A5052758540- Cancer Genomics and Diagnostics
- Dam Engineering and Safety
- Hydraulic flow and structures
- Hydrology and Sediment Transport Processes
- Water resources management and optimization
- Bioinformatics and Genomic Networks
- Water Quality Monitoring and Analysis
- Lung Cancer Treatments and Mutations
- Distributed and Parallel Computing Systems
- Radiomics and Machine Learning in Medical Imaging
- Water Quality Monitoring Technologies
- Hydrology and Watershed Management Studies
- Air Quality Monitoring and Forecasting
- Chromosomal and Genetic Variations
- Genomics and Chromatin Dynamics
- Water Treatment and Disinfection
- Genomics and Phylogenetic Studies
- Advanced Data Storage Technologies
- Data Stream Mining Techniques
- Water Systems and Optimization
- Water-Energy-Food Nexus Studies
- Genomic variations and chromosomal abnormalities
- Nutrition, Genetics, and Disease
- Lung Cancer Research Studies
- Gene expression and cancer classification
Universitat Politècnica de Catalunya
2014-2025
International Center for Numerical Methods in Engineering
2016-2025
Barcelona Supercomputing Center
2009-2024
Hospital Universitario Virgen Macarena
2024
Institució Catalana de Recerca i Estudis Avançats
2020
University of Graz
2018-2020
Heidelberg University
2020
Universidad Politécnica de Madrid
2014-2015
Pressure management (PM) is commonly used in water distribution systems (WDSs). In the last decade, a strategic objective field has been development of new scientific and technical methods for its implementation. However, due to lack systematic analysis results obtained practical cases, progress not always reflected actions. To address this problem, paper provides comprehensive most innovative issues related PM. The methodology proposed based on case-study comparison qualitative concepts...
The removal of contaminants through Advanced Oxidation Processes (AOPs) is a complex task that demands the simultaneous consideration multiple operating parameters, such as type and concentration oxidant catalyst, intensity radiation, composition aqueous matrix, etc. Designing efficient AOPs often requires expensive time-consuming laboratory experiments. To improve this process, study proposes Machine Learning approach based on Random Forest (RF) model, to predict Enterococcus sp. in...
Abstract Dam monitoring is crucial for behavior analysis and safety assessment. The data recorded by systems are the basis of behavioral models. Ensuring quality these vital making informed decisions improving prediction accuracy. However, often contain errors that need to be corrected before use. As acquisition become increasingly automated, resulting large databases present challenges conventional methods cannot effectively address. This work proposes a methodology based on autoencoders...
Abstract Introduction Continuous monitoring of the oncological process is essential for identifying inefficiencies and areas improvement, enabling better resource allocation in care lung cancer patients. Objective The objective to define key indicators identify critical variables care, aiming improve early detection, reduce delays diagnosis treatment, enhance biomarker research, ensuring timely effective treatments all Methods A multidisciplinary expert group conducted a consensus based on...
A methodology for computing thermal loads in arch dams is proposed. The considers the nonuniform distribution of solar insolation over dam faces because shading, curvature faces, orientation, and slopes. Because, most cases, mean daily global radiation only type available, a estimating hourly energy reaching described. applied to case study where observations from 21 thermometers embedded concrete data climatic variables are available. temperature field successfully computed, with good...
Dam safety assessment is typically made by comparison between the outcome of some predictive model and measured monitoring data. This done separately for each response variable, results are later interpreted before decision making. In this work, three approaches based on machine learning classifiers evaluated joint analysis a set variables: multi-class, two-class one-class classification. Support vector machines applied to all prediction tasks, random forest also used multi-class two-class....
This paper presents and evaluates a method to predict DRAM uncorrected errors, leading cause of hardware failures in large-scale HPC clusters. The uses random forest classifier, which was trained evaluated using error logs from two years production the MareNostrum 3 supercomputer. By enabling system take measures mitigate node failures, our reduces lost compute time by up 57%, net saving 21,000 node-hours per year. We release all source code as open source. also discuss clarify aspects...
LBA8612 Background: Amivantamab (ami), an EGFR-MET bispecific antibody with immune cell-directing activity, is approved as intravenous (IV) formulation. IV ami + lazertinib (laz), a 3 rd -generation EGFR TKI, demonstrated superior progression-free survival (PFS) in patients (pts) treatment-naïve, advanced EGFR-mutated NSCLC vs osimertinib (Cho Ann Oncol 2023). Subcutaneous (SC) substantially reduced infusion-related reactions (16% 67%) and administration time (≤7 mins 2–4 hours) historical...
Recent decades have witnessed an increasing number of large to very imaging studies, prominently in the field neurodegenerative diseases. The datasets collected during these studies form essential resources for research aiming at new biomarkers. Collecting, hosting, managing, processing, or reviewing those is typically achieved through a local neuroinformatics infrastructure. In particular organizations with their own equipment, setting up such system still hard task, and relying on...
We designed and implemented a parallel visualisation system for the analysis of large scale time-dependent particle type data. The particular challenge we address is how to analyse high perfor- mance computation style dataset when visual representation full set not possible or useful, one only interested in finding inspecting smaller subsets that fulfil certain complex criteria. used Paraview as user interface, which familiar tool many HPC users, runs parallel, can be conveniently extended....
The construction of double‐curvature arch dams is an attractive solution from economic viewpoint due to the reduced volume concrete necessary for their as compared conventional gravity dams. Due complex geometry, many criteria have arisen design. However, most widespread methods are based on recommendations traditional technical documents without taking into account possibilities computer‐aided In this paper, innovative software tool design FEM models presented. Several capabilities allowed:...
We study the recovery of piecewise constant functions finite bounded variation (BV) from their image under a linear partial differential operator with unknown boundary conditions. It is shown that minimizing total (TV) semi-norm subject to associated PDE-constraints yields perfect reconstruction up global mild geometric assumption on jump set function reconstruct. The proof bases establishing structural result about BV-solutions homogeneous PDE. Furthermore, we show satisfied negligible...
Clusters of emerging technologies are appearing with more and frequency in HPC. After years skepticism, data-centers adopting them as production systems thanks to several geopolitical technological factors. The most honorable example is the Fugaku supercomputer, powered by latest Fujitsu A64FX CPU. Which behavior mature HPC codes on such technology clusters? performance will obtain scientists when running their applications "as is" these This paper presents evaluation CTE-Arm, a Fugaku-like...