Elsevier最新文献

A central question about our shared capacity for language is how it is integrated with other cognitive systems. One important debate focuses on the extent to which the form of linguistic expressions is grounded in their communicative function: Can all constraints on linguistic form be attributed to the way constructions package information, or is linguistic form autonomous of meaning and function? One area of disagreement involves islands: phrases which block the formation of long-distance filler-gap dependencies (Ross, 1967). Grammatical subjects are considered islands, since questioning a sub-part of a subject results in an ill-formed sentence, e.g., "Which topic did the article about inspire you?". Autonomous syntactic approaches to islands attribute this ungrammaticality to the abstract movement dependency between the wh-phrase and the subject-internal position with which it is associated. An alternative developed in Abeillé et al. (2020) suggests that subjects' island status is specific to the information structure of wh-questions, suggesting that subjects are not islands for movement, but for focusing, due to their discourse-backgroundedness. This predicts that other constructions that involve movement but not focusing should not create a subject island effect. We test this in three acceptability studies, using a factorial design to isolate subject island violations across three constructions: wh-questions, relative clauses and topicalization. We find a subject island effect in each case, despite only wh-questions introducing what Abeillé et al. (2020) call "a clash in information structure". We argue that this motivates an account of islands in terms of syntactic representations shared across constructions, independent of communicative function.

Artificial intelligence (AI) is rapidly transforming digital, clinical, and cultural landscapes in ways that hold significant implications for body image and eating disorder (ED) prevention. This article outlines how traditional and generative AI technologies influence societal appearance ideals as well as digital environments, including online mental health tools. While AI offers opportunities for early detection, personalized and scalable prevention, and the promotion of more inclusive representation, it also poses ethical and psychological risks, including amplification of harmful appearance ideals, algorithmic bias, and overreliance on technology. This article identifies key research priorities relevant to body image spanning macro-level impacts, emerging use cases, ethics and safety, equity and representation in datasets, public perceptions, and the need for interdisciplinary and participatory governance. As AI becomes embedded in everyday life, its responsible and safe use will be critical to ensuring it does not exacerbate body image concerns or increase ED risk.

As automated vehicles (AVs) become increasingly prevalent in mixed-traffic environments, it is essential to understand how they interact with human-driven vehicles (HDVs), especially in safety-critical situations. Existing research has primarily focused on AVs' collision avoidance strategies, often neglecting how AV maneuvers simultaneously influence the decision-making behaviors of HDVs. This study develops the multi-agent state-space attention-enhanced deep deterministic policy gradient (MA-ASS-DDPG) framework, leveraging the Third Generation Simulation (TGSIM) dataset for the first time to learn interactive car-following behaviors of an AV and the following human-driven vehicles (FHDV) in safety-critical scenarios. By integrating the attention mechanism to dynamically prioritize critical motion features and the state-space model to effectively capture temporal dependencies, the proposed framework models AVs executing collision avoidance strategies while simultaneously prompting HDVs to adapt their behaviors to mitigate potential risks. Results showed that MA-ASS-DDPG demonstrated superior performance in learning maneuvers of both the AV and the FHDV, outperforming counterpart models. Further, the MA-ASS-DDPG was used to reconstruct evasive trajectories of AVs and HDVs in safety-critical scenarios, and the reconstructed data successfully replicated reaction times comparable to real-world observations, further validating the model's effectiveness. Analysis showed that AVs following HDVs reacted 0.3473 s faster than HDV-HDV pairs, while HDVs following AVs reacted 0.2143 s faster, demonstrating more cautious and adaptive driving in response to AV maneuvers. Counterfactual analysis revealed that HDVs following AVs adopt more conservative speeds and larger acceleration variability. In addition, incorporating a safety term into the reward function of the learning framework leads to substantial improvements in safety performance, including reduced conflict occurrences, fewer high-risk deceleration events, and enhanced car-following stability. These outcomes of this study can support safety-aware traffic simulation, scenario-based safety testing, and enhanced AV control strategies in mixed-traffic environments.

The current study aims to propose, develop, and validate a conceptual framework featuring viewer engagement and psychological consequences in the context of live streaming commerce. Focusing on how streamers' trustworthiness and attractiveness shape streamers' state mindfulness experiences for live streaming commerce among Uzbekistan-based consumers, our framework draws upon Stimulus-Organism-Response (S-O-R); Uses and Gratifications Theory (UGT) and Social Cognitive Theory (SCT). Survey data generated 319 valid responses from livestream viewers in Uzbekistan, which were used to empirically evaluate the proposed model through Structural Equation Modeling (SEM). Findings reveal that participants engage in a three-stage process, which includes the stimulus, organism, and response stage, in shaping their psychological engagement during livestreaming. The evidence demonstrates that streamer trustworthiness and attractiveness serve as important precursors to information seeking, recognition, and escapism gratifications, which, in turn, enhance mindful engagement online. By offering insights into viewers' mental and emotional reactions to streamer cues in a developing market environment, the study is expected to guide the creation of livestreaming platforms that foster sustained attention and online well-being in Uzbekistan and other developing economies with similar socio-cultural settings.

Molybdenum (Mo), a vital metallic element for the growth of flora and fauna, holds considerable commercial significance. However, research on Mo toxicity and its bioavailability remains limited. This study exploited the model organism Caenorhabditis elegans to examine the biological toxicity of Mo exposure in aquatic environments. By simulating environmental systems, the influence of fulvic acid (FA) on the bioavailability of Mo was investigated. The EquRay (Equilibrium Partitioning Ray) method was utilized to develop a binary mixed exposure system, exposing nematodes to a combination of FA and Mo with increased reactivity to examine the impact of FA on the composite toxicity of Mo. The results indicated that high-concentration Mo exposure (3000 mg L^-1) led to significant abnormalities in nematode survival and movement, with a 24-h median lethal concentration (LC₅₀) of 6000 mg L^-1. However, the addition of FA did not significantly ameliorate the survival toxicity of Mo but instead generated abnormally hyperactive movement in nematodes, particularly manifested as robust head thrashing,which was significantly higher than that of the control group. This study integrates "pollutants - biomarkers - effects" to analyze the bioavailability of heavy metals and their influencing factors, offering experimental evidence and theoretical support for creating and forecasting ecological risk models of heavy metal Mo in aquatic environments.