User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

User’s Guide to C2R: A Set of C Language Output Routines Compatible with the R Statistics Language

C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

User’s Guide to For2R: A Module of Fortran 95 Output Routines Compatible with the R Statistics Language

For2R is a collection of Fortran routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 For2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the For2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer For2R to others in the hope that they will find it useful. (PDF contains 31 pages)

PAnalyzer: A software tool for protein inference in shotgun proteomics

Background Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. Results In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS) software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file) files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. Conclusions We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates integration. PAnalyzer is an easy to use multiplatform and free software tool.

Moment of creation : conception of Brasília and of the National Congress

Contém uma síntese de ideias sobre Brasília e o Congresso Nacional, com foco na Câmara dos Deputados. Tem por intenção explorar as relações entre a cidade e o edifício, de modo a discutir sobre como ambos estão estreitamente associados, a ponto de ser difícil imaginar um apartado do outro.

The Grimsby Institute Group: Making it easy for students to use their own devices to learn

The Grimsby Institute wanted to create an infrastructure that would enable staff and students to use more mobile technology to enhance learning. They have improved the wifi connectivity in college and streamlined the software used to access college areas, as well as encouraging individuals to use their own technology. So far this has had a positive impact on retention and simplified the support that the college needs to provide, as well as saving the organisation money through some strategic changes.

FleSSR project: Sustainable business models for community cloud infrastructure in the UK higher education sector

Cloud-based infrastructure essentially comprises two offerings, cloud-based compute and cloud-based storage. These are perhaps best typified for most people by the two main components of the Amazon Web Services (AWS)1 public cloud offer, the Elastic Compute Cloud (EC2)2 and the Simple Storage Service (S3)3, though, of course, there are many other related services offered by Amazon and many other providers of similar public cloud infrastructure across the Internet.

Research Software Sustainability: Report on Knowledge Exchange Workshop

The report introduces software sustainability, provides definitions, clearly demonstrates that software is not the same as data and illustrates aspects of sustainability in the software lifecycle. The recommendations state that improving software sustainability requires a number of changes: some technical and others societal, some small and others significant. We must start by raising awareness of researchers’ reliance on software. This goal will become easier if we recognise the valuable contribution that software makes to research – and reward those people who invest their time into developing reliable and reproducible software. The adoption of software has led to significant advances in research. But if we do not change our research practices, the continued rise in software use will be accompanied by a rise in retractions. Ultimately, anyone who is concerned about the reliability and reproducibility of research should be concerned about software sustainability. Beside highlighting the benefits of software sustainability and addressing the societal and technical barriers to software sustainability, the report provides access to expertise in software sustainability and outlines the role of funders. The report concludes with a short landscape of national activities in Europe and outside Europe. As a result of the workshop steps will be explored to establish European coordination and cooperation of national initiatives.

Cine Digital y sus Contenedores. Herramientas de Software libre basadas en las Especificaciones DCI

El Cine Digital es aquel que utiliza la tecnología digital para grabar, distribuir y proyectar películas. En los años 90, el cine comenzó un proceso de transición, del soporte fílmico a la tecnología digital. Pero el salto definitivo se dio con las grandes superproducciones de principios del 2000. Con este cambio de era y debido a la rápida difusión del digital y la proliferación de formatos se creo el DCI (Digital Cinema Initiative), para cambiar el modo en que las personas consumen cine. Trabajando junto con los miembros del comité SMPTE (Organización americana encargada de crear los estándares de la industria audiovisual formada por ingenieros, técnicos y fabricantes) publicó un sistema de especificaciones que han adoptado las mayores productoras estadounidenses. Mediante este acuerdo, aseguraban la calidad técnica de las producciones, la compatibilidad entre sistemas y como no, su hegemonía particular. Entre las especificaciones técnicas que suscribieron que son la base actual del DCI figuran la resolución de fotograma, el espacio de color, la compresión de imagen, la encriptación y el método de empaquetado de archivos. Y hoy en día son un estándar en la masterización, distribución y en la proyección final en las salas de cine. Una de las grandes esperanzas que hay puestas en la tecnología digital es la democratización en el mundo del cine y la supuesta abolición de las barreras económicas a la hora de realizar películas, dado lo barato que puede resultar la grabación digital y la posibilidad de pasar el material a video y editarlo en un ordenador domestico. Independientemente de los sistemas de edición que se utilicen, el formato de archivo o incluso el códec usado, los servidores de cine digital solo aceptan un tipo de archivo llamado DCP (Digital Cinema Package). Hay que aclarar que el DCP es abierto, documentado y que esta basado en los estándares SMPTE. Por lo tanto, existen en el mercado actual herramientas de software libre que permiten crear un DCP válido según las normas del DCI y compatible con los actuales servidores de cine digital. El propósito de este proyecto principalmente es documentar desde un punto de vista técnico la creación de un archivo DCP y analizar las diferentes herramientas existentes en el mercado para poder realizarlo: tanto las de uso comercial, como las de software libre. Como base se partirá de las aplicaciones creadas por la empresa alemana Fraunhofer (EasyDCP Creator, Player) - es el software utilizado en el estudio REC - y de otras herramientas más rudimentarias y escritas en C++ como (asdcplib) de Cinecert.

Reuse of software components orientated to iOS mobile devices

Within the next few pages, I will try to give a wide description of the project that I have been doing for IK4-Ikerlan. For the last six months, I have been working in developing a socket-based application for Apple devices. These devices work under the iOS operative system, which is programmed in Objective-C, a language similar to C. Although I did not have the chance to develop this application for Apple TV, I was able to create an application for iPhone and another one for iPad. The only difference between both applications was the screen resolution, but we decided to make them separately, as it would be really hard to combine both resolutions, and wallpapers, everything in the same workspace. Finally, it is necessary to add that the main goal was not to create a new application for iOS, but to translate an Android application into iOS. To achieve this, it is required to translate Java code into Objective- C, which is the language used to develop applications for all kinds of Apple devices. Fortunately, there is a tool created by Google, which helped us with this exercise. This tool is called j2ObjC, and it is still being developed.