Searches for Squarks and Gluinos at CDF and D0 Detectors

This contribution reports on preliminary measurements on searches for squarks and gluinos at CDF and D\O detectors in $p\bar{p}$ collisions at $\sqrt{s}=1.96$ TeV. The analyses are performed using event topologies with multiple jets and large missing energy in the final state. The mSUGRA scenario and R-parity conservation is assumed. No excess with respect to the Standard Model predictions is observed and new limits on the gluino and squark masses are extracted.Comment: 3 pages, 2 figures, Proceedings Particles and Nuclei International Conference (PANIC 05), Santa Fe, NM, October 24-28, 200

Hardware acceleration of reaction-diffusion systems:a guide to optimisation of pattern formation algorithms using OpenACC

Reaction Diffusion Systems (RDS) have widespread applications in computational ecology, biology, computer graphics and the visual arts. For the former applications a major barrier to the development of effective simulation models is their computational complexity - it takes a great deal of processing power to simulate enough replicates such that reliable conclusions can be drawn. Optimizing the computation is thus highly desirable in order to obtain more results with less resources. Existing optimizations of RDS tend to be low-level and GPGPU based. Here we apply the higher-level OpenACC framework to two case studies: a simple RDS to learn the ‘workings’ of OpenACC and a more realistic and complex example. Our results show that simple parallelization directives and minimal data transfer can produce a useful performance improvement. The relative simplicity of porting OpenACC code between heterogeneous hardware is a key benefit to the scientific computing community in terms of speed-up and portability

Microscale heterogeneity of the spatial distribution of organic matter can promote bacterial biodiversity in soils: Insights from computer simulations

There is still no satisfactory understanding of the factors that enable soil microbial populations to be as highly biodiverse as they are. The present article explores in silico the hypothesis that the heterogeneous distribution of soil organic matter, in addition to the spatial connectivity of the soil moisture, might account for the observed microbial biodiversity in soils. A multi-species, individual-based, pore-scale model is developed and parameterized with data from 3 Arthrobacter sp. strains, known to be, respectively, competitive, versatile, and poorly competitive. In the simulations, bacteria of each strain are distributed in a 3D computed tomography (CT) image of a real soil and three water saturation levels (100, 50, and 25%) and spatial heterogeneity levels (high, intermediate, and low) in the distribution of the soil organic matter are considered. High and intermediate heterogeneity levels assume, respectively, an amount of particulate organic matter (POM) distributed in a single (high heterogeneity) or in four (intermediate heterogeneity) randomly placed fragments. POM is hydrolyzed at a constant rate following a first-order kinetic, and continuously delivers dissolved organic carbon (DOC) into the liquid phase, where it is then taken up by bacteria. The low heterogeneity level assumes that the food source is available from the start as DOC. Unlike the relative abundances of the 3 strains, the total bacterial biomass and respiration are similar under the high and intermediate resource heterogeneity schemes. The key result of the simulations is that spatial heterogeneity in the distribution of organic matter influences the maintenance of bacterial biodiversity. The least competing strain, which does not reach noticeable growth for the low and intermediate spatial heterogeneities of resource distribution, can grow appreciably and even become more abundant than the other strains in the absence of direct competition, if the placement of the resource is favorable. For geodesic distances exceeding 5 mm, microbial colonies cannot grow. These conclusions are conditioned by assumptions made in the model, yet they suggest that microscale factors need to be considered to better understand the root causes of the high biodiversity of soils

Gaia: la Galàxia en un petabyte

La missió Gaia de l'Agència Espacial Europea (ESA) es va llançar des del Centre Espacial de la Guaiana, a la Guaiana Francesa, el 19 de desembre de 2013 amb l'objectiu de determinar les posicions, moviments propis i distàncies de més de mil milions d'estrelles amb una precisió sense precedents. Aquestes dades permetran en els propers anys avenços significatius en moltes àrees de l'astrofísica, i en particular en el coneixement de la nostra galàxia. A més de constituir un repte tecnològic en si mateix, Gaia també suposa un repte en el tractament de les dades que generarà: uns 150TB enviats a terra, que es convertiran en 1PB en la base de dades resultant del seu processat. Per tal de processar aquestes dades s'ha format un consorci (DPAC) format per uns 450 cientifics i enginyers d'arreu d'Europa. Aquest consorci porta a terme diverses tasques, incloent el desenvolupament d'un simulador de missió, el processat massiu de dades i la implementació de l'arxiu que allotjarà les dades fi nals de la missió. Aquestes tasques son un bon exemple de com el processat de grans quantitats de dades científiques (Big Data) està esdevenint un repte tan significatiu com el de la construcció dels mateixos instruments

Individual-based observations and individual-based simulations to study Saccharomyces cerevisiae cultures

Saccharomyces cerevisiae is one of the yeasts with major economic, social, and health significance in human culture. Depending on the growth conditions experienced by the cell, S. cerevisiae growth can proceed via fermentative, respirative, or respirofermentative metabolism. Scar formation, unequal division, a limited replicative lifespan, and increase in cell size commensurate with the cell's replicative age are individual characteristics of this yeast affecting the performance of bioprocesses. These characteristics increase the complexity of predictive models and introducing them with ease into a continuous model is not realistic. Nevertheless, an individual-based model is able to accommodate this complexity in a single computational model. Once an individual model is implemented, it has to be parameterized, calibrated, and its adequacy assessed. All these processes ideally require a high number of both individual and system-level experimental observations. The aim of the present thesis is to advance the development of an individual-based methodology to tackle the study of microbial systems driven by the relevant yeast S. cerevisiae. The adequacy of INDISIM-YEAST, an existing individual-based model of a generic budding yeast, is first assessed. In order to obtain valuable individual-based observations to support the desired individual-based methodology, the diversity of S. cerevisiae in experimental individually-oriented observations under different growth conditions and at different stages of the growth curve is verified and assessed. A quantitative individual-based model focusing on the fermentative (anaerobic) growth of the yeast S. cerevisiae has been designed, implemented in Fortran 90, and termed INDISIM-Saccha. The developed model is parameterized, calibrated, its adequacy evaluated, and used to assess in silico ethanol production by means of virtual experiments. The calibration procedure, and the performance and analysis of the data from the virtual experiments is undertaken using the statistical programming language R. The model adequacy is assessed by testing several model predictions both at a system level (glucose depletion, population growth curves) and single-cell level (fraction of budded cells, genealogical age distribution, and cell diameter distribution evolutions). Individual cell diameter observations obtained within the present thesis play a significant role in this assessment. Results of the virtual experiments suggest that differences in cell size distribution can drastically affect the performance and productivity of fermentations, and encourage routine characterization of the inocula in the biotechnological industry. INDISIM-Saccha is also adapted to take into account the aerobic growth of S. cerevisiae and contrasted with two experimental trials with different oxygen levels in the medium. The preliminary simulated results achieved with the model suggest that the approach also has the potential for reproducing aerobic batch cultures of S. cerevisiae. This represents a further step in obtaining a microbial individual-based model to account for the whole set of metabolic alternatives experienced by S. cerevisiae. In order to communicate efficiently, increase accessibility, and favour usability of the INDISIM-Saccha methodology developed, the present thesis also designs and implements INDISIM-YEAST-NL in the freely available programming environment NetLogo. The implementation of this streamlined model in NetLogo lays the foundations for a deeper understanding of the developed methodology and microbial individual-based models in general, and will facilitate future interactions with potential users of INDISIM-Saccha.El Saccharomyces cerevisiae és un dels llevats que gaudeix de més significació econòmica, social i per a la salut humana. Depenent de les condicions experimentades, el llevat S. cerevisiae pot créixer mitjançant un metabolisme fermentatiu, respiratori o respirofermentatiu. La formació de cicatrius, una divisió desigual, una vida replicativa limitada i un increment de la mida de la cèl.lula amb l’edat replicativa són característiques individuals d’aquest llevat que afecten el comportament dels bioprocessos. Aquestes característiques incrementen la complexitat dels models predictius i dificulten, per tant, la seva inclusió en un model continu de manera realista. No obstant això, un model basat en l’individu sí que és capaç d’acomodar tota aquesta complexitat en un únic model computacional. Una vegada implementat, un model basat en l’individu ha de ser parametritzat, calibrat i la seva adequació ha de ser avaluada. Tots aquests processos requereixen idealment un gran nombre d’observacions experimentals, tant individuals com a nivell del sistema estudiat. L’objectiu general de la tesi present és avançar en el desenvolupament d’una metodologia basada en l’individu per estudiar sistemes microbians conduïts pel llevat S. cerevisiae. Primerament s’avalua l’adequació de INDISIM-YEAST, un model basat en l’individu, ja existent, focalitzat en un llevat genèric. Es verifica i s’avalua la diversitat del S. cerevisiae en observacions experimentals orientades a l’individu en diferents condicions de creixement i en diversos estadis de la corba de creixement de la població. Això permet obtenir observacions basades en l’individu molt valuoses a l’hora de donar suport a la metodologia desitjada. Es desenvolupa i s’implementa en Fortran 90 INDISIM-Saccha, un model quantitatiu basat en l’individu i focalitzat en el creixement fermentatiu (anaerobi) del S. cerevisiae. El model desenvolupat és parametritzat, calibrat, la seva adequació és avaluada i és utilitzat per estudiar in silico la producció d’etanol mitjançant experiments virtuals. El procés de calibratge, l’obtenció i l’anàlisi de les dades dels experiments virtuals s’han realitzat utilitzant el programari estadístic R. L’adequació del model s’avalua testejant diferents prediccions del model a nivell de sistema (corbes de disminució de la glucosa i de creixement de la població) i a nivell de la cèllula individual (evolucions temporals de la fracció de cèl.lules gemades, de la distribució d’edats genealògiques i de la distribució dels diàmetres cel.lulars). Les observacions del diàmetre de les cèl.lules individuals obtingudes a la tesi present juguen un paper significatiu en aquesta avaluació. Els resultats dels experiments virtuals suggereixen que les diferències en la distribució de mides cel.lulars poden afectar dràsticament l’evolució i la productivitat de les fermentacions i suggereixen una caracterització rutinària de l’inòcul a la indústria biotecnològica. L’INDISIM-Saccha també és adaptat per tenir en compte el creixement aeròbic del S. cerevisiae i és contrastat mitjançant dos assajos experimentals amb dos nivells d’oxigen al medi. Els resultats preliminars de la simulació denoten que aquesta aproximació també té el potencial de reproduir cultius discontinus aerobis del S. cerevisiae. Això representa un pas endavant cap a l’obtenció d’un model basat en l’individu que tingui en compte tot el conjunt d’alternatives metabòliques experimentades pel S. cerevisiae. Finalment, aquesta tesi també dissenya i implementa INDISIM-YEAST-NL en l’ambient de programació lliure anomenat NetLogo per tal de comunicar de manera eficient, d’incrementar l’accessibilitat i d’afavorir l’ús de la metodologia INDISIM-Saccha. La implementació d’aquest model simplificat amb NetLogo posa les bases per a una comprensió més alta de la metodologia desenvolupada, i dels models microbians basats en l’individu en general, i facilitarà futures interaccions amb usuaris potencials de l’INDISIM-Saccha

Digital image analysis of yeast single calls growing in two different oxygen concentrations to analyze the population growth and to assist individual-based modeling

Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM-Saccha. Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then discussed and compared to simulation results generated with INDISIM-Saccha, which allowed us to advance in the development of this yeast model, and illustrated the utility of data at different levels of observation and the needs and logic behind the development of a microbial individual-based model