Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Text

Generating natural human motion from a story has the potential to transform the landscape of animation, gaming, and film industries. A new and challenging task, Story-to-Motion, arises when characters are required to move to various locations and perform specific motions based on a long text description. This task demands a fusion of low-level control (trajectories) and high-level control (motion semantics). Previous works in character control and text-to-motion have addressed related aspects, yet a comprehensive solution remains elusive: character control methods do not handle text description, whereas text-to-motion methods lack position constraints and often produce unstable motions. In light of these limitations, we propose a novel system that generates controllable, infinitely long motions and trajectories aligned with the input text. (1) We leverage contemporary Large Language Models to act as a text-driven motion scheduler to extract a series of (text, position, duration) pairs from long text. (2) We develop a text-driven motion retrieval scheme that incorporates motion matching with motion semantic and trajectory constraints. (3) We design a progressive mask transformer that addresses common artifacts in the transition motion such as unnatural pose and foot sliding. Beyond its pioneering role as the first comprehensive solution for Story-to-Motion, our system undergoes evaluation across three distinct sub-tasks: trajectory following, temporal action composition, and motion blending, where it outperforms previous state-of-the-art motion synthesis methods across the board. Homepage: https://story2motion.github.io/.Comment: 8 pages, 6 figure

Eficácia da intervenção de enfermagem para aumento da esperança em pacientes com câncer: uma meta-análise

Objetivo: meta-análise para avaliar a eficácia da intervenção de enfermagem, no nível de esperança para pacientes com câncer. Método: foram pesquisados bancos de dados eletrônicos. Dois dos autores, de forma independente, extraíram os dados dos estudos elegíveis e os agruparam no software Stata 13.0. Resultado: nove ensaios clínicos randomizados foram incluídos e a qualidade metodológica destes estudos foi avaliada utilizando as recomendações do manual Cochrane. Um modelo de efeito aleatório foi usado para combinar resultados dos estudos elencados. O agrupamento dos resultados por meio de um modelo de efeitos fixos mostrou primeiros escores revelaram um efeito significativamente maior após o uso da intervenção de enfermagem entre os grupos. Foi identificada heterogeneidade entre os estudos para pós-teste (df = 8, p = 0.000; I2 =76.1 %). Os resultados indicaram heterogeneidade significativa nos nove estudos selecionados. O teste para heterogeneidade não demonstrou homogeneidade entre os estudos de acompanhamento (df = 8, p = 0.328; I2 = 12.9 %), mas sem significância estatística. Conclusão: as evidências atuais sugerem que a intervenção de enfermagem tem um efeito positivo no sentimento de esperança em pacientes com câncer. No entanto, são necessários mais ensaios controlados randomizados em maior escala e de alta qualidade para confirmar esses resultados.Objetivo: evaluar la eficacia de la intervención de enfermería para pacientes oncológicos en el nivel de esperanza en un meta análisis. Método: se buscó información en bases de datos electrónicas. Dos de los autores extrajeron de forma independiente los datos de los estudios de elegibilidad, y se utilizó el software Stata 13.0 para agrupar los datos. Resultados: se incluyeron nueve ensayos aleatorios controlados y se evaluó la calidad metodológica del ensayo controlado aleatorizado (ECA) utilizando las recomendaciones del manual Cochrane. Se utilizó un modelo de efectos aleatorios para combinar los resultados de los estudios elegibles. Los resultados agrupados utilizando el modelo de efectos fijos mostraron que las puntuaciones al primer efecto aumentan significativamente después del uso de la intervención de enfermería entre los grupos. Se observó heterogeneidad entre los estudios de post-prueba (df = 8, P = 0.000; I2 =76.1 %). Los resultados indicaron heterogeneidad significativa en los nueve estudios seleccionados. La prueba de heterogeneidad no mostró homogeneidad entre los estudios de seguimiento (df = 8, P = 0.328; I2 = 12.9 %), pero no hay significación estadística. Conclusión: la evidencia actual sugiere que la intervención de enfermería tiene un efecto positivo en la esperanza en pacientes con cáncer. Sin embargo, se necesitan más ensayos controlados aleatorios de gran escala y de alta calidad para confirmar estos resultados.Objective: to evaluate the efficacy of nursing interventions to increase the level of hope in cancer patients, in a meta-analysis. Methods: electronic databases were searched. Two of the authors independently extracted data from the eligible studies, and Stata 13.0 software was used to pool the data. Results: nine randomized controlled trials were included, and methodological quality of each randomized controlled trial (RCT) was evaluated using Cochrane handbook recommendations. A random effects model was used to combine results from eligible studies. The pooled results using the fixed effects model showed that scores to first effects increase significantly after the use of nursing intervention between the groups. Heterogeneity was observed among the studies for posttest (df = 8, P = 0.000; I2 =76.1 %). The results indicated significant heterogeneity across the nine selected studies. The test for heterogeneity showed no homogeneity among studies for follow-up (df = 8, P = 0.328; I2 = 12.9 %), and there was no statistical significance. Conclusion: the current evidence suggests that nursing intervention has a positive effect on hope in cancer patients. However, more large-scale and high-quality randomized controlled trials are needed to confirm these results

On the Security of Information Dissemination in the Internet-of-Vehicles

Internet of Vehicles (IoV) is regarded as an emerging paradigm for connected vehicles to exchange their information with other vehicles using vehicle-to-vehicle (V2V) communications by forming a vehicular ad hoc networks (VANETs), with roadside units using vehicle-to-roadside (V2R) communications. IoV offers several benefits such as road safety, traffic efficiency, and infotainment by forwarding up-to-date traffic information about upcoming traffic. For instance, IoV is regarded as a technology that could help reduce the number of deaths caused by road accidents, and reduce fuel costs and travel time on the road. Vehicles could rapidly learn about the road condition and promptly respond and notify drivers for making informed decisions. However, malicious users in IoV may mislead the whole communications and create chaos on the road. Data falsification attack is one of the main security issues in IoV where vehicles rely on information received from other peers/vehicles. In this paper, we present data falsification attack detection using hashes for enhancing network security and performance by adapting contention window size to forward accurate information to the neighboring vehicles in a timely manner (to improve throughput while reducing end-to-end delay). We also present clustering approach to reduce travel time in case of traffic congestion. Performance of the proposed approach is evaluated using numerical results obtained from simulations. We found that the proposed adaptive approach prevents IoV from data falsification attacks and provides higher throughput with lower delay