Power Models for Multicore Processor Simulators with Multiple Levels of Abstraction

En aquest projecte he creat una eina capaç de generar models energètics per diferents aplicacions donat un hardware determinat. Amb aquesta eina, es pot obtenir el consum energètic total de qualsevol aplicació i dels diferents components involucrats en l'execució.In this project I have created a tool capable of generating power models for different applications given a determined hardware. With this tool, it is possible to obtain the total consumption of any application and the different components involved in the execution

Power Models for Multicore Processor Simulators with Multiple Levels of Abstraction

En aquest projecte he creat una eina capaç de generar models energètics per diferents aplicacions donat un hardware determinat. Amb aquesta eina, es pot obtenir el consum energètic total de qualsevol aplicació i dels diferents components involucrats en l'execució.In this project I have created a tool capable of generating power models for different applications given a determined hardware. With this tool, it is possible to obtain the total consumption of any application and the different components involved in the execution

Tourist mobility at coastal mass destinations: implications for sustainability

The aim of this paper is to analyse the spatial behaviour of mass tourism demand in coastal destinations and its implications from the point of view of sustainable tourism development. The paper is based on primary research carried out in one of the main Mediterranean tourist destinations, Benidorm (Spain). This research involved the use of Global Positioning Systems (GPS) devices for the tracking of a sample of 257 tourists (from Spain and United Kingdom). Although the research has an experimental basis, these advanced technologies allow new approaches to spatial analysis in order to achieve a better understanding of tourist mobility at coastal destinations. Until now, most studies of intradestination movements have been applied to urban and cultural destinations, where the points of interest and tourist routes are easily identifiable. However, spatial behaviour of mass tourism in coastal destinations has rarely been studied in detail using new tracking technologies. While tourist movements may seem, a priori, predictable, the identification of mobility patterns offers interesting results about the main characteristics of the tourist experience, the relationship with the urban model, the use of public and private spaces, the perception of the destination, and the differences between segments of demand. The conclusions of the study are relevant from the methodological and theoretical point of view, and include some recommendations for planning and destination management in the context of sustainability.This research has been carried out within the framework of the project “New approaches for tourism destinations planning and management: conceptualization, case studies and problems. Definition of smart tourist destinations models” (CSO2014-59193-R) under the Spanish National R&D&I Plan financed by the Ministry of Economy and Competitiveness

ALEPH: a network-oriented approach for the generation of fragment-based libraries and for structure interpretation.

The analysis of large structural databases reveals general features and relationships among proteins, providing useful insight. A different approach is required to characterize ubiquitous secondary-structure elements, where flexibility is essential in order to capture small local differences. The ALEPH software is optimized for the analysis and the extraction of small protein folds by relying on their geometry rather than on their sequence. The annotation of the structural variability of a given fold provides valuable information for fragment-based molecular-replacement methods, in which testing alternative model hypotheses can succeed in solving difficult structures when no homology models are available or are successful. ARCIMBOLDO_BORGES combines the use of composite secondary-structure elements as a search model with density modification and tracing to reveal the rest of the structure when both steps are successful. This phasing method relies on general fold libraries describing variations around a given pattern of β-sheets and helices extracted using ALEPH. The program introduces characteristic vectors defined from the main-chain atoms as a way to describe the geometrical properties of the structure. ALEPH encodes structural properties in a graph network, the exploration of which allows secondary-structure annotation, decomposition of a structure into small compact folds, generation of libraries of models representing a variation of a given fold and finally superposition of these folds onto a target structure. These functions are available through a graphical interface designed to interactively show the results of structure manipulation, annotation, fold decomposition, clustering and library generation. ALEPH can produce pictures of the graphs, structures and folds for publication purposes

SEQUENCE SLIDER: expanding polyalanine fragments for phasing with multiple side-chain hypotheses.

Fragment-based molecular-replacement methods can solve a macromolecular structure quasi-ab initio. ARCIMBOLDO, using a common secondary-structure or tertiary-structure template or a library of folds, locates these with Phaser and reveals the rest of the structure by density modification and autotracing in SHELXE. The latter stage is challenging when dealing with diffraction data at lower resolution, low solvent content, high β-sheet composition or situations in which the initial fragments represent a low fraction of the total scattering or where their accuracy is low. SEQUENCE SLIDER aims to overcome these complications by extending the initial polyalanine fragment with side chains in a multisolution framework. Its use is illustrated on test cases and previously unknown structures. The selection and order of fragments to be extended follows the decrease in log-likelihood gain (LLG) calculated with Phaser upon the omission of each single fragment. When the starting substructure is derived from a remote homolog, sequence assignment to fragments is restricted by the original alignment. Otherwise, the secondary-structure prediction is matched to that found in fragments and traces. Sequence hypotheses are trialled in a brute-force approach through side-chain building and refinement. Scoring the refined models through their LLG in Phaser may allow discrimination of the correct sequence or filter the best partial structures for further density modification and autotracing. The default limits for the number of models to pursue are hardware dependent. In its most economic implementation, suitable for a single laptop, the main-chain trace is extended as polyserine rather than trialling models with different sequence assignments, which requires a grid or multicore machine. SEQUENCE SLIDER has been instrumental in solving two novel structures: that of MltC from 2.7 Å resolution data and that of a pneumococcal lipoprotein with 638 residues and 35% solvent content

Cold-air pooling in the Cerdanya valley (Pyrenees)

Peer ReviewedPostprint (published version

Slope and valley flows at the Cerdanya valley in the Pyrenees

The Pyrenees are a mountain range running in the east-west direction. Most of their valleys are oriented in the north-south direction on both sides of the range. A significant exception is the Cerdanya valley, in Catalonia, which is a graben with NE-SW orientation , roughly 35 km long and 15 km wide with the bottom about 1000 m asl, surrounded by the main axis of the Pyrenees at the north (peaks above 2900 m asl) and by the Cadi range at the south (maximum high 2648 m asl). The valley bottom is covered essentially by pastures, whereas the slopes at its southern side are very steep and covered by forests of conifers, and the slope at the northern side consists mainly of pastures with trees at the bottom of the valleys, less steep than the southern side and with longer river valleys in the N-S direction. This area is very dynamic in an economical sense: divided between Spain and France, it includes many ski stations, and the valley is a major touristic spot, even in summertime. In the valley center, at the municipality of Das, there is a private aerodrome where an o_cial weather station has been very recently supplemented with a full energy budget station and a Windrass by the Meteorological Service of Catalonia. For this reason, in order to get a preliminary characterization of local circulations in view of future experimental campaigns, a study of the recently available data was performed and is presented here. These data originate from seven meteorological stations, at di_erent heights, belonging to the meteorological services of France, Spain and Catalonia. The analysis covers the period 1/9/2010-31/8/2014. Conditional filtering allowed to isolate the cases when local circulations prevail and to provide a first explanation of the valley and slope flows as seen by the statistics at the surface level. A particular case, which occurred on 1-4 October 2011, was selected for a more detailed study, since at this time of the year there is no snow over the mountains and the diurnal temperature range is very large, usually above 20°C, with similar duration of daytime and nighttime. An episode of 4 days has been studied, combining meteorological data, satellite information and a high-resolution simulation for the valley, and the preliminary results are shown. This analysis describes the valley and slope wind circulations generated by the local topography, as well as the accumulation of cold air over the valley bottom at night, favouring the establishment of a strong surface inversion of temperature.Peer ReviewedPostprint (published version

Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER

11 pags., 5 figs., 3 tabsStructure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions tend to be present. These are suitable for successful fragment-based phasing as implemented in ARCIMBOLDO. The particularities of predicted models are inherently addressed in the new predicted_model mode, rendering preliminary treatment superfluous but also harmless. B-value conversion from predicted LDDT or error estimates, the removal of unstructured polypeptide, hierarchical decomposition of structural units from domains to local folds and systematically probing the model against the experimental data will ensure the optimal use of the model in phasing. Concomitantly, the exhaustive use of models and stereochemistry in phasing, refinement and validation raises the concern of crystallographic model bias and the need to critically establish the information contributed by the experiment. Therefore, in its predicted_model mode ARCIMBOLDO_SHREDDER will first determine whether the input model already constitutes a solution or provides a straightforward solution with Phaser. If not, extracted fragments will be located. If the landscape of solutions reveals numerous, clearly discriminated and consistent probes or if the input model already constitutes a solution, model-free verification will be activated. Expansions with SHELXE will omit the partial solution seeding phases and all traces outside their respective masks will be combined in ALIXE, as far as consistent. This procedure completely eliminates the molecular replacement search model in favour of the inferences derived from this model. In the case of fragments, an incorrect starting hypothesis impedes expansion. The predicted_model mode has been tested in different scenarios.We are grateful to the Spanish MICINN/AEI/FEDER/UE for support through the PGC2018-101370-B-100 project to IU, PID2020-115331GB-I00 to JH, a scholarship (PRE2019-087953) to EJ and a scholarship (BES-2017-080368) associated with the Structural Biology Maria de Maeztu Unit of Excellence (MDM2014-0435-01) to AM. Support from STFC-UK/ CCP4 ‘Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW’ is gratefully acknowledged.Peer reviewe

CCP4 Cloud for structure determination and project management in macromolecular crystallography

Nowadays, progress in the determination of three-dimensional macromolecular structures from diffraction images is achieved partly at the cost of increasing data volumes. This is due to the deployment of modern high-speed, high-resolution detectors, the increased complexity and variety of crystallographic software, the use of extensive databases and high-performance computing. This limits what can be accomplished with personal, offline, computing equipment in terms of both productivity and maintainability. There is also an issue of long-term data maintenance and availability of structure-solution projects as the links between experimental observations and the final results deposited in the PDB. In this article, CCP4 Cloud, a new front-end of the CCP4 software suite, is presented which mitigates these effects by providing an online, cloud-based environment for crystallographic computation. CCP4 Cloud was developed for the efficient delivery of computing power, database services and seamless integration with web resources. It provides a rich graphical user interface that allows project sharing and long-term storage for structure-solution projects, and can be linked to data-producing facilities. The system is distributed with the CCP4 software suite version 7.1 and higher, and an online publicly available instance of CCP4 Cloud is provided by CCP4.The following funding is acknowledged: Biotechnology and Biological Sciences Research Council (grant No. BB/L007037/1; grant No. BB/S007040/1; grant No. BB/S007083/1; grant No. BB/S005099/1; grant No. BB/S007105/1; award No. BBF020384/1); Medical Research Council (grant No.MC_UP_A025_1012; grant No. MC_U105184325); Ro¨ntgenA˚ ngstro¨m Cluster (grant No. 349-2013-597); Nederlandse Wetenschappelijke Organisatie (grant No. TKI 16219)

The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.Jon Agirre is a Royal Society University Research Fellow (UF160039 and URF\R\221006). Mihaela Atanasova is funded by the UK Engineering and Physical Sciences Research Council (EPSRC; EP/R513386/1). Haroldas Bagdonas is funded by The Royal Society (RGF/R1/181006). Jose´ Javier Burgos-Ma´rmol and Daniel J. Rigden are supported by the BBSRC (BB/S007105/1). Robbie P. Joosten is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 871037 (iNEXTDiscovery) and by CCP4. This work was supported by the Medical Research Council as part of United Kingdom Research and Innovation, also known as UK Research and Innovation: MRC file reference No. MC_UP_A025_1012 to Garib N. Murshudov, which also funded Keitaro Yamashita, Paul Emsley and Fei Long. Robert A. Nicholls is funded by the BBSRC (BB/S007083/1). Soon Wen Hoh is funded by the BBSRC (BB/T012935/1). Kevin D. Cowtan and Paul S. Bond are funded in part by the BBSRC (BB/S005099/1). John Berrisford and Sameer Velankar thank the European Molecular Biology Laboratory–European Bioinformatics Institute, who supported this work. Andrea Thorn was supported in the development of AUSPEX by the German Federal Ministry of Education and Research (05K19WWA and 05K22GU5) and by Deutsche Forschungsgemeinschaft (TH2135/2-1). Petr Kolenko and Martin Maly´ are funded by the MEYS CR (CZ.02.1.01/0.0/0.0/16_019/0000778). Martin Maly´ is funded by the Czech Academy of Sciences (86652036) and CCP4/STFC (521862101). Anastassis Perrakis acknowledges funding from iNEXT (grant No. 653706), iNEXT-Discovery (grant No. 871037), West-Life (grant No. 675858) and EOSC-Life (grant No. 824087) funded by the Horizon 2020 program of the European Commission. Robbie P. Joosten has been the recipient of a Veni grant (722.011.011) and a Vidi grant (723.013.003) from the Netherlands Organization for Scientific Research (NWO). Maarten L. Hekkelman, Robbie P. Joosten and Anastassis Perrakis thank the Research High Performance Computing facility of the Netherlands Cancer Institute for providing and maintaining computation resources and acknowledge the institutional grant from the Dutch Cancer Society and the Dutch Ministry of Health, Welfare and Sport. Tarik R. Drevon is funded by the BBSRC (BB/S007040/1). Randy J. Read is supported by a Principal Research Fellowship from the Wellcome Trust (grant 209407/Z/17/Z). Atlanta G. Cook is supported by a Wellcome Trust SRF (200898) and a Wellcome Centre for Cell Biology core grant (203149). Isabel Uso´n acknowledges support from STFC-UK/CCP4: ‘Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW’ and Spanish MICINN/AEI/FEDER/UE (PID2021-128751NB-I00). Pavol Skubak and Navraj Pannu were funded by the NWO Applied Sciences and Engineering Domain and CCP4 (grant Nos. 13337 and 16219). Bernhard Lohkamp was supported by the Ro¨ntgen A˚ ngstro¨m Cluster (grant 349-2013-597). Nicholas Pearce is currently funded by the SciLifeLab and Wallenberg Data Driven Life Science Program (grant KAW 2020.0239) and has previously been funded by a Veni Fellowship (VI.Veni.192.143) from the Dutch Research Council (NWO), a Long-term EMBO fellowship (ALTF 609-2017) and EPSRC grant EP/G037280/1. David M. Lawson received funding from BBSRC Institute Strategic Programme Grants (BB/P012523/1 and BB/P012574/1). Lucrezia Catapano is the recipient of an STFC/CCP4-funded PhD studentship (Agreement No: 7920 S2 2020 007).Peer reviewe