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Topological phases of matter give rise to exotic physics that can be leveraged for next generation quantum computation1–3 and spintronic devices4,5. Thus, the search for topological phases and the quantum states that they exhibit have become the subject of a massive research effort in condensed matter physics. Topologically protected states have been produced in a variety of systems, including artificial lattices6–9, graphene nanoribbons (GNRs)10,11 and bismuth bilayers12,13. Despite these advances, the real-time manipulation of individual topological states and their relative coupling, a necessary feature for the realization of topological qubits, remains elusive. Guided by first-principles calculations, we spatially manipulate robust, zero-dimensional topological states by altering the topological invariants of quasi-one-dimensional artificial graphene nanostructures. This is achieved by positioning carbon monoxide molecules on a copper surface to confine its surface state electrons into artificial atoms positioned to emulate the low-energy electronic structure of graphene derivatives. Ultimately, we demonstrate control over the coupling between adjacent topological states that are finely engineered and simulate complex Hamiltonians. Our atomic synthesis gives access to an infinite range of nanoribbon geometries, including those beyond the current reach of synthetic chemistry, and thus provides an ideal platform for the design and study of novel topological and quantum states of matter.

Introduction: Atrial myxomas are rare cardiac tumours. This case report illustrates a case of myxoma in the right atrium, which is a rare location for this condition. Case Presentation: A 55 year old Myanmar (Burmese) man had two syncopes within one week. Cardiac evaluation showed changing cardiac murmur. Right atrial enlargement was obvious on electrocardiogram. Transthoracic echocardiogram revealed an echogenic mass in the right atrium which prolapsed through tricuspid valve. The myxoma was successfully excised, the base of which was attached to the interatrial septum at the lower margin of fossa ovalis. Conclusion: In this case report, we emphasize the uncommon site of myxomas in the right atrium. Clinical suspicion will lead to early diagnosis by echocardiogram and surgical excision is the curative treatment.

Reason for Withdrawal The completion of the last task is overdue for more than one year. New authors are being sought to take over this protocol. To view the published versions of this article, please click the 'Other versions' tab.

With the exponentially growing amount of information available on the Internet, an effective technique for users to discern the useful information from the unnecessary information is urgently required. Cleaning web pages for web data extraction becomes critical for improving performance of information retrieval and information extraction. So, we investigate to remove various noise patterns in Web pages instead of extracting relevant content from Web pages to get main content information. In this paper, we propose an approach that detect multiple noise patterns and remove these noise patterns from Web pages of any Web sites. The method first build DOM tree for any Web page. Our approach is based on the basic idea of Case-Based Reasoning (CBR) to find noise pattern in current Web page by matching similar noise pattern kept in Case-Based. We also apply a back propagation neural network algorithm to classify the stored various noise patterns by matching similar noise data in current Web page. We have implemented our method on several commercial Web sites and News Web sites to evaluate the performance and improvement of our approach. Experiments show that results leads to a more accurate and effectiveness of the approach.

To enable effective access to databases on the Web, it is critical to integrate the large scale deep Web sources. Therefore, schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching has some significant limitations until now. And also, there are some problems of the interfaces which often have some hidden regularities over many sources. These regularities can be essentially leveraged in enabling semantics discover of schema matching. In this paper, we focus on the specific problem of semantic heterogeneity between schema matching. We propose a clustering algorithm to organize similar sources with metadata-labeling. Our system includes a same model representation for all relational databases schemas with their own ontologies. In this paper, we represent the experimental results of semantic mapping for two schemas.

Web page classification is the automated assigning of predefined subject category to the document. Automatic web page classification is one of the most essential techniques for Web Mining given that the web is a huge repository of various information including images, videos etc. And there is a need for categorization web pages to satisfy user needs. The classification of web pages into each category exclusively relies on man power which cost much time and effort. To alleviate this manually classification problem, more researchers focus on the issue of web pages classification technology. In this paper, we proposed Random Forest Classifier (RF) based on random forest method for multi-category web page classification. The proposed RF classifier can classify web pages efficiently according to their corresponding class without using other feature selection methods. We compared the accuracy of the proposed approach to decision tree classifier using in the same Yahoo web pages. The experiments have shown that the proposed approach is suitable for the multi-category web page classification.

This study proposes a mobility enhancement in nanorobots by using the particle swarm optimization (PSO) algorithm. The study is based on the premise that the deployment of nanorobots and used for investigating within human body. The spatially distributed nanorobots collect information about the target environment by moving throughout the body. Such investigation within human body might face many challenges since nanorobots need to be decentrally controlled and algorithms need to work in lack of global information and constrained environment. This paper proposes to use particle swarm optimization as a feasible approach for self organized movement control of nanorobots. Along with the self organized behavior, coverage is also considered to achieve the complete monitoring throughout the investigation. The simulation results have approved that the proposed scheme effectively constructs a self organized mobility within the optimized coverage area.

This study presents a self organized control of nano sensor's mobility based on the particle swarm optimization (PSO) algorithm. PSO models the set of potential problem solutions as a swarm of particles moving about in a virtual search space by adapting self organizing concept. The study is based on the premise that the deployment of nanosensors and used for investigating within human body. The spatially distributed nanosensors collect information about the target environment by moving throughout the body. Movement of sensors will be addressed how sensors are perimeter covered to the target environment. There may be two kinds of issues for coverage such that insufficient coverage and covered by too many sensors in certain areas without necessary. If there is not enough coverage, the required information may not get properly. If there are more sensors than necessary, there may be some redundant nodes and it may consume more energy. Therefore, the sensors should move to the next target, which has proper coverage criteria. The simulation results have approved that the proposed scheme effectively constructs a self organized mobility within the optimized coverage area.

Almost all current database systems offer tools to export or view its content as XML which is also accepted as the emerging standard for promoting data interoperability over the web. However, XML focuses only on the syntax of data instead of the semantic and at the same time users get full freedom to model XML sources according to their local requirements. Consequently, these sources of the same domain adapt to different structures may represent data with similar semantic. In our work, we concentrate on integrating (interoperating) heterogeneous XML sources of the same domain to eliminate the structural differences of the user queries (accessing these sources) while they represent similar semantic. In this paper, we proposed architecture of semantic mediation approach based on OWL ontology. We also highlight how we can take the profit of OWL for integrating local ontologies that will be a great help for the completion of our architecture.

We have witnessed an increasing interest in GIScience and Semantic Web technology in the recent years. In today's fast growing information age, currently available methods for finding and using information on the Web are often insufficient. Toady's retrieval methods are typically limited to keywords searches or sub string matches; therefore, users may often miss critical information when searching the web. A query system is needed to support efficient geospatial information retrieval based on geospatial relations. We need to combine GIScience and Semantic Web technology. To accomplish the development of Geospatial Semantic Web, two research issues are apparent: 1sts is geospatial data query and 2ndis method to assess the semantics of available data sources. We have proposed to develop Geospatial Semantic Query System by Integrating Geospatial Reasoning. In this paper, we propose a method to extend and enhance current semantic similarity measures between geospatial entity classes. We need to measure semantic similarity and geospatial similarity to query geospatial semantic. So, our proposed method contains two portions. The first portion contains a function of semantic similarity to measure semantic similarity of geospatial entity classes. The second portion contains a function of GeoSpatial Similarity (GSS) to measure spatial similarity of geospatial entity classes that have semantic similarity. This similarity function determines spatially similar results by using the fundamental logical or Boolean operators.

Recommender systems (RS) use a database about user preferences to predict additional topics or products a new user might like. These conventional recommender systems make their recommendations based on the user times item information and don't take into consideration a temporal data that may be crucial in many applications. The distinguishing feature of the temporal database is time itself. When user preferences change over time, these may not be sufficient to simply recommend between users and items; the recommender systems must need to take the temporal data into consideration when recommending a new product. In this paper, we present a recommender system based on the Temporal data during a specific time that make predictions about which movie a user should like given a partial list of that user's tastes. Moreover we also present the temporal database queries and recommendations using the first order temporal logic operators

Nowadays, the demand of conceptual document clustering is becoming increase to manage various types of vast amount of information published on the World Wide Web. In this paper, we use formal concept analysis (FCA) method for clustering documents according to their formal contexts. Concept hierarchy of documents is built using the formal concepts of the documents in the document corpus. We use tf.idf (term frequency /spl times/ inverse document frequency) term weighting model to reduce less useful concepts from these formal concepts and the association and correlation mining techniques to analyze the relationship of terms in the document corpus.

To discover information needs among information resulting from an information retrieval (IR) system by a user, it is needed to be managed them in some effective ways. Document clustering is a common and useful technique for Web information retrieval. In this paper, we use formal concept analysis (FCA) method for reorganizing documents resulting from an IR system according to their formal concepts. We use tf.idf (term frequency x inverse document frequency) term weighting scheme in selecting terms from the documents to construct the formal context of documents and terms which will then be used to extract formal concepts among resulting documents. We use text mining technique, association rule mining, on the frequent termsets of the given domain to analyze relationships of terms existing in the resulted documents. Finally, the concept lattice of the documents is built on these associated terms to obtain formal concept based clustered resulted documents by discovering ordering relations among frequent termsets using lattice theory

The Web is rich with information. However, the data contained in the web is not well organized which makes obtaining useful information from the Web a difficult task. The successful development of extensible Markup Language (XML) as a standard to represent semi structured data makes the data contained in the Web more readable and the task of mining useful information from the Web becomes feasible. XML has become very popular for representing semistructured data and a standard for data exchange over the Web. Mining XML data from the Web is becoming increasingly important. The previous studies adopt an Apriori-like candidate set generation approach but candidate set generation is still costly. We propose that extracting association rules from XML documents without any preprocessing or postprocessing using XML query language XQuery is possible and analyze the XQuery implementation of the efficient FP-tree based mining method, FP-growth, for mining the complete set of frequent patterns by pattern fragment growth. FP-tree based mining adopts a pattern fragment growth method to avoid the costly generation of a large number of candidate sets and a partition-based, divide-and-conquer method is used. Divide-and-conquer method divides the problem into a number of subproblems and the subproblems by solving them recursively. If the subproblem sizes are small enough, however, just solve the subproblems in a straightforward manner and then combine the solutions to the subproblems into the solution for the original problem. In addition, we suggest features that need to be added into XQuery in order to make the implementation of the FP growth more efficient

In software development process, many engineering disciplines rely on engineering failure data to improve their designs. We expect that security analysts can use this approach to document and identify commonly occurring attack patterns and that the information system designer and analysts can use these patterns to develop more survivable information systems. A formal approach to security in the software life cycle is essential to protect corporate resources. Software security has been treated as an afterthought leading to a cycle of software development. Due to its criticality, security should be integrated as a formal approach in the software life cycle. It includes the critical areas of requirements analysis and specification, design and code issues, and maintenance and decommissioning of software and systems. We propose an attack detection method based on clustering technique that provide network intrusion detection systems to identify attacks with a high detection rate and a low false alarm rate in analysis and design phase of the software development life cycle. We critically focus on the analysis of security and classification of attack pattern for the software life cycle

In today's fast-growing information age, currently available methods for finding and using information on the Web are often insufficient. Today's retrieval methods are typically limited to keywords searches or sub-string matches, therefore, users may often miss critical information when searching the Web. After reviewing the real world semantic Web, additional research is needed on the geospatial semantic Web. We are rich in geospatial data but poor in up-to-date geospatial information and knowledge that are ready to be used by anyone who wants to use it. In this paper, we implement an approach for querying geospatial semantic by integrating spatial reasoning that contributes to the development of geospatial semantic Web. It is important to establish a geospatial semantics that support for effective spatial reasoning for performing geospatial semantic query. People are more understandable spatial relation (i.e. qualitative reasoning) through natural language instead of metric measurements (i.e. quantitative reasoning). Qualitative spatial reasoning is necessary because the common-sense reasoning which humans apply to spatial issues is generally qualitative. These include the use of qualitative modifiers, proxy place names to support effective spatial ontologies with a formal semantics; the representation of those semantics such that they are available to machines for processing and to people for understanding. Compared to earlier keyword-based and information retrieval techniques that rely on syntax, we use semantic approaches in our spatial queries. Semantic approaches needs the development of ontologies. We use ontology mapping because such complex semantic comparisons between domain values of different data sets cannot be done using a simple algorithm or a fully automatic method. To be efficient and effective querying, we integrate geospatial reasoning such as coordinate relationships, topological relationships, spatial inference and etc

One of the key challenges of applications concerning with Wireless Sensor Network (WSN) is finding suitable and timely information in the dynamic environment. To address these issues, this paper proposes to employ multi agent community by combined used of intelligent sensors and middle agent architecture. The idea is to use intelligent sensor as a service provider agent that announces for the active events and middle agent as a directory facilitator that assists in locating the service providers with the information requesters in the dynamic WSN environment. Simulation results have approved that proposed system enhances the information searching time, reduces the service discovery cost and communication cost.

The in vitro leishmanicidal and trypanocidal activities of a petroleum ether extract of #Oxandra espintana$ have been investigated. Four aromatic monoterpenes were isolated, of which two are novel : espintanol (3a), responsible for the antiparasite activity, and O-methylespintanol (4). Espintanol was tested in vitro on 20 strains of #Trypanosoma cruzi$ and 12 strains of #Leishmania$ spp. Its structure was determined by spectroscopic methods and confirmed by its preparation starting from carvacrol. (Résumé d'auteur)

Using cytotoxicity as a bioassay guide led to the isolation of a new active acetogenin from the seed of Annona muricata. Murisolin, 1 is the first example of a mono-tetrahydrofuran-γ-lactone acetogenin with only three hydroxyl groups. Its structure was characterised by mass spectrometry and 2D homonuclear and heteronuclear correlations nmr spectroscopy. The relative stereochemistry of four of its six chiral centers was established bh 1 H-nmr comparative spectral studies between the murisolin triacetate and some bistetrahydrofuran acetogenin acetates