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11th CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2019

作者： Wang, Zhonghao Xu, Zhengguo State Key Lab of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310058 China City University of Hong Kong Department of Systems Engineering and Engineering Management Hong Kong

ISBN: (纸本)9781728106816

This paper focuses on the photovoltaic (PV) system and studies the dust depositing diagnosis of the PV modules. An unsupervised data-driven method called Similarity-Based Modeling (SBM) was used to deal with this problem and some improvements of this method were adopted. SBM is a nonparametric empirical modeling technology that uses pattern recognition from historical data to generate estimates of the current values of each variable in a set of modeled data sources. The motivation to use SBM is that the mainstream approaches now, contrast experiments approaches and theoretical formulas approaches have many disadvantages. Contrast experiments are complicated and need experiment systems with high-cost. Theoretical formulas approaches are not accurate enough. SBM overcomes them to some extent. Numerical experiments are also studied to testify that the proposed method has good performance in the application. © 2019 IEEE.

关键词： Dust

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Recursive Weighted Null-Space Fitting Method for Identification of Multivariate systems ⁎

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IFAC-PapersOnLine 2021年第7期54卷 345-350页

作者： Mengyuan Fang Miguel Galrinho Håkan Hjalmarsson Zhejiang Engineering Laboratory of Industrial Internet Communication Technology Zhejiang Sci-Tech University Hangzhou China. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China OHB Sweden AB Kista Sweden Centre for Advanced Bio Production and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.

关键词： Recursive system identification multivariate systems weighted null-space fitting

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THE METHOD OF PROCESSING DIGITAL PCR IMAGES BASED ON MASK R-CNN MODEL FOR ISMM 2019

THE METHOD OF PROCESSING DIGITAL PCR IMAGES BASED ON MASK R-...

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中国化学会第十二届全国微全分析系统学术会议、第七届全国微纳尺度生物分离分析学术会议、第七届国际微流控学学术论坛、The 11th International Symposium on Microchemistry and Microsystems

作者： Zhen-Ming Hu Tong Gou Ying Mu Research Center for Analytical Instrumentation Institute of Cyber-Systems and ControlState Key Laboratory of Industrial Control TechnologyZhejiang University

INTRODUCTION Digital polymerase chain reaction(dPCR) using fluorescence images for collecting quantitative information needs efficient software tools to automate the image analysis process. However,due to the broad range of dPCR fluorescence image characteristics,such as uneven fluorescence intensity distribution,irregular structure of microarray,existing tools failed to extract signals from dPCR images properly which hindering the full exportation of dPCR technology's precision. In this paper,a deep learning method was used for image processing to achieve more accurate quantification of nucleic acids in both microarray and droplet dPCR METHODS This Mask R-CNN[1] based method uses massive dPCR fluorescence image data to train a model that has the ability to recognize target signals in dPCR images precisely and automatically,regardless of the non-uniform luminosity or spot impurities appearing in dPCR *** CONCLUSIONS In this paper,we improved a Mask R-CNN model for processing the images of both chip-based and droplet dPCR. The method has higher precision and stronger robustness than the traditional threshold segmentation method in dealing with non-uniform light images and impure images,and will benefit for popularizing dPCR in molecular diagnosis and biological research,as well as has potential for other types of digital detection.

关键词： Deep learning Digital polymerase chain reaction Image process Data analysis

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Preparation and Characterization of Novel Niln2s4/Uio-66 Photocatalysts for the Efficient Degradation of Antibiotics in Water

SSRN

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SSRN 2022年

作者： Wang, Anhu Liang, Huagen Chen, Fu Tian, Xinlong Jing, Shengyu Tsiakaras, Panagiotis Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization Low Carbon Energy Institute China University of Mining and Technology Xuzhou221008 China School of Materials Science and Engineering China University of Mining and Technology Xuzhou221008 China Key Laboratory of Fuel Cell Technology of Guangdong Province Guangzhou510640 China State Key Laboratory of Marine Resource Utilization in South China Sea Hainan Provincial Key Lab of Fine Chemistry School of Chemical Engineering and Technology Hainan University Haikou570228 China School of Information and Control Engineering China University of Mining and Technology Jiangsu Xuzhou221008 China Laboratory of Alternative Energy Conversion Systems Department of Mechanical Engineering School of Engineering University of Thessaly 1 Sekeri Str. Pedion Areos 38834 Greece

Photocatalysis is considered an economical, environmentally friendly, and effective technology for removing pollutants. The construction of Z-Scheme heterojunctions has been identified as one of the feasible solutions capable of enhancing the photocatalytic activity. Herein, a series of visible light responsive photocatalysts (NiIn2S4/Uio-66 composites) with excellent activity and stability were prepared by using a solvothermal process. It is found that 20 mg L-1 of tetracycline (TC) could be almost completely degraded under visible light irradiation within 1 h, when the mass ratio of NiIn2S4 to Uio-66 is 0.5:1 (NISU-0.5) and the solution pH=11. In addition, after six cycles, the degradation rate of tetracycline photocatalyzed by NISU-0.5 still reach up to 90%. Ultraviolet photoelectron spectra (UPS), X-ray photoelectron spectra (XPS) and electron spin resonance measurements (ESR) confirm the formation of the Z-Scheme heterostructure between NiIn2S4 and Uio-66. The synergistic effect between built-in electric field, energy band bending and coulomb interactions in interface of Z-Scheme heterojunction is conducive to restrain the recombination of photogenerated electrons and holes, which greatly improve the photocatalytic activity. In conclusion, this study offers a new thought for design and synthesis of Z-Scheme heterojunctions and provides a cost-effective strategy for solving environmental pollution and energy problems in the future. © 2022, The Authors. All rights reserved.

关键词： Nickel compounds

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Zwitterionic Liquid Hydrogel Sustained-Release Strategy for High-Performance Nanofiltration Membrane

SSRN

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SSRN 2022年

作者： Xiao, Luqi Bai, Ju Lai, Wei Jiao, Yang Wu, Qi Liu, Hongyan Zhang, Yizhou Shan, Linglong Luo, Shuangjiang School of Rare Earths University of Science and Technology of China Hefei230026 China CAS Key Laboratory of Green Process and Engineering State Key Laboratory of Multiphase Complex Systems Beijing Key Laboratory of Ionic Liquids Clean Process Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China Ganjiang Innovation Academy Chinese Academy of Sciences Ganzhou341000 China Key Laboratory of Organic Compound Pollution Control Engineering Ministry of Education School of Environmental and Chemical Engineering Shanghai University Shanghai200444 China Langfang Green Industrial Technology Center Langfang065000 China

controlling amine monomer diffusion behavior plays a crucial role in fabricating well-defined architecture and high-performance nanofiltration (NF) membranes through interfacial polymerization. Herein, a zwitterionic liquid hydrogel transition layer was introduced to the sustained-release amine monomer to the regulated interfacial polymerization process to fabricate a high-performance NF membrane. The hydrogel (Gel) was fabricated via in-situ one-step UV photo-initiated free-radical polymerization between 1-vinyl-3-ethylimidazolium chloride ([VEIm][Cl]) and 3-sulfopropyl methacrylate potassium salt (SMP) on PES substrate membrane surface. Then polyamide layer formed on the Gel layer surface under the regulation of mitigating the amine diffusion behavior. Low-field time-domain NMR (LF-NMR) analysis and water-absorbing demonstrated that the Gel-PA membrane showed high water-membrane interaction. Positron annihilation lifetime spectroscopy (PALS) also confirmed the Gel-PA composite membrane possessed enlarged free volume . Membrane surface and cross-sectional SEM morphologies also showed the Gel-PA membrane with a less ridge-and-valley loose structure and thinner thickness. Combined with the uptake ability of the Gel layer, the obtained Gel-PA composite membrane displayed a high permeance of 13.22 L m -2 h -1 bar -1 , a high Na 2 SO 4 rejection of 98.23%, a favorable NaCl/Na 2 SO 4 selectivity of 49.75, and excellent long-term operational stability . This sustained-release strategy provides a facial and feasible approach to controlling the IP process and obtaining high-performance nanofiltration membranes. © 2022, The Authors. All rights reserved.

关键词： Nanofiltration

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Recent selection and introgression facilitated high-altitude adaptation in cattle

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Science Bulletin 2024年第21期69卷 3415-3424页

作者： Yang Lyu Fuwen Wang Haijian Cheng Jing Han Ruihua Dang Xiaoting Xia Hui Wang Jincheng Zhong Johannes A.Lenstra Hucai Zhang Jianlin Han David E.MacHugh Ivica Medugorac Maulik Upadhyay Alexander SLeonard He Ding Xiaorui Yang Ming-Shan Wang Suolang Quji Basang Zhuzha Pubu Quzhen Silang Wangmu Nima Cangjue Da Wa Weidong Ma Jianyong Liu Jicai Zhang Bizhi Huang Xingshan Qi Fuqiang Li Yongzhen Huang Yun Ma Yu Wang Yuanpeng Gao Wenfa Lu Chuzhao Lei Ningbo Chen Key Laboratory of Animal Genetics Breeding and Reproduction of Shaanxi ProvinceCollege of Animal Science and TechnologyNorthwest A&F UniversityYangling 712100China Key Laboratory of Animal Production Product Qualityand SecurityMinistry of EducationCollege of Animal Science and TechnologyJilin Agricultural UniversityChangchun 130118China Institute of Animal Science and Veterinary Medicine Shandong Academy of Agricultural SciencesShandong Key Lab of Animal Disease Control and BreedingJinan 250000China College of Veterinary Medicine Northwest A&F UniversityYangling 712100China Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization Sichuan Province and Ministry of EducationSouthwest Minzu UniversityChengdu 610000China Faculty of Veterinary Medicine Utrecht UniversityUtrecht 3584 CMThe Netherlands Institute for Ecological Research and Pollution Control of Plateau Lakes School of Ecology and Environmental ScienceYunnan UniversityKunming 650500China Southwest United Graduate School Kunming 650500China Yazhouwan National Laboratory Sanya 572024China CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources Institute of Animal ScienceChinese Academy of Agriculture Sciences(CAAS)Beijing 100000China Animal Genomics Laboratory UCD School of Agriculture and Food ScienceUniversity College DublinDublin D04 V1W8Ireland UCD Conway Institute of Biomolecular and Biomedical Research University College DublinDublin D04 V1W8Ireland Population Genomics Group Department of Veterinary SciencesLMU MunichMartinsried 82152Germany Animal Genomics ETH ZurichUniversitaetstrasse 2Zurich 8006Switzerland State Key Laboratory of Genetic Resources and Evolution Yunnan Laboratory of Molecular Biology of Domestic AnimalsKunming Institute of ZoologyChinese Academy of SciencesKunming 650223China Institute of Animal Husbandry and Veterinary Science Xizang Autonomous Region Academy of Agricultural and Animal Husbandry SciencesLhasa 850000China Shigatse City Kan

During the past 3000 years,cattle on the Qinghai-Xizang Plateau have developed adaptive phenotypes under the selective pressure of hypoxia,ultraviolet(UV)radiation,and extreme *** genetic mechanism underlying this rapid adaptation is not yet well ***,we present whole-genome resequencing data for 258 cattle from 32 cattle breeds/populations,including 89 Tibetan cattle representing eight populations distributed at altitudes ranging from 3400 m to 4300 *** genomic analysis revealed that Tibetan cattle exhibited a continuous phylogeographic cline from the East Asian taurine to the South Asian indicine *** found that recently selected genes in Tibetan cattle were related to body size(HMGA2 and NCAPG)and energy expenditure(DUOXA2).We identiﬁed signals of sympatric introgression from yak into Tibetan cattle at different altitudes,covering 0.64%–3.26%of their genomes,which included introgressed genes responsible for hypoxia response(EGLN1),cold adaptation(LRP11),DNA damage repair(LATS1),and UV radiation resistance(GNPAT).We observed that introgressed yak alleles were associated with noncoding variants,including those in present *** Tibetan cattle,three yak introgressed SNPs in the EGLN1 promoter region reduced the expression of EGLN1,suggesting that these genomic variants enhance hypoxia *** together,our results indicated complex adaptation processes in Tibetan cattle,where recently selected genes and introgressed yak alleles jointly facilitated rapid adaptation to high-altitude environments.

关键词： Tibetan cattle Introgression High-altitude adaptation Noncoding variant Cis-regulation

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Cutting forces and microstructures evolution in ultraprecision machining SLM Ti6Al4V

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International Journal of Mechanical Sciences 2025年

作者： Zejia Zhao Canwen Dai Zhimin Weng Yiji Liang Yingxue Yao Suet To Yang Yang State Key Laboratory of Radio Frequency Heterogeneous Integration College of Mechatronics and Control Engineering Shenzhen University Shenzhen 518060 Guangdong China State Key Laboratory of Ultra-precision Machining Technology Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong SAR China School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen 518055 Guangdong China

Selective laser melting (SLM) has been widely used to fabricate titanium components due to the significant advantages of reducing fabrication cost in comparison to the traditional casting or forging methods. This study aims to explore the machinability of the SLM-manufactured Ti6Al4V alloy concerning material anisotropic properties of the top and front surfaces in the diamond turning. Cutting force variation of the two surfaces was systematically studied in the turning via theoretical analyses and experimental validation. The top surface was found to achieve high cutting forces and high surface roughness. Furthermore, microstructure evolution including grain refinement and phase transformation mechanisms in the subsurface of the alloy was investigated and discussed on the nanometer scale. In the subsurface, it is observed that the coarsened lamellar martensitic α' phase transformed to equiaxial nano α+β phases, and the smallest size of nano phases or grains could reach about 5 nm at the superficial layer of the subsurface. The phase or grain refinement is primarily attributed to the machining induced splitting of the coarsened α' phase to the refined α' phase and the subsequent dynamic recrystallization as well as the dislocation twinning formation. Besides, a face centered cubic (FCC) phase is discovered at the superficial layer of the subsurface. Furthermore, the lattice distortion, edge dislocations and strain distribution of the FCC phase are discussed via the inverse fast Fourier transform and geometric phase analysis.

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Model Predictive control Based on Bayesian Forecasting for a Nitrobenzene Rectifying Tower

Model Predictive Control Based on Bayesian Forecasting for a...

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第三十八届中国控制会议

作者： Bingqiang Huang Biniyam Anteneh Ayalew Xinjian Xiang Zhiyuan He Yong Gu School of Automation and Electrical Engineering Zhejiang University of Science and Technology State Key Laboratory of Industrial Control Industrial Technology Institute of Cyber-Systems and Control Zhejiang University

Step test method is a commonly used system identification method in the plant advanced process control application. Bayesian forecasting method is a kind of method based on subjective experience information and historical data. In this paper, a model identification method based on Bayesian forecasting is proposed. Combining the operators experience information and historical model data, the Bayesian method is used to predict the process model, and the model monitoring is used to abandon the abnormal data. Finally, the MPC controller is designed and the practical application of the top temperature control of the nitrobenzene rectifying tower proves the effectiveness of this method.

关键词： Model predictive control Bayesian dynamic linear model Nitrobenzene rectifying tower

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Secure and Privacy-preserving Data-sharing Framework based on Blockchain technology for Al-Najaf/Iraq Oil Refinery

Secure and Privacy-preserving Data-sharing Framework based o...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Samir M. Umran SongFeng Lu Zaid Ameen Abduljabbar Zhi Lu Bingyan Feng Lu Zheng Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Ministry of Industry and Minerals Iraqi Cement State Company Baghdad Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China College of Education for Pure Sciences University of Basrah Technical Computer Engineering Department Al-Kunooze University College Basrah Iraq School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Huazhong Numerical Control Co. Ltd Industrial Internet Research Institute Wuhan China College of Computer Science South-Central University for Nationalities Wuhan China

The industrial Internet of Things or Industry 4.0 efficiently enhances the manufacturing process in terms of raising productivity, system performance, cost reduction, and building large-scale systems. It enables the connection of numerous heterogeneous devices and sensors into the internet network through the utilization of revolutionary techniques that transfer the manufacturing paradigm to intelligent processes. The traditional industrial internet of things adopts centralized architectures and complex encryption algorithms that suffer from several cyber-security threats and lead to data leakage, privacy disclosure, and high computational and communicational costs. In our work, we proposed a decentralized, efficient, low-power, scalable, secure, privacy-preserving, and trusting architecture based on a private blockchain network/smart contract and interplanetary file system technology for the Al-NajafyIraq oil refinery factory. That enables autonomous working and provides a high level of security authentication and privacy preservation, P2P communication, remote access, immutability and information backtracking. Traditional blockchain technology has storage limitation issues, most recent works adopted external servers or the cloud for storage purposes. Our proposed scheme addresses the limitations of blockchain data storage by adopting an interplanetary file system (IPFS) network; provides an efficient data encryption mechanism at the perceptual layer by adopting a lightweight encryption algorithm, high-performance, and ultra-low-power consumption ARM Cortex-M microcontroller. In addition, our architecture succeeds in merging blockchain technology, IoTs, and an IPFS with the oil refinery as an industrial application area. Moreover, it provides an efficient framework that resists common cyber-security attacks and realizes cyber-security requirements represented by data availability, integrity, and confidentiality.

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Observed Effects on Very Early Pregnancy Linked to Ambient PM_(2.5) Exposure in China among Women Undergoing In Vitro FertilizationEmbryo Transfer

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Environment & Health 2024年第12期2卷 918-928页

作者： Changxin Lan Yichun Guan Haining Luo Xiaoling Ma Yihua Yang Hongchu Bao Cuifang Hao Xiaojin He Han Zhang Ning Gao Weinan Lin Mengyuan Ren Tianxiang Wu Chao Wang Xiaoqing Ni Chunyan Shen Jianrui Zhang Junfang Ma Rui Zhang Yin Bi Lili Zhuang Ruichao Miao Ziyi Song Tong An Zhengteng Liu Bo Pan Mingliang Fang Jing Liu Zhipeng Bai Fangang Meng Yuanchen Chen Xiaoxia Lu Yuming Guo Yunxia Cao Qun Lu Bin Wang Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijing 100191China Institute of Reproductive and Child Health Key Laboratory of Reproductive HealthNational Health and Family Planning Commission of the People’s Republic of ChinaBeijing 100191China Department of Reproductive Medicine the Third Affiliated Hospital of Zhengzhou UniversityZhengzhou 450003China Reproductive Medicine Center Tianjin Central Hospital of Gynecology ObstetricsMaternity Hospital of Nankai UniversityTianjin 300052China The First Hospital of Lanzhou University the First Clinical Medical School of Lanzhou UniversityLanzhou 730000China Guangxi Reproductive Medical Center the First Affiliated Hospital of Guangxi Medical UniversityNanning 530021China Reproductive Medicine Centre Yuhuangding Hospital of YantaiAffiliated Hospital of Qingdao UniversityYantai 264000China Qingdao Women and Children’s Hospital Affiliated Hospital of Qingdao UniversityQingdao 266555China Reproductive Medicine Center Department of Obstetrics and GynecologyShanghai General HospitalShanghai Jiao Tong University School of MedicineShanghai 200080China Department of Obstetrics and Gynecology the First Affiliated Hospital of Anhui Medical UniversityHefei 230022China Engineering Research Center of Biopreservation and Artificial Organs Ministry of EducationHefei 230022China Medical Center for Human Reproduction Beijing Chao-Yang HospitalCapital Medical UniversityBeijing 100020China Yunnan Provincial Key Lab of Soil Carbon Sequestration and Pollution Control Faculty of Environmental Science and EngineeringKunming University of Science and TechnologyKunming 650500China MOE Key Laboratory of Environmental Remediation and Ecosystem Health College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing 100012China Beijing Neurosurgical Institute Beijing Tiantan Hos

The adverse effect of ambient PM_(2.5) exposure on very early pregnancy(VEP)remains controversial among epidemiological studies but is supported by toxicological *** adopted a multicenter retrospective cohort of 141,040 cycles to evaluate the effect of PM_(2.5) exposure on the VEP using the in vitro fertilization and embryo transfer platform and high-resolution PM_(2.5) data in *** first investigated the association between PM_(2.5) exposure 1 week before and 1 week after the embryo transfer date and *** average PM_(2.5) concentrations of the 2 weeks were approximately 47μg/m^(3).The pooled results revealed a negative association between women’s accumulated PM_(2.5) exposure during the 2 weeks near the day of embryo transfer and success odds of VEP with the relative risk of 0.999(95%CI:0.997-0.999)at each increase of 10μg/*** women with the fresh cycle or one transplanted embryo were considered as a vulnerable ***,seven periods for the fresh cycle and five periods for the frozen cycle from 85 days before oocyte retrieval to the day of gestational sac detection by ultrasound detection were *** these exposure periods,no association between the average PM_(2.5) exposure and VEP risk was *** study provided large-scale population evidence for the association between PM_(2.5) exposure near embryo transfer day and VEP and identified vulnerable populations among women undergoing in vitro fertilization-embryo transfer.

关键词： Fine particulate matter Very early pregnancy IVF-ET Biochemical pregnancy Clinical pregnancy

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