Modelado termo-metalúrgico del enfriamiento de una fundición nodular

Tesis (DCI)--FCEFN-UNC, 2012En esta tesis se desarrolla un nuevo modelo termo-metalúrgico de los cambios de fase difusionales de la austenita que ocurren durante el enfriamiento continuo de una fundición nodular. El modelo se implementa en un programa de elementos finitos y se aplica en un estudio paramétrico y en la simulación del enfriamiento de una fundición nodular eutéctica colada en dos probeteros: uno de sección circular y otro cuadrada. Los resultados numéricos obtenidos y su comparación con los resultados experimentales ponen de manifiesto la necesidad de modelar los procesos termometal úrgicos en múltiples escalas y la validez de algunas de las hipótesis propuestas en esta tesis.Fil: Carazo Rodríguez, Fernando Diego. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.

About Equilibrium Mode Ruling Ferritic Transformation in Low-Alloy SGI

Ferrite precipitating around the graphite nodules shaping the typical bull’s-eye microstructure could grow under negligible partitioning local equilibrium or under paraequilibrium conditions, as both imply that ferrite inherits the composition of the parent austenite. The first mechanism has been rejected by other researchers by means of simple calculations of the silicon spike width necessary for local equilibrium conditions to take place. Nevertheless, experimental analyses are necessary to verify this conclusion. In this study, transmission electron microscopy has been used to assess the presence of a silicon spike in front of the growing ferrite interface. The outcome allowed the authors to confirm that a paraequilibrium mode governs the transformation, supporting the conclusions of previous calculations. In addition, some issues about ferrite growth modeling are discussed.Fil: García, Laura Noel. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Mecánica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Carazo, Fernando Diego. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Mecánica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Boeri, Roberto Enrique. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Mecánica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

Reducing the LSQ and L1 Data Cache Power Consuption

In most modern processor designs, the HW dedicated to store data and instructions (memory hierarchy) has become a major consumer of power. In order to reduce this power consumption, we propose in this paper two techniques, one to filter accesses to the LSQ (Load-Store Queue) based on both timing and address information, and the other to filter accesses to the first level data cache based on a forwarding predictor. Our simulation results show that the power consumption decreases in 30-40% in each structure, with a negligible performance penalty of less than 0.1%

Reducción de consumo en la caché de datos de nivel 1 utilizando un predictor de forwarding

En la mayoría de los diseños de los procesadores actuales, el acceso a la caché de datos de nivel 1 (L1D) se ha convertido en uno de los componentes de mayor consumo debido a su incremento de tamaño y elevadas frecuencias de acceso. Para reducir este consumo, proponemos una sencilla técnica de filtrado. Nuestra idea se basa en un predictor de forwarding de alta precisión que determina si una instrucción de load tomará su dato vía forwarding a través de la LSQ –evitando en este caso el acceso a la L1D- o si debe ir a por él a la caché de datos. Nuestros resultados de simulación muestran que podemos ahorrar de media un 35% del consumo de la L1D, con una degradación despreciable de rendimient

Reducing the LSQ and L1 data cache power consumption

In most modern processor designs, the HW dedicated to store data and instructions (memory hierarchy) has become a major consumer of power. In order to reduce this power consumption, we propose in this paper two techniques, one to filter accesses to the LSQ (Load-Store Queue) based on both timing and address information, and the other to filter accesses to the first level data cache based on a forwarding predictor. Our simulation results show that the power consumption decreases in 30-40% in each structure, with a negligible performance penalty of less than 0.1%.Presentado en el V Workshop Arquitectura, Redes y Sistemas Operativos (WARSO)Red de Universidades con Carreras en Informática (RedUNCI

Integration of CLIP experiments of RNAbinding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data

Background: Splicing is a genetic process that has important implications in several diseases including cancer. Deciphering the complex rules of splicing regulation is crucial to understand and treat splicing-related diseases. Splicing factors and other RNA-binding proteins (RBPs) play a key role in the regulation of splicing. The specific binding sites of an RBP can be measured using CLIP experiments. However, to unveil which RBPs regulate a condition, it is necessary to have a priori hypotheses, as a single CLIP experiment targets a single protein. Results: In this work, we present a novel methodology to predict context-specific splicing factors from transcriptomic data. For this, we systematically collect, integrate and analyze more than 900 CLIP experiments stored in four CLIP databases: POSTAR2, CLIPdb, DoRiNA and StarBase. The analysis of these experiments shows the strong coherence between the binding sites of RBPs of similar families. Augmenting this information with expression changes, we are able to correctly predict the splicing factors that regulate splicing in two gold-standard experiments in which specific splicing factors are knocked-down. Conclusions: The methodology presented in this study allows the prediction of active splicing factors in either cancer or any other condition by only using the information of transcript expression. This approach opens a wide range of possible studies to understand the splicing regulation of different conditions. A tutorial with the source code and databases is available at https://gitlab.com/fcarazo.m/sfprediction

Reducing cache hierarchy energy consumption by predicting forwarding and disabling associative sets

The first level data cache in modern processors has become a major consumer of energy due to its increasing size and high frequency access rate. In order to reduce this high energy consumption, we propose in this paper a straightforward filtering technique based on a highly accurate forwarding predictor. Specifically, a simple structure predicts whether a load instruction will obtain its corresponding data via forwarding from the load-store structure - thus avoiding the data cache access - or if it will be provided by the data cache. This mechanism manages to reduce the data cache energy consumption by an average of 21.5% with a negligible performance penalty of less than 0.1%. Furthermore, in this paper we focus on the cache static energy consumption too by disabling a portion of sets of the L2 associative cache. Overall, when merging both proposals, the combined L1 and L2 total energy consumption is reduced by an average of 29.2% with a performance penalty of just 0.25%

TranscriptAchilles: a genome-wide platform to predict isoform biomarkers of gene essentiality in cancer

Background Aberrant alternative splicing plays a key role in cancer development. In recent years, alternative splicing has been used as a prognosis biomarker, a therapy response biomarker, and even as a therapeutic target. Next-generation RNA sequencing has an unprecedented potential to measure the transcriptome. However, due to the complexity of dealing with isoforms, the scientific community has not sufficiently exploited this valuable resource in precision medicine. Findings We present TranscriptAchilles, the first large-scale tool to predict transcript biomarkers associated with gene essentiality in cancer. This application integrates 412 loss-of-function RNA interference screens of >17,000 genes, together with their corresponding whole-transcriptome expression profiling. Using this tool, we have studied which are the cancer subtypes for which alternative splicing plays a significant role to state gene essentiality. In addition, we include a case study of renal cell carcinoma that shows the biological soundness of the results. The databases, the source code, and a guide to build the platform within a Docker container are available at GitLab. The application is also available online. Conclusions TranscriptAchilles provides a user-friendly web interface to identify transcript or gene biomarkers of gene essentiality, which could be used as a starting point for a drug development project. This approach opens a wide range of translational applications in cancer

Rehabilitación energética de la ETSAM: análisis-diagnóstico-propuesta

Rehabilitación energética de la ETSAM: análisis, diagnóstico, propuest

ISOGO: Functional annotation of protein-coding splice variants

The advent of RNA-seq technologies has switched the paradigm of genetic analysis from a genome to a transcriptome-based perspective. Alternative splicing generates functional diversity in genes, but the precise functions of many individual isoforms are yet to be elucidated. Gene Ontology was developed to annotate gene products according to their biological processes, molecular functions and cellular components. Despite a single gene may have several gene products, most annotations are not isoform-specifc and do not distinguish the functions of the diferent proteins originated from a single gene. Several approaches have tried to automatically annotate ontologies at the isoform level, but this has shown to be a daunting task. We have developed ISOGO (ISOform+GO function imputation), a novel algorithm to predict the function of coding isoforms based on their protein domains and their correlation of expression along 11,373 cancer patients. Combining these two sources of information outperforms previous approaches: it provides an area under precision-recall curve (AUPRC) fve times larger than previous attempts and the median AUROC of assigned functions to genes is 0.82. We tested ISOGO predictions on some genes with isoform-specifc functions (BRCA1, MADD,VAMP7 and ITSN1) and they were coherent with the literature. Besides, we examined whether the main isoform of each gene -as predicted by APPRIS- was the most likely to have the annotated gene functions and it occurs in 99.4% of the genes. We also evaluated the predictions for isoform-specifc functions provided by the CAFA3 challenge and results were also convincing. To make these results available to the scientifc community, we have deployed a web application to consult ISOGO predictions (https://biotecnun.unav. es/app/isogo). Initial data, website link, isoform-specifc GO function predictions and R code is available at https://gitlab.com/icassol/isogo