Bridges in three-dimensional granular packings: experiments and simulations

In this letter, we present the first experimental study of bridge structures in three-dimensional dry granular packings. When bridges are small, they are predominantly 'linear', and have an exponential size distribution. Larger, predominantly 'complex' bridges, are confirmed to follow a power-law size distribution. Our experiments, which use X-ray tomography, are in good agreement with the simulations presented here, for the distribution of sizes, end-to-end lengths, base extensions and orientations of predominantly linear bridges. Quantitative differences between the present experiment and earlier simulations suggest that packing fraction is an important determinant of bridge structure.Comment: 6 pages, 7 figures, accepted by EPL (2013

How many keywords do authors assign to research articles – a multi-disciplinary analysis?

Author keywords are one important data source for co-word analysis. The distri-bution of author keywords in papers has not been investigated at the discipline level. We analyzed six research fields from soft science to hard science to reveal the underlying quantitative patterns of author keywords. Normal distribution, Poisson distribution, and Weibull distribution were fitted by applying Maximum Likelihood Estimation. Chi-Square tests and Kolmogorov-Smirnov tests were used to evaluate the goodness of fit. The results show that a large portion of pa-pers have no keyword or only one keyword in all these fields. The author key-word distributions of the six fields are represented. It’s shown that Weibull dis-tribution is the best fitted. This study provides practical implications for keyword selection in co-word analysis

Resolving Taxonomic Names using Evidence Extracted from Text

Biological taxonomy is established on organism relationships with scientific names as the primary identifiers; however, resolving various taxonomic names remains one of the greatest challenges in taxonomy and systematic biology overall. We proposed an evidence-based approach that extracts trait (character) evidence from published literature to facilitate the comparison of taxonomic concepts. In this poster, we report an initial set of results from our first case study using the plant genus Rubus. The case study tested the entire pipeline of the Explorer of Taxon Concepts toolkit we have developed and revealed challenging phenomena to be solved in the near future

Perspectivas de estudiantes universitarios sobre la Inteligencia Artificial: Un estudio de actitudes y conciencia entre estudiantes de Arquitectura de Interiores

This study explores interior architecture students' perspectives on artificial intelligence (AI) technologies and their implications for future career prospects. A survey of 230 third-year interior architecture students in China utilized a Technology Acceptance Model (TAM)-based questionnaire, yielding 158 valid responses. The investigation aimed to gauge students' familiarity with recent AI advancements (e.g., ChatGPT, Stable Diffusion, Midjourney) and their readiness to incorporate AI into their future careers. Findings unveiled limited awareness of cutting-edge AI technologies and concerns about AI's impact on employment opportunities. Nonetheless, students exhibited receptiveness to integrating AI for enhanced productivity and creativity. The structural equation modeling verified TAM's efficacy in forecasting students' AI acceptance intentions, highlighting perceived usefulness and ease of use as pivotal factors. The study's insights offer guidance for educational institutions to cultivate emerging technology competence among students, enabling them to excel in a design industry undergoing AI-driven transformations. The study's contribution lies in the application of TAM to evaluate AI acceptance within the distinct domain of interior design education.Este estudio explora las perspectivas de los estudiantes de arquitectura de interiores sobre las tecnologías de inteligencia artificial (IA) y sus implicaciones para las perspectivas futuras de carrera. Se realizó una encuesta a 230 estudiantes de tercer año de arquitectura de interiores en China, utilizando un cuestionario basado en el Modelo de Aceptación de Tecnología (TAM) que obtuvo 158 respuestas válidas. La investigación tuvo como objetivo evaluar la familiaridad de los estudiantes con los avances recientes en IA (por ejemplo, ChatGPT, Stable Diffusion, Midjourney) y su disposición para incorporar la IA en sus futuras carreras. Los resultados revelaron una conciencia limitada sobre las tecnologías de IA de vanguardia y preocupaciones sobre el impacto de la IA en las oportunidades laborales. Sin embargo, los estudiantes mostraron receptividad para integrar la IA con el fin de mejorar la productividad y la creatividad. El modelo de ecuaciones estructurales verificó la eficacia del TAM para predecir las intenciones de aceptación de la IA por parte de los estudiantes, resaltando la utilidad percibida y la facilidad de uso como factores cruciales. Las ideas obtenidas en el estudio ofrecen orientación a las instituciones educativas para cultivar la competencia en tecnologías emergentes entre los estudiantes, permitiéndoles sobresalir en una industria de diseño que está experimentando transformaciones impulsadas por la IA. La contribución del estudio radica en la aplicación del TAM para evaluar la aceptación de la IA en el ámbito específico de la educación en diseño de interiores

Direct tests of General Relativity under screening effect with galaxy-scale strong lensing systems

Observations of galaxy-scale strong gravitational lensing (SGL) systems have enabled unique tests of nonlinear departures from general relativity (GR) on the galactic and supergalactic scales. One of the most important cases of such tests is constraints on the gravitational slip between two scalar gravitational potentials. In this paper, we use a newly compiled sample of strong gravitational lenses to test the validity of GR, focusing on the screening effects on the apparent positions of lensed sources relative to the GR predictions. This is the first simultaneous measurement of the Post-Newtonian (PN) parameter ($\gamma_{PN}$) and the screening radius ($\Lambda$) without any assumptions about the contents of the Universe. Our results suggest that the measured PPN is marginally consistent with GR ($\gamma_{PN}=1$) with increasing screening radius ($\Lambda = 10-300$kpc), although the choice of lens models may have a significant influence on the final measurements. Based on a well-defined sample of 5000 simulated strong lenses from the forthcoming LSST, our methodology will provide a strong extragalactic test of GR with an accuracy of 0.5\%, assessed up to scales of $\Lambda \sim 300$ kpc. For the current and future observations of available SGL systems, there is no noticeable evidence indicating some specific cutoff scales on kpc-Mpc scales, beyond which new gravitational degrees of freedom are expressed.Comment: 14 pages, 9 figures, accepted for publication in Ap