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Interactions of complement proteins C1q and factor H with lipid A and Escherichia coli:further evidence that factor H regulates the classical complement pathway

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Protein & Cell 2011年第4期2卷 320-332页

作者： lee aun tan Andrew C.Yang Uday Kishore Robert B.Sim Medical Research Council Immunochemistry Unit Department of BiochemistryUniversity of OxfordSouth Parks RoadOxford OX13QUUK Present address:Department of Immunology Faculty of MedicineImperial College LondonHammersmith HospitalDu Cane RoadLondon W120NNUK St Peter’s College New Inn Hall St.Oxford OX12DLUK Present address:SUNY Downstate College of Medicine 450 Clarkson Avenue BrooklynNY 11203USA Weatherall Institute of Molecular Medicine John Radcliffe HospitalUniversity of OxfordHeadingtonOxford OX39DSUK Present address:Center for Infection Immunity and Disease MechanismsBiosciencesSchool of Health Sciences and Social CareBrunel UniversityUxbridge UB83PH West LondonUK Present address:Department of Pharmacology University of OxfordMansfield RoadOxford OX13QTUK

Proteins of the complement system are known to interact with many charged *** recently characterized binding of C1q and factor H to immobilized and liposomal anionic *** H inhibited C1q binding to anionic phospholipids,suggesting a role for factor H in regulating activation of the complement classical pathway by anionic *** extend this finding,we examined interactions of C1q and factor H with lipid A,a well-characterized activator of the classical *** report that C1q and factor H both bind to immobilized lipid A,lipid A liposomes and intact Escherichia coli *** H competes with C1q for binding to these ***,increasing the factor H:C1q molar ratio in serum diminished C4b fixation,indicating that factor H diminishes classical pathway *** recombinant forms of the Cterminal,globular heads of C1q A,B and C chains bound to lipid A and *** in a manner qualitatively similar to native C1q,confirming that C1q interacts with these targets via its globular head *** observations reinforce our proposal that factor H has an additional complement regulatory role of down-regulating classical pathway activation in response to certain *** is distinct from its role as an alternative pathway *** suggest that under physiological conditions,factor H may serve as a downregulator of bacterially-driven inflammatory responses,thereby finetuning and balancing the inflammatory response in infections with Gram-negative bacteria.

关键词： complement lipid A bacteria factor H C1q

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Complement activation by phospholipids: the interplay of factor H and C1q

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Protein & Cell 2010年第11期1卷 1033-1049页

作者： lee aun tan Bingbin Yu Francis CJ Sim Uday Kishore Robert B Sim MRC Immunochemistry Unit Department of BiochemistryUniversity of OxfordSouth Parks RdOxford OX13QUUK Department of Pharmacology University of OxfordMansfield RoadOxford OX13QTUK Centre for Infection Immunity and Disease MechanismsBiosciencesSchool of Health Sciences and Social CareBrunel UniversityUxbridge UB83PH West LondonUK Present address Department of Immunology Faculty of MedicineImperial College LondonHammersmith HospitalDu Cane RoadLondon W120NNUK Present address School of Life Sciences and Engineering Biology BuildingTsinghua UniversityBeijing 100084China

Complement proteins in blood recognize charged *** anionic phospholipid(aPL)cardiolipin binds both complement proteins C1q and factor H.C1q is an activator of the complement classical pathway,while factor H is an inhibitor of the alternative *** examine opposing effects of C1q and factor H on complement activation by aPL,we surveyed C1q and factor H binding,and complement activation by aPL,either coated on microtitre plates or in *** C1q and factor H bound to all aPL tested,and competed directly with each other for *** the aPL activated the complement classical pathway,but negligibly the alternative pathway,consistent with accepted roles of C1q and factor ***,in this system,factor H,by competing directly with C1q for binding to aPL,acts as a direct regulator of the complement classical *** regulatory mechanism is distinct from its action on the alternative *** of classical pathway activation by factor H was confirmed by measuring C4 activation by aPL in human sera in which the C1q:factor H molar ratio was adjusted over a wide *** factor H,which is regarded as a down-regulator only of the alternative pathway,has a distinct role in downregulating activation of the classical complement pathway by aPL.A factor H homologue,β2-glycoprotein-1,also strongly inhibits C1q binding to *** globular domains of C1q A,B and C chains bound aPL similarly to native C1q,confirming that C1q binds aPL via its globular heads.

关键词： complement regulation classical pathway C1q factor H anionic phospholipid

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净化河水的废锰砂和废离子交换树脂处置方法

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精细与专用化学品 2024年第5期32卷 14-16,30页

作者：张建勋盐城市大丰生态环境局经济开发区分局江苏盐城224100

在工业生产中,合法合规地取用河水,并对取用的河水进行有效净化,可以丰富工业用水的来源方式。河水净化工艺过程中通常有废锰砂、废离子交换树脂等固废产生。明确这类固废的规范处置流程既有利于提高生态环境执法效率、保护生态环境,也... 详细信息

在工业生产中,合法合规地取用河水,并对取用的河水进行有效净化,可以丰富工业用水的来源方式。河水净化工艺过程中通常有废锰砂、废离子交换树脂等固废产生。明确这类固废的规范处置流程既有利于提高生态环境执法效率、保护生态环境,也有利于降低企业的运营成本。通过模拟废锰砂、废离子交换树脂对土壤环境的影响,得出净化特定河水的废锰砂、废离子交换树脂可以作为一般固废处置的结论。

关键词：河水净化废锰砂废离子交换树脂一般固废

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欧盟碳边境调节机制对我国出口贸易的影响研究

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生态经济 2024年第8期40卷 37-44页

作者：张力左鹏顾阿伦王天鹏中国电力工程顾问集团有限公司北京100120 中国电力工程顾问集团国际工程有限公司北京100013 清华大学能源环境经济研究所北京100084

欧盟即将实施碳边境调节机制作为其实现气候和能源目标战略的一部分,试图为境内企业提供公平的竞争环境,并减少碳泄漏的风险。欧盟的碳边境调节机制会增加我国向欧盟出口产品的成本,降低我国出口产品在欧盟市场的竞争力。论文利用多区... 详细信息

欧盟即将实施碳边境调节机制作为其实现气候和能源目标战略的一部分,试图为境内企业提供公平的竞争环境,并减少碳泄漏的风险。欧盟的碳边境调节机制会增加我国向欧盟出口产品的成本,降低我国出口产品在欧盟市场的竞争力。论文利用多区域投入产出模型测算了我国与欧盟之间的贸易隐含碳排放,并基于欧盟当前的碳价水平定量评估了碳边境调节机制对我国向欧盟出口产品成本的影响。研究结果显示,当前出台的碳边境调节机制覆盖范围较窄,且主要考虑直接排放,虽然对覆盖部门的影响较为显著,但对我国与欧盟的总体贸易影响较小。不过,考虑到后续碳边境调节机制可能的政策调整方向,我国对欧盟的出口贸易可能在未来受到更大的挑战。

关键词：碳边境调节机制欧盟出口贸易投入产出模型

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Social Engineering Attack Classifications on Social Media Using Deep Learning

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Computers, Materials & Continua 2023年第3期74卷 4917-4931页

作者： Yichiet aun Ming-lee Gan Nur Haliza Binti Abdul Wahab Goh Hock Guan Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanPerakMalaysia Faculty of Engineering Universiti Teknologi MalaysiaJohorMalaysia

In defense-in-depth,humans have always been the weakest link in ***,unlike common threats,social engineering poses vulnerabilities not directly quantifiable in penetration *** skilled social engineers trick users into giving up information voluntarily through attacks like phishing and *** Engineering(SE)in social media is structurally similar to regular posts but contains malicious intrinsic meaning within the sentence *** this paper,a novel SE model is trained using a Recurrent Neural Network Long Short Term Memory(RNN-LSTM)to identify well-disguised SE threats in social media *** use a custom dataset crawled from hundreds of corporate and personal Facebook ***,the social engineering attack detection pipeline(SEAD)is designed to filter out social posts with malicious intents using domain ***,each social media post is tokenized into sentences and then analyzed with a sentiment analyzer before being labelled as an anomaly or normal training ***,we train an RNN-LSTM model to detect five types of social engineering attacks that potentially contain signs of information *** experimental result showed that the Social Engineering Attack(SEA)model achieves 0.84 in classification precision and 0.81 in recall compared to the ground truth labeled by network *** experimental results showed that the semantics and linguistics similarities are an effective indicator for early detection of SEA.

关键词： Social engineering attack cybersecurity machine learning(ML) artificial neural network(ANN) random forest classifier decision tree(DT)classifier

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Pandemic Analysis and Prediction of COVID-19 Using Gaussian Doubling Times

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Computers, Materials & Continua 2022年第7期72卷 833-849页

作者： Saleh Albahli Farman Hassan Ali Javed aun Irtaza Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of Computer Science and Engineering Oakland UniversityMIUSA Department of Computer and Electrical Engineering University of MichiganDearbornUSA

COVID-19 has become a pandemic,with cases all over the world,with widespread disruption in some countries,such as Italy,US,India,South Korea,and *** and reliable detection of COVID-19 is mandatory to control the spread of ***,prediction of COVID-19 spread in near future is also crucial to better plan for the disease *** this purpose,we proposed a robust framework for the analysis,prediction,and detection of *** make reliable estimates on key pandemic parameters and make predictions on the point of inflection and possible washout time for various countries around the *** estimates,analysis and predictions are based on the data gathered fromJohns Hopkins Center during the time span of April 21 to June 27,*** use the normal distribution for simple and quick predictions of the coronavirus pandemic model and estimate the parameters of Gaussian curves using the least square parameter curve fitting for several countries in different *** predictions rely on the possible outcomes of Gaussian time evolution with the central limit theorem of statistics the predictions to be well *** parameters of Gaussian distribution,i.e.,maximumtime and width,are determined through a statisticalχ^(2)-fit for the purpose of doubling times after April 21,*** COVID-19 detection,we proposed a novel method based on the Histogram of Oriented Gradients(HOG)and CNN in multi-class classification scenario i.e.,Normal,COVID-19,viral pneumonia *** results show the effectiveness of our framework for reliable prediction and detection of COVID-19.

关键词： Prediction coronavirus time-series prediction gaussian mathematical model pandemic spreading

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Recognition and Detection of Diabetic Retinopathy Using Densenet-65 Based Faster-RCNN

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Computers, Materials & Continua 2021年第5期67卷 1333-1351页

作者： Saleh Albahli Tahira Nazir aun Irtaza Ali Javed Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of Software Engineering University of Engineering and TechnologyTaxila47050Pakistan

Diabetes is a metabolic disorder that results in a retinal complication called diabetic retinopathy(DR)which is one of the four main reasons for sightlessness all over the *** usually has no clear symptoms before the onset,thus making disease identication a challenging *** healthcare industry may face unfavorable consequences if the gap in identifying DR is not lled with effective ***,our objective is to develop an automatic and cost-effective method for classifying DR *** this work,we present a custom Faster-RCNN technique for the recognition and classication of DR lesions from retinal *** pre-processing,we generate the annotations of the dataset which is required for model ***,introduce DenseNet-65 at the feature extraction level of Faster-RCNN to compute the representative set of key ***,the Faster-RCNN localizes and classies the input sample into ve *** experiments performed on a Kaggle dataset comprising of 88,704 images show that the introduced methodology outperforms with an accuracy of 97.2%.We have compared our technique with state-of-the-art approaches to show its robustness in term of DR localization and ***,we performed cross-dataset validation on the Kaggle and APTOS datasets and achieved remarkable results on both training and testing phases.

关键词： Deep learning medical informatics diabetic retinopathy healthcare computer vision

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Intrusion Detection Systems in Internet of Things and Mobile Ad-Hoc Networks

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Computer Systems Science & Engineering 2022年第3期40卷 1199-1215页

作者： Vasaki Ponnusamy Mamoona Humayun NZJhanjhi aun Yichiet Maram Fahhad Almufareh Faculty of Information and Communication Technology Universiti Tunku Abdul RahmanKamparMalaysia Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufSaudi Arabia School of Computer Science and Engineering(SCE) Taylor’s UniversitySelangorMalaysia

Internet of Things(IoT)devices work mainly in wireless mediums;requiring different Intrusion Detection System(IDS)kind of solutions to leverage 802.11 header information for intrusion ***-specific traffic features with high information gain are primarily found in data link layers rather than application layers in wired *** survey investigates some of the complexities and challenges in deploying wireless IDS in terms of data collection methods,IDS techniques,IDS placement strategies,and traffic data analysis *** paper’s main finding highlights the lack of available network traces for training modern machine-learning models against IoT specific ***,the Knowledge Discovery in Databases(KDD)Cup dataset is reviewed to highlight the design challenges of wireless intrusion detection based on current data attributes and proposed several guidelines to future-proof following traffic capture methods in the wireless network(WN).The paper starts with a review of various intrusion detection techniques,data collection methods and placement *** main goal of this paper is to study the design challenges of deploying intrusion detection system in a wireless *** detection system deployment in a wireless environment is not as straightforward as in the wired network environment due to the architectural *** this paper reviews the traditional wired intrusion detection deployment methods and discusses how these techniques could be adopted into the wireless environment and also highlights the design challenges in the wireless *** main wireless environments to look into would be Wireless Sensor Networks(WSN),Mobile Ad Hoc Networks(MANET)and IoT as this are the future trends and a lot of attacks have been targeted into these *** it is very crucial to design an IDS specifically to target on the wireless networks.

关键词： Internet of Things MANET intrusion detection systems wireless networks

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Time to forge ahead:The Internet of Things for healthcare

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Digital Communications and Networks 2023年第1期9卷 223-235页

作者： Denzil Furtado Andre F.Gygax Chien aun Chan Ashley I.Bush Melbourne Dementia Research Centre&Department of Chemical Engineering University of MelbourneVIC3010Australia Faculty of Business and Economics University of MelbourneVIC3010Australia Department of Electrical and Electronic Engineering University of MelbourneVIC3010Australia Florey Institute of Neuroscience and Mental Health University of MelbourneVIC3010Australia

Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to overburdened hospital systems,to dealing with the COVID-19 ***,despite considerable recent technological advances,the pace of successful implementation of promising IoT healthcare initiatives has been *** inspire more productive collaboration,we present here a simple—but surprisingly underrated—problemoriented approach to developing healthcare *** further assist in this effort,we reviewed the various commercial,regulatory,social/cultural,and technological factors in the development of the *** propose that fog computing—a technological paradigm wherein the burden of computing is shifted from a centralized cloud server closer to the data source—offers the greatest promise for building a robust and scalable healthcare IoT *** this end,we explore the key enabling technologies that underpin the fog architecture,from the sensing layer all the way up to the *** is our hope that ongoing advances in sensing,communications,cryptography,storage,machine learning,and artificial intelligence will be leveraged in meaningful ways to generate unprecedented medical intelligence and thus drive improvements in the health of many people.

关键词： Internet of Things Healthcare Information Fog computing Artificial intelligence Machine learning Big data COVID-19 pandemic

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IoT Wireless Intrusion Detection and Network Traffic Analysis

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Computer Systems Science & Engineering 2022年第3期40卷 865-879页

作者： Vasaki Ponnusamy aun Yichiet NZ Jhanjhi Mamoona humayun MaramFahhad Almufareh University Tunku Abdul Rahman Kampar31900Malaysia School of Computer Science and Engineering(SCE) Taylor’s UniversitySelangorMalaysia Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufSaudi Arabia

Enhancement in wireless networks had given users the ability to use the Internet without a physical connection to the *** every Internet of Things(IoT)devices such as smartphones,drones,and cameras use wireless technology(Infrared,Bluetooth,IrDA,IEEE 802.11,etc.)to establish multiple interdevice connections *** the flexibility of the wireless network,one can set up numerous ad-hoc networks on-demand,connecting hundreds to thousands of users,increasing productivity and profitability ***,the number of network attacks in wireless networks that exploit such flexibilities in setting and tearing down networks has become very *** can launch attacks since there is no first line of defense in an ad hoc network setup besides the standard IEEE802.11 WPA2 *** feasible countermeasure is to deploy intrusion detection systems at the edge of these ad hoc networks(Network-based IDS)or at the node level(Host-based IDS).The challenge here is that there is no readily available benchmark data available for IoT network *** this benchmark data is very tedious as IoT can work on multiple platforms and networks,and crafting and labelling such dataset is very *** research aims to study the characteristics of existing datasets available such as KDD-Cup and NSL-KDD,and their suitability for wireless IDS *** hypothesize that network features are parametrically different depending on the types of network and assigning weight dynamically to these features can potentially improve the subsequent threat *** paper analyses packet and flow features for the data packet captured on a wireless network rather than a wired *** domain heuristcs and early classification results,the paper had identified 19 header fields exclusive to wireless network that contain high information gain to be used as ML features in Wireless IDS.

关键词： IoT machine learning traffic features IDS KDD-CUP NSL-KDD

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