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Multifunctional silicene/CeO_(2)heterojunctions:Desirable electronic material and promising water-splitting photocatalyst

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Chinese Chemical Letters 2022年第8期33卷 3947-3950页

作者： Liang Xu Jian Zeng Quan Li Xin Luo Tong Chen Jingjing Liu Ling-Ling Wang Energy Materials Computing Center School of Energy and Mechanical EngineeringJiangxi University of Science and TechnologyNanchang 330013China Department of Applied Physics School of ScienceEast China Jiaotong UniversityNanchang 330013China Key Laboratory for Micro-Nano Optoelectronic Devices of Ministry of Education School of Physics and ElectronicsHunan UniversityChangsha 410082China

The first-principles calculations demonstrate that covalently bonded(cb)heterojunction and van der Waals(vd W)heterojunction can coexist in silicene/CeO_(2) heterojunctions,due to the different stacking ***,the cb heterojunction with band gap of 1.97 e V,forms a type-II heterojunction,exhibits good redox performance and has high-effective optical absorption spectra,thus it is a promising photocatalyst for overall water ***,for the vd W heterojunction,the Dirac cone of silicene is well kept on CeO_(2) semiconducting substrate,with a considerable energy gap of 0.43 e V,which can be an ideal material in building silicene-based electronic *** results may open a new gateway in both of nanoelectronic device and energy conversion for silicene/Ce O2 nanocomposites.

关键词： Silicene CeO_(2) Photocatalyst Interfacial interaction Dirac cone

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MEFA-Net: A mask enhanced feature aggregation network for polyp segmentation

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Computers in Biology and Medicine 2025年 186卷 109601-109601页

作者： Ke, Xiao Chen, Guanhong Liu, Hao Guo, Wenzhong Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350116 China

Accurate polyp segmentation is crucial for early diagnosis and treatment of colorectal cancer. This is a challenging task for three main reasons: (i) the problem of model overfitting and weak generalization due to the multi-center distribution of data;(ii) the problem of interclass ambiguity caused by motion blur and overexposure to endoscopic light;and (iii) the problem of intraclass inconsistency caused by the variety of morphologies and sizes of the same type of polyps. To address these challenges, we propose a new high-precision polyp segmentation framework, MEFA-Net, which consists of three modules, including the plug-and-play Mask Enhancement Module (MEG), Separable Path Attention Enhancement Module (SPAE), and Dynamic Global Attention Pool Module (DGAP). Specifically, firstly, the MEG module regionally masks the high-energy regions of the environment and polyps through a mask, which guides the model to rely on only a small amount of information to distinguish between polyps and background features, avoiding the model from overfitting the environmental information, and improving the robustness of the model. At the same time, this module can effectively counteract the "dark corner phenomenon" in the dataset and further improve the generalization performance of the model. Next, the SPAE module can effectively alleviate the inter-class fuzzy problem by strengthening the feature expression. Then, the DGAP module solves the intra-class inconsistency problem by extracting the invariance of scale, shape and position. Finally, we propose a new evaluation metric, MultiColoScore, for comprehensively evaluating the segmentation performance of the model on five datasets with different domains. We evaluated the new method quantitatively and qualitatively on five datasets using four metrics. Experimental results show that MEFA-Net significantly improves the accuracy of polyp segmentation and outperforms current state-of-the-art algorithms. Code posted on https://***/

关键词： Endoscopy

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An Advantage-based Optimization Method for Reinforcement Learning in Large Action Space

arXiv

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arXiv 2024年

作者： Lin, Hai Huang, Cheng Chen, Zhihong Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education Hubei Wuhan430072 China School of Cyber Science and Engineering Wuhan University Hubei Wuhan430072 China

Reinforcement learning tasks in real-world scenarios often involve large, high-dimensional action spaces, leading to challenges such as convergence difficulties, instability, and high computational complexity. It is widely acknowledged that traditional value-based reinforcement learning algorithms struggle to address these issues effectively. A prevalent approach involves generating independent sub-actions within each dimension of the action space. However, this method introduces bias, hindering the learning of optimal policies. In this paper, we propose an advantage-based optimization method and an algorithm named Advantage Branching Dueling Q-network (ABQ). ABQ incorporates a baseline mechanism to tune the action value of each dimension, leveraging the advantage relationship across different sub-actions. With this approach, the learned policy can be optimized for each dimension. Empirical results demonstrate that ABQ outperforms BDQ, achieving 3%, 171%, and 84% more cumulative rewards in HalfCheetah, Ant, and Humanoid environments, respectively. Furthermore, ABQ exhibits competitive performance when compared against two continuous action benchmark algorithms, DDPG and TD3. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization algorithms

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Intermodal interference based refractive index sensor employing elliptical core photonic crystal fiber

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Optoelectronics Letters 2021年第5期17卷 271-275页

作者： WU Xu-jie SONG Bin-bin WU Ji-xuan HUANG Wei The Key Laboratory of Computer Vision and System of Ministry of Education Tianjin Key Laboratory of Intelligence Computing and Novel Software TechnologyTianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems College of Electronic and Information EngineeringTiangong UniversityTianjin 300387China

A refractive index(RI)sensor based on elliptical core photonic crystal fiber(EC-PCF)has been *** asymmetric elliptical core introduces the polarization-dependent characteristics of the fiber core *** performances of intermodal interference between the intrinsic polarization fiber core modes are investigated by contrast in two interferometers based on the Mach-Zehnder(M-Z)and Sagnac interference *** addition,the RI sensing characteristics of the two interferometers are studied by successively filling the three layers air holes closest to the elliptical core in the *** results show that the M-Z interference between LP_(01)and LP_(11)mode in the same polarized direction is featured with the incremental RI sensing sensitivity as the decreasing interference length,and the infilled scope around the elliptical core has a weak correlation with the RI sensing *** to the high birefringence of LP11 mode,the Sagnac interferometer has better RI sensing performance,the maximum RI sensing sensitivity of 12000 nm/RIU is achieved under the innermost one layer air holes infilled with RI matching liquid of RI=1.39 at the pre-setting EC-PCF length of 12 cm,which is two orders of magnitude higher than the M-Z interferometer with the same fiber *** series of theoretical optimized analysis would provide guidance for the applications in the field of biochemical sensing.

关键词： Sagnac PCF Intermodal interference based refractive index sensor employing elliptical core photonic crystal fiber

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The Leakage Assessment Based on the Discrete Fréchet Distance Similarity

SSRN

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SSRN 2024年

作者： Wang, Yaru Tang, Ming School of Cyber Science and Engineering Wuhan University Wuhan430072 China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education Wuhan University Wuhan430072 China

Test Vector Leakage Assessment (TVLA) is a widely used side channel leakage detection method. TVLA is used to perform the leakage detection on each power sequence of trace obtained from the AES algorithm. We used the correlation-test to investigate the relationship between the power sequences and found that there is a correlation. While the correlation information between the power sequences is not considered in TVLA. We performed both the independent T-test and the correlated sample T-test on two correlated sequences to investigate the effect of the correlation on the detection results and found that ignoring the correlation information may be a risk of missed detection. Based on this, we added a correlation-test to the detection process to find a few nearby correlated power sequences and form a feature segment. And we propose a leakage assessment based on the discrete Fréchet distance similarity (referred to as Fréchet test) to determine the existence of leakage by comparing the similarity between the feature trace segments of the fixed plaintexts and the random plaintexts. If two feature trace segments are dissimilar, there is the side channel leakage in the feature segment. To verify the effectiveness and superiority of the Fréchet test, we used both the Fréchet test and TVLA to detect the leakage feature segments and used the minimum sample size as an indicator to demonstrate the superiority of Fréchet test. The experiment results indicate that the Fréchet test successfully detects the leakage within the feature segments of DPA-contest-V2 or CDPA-SCA, when the minimum sample size is approximatelyor . In contrast, the T-test requires a sample size of approximately or . Compared to TVLA, the Fréchet test can detect the side channel leakage with a smaller sample size. The Fréchet test can apply the correlation information between the power sequence to the leakage detection, and can be proposed as a complement to TVLA to improve the leakage detection efficiency. ©

关键词： Feature extraction

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Demand Response Scheme: Achieving Sustainability in Distributed Data Processing 9

Demand Response Scheme: Achieving Sustainability in Distribu...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Zhai, Xueying Peng, Yunfeng Guo, Xiuping Zhang, Liang Zhang, Wei University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Beijing University of Posts and Telecommunications School of Economics and Management Beijing China Guizhou Institute of Technology Guizhou Key Laboratory of Electric Power Big Data Guizhou China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China

ISBN: (纸本)9798350391367

The rapid development of Internet of Things (IoT) technology has driven the intelligent transformation of various industries, including manufacturing, agriculture, and healthcare, etc., significantly enhancing their management capabilities and decision-making efficiency. Data analysis is crucial, serving as both the core technology of this transformation and a major driving force for advancing industry intelligence. However, the increasing volume of data has led to high energy consumption during data analysis, posing significant challenges to environmental and economic sustainability. Integrating renewable energy sources (RESs) is an effective way to reduce greenhouse gas emissions due to their low-carbon and renewable nature. Additionally, the spatiotemporal variability and complementarity of RES generation and grid electricity prices provide favorable conditions for distributed data processing. Therefore, a two-stage demand response scheme is proposed to reduce carbon emissions and electricity costs by prioritizing data processing in data centers (DCs) where RES is abundant or electricity prices are low, based on RES generation and electricity price signals. Simulation results show that the proposed scheme reduces 36.37% carbon emissions and 20.49% electricity costs compared to the benchmark algorithm, indicating its potential for both environmental and economic optimization. © 2024 IEEE.

关键词： Low emission

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International research initiative on genomicsguided sugarcane breeding

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Molecular Plant 2025年第2期18卷 171-174页

作者： Xingtan Zhang Jungang Wang Noor-ul-Ain Youxiong Que Jisen Zhang Javeria Abid Peifang Zhao Yuebin Zhang Jishan Lin Li-yu Chen Yixue Bao Robert Herry Sithichoke Tangphatsornruang Qinnan Wang Dongliang Huang Jian Ye Muqing Zhang Ming Luo Mike Butterfield Ren Wang Ray Ming National Key Laboratory of Tropical Crop Breeding Institute of Tropical Bioscience and BiotechnologyChinese Academy of Tropical Agricultural SciencesSanyaHainanChina National Key Laboratory for Tropical Crop Breeding Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenGuangdong 518120China State Key Laboratory for Conservation and Utilization of Subtropical Agri-Biological Resources&Guangxi Key Laboratory for Sugarcane Biology Guangxi UniversityNanningGuangxiChina National Key Laboratory of Tropical Crop Breeding Yunan Academy of Agricultural SciencesKaiyuanYunnanChina National Engineering Research Center for Sugarcane Fujian Provincial Key Laboratory of Haixia Applied Plant Systems BiologyKey Laboratory of GeneticsBreeding and Multiple Utilization of CropsMinistry of EducationFujian Agriculture and Forestry UniversityFuzhouFujianChina Queensland Alliance for Agriculture and Food Innovation University of QueenslandBrisbaneQLDAustralia National Omics Center National Science and Technology Development AgencyPathum ThaniThailand Institute of Nanfan&Seed Industry Guangdong Academy of Sciencesand Ministry of Agriculture of Guangdong Sugarcane Germplasm Resources and Utilization of Scientific Observation Test StationNo.10 Shiliugang RdGuangzhouGuangdong China Guangxi Key Laboratory of Sugarcane Genetic Improvement Guangxi Academy of Agricultural SciencesNanningGuangxiChina State Key Laboratory of Plant Genomics Institute of MicrobiologyChinese Academy of SciencesBeijingChina State Key Laboratory of Plant Diversity and Specialty Crops Guangdong Provincial Key Laboratory of Applied BotanySouth China Botanical Garden Chinese Academy of SciencesGuangzhou 510650China 12Centro De Tecnologia CanavieiraPiracicabaSão PauloBrazil

Addressing global challenges such as energy sustainability,food security,and environmental conservation requires innovative agricultural *** sugarcane(Saccharum hybrid)is a crucial crop that contributes not only to the sugar industry but also to bioenergy *** its traditional role,sugarcane supports global food security,environmental sustainability,and economic empowerment of *** 80%of the worldwide sugarcane production is dedicated to sugar,a dietary staple(OECD-FAO,2024).The remaining 19%aid biofuel production,with sugarcane accounting for 24%of the global ethanol feedstock by *** a C4 plant,sugarcane efficiently captures atmospheric carbon and acts as an important carbon ***,sugarcane cultivation can lower local temperatures by nearly 1°C compared to pastures/natural vegetation(Loarie et al.,2011).Economically,sugarcane is a high-value cash crop,generating$43 billion annually in Brazil alone(Voora et al.,2023).

关键词： annually sugar breeding

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Robust Imagined Speech Production Using AI-Generated Content Network for Patients with Language Impairments

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IEEE Transactions on Consumer Electronics 2024年

作者： Xu, Xu Fu, Chong Dalian University of Technology School of Software Dalian116621 China Northeastern University School of Computer Science and Engineering Shenyang110004 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Ministry of Education Engineering Research Center of Security Technology of Complex Network System Shenyang110004 China

Imagined speech production is critical for brain-computer interface systems. It is able to provide the communication ability for patients with language impairments. Nowadays, many studies have developed algorithms for this purpose. However, they often struggle with an issue that is the noise in physiological signals from various devices. This makes current methods have low robustness when performing speech generation. To this end, we propose a framework to robustly producing imagined speech for patients with language impairments. It is based on artificial intelligent-generated content (AIGC). In specific, this work develops a diffusion model to remove noise from brain signals, which are then converted and normalized into log-mel spectrograms. Next, the product feeds into a transformer-based model to extract local and global features. Finally, these enhanced features are inputted into full connected layers to generate the imagined speech. The effectiveness of our model is validated using the high-quality, i.e., single-word-production-Dutch-iBIDS dataset. It achieves Pearson correlation scores above 0.8 and standard deviations below 0.2 across different volunteers. Experimental results well demonstrate that our model is robust and has advantages over peer methods. © 2024 IEEE.

关键词： Deep learning

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Spatio-Temporal Context Modeling for Road Obstacle Detection 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Wu, Xiuen Wang, Tao Liang, Lingyu Li, Zuoyong Ching, Fum Yew College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan354300 China School of Electronic and Information Engineering South China University of Technology Guangzhou510641 China Ministry of Education Key Laboratory of Computer Network and Information Integration Southeast University Nanjing211189 China Guangzhou510320 China Penang11800 Malaysia

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

Road obstacle detection is an important problem for vehicle driving safety. In this paper, we aim to obtain robust road obstacle detection based on spatio-temporal context modeling. Firstly, a data-driven spatial context model of the driving scene is constructed with the layouts of the training data. Then, obstacles in the input image are detected via the state-of-the-art object detection algorithms, and the results are combined with the generated scene layout. In addition, to further improve the performance and robustness, temporal information in the image sequence is taken into consideration, and the optical flow is obtained in the vicinity of the detected objects to track the obstacles across neighboring frames. Qualitative and quantitative experiments were conducted on the Small Obstacle Detection (SOD) dataset and the Lost and Found dataset. The results indicate that our method with spatio-temporal context modeling is superior to existing methods for road obstacle detection. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

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Biomedical polymers: synthesis, properties, and applications

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Science China Chemistry 2022年第6期65卷 1010-1075页

作者： Wei-Hai Chen Qi-Wen Chen Qian Chen Chunyan Cui Shun Duan Yongyuan Kang Yang Liu Yun Liu Wali Muhammad Shiqun Shao Chengqiang Tang Jinqiang Wang Lei Wang Meng-Hua Xiong Lichen Yin Kuo Zhang Zhanzhan Zhang Xu Zhen Jun Feng Changyou Gao Zhen Gu Chaoliang He Jian Ji Xiqun Jiang Wenguang Liu Zhuang Liu Huisheng Peng Youqing Shen Linqi Shi Xuemei Sun Hao Wang Jun Wang Haihua Xiao Fu-Jian Xu Zhiyuan Zhong Xian-Zheng Zhang Xuesi Chen Key Laboratory of Biomedical Polymers of Ministry of Education&Department of Chemistry Wuhan UniversityWuhan430072China Institute of Functional Nano&Soft Materials(FUNSOM) Jiangsu Key Laboratory for Carbon-Based Functional Materials&DevicesSoochow UniversitySuzhou215123China School of Materials Science and Engineering Tianjin Key Laboratory of Composite and Functional MaterialsTianjin UniversityTianjin300350China Key Laboratory of Biomedical Materials of Natural Macromolecules(Beijing University of Chemical Technology) Ministry of EducationBeijing Laboratory of Biomedical MaterialsCollege of Materials Science and EngineeringBeijing University of Chemical TechnologyBeijing100029China MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhou310027China State Key Laboratory of Medicinal Chemical Biology Key Laboratory of Functional Polymer Materials of Ministry of EducationCollege of ChemistryNankai UniversityTianjin300071China Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province College of Pharmaceutical SciencesZhejiang UniversityHangzhou310058China Jinhua Institute of Zhejiang University Jinhua321299China Zhejiang Key Laboratory of Smart BioMaterials and Center for Bionanoengineering College of Chemical and Biological EngineeringZhejiang UniversityHangzhou310027China ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou311215China State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular Science and Laboratory of Advanced MaterialsFudan UniversityShanghai200438China CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety CAS Center for Excellence in Nano-scienceNational Center for Nanoscience and Technology(NCNST)Beijing100190China School of Biomedical Sciences and Engineering Guangzhou International CampusSouth China University of TechnologyGuangzhou510006China Institute of Functional Nano and So

Biomedical polymers have been extensively developed for promising applications in a lot of biomedical fields, such as therapeutic medicine delivery, disease detection and diagnosis, biosensing, regenerative medicine, and disease treatment. In this review, we summarize the most recent advances in the synthesis and application of biomedical polymers, and discuss the comprehensive understanding of their property-function relationship for corresponding biomedical applications. In particular, a few burgeoning bioactive polymers, such as peptide/biomembrane/microorganism/cell-based biomedical polymers, are also introduced and highlighted as the emerging biomaterials for cancer precision therapy. Furthermore, the foreseeable challenges and outlook of the development of more efficient, healthier and safer biomedical polymers are discussed. We wish this systemic and comprehensive review on highlighting frontier progress of biomedical polymers could inspire and promote new breakthrough in fundamental research and clinical translation.

关键词： biomedical polymer nanomedicine cancer therapy drug delivery bioimaging and biosensing tissue engineering regenerative medicine cytotoxicity biocompatibility

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