dataesr/scientific-paragraphs-categorization huggingface dataset:
The only exceptions to these rules are a few prokaryotic and invertebrate receptors. To look for a possible functional significance of these residues, we investigated their variability more specifically among GABA receptor subunits through sequence alignments of vertebrate GABA A subunits from the Uniprot database. The pattern is conserved across subtypes and species: all annotated subunits of types a and g possess both cysteines, whereas b subunits have the cysteine on M3 but lack that on M1. This extends to vertebrates (most of the available sequences), but also to invertebrates such as Lymnea and Drosophila. The only exception we found is a GABA receptor subunit b from C. elegans (Uniprot ID O18276), which has both cysteines. This raises the distinct possibility that the presence or absence of these disulfide bridges is not neutral, but could play a specific functional role in a and g subunits of GABA A Rs at least in all vertebrate species.
This article describes the research project MAEOS, whose purpose is to model the organizational and strategic development of SMEs. The main objective of this project is to improve the efficiency and performance of business advice given to this kind of companies by establishing a set of methods and software tools for analysis and diagnosis. In order to achieve this, a multi-disciplinary team was created in which two main research areas are represented: artificial intelligence and management science. In this work several key questions of the knowledge engineering field are addressed by the team: how to extract theoretical knowledge (e. g. from scientific works in management science) and practical one (e. g. from consultants); how to formalize it and use it to assist consultants in their daily work.
Methodology In the framework of MAEOS project, two software modules have been developed for the moment: a module for diagnosis of the situation of SMEs based on diverse theoretical knowledge and a recommendation module that provides models of recommendations for improving this situation according to a goal, which could be analyzed and supplemented by recommendations provided by the consultant from his previous experience. If these recommendations are followed, an "ideal" situation of the company should be reached. The consultant visits an SME and based on his observations, he draws a map of the current situation of the company using the diagnosis module. With the recommendation module, he is able to suggest different courses of action to improve the current identified status of the company.
DISKO DISKO provides a user-friendly interface to facilitate the acquisition and visualisation of results, with two main goals • to reason about a real business from the ontologies that have been formalized in DONNA • to capitalize the past cases in order to assist the reasoning. It should be noted that the modules for diagnosis and recommendation are already operational and that are currently constrained only by the amount of ontologies formalized in DONNA. The experience capitalization module is under development. The DISKO interface (figure  7 ) allows the user to choose the ontology to be instantiated, to visualize the instances in text or graphical mode, to perform the analysis and to launch the diagnosis. Unlike current trends, which try to represent knowledge in a homogeneous knowledge base that covers the whole domain of a problem, our choice is different.
INTRODUCTION Business intelligence (BI) is a broad field related to integrating, storing and analyzing data to help decisionmakers in many domains (from business to administration, health, and environment) make better decisions using analytics methods include reporting, on-line analytical processing (OLAP), and data mining. With the increasing success of cloud computing, cloud business intelligence "as a service" offerings have arisen, both from cloud start-ups and major BI industry vendors. Beyond porting BI features into the cloud, which already implies numerous issues (e. g. , BigData/NoSQL database modeling and storage, data localization, data marketplaces, security and privacy, performance, cost and usage models. ), this trend also poses new, broader challenges for making data analytics available to small and medium-size enterprises (SMEs), non-governmental organizations, web communities (e.
g. , supported by social networks), and even the average citizen. This vision requires new integration and deployment models. For example, some deployments would benefit from an integrated database of private and open data. Thus, Cloud Intelligence is not only a current technological and research challenge, but also an important societal stake, since people increasingly demand open data (e. g. , the Spanish indignados), which they possibly mix with private data, and analyze with tools with advanced collaborative features, enabling users to share and re-use business intelligence concepts and analysis results world-wide. The First International Workshop on Cloud Intelligence (Cloud-I 2012) [1] was held in conjunction with VLDB 2012 in Istanbul, Turkey on August 31, with the aim of becoming an interdisciplinary, regular exchange forum for researchers, industry and practitioners, as well as all potential users of Cloud Intelligence.
Session 1: Data and Knowledge Management The position paper entitled "Towards a Hybrid Row-Column Database for a Cloud-based Medical Data Management System", by Baraa Mohamad, Laurent d'Orazio and Le Gruenwald, pinpoints the challenges in integrating high-volume, heterogeneous medical data in the form of DICOM files in the cloud. A novel hybrid "row-column", two-level database architecture is pro-posed, where mandatory/frequently used attributes and attributes frequently accessed together are stored in a row-oriented database, and optional/private attributes are stored in a column-oriented database. This architecture is easy to use, extensible, efficient and allows ad-hoc queries over DICOM files, while benefiting from the elasticity, billing by use, and scalability of the cloud. Yasin Silva, Jason Reed and Lisa Tsosie, in "Map-Reduce-based Similarity Join for Metric Spaces", study cloud-based similarity joins (a sparsely studied issue up till now).
The former are used to specify the GAINS (Greenhouse Gas -Air Pollution Interactions and Synergies) data warehouse, while the latter help publish key data of scientific analysis in a transparent manner. In their position paper "On Saying "Enough Already!" in MapReduce", Christos Doulkeridis and Kjetil Nørvåg criticize the brute force approach of MapReduce, which leads to performing redundant work, especially in the case of top-k queries. Different techniques that allow the efficient processing of top-k queries without exhaustively accessing input data are investigated. Various individual approaches and combinations of such approaches are proposed to provide the first steps towards integrating efficient top-k processing in MapReduce.
ACKNOWLEDGEMENTS The Cloud-I Chairs would like to thank all the authors of submitted papers for their interest in the workshop and the high quality of the submitted papers. We would also like to thank all the referees (both PC members and external reviewers) for their careful and dedicated work, both during the reviewing and the discussion phases. Working in cooperation with this Program Committee has been both an honor and a pleasure. Finally, we would like to express our gratitude to the members of the Organizing Committee of VLDB 2012, especially the Workshop Chairs James Joshi, Hakan Ferhatosmanoglu, and Andreas Wombacher, for their support in organizing this workshop.
g. OPNET, NS-3. The modeling language (ArchiMate) relies on the EA standard, thus it has an architecture that shares the different viewpoints 1  in the design thanks to the multiple layers that it has  (business, application, technology). Representing these highly abstract layers in the simulation program helps, at least, to check the data flow between the design elements (from cause to the result). Based on that context and problematic, the research question is: How to transform the multiple viewpoints of ArchiMate from the TS highly abstract design to the scenario of classical network simulators?. In this paper we present our contribution in conveying the viewpoints represented in ArchiMate/EA to the simulation scenario. We rely on our code gen-erator presented in  (Alloush et al. , 2013)  where we select NS-3 as a target tool.
As benefits and in addition to the rapid and automated code generation of the simulation program  (Alloush et al. , 2013) , our contribution helps the TS designer during the evaluation of the design model by: (1) improving the clarity of the generated code as it applies some object oriented "class concept"; (2) improving the reconfigurability of the simulation parameters and service functions as they are abstracted; (3) separating the control from the user plane descriptions thanks to the separation between the application and technology layers in the design model. This paper is structured as follows: In section 2, we present the related work by analyzing the similarities and differences from our work. Section 3 highlights the service creation environments and points to our approach. In section 4, we explain the EA and ArchiMate concepts that directly affect our contribution.
, 2007) , or Open Service Architectures (OSA) and Parlay in  (Bakker and Jain, 2002; Glitho et al. , 2003). However, all of these approaches do not consider the performance evaluation of the hardware elements in the system design, where they concentrate on implementing the functions and protocols only. In our approach, we consider both the behavioral and structural (including hardware elements) aspects thanks to the concepts of the modeling language (ArchiMate). • Regarding the multiple viewpoints (C3) concern, the authors in  (Berthomieu et al. , 2010)  rely on the AADL language to model their design. AADL enables the designer to separate software components of the system (e. g. process, thread, etc) from 2 Cheddar framework: http://beru. univ-brest. fr/ ˜singhoff/cheddar/#Ref6 3 COTS is a synonym for "Commercial Off-The-Shelf" existing tools.
ENTERPRISE ARCHITECTURE AND ARCHIMATE In this section, we present the EA and ArchiMate modeling language, as our contribution relies directly on ArchiMate concepts. According to  (Jonkers et al. , 2006) , the enterprise architecture (EA) is defined as: "a coherent whole of principles, methods, and models that are used in the design and realization of the enterprise's organizational structure, business processes, information systems, and infrastructure". The EA objective is to define frameworks that provide a way to structure concepts and activities necessary for designing and building systems. The Open Group Architecture Framework (TOGAF) covers the activities that are related to the IT domain. The closest EA modeling language to TOGAF is ArchiMate. This makes Archi-Mate suitable for modeling telecommunication applications and development.
ArchiMate includes the three phases of TOGAF (Fig. 2 ): Business Architecture, Information Systems Architecture, and Technology Architecture. It represents these architectures using three corresponding layers. Furthermore, it can provide interoperability between these three layers thanks to the different dependencies and the passive structural elements that ArchiMate contains. Like other modeling languages ArchiMate has both (abstract and concrete) syntaxes and semantics. The multi-layered architecture is represented in the meta-model of ArchiMate that represents the abstract syntax of the modeling language. Every layer contains different concepts: structural, behavioral, and passive structural (C2 in section 2). This helps the designer of the service to represent the system from different viewpoints (multi-layers) (C3 in section 2), and provides the ability to represent software and hardware concepts (behavioral and structural aspects).
EXPRESSING THE VIEWPOINTS OF ARCHIMATE IN THE NETWORK SIMULATION SCRIPTS In this section, we present our method to transform the multi-layered architecture of the ArchiMate modeling language (see section 4) to the NS-3 simulation scenario through the code generation process. The objective from the viewpoints concept is to organize the different activities between the designers from different domains and backgrounds. The point of transforming this concept to the network simulation is to represent the different actors, roles, functions, components in order to: (1) trace the flow of execution of the design; (2) implement functions even if abstracted for override (reconfiguration) later by the developers according to their needs; (3) separate the concepts of the TS design (user and control planes) in the simulation program.
On one hand, ArchiMate provides a language to describe the EA through its multiple layers and the different domains of concepts. On the other hand, NS-3  (Henderson et al. , 2006)  relies on class concepts as it accepts the C++ language for configuration. The C++ program can control the simulation scenario through different APIs that are provided by the libraries of the NS-3 simulator. Our method in this section relies on these features of both the ArchiMate language and the NS-3 simulator to express the architecture of ArchiMate in the simulation C++ program. The Eclipse IDE 4  is a powerful IDE rich in plugins and tools to start with research and development. The Eclipse modeling framework (EMF) 5  provides us with a powerful means to model and generate codes in the Model Driven Engineering discipline.
There are many languages that are used for model transformations (e. g. ATL as a model-to-model transformation, and XPAND as a model-to-text transformation). We chose the XPAND language to build templates that are used to generate simulation code directly from design models relying on the abstract syntax of the modeling language. XPAND is used because it contains means to make syntax checks, and to analyze and manage the replacement of variables with their values from the design model. This replacement occurs side by side with the static implementations that respects the language of the target tool. In the following we present the mapping rules that we implement through the XPAND model transformation: (1) Every Business Actor or Role, and Application Component in the design model is mapped as a class in NS-3; (2) Every Business Function or Activity, and Application Function in the design model is mapped as a function that is implemented in the corresponding class in NS-3 (correspondence is represented by an assignment relationship in the design model); (3) The relationship between the functions/activities of the different layers is accepted to be an association relationship while it is excluded (through the model transformation analysis) when it occurs between elements that do not belong to two consequent layers; (4) The calls between the functions in the simulation scenario are initiated by triggering and cross-layer association relationships in the design model; (5) Regarding the technology layer mapping, it stays as implemented in  (Alloush et al.
These tools are extensible as they can be generated from meta-models (e. g. Archi tool) and they rely on the Eclipse Modeling Framework that is well supported and widely used too. Additionally, as far as we know, there is not yet any state of the art code generation technique to link between models and classical (or COTS) tools like NS-3 simulator. We make use of the architecture of ArchiMate to generate a fine-grained simulation program. This enables the designer to reconfigure the part of the code that is related to his domain experience. Our model transformation enables the designer to generate complex and large simulation scenarios directly from the design model in a very short time (few seconds). Additionally, it helps to separate the user and control planes in the simulation program.
On the other hand, the implementation of the transformation template consumes considerable time and needs accuracy and domain experience in both the modeling and network simulation activities. In the future, we expect to generate executable analysis scripts from the constraints that belong to the performance and QoS requirements. These scripts can be run directly in COTS such as MATLAB. Analysis tools helps to obtain valuable feedbacks that help the designer to make decisions to improve the design quality. Additionally, we intend to provide a checker for the domain-specific constraints that are related to the language (DSML) through the code generation process. This checker should generate reports that help the designer to modify the model efficiently.
Within the alternative tasks "Voltage failure" and "Signal failure" one can see that failure code must be an input parameter. Depending on its value VOLTAGE_FAILURE or Fig. 5. Parameterization of a sub-routine SIGNAL_FAILURE the corresponding sub-tree is executed. Both sub-trees have a very similar structure. There might be the chance to specify them with generic specifications. This will be explained within the following sub-section. Having a look at the graphical specification of the task "Record failure" (Fig. 6 ) one can see some further features offered by the HAMSTERS notation that have been introduced in  [16]. The rectangles with an "I:" at their left describe the information required to perform the tasks that are connected to them. For example, the human task "Find failing generator number" produces the information "Failing generator number" which is then consumed by the interactive input task "Enter failing generator number".
DATA REDUCTION AND ANALYSIS The data obtained with VLT/ISAAC in period 89 were reduced with the ISAAC pipeline in the Gasgano environment, following the steps outlined in the ISAAC Data Reduction Guide 2. The output of the pipeline is a co-added, sky-subtracted image without astrometric calibration. We used the astrometry tool 'fit to star positions' in the Starlink program Gaia to calculate the astrometric solutions, using 2 Micron All Sky Survey (2MASS,  Skrutskie et al. 2006 ) sources in the field of view if at least four were present. When this was not the case we used sources from the USNO B1. 0 catalog  (Monet et al. 2003)  for the calibration. We adopt the root-mean-square (rms) error of the fit as the 1-σ uncertainty on the positions of the NIR sources. We used the general data reduction software package Theli  (Schirmer 2013)  to reduce the data obtained with WHT/LIRIS, MMT/SWIRC and the data obtained with VLT/ISAAC in p90.
There is an additional uncertainty in the 2MASS and USNO B1. 0 positions with respect to the international celestial reference system (ICRS), but this error (0. 015 arcsec for 2MASS, 0. 2 arcsec for USNO B1. 0,  Skrutskie et al. 2006; Monet et al. 2003 ) is negligible in the total error budget (that is dominated by the uncertainty in the X-ray position). We used the tasks DAOFIND and PHOT from the Apphot package in Iraf 3  to calibrate the zeropoints of the images using 2MASS sources near the targets, detect counterparts within the error circles and calculate their apparent magnitude. For the cases where we did not detect a counterpart we calculated the limiting magnitude at the position of the ULX by simulating stars at that position with a range of magnitudes using the Iraf task MKOBJECTS.
ACKNOWLEDGEMENTS EK thanks  Mischa Schirmer  for his help with the data reduction software Theli. We thank the anonymous referee for their comments that helped improve the paper. TPR's contribution to this paper was funded as part of  STFC  consolidated grant  ST/K000861/1. Based on observations collected at the  European Southern Observatory, Chile , programmes  089. D-0663 (A) and  090. D-0417 (A). The William Hershel Telescope is operated on the island of  La Palma  by the  Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos  of the  Instituto de Astrofisica de Canarias. Observations reported here were obtained at the  MMT Observatory , a joint facility of the  Smithsonian Institution  and the  University of Arizona.
9 0. 7" this work Chandra NGC [SST2011] J110545. 62+000016. 2 11:05:45. 63 00:00:16. 5 1. 0" Liu 2011 Chandra NGC [GSE2009] B 11:18:15. 16 -32:48:40. 6 0. 7  † Gliozzi et al. 2009 Chandra NGC [LB2005] NGC 3623 ULX1 11:18:58. 54 13:05:30. 9 1. 0" Liu 2011 Chandra NGC [SST2011] J112020. 90+125846. 6 11:20:20. 89 12:58:46. 0 1. 0" Liu 2011 Chandra NGC [SST2011] J112018. 32+125900. 8 11:20:18. 31 12:59:00. 3 1. 0" Liu 2011 Chandra NGC CXOU J112037. 3+133429 11:20:37. 37 13:34:29. 2 1. 0" Liu 2011 Chandra NGC CXOU J120922. 6+295551 12:09:22. 58 29:55:50. 6 1. 0" Liu 2011 Chandra NGC [SST2011] J120922. 18+295559. 7 12:09:22. 19 29:55:59. 7 1. 0" Liu 2011 Chandra NGC [SST2011] J121510. 91+203912. 4 12:15:10. 91 20:39:12. 4 1. 0" Liu 2011 Chandra NGC RX J121844. 0+471730 12:18:43. 88 47:17:31. 7 1.
Using a network to manage enterprise office affairs is an important means of improving efficiency of the office management and achieving standardization for the enterprise business. The major technology about using PHP and MySQL to develop an enterprise office management system was illustrated in this paper. The contents including the realization of functional modules were discussed, such as: The foreground web page module used by employees, business management module, design of the database tables and web management technology of administrator. The system has features of fullfeatured, high-efficiency, advanced technology. The systems provide an important reference platform to help enterprise reduce management costs, improve internal management, and enhance competition in the market for comprehensive competitiveness.
It provided the convenient, fast and practical software for the enterprise's daily management. PHP (Hypertext Preprocessor) is a server scripting language, which is designed specifically for the Web. PHP codes can be embedded in an HTML page, which were executed when the page was accessed in each time  [1]. PHP has advantages in many aspects, such as: PHP is very fast, with high performance; PHP are open source software, with a very good development space and scalability, and it can also be effective to make horizontal extension for a large number of servers; PHP can be applied on all major operating systems, and its code can be run without any modification in different systems; PHP supports multiple databases, and it can be connected to any database providing ODBC driver; PHP is free, in which a lot of open source codes are available.
If modifying or adding new features to the language, it can be free of charge, therefore the cost of using PHP is low  [2]. The unique syntax of PHP is the mixture of C, Java, Perl and PHP own syntax  [3]. MySQL is a relational database management system. The relational database is the most common type of database, because of its faster access, and more flexible for data expression. MySQL supports structured query language SQL, so data query is simple and quick. For medium-sized enterprises, MySQL function can be fully met. The advantages of MySQL are its small in size, fast, cross-platform, and open-source. It is especially the feature of the open-source that a lot of free resources can be obtained, which causes many small and medium sized websites to choose MySQL as a database support of website background, in order to reduce the overall cost of the website.