous systems, but it can at best produce only modest improvement in temporal precision. Nevertheless, models with an elementary elaboration of such coupling show that circadian precision could be derived from oscillators that are intrinsically "sloppy"; sufficient conditions are that output of the individual components be summed and that mutual triggering be mediated by a nonlinear phenomenon, such as a threshold.

Systems of mutually-triggering event generators: Basic properties and functions in information transmission and rhythm generation

1. Linkages of multiple distinct event generators, coupled so that the firing of any one triggers the remainder, are found in many biological settings. This paper analyzes such networks under the assumption that individual event generators emit discrete events of a fixed type in a more-orless random time series. The aspects of their behavior studied herein include the frequency of network event emissions, their regularity, and their sensitivity to stimuli impinging equally on all generators. This analysis includes rhythm-generating and information-encoding functions within its purview. 2. Under specified conditions on the “ageing” properties of interevent intervals characterizing individual generators, the output frequency of such networks depends weakly on the number of more-or-less similar generators in the network. This phenomenon, termedpseudosaturation, would promote robustness of function in the face of injury or elaborational error, and is enhanced when all generators exhibit a substantial sure silent period following event emission. 3. Given certain assumptions about the manner of encoding and decoding of a single stimulus parameter, networks whose function is to encode information improve their overall signal-to-noise ratios with increasing numbers of generators. Where the properties of the generators permit pseudosaturation in output rate, this improvement comes about at a low expense of dynamic range, so that in addition to redundancy, this type of linkage offers a potentially adaptive means of channel compression. 4. The dependence of generator output on an encoded stimulus parameter may be severely distorted under mutually-triggering linkage. Conditions guaranteeing the absence of various degrees of distortion are given, and the possible selective advantage of serious distortion in respect of reducing sensitivity to extraneous influences is discussed. 5. The mutually-triggering feature in networks functioning to produce rhythmic behavior does not necessarily enhance the regularity of a rhythm, the presence of enhancement depending both upon the detailed statistical characteristics of the constituent generators, and upon the statistic used to assess “regularity”. Larger networks generally display less variation in longterm output frequency, but their instantaneous frequencies seem to be more constant only when individual generators tend to emit a substantial number of atypically long intervals, and/or exhibit sizeable post-event silent periods. 6. Various of the ideas developed are applied to two systems which have been studied experimentally. Mutual triggering between different spikeinitiating zones in the lateral-line afferents ofXenopus laevis can not at present be shown to improve signal-to-noise ratio, sensitivity, or robustness — its function remains unknown. The published statistical properties of isolated marginal-ganglion oscillators in scyphomedusae would permit, in the absence of influences other than mutual triggering, both increases in robustness and in rhythm regularity. Experiments are suggested to determine the nature of additional influences known to exist.