Summary of the searches for squarks and gluinos using root s=8 TeV pp collisions with the ATLAS experiment at the LHC

A summary is presented of ATLAS searches for gluinos and first- and second-generation squarks in final states containing jets and missing transverse momentum, with or without leptons or b-jets, in the s√=8 TeV data set collected at the Large Hadron Collider in 2012. This paper reports the results of new interpretations and statistical combinations of previously published analyses, as well as a new analysis. Since no significant excess of events over the Standard Model expectation is observed, the data are used to set limits in a variety of models. In all the considered simplified models that assume R-parity conservation, the limit on the gluino mass exceeds 1150 GeV at 95% confidence level, for an LSP mass smaller than 100 GeV. Furthermore, exclusion limits are set for left-handed squarks in a phenomenological MSSM model, a minimal Supergravity/Constrained MSSM model, R-parity-violation scenarios, a minimal gauge-mediated supersymmetry breaking model, a natural gauge mediation model, a non-universal Higgs mass model with gaugino mediation and a minimal model of universal extra dimensions.

Search for metastable heavy charged particles with large ionisation energy loss in pp collisions at root s=8 TeV using the ATLAS experiment

Many extensions of the Standard Model predict the existence of charged heavy long-lived particles, such as R-hadrons or charginos. These particles, if produced at the Large Hadron Collider, should be moving non-relativistically and are therefore identifiable through the measurement of an anomalously large specific energy loss in the ATLAS pixel detector. Measuring heavy long-lived particles through their track parameters in the vicinity of the interaction vertex provides sensitivity to metastable particles with lifetimes from 0.6 ns to 30 ns. A search for such particles with the ATLAS detector at the Large Hadron Collider is presented, based on a data sample corresponding to an integrated luminosity of 18.4 fb−1 of pp collisions at s√ = 8 TeV. No significant deviation from the Standard Model background expectation is observed, and lifetime-dependent upper limits on R-hadrons and chargino production are set. Gluino R-hadrons with 10 ns lifetime and masses up to 1185 GeV are excluded at 95% confidence level, and so are charginos with 15 ns lifetime and masses up to 482 GeV.

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.

Estrategias estadístico-computacionales avanzadas para análisis de expresión de proteínas/genes en cáncer. Advanced statistical and computational strategies for protein/gene expression analysis in cancer.

El objetivo de este proyecto, enmarcado en el área de metodología de análisis en bioingeniería-biotecnología aplicadas al estudio del cancer, es el análisis y caracterización a través modelos estadísticos con efectos mixtos y técnicas de aprendizaje automático, de perfiles de expresión de proteínas y genes de las vías metabolicas asociadas a progresión tumoral. Dicho estudio se llevará a cabo mediante la utilización de tecnologías de alto rendimiento. Las mismas permiten evaluar miles de genes/proteínas en forma simultánea, generando así una gran cantidad de datos de expresión. Se hipotetiza que para un análisis e interpretación de la información subyacente, caracterizada por su abundancia y complejidad, podría realizarse mediante técnicas estadístico-computacionales eficientes en el contexto de modelos mixtos y técnias de aprendizaje automático. Para que el análisis sea efectivo es necesario contemplar los efectos ocasionados por los diferentes factores experimentales ajenos al fenómeno biológico bajo estudio. Estos efectos pueden enmascarar la información subycente y así perder informacion relavante en el contexto de progresión tumoral. La identificación de estos efectos permitirá obtener, eficientemente, los perfiles de expresión molecular que podrían permitir el desarrollo de métodos de diagnóstico basados en ellos. Con este trabajo se espera poner a disposición de investigadores de nuestro medio, herramientas y procedimientos de análisis que maximicen la eficiencia en el uso de los recursos asignados a la masiva captura de datos genómicos/proteómicos que permitan extraer información biológica relevante pertinente al análisis, clasificación o predicción de cáncer, el diseño de tratamientos y terapias específicos y el mejoramiento de los métodos de detección como así tambien aportar al entendimieto de la progresión tumoral mediante análisis computacional intensivo.

Vorbereitungen für das Biolab Experiment TRIPLE LUX A : Hardwareentwicklung, Kalibrierung und biologische Bodenkontrollen

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2011

Flame simulation in rotary kilns using computational fluid dynamics

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2011

Variations and application conditions of the data type "Image" : the foundation of computational visualistics

Visualistics, computer science, picture syntax, picture semantics, picture pragmatics, interactive pictures

Analysis of complex microwave structures using suitable computational electromagnetic techniques

Complex Microwave Structures Wake Field Computatation PETRA III Generalized Multipole Technique Antenna Antennen Wakefelder Berechnung

Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods

Optimization of radial jets mixing in cross-flow of combustion chambers using computational fluid dynamics

Cross-Flow, Radial Jets Mixing, Temperature Homogenization, Optimization, Combustion Chamber, CFD

Neural correlates of context-dependent memory : the role of the insula in episodic encoding and recognition memory ; an fMRI experiment

Magdeburg, Univ., Med. Fak., Diss., 2014