检索结果-南通市图书馆

Takotsubo cardiomyopathy following envenomation:An updated review

World Journal of Cardiology 2023年第1期15卷 33-44页

作者： Ajay K Mishra Anu A George Kevin John John Pramukh Arun Kumar Mahati Dasari mohammed afraz pasha Michelle Hadley Division of Cardiology Saint Vincent HospitalWorcesterMA 01608United States Department of Medicine Saint Vincent HospitalWorcesterMA 01608United States Department of Medicine Tufts Medical CenterBostonMA 02111United States Department of Medicine North Alabama Medical CenterFlorenceAL 35630United States

BACKGROUND Takotsubo cardiomyopathy(TTC)can be diagnosed in patients presenting with clinical features of acute coronary syndrome(ACS)by using Mayo clinic *** precipitators have been attributed to causing *** it has been reported to occur following an acute *** This review describes the various patterns,mechanisms,and outcomes of envenomation induced *** In this review,we included all studies on“TTC”and“envenomation”published in the various databases before June *** be included in the review articles had to have a distinct diagnosis of TTC and an envenomation RESULTS A total of 20 patients with envenomation induced TTC were *** episodes of envenomation induced TTC were reported following a bee sting,scorpion sting,and snake *** and anxiety related to the sting,direct catecholamine toxicity and administration of exogenous beta-adrenergic agents have been commonly postulated to precipitate TTC in these patients.95%of these patients presented with a clinical picture of *** of these patients also fulfill at least 3 out of 4 criteria of Mayo clinic criteria for *** evidence of Apical TTC was noted in 72%of patients.94%of these patients had clinical improvement following optimal management and 35%of these patients were treated with guideline directed medications for heart *** Envenomation following multiple insect stings and reptile bites can precipitate *** reported envenomation related TTC has been due to bee stings and scorpion *** mechanisms causing TTC were fear,anxiety,and stress of *** of these patients present with clinical presentation of ACS,ST elevation,and elevated *** most common type of TTC in these patients is Apical,which improved following medical management.

关键词： Takotsubo cardiomyopathy Envenomation Mechanism Outcome

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Modeling of Combined Economic and Emission Dispatch Using Improved Sand Cat Optimization Algorithm

引用

Computers, Materials & Continua 2023年第6期75卷 6145-6160页

作者： Fadwa Alrowais Jaber S.Alzahrani Radwa Marzouk Abdullah Mohamed Gouse pasha mohammed Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Combined Economic and Emission Dispatch(CEED)task forms multi-objective optimization problems to be resolved to minimize emission and fuel *** disadvantage of the conventional method is its incapability to avoid falling in local optimal,particularly when handling nonlinear and complex *** have recently received considerable attention due to their enhanced capacity to prevent local optimal solutions in addressing all the optimization problems as a black ***,this paper focuses on the design of an improved sand cat optimization algorithm based CEED(ISCOA-CEED)*** ISCOA-CEED technique majorly concen-trates on reducing fuel costs and the emission of generation ***,the presented ISCOA-CEED technique transforms the equality constraints of the CEED issue into inequality ***,the improved sand cat optimization algorithm(ISCOA)is derived from the integration of tra-ditional SCOA with the Levy Flight(LF)*** last,the ISCOA-CEED technique is applied to solve a series of 6 and 11 generators in the CEED *** experimental validation of the ISCOA-CEED technique ensured the enhanced performance of the presented ISCOA-CEED technique over other recent approaches.

关键词： Economic and emission dispatch multi-objective optimization metaheuristics fuel cost minimization sand cat optimization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

User Behavior Traffic Analysis Using a Simplified Memory-Prediction Framework

引用

Computers, Materials & Continua 2022年第2期70卷 2679-2698页

作者： Rahmat Budiarto Ahmad A.Alqarni mohammed YAlzahrani Muhammad Fermi pasha Mohamed FazilMohamed Firdhous Deris Stiawan College of Computer Science&IT Albaha UniversityAlaqiq65779-7738Saudi Arabia Malaysia School of Information Technology Monash UniversityBandar Sunway47500Malaysia Department of Information Technology University of MoratuwaMoratuwa10400Sri Lanka Faculty of Computer Science Universitas SriwijayaIndralaya30662Indonesia

As nearly half of the incidents in enterprise security have been triggered by insiders,it is important to deploy a more intelligent defense system to assist enterprises in pinpointing and resolving the incidents caused by insiders or malicious software(malware)in *** to do so may cause a serious loss of reputation as well as *** the same time,modern network traffic has dynamic patterns,high complexity,and large volumes that make it more difficult to detect malware *** ability to learn tasks sequentially is crucial to the development of artificial *** neurogenetic computation models with deep-learning techniques are able to detect complex patterns;however,the models have limitations,including catastrophic forgetfulness,and require intensive computational *** defense systems using deep-learning models require more time to learn new traffic patterns,they cannot perform fully online(on-the-fly)***,an intelligent attack/malware detection system with on-the-fly learning capability is *** this paper,a memory-prediction framework was adopted,and a simplified single cell assembled sequential hierarchical memory(***)model instead of the hierarchical temporal memory(HTM)model is proposed to speed up learning convergence to achieve onthe-fly *** *** consists of a Single Neuronal Cell(SNC)model and a simplified Sequential Hierarchical Superset(SHS)*** *** implemented as the prediction engine of a user behavior analysis tool to detect insider attacks/*** experimental results show that the proposed memory model can predict users’traffic behavior with accuracy level ranging from 72%to 83%while performing on-the-fly learning.

关键词： Machine learning memory prediction framework insider attacks user behavior analytics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nanoscaled MnSnO_(2)@CsPbBr_(3) quantum dots heterostructure photocatalyst as efficient organic pollutants degradation by peroxymonosulfate;DFT calculation

引用

Journal of Materials Science & Technology 2023年第22期153卷 41-55页

作者： Raqiqa Tur Rasool Ghulam Abbas Ashraf Mohsin pasha Muhammad Farooq Saleem Djamel Ghernaout mohammed M.Fadhali Hai Guo Department of Physics Zhejiang Normal UniversityJinhuaZhejiang 321004China School of Chemistry and Chemical Engineering Frontiers Science Center for Transformative MoleculesShanghai Jiao Tong UniversityShanghai 200240China GBA branch of Aerospace Information Research Institute Chinese Academy of SciencesGuangzhou 510700China Chemical Engineering Department College of EngineeringUniversity of Ha’ilPO Box 2440Ha’il 81441Saudi Arabia Chemical Engineering Department Faculty of EngineeringUniversity of BlidaPO Box 270Blida 09000Algeria Department of Physics Faculty of ScienceJazan UniversityJazan 45142Saudi Arabia Department of Physics Faculty of ScienceIbb University 70270Yemen

In this work,we developed a promising photocatalyst in CsPbBr_(3) quantum dots(QDs)because of their exceptional optoelectronic ***,QDs applications in the field of photocatalysis were mainly hampered by their poor stability and insufficient charge transfer ***,a novel and efficient MnSnO_(2)@CsPbBr_(3)(MSO@QDs)nanocomposite was first time effectively designed and synthe-sized by a wet impregnation method for peroxymonosulfate(PMS)activation under the *** newly generated interface phase of QDs between MnSnO_(2)(MSO)showed great potential to improve light ab-sorption,leading to effective separation and transfer of photoelectron-hole *** novel nanocompos-ite MSO@QDs showed great Flurbiprofen(FL)removal efficiency under the PMS/Light *** should be noted that this nanocomposite removed 85.74%of FL in just 70 min,which was almost 1.11 and 2.51 times greater than using pure QDs and pure MSO,*** on thorough measurements of structural analysis,Brunauer-Emmett-Teller(BET),UV-vis spectra,electrochemical impedance spec-troscopy(EIS),transient photocurrent response,and a potential mechanism for organic pollutants degra-dation over MSO@QDs nanocomposite was *** principal reactive species of photoinduced holes(h^(+)),i.e.O_(2)^(˙−),SO_(4)^(˙−),^(˙)OH,and non-radical(^(1)O_(2))were characterized via scavengers’technique and electron paramagnetic resonance(EPR)*** highest photocatalytic performance for the re-moval of MO,MB,and IBU was demonstrated by MSO@QDs nanocomposite/PMS,revealing their excellent ability to remove organic pollutants through ***,the developed nanocompos-ite exhibited good stability in an aqueous *** to computational investigation using the density functional theory(DFT)method,the site’s higher Fukui index f^(0) value corresponds to a greater propensity to be attacked by reactive *** work offers a fresh perspective on developi

关键词： CsPbBr_(3)QDs MnSnO_(2) Peroxymonosulfate Nanocomposite Photocatalyst Organic pollutants DFT

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Efficient Blockchain-Based Healthcare System Using Artificial Intelligence

引用

Computers, Materials & Continua 2022年第5期71卷 2721-2738页

作者： Aitizaz Ali Muhammad Fermi pasha Ong Huey Fang Jehad Ali mohammed A.Al.Zain Mehedi Masud Department of Software Systems and Cyber-Security School of ITMonash University47500Subang JayaMalaysia Department of Computer Engineering and Department of AI Convergence Network Ajou UniversitySuwon16499Korea Department of Information Technology College of Computers and Information TechnologyTaif University11099Taif21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif University11099Taif21944Saudi Arabia

Personal health records and electronic health records are considered as the most sensitive information in the healthcare *** solutions have been provided for implementing the digital health system using blockchain,but there are several challenges,such as secure access control and privacy is one of the prominent ***,we propose a novel framework and implemented an attribute-based access control system using ***,we have also integrated artificial intelligence(AI)based approach to identify the behavior and activity for security *** current methods only focus on the related clinical records received from a medical ***,existing methods are too inflexible to resourcefully sustenance metadata changes.A secure patient data access framework is proposed in this research,integrating blockchain,trust chain,and blockchain methods to overcome these problems in the literature for sharing and accessing digital healthcare *** have used a neural network and classifier to categorize the user access to our proposed *** proposed scheme provides an intelligent and secure blockchain-based access control system in the digital healthcare *** results surpass the existing solutions by collecting attributes such as the number of transactions,number of nodes,transaction delay,block creation,and signature verification time.

关键词： Personal health records blockchain technology artificial intelligence access control attributes health care system

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Optimal Fuzzy Logic Enabled Intrusion Detection for Secure IoT-Cloud Environment

引用

Computers, Materials & Continua 2023年第3期74卷 6737-6753页

作者： Fatma S.Alrayes Nuha Alshuqayran Mohamed K Nour Mesfer Al Duhayyim Abdullah Mohamed Amgad Atta Abdelmageed mohammed Gouse pasha mohammed Ishfaq Yaseen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Recently,Internet of Things(IoT)devices have developed at a faster rate and utilization of devices gets considerably increased in day to day *** the benefits of IoT devices,security issues remain challenging owing to the fact that most devices do not include memory and computing resources essential for satisfactory security ***,IoT devices are vulnerable to different kinds of attacks.A single attack on networking system/device could result in considerable data to data security and *** the emergence of artificial intelligence(AI)techniques can be exploited for attack detection and classification in the IoT *** this view,this paper presents novel metaheuristics feature selection with fuzzy logic enabled intrusion detection system(MFSFL-IDS)in the IoT *** presented MFSFL-IDS approach purposes for recognizing the existence of intrusions and accomplish security in the IoT *** achieve this,the MFSFL-IDS model employs data pre-processing to transform the data into useful ***,henry gas solubility optimization(HGSO)algorithm is applied as a feature selection approach to derive useful feature ***,adaptive neuro fuzzy inference system(ANFIS)technique was utilized for the recognition and classification of intrusions in the ***,binary bat algorithm(BBA)is exploited for adjusting parameters involved in the ANFIS model.A comprehensive experimental validation of the MFSFL-IDS model is carried out using benchmark dataset and the outcomes are assessed under distinct *** experimentation outcomes highlighted the superior performance of the MFSFL-IDS model over recentapproaches with maximum accuracy of 99.80%.

关键词： Cloud computing security fuzzy logic intrusion detection internet of things metaheuristics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Political Optimizer with Probabilistic Neural Network-Based Arabic Comparative Opinion Mining

引用

Intelligent Automation & Soft Computing 2023年第6期36卷 3121-3137页

作者： Najm Alotaibi Badriyya B.Al-onazi Mohamed K.Nour Abdullah Mohamed Abdelwahed Motwakel Gouse pasha mohammed Ishfaq Yaseen mohammed Rizwanullah Prince Saud AlFaisal Institute for Diplomatic Studies Riyadh13369Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16242Saudi Arabia

Opinion Mining(OM)studies in Arabic are limited though it is one of the most extensively-spoken languages *** the interest in OM studies in the Arabic language is growing among researchers,it needs a vast number of investigations due to the unique morphological principles of the *** OM studies experience multiple challenges owing to the poor existence of language sources and Arabic-specific linguistic *** comparative OM studies in the English language are wide and ***,comparative OM studies in the Arabic language are yet to be established and are still in a nascent *** unique features of the Arabic language make it essential to expand the studies regarding the Arabic *** contains unique featuressuchasdiacritics,elongation,*** study proposes a Political Optimizer with Probabilistic Neural Network-based Comparative Opinion Mining(POPNN-COM)model for the Arabic *** proposed POPNN-COM model aims to recognize comparative and non-comparative texts in Arabic in the context of social ***,the POPNN-COM model involves different levels of data pre-processing to transform the input data into a useful ***,the pre-processed data is fed into the PNN model for classification and recognition of the data under different class *** last,the PO algorithm is employed for fine-tuning the parameters involved in this model to achieve enhanced *** proposed POPNN-COM model was experimentally validated using two standard datasets,and the outcomes established the promising performance of the proposed POPNN-COM method over other recent approaches.

关键词： Comparative opinion mining Arabic text social media parameter tuning machine learning political optimizer

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Modified Garden Balsan Optimization Based Machine Learning for Intrusion Detection

引用

Computer Systems Science & Engineering 2023年第8期46卷 1471-1485页

作者： Mesfer Al Duhayyim Jaber S.Alzahrani Hanan Abdullah Mengash Mrim M.Alnfiai Radwa Marzouk Gouse pasha mohammed mohammed Rizwanullah Amgad Atta Abdelmageed Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityAl QunfidhahSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The Internet of Things(IoT)environment plays a crucial role in the design of smart *** and privacy are the major challenging problems that exist in the design of IoT-enabled real-time *** susceptibilities in IoT-based systems pose security threats which affect smart environment *** detection systems(IDS)can be used for IoT environments to mitigate IoT-related security attacks which use few security *** paper introduces a modified garden balsan optimizationbased machine learning model for intrusion detection(MGBO-MLID)in the IoT cloud *** presented MGBO-MLID technique focuses on the identification and classification of intrusions in the IoT cloud ***,the presented MGBO-MLID model applies min-max normalization that can be utilized for scaling the features in a uniform *** addition,the MGBO-MLID model exploits the MGBO algorithm to choose the optimal subset of ***,the attention-based bidirectional long short-term(ABiLSTM)method can be utilized for the detection and classification of *** the final level,the Aquila optimization(AO)algorithm is applied as a hyperparameter optimizer to fine-tune the ABiLSTM *** experimental validation of the MGBO-MLID method is tested using a benchmark *** extensive comparative study reported the betterment of the MGBO-MLID algorithm over recent approaches.

关键词： Deep learning internet of things cloud computing feature selection intrusion detection

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Quantum Particle Swarm Optimization with Deep Learning-Based Arabic Tweets Sentiment Analysis

引用

Computers, Materials & Continua 2023年第5期75卷 2575-2591页

作者： Badriyya BAl-onazi Abdulkhaleq Q.A.Hassan Mohamed K.Nour Mesfer Al Duhayyim Abdullah Mohamed Amgad Atta Abdelmageed Ishfaq Yaseen Gouse pasha mohammed Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of English College of Science and Arts at MahayilKing Khalid UniversityAbha62217Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24231Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16828Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16436Saudi Arabia

Sentiment Analysis(SA),a Machine Learning(ML)technique,is often applied in the *** SA technique is specifically applied to the data collected from social media *** research studies conducted earlier upon the SA of the tweets were mostly aimed at automating the feature extraction *** this background,the current study introduces a novel method called Quantum Particle Swarm Optimization with Deep Learning-Based Sentiment Analysis on Arabic Tweets(QPSODL-SAAT).The presented QPSODL-SAAT model determines and classifies the sentiments of the tweets written in ***,the data pre-processing is performed to convert the raw tweets into a useful ***,the word2vec model is applied to generate the feature *** Bidirectional Gated Recurrent Unit(BiGRU)classifier is utilized to identify and classify the ***,the QPSO algorithm is exploited for the optimal finetuning of the hyperparameters involved in the BiGRU *** proposed QPSODL-SAAT model was experimentally validated using the standard *** extensive comparative analysis was conducted,and the proposed model achieved a maximum accuracy of 98.35%.The outcomes confirmed the supremacy of the proposed QPSODL-SAAT model over the rest of the approaches,such as the Surface Features(SF),Generic Embeddings(GE),Arabic Sentiment Embeddings constructed using the Hybrid(ASEH)model and the Bidirectional Encoder Representations from Transformers(BERT)model.

关键词： Sentiment analysis Arabic tweets quantum particle swarm optimization deep learning word embedding

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Modified Sine Cosine Optimization with Adaptive Deep Belief Network for Movie Review Classification

引用

Intelligent Automation & Soft Computing 2023年第7期37卷 283-300页

作者： Hala J.Alshahrani Abdulbaset Gaddah Ehab S.Alnuzaili Mesfer Al Duhayyim Heba Mohsen Ishfaq Yaseen Amgad Atta Abdelmageed Gouse pasha mohammed Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of English College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer63311Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16828Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sentiment analysis(SA)is a growing field at the intersection of computer science and computational linguistics that endeavors to automati-cally identify the sentiment presented in *** linguistics aims to describe the fundamental methods utilized in the formation of computer methods for understanding natural *** is classified as a negative or positive assessment articulated through *** can be commonly used for the movie review classification that involves the automatic determination that a review posted online(of a movie)can be negative or positive toward the thing that has been *** learning(DL)is becoming a powerful machine learning(ML)method for dealing with the increasing demand for precise *** this motivation,this study designs a computational intelligence enabled modified sine cosine optimization with a adaptive deep belief network for movie review classification(MSCADBN-MVC)*** major intention of the MSCADBN-MVC technique is focused on the identification of sentiments that exist in the movie review ***,the MSCADBN-MVC model follows data pre-processing and the word2vec word embedding *** the classification of sentiments that exist in the movie reviews,the ADBN model is utilized in this *** last,the hyperparameter tuning of the ADBN model is carried out using the MSCA technique,which integrates the Levy flight concepts into the standard sine cosine algorithm(SCA).In order to demonstrate the significant performance of the MSCADBN-MVC model,a wide-ranging experimental analysis is performed on three different *** comprehensive study highlighted the enhancements of the MSCADBN-MVC model in the movie review classification process with maximum accuracy of 88.93%.

关键词： Computational linguistics movie review analysis sentiment analysis sentiment classification deep learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：