Coherent Event Research Articles

Event Stream Denoising Method Based on Spatio-Temporal Density and Time Sequence Analysis.

An event camera is a neuromimetic sensor inspired by the human retinal imaging principle, which has the advantages of high dynamic range, high temporal resolution, and low power consumption. Due to the interference of hardware and software and other factors, the event stream output from the event camera usually contains a large amount of noise, and traditional denoising algorithms cannot be applied to the event stream. To better deal with different kinds of noise and enhance the robustness of the denoising algorithm, based on the spatio-temporal distribution characteristics of effective events and noise, an event stream noise reduction and visualization algorithm is proposed. The event stream enters fine filtering after filtering the BA noise based on spatio-temporal density. The fine filtering performs time sequence analysis on the event pixels and the neighboring pixels to filter out hot noise. The proposed visualization algorithm adaptively overlaps the events of the previous frame according to the event density difference to obtain clear and coherent event frames. We conducted denoising and visualization experiments on real scenes and public datasets, respectively, and the experiments show that our algorithm is effective in filtering noise and obtaining clear and coherent event frames under different event stream densities and noise backgrounds.

Transient susceptibility to interference at event boundaries impacts long-term memory of naturalistic episodes

ABSTRACT During ongoing narratives, event boundaries trigger processes relevant for subsequent memory. Previous work has shown that novel, unrelated input presented at an event boundary can retroactively interfere with short-term retention of the preceding event. This interference was attributed to a perturbation of offset-related processes taking place within seconds after encoding and supporting the binding of elements into a coherent event memory. However, the temporal specificity of this memory interference and whether its impact extends to longer retention delays has not been addressed. Here, participants viewed either individual or pairs of short narrative movie clips. Susceptibility to interference at event boundaries was probed by presenting the second clip either immediately after the first, or with a 2s encoding delay. In free and cued recall, after 20 min and 24 h, only memory for movie clips that were immediately followed by a second clip was reduced compared to clips shown in isolation. Intact offset-related processes (as indexed by successful recall of the first movie) did not negatively affect encoding of the subsequent clip. Together, these results indicate that the 2s time-window immediately after an event is relevant for successful consolidation and long-term retention of memory.

Peering into the future: Eye movements predict neural repetition effects during episodic simulation

Imagining future scenarios involves recombining different elements of past experiences into a coherent event, a process broadly supported by the brain's default network. Prior work suggests that distinct brain regions may contribute to the inclusion of different simulation features. Here we examine how activity in these brain regions relates to the vividness of future simulations. Thirty-four healthy young adults imagined future events involving familiar people and locations in a two-part study involving a repetition suppression paradigm. First, participants imagined events while their eyes were tracked during a behavioral session. Immediately after, participants imagined events during MRI scanning. The events to be imagined were manipulated such that some were identical to those imagined in the behavioral session while others involved new locations, new people, or both. In this way, we could examine how self-report ratings and eye movements predict brain activity during simulation along with specific simulation features. Vividness ratings were negatively correlated with eye movements, in contrast to an often-observed positive relationship with past recollection. Moreover, fewer eye movements predicted greater involvement of the hippocampus during simulation, an effect specific to location features. Our findings suggest that eye movements may facilitate scene construction for future thinking, lending support to frameworks that spatial information forms the foundation of episodic simulation.

Infants infer and predict coherent event interactions: Modeling cognitive development.

Mental representations of the environment in infants are sparse and grow richer during their development. Anticipatory eye fixation studies show that infants aged around 7 months start to predict the goal of an observed action, e.g., an object targeted by a reaching hand. Interestingly, goal-predictive gaze shifts occur at an earlier age when the hand subsequently manipulates an object and later when an action is performed by an inanimate actor, e.g., a mechanical claw. We introduce CAPRI2 (Cognitive Action PRediction and Inference in Infants), a computational model that explains this development from a functional, algorithmic perspective. It is based on the theory that infants learn object files and events as they develop a physical reasoning system. In particular, CAPRI2 learns a generative event-predictive model, which it uses to both interpret sensory information and infer goal-directed behavior. When observing object interactions, CAPRI2 (i) interprets the unfolding interactions in terms of event-segmented dynamics, (ii) maximizes the coherence of its event interpretations, updating its internal estimates and (iii) chooses gaze behavior to minimize expected uncertainty. As a result, CAPRI2 mimics the developmental pathway of infants' goal-predictive gaze behavior. Our modeling work suggests that the involved event-predictive representations, longer-term generative model learning, and shorter-term retrospective and active inference principles constitute fundamental building blocks for the effective development of goal-predictive capacities.

Monitoring seismicity in the southern Sichuan Basin using a machine learning workflow

Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses. In this study, we propose an automatic workflow based on machine learning (ML) to monitor seismicity in the southern Sichuan Basin of China. This workflow includes coherent event detection, phase picking, and earthquake location using three-component data from a seismic network. By combining PhaseNet, we develop an ML-based earthquake location model called PhaseLoc, to conduct real-time monitoring of the local seismicity. The approach allows us to use synthetic samples covering the entire study area to train PhaseLoc, addressing the problems of insufficient data samples, imbalanced data distribution, and unreliable labels when training with observed data. We apply the trained model to observed data recorded in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average differences in latitude, longitude, and depth are 5.7 ​km, 6.1 ​km, and 2 ​km, respectively, compared to the reference catalog. PhaseLoc combines all available phase information to make fast and reliable predictions, even if only a few phases are detected and picked. The proposed workflow may help real-time seismic monitoring in other regions as well.

EFT analysis of New Physics at COHERENT

Using an effective field theory approach, we study coherent neutrino scattering on nuclei, in the setup pertinent to the COHERENT experiment. We include non-standard effects both in neutrino production and detection, with an arbitrary flavor structure, with all leading Wilson coefficients simultaneously present, and without assuming factorization in flux times cross section. A concise description of the COHERENT event rate is obtained by introducing three generalized weak charges, which can be associated (in a certain sense) to the production and scattering of νe, νμ and {overline{nu}}_{mu } on the nuclear target. Our results are presented in a convenient form that can be trivially applied to specific New Physics scenarios. In particular, we find that existing COHERENT measurements provide percent level constraints on two combinations of Wilson coefficients. These constraints have a visible impact on the global SMEFT fit, even in the constrained flavor-blind setup. The improvement, which affects certain 4-fermion LLQQ operators, is significantly more important in a flavor-general SMEFT. Our work shows that COHERENT data should be included in electroweak precision studies from now on.

Out of many modes and motivations

This article explores a sequence of events, a combination of Orthodox Christian village and chapel festivals, associated processions and a cross-border procession, through the theoretical concept of ritualisation. The sequence of events takes place annually in the Finnish villages of Saarivaara and Hoilola, the Pörtsämö wilderness cemetery and the former Finnish municipality of Korpiselkä, located today in Russia; it attracts participants with religious and other motives, including nostalgia and family history. An analysis is made of how different and sometimes contradictory modes of action are structured and intertwined to form a coherent ritual event. On the basis of original anthropological research undertaken near and over the border between Finland and Russia, in Karelia, it emerges that the ritual mastery by Orthodox priests and shared goals and motives of heritage and culture give the journey a necessary structure, which can be studied and explained in terms of ritualisation.

Exploring the impacts of implicit context association and arithmetic booster in impulsivity reduction.

People have a higher preference for immediate over delayed rewards, and it is suggested that such an impulsive tendency is governed by one’s ability to simulate future rewards. Consistent with this view, recent studies have shown that enforcing individuals to focus on episodic future thoughts reduces their impulsivity. Inspired by these reports, we hypothesized that administration of a simple cognitive task linked to future thinking might effectively modulate individuals’ delay discounting. Specifically, we used one associative memory task targeting intervention of context information, and one working memory task targeting enhancement of individual’s ability to construct a coherent future event. To measure whether each type of cognitive task reduces individuals’ impulsivity, a classic intertemporal choice task was used to quantify individuals’ baseline and post-intervention impulsivity. Across two experiments and data from 216 healthy young adult participants, we observed that the impacts of intervention tasks were inconsistent. Still, we observed a significant task repetition effect such that the participants showed more patient choices in the second impulsivity assessment. In conclusion, there was no clear evidence supporting that our suggested intervention tasks reduce individuals’ impulsivity, and that the current results call attention to the importance of taking into account task repetition effects in studying the impacts of cognitive training and intervention.

Diffraction separation using structure-oriented orthogonal polynomial transform

Diffractions possess the potential to reveal subsurface discontinuities, such as faults, collapsed columns, and the rough edges of the salt body. We have developed a novel diffraction separation method that first flattens the dominant reflections and then identifies the diffraction wavefields through an orthogonal polynomial transform (OPT). Based on the plane-wave assumption and local slope, the reflection events can be predicted and flattened using plane-wave differential equations. To enhance the stability of the flattening process, a sliding window algorithm and three finite-difference forms are adopted. As the dominant coherent event, a reflection often corresponds to low-order coefficients in the OPT. To better preserve the diffraction energy, a time-varying order threshold is used when removing the dominant reflections. Two field data applications are presented to demonstrate the feasibility and effectiveness of the proposed diffraction separation strategy.

Midpoints, endpoints and the cognitive structure of events

ABSTRACT Events unfold over time, i.e. they have a beginning and endpoint. Previous studies have illustrated the importance of endpoints for event perception and memory. However, this work has only discussed events with a self-evident endpoint, and the internal temporal structure of events has not received much attention. In this study, we hypothesise that event cognition computes boundedness, an abstract feature of the internal temporal structure of events. We further hypothesise that sensitivity to boundedness affects how individual temporal slices of events (such as event midpoints or endpoints) are processed and integrated into a coherent event representation. The results of three experiments confirm these hypotheses. In Experiment 1, viewers identified the class of bounded (non-homogeneous, culminating) and unbounded (homogeneous, non-culminating) events in a categorisation task. In Experiments 2 and 3, viewers reacted differently to temporal disruptions in bounded versus unbounded events. We conclude that boundedness shapes how events are temporally processed.

Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs. weather-generator-based approach

Abstract. Flood risk assessment is an important prerequisite for risk management decisions. To estimate the risk, i.e. the probability of damage, flood damage needs to be either systematically recorded over a long period or modelled for a series of synthetically generated flood events. Since damage records are typically rare, time series of plausible, spatially coherent event precipitation or peak discharges need to be generated to drive the chain of process models. In the present study, synthetic flood events are generated by two different approaches to modelling flood risk in a meso-scale alpine study area (Vorarlberg, Austria). The first approach is based on the semi-conditional multi-variate dependence model applied to discharge series. The second approach relies on the continuous hydrological modelling of synthetic meteorological fields generated by a multi-site weather generator and using an hourly disaggregation scheme. The results of the two approaches are compared in terms of simulated spatial patterns of peak discharges and overall flood risk estimates. It could be demonstrated that both methods are valid approaches for risk assessment with specific advantages and disadvantages. Both methods are superior to the traditional assumption of a uniform return period, where risk is computed by assuming a homogeneous return period (e.g. 100-year flood) across the entire study area.

Activating words beyond the unfolding sentence: Contributions of event simulation and word associations to discourse reading

Previous studies have shown that during comprehension readers activate words beyond the unfolding sentence. An open question concerns the mechanisms underlying this behavior. One proposal is that readers mentally simulate the described event and activate related words that might be referred to as the discourse further unfolds. Another proposal is that activation between words spreads in an automatic, associative fashion. The empirical support for these proposals is mixed. Therefore, theoretical accounts differ with regard to how much weight they place on the contributions of these sources to sentence comprehension. In the present study, we attempted to assess the contributions of event simulation and lexical associations to discourse reading, using event-related brain potentials (ERPs). Participants read target words, which were preceded by associatively related words either appearing in a coherent discourse event (Experiment 1) or in sentences that did not form a coherent discourse event (Experiment 2). Contextually unexpected target words that were associatively related to the described events elicited a reduced N400 amplitude compared to contextually unexpected target words that were unrelated to the events (Experiment 1). In Experiment 2, a similar but reduced effect was observed. These findings support the notion that during discourse reading event simulation and simple word associations jointly contribute to language comprehension by activating words that are beyond contextually congruent sentence continuations.

On turbulence and turbulent events in a breaking bore

A breaking bore is a highly unsteady turbulent motion that may affect both riverine and estuarine systems. Like many steady turbulent flows, the turbulent motion is dominated by intense coherent structure and turbulent event activities. A novel analysis of unsteady turbulent events is developed for transient breaking bores in which turbulent bursting events are defined in terms of the instantaneous relative turbulent flux. Using new physical data collected in a large facility under controlled flow conditions, the data analysis is applied to a breaking bore. The unsteady event data show some intense bursting during the flow deceleration associated with the bore passage. The results indicate that a turbulent event analysis may deliver valuable quantitative details into the turbulent bursts beneath bores, with applications relevant to turbulent mixing and sedimentary processes.

Nd Isotopic and Model Age Study of the Shandong Province, North China Craton: Implications for Correlation with South Korea

The geological units in Shandong Province, North China are important parts of the North China Craton and offer important insights into their crustal evolutionary history. This work compiled 611 sets of Nd isotopic data of Archean-Mesozoic rocks from Shandong including the Luxi, Jiaobei, and Sulu terranes, which provided important constraints for crustal growth and reactivation. Nd-depleted mantle model ages (TDM) of Archean rocks with positive eNd(t) values showed that ca. 2.9 and 2.8-2.7 Ga were the most important periods of crustal growth in the Jiaobei and Luxi terranes, respectively, while the period of ca. 2.6-2.5 Ga in the Jiaobei terrane likely indicated a coherent event of crustal growth and reworking. During the Proterozoic, multi-stage rifting and collisional orogenic events possibly led to the reworking of Archean crust in the source region. The Nd isotopic data of the Paleoproterozoic and Neoproterozoic rocks from Sulu indicated significant reworking of older crust with juvenile magmatic input. Crustal reactivation occurred during the Mesozoic. The younger TDM ages of the Mesozoic rocks with low negative eNd(t) values indicated that a juvenile crustal/mantle component was added to the ancient basement. The reactivation reflected significant crust-mantle interaction via the mechanism of crustal subduction and mantle-derived magma un-derplating, or possibly asthenospheric upwelling. Our work also attempted to establish the crustal correlation between Shandong and Korea (including the Gyeonggi massif, Ogcheon belt, and Yeongnam massif). The TDM age distribution provided evidence favoring the affinity relationship between the Gyeonggi massif and Ogcheon belt of South Korea and the Jiaobei and Sulu terranes of Shandong, while the Yeongnam massif was more correlated with the South China Block.

Stochastic generation of spatially coherent river discharge peaks for continental event-based flood risk assessment

Abstract. We present a new method to generate spatially coherent river discharge peaks over multiple river basins, which can be used for continental event-based probabilistic flood risk assessment. We first extract extreme events from river discharge time series data over a large set of locations by applying new peak identification and peak-matching methods. Then we describe these events using the discharge peak at each location while accounting for the fact that the events do not affect all locations. Lastly we fit the state-of-the-art multivariate extreme value distribution to the discharge peaks and generate from the fitted model a large catalogue of spatially coherent synthetic event descriptors. We demonstrate the capability of this approach in capturing the statistical dependence over all considered locations. We also discuss the limitations of this approach and investigate the sensitivity of the outcome to various model parameters.

A probabilistic risk modelling chain for analysis of regional flood events

A probabilistic flood risk modelling chain is proposed for flood risk analysis with consideration of spatial spreading and temporal clustering of the flood events. The proposed method consists of (1) a continuous simulation of long-term climatic and hydrologic fields, (2) Monte-Carlo simulations of a 1D river and inundation model and (3) a probabilistic loss model. In the first stage, three multisite multivariate weather generators were tested and a K-nearest neighbor weather generator (KNN-CAD v4) was found most suitable to reproduce hydrological extremes. The methodology was then applied to identify variations in risk between spatially coherent and simplified event sets generated from 5000 years of synthetic data across four river basins in Uttarakhand, India. The results showed that preserving the spatial coherency of regional events lead to a spreading of the T-year local event distributions on both sides of a uniform regional T-year return period. The specificity of the exposure and the correlations between local events translated into minimal (4%) differences in losses at high return periods (> 50 year) but larger difference (20%) at low return periods (5 to 10-year). The redistribution of loss frequencies led to negligible differences in the Annual Average Losses between the different event sets. In this application, a simplified event set structure with uniform but appropriate T-year return periods proved to capture reasonably well the averaged risk metrics regionally. This study illustrates the complexity of estimating regional flood risk accumulation and exemplifies how a probabilistic risk model chain with continuous simulation can provide a more detailed picture of flood risks.

Neural mechanisms for integrating consecutive and interleaved natural events.

To understand temporally extended events, the human brain needs to accumulate information continuously across time. Interruptions that require switching of attention to other event sequences disrupt this process. To reveal neural mechanisms supporting integration of event information, we measured brain activity with functional magnetic resonance imaging (fMRI) from 18 participants while they viewed 6.5-minute excerpts from three movies (i) consecutively and (ii) as interleaved segments of approximately 50-s in duration. We measured inter-subject reliability of brain activity by calculating inter-subject correlations (ISC) of fMRI signals and analyzed activation timecourses with a general linear model (GLM). Interleaving decreased the ISC in posterior temporal lobes, medial prefrontal cortex, superior precuneus, medial occipital cortex, and cerebellum. In the GLM analyses, posterior temporal lobes were activated more consistently by instances of speech when the movies were viewed consecutively than as interleaved segments. By contrast, low-level auditory and visual stimulus features and editing boundaries caused similar activity patterns in both conditions. In the medial occipital cortex, decreases in ISC were seen in short bursts throughout the movie clips. By contrast, the other areas showed longer-lasting differences in ISC during isolated scenes depicting socially-relevant and suspenseful content, such as deception or inter-subject conflict. The areas in the posterior temporal lobes also showed sustained activity during continuous actions and were deactivated when actions ended at scene boundaries. Our results suggest that the posterior temporal and dorsomedial prefrontal cortices, as well as the cerebellum and dorsal precuneus, support integration of events into coherent event sequences. Hum Brain Mapp 38:3360-3376, 2017. © 2017 Wiley Periodicals, Inc.

Slope tomography based on eikonal solvers and the adjoint-state method

Velocity macromodel building is a crucial step in the seismic imaging workflow as it provides the necessary background model for migration or full waveform inversion. In this study, we present a new formulation of stereotomography that can handle more efficiently long-offset acquisition, complex geological structures and large-scale data sets. Stereotomography is a slope tomographic method based upon a semi-automatic picking of local coherent events. Each local coherent event, characterized by its two-way traveltime and two slopes in common-shot and common-receiver gathers, is tied to a scatterer or a reflector segment in the subsurface. Ray tracing provides a natural forward engine to compute traveltime and slopes but can suffer from non-uniform ray sampling in presence of complex media and long-offset acquisitions. Moreover, most implementations of stereotomography explicitly build a sensitivity matrix, leading to the resolution of large systems of linear equations, which can be cumbersome when large-scale data sets are considered. Overcoming these issues comes with a new matrix-free formulation of stereotomography: a factored eikonal solver based on the fast sweeping method to compute first-arrival traveltimes and an adjoint-state formulation to compute the gradient of the misfit function. By solving eikonal equation from sources and receivers, we make the computational cost proportional to the number of sources and receivers while it is independent of picked events density in each shot and receiver gather. The model space involves the subsurface velocities and the scatterer coordinates, while the dips of the reflector segments are implicitly represented by the spatial support of the adjoint sources and are updated through the joint localization of nearby scatterers. We present an application on the complex Marmousi model for a towed-streamer acquisition and a realistic distribution of local events. We show that the estimated model, built without any prior knowledge of the velocities, provides a reliable initial model for frequency-domain FWI of long-offset data for a starting frequency of 4 Hz, although some artefacts at the reservoir level result from a deficit of illumination. This formulation of slope tomography provides a computationally efficient alternative to waveform inversion method such as reflection waveform inversion or differential-semblance optimization to build an initial model for pre-stack depth migration and conventional FWI.

Out of place, out of mind: Schema-driven false memory effects for object-location bindings.

Events consist of diverse elements, each processed in specialized neocortical networks, with temporal lobe memory systems binding these elements to form coherent event memories. We provide a novel theoretical analysis of an unexplored consequence of the independence of memory systems for elements and their bindings, 1 that raises the paradoxical prediction that schema-driven false memories can act solely on the binding of event elements despite the superior retrieval of individual elements. This is because if 2, or more, schema-relevant elements are bound together in unexpected conjunctions, the unexpected conjunction will increase attention during encoding to both the elements and their bindings, but only the bindings will receive competition with evoked schema-expected bindings. We test our model by examining memory for object-location bindings in recognition (Study 1) and recall (Studies 2 and 3) tasks. After studying schema-relevant objects in unexpected locations (e.g., pan on a stool in a kitchen scene), participants who then viewed these objects in expected locations (e.g., pan on stove) at test were more likely to falsely remember this object-location pairing as correct, compared with participants that viewed a different unexpected object-location pairing (e.g., pan on floor). In recall, participants were more likely to correctly remember individual schema-relevant objects originally viewed in unexpected, as opposed to expected locations, but were then more likely to misplace these items in the original room scene to expected places, relative to control schema-irrelevant objects. Our theoretical analysis and novel paradigm provide a tool for investigating memory distortions acting on binding processes. (PsycINFO Database Record

A Field RNG Experiment: Use of a Digital RNG at Movie Theaters

Over the past two decades, field RNG studies have reported anomalous statistical biases when a coherent event evokes emotions from an audience. A hardware device must be dedicated to generate true random numbers. Recent Intel’s Ivy Bridge CPU has an internal RNG, called a Digital RNG (Drng), which uses thermal noise. Using RdRand command, the present study involved a repeated-design field RNG experiment at theaters showing the movies Gekijo Rei (13 times), Star Wars Episode 7 (5 times), and Zang-e (8 times) to confirm this device’s sensitivity to anomalies. The Drng chi-square results showed a positive bias eight times during Zang-e, whereas no bias was detected during the other movies. No differences or correlations were found among the other kinds of RNG devices, suggesting that RNGs behave independently from each other. Drng outputs could be a useful way to apply micro PK studies in the absence of access to a dedicated device.