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Journal of Molecular Cell Biology 2020年第8期12卷 644-653页

作者： Tijmen H.Booij Wouter N.Leonhard Hester Bange Kuan Yan Michiel Fokkelman Anna J.Plugge Kimberley A.M.Veraar Johannes G.Dauwerse Gerard J.P.van Westen bob van de water Leo S.Price Dorien j.M.Peters Division of Toxicology Leiden Academic Centre for Drug Research(LACDR)Leiden UniversityLeidenThe Netherlands Present address:NEXUS Personalized Health Technologies ETH ZurichSwitzerland department of Human Genetics Leiden University Medical Center(LUMC)LeidenThe Netherlands OcellO B.V. LeidenThe Netherlands Division of Medicinal Chemistry Leiden Academic Centre for Drug Research(LACDR)LeidenThe Netherlands

Polycystic kidney disease(PKD)is a prevalent genetic disorder,characterized by the formation of kidney cysts that progressively lead to kidney *** currently available drug tolvaptan is not well tolerated by all patients and there remains a strong need for alternative *** signalling rewiring in PKD that drives cyst formation is highly complex and not fully *** a consequence,the effects of drugs are sometimes difficult to *** previously established a high-throughput microscopy phenotypic screening method for quantitative assessment of renal cyst ***,we applied this 3D cyst growth phenotypic assay and screened 2320 small drug-like molecules,including approved *** identified 81 active molecules that inhibit cyst ***-parametric phenotypic profiling of the effects on 3D cultured cysts discriminated molecules that showed preferred pharmacological effects above genuine toxicological ***,a triterpenoid from Tripterygium wilfordii,was identified as a potent inhibitor of cyst growth in *** an in vivo iKspCre-Pkd1^lox,lox mouse model for PKD,celastrol inhibited the growth of renal cysts and maintained kidney function.

关键词： PKD celastrol pyrvinium pamoate high-content screening 3D

An Enhanced GAN for Image Generation

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Computers, Materials & Continua 2024年第7期80卷 105-118页

作者： Chunwei Tian Haoyang Gao Pengwei Wang bob Zhang PAMI Research Group University of MacaoMacao999078China School of Software Northwestern Polytechnical UniversityXi’an710129China Yangtze River delta Research Institute Northwestern Polytechnical UniversityTaicang215400China Research&development Institute Northwestern Polytechnical UniversityShenzhen518057China

Generative adversarial networks(GANs)with gaming abilities have been widely applied in image ***,gamistic generators and discriminators may reduce the robustness of the obtained GANs in image generation under varying *** the relation of hierarchical information in a generation network and enlarging differences of different network architectures can facilitate more structural information to improve the generation effect for image *** this paper,we propose an enhanced GAN via improving a generator for image generation(EIGGAN).EIGGAN applies a spatial attention to a generator to extract salient information to enhance the truthfulness of the generated *** into relation the context account,parallel residual operations are fused into a generation network to extract more structural information from the different ***,a mixed loss function in a GAN is exploited to make a tradeoff between speed and accuracy to generate more realistic *** results show that the proposed method is superior to popular methods,i.e.,Wasserstein GAN with gradient penalty(WGAN-GP)in terms of many indexes,i.e.,Frechet Inception Distance,Learned Perceptual Image Patch Similarity,Multi-Scale Structural Similarity Index Measure,Kernel Inception Distance,Number of Statistically-Different Bins,Inception Score and some visual images for image generation.

关键词： Generative adversarial networks spatial attention mixed loss image generation

Interworking between Modbus and internet of things platform for industrial services

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Digital Communications and Networks 2024年第2期10卷 461-471页

作者： Sherzod Elamanov Hyeonseo Son bob Flynn Seong Ki Yoo Naqqash Dilshad JaeSeung Song department of Convergence Engineering for Intelligent Drone Sejong UniversitySouth Korea SyncTechno Inc South Korea Exacta Global Smart Solutions USA Coventry University UK

In the era of rapid development of Internet of Things(IoT),numerous machine-to-machine technologies have been applied to the industrial *** to the divergence of IoT solutions,the industry is faced with a need to apply various technologies for automation and *** fact leads to a demand for an establishing interworking mechanism which would allow smooth interoperability between heterogeneous *** of the major protocols widely used today in industrial electronic devices is ***,data generated by Modbus devices cannot be understood by IoT applications using different protocols,so it should be applied in a couple with an IoT service layer ***2M,a global IoT standard,can play the role of interconnecting various protocols,as it provides flexible tools suitable for building an interworking framework for industrial ***,in this paper,we propose an interworking architecture between devices working on the Modbus protocol and an IoT platform implemented based on oneM2M *** the proposed architecture,we introduce the way to model Modbus data as oneM2M resources,rules to map them to each other,procedures required to establish interoperable communication,and optimization methods for this *** analyze our solution and provide an evaluation by implementing it based on a solar power management use *** results demonstrate that our model is feasible and can be applied to real case scenarios.

关键词： Internet of things Interoperability Interworking Modbus oneM2M

Sparse representation scheme with enhanced medium pixel intensity for face recognition

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 116-127页

作者： Xuexue Zhang Yongjun Zhang Zewei Wang Wei Long Weihao Gao bob Zhang State Key Laboratory of Public Big Data Institute for Artificial IntelligenceCollege of Computer Science and TechnologyGuizhou UniversityGuiyangGuizhouChina department of Computer and Information Science University of MacaoAvenida da UniversidadeTaipaMacaoChina

Sparse representation is an effective data classification algorithm that depends on the known training samples to categorise the test *** has been widely used in various image classification *** in sparse representation means that only a few of instances selected from all training samples can effectively convey the essential class-specific information of the test sample,which is very important for *** deformable images such as human faces,pixels at the same location of different images of the same subject usually have different ***,extracting features and correctly classifying such deformable objects is very ***,the lighting,attitude and occlusion cause more *** the problems and challenges listed above,a novel image representation and classification algorithm is ***,the authors’algorithm generates virtual samples by a non-linear variation *** method can effectively extract the low-frequency information of space-domain features of the original image,which is very useful for representing deformable *** combination of the original and virtual samples is more beneficial to improve the clas-sification performance and robustness of the ***,the authors’algorithm calculates the expression coefficients of the original and virtual samples separately using the sparse representation principle and obtains the final score by a designed efficient score fusion *** weighting coefficients in the score fusion scheme are set entirely ***,the algorithm classifies the samples based on the final *** experimental results show that our method performs better classification than conventional sparse representation algorithms.

关键词： computer vision face recognition image classification image representation

A deep convolutional neural network for diabetic retinopathy detection via mining local and long-range dependence

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 153-166页

作者： Xiaoling Luo Wei Wang Yong Xu Zhihui Lai Xiaopeng Jin bob Zhang David Zhang Shenzhen Key Laboratory of Visual Object detection and Recognition Harbin Institute of TechnologyShenzhenChina Peng Cheng Laboratory ShenzhenChina Shenzhen Institute of Artificial Intelligence and Robotics for Society ShenzhenChina College of Big Data and Internet Shenzhen Technology UniversityShenzhenChina The department of Computer and Information Science University of MacaoMacaoMacaoChina The Chinese University of Hong Kong(Shenzhen) ShenzhenChina

Diabetic retinopathy(DR),the main cause of irreversible blindness,is one of the most common complications of *** present,deep convolutional neural networks have achieved promising performance in automatic DR detection *** convolution operation of methods is a local cross-correlation operation,whose receptive field de-termines the size of the local neighbourhood for ***,for retinal fundus photographs,there is not only the local information but also long-distance dependence between the lesion features(*** and exudates)scattered throughout the whole *** proposed method incorporates correlations between long-range patches into the deep learning framework to improve DR ***-wise re-lationships are used to enhance the local patch features since lesions of DR usually appear as *** Long-Range unit in the proposed network with a residual structure can be flexibly embedded into other trained *** experimental results demon-strate that the proposed approach can achieve higher accuracy than existing state-of-the-art models on Messidor and EyePACS datasets.

关键词： image classification medical image processing pattern recognition

Paxillin serine 178 phosphorylation in control of cell migration and metastasis formation through regulation of EGFR expression in breast cancer

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Journal of Cancer Metastasis and Treatment 2019年第6期4卷 71-86页

作者： Saertje Verkoeijen Ya-Feng Ma Wies van Roosmalen Reshma Lalai Martine H.A.M.van Miltenburg Marjo de Graauw bob van de water Sylvia E.Le Dévédec Institute for Life Sciences&Chemistry Hogeschool Utrecht HUUtrecht 3501 AAthe Netherlands Division of Drug Discovery and Safety Leiden Academic Centre for Drug ResearchLeiden UniversityLeiden 2300 RAthe Netherlands

Aim:Paxillin is a well-known multidomain scaffold protein that is involved in the regulation of cell-matrix adhesion dynamics,a process required for the tumor cell migration and *** of the serine residue 178 requires c-Jun NH2-terminal kinase(JNK)activation,which occurs downstream of epidermal growth factor receptor(EGFR)-mediated signaling and drives cell *** this study,we investigated the significance of paxillin Ser178 phosphorylation in breast cancer ***:We employed the rat mammary carcinoma MTLn3 cell line with which we established stabile variants of both wild type and mutant GFP-paxillin *** those,we next performed several in vitro assays including cell proliferation,migration and focal adhesion ***,we monitored the metastatic spread of both cell line variants in an othrotopic mouse model for breast ***:Here we show that expression of the phospho-defective mutant paxillinS178A in the metastatic mammary adenocarcinoma MTLn3 cell-line significantly decreased EGF-induced cell migration,which was correlated with impaired focal adhesion ***,paxillinS178A attenuated lung metastasis formation in an orthotopic in vivo mammary gland tumor/metastasis model,demonstrating the importance of JNK-mediated paxillin phosphorylation in breast cancer *** of paxillinS178A caused a decrease in EGFR expression, ;while re-expression of EGFR in MTLn3-paxillinS178A cells fully restored EGF-driven cell motility and focal adhesion ***,re-expression of EGFR in MTLn3-paxillinS178A rescued spontaneous metastasis from breast to ***:Overall our data show an important role for JNK-mediated paxillin Ser178 phosphorylation in the regulation of EGFR expression and thereby,in EGF-driven cell migration and metastasis formation.

关键词： Paxillin c-Jun NH2-terminal kinase focal adhesion epidermal growth factor receptor cell migration metastasis breast cancer

A multi-feature-based intelligent redundancy elimination scheme for cloud-assisted health systems

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 491-510页

作者： Ling Xiao Beiji Zou Xiaoyan Kui Chengzhang Zhu Wensheng Zhang Xuebing Yang bob Zhang School of Computer Science and Engineering Central South UniversityChangshaChina Hunan Engineering Research Center of Machine Vision and Intelligent Medicine Central South UniversityChangshaChina The College of Literature and Journalism Central South UniversityChangshaChina Institute of Automation Chinese Academy of SciencesBeijingChina department of Computer and Information Science University of MacaoMacaoChina

Redundancy elimination techniques are extensively investigated to reduce storage overheads for cloud-assisted health *** eliminates the redundancy of duplicate blocks by storing one physical instance referenced by multiple *** compression is usually regarded as a complementary technique to deduplication to further remove the redundancy of similar blocks,but our observations indicate that this is disobedient when data have sparse duplicate *** addition,there are many overlapped deltas in the resemblance detection process of post-deduplication delta compression,which hinders the efficiency of delta compression and the index phase of resemblance detection inquires abundant non-similar blocks,resulting in inefficient system ***,a multi-feature-based redundancy elimination scheme,called MFRE,is proposed to solve these *** similarity feature and temporal locality feature are excavated to assist redundancy elimination where the similarity feature well expresses the duplicate ***,similarity-based dynamic post-deduplication delta compression and temporal locality-based dynamic delta compression discover more similar base blocks to minimise overlapped deltas and improve compression ***,the clustering method based on block-relationship and the feature index strategy based on bloom filters reduce IO overheads and improve system *** demonstrate that the proposed method,compared to the state-of-the-art method,improves the compression ratio and system throughput by 9.68%and 50%,respectively.

关键词： big data cloud computing compression data compression medical applications performance evaluation

Enhanced Acceleration for Generalized Nonconvex Low-Rank Matrix Learning

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Chinese Journal of Electronics 2024年

作者： Hengmin ZHANG Jian YANG Wenli DU bob ZHANG Zhiyuan ZHA Bihan WEN School of Electrical and Electronic Engineering Nanyang Technological University School of Computer Science and Engineering Nanjing University of Science and Technology College of Information Science and Engineering East China University of Science and Technology department of Electrical and Computer Engineering University of Macau

Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inherent biases and computational burdens, especially when used to relax the rank function, making them less effective and efficient in real-world scenarios. To address these challenges, our research focuses on generalized nonconvex rank regularization problems in robust matrix completion (RMC), low-rank representation (LRR), and robust matrix regression (RMR). We introduce innovative approaches for effective and efficient low-rank matrix learning, grounded in generalized nonconvex rank relaxations inspired by various substitutes for the?0-norm relaxed functions. These relaxations allow us to more accurately capture low-rank structures. Our optimization strategy employs a nonconvex and multi-variable alternating direction method of multipliers (ADMM), backed by rigorous theoretical analysis for complexity and convergence. This algorithm iteratively updates blocks of variables, ensuring efficient convergence. Additionally, we incorporate the randomized singular value decomposition technique and/or other acceleration strategies to enhance the computational efficiency of our approach, particularly for large-scale constrained minimization problems. In conclusion, our experimental results across a variety of image vision-related application tasks unequivocally demonstrate the superiority of our proposed methodologies in terms of both efficacy and efficiency when compared to most other related learning methods.

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Nitrate reduction capacity of the oral microbiota is impaired in periodontitis:potential implications for systemic nitric oxide availability

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International Journal of Oral Science 2024年第1期16卷 52-61页

作者： bob T.Rosier William Johnston Miguel Carda-Diéguez Annabel Simpson Elena Cabello-Yeves Krystyna Piela Robert Reilly Alejandro Artacho Chris Easton Mia Burleigh Shauna Culshaw Alex Mira department of Genomics and Health FISABIO FoundationCenter for Advanced Research in Public HealthValenciaSpain department of Biological and Biomedical Sciences Glasgow Caledonian UniversityGlasgowUK Oral Sciences University of Glasgow Dental SchoolSchool of MedicineDentistry and NursingCollege of MedicalVeterinary and Life SciencesUniversity of GlasgowGlasgowUK Sport and Physical Activity Research Institute University of the West of ScotlandBlantyreScotland Instituto de Biomedicina de Valencia Consejo Superior de Investigaciones Científicas(IBV-CSIC)ValenciaSpain CIBER Center for Epidemiology and Public Health MadridSpain

The reduction of nitrate to nitrite by the oral microbiota has been proposed to be important for oral health and results in nitric oxide formation that can improve cardiometabolic conditions. Studies of bacterial composition in subgingival plaque suggest that nitrate-reducing bacteria are associated with periodontal health, but the impact of periodontitis on nitrate-reducing capacity(NRC)and, therefore, nitric oxide availability has not been evaluated. The current study aimed to evaluate how periodontitis affects the NRC of the oral microbiota. First, 16S rRNA sequencing data from five different countries were analyzed, revealing that nitratereducing bacteria were significantly lower in subgingival plaque of periodontitis patients compared with healthy individuals(P determined in vitro by incubating saliva with 8 mmol/L nitrate(a concentration found in saliva after nitrate-rich vegetable intake) and compared with the NRC of 15healthy individuals. Salivary NRC was found to be diminished in periodontal patients before treatment(P derived nitric oxide levels, and the effect on systemic health should be explored in future studies.

关键词： impaired intake nitrate

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适用于工业和交通市场的电感式位置传感器

传感器世界 2024年第3期30卷 43-45页

作者： bob Card 安森美模拟与混合信号事业部

随着各行各业自动化程度的提高,运动控制的重要性日益凸显。为了有效地驱动电机,描述速度和位置的控制输入必不可少。然而,实现这种感测的技术有多种,每种技术都有不同的特点和应用场景。文章将比较不同的旋转感测技术,并讨论选择它们... 详细信息

随着各行各业自动化程度的提高,运动控制的重要性日益凸显。为了有效地驱动电机,描述速度和位置的控制输入必不可少。然而,实现这种感测的技术有多种,每种技术都有不同的特点和应用场景。文章将比较不同的旋转感测技术,并讨论选择它们的原因,然后以NCS32100双电感位置传感器为例,介绍了其技术特点和应用方案。

关键词：位置传感器旋转感测光学编码器磁性编码器电感编码器位置控制工业4.0 自动化高精度双电感位置传感机器人无人机