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signal transduction and Targeted Therapy 2024年第8期9卷 3163-3164页

作者： Marina Kolesnichenko Claus Scheidereit department of Hepatology and Gastroenterology Charite-Universitatsmedizin BerlinBerlinGermany Laboratory for signal transduction in Tumor Cells Max Delbruck Center for Molecular Medicine in the Helmholtz Association(MDC)BerlinGermany

In a landmark study recently published in Nature,Petropoulous et *** that synthetic lethality of poly(ADP-ribose)polymerase(PARP)inhibitors in cells with defective homologous recombination repair(HR)results predominantly from transcription replication conflicts(TRC)and not,as previously proposed,from PARP trapping on DNA(Fig.1).The article unveils a new mechanism behind synthetic lethality of PARP inhibitors with relevance for cancer therapy.

关键词： al. PARP mechanism

Interference mitigation and target detection for automotive FMCW radar with range-Doppler sparse regularization

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science China(Information sciences) 2024年第9期67卷 342-343页

作者： Yan HUANG Yunxuan WANG Xiao ZHOU Hui ZHANG Yuan MAO Guisheng LIAO Wei HONG State Key Lab of Millimeter Waves Southeast University department of Computer science University College London National Key Lab of Radar signal Processing Xidian University

The invention of vehicles has shaped our modern society and accelerated our economy while causing many tragic incidents simultaneously. Some advanced driver-assistance systems(ADAS) based on surrounding environment se... 详细信息

关键词： Radar interference

Improving Video Watermarking through Galois Field GF(2^(4)) Multiplication Tables with Diverse Irreducible Polynomials and Adaptive Techniques

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Computers, Materials & Continua 2024年第1期78卷 1423-1442页

作者： Yasmin Alaa Hassan Abdul Monem S.Rahma department of Computer science College of ScienceUniversity of BaghdadBaghdadIraq department of Computer science College of ScienceAl-Maarif University CollegeAl-AnbarIraq

Video watermarking plays a crucial role in protecting intellectual property rights and ensuring content *** study delves into the integration of Galois Field(GF)multiplication tables,especially GF(2^(4)),and their interaction with distinct irreducible *** primary aim is to enhance watermarking techniques for achieving imperceptibility,robustness,and efficient execution *** research employs scene selection and adaptive thresholding techniques to streamline the watermarking *** selection is used strategically to embed watermarks in the most vital frames of the video,while adaptive thresholding methods ensure that the watermarking process adheres to imperceptibility criteria,maintaining the video's visual ***,careful consideration is given to execution time,crucial in real-world scenarios,to balance efficiency and *** Peak signal-to-Noise Ratio(PSNR)serves as a pivotal metric to gauge the watermark's imperceptibility and video *** study explores various irreducible polynomials,navigating the trade-offs between computational efficiency and watermark *** parallel,the study pays careful attention to the execution time,a paramount consideration in real-world scenarios,to strike a balance between efficiency and *** comprehensive analysis provides valuable insights into the interplay of GF multiplication tables,diverse irreducible polynomials,scene selection,adaptive thresholding,imperceptibility,and execution *** evaluation of the proposed algorithm's robustness was conducted using PSNR and NC metrics,and it was subjected to assessment under the impact of five distinct attack *** findings contribute to the development of watermarking strategies that balance imperceptibility,robustness,and processing efficiency,enhancing the field's practicality and effectiveness.

关键词： Video watermarking galois field irreducible polynomial multiplication table scene selection adaptive thresholding

Network Intrusion Traffic Detection Based on Feature Extraction

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Computers, Materials & Continua 2024年第1期78卷 473-492页

作者： Xuecheng Yu Yan Huang Yu Zhang Mingyang Song Zhenhong Jia College of Information science and Engineering Xinjiang UniversityUrumqi830046China Network department China Mobile Communications Group Xinjiang CoLtd.UrumqiUrumqi830011China Xinjiang signal Detection and Processing Key Laboratory Xinjiang UniversityUrumqi830000China

With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal ***,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion *** method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after *** network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between *** datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the ***,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic *** empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing *** results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%.

关键词： Network intrusion traffic detection PCA Hotelling’s T^(2) BiLSTM

Diverse functions of sox9 in liver development and homeostasis and hepatobiliary diseases

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Genes & Diseases 2024年第4期11卷 170-187页

作者： Taiyu Shang Tianyi Jiang Xiaowen Cui Yufei Pan Xiaofan Feng Liwei Dong Hongyang Wang School of Life sciences Institute of Metabolism and Integrative BiologyFudan UniversityShanghai 200438China National Center for Liver Cancer The Naval Medical UniversityShanghai 201805China International Cooperation Laboratory on signal transduction Eastern Hepatobiliary Surgery InstituteThe Second Military Medical UniversityShanghai 200438China Laboratory of signaling Regulation and Targeting Therapy of Liver Cancer Second Military Medical University&Ministryof EducationShanghai 200438China

The liver is the central organ for digestion and detoxification and has unique metabolic and regenerative *** hepatobiliary system originates from the foregut endoderm,in which cells undergo multiple events of cell proliferation,migration,and differentiation to form the liver parenchyma and ductal system under the hierarchical regulation of transcription *** on liver development and diseases have revealed that SRY-related high-mobility group box 9(SOx9)plays an important role in liver embryogenesis and the progression of hepatobiliary ***9 is not only a master regulator of cell fate determination and tissue morphogenesis,but also regulates various biological features of cancer,including cancer stemness,invasion,and drug resistance,making Sox9 a potential biomarker for tumor prognosis and *** review systematically summarizes the latest findings of sox9 in hepatobiliary development,homeostasis,and *** also highlight the value of sox9 as a novel biomarker and potential target for the clinical treatment of major liverdiseases.

关键词： Biliary system Cancer Homeostasis Liver diseases SOX9

Cancer stem cell-immune cell crosstalk in the tumor microenvironment for liver cancer progression

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Frontiers of Medicine 2024年第3期18卷 430-445页

作者： Yue Ma Hongwei Lv Fuxue Xing Wei Xiang Zixin Wu Qiyu Feng Hongyang Wang Wen Yang Cancer Research Center First Affiliated Hospital of USTCDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefei230027China National Center for Liver Cancer Naval Medical University(Second Military Medical University)Shanghai201805China International Co-operation Laboratory on signal transduction Eastern Hepatobiliary Surgery HospitalNaval Medical University(Second Military Medical University)Shanghai200438China Shanghai Key Laboratory of Hepato-biliary Tumor Biology Shanghai200438China Key Laboratory of signaling Regulation and Targeting Therapy of Liver Cancer Ministry of EducationShanghai200438China

Crosstalk between cancer cells and the immune microenvironment is determinant for liver cancer progression.A tumor subpopulation called liver cancer stem cells(CSCs)significantly accounts for the initiation,metastasis,therapeutic resistance,and recurrence of liver *** evidence demonstrates that the interaction between liver CSCs and immune cells plays a crucial role in shaping an immunosuppressive microenvironment and determining immunotherapy *** review sheds light on the bidirectional crosstalk between liver CSCs and immune cells for liver cancer progression,as well as the underlying molecular mechanisms after presenting an overview of liver CSCs characteristic and their ***,we discuss the potential application of liver CSCs-targeted immunotherapy for liver cancer treatment.

关键词： liver cancer cancer stem cell immune cell immunotherapy

ReChoreoNet: Repertoire-based Dance Re-choreography with Music-conditioned Temporal and Style Clues

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Machine Intelligence Research 2024年第4期21卷 771-781页

作者： Ho Yin Au Jie Chen Junkun Jiang Yike Guo department of Computer science Hong Kong Baptist UniversityHong Kong 999077China department of Computer science and Engineering The Hong Kong University of Science and EngineeringHong Kong 999077China

To generate dance that temporally and aesthetically matches the music is a challenging problem in three ***,the generated motion should be beats-aligned to the local musical ***,the global aesthetic style should be matched between motion and *** third,the generated motion should be diverse and *** address these challenges,we propose ReChoreoNet,which re-choreographs high-quality dance motion for a given piece of music.A data-driven learning strategy is proposed to efficiently correlate the temporal connections between music and motion in a progressively learned cross-modality embedding *** beats-aligned content motion will be subsequently used as autoregressive context and control signal to control a normalizing-flow model,which transfers the style of a prototype motion to the final generated *** addition,we present an aesthetically labelled music-dance repertoire(MDR)for both efficient learning of the cross-modality embedding,and understanding of the aesthetic connections between music and *** demonstrate that our repertoire-based framework is robustly extensible in both content and *** quantitative and qualitative experiments have been carried out to validate the efficiency of our proposed model.

关键词： Generative model cross-modality learning normalizing flow tempo synchronization style transfer.

AutoRhythmAI: A Hybrid Machine and Deep Learning Approach for Automated Diagnosis of Arrhythmias

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Computers, Materials & Continua 2024年第2期78卷 2137-2158页

作者： S.Jayanthi S.Prasanna Devi department of Computer science and Engineering SRM Institute of Science and Technology-Vadapalani CampusChennaiTamil NaduIndia

In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation *** glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between data preprocessing and model *** validate our system,we have rigorously tested AutoRhythmAI using a multimodal dataset,surpassing the accuracy achieved using a single dataset and underscoring the robustness of our *** the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by data balancing and split for *** second pipeline is dedicated to feature extraction and classification,utilizing deep learning ***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then amalgamates all models,considering their respective weights,resulting in an optimal model *** our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-balanced performance metrics.

关键词： Automated machine learning neural networks deep learning arrhythmias

Electrochemical protein biosensors for disease marker detection:progress and opportunities

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Microsystems & Nanoengineering 2024年第3期10卷 1-20页

作者： Lanpeng Guo Yunong Zhao Qing Huang Jing Huang Yanbing Tao Jianjun Chen Hua-Yao Li Huan Liu School of Integrated Circuits Wuhan National Laboratory for OptoelectronicsOptics Valley LaboratoryHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Intelligent Computing and signal Processing of Ministry of Education School of Integrated CircuitsAnhui UniversityHefei 230601China School of Optoelectronic Materials and Technology Jianghan UniversityWuhan 430056China department of Otorhinolaryngology Union HospitalTongji Medical CollegeHuazhong University of Science and Technology1277 Jiefang AvenueWuhan 430022China Wenzhou Institute of Advanced Manufacturing Technology Huazhong University of Science and TechnologyWenzhou 325000China

The development of artificial intelligence-enabled medical health care has created both opportunities and challenges for next-generation biosensor *** are extensively used as biological macromolecular markers in disease diagnosis and the analysis of therapeutic *** protein biosensors have achieved desirable specificity by using the specific antibody–antigen binding principle in ***,the active centers of protein biomarkers are surrounded by a peptide matrix,which hinders charge transfer and results in insufficient sensor ***,electrode-modified materials and transducer devices have been designed to increase the sensitivity and improve the practical application prospects of electrochemical protein *** this review,we summarize recent reports of electrochemical biosensors for protein biomarker *** highlight the latest research on electrochemical protein biosensors for the detection of cancer,viral infectious diseases,inflammation,and other *** corresponding sensitive materials,transducer structures,and detection principles associated with such biosensors are also addressed ***,we present an outlook on the use of electrochemical protein biosensors for disease marker detection for the next few years.

关键词： diagnosis specificity Electrochemical

Memory-enhanced text style transfer with dynamic style learning and calibration

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science China(Information sciences) 2024年第4期67卷 181-196页

作者： Fuqiang LIN Yiping SONG Zhiliang TIAN Wangqun CHEN Diwen DONG Bo LIU College of Computer science and Technology National University of Defense Technology department of Computer science and Engineering The Hong Kong University of Science and Technology Strategic Assessments and Consultation Institute Academy of Military Sciences

Text style transfer aims to rephrase a sentence to match the desired style while retaining the original content. As a controllable text generation task, mainstream approaches use content-independent style embedding as control variables to guide stylistic generation. Nonetheless, stylistic properties are contextsensitive even under the same style. For example, “delicious” and “helpful” convey positive sentiments,although they are more likely to describe food and people, respectively. Therefore, desired style signals must vary with the content. To this end, we propose a memory-enhanced transfer method, which learns fine-grained style representation concerning content to assist transfer. Rather than employing static style embedding or latent variables, our method abstracts linguistic characteristics from training corpora and memorizes subdivided content with the corresponding style representations. The style signal is dynamically retrieved from memory using the content as a query, providing a more expressive and flexible latent style space. To address the imbalance between quantity and quality in different content, we further introduce a calibration method to augment memory construction by modeling the relationship between candidate *** results obtained using three benchmark datasets confirm the superior performance of our model compared to competitive approaches. The evaluation metrics and case study also indicate that our model can generate diverse stylistic phrases matching context.

关键词： style transfer memory-enhanced method text generation deep learning text representation