Relationships between characters are not just themes in a story but key elements that shape how plots unfold. This article presents a large-scale study of relational arcs, the trajectories of ties, such as kinship, romance, alliance and enmity as they rise and fall across the course of a novel. We build on the Artificial Relationships in Fiction dataset, which contains over 120,000 automatically annotated relationships from 96 novels published between 1850 and 1950. Our study makes four contributions. First, we show that relationship dynamics can be modeled as arcs that highlight recurring narrative patterns, such as conflicts peaking near the climax or romances resolving toward the end. Second, we use temporal normalization to compare books of very different lengths, allowing us to identify consistent trends across the corpus. Third, we demonstrate that genres and historical periods leave clear relational “fingerprints.” For instance, domestic fiction emphasizes family ties, while adventure stories highlight shifting alliances and adversaries. Finally, we cluster arcs into four common shapes (Rise, U-shape, Decline and Oscillating) that echo well-known narrative prototypes. By bringing narratology together with modern natural language processing, we argue that relationships provide a measurable grammar of plot. This approach offers new resources for literary analysis, new methods for computational modeling of narrative, and fresh evidence about how cultural storytelling patterns change over time.

We propose a novel approach to check whether individual behaviour in binary-choice participation games is consistent with the restrictions imposed by symmetric models. This approach allows in particular an assessment of how much cluster-heterogeneity a symmetric model can tolerate to remain consistent with its behavioural restrictions. We assess our approach with data from market-entry experiments which we analyse through the lens of ‘Exploration versus Exploration’ (EvE, which is equivalent to Logit-QRE) or of Impulse Balance Equilibrium (IBE). We find that when the symmetry assumption is imposed, both models are typically rejected when assuming pooled data and IBE yields more data-consistent estimates than EvE, i.e., IBE’s estimates of session and pooled data are more consistent than those of EvE. When relaxing symmetry, EvE (IBE) is rejected for 17% (42%) of the time. Although both models support cluster-heterogeneity, IBE is much less likely to yield over-parametrised specifications and insignificant estimates so it outperforms EvE in accommodating a model-consistent cluster-heterogeneity. The use of regularisation procedures in the estimations partially addresses EvE’s shortcomings but leaves our overall conclusions unchanged.

U.S. adaptive optics telescopes using laser guide stars for an artificial reference source are impacted by the presence of satellite constellations (SATCONs) because of the requirement to follow Department of Defense laser deconfliction protocol as administered by the U.S. Space Command’s Laser Clearinghouse. The Laser Deconfliction protocol is designed to protect damage to satellites and their operation due to inadvertent illumination. As SATCONs begin to dominate the number of satellites in orbit they contribute highly to the number of closure windows when the astronomical lasers cannot be propagated. If left unchecked, the proposed number of SATCONs over the next decade will severely impact the laser open-shutter time, especially for the U.S. extremely large telescopes (US-ELTs) reducing the competitiveness of U.S. astronomical adaptive optics. Mitigation of the closure windows is therefore important.

Nowadays public policymakers are offered with opportunities to take data-driven evidence-based decisions by analyzing the very large volumes of policy-related data that are generated through different channels (e.g., e-services, mobile apps, social media). Machine learning (ML) and artificial intelligence (AI) tehcnologies ease and automate the analysis of large policy-related datasets, which helps policymakers to realize a shift toward data-driven decisions. Nevertheless, the deployment and use of AI tools for public policy development is also associated with significant technical, political, and operation challenges. For instance, AI-based policy development solutions must be transparent and explainable to policymakers, while at the same time adhering to the mandates of emerging regulations such as the AI Act of the European Union. This paper introduces some of the main technical, operational, regulatory compliance challenges of AI-based policymaking. Accordingly, it introduces technological solutions for overcoming them, including: (i) a reference architecture for AI-based policy development, (ii) a virtualized cloud-based tool for the specification and implementation of ML-based data-driven policies, (iii) a ML framework that enables the development of transparent and explainable ML models for policymaking, and (iv) a set of guidelines for using the introduced technical solutions to achieve regulatory compliance. The paper ends up illustrating the validation and use of the introduced solutions in real-life public policymaking cases for various local governments.

The asteroid belt is a unique source of information on some of the most important questions facing solar system science. These questions include the sizes, numbers, types and orbital distributions of the planetesimals that formed the planets, and the identification of those asteroids that are the sources of meteorites and near-Earth asteroids. Answering these questions requires an understanding of the dynamical evolution of the asteroid belt, but this evolution is governed by a complex interplay of mechanisms that include catastrophic disruption, orbital evolution driven by Yarkovsky radiation forces, and chaotic orbital evolution driven by gravitational forces. While the timescales of these loss mechanisms have been calculated using estimates of some critical parameters that include the thermal properties, strengths and mean densities of the asteroids, we argue here that the uncertainties in these parameters are so large that deconvolution of the structure of the asteroid belt must be guided primarily by observational constraints. We argue that observations of the inner asteroid belt indicate that the size-frequency distribution is not close to the equilibrium distribution postulated by Dohnanyi (1969). We also discuss the correlations observed between the sizes and the orbital elements of the asteroids. While some of these correlations are significant and informative, others are spurious and may arise from the limitations of the Hierarchical Clustering Method that is currently used to define family membership.

The comprehension of Spanish verbal future and past tense of children with developmental language disorder (DLD) was evaluated in an eye-tracking experiment with 96 Spanish- and Catalan-speaking participants distributed in 4 groups: 24 children with DLD (Mage 7.8 years), 24 children with the same chronological age (Mage 7.8), 24 children with the same linguistic level (Mage 6.8 years), and 24 adults (Mage 22.5 years). Empirical data revealed that children with DLD can comprehend verbal tense, at least in the present experimental conditions. Based on the empirical results and despite some minor differences between the DLD group and the chronological control group, we suggest that tense morphology comprehension in DLD might be more typical than what is generally considered. Additionally, we propose that verbal comprehension difficulties in children with DLD might be less related to the lack of understanding of specific morphological markers, and more to an accumulation of difficulty which leads to a linguistic processing slowdown.

Studies on the processing of non-active (NACT) voice have indicated that passive sentences are more difficult to comprehend and require more time to process. Children with Reading Difficulties (RDs) face problems with sentence comprehension, which are often attributed to phonological processing, working memory, syntactic awareness limitations, or a maturation delay. Using an online self-paced reading task, we investigated the effect of voice morphology and argument structure on sentence processing in 3 groups of participants; 30 children RDs, 28 Age-Matched (AM) controls without RDs, and 28 young Beginning Readers (BRs). Our results suggest that although the RDs and BR groups present similar reading times, their reading patterns differ qualitatively. Beginning Readers experienced greater processing delays when processing NACT structures, suggesting that they have not yet fully grasped the properties of the various NACT verbs. However, the RDs group presents effects not found in the BR group; children with RDs were sensitive to the properties of the different types of NACT verbs showing (a) evidence that the language processor successfully engages in predictions based on the morphosyntactic and lexical characteristics of verbs and (b) preference for default/prototypical readings. These results point toward processing limitations that are greatly affected by syntactic complexity.

We have shown that in the inner belt the loss of asteroids from the ν6 secular resonance and the 3:1 Jovian mean motion resonance accounts for the observation that the mean size of the asteroids increases with increasing orbital inclination. We have used that observation to constrain the Yarkovsky loss timescale and to show that the family asteroids are embedded in a background population of old ghost families. We argue that all the asteroids in the inner belt originated from a small number of asteroids and that the initial mass of the belt was similar to that of the present belt. We also show that the observed size frequency distribution of the Vesta asteroid family was determined by the action of Yarkovsky forces, and that the age of this family is comparable to the age of the solar system.

OBJECTIVES/SPECIFIC AIMS: This study seeks to understand the relationship between opioid prescribing and patient satisfaction among non-surgical, hospitalized patients. As part of this study, we qualitatively examined challenges in delivering safe and patient-centered care through voices of physicians’, and nurses.’ METHODS/STUDY POPULATION: We collected data through in-person interviews using semi-structured guides tailored to the informant roles. Study participants came from 1 healthcare system located in a mid-Western state. Each interview lasted 30–45 minutes, was audio-recorded with consent, and transcribed for analysis. Two researchers each coded 17 transcripts for discussions around patient-centeredness (including patient satisfaction, patient experiences), and patient safety for hospitalized patients experiencing pain. Analysis followed a general inductive approach, where researchers identified themes related to the research questions using an open coding technique. They discussed and reached consensus on all codes, and extracted several preliminary themes. The analysis was supported by NVivo software. RESULTS/ANTICIPATED RESULTS: The following themes emerged: (1) complex decision-making process to prescribe opioids for hospitalized patients; (2) the role of objective findings in prescribing decisions; (3) bargaining process in prescribing opioids; (4) balancing patient-centeredness and patient safety for selected populations; (5) opioids are the predominant medications for pain care. DISCUSSION/SIGNIFICANCE OF IMPACT: Clinicians’ decision to prescribe opioids for nonsurgical hospitalized patients is based on multiple factors, including patient’s condition, patient’s preference for pain medications, or standard hospital’s pain care regimen. Interventions that improve clinicians’ ability to prescribe opioids may be needed to improve delivery of patient-centered and safe pain care.

The observed size-frequency distributions (SFDs) of the five major asteroid families in the Inner Main Belt (IMB), defined by Nesvorný (2015) using the Hierarchical Clustering Method (Zappala et al. 1990), are distinctly different and deviate significantly from the linear log-log relation described by Dohnanyi (1969). The existence of these differences in the SFDs, and the fact that the precursor bodies of the major families have distinctly different eccentricities and inclinations, provides an explanation for the observations that the mean sizes of both the family and the non-family asteroids are correlated with their mean proper eccentricities and anti-correlated with their mean proper inclinations. We deduce from this, and from the fact that the SFDs of the family and the non-family asteroids are almost identical, that the family and most of the non-family asteroids in the IMB have a common origin (Dermott et al. 2018).