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"Liang, Jing"
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The application of artificial intelligence-assisted technology in cultural and creative product design
This study proposes a novel artificial intelligence (AI)-assisted design model that combines Variational Autoencoders (VAE) with reinforcement learning (RL) to enhance innovation and efficiency in cultural and creative product design. By introducing AI-driven decision support, the model streamlines the design workflow and significantly improves design quality. The study establishes a comprehensive framework and applies the model to four distinct design tasks, with extensive experiments validating its performance. Key factors, including creativity, cultural adaptability, and practical application, are evaluated through structured surveys and expert feedback. The results reveal that the VAE + RL model surpasses alternative approaches across multiple criteria. Highlights include a user satisfaction rate of 95%, a Structural Similarity Index (SSIM) score of 0.92, model accuracy of 93%, and a loss reduction to 0.07. These findings confirm the model’s superiority in generating high-quality designs and achieving high user satisfaction. Additionally, the model exhibits strong generalization capabilities and operational efficiency, offering valuable insights and data support for future advancements in cultural product design technology.
Journal Article
Bioactive hierarchical silk fibers created by bioinspired self-assembly
Artificial recapitulation of the hierarchy of natural protein fibers is crucial to providing strategies for developing advanced fibrous materials. However, it is challenging due to the complexity of the natural environment. Inspired by the liquid crystalline spinning of spiders, we report the development of natural silk-like hierarchical fibers, with bundles of nanofibrils aligned in their long-axis direction, by self-assembly of crystallized silk fibroin (SF) droplets. The formation of self-assembled SF fibers is a process of coalesced droplets sprouting to form a branched fibrous network, which is similar to the development of capillaries in our body. The as-assembled hierarchical SF fibers are highly bioactive and can significantly enhance the spreading and growth of human umbilical vein endothelial cells compared to the natural SF fibers. This work could help to understand the natural silk spinning process of spiders and provides a strategy for design and development of advanced fibrous biomaterials for various applications.
The creation of silk fibres using bioinspired approaches is of interest for biomaterials development. Here, the authors report on the creation of mimetic hierarchical silk fibres by the rotational self-assembly of silk fibroin droplets and demonstrate the creation of bioactive silk materials.
Journal Article
Mixed-Dimensional Assembly Strategy to Construct Reduced Graphene Oxide/Carbon Foams Heterostructures for Microwave Absorption, Anti-Corrosion and Thermal Insulation
HighlightsReduced graphene oxide/carbon foams (RGO/CFs) vdWs heterostructures are efficiently fabricated via a simple mixed-dimensional assembly strategy.Linkage effect of optimized impedance matching and enhanced dielectric loss abilities endows the excellent microwave absorption performances of RGO/CFs vdWs heterostructures.Multiple functions such as good corrosion resistance performances and outstanding thermal insulation capabilities can be integrated into RGO/CFs vdWs heterostructures.Considering the serious electromagnetic wave (EMW) pollution problems and complex application condition, there is a pressing need to amalgamate multiple functionalities within a single substance. However, the effective integration of diverse functions into designed EMW absorption materials still faces the huge challenges. Herein, reduced graphene oxide/carbon foams (RGO/CFs) with two-dimensional/three-dimensional (2D/3D) van der Waals (vdWs) heterostructures were meticulously engineered and synthesized utilizing an efficient methodology involving freeze-drying, immersing absorption, secondary freeze-drying, followed by carbonization treatment. Thanks to their excellent linkage effect of amplified dielectric loss and optimized impedance matching, the designed 2D/3D RGO/CFs vdWs heterostructures demonstrated commendable EMW absorption performances, achieving a broad absorption bandwidth of 6.2 GHz and a reflection loss of − 50.58 dB with the low matching thicknesses. Furthermore, the obtained 2D/3D RGO/CFs vdWs heterostructures also displayed the significant radar stealth properties, good corrosion resistance performances as well as outstanding thermal insulation capabilities, displaying the great potential in complex and variable environments. Accordingly, this work not only demonstrated a straightforward method for fabricating 2D/3D vdWs heterostructures, but also outlined a powerful mixed-dimensional assembly strategy for engineering multifunctional foams for electromagnetic protection, aerospace and other complex conditions.
Journal Article
Harmonizing minds and machines: survey on transformative power of machine learning in music
This survey explores the symbiotic relationship between Machine Learning (ML) and music, focusing on the transformative role of Artificial Intelligence (AI) in the musical sphere. Beginning with a historical contextualization of the intertwined trajectories of music and technology, the paper discusses the progressive use of ML in music analysis and creation. Emphasis is placed on present applications and future potential. A detailed examination of music information retrieval, automatic music transcription, music recommendation, and algorithmic composition presents state-of-the-art algorithms and their respective functionalities. The paper underscores recent advancements, including ML-assisted music production and emotion-driven music generation. The survey concludes with a prospective contemplation of future directions of ML within music, highlighting the ongoing growth, novel applications, and anticipation of deeper integration of ML across musical domains. This comprehensive study asserts the profound potential of ML to revolutionize the musical landscape and encourages further exploration and advancement in this emerging interdisciplinary field.
Journal Article
Dermoscopic image segmentation based on Pyramid Residual Attention Module
We propose a stacked convolutional neural network incorporating a novel and efficient pyramid residual attention (PRA) module for the task of automatic segmentation of dermoscopic images. Precise segmentation is a significant and challenging step for computer-aided diagnosis technology in skin lesion diagnosis and treatment. The proposed PRA has the following characteristics: First, we concentrate on three widely used modules in the PRA. The purpose of the pyramid structure is to extract the feature information of the lesion area at different scales, the residual means is aimed to ensure the efficiency of model training, and the attention mechanism is used to screen effective features maps. Thanks to the PRA, our network can still obtain precise boundary information that distinguishes healthy skin from diseased areas for the blurred lesion areas. Secondly, the proposed PRA can increase the segmentation ability of a single module for lesion regions through efficient stacking. The third, we incorporate the idea of encoder-decoder into the architecture of the overall network. Compared with the traditional networks, we divide the segmentation procedure into three levels and construct the pyramid residual attention network (PRAN). The shallow layer mainly processes spatial information, the middle layer refines both spatial and semantic information, and the deep layer intensively learns semantic information. The basic module of PRAN is PRA, which is enough to ensure the efficiency of the three-layer architecture network. We extensively evaluate our method on ISIC2017 and ISIC2018 datasets. The experimental results demonstrate that PRAN can obtain better segmentation performance comparable to state-of-the-art deep learning models under the same experiment environment conditions.
Journal Article
Comprehensive landscape and future perspectives of circular RNAs in colorectal cancer
Colorectal cancer (CRC) is a common hereditary tumor that is often fatal. Its pathogenesis involves multiple genes, including circular RNAs (circRNAs). Notably, circRNAs constitute a new class of noncoding RNAs (ncRNAs) with a covalently closed loop structure and have been characterized as stable, conserved molecules that are abundantly expressed in tissue/development-specific patterns in eukaryotes. Based on accumulating evidence, circRNAs are aberrantly expressed in CRC tissues, cells, exosomes, and blood from patients with CRC. Moreover, numerous circRNAs have been identified as either oncogenes or tumor suppressors that mediate tumorigenesis, metastasis and chemoradiation resistance in CRC. Although the regulatory mechanisms of circRNA biogenesis and functions remain fairly elusive, interesting results have been obtained in studies investigating CRC. In particular, the expression of circRNAs in CRC is comprehensively modulated by multiple factors, such as splicing factors, transcription factors, specific enzymes and cis-acting elements. More importantly, circRNAs exert pivotal effects on CRC through various mechanisms, including acting as miRNA sponges or decoys, interacting with RNA binding proteins, and even translating functional peptides. Finally, circRNAs may serve as promising diagnostic and prognostic biomarkers and potential therapeutic targets in the clinical practice of CRC. In this review, we discuss the dysregulation, functions and clinical significance of circRNAs in CRC and further discuss the molecular mechanisms by which circRNAs exert their functions and how their expression is regulated. Based on this review, we hope to reveal the functions of circRNAs in the initiation and progression of cancer and highlight the future perspectives on strategies targeting circRNAs in cancer research.
Journal Article
Effects of physical activity and exercise on the cognitive function of patients with Alzheimer disease: a meta-analysis
Background
Alzheimer’s disease (AD), as the most common cause of dementia, brings huge economic burden for patients and social health care systems, which motivates researchers to study multiple protective factors, among which physical activity and exercise have been proven to be both effective and economically feasible.
Methods
A systematic literature search was performed for eligible studies published up to November 1st 2018 on three international databases (PubMed, Cochrane Library, and Embase) and two Chinese databases (Wanfang Data, China National Knowledge Infrastructure). All analyses were conducted using Stata 14.0. Due to heterogeneity between studies, a random-effects model was used for this meta-analysis. Meta-analysis was used to explore if physical activity and exercise can exert positive effects on cognition of elderly with AD and subgroup analyses were conducted to find out if there are dose-response effects.
Results
A total of 13 randomized controlled trials were included with a sample size of 673 subjects diagnosed with AD. Intervention groups showed a statistically significant improvement in cognition of included subjects measured by the MMSE score (SMD = 1.12 CI:0.66~1.59) compared to the control groups. Subgroup analyses showed different amounts of physical activity and exercise can generate different effects.
Conclusions
As one of few meta-analyses comparing different quantities of physical activity and exercise interventions for AD in details, our study suggests that physical activity and exercise can improve cognition of older adults with AD. While the concomitant effects on cognition functions of high frequency interventions was not greater than that of low frequency interventions, the threshold remains to be settled. However, more RCTs with rigorous study design are needed to support our findings.
Journal Article
A phosphatidic acid-binding lncRNA SNHG9 facilitates LATS1 liquid–liquid phase separation to promote oncogenic YAP signaling
Long noncoding RNAs (lncRNAs) are emerging as a new class of important regulators of signal transduction in tissue homeostasis and cancer development. Liquid–liquid phase separation (LLPS) occurs in a wide range of biological processes, while its role in signal transduction remains largely undeciphered. In this study, we uncovered a lipid-associated lncRNA, small nucleolar RNA host gene 9 (
SNHG9
) as a tumor-promoting lncRNA driving liquid droplet formation of Large Tumor Suppressor Kinase 1 (LATS1) and inhibiting the Hippo pathway. Mechanistically,
SNHG9
and its associated phosphatidic acids (PA) interact with the C-terminal domain of LATS1, promoting LATS1 phase separation and inhibiting LATS1-mediated YAP phosphorylation. Loss of
SNHG9
suppresses xenograft breast tumor growth. Clinically, expression of
SNHG9
positively correlates with YAP activity and breast cancer progression. Taken together, our results uncover a novel regulatory role of a tumor-promoting lncRNA (i.e.,
SNHG9
) in signal transduction and cancer development by facilitating the LLPS of a signaling kinase (i.e., LATS1).
Journal Article
Progress in the Understanding and Applications of the Intrinsic Reactivity of Graphene‐Based Materials
Enhancing the intrinsic reactivity of graphene materials is essential for the development of low‐cost materials such as catalysts for various applications. Although an increasing understanding of the intrinsic reactivity of these materials is being achieved, the mechanisms of these materials for catalyzing various reactions have not been fully understood. It is believed that the intrinsic reactivity of pristine graphene originates from its edge and defect sites, and unpaired electrons (radicals) particularly of graphene oxide have also been demonstrated to contribute to the reactivity. Herein, the various edges and defects, and radicals, as well as their influences on the electron structure, reactivity, and applications of graphene‐based materials are reviewed and analyzed. Knowledge gaps in advancing the understanding of the structure–property–reactivity correlations of these materials are discussed. The intrinsic reactivity of graphene materials can be enhanced by engineering its edge, defects, and free radicals, which enables fabrication of low‐cost carbon‐based metal‐free and dopant‐free catalysts for various applications.
Journal Article