Adsorption of organic friction modifier additives

Organic friction modifier additives (OFMs) are surfactant molecules added to engine oils to reduce friction in the boundary lubrication regime. They are thought to work by forming an absorbed layer which provides low friction. This paper studied the relationship between the adsorption of OFMs and their friction and wear reducing properties in a rubbing contact formed by a stationary glass ball and a rotating silicon disk under the boundary lubrication regime. The effect of molecular structure was investigated by using OFMs of various tail saturation and head group chemistry. OFM tested were oleic acid, octadecylamine, oleylamine and glycerol monooleate. The thickness of an OFM adsorbed layer in hexadecane, examined in-situ by spectroscopic ellipsometry and quartz crystal microbalance (QCM), depends on the molecular structure and the concentration of the OFM. As expected, saturated, linear chain gives the thickest film. A critical OFM layer thickness of about 0.6 nm is necessary to achieve low initial and maximum friction. The thicker OFM layers are accompanied by narrower wear tracks, which are rougher than the wider, smoother wear tracks formed with thinner OFM layers. The interplay between the thickness of the OFM layer and wear track surface roughness results in all OFM layers having similar steady friction. This shows that the apparent effect of OFM depends on the stage of rubbing test: initially on friction; and then subsequently on surface damage. Despite OFMs and the base oil having similar refractive indices, ellipsometry was found to be a suitable technique for examining the adsorption of OFM additives from an oil based solution, and showed reasonable correlation with QCM results

High Resolution Genotyping of Clinical Aspergillus flavus Isolates from India Using Microsatellites

Contains fulltext : 124312.pdf (publisher's version ) (Open Access)BACKGROUND: Worldwide, Aspergillus flavus is the second leading cause of allergic, invasive and colonizing fungal diseases in humans. However, it is the most common species causing fungal rhinosinusitis and eye infections in tropical countries. Despite the growing challenges due to A. flavus, the molecular epidemiology of this fungus has not been well studied. We evaluated the use of microsatellites for high resolution genotyping of A. flavus from India and a possible connection between clinical presentation and genotype of the involved isolate. METHODOLOGY/PRINCIPAL FINDINGS: A panel of nine microsatellite markers were selected from the genome of A. flavus NRRL 3357. These markers were used to type 162 clinical isolates of A. flavus. All nine markers proved to be polymorphic displaying up to 33 alleles per marker. Thirteen isolates proved to be a mixture of different genotypes. Among the 149 pure isolates, 124 different genotypes could be recognized. The discriminatory power (D) for the individual markers ranged from 0.657 to 0.954. The D value of the panel of nine markers combined was 0.997. The multiplex multicolor approach was instrumental in rapid typing of a large number of isolates. There was no correlation between genotype and the clinical presentation of the infection. CONCLUSIONS/SIGNIFICANCE: There is a large genotypic diversity in clinical A. flavus isolates from India. The presence of more than one genotype in clinical samples illustrates the possibility that persons may be colonized by multiple genotypes and that any isolate from a clinical specimen is not necessarily the one actually causing infection. Microsatellites are excellent typing targets for discriminating between A. flavus isolates from various origins

The Effect of Modularity Representation and Presentation Medium on the Understandability of Business Process Models in BPMN

Many factors influence the creation of understandable business process models for an appropriate audience. Understandability of process models becomes critical particularly when a process is complex and its model is large in structure. Using modularization to represent such models hierarchically (e.g. using sub-processes) is considered to contribute to the understandability of these models. To investigate this assumption, we conducted an experiment that involved 2 large-scale real-life business process models that were modeled using BPMN v2.0 (Business Process Model and Notation). Each process was modeled in 3 modularity forms: fully-flattened, flattened where activities are clustered using BPMN groups, and modularized using separately viewed BPMN sub-processes. The objective is to investigate if and how different forms of modularity representation in BPMN collaboration diagrams influence the understandability of process models. In addition to the forms of modularity representation, we also looked into the presentation medium (paper vs. computer) as a factor that potentially influences model comprehension. Sixty business practitioners from a large organization participated in the experiment. The results of our experiment indicate that for business practitioners, to optimally understand a BPMN model in the form of a collaboration diagram, it is best to present the model in a ‘fully-flattened’ fashion (without using collapsed sub-processes in BPMN) in the ‘paper’ format

Considerations about quality in model-driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. ISO/IEC/IEEE 42010:2011(E) (Revision of ISO/IEC 42010:2007 and IEEE Std 1471-2000) (pp. 1–46).Abran, A., Moore, J.W., Bourque, P., Dupuis, R., & Tripp, L.L. (2013). Guide to the Software Engineering Body of Knowledge (SWEBOK) version 3 public review. IEEE. ISO Technical Report ISO/IEC TR 19759.Agner, L.T.W., Soares, I.W., Stadzisz, P.C., & Simão, J.M. (2013). A brazilian survey on {UML} and model-driven practices for embedded software development. Journal of Systems and Software, 86(4), 997–1005. {SI} : Software Engineering in Brazil: Retrospective and Prospective Views.Amstel, M.F.V. (2010). The right tool for the right job: assessing model transformation quality. pages 69–74. Affiliation: Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, Netherlands. Cited By (since 1996):1.Aranda, J., Damian, D., & Borici, A. (2012). Transition to model-driven engineering: what is revolutionary, what remains the same?. In Proceedings of the 15th international conference on model driven engineering languages and systems, MODELS’12 (pp. 692–708). Berlin, Heidelberg: Springer.Arendt, T., & Taentzer, G. (2013). A tool environment for quality assurance based on the eclipse modeling framework. Automated Software Engineering, 20(2), 141–184.Atkinson, C., Bunse, C., & Wüst, J. (2003). Driving component-based software development through quality modelling, volume 2693. Cited By (since 1996):3.Baker, P., Loh, S., & Weil, F. (2005). Model-driven engineering in a large industrial context—motorola case study. In Briand, L., & Williams, C. (Eds.) Model Driven Engineering Languages and Systems, volume 3713 of Lecture Notes in Computer Science (pp. 476–491). Berlin, Heidelberg: Springer.Barišić, A., Amaral, V., Goulão, M., & Barroca, B. (2011). Quality in use of domain-specific languages: a case study. In Proceedings of the 3rd ACM SIGPLAN workshop on evaluation and usability of programming languages and tools, PLATEAU ’11 (pp. 65–72). New York: ACM.Becker, J., Bergener, P., Breuker, D., & Rackers, M. (2010). Evaluating the expressiveness of domain specific modeling languages using the bunge-wand-weber ontology. In 2010 43rd Hawaii international conference on system sciences (HICSS) (pp. 1–10).Bertrand Portier, L.A. (2009). Model driven development misperceptions and challenges.Bézivin, J., & Kurtev, I. (2005). Model-based technology integration with the technical space concept. In Proceedings of the Metainformatics Symposium: Springer.Brambilla, M. (2016). How mature is of model-driven engineering as an engineering discipline @ONLINE.Brambilla, M., & Fraternali, P. (2014). Large-scale model-driven engineering of web user interaction: The webml and webratio experience. Science of Computer Programming, 89 Part B(0), 71 – 87. Special issue on Success Stories in Model Driven Engineering.Brown, A. (2009). Simple and practical model driven architecture (mda) @ONLINE.Bruel, J.-M., Combemale, B., Ober, I., & Raynal, H. (2015). Mde in practice for computational science. Procedia Computer Science, 51, 660–669.Budgen, D., Burn, A.J., Brereton, O.P., Kitchenham, B.A., & Pretorius, R. (2011). Empirical evidence about the uml: a systematic literature review. Software: Practice and Experience, 41(4), 363–392.Burden, H., Heldal, R., & Whittle, J. (2014). Comparing and contrasting model-driven engineering at three large companies. In Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM ’14 (pp. 14:1–14:10). New York: ACM.Cabot, J. Has mda been abandoned (by the omg)?Cabot, J. (2009). Modeling will be commonplace in three years time @ONLINE.Cachero, C., Poels, G., Calero, C., & Marhuenda, Y. (2007). Towards a Quality-Aware Engineering Process for the Development of Web Applications. Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/462, Ghent University, Faculty of Economics and Business Administration.Challenger, M., Kardas, G., & Tekinerdogan, B. (2015). A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems. Software Quality Journal, 1–41.Chaudron, M.V., Heijstek, W., & Nugroho, A. (2012). How effective is uml modeling? Software & Systems Modeling, 11(4), 571–580. J2: Softw Syst Model.Chenouard, R., Granvilliers, L., & Soto, R. (2008). Model-driven constraint programming. pages 236–246. Affiliation: CNRS, LINA, Universit de Nantes, France; Affiliation: Pontificia Universidad Catlica de, Valparaiso, Chile. Cited By (since 1996):8.Clark, T., & Muller, P.-A. (2012). Exploiting model driven technology: a tale of two startups. Software and Systems Modeling, 11(4), 481–493.Corneliussen, L. (2008). What do you think of model-driven software development?Costal, D., Gómez, C., & Guizzardi, G. (2011). Formal semantics and ontological analysis for understanding subsetting, specialization and redefinition of associations in uml. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6998 LNCS:189–203. cited By (since 1996)3.Cruz-Lemus, J.A., Maes, A., Género, M., Poels, G., & Piattini, M. (2010). The impact of structural complexity on the understandability of uml statechart diagrams. Information Sciences, 180(11), 2209–2220. Cited By (since 1996):14.Cuadrado, J.S., Izquierdo, J.L.C., & Molina, J.G. (2014). Applying model-driven engineering in small software enterprises. Science of Computer Programming, 89 Part B(0), 176 – 198. Special issue on Success Stories in Model Driven Engineering.Da Silva, A.R. (2015). Model-driven engineering: a survey supported by the unified conceptual model. Computer Languages Systems and Structures, 43, 139–155.Da Silva Teixeira, D.G.M., Quirino, G.K., Gailly, F., De Almeida Falbo, R., Guizzardi, G., & Perini Barcellos, M. (2016). PoN-S: a Systematic Approach for Applying the Physics of Notation (PoN), (pp. 432–447). Cham: Springer International Publishing.Davies, I., Green, P., Rosemann, M., Indulska, M., & Gallo, S. (2006). How do practitioners use conceptual modeling in practice? Data and Knowledge Engineering, 58(3), 358 – 380. Including the special issue : {ER} 2004ER 2004.Davies, J., Milward, D., Wang, C.-W., & Welch, J. (2015). Formal model-driven engineering of critical information systems. Science of Computer Programming, 103(0), 88 – 113. Selected papers from the First International Workshop on Formal Techniques for Safety-Critical Systems (FTSCS 2012).De Oca, I.M.-M., Snoeck, M., Reijers, H.A., & Rodríguez-Morffi, A. (2015). A systematic literature review of studies on business process modeling quality. Information and Software Technology, 58, 187–205.DenHaan, J. (2009). 8 reasons why model driven development is dangerous @ONLINE.DenHaan, J. (2010). Model driven engineering vs the commando pattern @ONLINE.DenHaan, J. (2011a). Why aren’t we all doing model driven development yet @ONLINE.DenHaan, J. (2011b). Why there is no future model driven development @ONLINE.Di Ruscio, D., Iovino, L., & Pierantonio, A. (2013). Managing the coupled evolution of metamodels and textual concrete syntax specifications. cited By (since 1996)0.Dijkman, R.M., Dumas, M., & Ouyang, C. (2008). Semantics and analysis of business process models in {BPMN}. Information and Software Technology, 50(12), 1281–1294.Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., Ramos, I., & Fernández, L. (2011). A framework for the quality evaluation of mdwe methodologies and information technology infrastructures. International Journal of Human Capital and Information Technology Professionals, 2(4), 11–22.Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., & Torres, A.H. (2010). A quality model in a quality evaluation framework for mdwe methodologies. pages 495–506. Affiliation: Departamento de Lenguajes y Sistemas Informíticos, University of Seville, Seville, Spain., Cited By (since 1996):1.Dubray, J.-J. (2011). Why did mde miss the boat?.Escalona, M.J., Gutiérrez, J.J., Pérez-Pérez, M., Molina, A., Domínguez-Mayo, E., & Domínguez-Mayo, F.J. (2011). Measuring the Quality of Model-Driven Projects with NDT-Quality, (pp. 307–317). New York: Springer.Espinilla, M., Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., Ross, M., & Staples, G. (2011). A Method Based on AHP to Define the Quality Model of QuEF (Vol. 123, pp. 685–694). Berlin, Heidelberg: Springer.Fabra, J., Castro, V.D., Álvarez, P., & Marcos, E. (2012). Automatic execution of business process models: exploiting the benefits of model-driven engineering approaches. Journal of Systems and Software, 85(3), 607–625. Novel approaches in the design and implementation of systems/software architecture.Falkenberg, E.D., Hesse, W., Lindgreen, P., Nilsson, B.E., Oei, J.L.H., Rolland, C., Stamper, R.K., Assche, F.J.M.V., Verrijn-Stuart, A.A., & Voss, K. (1996). Frisco: a framework of information system concepts. Technical report, The IFIP WG 8. 1 Task Group FRISCO.Fettke, P., Houy, C., Vella, A.-L., & Loos, P. (2012). Towards the Reconstruction and Evaluation of Conceptual Model Quality Discourses – Methodical Framework and Application in the Context of Model Understandability, volume 113 of Lecture Notes in Business Information Processing, chapter 28, pages 406–421, Springer, Berlin, Heidelberg.Finnie, S. (2015). Modeling community: Are we missing something?Fournier, C. (2008). Is uml [email protected], R., & Rumpe, B. (2007). Model-driven development of complex software: a research roadmap. In Future of Software Engineering, 2007, FOSE ’07 (pp. 37–54).Gallego, M., Giraldo, F.D., & Hitpass, B. (2015). Adapting the pbec-otss software selection approach for bpm suites: an application case. In 2015 34th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–10).Galvão, I., & Goknil, A. (2007). Survey of traceability approaches in model-driven engineering. cited By (since 1996)22.Giraldo, F., España, S., Giraldo, W., & Pastor, O. (2015). Modelling language quality evaluation in model-driven information systems engineering: a roadmap. In 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS) (pp. 64–69).Giraldo, F., España, S., & Pastor, O. (2014). Analysing the concept of quality in model-driven engineering literature: a systematic review. In 2014 IEEE Eighth International Conference on Research Challenges in Information Science (RCIS) (pp. 1–12).Giraldo, F.D., España, S., & Pastor, O. (2016). Evidences of the mismatch between industry and academy on modelling language quality evaluation. arXiv: 1606.02025 .González, C., & Cabot, J. (2014). Formal verification of static software models in mde: a systematic review. Information and Software Technology, 56(8), 821–838. cited By (since 1996)0.González, C.A., Büttner, F., Clarisó, R., & Cabot, J. (2012). Emftocsp: a tool for the lightweight verification of emf models. pages 44–50. Affiliation: cole des Mines de Nantes, INRIA, LINA, Nantes, France; Affiliation: Universitat Oberta de Catalunya, Barcelona, Spain. Cited By (since 1996):1.Gorschek, T., Tempero, E., & Angelis, L. (2014). On the use of software design models in software development practice: an empirical investigation. Journal of Systems and Software, 95(0), 176– 193.Goulão, M., Amaral, V., & Mernik, M. (2016). Quality in model-driven engineering: a tertiary study. Software Quality Journal, 1–33.Grobshtein, Y., & Dori, D. (2011). Generating sysml views from an opm model: design and evaluation. Systems Engineering, 14(3), 327–340.Haan, J.d. (2008). 8 reasons why model-driven approaches (will) fail.Harel, D., & Rumpe, B. (2000). Modeling languages: Syntax, semantics and all that stuff, part i: The basic stuff, Israel. Technical report Jerusalem Israel.Harel, D., & Rumpe, B. (2004). Meaningful modeling: what’s the semantics of semantics? Computer, 37(10), 64–72.Hebig, R., & Bendraou, R. (2014). On the need to study the impact of model driven engineering on software processes. In Proceedings of the 2014 International Conference on Software and System Process, ICSSP 2014 (pp. 164–168). New York: ACM.Heidari, F., & Loucopoulos, P. (2014). Quality evaluation framework (qef): modeling and evaluating quality of business processes. International Journal of Accounting Information Systems, 15(3), 193–223. Business Process Modeling.Heymans, P., Schobbens, P.Y., Trigaux, J.C., Bontemps, Y., Matulevicius, R., & Classen, A. (2008). Evaluating formal properties of feature diagram languages. Software, IET, 2(3), 281–302. ID 2.Hindawi, M., Morel, L., Aubry, R., & Sourrouille, J.-L. (2009). Description and Implementation of a UML Style Guide (Vol. 5421, pp. 291–302). Berlin: Springer.Hoang, D. (2012). Current limitations of mdd and its implications @ONLINE.Hodges, W. (2013). Model theory Zalta, E.N. (Ed.) The Stanford Encyclopedia of Philosophy. Fall 2013 edition.Hutchinson, J., Rouncefield, M., & Whittle, J. (2011a). Model-driven engineering practices in industry. In Proceedings of the 33rd International Conference on Software Engineering, ICSE’11 (pp. 633–642). New York: ACM.Hutchinson, J., Whittle, J., & Rouncefield, M. (2014). Model-driven engineering practices in industry: social, organizational and managerial factors that lead to success or failure. Science of Computer Programming, 89 Part B(0), 144–161. Special issue on Success Stories in Model Driven Engineering.Hutchinson, J., Whittle, J., Rouncefield, M., & Kristoffersen, S. (2011b). Empirical assessment of mde in industry. In Proceedings of the 33rd International Conference on Software Engineering, ICSE’11 (pp. 471–480). New York: ACM.Igarza, I.M.H., Boada, D.H.G., & Valdés, A.P. (2012). Una introducción al desarrollo de software dirigido por modelos. Serie Científica, 5(3).ISO/IEC (2001). ISO/IEC 9126. Software engineering—Product quality. ISO/IEC.Izurieta, C., Rojas, G., & Griffith, I. (2015). Preemptive management of model driven technical debt for improving software quality. In Proceedings of the 11th International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA’15 (pp. 31–36). New York: ACM.Jalali, S., & Wohlin, C. (2012). Systematic literature studies: Database searches vs. backward snowballing. In Proceedings of the ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM’12 (pp. 29–38). New York: ACM.Kahraman, G., & Bilgen, S. (2013). A framework for qualitative assessment of domain-specific languages. Software & Systems Modeling, 1–22.Kessentini, M., Langer, P., & Wimmer, M. (2013). Searching models, modeling search: On the synergies of sbse and mde (pp. 51–54).Kitchenham, B., & Charters, S. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report.Kitchenham, B., Pfleeger, S., Pickard, L., Jones, P., Hoaglin, D., El Emam, K., & Rosenberg, J. (2002). Preliminary guidelines for empirical research in software engineering. IEEE Transactions on Software Engineering, 28(8), 721–734.Klinke, M. (2008). Do you use mda/mdd/mdsd, any kind of model-driven approach? Will it be the future?Köhnlein, J. (2013). Eclipse diagram editors from a user’s perspective.Kolovos, D.S., Paige, R.F., & Polack, F.A. (2008). The grand challenge of scalability for model driven engineering. In Models in Software Engineering (pp. 48–53): Springer.Kolovos, D.S., Rose, L.M., Matragkas, N., Paige, R.F., Guerra, E., Cuadrado, J.S., De Lara, J., Ráth, I., Varró, D., Tisi, M., & Cabot, J. (2013). A research roadmap towards achieving scalability in model driven engineering. In Proceedings of the Workshop on Scalability in Model Driven Engineering, BigMDE’13 (pp. 2:1–2:10). New York: ACM.Krill, P. (2016). Uml to be ejected from microsoft visual studio (infoworld).Krogstie, J. (2012a). Model-based development and evolution of information systems: a quality approach, Springer Publishing Company, Incorporated.Krogstie, J. (2012b). Quality of modelling languages, (pp. 249–280). London: Springer.Krogstie, J. (2012c). Quality of models, (pp. 205–247). London: Springer.Krogstie, J. (2012d). Specialisations of SEQUAL, (pp. 281–326). London: Springer.Krogstie, J., Lindland, O.I., & Sindre, G. (1995). Defining quality aspects for conceptual models. In Proceedings of the IFIP International Working Conference on Information System Concepts: Towards a Consolidation of Views (pp. 216–231). London: Chapman & Hall, Ltd.Kruchten, P. (2000). The rational unified process: an introduction, 2nd edn. Boston: Addison-Wesley Longman Publishing Co., Inc.Kruchten, P., Nord, R., & Ozkaya, I. (2012). Technical debt: from metaphor to theory and practice. Software, IEEE, 29(6), 18–21.Kulkarni, V., Reddy, S., & Rajbhoj, A. (2010). Scaling up model driven engineering – experience and lessons learnt. In Petriu, D., Rouquette, N., & Haugen, y. (Eds.) Model Driven Engineering Languages and Systems, volume 6395 of Lecture Notes in Computer Science (pp. 331–345). Berlin, Heidelberg: Springer.Laguna, M.A., & Marqués, J.M. (2010). Uml support for designing software product lines: the package merge mechanism, 16(17), 2313–2332.Lange, C. (2007a). Model size matters. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4364 LNCS:211–216. cited By (since 1996)1.Lange, C., & Chaudron, M. (2005). Managing Model Quality in UML-Based Software Development. In 13th IEEE International Workshop on Technology and Engineering Practice, 2005 (pp. 7–16).Lange, C., Chaudron, M.R.V., Muskens, J., Somers, L.J., & Dortmans, H.M. (2003). An empirical investigation in quantifying inconsistency and incompleteness of uml designs. In Incompleteness of UML Designs, Proceedings Workshop on Consistency Problems in UML-based Software Development, 6th International Conference on Unified Modeling Language, UML, 2003.Lange, C., DuBois, B., Chaudron, M., & Demeyer, S. (2006). An experimental investigation of uml modeling conventions. In Nierstrasz, O., Whittle, J., Harel, D., & Reggio, G. (Eds.) Model Driven Engineering Languages and Systems, volume 4199 of Lecture Notes in Computer Science (pp. 27–41). Berlin, Heidelberg: Springer.Lange, C.F.J., & Chaudron, M.R.V. (2006). Effe

A small world of citations? The influence of collaboration networks on citation practices

This paper examines the proximity of authors to those they cite using degrees of separation in a co-author network, essentially using collaboration networks to expand on the notion of self-citations. While the proportion of direct self-citations (including co-authors of both citing and cited papers) is relatively constant in time and across specialties in the natural sciences (10% of citations) and the social sciences (20%), the same cannot be said for citations to authors who are members of the co-author network. Differences between fields and trends over time lie not only in the degree of co-authorship which defines the large-scale topology of the collaboration network, but also in the referencing practices within a given discipline, computed by defining a propensity to cite at a given distance within the collaboration network. Overall, there is little tendency to cite those nearby in the collaboration network, excluding direct self-citations. By analyzing these social references, we characterize the social capital of local collaboration networks in terms of the knowledge production within scientific fields. These results have implications for the long-standing debate over biases common to most types of citation analysis, and for understanding citation practices across scientific disciplines over the past 50 years. In addition, our findings have important practical implications for the availability of 'arm's length' expert reviewers of grant applications and manuscripts

Major Reduction in Anti-Malarial Drug Consumption in Senegal after Nation-Wide Introduction of Malaria Rapid Diagnostic Tests

BACKGROUND: While WHO recently recommended universal parasitological confirmation of suspected malaria prior to treatment, debate has continued as to whether wide-scale use of rapid diagnostic tests (RDTs) can achieve this goal. Adherence of health service personnel to RDT results has been poor in some settings, with little impact on anti-malarial drug consumption. The Senegal national malaria control programme introduced universal parasite-based diagnosis using malaria RDTs from late 2007 in all public health facilities. This paper assesses the impact of this programme on anti-malarial drug consumption and disease reporting. METHODS AND FINDINGS: Nationally-collated programme data from 2007 to 2009 including malaria diagnostic outcomes, prescription of artemisinin-based combination therapy (ACT) and consumption of RDTs in public health facilities, were reviewed and compared. Against a marked seasonal variation in all-cause out-patient visits, non-malarial fever and confirmed malaria, parasite-based diagnosis increased nationally from 3.9% of reported malaria-like febrile illness to 86.0% over a 3 year period. The prescription of ACT dropped throughout this period from 72.9% of malaria-like febrile illness to 31.5%, reaching close equivalence to confirmed malaria (29.9% of 584,873 suspect fever cases). An estimated 516,576 courses of inappropriate ACT prescription were averted. CONCLUSIONS: The data indicate high adherence of anti-malarial prescribing practice to RDT results after an initial run-in period. The large reduction in ACT consumption enabled by the move from symptom-based to parasite-based diagnosis demonstrates that effective roll-out and use of malaria RDTs is achievable on a national scale through well planned and structured implementation. While more detailed information on management of parasite-negative cases is required at point of care level to assess overall cost-benefits to the health sector, considerable cost-savings were achieved in ACT procurement. Programmes need to be allowed flexibility in management of these funds to address increases in other programmatic costs that may accrue from improved diagnosis of febrile disease

Women gaze behaviour in assessing female bodies: the effects of clothing, body size, own body composition and body satisfaction

Often with minimally clothed figures depicting extreme body sizes, previous studies have shown women tend to gaze at evolutionary determinants of attractiveness when viewing female bodies, possibly for self-evaluation purposes, and their gaze distribution is modulated by own body dissatisfaction level. To explore to what extent women’s body-viewing gaze behaviour is affected by clothing type, dress size, subjective measurements of regional body satisfaction and objective measurements of own body composition (e.g., chest size, body mass index, waist-to-hip ratio), in this self-paced body attractiveness and body size judgement experiment, we compared healthy, young women’s gaze distributions when viewing female bodies in tight and loose clothing of different dress sizes. In contrast to tight clothing, loose clothing biased gaze away from the waist-hip to the leg region, and subsequently led to enhanced body attractiveness ratings and body size underestimation for larger female bodies, indicating the important role of clothing in mediating women’s body perception. When viewing preferred female bodies, women’s higher satisfaction of a specific body region was associated with an increased gaze towards neighbouring body areas, implying satisfaction might reduce the need for comparison of confident body parts; furthermore undesirable body composition measurements were correlated with a gaze avoidance process if the construct was less changeable (i.e. chest size) but a gaze comparison process if the region was more changeable (i.e. body mass index, dress size). Clearly, own body satisfaction and body composition measurements had an evident impact on women’s body-viewing gaze allocation, possibly through different cognitive processes

Human Papillomaviruses Activate the ATM DNA Damage Pathway for Viral Genome Amplification upon Differentiation

Human papillomaviruses (HPV) are the causative agents of cervical cancers. The infectious HPV life cycle is closely linked to the differentiation state of the host epithelia, with viral genome amplification, late gene expression and virion production restricted to suprabasal cells. The E6 and E7 proteins provide an environment conducive to DNA synthesis upon differentiation, but little is known concerning the mechanisms that regulate productive viral genome amplification. Using keratinocytes that stably maintain HPV-31 episomes, and chemical inhibitors, we demonstrate that viral proteins activate the ATM DNA damage response in differentiating cells, as indicated by phosphorylation of CHK2, BRCA1 and NBS1. This activation is necessary for viral genome amplification, as well as for formation of viral replication foci. In contrast, inhibition of ATM kinase activity in undifferentiated keratinocytes had no effect on the stable maintenance of viral genomes. Previous studies have shown that HPVs induce low levels of caspase 3/7 activation upon differentiation and that this is important for cleavage of the E1 replication protein and genome amplification. Our studies demonstrate that caspase cleavage is induced upon differentiation of HPV positive cells through the action of the DNA damage protein kinase CHK2, which may be activated as a result of E7 binding to the ATM kinase. These findings identify a major regulatory mechanism responsible for productive HPV replication in differentiating cells. Our results have potential implications for the development of anti-viral therapies to treat HPV infections

Management of uncomplicated malaria in febrile under five-year-old children by community health workers in Madagascar: reliability of malaria rapid diagnostic tests

<p>Abstract</p> <p>Background</p> <p>Early diagnosis, as well as prompt and effective treatment of uncomplicated malaria, are essential components of the anti-malaria strategy in Madagascar to prevent severe malaria, reduce mortality and limit malaria transmission. The purpose of this study was to assess the performance of the malaria rapid diagnostic tests (RDTs) used by community health workers (CHWs) by comparing RDT results with two reference methods (microscopy and Polymerase Chain Reaction, PCR).</p> <p>Methods</p> <p>Eight CHWs in two districts, each with a different level of endemic malaria transmission, were trained to use RDTs in the management of febrile children under five years of age. RDTs were performed by CHWs in all febrile children who consulted for fever. In parallel, retrospective parasitological diagnoses were made by microscopy and PCR. The results of these different diagnostic methods were analysed to evaluate the diagnostic performance of the RDTs administered by the CHWs. The stability of the RDTs stored by CHWs was also evaluated.</p> <p>Results</p> <p>Among 190 febrile children with suspected malaria who visited CHWs between February 2009 and February 2010, 89.5% were found to be positive for malaria parasites by PCR, 51.6% were positive by microscopy and 55.8% were positive by RDT. The performance accuracy of the RDTs used by CHWs in terms of sensitivity, specificity, positive and negative predictive values was greater than 85%. Concordance between microscopy and RDT, estimated by the Kappa value was 0.83 (95% CI: 0.75-0.91). RDTs stored by CHWs for 24 months were capable of detecting <it>Plasmodium falciparum </it>in blood at a level of 200 parasites/μl.</p> <p>Conclusion</p> <p>Introduction of easy-to-use diagnostic tools, such as RDTs, at the community level appears to be an effective strategy for improving febrile patient management and for reducing excessive use of anti-malarial drugs.</p