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Two-dimensional transition metal chalcogenide nanomaterials for cancer diagnosis and treatment

Chinese Chemical Letters 2022年第10期33卷 4437-4448页

作者： Jingjing Wu Tingting Hu Guoping Zhao Anran Li Ruizheng Liang State Key Laboratory of Chemical Resource Engineering Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing 100029China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Engineering MedicineBeihang UniversityBeijing 100191China Department of Orthopedics Guilin People's HospitalGuilin 541002China

For more than a decade,the exfoliation of graphene and other layered materials has led to a tremendous amount of research in two-dimensional(2D)materials,among which 2D transition metal chalcogenides(TMCs)nanomaterials have attracted much attention in a wide range of applications including photoelectric devices,lithium-ion batteries,catalysis,and energy conversion and storage owing to their unique photoelectric physical *** such large specific surface area,strong near-infrared(NIR)absorption and abundant chemical element composition,2D TMCs nanomaterials have become good candidates in biomedical imaging and cancer *** review systematically summarizes recent progress on 2D TMCs nanomaterials,which includes their synthesis methods and applications in cancer *** the end of this review,we also highlight the future prospects and challenges of 2D TMCs *** is expected that this work can provide the readers with a detailed overview of the synthesis of 2D TMCs and inspire more novel functional biomaterials based on 2D TMCs for cancer treatment in the future.

关键词： Two-dimensional(2D)nanomaterials Transition metal chalcogenides(TMCs) Synthesis method Biomedical imaging Cancer treatment

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The Master-Slave Encoder Model for Improving Patent Text Summarization: A New Approach to Combining Specifications and Claims

arXiv

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arXiv 2024年

作者： Zhou, Shu Wang, Xin Zhou, Zhengda Yi, Haohan Zheng, Xuhui Wang, Hao School of Information Management Nanjing University China Key Laboratory of Data Engineering and Knowledge Services in Jiangsu Provincial Universities Nanjing University China Baidu Inc. Beijing China

In order to solve the problem of insufficient generation quality caused by traditional patent text abstract generation models only originating from patent specifications, the problem of new terminology OOV caused by rapid patent updates, and the problem of information redundancy caused by insufficient consideration of the high professionalism, accuracy, and uniqueness of patent texts, we proposes a patent text abstract generation model (MSEA) based on a master-slave encoder architecture;Firstly, the MSEA model designs a master-slave encoder, which combines the instructions in the patent text with the claims as input, and fully explores the characteristics and details between the two through the master-slave encoder;Then, the model enhances the consideration of new technical terms in the input sequence based on the pointer network, and further enhances the correlation with the input text by re weighing the "remembered" and "for-gotten" parts of the input sequence from the encoder;Finally, an enhanced repetition suppression mechanism for patent text was introduced to ensure accurate and non redundant abstracts generated. On a publicly available patent text dataset, compared to the state-of-the-art model, Improved Multi-Head Attention Mechanism (IMHAM), the MSEA model achieves an improvement of 0.006, 0.005, and 0.005 in Rouge-1, Rouge-2, and Rouge-L scores, respectively. MSEA leverages the characteristics of patent texts to effectively enhance the quality of patent text generation, demonstrating its advancement and effectiveness in the experiments. Copyright © 2024, The Authors. All rights reserved.

关键词： Specifications

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Microbiologically Influenced Corrosion Behavior of Fe_(40)(CoCrMnNi)_(60) and Fe_(60)(CoCrMnNi)_(40) Medium Entropy Alloys in the Presence of Pseudomonas Aeruginosa

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Acta Metallurgica Sinica(English Letters) 2023年第3期36卷 379-390页

作者： Weiwei Chang Yangyang Li Huaibei Zheng Hongchang Qian Dawei Guo Shuyuan Zhang Yuntian Lou Chi Tat Kwok Lap Mou Tam Dawei Zhang National Materials Corrosion and Protection Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Graduate School of University of Science and Technology BeijingFoshan 528399China State Key Laboratory of Metal Material for Marine Equipment and Application Anshan 114002China Department of Electromechanical Engineering University of MacaoMacao 999078China Institute for the Development and Quality Macao 999078China

In this work,the microbiologically influenced corrosion(MIC)of Fe_(40)(CoCrMnNi)_(60) and Fe_(60)(CoCrMnNi)_(40) medium entropy alloys(MEAs)induced by Pseudomonas aeruginosa(***)was *** behaviors during 14 days of immersion in sterile and ***-inoculated culture media are *** sterile conditions,both MEAs exhibited good corrosion resistance against the culture medium *** the presence of ***,the pitting corrosion of MEAs was *** results of inductively coupled plasma‒mass spectrometry(ICP‒MS)and potentiodynamic polarization tests showed that the presence of *** promoted the selective dissolution of passive film and accelerated the corrosion of *** results of X-ray photoelectron spectroscopy(XPS)and Mott-Schottky measurements further demonstrated the degradation effect of *** on the passive *** with Fe_(60)(CoCrMnNi)_(40),Fe_(40)(CoCrMnNi)_(60) manifested better resistance to the MIC caused by ***,which may be attributed to more Cr oxides and fewer Fe oxides of the passive film.

关键词： Microbiologically influenced corrosion Medium entropy alloys Pseudomonas aeruginosa

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Any-Angle Routing Algorithm for Microfluidic Biochips Driven by Flow Path

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2025年第4期62卷 978-988页

作者： Youlin, Pan Shuai, Guo Xing, Huang Genggeng, Liu College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Fuzhou University Ministry of Education Fuzhou350116 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China School of Computer Science Northwestern Polytechnical University Xi’an710072 China

Continuous-flow microfluidic biochips (CFMBs) have become a hot research topic in recent years due to their ability to perform biochemical assays automatically and efficiently. For the first time, PathDriver+ takes the requirements of the actual fluid transportation into account in the design process of CFMBs and implements the actual fluid transport and removal, and plans separate flow paths for each transport task, which have been neglected in previous work. However, PathDriver+ does not take full advantage of the flexibility of CFMBs routing because it only considers the optimization of flow channel length for the global routing in the mesh model, except for the detailed routing. In addition, PathDriver+ only considers the X architecture, while the existing work shows that the any-angle routing can utilize the routing resources more efficiently and shorten the flow channel length. To address the above issues, we propose a flow path-driven arbitrary angle routing algorithm, which can improve the utilization of routing resources and reduce the flow channel length while considering the actual fluid transportation requirements. The proposed algorithm constructs a search graph based on constrained Delaunay triangulation to improve the search efficiency of routing solutions while ensuring the routing quality. Then, a Dijkstra-based flow path routing method is used on the constructed search graph to generate a routing result with a short channel length quickly. In addition, in the routing process, channel reuse strategy and intersection optimization strategy are proposed for the flow path reuse and intersection number optimization problems, respectively, to further improve the quality of routing results. The experimental results show that compared with the latest work PathDriver+, the length of channels, the number of ports used, and the number of channel intersections are significantly reduced by 33.21%, 11.04%, and 44.79%, respectively, and the channel reuse rate is i

关键词： High level synthesis

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DMAM-ECG: A Diffusion Model with Self-Attention Module for ECG Signal Denoising

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第3期9卷 1278-1296页

作者： Hu, Zheng-Dong Hong, Yang Huang, Jia-Yan Chen, Kai-Hong Zhao, Wan-Qi Grau, Antoni Guerra, Edmundo Wang, Chuan-Sheng Zhang, Fu-Quan New Engineering Industry College Putian University Putian351100 China School of Mathematics and Data Science Minjiang University Fuzhou350108 China The University of Sheffield SheffieldS10 2TN United Kingdom Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona08034 Spain Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China

Electrocardiogram (ECG) is the most common and non-invasive auxiliary diagnostic technique for heart disease. However, the ECG signal is susceptible to various noises during the collection process, which will impact subsequent analysis and diagnosis. Therefore, ECG signal denoising has become the primary task after signal acquisition. ECG signal denoising aims to remove noise interference from the collected noisy signals for clarify abnormal waveforms in it, and thus diagnose diseases more accurately. In this paper, to obtain high-quality and high-fidelity denoised ECG signals, we propose a novel diffusion model with self-attention module for ECG signal denoising (DMAM-ECG). Specifically, the DMAM-ECG contains two main branches used to extract features of input noise signal observations and potential variables, respectively. Each branch consists of 6 designed Convolution-Instancenormal-LeakyReLU Filter Blocks (CIL-Filter Blocks). Meanwhile, DMAM-ECG introduces the self-Attention Module Fusion Blocks (SAM-Fusion Blocks) to further extract features for the first branch, and then fuse the output features with the second branch. Besides, we use a multi-shot reconstruction strategy to further improve signal denoising. Quantitative and qualitative results on the QT database show that the proposed DMAM-ECG performs better than the existing 5 state-of-the-art ECG signal denoising methods, especially for strong noise interference ECG signal removal. To sum up, our DMAM-ECG introduces self-attention module into the diffusion model to improve the grasp of global information and achieve high-quality information preservation for extremely noise removal of ECG signal. In particular, it uses only 3-shot reconstruction gets much better denoised results than that of the best baseline with 10-shot. The code of the proposed DMAM-ECG is available at https://***/luvletterh/DMAM-ECG. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Signal denoising

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CLOE: Novelty Detection via Contrastive Learning with Outlier Exposure 1

引用

16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Liu, Tianyang Liang, Quan Yang, Hua Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China School of Mechanical Science and Engineering State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

Novelty detection (ND) methods seek to identify anomalies within a specific dataset. Although self-supervised representation learning is commonly used in such applications, inadequate training data may reduce the effectiveness of these methods. It is thus reasonable to use external data to improve these performances. Here, we propose a simple and effective network, CLOE, for image-based novelty detection. Our method includes a pretrained ViT model as a feature extractor and employs the contrastive learning technique to train the dataset with external data. We compare the performance of two types of extra training settings: (1) The augmented data of the original dataset. (2) The fake images obtained from generative models. The demonstrated approach achieves a new state-of-the-art performance in novelty detection, as evidenced by achieving an ROC-AUC of 99.72% on the CIFAR-10 dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Statistics

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Development of stimuli responsive polymeric nanomedicines modulating tumor microenvironment for improved cancer therapy

引用

Medical Review 2023年第1期3卷 4-30页

作者： Yuanzhen Su Guanyu Jin Huicong Zhou Zhaofan Yang Lanqing Wang Zi Mei Qionghua Jin Shixian Lv Xuesi Chen Key Laboratory of Polymer Ecomaterials Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchunChina School of Materials Science and Engineering Peking UniversityBeijingChina School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefeiAnhui ProvinceChina Department of Chemistry Capital Normal UniversityBeijingChina School of Materials Science and Engineering Peking UniversityNo.5 Yiheyuan RoadBeijing 100871China Key Laboratory of Polymer Ecomaterials Changchun Institute of Applied ChemistryChinese Academy of Sciences5625 Renmin StreetChangchun 130022China School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefei 230026Anhui ProvinceChina

The complexity of the tumor microenvironment(TME)severely hinders the therapeutic effects of various cancer treatment *** TME differs from normal tissues owing to the presence of hypoxia,lowpH,and immunesuppressive *** of the TME to reverse tumor growth equilibrium is considered an effective way to treat ***,polymeric nanomedicines have been widely used in cancer therapy,because their synthesis can be controlled and they are highly modifiable,and have demonstrated great potential to remodel the *** this review,we outline the application of various stimuli responsive polymeric nanomedicines to modulate the TME,aiming to provide insights for the design of the next generation of polymeric nanomedicines and promote the development of polymeric nanomedicines for cancer therapy.

关键词： cancer therapy polymeric nanomedicines stimuli responsive tumor microenvironment

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Real-Time Proportional-Integral-Derivative(PID)Tuning Based on Back Propagation(BP)Neural Network for Intelligent Vehicle Motion Control

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Computers, Materials & Continua 2025年第5期83卷 2375-2401页

作者： Liang Zhou Qiyao Hu Xianlin Peng Qianlong Liu School of Information Science and Technology Northwest UniversityXi’an710127China State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services Northwest UniversityXi’an710127China Generative Artificial Intelligence and Mixed Reality Key Laboratory of Higher Education Institutions in Shaanxi Province Xi’an710127China Shaanxi Silk Road Cultural Heritage Digital Protection and Inheritance Collaborative Innovation Center Xi’an710127China School of Art Northwest UniversityXi’an710127China Network and Data Center Northwest UniversityXi’an710127China

Over 1.3 million people die annually in traffic accidents,and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control *** modern industrial and technological applications and collaborative edge intelligence,control systems are crucial for ensuring efficiency and ***,deficiencies in these systems can lead to significant operational *** paper uses edge intelligence to address the challenges of achieving target speeds and improving efficiency in vehicle control,particularly the limitations of traditional Proportional-Integral-Derivative(PID)controllers inmanaging nonlinear and time-varying dynamics,such as varying road conditions and vehicle behavior,which often result in substantial discrepancies between desired and actual speeds,as well as inefficiencies due to manual parameter *** paper uses edge intelligence to propose a novel PID control algorithm that integrates Backpropagation(BP)neural networks to enhance robustness and *** BP neural network is first trained to capture the nonlinear dynamic characteristics of the *** network is then combined with the PID controller to forma hybrid control *** output layer of the neural network directly adjusts the PIDparameters(k_(p),k_(i),k_(d)),optimizing performance for specific driving scenarios through self-learning and weight *** experiments demonstrate that our BP neural network-based PID design significantly outperforms traditional methods,with the response time for acceleration from 0 to 1 m/s improved from 0.25 s to just 0.065 ***,real-world tests on an intelligent vehicle show its ability to make timely adjustments in response to complex road conditions,ensuring consistent speed maintenance and enhancing overall system performance.

关键词： PID control backpropagation neural network hybrid control nonlinear dynamic processes edge intelligence

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Intelligent Aquaculture Water Quality Detection Scheme Based on TurMass Technology 8

Intelligent Aquaculture Water Quality Detection Scheme Based...

引用

8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Zhang, Yafang Huang, Yongxin Chen, Hongming Zhejiang Ocean University School of Information Engineering Zhoushan316022 China Zhejiang Ocean University Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhoushan316022 China Nankai University College of Electronics Information and Optical Engineering Tianjin300350 China

ISBN: (纸本)9798350302455

To address the shortcomings of wireless data transmission in aquaculture water quality monitoring, we have developed an intelligent water quality detection device based on the STM32 microcontroller system as the processing unit and TurMass transmission technology. This device can detect water quality in real-time and transmit the data to the user end for real-time monitoring so that users can monitor water quality in real-time. Through rigorous and systematic experimental measurements, the accuracy of the detected data by the device was found to be extremely high, indicating that it can be used in practical applications. © 2023 IEEE.

关键词： Water quality

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Control Logic Routing for Continuous-Flow Microfluidic Biochips Based on Deep Reinforcement Learning

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2025年第4期62卷 950-962页

作者： Cai, Huayang Huang, Xing Liu, Genggeng College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Fuzhou University Ministry of Education Fuzhou350116 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China School of Computer Science Northwestern Polytechnical University Xi’an710072 China

With the advancement of electronic design automation, continuous-flow microfluidic biochips have become one of the most promising platforms for biochemical experiments. This chip manipulates fluid samples in milliliters or nanoliters by utilizing internal microvalves and microchannels, and thus automatically performs basic biochemical experiments, such as mixing and detection. To achieve the correct bioassay function, the microvalves deployed inside the chip are usually managed by a multiplexer-based control logic, and valves receive control signals from a core input through the control channel for accurate switching. Since biochemical reactions typically require high sensitivity, the length of control paths connecting each valve needs to be reduced to ensure immediate signal propagation, and thus to reduce the signal propagation delay. In addition, to reduce the fabrication cost of chips, a vital issue to be addressed in the logic architecture design is how to effectively reduce the total channel length within the control logic. To address the above issues, we propose a deep reinforcement learning-based control logic routing algorithm to minimize the signal propagation delay and total control channel length, thereby automatically constructing an efficient control channel network. The algorithm employs the dueling deep Q-network architecture as the agent of the deep reinforcement learning framework to evaluate the tradeoff between signal propagation delay and total channel length. Besides, the diagonal channel routing is implemented for the first time for control logic, thus fundamentally improving the efficiency of valve switching operations and reducing the fabrication cost of the chip. The experimental results demonstrate that the proposed algorithm can effectively construct a high-performance and low-cost control logic architecture. © 2025 Science Press. All rights reserved.

关键词： Deep reinforcement learning

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