Can Deep Learning Approach Be Virtually Cultivated Via Social Learning Network

With the development of information technology especially kinds of social interaction techniques, social learning networks as a new platform have changed students’ learning behaviors and improve their learning performance. However, how this change happens especially how social learning networks change students’ learning approaches were not very clear. To address this gap, in this research, we try to investigate the impacts of social learning network on students’ learning approaches by conducting an experiment. In the experiment, students were randomly divided into two groups: control group and experimental group. We try to investigate the differences of students’ leaning behavior in terms of learning approaches in the two groups. We also present the theoretical, practical implications and future research

DiverseMotion: Towards Diverse Human Motion Generation via Discrete Diffusion

We present DiverseMotion, a new approach for synthesizing high-quality human motions conditioned on textual descriptions while preserving motion diversity.Despite the recent significant process in text-based human motion generation,existing methods often prioritize fitting training motions at the expense of action diversity. Consequently, striking a balance between motion quality and diversity remains an unresolved challenge. This problem is compounded by two key factors: 1) the lack of diversity in motion-caption pairs in existing benchmarks and 2) the unilateral and biased semantic understanding of the text prompt, focusing primarily on the verb component while neglecting the nuanced distinctions indicated by other words.In response to the first issue, we construct a large-scale Wild Motion-Caption dataset (WMC) to extend the restricted action boundary of existing well-annotated datasets, enabling the learning of diverse motions through a more extensive range of actions. To this end, a motion BLIP is trained upon a pretrained vision-language model, then we automatically generate diverse motion captions for the collected motion sequences. As a result, we finally build a dataset comprising 8,888 motions coupled with 141k text.To comprehensively understand the text command, we propose a Hierarchical Semantic Aggregation (HSA) module to capture the fine-grained semantics.Finally,we involve the above two designs into an effective Motion Discrete Diffusion (MDD) framework to strike a balance between motion quality and diversity. Extensive experiments on HumanML3D and KIT-ML show that our DiverseMotion achieves the state-of-the-art motion quality and competitive motion diversity. Dataset, code, and pretrained models will be released to reproduce all of our results.Comment: 12 pages, 7 figure

Effective electro-optic modulation in low-loss graphene-plasmonic slot waveguides

Surface plasmon polaritons enable light concentration within subwavelength regions, opening thereby new avenues for miniaturizing the device and strengthening light-matter interactions. Here we realize effective electro-optic modulation in low-loss plasmonic waveguides with the aid of graphene, and the devices are fully integrated in the silicon-on-insulator platform. By advantageously exploiting low-loss plasmonic slot-waveguide modes, which weakly leak into a substrate while feature strong fields within the two-layer-graphene covered slots in metal, we successfully achieve a tunability of 0.13 dB/um for our fabricated graphene-plasmonic waveguide devices with extremely low insertion loss, which outperforms previously reported graphene-plasmonic devices. Our results highlight the potential of graphene plasmonic leaky-mode hybrid waveguides to realized active ultra-compact devices for optoelectronic applications.Comment: revised version with 12 pages and 4 figure

HPV E6 induces eIF4E transcription to promote the proliferation and migration of cervical cancer

AbstractIncreasing evidence has placed eukaryotic translation initiation factor 4E (eIF4E) at the hub of tumor development and progression. Several studies have reported that eIF4E is over-expressed in cervical cancer; however, the mechanism remains elusive. The results of this study further confirm over-expression of eIF4E in cervical cancer tumors and cell lines, and we have discovered that the transcription of eIF4E is induced by protein E6 of the human papillomavirus (HPV). Moreover, regulation of eIF4E by E6 significantly influences cell proliferation, the cell cycle, migration, and apoptosis. Therefore, eIF4E emerges as a key player in tumor development and progression and a potential target for CC treatment and prevention

Effective electro-optical modulation with high extinction ratio by a graphene-silicon microring resonator

Graphene opens up for novel optoelectronic applications thanks to its high carrier mobility, ultra-large absorption bandwidth, and extremely fast material response. In particular, the opportunity to control optoelectronic properties through tuning of Fermi level enables electro-optical modulation, optical-optical switching, and other optoelectronics applications. However, achieving a high modulation depth remains a challenge because of the modest graphene-light interaction in the graphene-silicon devices, typically, utilizing only a monolayer or few layers of graphene. Here, we comprehensively study the interaction between graphene and a microring resonator, and its influence on the optical modulation depth. We demonstrate graphene-silicon microring devices showing a high modulation depth of 12.5 dB with a relatively low bias voltage of 8.8 V. On-off electro-optical switching with an extinction ratio of 3.8 dB is successfully demonstrated by applying a square-waveform with a 4 V peak-to-peak voltage.Comment: 12 pages, including 7 figure

Research progress on the STAT signaling pathway in pregnancy and pregnancy-associated disorders

Signal transducer and activator of transcription (STAT) proteins, pivotal regulators of signaling cascades, undergo activation in response to the stimulation of cytokines and growth factors, and participate in biological processes, including inflammation, immune responses, cell proliferation, and differentiation. During the process of pregnancy, STAT signaling is involved in regulating embryonic implantation, endometrial decidualization, and establishing and maintaining maternal-fetal immune tolerance. Increasing evidence suggests that aberrant STAT signaling contributes to the occurrence and development of pregnancy disorders, including repeated implantation failure (RIF), preeclampsia (PE), recurrent spontaneous abortion (RSA), preterm birth (PTB) and gestational diabetes mellitus (GDM). Elucidating the molecular mechanisms of the STAT signaling pathway holds promise for further understanding the establishment and maintenance of normal pregnancy, and thereby providing potent targets and strategic avenues for the prevention and management of ailments associated with pregnancy. In this review, we summarized the roles of the STAT signaling pathway and its related regulatory function in embryonic implantation, endometrial decidualization, and maternal-fetal immune tolerance. In conclusion, in-depth research on the mechanism of the STAT signaling pathway not only enhances our understanding of normal pregnancy processes but also offers STAT-based therapeutic approaches to protect women from the burden of pregnancy-related disorders