The manipulation of articulated objects for part-level motion is crucial due to their prevalence in real-world applications. Although current manipulation methods have improved interaction quality, they share a common issue: neglecting the completeness of motion trajectories. For example, when we use a front-loading drum washing machine, the expected action is to manipulate the door from fully closed to fully open. However, these methods might only result in it being half-open. To tackle this limitation, we introduce a novel framework for optimizing motion trajectories based on multimodal fusion. Specifically, we explicitly model trajectory completeness and propose a motion trajectory construction paradigm (MTCP). This paradigm is applied to a large-scale dataset containing a wide range of articulated objects, generating high-quality motion trajectories for multimodal fusion. Furthermore, to handle trajectory homogeneity, we propose a trajectory enhancement policy (TEP) that enriches the trajectory set by capturing the multimodal distribution of feasible trajectories. Subsequently, to enhance the learning efficiency and task adaptability of Multimodal Large Language Models (MLLMs), we propose a learning strategy for 3D perception inspired by 2D perception (3PI2P), complemented by a progressive reasoning approach. This strategy integrates a dual-branch input design using RGB images and depth maps, combined with six forms of visual question answering tasks, to achieve collaborative reasoning and deep fusion of 2D semantics and 3D geometric information. The robustness and generalizability of the framework are demonstrated through evaluations in both simulation and real-world environments.
Glenoid reconstruction strategy is a critical determinant of biomechanics, implant fixation, and clinical outcomes in reverse shoulder arthroplasty (RSA). While standard reconstruction remains widely used, biological increased offset (BIO-RSA) and metal-based modified increased offset (MIO-RSA) techniques have been increasingly adopted to address glenoid bone loss and medialization. However, comparative clinical evidence among these contemporary strategies remains inconsistent. This meta-analysis provides the most comprehensive comparative evaluation to date of standard RSA, BIO-RSA, and MIO-RSA in primary RSA. A systematic search of four electronic databases identified randomized controlled trials and comparative observational studies evaluating glenoid reconstruction strategies in primary RSA. Eighteen studies encompassing approximately 3000 shoulders were included. Pairwise comparisons were performed between BIO-RSA versus standard RSA, MIO-RSA versus standard RSA, and BIO-RSA versus MIO-RSA. Outcomes included functional scores, patient-reported outcome measures, range of motion, pain, radiographic findings, postoperative complications, and revision surgery. Pooled analyses were conducted using fixed- or random-effects models according to heterogeneity. Functional outcomes demonstrated selective differences across reconstruction strategies. BIO-RSA achieved higher Constant–Murley scores compared with standard RSA (MD + 3.94, p = 0.005) and MIO-RSA (MD + 9.47, p = 0.03), as well as greater improvement in Subjective Shoulder Value versus MIO-RSA (MD + 5.88, p = 0.02). MIO-RSA was associated with higher UCLA scores (MD + 1.01, p = 0.04) and lower SPADI scores (MD − 3.48, p = 0.006) compared with standard RSA. Objective range-of-motion outcomes were largely equivalent across techniques, with the exception of greater external rotation following BIO-RSA versus standard RSA (MD + 4.64°, p = 0.03). Pain outcomes did not differ significantly between groups. Radiographically, BIO-RSA demonstrated a lower risk of scapular notching compared with standard RSA (RR 0.60, p = 0.004), while implant loosening rates were similar across techniques. Overall complication rates were comparable; however, revision surgery occurred less frequently with MIO-RSA compared with standard RSA (RR 0.31, p = 0.003). Standard, biological, and metal-augmented glenoid reconstruction strategies in RSA demonstrate broadly comparable safety and functional performance, with selective, outcome-specific advantages rather than global superiority. BIO-RSA offers benefits in rotational function, functional improvement, and scapular notching reduction, whereas MIO-RSA provides advantages in selected patient-reported outcomes and revision risk. These findings support an individualized, anatomy-driven approach to glenoid reconstruction selection in contemporary reverse shoulder arthroplasty.
This paper examines how Chinese secondary and tertiary English as a second language (ESL) learners engage with generative AI (GenAI) tools, such as ChatGPT, Claude, Doubao, and Pigai, not merely as writing aids but as coauthors in the academic writing process. Against the backdrop of an assessment-centered education system that emphasizes memorization and structured learning, GenAI opens new possibilities for dialogic learning and critical thinking. Drawing on case studies and current research, this paper examines how prompt engineering, both as a technical and pedagogical skill, supports digital literacy, rhetorical awareness, and metacognition. It further investigates how GenAI scaffolds language production and supports student agency, while also presenting risks such as epistemic dependency, reduced critical thinking, and ethical ambiguity. The concept of Human–AI co-learning is advanced as a theoretical framework for understanding this interaction. The paper concludes by calling for critical AI literacy, educator mediation, and culturally responsive pedagogy that reconciles traditional Chinese learning practices with reflective engagement in digital environments. By reframing GenAI from a shortcut to a scaffold, this study proposes a pedagogical model that empowers learners to reclaim authorship and engage more deeply in academic inquiry.
Multivariate time series forecasting is critical in domains such as energy management, traffic prediction, and weather monitoring. Existing Transformer-based approaches face a trade-off between efficiently modeling inter-variable dependencies and adaptively capturing diverse temporal patterns. To address this, we propose a Dynamic Ring-Star Transformer (DRSFormer), a structure-driven Transformer that represents each variable as a node in a virtual topology and combines sparse local routing with multi-center global fusion. The architecture jointly models inter-variable dependencies by combining sparse local interactions with global semantic fusion, while capturing diverse temporal dynamics through adaptive multi-scale temporal modeling. Extensive experiments are conducted on multiple public benchmarks, including ETT, Weather, ECL, Traffic, Exchange, and PEMS. The results demonstrate that DRSFormer achieves robust and competitive performance. On PEMS04, it attains a mean squared error (MSE) of 0.089, representing a 19.8
Chinese student mobilities within Asia have expanded significantly amid the Belt and Road Initiative (BRI) and shifting geopolitical conditions. This paper examines Chinese youth studying in two prominent Southeast Asian destinations—Thailand and Singapore—to understand how their aspirations intersect with macro-structural forces to shape differentiated mobility pathways. Drawing on interviews with 59 participants, we explore three interrelated themes: (1) how geopolitical and geoeconomic developments reconfigure opportunity structures for Chinese youth; (2) how students navigate enduring hierarchies within the regional and global landscapes of higher education; and (3) how transregional education spaces reshape future-making projects under conditions of heightened uncertainty. Our findings reveal that in Thailand, the BRI has widened access to regional education-migration opportunities for Chinese youth by expanding institutional linkages and legitimising alternative mobility routes. In contrast, Chinese students in Singapore rarely frame their educational choices through the BRI, instead mobilising other forms of capital within established hierarchies of international education. Despite the emergence of diversified intra-Asian pathways beyond traditional Western destinations, students' aspirations remain structured by stratified geographies of higher education and calibrated to broader geopolitical dynamics. By foregrounding the interplay between macro-structural forces and individual mobility projects, this paper highlights how diversified yet hierarchical aspirational pathways are forged within an evolving transregional educational landscape.
