Predicting and compensating for small-sample thermal information data in precision machine tools: A spatial-temporal interactive integration network and digital twin system approach

Wu, Zheng; Ma, Chi; Zhang, Lang; Gui, Hongquan; Liu, Jialan; Liu, Zijie

doi:10.1016/j.asoc.2024.111760

Applied Soft Computing

2024

DOI: 10.1016/j.asoc.2024.111760

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Predicting and compensating for small-sample thermal information data in precision machine tools: A spatial-temporal interactive integration network and digital twin system approach

Zheng Wu,

Chi Ma,

Lang Zhang

et al.

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Cited by 22 publications

References 37 publications

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Semi‐Supervised Medical Image Segmentation Based on Feature Similarity and Multi‐Level Information Fusion Consistency

Long,

Liu,

Yang

2024

Int J Imaging Syst Tech

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Semantic segmentation is a key task in computer vision, with medical image segmentation as a prominent downstream application that has seen significant advancements in recent years. However, the challenge of requiring extensive annotations in medical image segmentation remains exceedingly difficult. In addressing this issue, semi‐supervised semantic segmentation has emerged as a new approach to mitigate annotation burdens. Nonetheless, existing methods in semi‐supervised medical image segmentation still face challenges in fully exploiting unlabeled data and efficiently integrating labeled and unlabeled data. Therefore, this paper proposes a novel network model—feature similarity multilevel information fusion network (FSMIFNet). First, the feature similarity module is introduced to harness deep feature similarity among unlabeled images, predicting true label constraints and guiding segmentation features with deep feature relationships. This approach fully exploits deep feature information from unlabeled data. Second, the multilevel information fusion framework integrates labeled and unlabeled data to enhance segmentation quality in unlabeled images, ensuring consistency between original and feature maps for comprehensive optimization of detail and global information. In the ACDC dataset, our method achieves an mDice of 0.684 with 5% labeled data, 0.873 with 10%, 0.884 with 20%, and 0.897 with 50%. Experimental results demonstrate the effectiveness of FSMIFNet in semi‐supervised semantic segmentation of medical images, outperforming existing methods on public benchmark datasets. The code and models are available at https://github.com/liujiayin12/FSMIFNet.git.

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Semi‐Supervised Medical Image Segmentation Based on Feature Similarity and Multi‐Level Information Fusion Consistency

Long,

Liu,

Yang

2024

Int J Imaging Syst Tech

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Recent Advances in Potential Biomedical Applications of MXene‐Based Hydrogels

Hamzehlouy,

Tavakoli Dare,

Shahi

et al. 2024

Polymers for Advanced Techs

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MXene‐based hydrogels represent a significant advancement in biomedical material science, leveraging the unique properties of 2D MXenes and the versatile functionality of hydrogels. This review discusses recent developments in the integration of MXenes into hydrogel matrices, focusing on their biomedical applications such as wound healing, drug delivery, antimicrobial activity, tissue engineering, and biosensing. MXenes, due to their remarkable electrical conductivity, mechanical robustness, and tunable surface chemistry, enhance the mechanical properties, conductivity, and responsiveness of hydrogels to environmental stimuli. Specifically, MXene‐based hydrogels have shown great promise in accelerating wound healing through photothermal effects, delivering drugs in a controlled manner, and serving as antibacterial agents. Their integration into hydrogels also enables applications in targeted cancer therapies, including photothermal and chemodynamic therapies, facilitated by their high conductivity and tunable properties. Despite the promising progress, challenges such as ensuring biocompatibility and optimizing the synthesis for large‐scale production remain. This review aims to provide a comprehensive overview of the current state of MXene‐based hydrogels in biomedical applications, highlighting the ongoing advancements and potential future directions for these multifunctional materials.

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Recent Advances in Multifunctional Naturally Derived Bioadhesives for Tissue Engineering and Wound Management

Jafari,

Al‐Ostaz,

Nouranian

2024

Polymers for Advanced Techs

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Recent advancements in naturally derived bioadhesives have transformed their application across diverse medical fields, including tissue engineering, wound management, and surgery. This review focuses on the innovative development and multifunctional nature of these bioadhesives, particularly emphasizing their role in enhancing adhesion performance in wet environments and optimizing mechanical properties for use in dynamic tissues. Key areas covered include the chemical and physical mechanisms of adhesion, the incorporation of multi‐adhesion strategies that combine covalent and non‐covalent bonding, and bioinspired designs mimicking natural adhesives such as those of barnacles and mussels. Additionally, the review discusses emerging applications of bioadhesives in the regeneration of musculoskeletal, cardiac, neural, and ocular tissues, highlighting the potential for bioadhesive‐based therapies in complex biological settings. Despite substantial progress, challenges such as scaling lab‐based innovations for clinical use and overcoming environmental and mechanical constraints remain critical. Ongoing research in bioadhesive technologies aims to bridge these gaps, promising significant improvements in medical adhesives tailored for diverse therapeutic needs.

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Predicting and compensating for small-sample thermal information data in precision machine tools: A spatial-temporal interactive integration network and digital twin system approach

Cited by 22 publications

References 37 publications

Semi‐Supervised Medical Image Segmentation Based on Feature Similarity and Multi‐Level Information Fusion Consistency

Semi‐Supervised Medical Image Segmentation Based on Feature Similarity and Multi‐Level Information Fusion Consistency

Recent Advances in Potential Biomedical Applications of MXene‐Based Hydrogels

Recent Advances in Multifunctional Naturally Derived Bioadhesives for Tissue Engineering and Wound Management

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