Event Structure Research Articles

Beyond Grounding: Extracting Fine-Grained Event Hierarchies across Modalities

Events describe happenings in our world that are of importance. Naturally, understanding events mentioned in multimedia content and how they are related forms an important way of comprehending our world. Existing literature can infer if events across textual and visual (video) domains are identical (via grounding) and thus, on the same semantic level. However, grounding fails to capture the intricate cross-event relations that exist due to the same events being referred to on many semantic levels. For example, the abstract event of "war'' manifests at a lower semantic level through subevents "tanks firing'' (in video) and airplane "shot'' (in text), leading to a hierarchical, multimodal relationship between the events. In this paper, we propose the task of extracting event hierarchies from multimodal (video and text) data to capture how the same event manifests itself in different modalities at different semantic levels. This reveals the structure of events and is critical to understanding them. To support research on this task, we introduce the Multimodal Hierarchical Events (MultiHiEve) dataset. Unlike prior video-language datasets, MultiHiEve is composed of news video-article pairs, which makes it rich in event hierarchies. We densely annotate a part of the dataset to construct the test benchmark. We show the limitations of state-of-the-art unimodal and multimodal baselines on this task. Further, we address these limitations via a new weakly supervised model, leveraging only unannotated video-article pairs from MultiHiEve. We perform a thorough evaluation of our proposed method which demonstrates improved performance on this task and highlight opportunities for future research. Data: https://github.com/hayyubi/multihieve

Mastering Context-to-Label Representation Transformation for Event Causality Identification with Diffusion Models

To understand event structures of documents, event causality identification (ECI) emerges as a crucial task, aiming to discern causal relationships among event mentions. The latest approach for ECI has introduced advanced deep learning models where transformer-based encoding models, complemented by enriching components, are typically leveraged to learn effective event context representations for causality prediction. As such, an important step for ECI models is to transform the event context representations into causal label representations to perform logits score computation for training and inference purposes. Within this framework, event context representations might encapsulate numerous complicated and noisy structures due to the potential long context between the input events while causal label representations are intended to capture pure information about the causal relations to facilitate score estimation. Nonetheless, a notable drawback of existing ECI models stems from their reliance on simple feed-forward networks to handle the complex context-to-label representation transformation process, which might require drastic changes in the representations to hinder the learning process. To overcome this issue, our work introduces a novel method for ECI where, instead abrupt transformations, event context representations are gradually updated to achieve effective label representations. This process will be done incrementally to allow filtering of irrelevant structures at varying levels of granularity for causal relations. To realize this, we present a diffusion model to learn gradual representation transition processes between context and causal labels. It operates through a forward pass for causal label representation noising and a reverse pass for reconstructing label representations from random noise. Our experiments on different datasets across multiple languages demonstrate the advantages of the diffusion model with state-of-the-art performance for ECI.

Abstract 4334: Insight into the structure of breakage fusion bridge events and chromothripsis in cancer cell lines using long-read sequencing

Abstract Cervical cancer is caused by human papillomavirus (HPV) infection and is the most common cause of cancer death in low-resource countries. We characterized 18 cervical and 4 head and neck cancer cell lines using long-read DNA and RNA sequencing and identified the HPV types, HPV integration sites, and cancer driver mutations. This cell line panel represents the major molecular subtypes of cervical cancer. Structural variation analysis revealed recurrent chromosomal alteration and telomeric deletions associated with DNA inversions resulting from breakage-fusion-bridge (BFB) cycles. BFB is a common mechanism of chromosomal alteration in cancer that has not been studied using long-read sequencing. Analysis of the inversion sites revealed staggered ends consistent with exonuclease deletion of the DNA after breakage. Some BFB events are complex, involving interchromosomal or intrachromosomal insertions or rearrangements. In total, there were three different types of BFB events: Type I, II, and III. Type I BFB events have staggered ends but no additional insertion at the fusion site. Type II BFB events have an insertion of DNA from another chromosome at the junction, and Type III has an insertion of sequences from the same chromosome as the BFB. BFB cycles are thought to resolve with the addition of a telomere. However, a search for telomeric sequences did not identify any on chromosomes impacted by BFB. In many cancers, BFB events co-occur with chromothripsis; however, in our cervical cancers, only 1 out of 13 had chromosomal shattering near the BFB event, indicating that the mechanism of chromosome rearrangement may be different in cervical cancers. Five cell lines have a Chr11q BFB event, with YAP1/BIRC2/BIRC3 gene amplification. Analysis of 911 publicly available cervical cancer exomes showed that YAP1 amplification is associated with a 10-year earlier age of diagnosis of cervical cancer (x2, p<0.0001) and is three times more common in African Americans (x2=12, p=0.003). Therefore, cervical cancer patients with YAP1/BIRC2/BIRC3 amplification, especially those of African American ancestry, might benefit from anti-YAP1/BIRC2/BIRC3 therapies. Our panel provides models for all the major HPV types and subtypes of cervical cancer that will aid in developing new therapeutic approaches. In summary, we uncovered novel insights into the mechanisms and consequences of BFB cycles in cervical cancer using long-read sequencing. We are expanding long-read sequencing to other cancer cell lines to gain knowledge of events associated with BFB. Citation Format: Isabel Rodriguez, Nicole Rossi, Ayse Gokce Kesus, Yi Xie, Tanveer Ahmad, Asher Bryant, Hong Lou, Jesica Godinez Paredes, Rose Milano, Mikhail Kolmogorov, Sonam Tulsyan, Jazmyn Bess, Vera Mukhina, Daria Gaykalova, Laksh Malik, Kimberley J. Billingsley, Cornelis Blauwendraat, Lisa Mirabello, Michael Dean. Insight into the structure of breakage fusion bridge events and chromothripsis in cancer cell lines using long-read sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4334.

Abstract 2280: HPV integration identifies emerging oncogenes and carcinogenic mechanisms, potentially indicating tumor recurrences

Abstract HPV integration events in Head and neck squamous cell carcinomas (HNSCC) are strongly associated with carcinogenesis and tumor progression. Previous studies have elucidated the mechanisms and structures of HPV-human fusion events, pinpointing potential integration “hotspots” (i.e. genes with nearby HPV integration in recurrent patients). However, none has comprehensively investigated the effects of HPV integration on both HPV and human gene expression, nor assessed the clinical implications of these bidirectional expression changes. In this study, we conducted bulk RNA sequencing on 67 Formalin-Fixed Paraffin-Embedded Oropharyngeal Squamous Cell Carcinoma (OPSCC) tumor samples from the University of Michigan hospital, and analyzed them in conjunction with bulk and single cell RNA-seq from another >200 HPV(+) HNSCC patients from four previous studies. Among the 117 samples confidently identified as HPV integration positive, we recaptured all previously known integration “hotspot” genes as well as several novel ones that have altered expression in the integrated samples. Exploring the impact of HPV integration on the expression of human and HPV genes, we found that HPV integration in HNSCC is strongly associated with keratinization, immune response, and the development of HPV(+) HNSCC subtypes. Upon HPV integration, expression of non-oncogenic HPV genes is often lost. We hypothesized that the expression ratio of these potentially HPV immunogenic genes (E1-E5, L1,L2) to the HPV oncogenic genes E6 and E7 (termed the ImmunOnco Score) would predict clinical outcomes. Survival analysis of 70 University of Michigan patients showed low ImmunOnco Score is associated with tumor recurrence. Citation Format: Shiting Li, Shaomiao Xia, Maria Lawas, Tingting Qin, Bailey Grab, Nisha D'Silva, Laura Rozek, Maureen Sartor. HPV integration identifies emerging oncogenes and carcinogenic mechanisms, potentially indicating tumor recurrences [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2280.

Quantum Clock in the Projection Evolution Formalism

Using the projection evolution (PEv) approach, time can be included in quantum mechanics as an observable. Having the time operator, it is possible to explore the temporal structure of various quantum events. In the present paper, we discuss the possibility of constructing a quantum clock which advances in time during its quantum evolution, in each step having some probability to localize itself on the time axis in the new position. We propose a working two-state model as the simplest example of such a clock.

Eruptive events with exceptionally bright emission in H I Ly-α observed by the Metis coronagraph

Context. Ultraviolet (UV) emission from coronal mass ejections can provide information on the evolution of plasma dynamics, temperature, and elemental composition, as demonstrated by the UV Coronagraph Spectrometer (UVCS) on board the SOlar and Heliospheric Observatory (SOHO). Metis, the coronagraph on board Solar Orbiter, provides for the first time coronagraphic imaging in the UV H I Ly-α line and, simultaneously, in polarized visible light, thus providing a host of information on the properties of coronal mass ejections and solar eruptions such as their overall dynamics, time evolution, mass content, and outflow propagation velocity in the expanding corona. Aims. For this work, we analyzed six coronal mass ejections observed by Metis between April and October 2021, which are characterized by a very strong H I Ly-α emission. We studied in particular the morphology, kinematics, and the temporal and radial evolution of the emission of such events, focusing on the brightest UV features. Methods. The kinematics of the eruptive events under consideration were studied by determining the height-time profiles of the brightest parts on the Metis plane of the sky. Furthermore, the 3D positions in the heliosphere of the coronal mass ejections were determined by employing co-temporal images, when available, from two other coronagraphs: LASCO/C2 on board SOHO, and COR2 on board STEREO-A. In three cases, the most likely source region on the solar surface could be identified. Finally, the radiometrically calibrated Metis images of the bright UV features were analyzed to provide estimates of their volume and density. From the kinematics and radiometric analysis, we obtained indications of the temperatures of the bright UV cores of these events. These results were then compared with previous studies with the UVCS spectrocoronagraph. Results. The analysis of these strong UV-emitting features associated with coronal mass ejections demonstrates the capabilities of the current constellation of space coronagraphs, Metis, LASCO/C2, and COR2, in providing a complete characterization of the structure and dynamics of eruptive events in their propagation phase from their inception up to several solar radii. Furthermore, we show how the unique capabilities of the Metis instrument to observe these events in both the H I Ly-α line and polarized VL radiation allow plasma diagnostics on the thermal state of these events.

Enhancing Seismic Resilience: Evaluating Buildings with Passive Energy Dissipation Strategies

Structures are recommended to be designed and constructed with the integration of structural health monitoring techniques to ensure that they can dissipate a large amount of energy without considerable damage when subjected to earthquakes. Hysteretic (H), friction (F), viscous (V), and viscoelastic (VE) dampers were employed in this study to observe the response of buildings using the commercially available software ETABS. The effect of different dampers along with configurations on three prototype concrete buildings (3, 5, and 10-storey) was studied by performing a time history analysis. Initially, the response of the buildings was observed in terms of storey drifts, base shear, and displacement without using dampers, while gradually increasing the damping ratio from 0 to 40%. Subsequently, the response of the buildings was evaluated in terms of displacements and base shear using various types of dampers with different configurations. The analysis results demonstrated that the effectiveness of viscous and viscoelastic dampers is higher for 3 and 5-storey buildings, while friction and hysteresis dampers are more suitable for 10-storey buildings. This information enables informed decisions regarding the performance and maintenance of dampers, contributing to the overall resilience and durability of structures in seismic events.

Elucidate the molecular basis of ampholytic chitosan as a high-performance cryoprotectant to myosin denaturation: The importance of saccharide charges

The uses of charged poly/oligo-saccharides enable the retarding of protein denaturation against various environmental stresses during food storage and manufacturing. However, at subzero temperatures, the molecular basis of such stabilization behaviors, i.e., cryoprotections, remain less explored. In this study, we introduced an ampholytic saccharide, carboxymethyl chitooligosaccharide (CMCO) that effectively inhibited the freezing-induced myosin denaturation. The in-depth cryoprotective mechanism was systematically investigated by using molecular dynamic simulation and multispectral characterizations. Results showed that CMCO may interact with myosin through hydrogen bonding and electrostatic interactions, which caused the expelling of water at protein surfaces and the reduced conformational flexibility of myosin molecules. Due to this water replacement event, both secondary and ternary structures of myosin became freezing-resistant, leading to the inhibited protein aggregations and retained functionalities, such as solubility, Ca2+-ATPase activity, and gelling properties. Moreover, cryoprotective behaviors of CMCO were charge-dependent. CMCO with a higher degree of carboxymethyl substitution (DS: 1.2) was inclined to bind and stabilize myosin molecules better than the low-DS (DS: 0.8) one, even though both outperformed other cryoprotective saccharides. Therefore, this investigation not only introducing a high-performance myosin cryoprotectant, but also elaborated the cryoprotective mechanism of ampholytic saccharides.

Sleep shapes the associative structure underlying pattern completion in multielement event memory

Sleep supports the consolidation of episodic memory. It is, however, a matter of ongoing debate how this effect is established, because, so far, it has been demonstrated almost exclusively for simple associations, which lack the complex associative structure of real-life events, typically comprising multiple elements with different association strengths. Because of this associative structure interlinking the individual elements, a partial cue (e.g., a single element) can recover an entire multielement event. This process, referred to as pattern completion, is a fundamental property of episodic memory. Yet, it is currently unknown how sleep affects the associative structure within multielement events and subsequent processes of pattern completion. Here, we investigated the effects of post-encoding sleep, compared with a period of nocturnal wakefulness (followed by a recovery night), on multielement associative structures in healthy humans using a verbal associative learning task including strongly, weakly, and not directly encoded associations. We demonstrate that sleep selectively benefits memory for weakly associated elements as well as for associations that were not directly encoded but not for strongly associated elements within a multielement event structure. Crucially, these effects were accompanied by a beneficial effect of sleep on the ability to recall multiple elements of an event based on a single common cue. In addition, retrieval performance was predicted by sleep spindle activity during post-encoding sleep. Together, these results indicate that sleep plays a fundamental role in shaping associative structures, thereby supporting pattern completion in complex multielement events.

Construction or updating? Event model processes during visual narrative comprehension

The plot of a narrative is represented in the form of event models in working memory. Because only parts of the plot are actually presented and information is continually changing, comprehenders have to infer a good portion of a narrative and keep their mental representation updated. Research has identified two related processes (e.g., Gernsbacher, 1997): During model construction (shifting, laying a foundation) at large coherence breaks an event model is completely built anew. During model updating (mapping) at smaller omissions, however, the current event model is preserved, and only changed parts are updated through inference processes. Thus far, reliably distinguishing those two processes in visual narratives like comics was difficult. We report a study (N = 80) that aimed to map the differences between constructing and updating event models in visual narratives by combining measures from narrative comprehension and event cognition research and manipulating event structure. Participants watched short visual narratives designed to (not) contain event boundaries at larger coherence breaks and elicit inferences through small omissions, while we collected viewing time measures as well as event segmentation and comprehensibility data. Viewing time, segmentation, and comprehensibility data were in line with the assumption of two distinct comprehension processes. We thus found converging evidence across multiple measures for distinct model construction and updating processes in visual narratives.

Open‐domain event schema induction via weighted attentive hypergraph neural network

SummaryEvent schema refers to the use of a template to depict similar events, and it is a necessary prerequisite for event causality extractions. The induction of event schemas is a difficult task, especially for texts in the open domain, due to the complex and diverse manifestations of events. Previous models considered participants in event mentions are independent or compositional, ignoring the high‐order correlations among participants, which limit their capability of induce event schema. To remedy this, we propose constructing an Event Structure Hypergraph (ESH) to better utilizes the event structural information for event schema induction. In particular, we first extract event mentions from the open‐domain corpus. and then construct an ESH by representing event mentions as a hyperedges. ESH contains high‐order information between participants in event mention. To, learn event mentions representation based on ESH, we propose a weighted attentive hypergraph neural network (WHGNN) to model event high‐order correlations and then integrate node‐category weight matrix into the training of network by improving event representation. By applying jointly cluster algorithm on the event mentions representation, we can induce reliable event schemas. Experimental results on three datasets demonstrate that our approach can induce salient and high‐quality event schemas on open‐domain corpus.

Mechanical performance of CRTS II slab tracks in reinforced-unreinforced transition zone in extreme heat events

Anchors have been widely utilized to reinforce the CRTS II slab tracks. The mechanical performance of the tracks in the reinforced-unreinforced transition zone exposed to extreme heat waves can be very complex due to the difference in mechanical properties between the two kinds of track segments. This paper investigates the damage behavior of the tracks in the reinforced-unreinforced transition zone in extreme heat events. A finite element model of the CRTS II slab track in the transition zone has been established and validated, in which the nonlinear mechanical properties of track materials and interfaces are considered by applying the Concrete Damaged Plasticity model and the Cohesive Zone Model respectively. The nonlinear temperature field in the track structure in extreme heat events is applied to the model. Structural damage of the track, including slab-end arching and interfacial failure, in the transition zone under extreme heat is thoroughly investigated. In particular, the effects of joint use of post-installed reinforcement anchors and other track maintenance measures like interface adhesives and concrete joint restoration are studied. The following conclusions are drawn: (1) The more reinforced track-slabs in the transition zone, the milder the track diseases including slab-end arching and interfacial gapping. (2) Joint use of anchor installation and other maintenance measures such as interface adhesives and concrete joint restoration shows a better effect on mitigating track damage than using post-installed reinforcement anchors solely. (3) Concrete joint restoration overweighs interface adhesives in terms of reducing slab-end arching and interfacial damage when they are jointly used with post-installed reinforcement anchors. (4) In the transition zone, track damage surges when the air temperature increases from 42 ℃ to 47 ℃, which is the temperature range for an extreme heat wave. Monitoring of track state in the transition zones is necessary during extreme heat waves. The novel findings are expected to provide some insights into the mechanical performance of slab tracks and help to prevent potential damage to the tracks in the transition zone, which is a common and practical issue in railway engineering.

Evaluating the Bayesian causal inference model of intentional binding through computational modeling.

Intentional binding refers to the subjective compression of the time interval between an action and its consequence. While intentional binding has been widely used as a proxy for the sense of agency, its underlying mechanism has been largely veiled. Bayesian causal inference (BCI) has gained attention as a potential explanation, but currently lacks sufficient empirical support. Thus, this study implemented various computational models to describe the possible mechanisms of intentional binding, fitted them to individual observed data, and quantitatively evaluated their performance. The BCI models successfully isolated the parameters that potentially contributed to intentional binding (i.e., causal belief and temporal prediction) and generally better explained an observer's time estimation than traditional models such as maximum likelihood estimation. The estimated parameter values suggested that the time compression resulted from an expectation that the actions would immediately cause sensory outcomes. Furthermore, I investigated the algorithm that realized this BCI and found probability-matching to be a plausible candidate; people might heuristically reconstruct event timing depending on causal uncertainty rather than optimally integrating causal and temporal posteriors. The evidence demonstrated the utility of computational modeling to investigate how humans infer the causal and temporal structures of events and individual differences in that process.

Single-neuronal elements of speech production in humans

Humans are capable of generating extraordinarily diverse articulatory movement combinations to produce meaningful speech. This ability to orchestrate specific phonetic sequences, and their syllabification and inflection over subsecond timescales allows us to produce thousands of word sounds and is a core component of language1,2. The fundamental cellular units and constructs by which we plan and produce words during speech, however, remain largely unknown. Here, using acute ultrahigh-density Neuropixels recordings capable of sampling across the cortical column in humans, we discover neurons in the language-dominant prefrontal cortex that encoded detailed information about the phonetic arrangement and composition of planned words during the production of natural speech. These neurons represented the specific order and structure of articulatory events before utterance and reflected the segmentation of phonetic sequences into distinct syllables. They also accurately predicted the phonetic, syllabic and morphological components of upcoming words and showed a temporally ordered dynamic. Collectively, we show how these mixtures of cells are broadly organized along the cortical column and how their activity patterns transition from articulation planning to production. We also demonstrate how these cells reliably track the detailed composition of consonant and vowel sounds during perception and how they distinguish processes specifically related to speaking from those related to listening. Together, these findings reveal a remarkably structured organization and encoding cascade of phonetic representations by prefrontal neurons in humans and demonstrate a cellular process that can support the production of speech.

Proportional rates models for multivariate panel count data.

Multivariate panel count data arise when there are multiple types of recurrent events, and the observation for each study subject consists of the number of recurrent events of each type between two successive examinations. We formulate the effects of potentially time-dependent covariates on multiple types of recurrent events through proportional rates models, while leaving the dependence structures of the related recurrent events completely unspecified. We employ nonparametric maximum pseudo-likelihood estimation under the working assumptions that all types of events are independent and each type of event is a nonhomogeneous Poisson process, and we develop a simple and stable EM-type algorithm. We show that the resulting estimators of the regression parameters are consistent and asymptotically normal, with a covariance matrix that can be estimated consistently by a sandwich estimator. In addition, we develop a class of graphical and numerical methods for checking the adequacy of the fitted model. Finally, we evaluate the performance of the proposed methods through simulation studies and analysis of a skin cancer clinical trial.

Transformation of Melodrama in Turkish Cinema from Yeşilçam to the Present: The Films Innocence and Destiny

Melodramas are dramatic works of art where the detailed character studies dominate the plot. The dialogues used in melodramas are generally emotional, and the characters are often portrayed in stereotypical forms. Melodramas usually focus on emotions like love. As a subgenre of drama films, melodramas carry the mentioned characteristics of this genre; thus, they have plotlines driven by powerful emotions such as love. Content-wise, melodrama films often deal with tragedies like hopeless love stories. Characters must struggle against significant social pressures from their lovers or families. Sacrifice is a fundamental tool for characters in this struggle. Yeşilçam melodramas adhere to the requirements of this genre. They typically revolve around an exalted love that could be noble and spiritual. Characters must fight for this love like medieval knights. The characters in these films are usually unfortunate, and their mistakes turn their lives into hell. Zeki Demirkubuz, an important director of the New Turkish Cinema, continues the tradition of melodrama as an inheritor of its themes. However, he differentiates himself from them in terms of how he approaches the concept of good and evil. This study examines the difference between these two understandings of melodrama through Demirkubuz's films "Innocence" and "Destiny" using content analysis and critical discourse analysis methods. Demirkubuz’s two films selected as samples carry the general characteristics of Yeşilçam melodramas such as exaggerated emotions, missed happiness, extremes, bipolar lives, event structures based on cause-and-effect relationships, monologue uses, music uses, while they differ from them at an important point. While Yeşilçam melodramas view humans as ontologically good beings despite their mistakes, Demirkubuz's cinema accepts humans as ontologically evil beings. This study will reveal that, unlike the previous studies’ theses, Demirkubuz’s cinema places evil at the center of its films through their event structures, dialogues and word choices, and thus turns upside down the approach of Yeşilçam melodramas to evil.

WORKSHOP DAN PENDAMPINGAN GURU DALAM MENDESAIAN BAHAN AJAR DIGITAL DI SMK MUHAMMADIYAH PONJONG

This Prodamat activity aims to provide workshops and assistance to teachers in designing digital teaching materials at Ponjong Muhammadiyah Vocational School. Prodamat's activity methods include: measuring teachers' abilities in designing digital teaching materials, workshops introducing Flip PDF Corporate Edition software, assisting in designing digital teaching materials with Flip PDF Corporate Edition software, and evaluating the effectiveness of workshops and mentoring activities on teachers' ability to design the teaching materials. The results of the activity feedback show the effectiveness of the implementation of the activity because the average participant assessment is at a high and highest level, namely a score of 4 and a score of 5. This shows a very good response to aspects of the usefulness of the event, tight time with the event structure, completeness of the material, attitude committee, suitability of the presenter to the event theme, clarity of the event, mastery of the material, interaction with participants, and management/time management

The Nanling Mountains of southern China played a variable role as a barrier and refuge for birds depending upon landscape structure and timing of events

The Nanling Mountains, an important mountain range and watershed in south China, harbor a wealth of relictual plant species, and are considered a ‘museum' of subtropical biodiversity. With respect to birds, however, the roles of the Nanling Mountains in impeding the dispersal of the subtropical birds and, as a result, shaping their population and community structures have received little consideration. To examine these roles, we compiled and analyzed two datasets. 1) To test the mountains' influence on gene flow, we undertook a comparative phylogeographic study comparing mitochondrial COI and Cytb DNA sequences of five sylvioid resident bird species of the mountains (Huet's fulvetta Alcippe hueti, red‐billed leiothrix Leiothrix lutea, greater necklaced laughingthrush Pterorhinus pectoralis, Indochinese yuhina Staphida torqueola and mountain bulbul Ixos mcclellandii). 2) To examine differential community development over the history of modern birds, we examined distributional data of all species of the Nanling region using public species occurrence records. For part 1), we sampled 327 individuals from 36 sites and conducted correlation analysis of genetic and geographic distances, taking into account the landscape of the mountains. We found that the mountains do not seriously impede gene flow among populations but influenced species differently. For part 2), comparative analysis of 446 species in 81 families indicated that family membership influenced the community composition of birds in Nanling region. Variation in family distributions is attributable to both environmental and evolutionary factors. Overall, we found that the Nanling Mountains are not currently a substantial barrier to gene flow among the species we studied but act as a corridor and refuge for these birds. However, analyses on higher ranked community data suggest the mountains acted as a barrier in older times, corresponding to the known diversification events in southeast Asian avifauna.

Stochastic properties of coastal flooding events – Part 2: Probabilistic analysis

Abstract. Low-intensity but high-frequency coastal flooding, also known as nuisance flooding, can negatively affect low-lying coastal communities with potentially large socioeconomic effects. Partially driven by wave runup, this type of flooding is difficult to predict due to the complexity of the processes involved. Here, we present the results of a probabilistic analysis of flooding events measured on an eroded beach at the Texas coast. A high-resolution time series of the flooded area was obtained from pictures using convolutional neural network (CNN)-based semantic segmentation methods, as described in the first part of this contribution. After defining flooding events using a peak-over-threshold method, we found that their size follows an exponential distribution. Furthermore, consecutive flooding events were uncorrelated at daily timescales but correlated at hourly timescales, as expected from tidal and day–night cycles. Our measurements confirm the broader findings of a recent multi-site investigation of the probabilistic structure of high-water events that used a semi-empirical formulation for wave runup. Indeed, we found a relatively good statistical agreement between our CNN-based empirical flooding data and predictions using total-water-level estimations. As a consequence, our work supports the validity of a relatively simple probabilistic model of high-frequency coastal flooding driven by wave runup that can be used in coastal risk management and landscape evolution models.

A Reduction based on Event Structure in Automorphism Group

A Reduction based on Event Structure in Automorphism Group