Analysis of blasting vibrations produced In a gold mine using the damage prevention abacus

The present work was partially funded by Perforaciones Noroeste S.A. in the frame of the University-Company collaboration project FUO-20-052Peer ReviewedObjectius de Desenvolupament Sostenible::12 - Producció i Consum ResponsablesObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

Representative-area approach to define blast-induced ground vibrations-damage prevention criterion abacus

Peer ReviewedObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura::9.2 - Promoure una industrialització inclusiva i sostenible i, a tot tardar el 2030, augmentar de manera significativa la contribució de la indústria a l’ocupació i al producte interior brut, d’acord amb les circumstàncies nacionals, i duplicar aquesta contribució als països menys avançatsObjectius de Desenvolupament Sostenible::12 - Producció i Consum ResponsablesObjectius de Desenvolupament Sostenible::12 - Producció i Consum Responsables::12.2 - Per a 2030, assolir la gestió sostenible i l’ús eficient dels recursos naturalsPostprint (published version

Adaptive surrogates of crashworthiness models for multi-purpose engineering analyses accounting for uncertainty

© 2022 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Uncertainty Quantification (UQ) is a booming discipline for complex computational models based on the analysis of robustness, reliability and credibility. UQ analysis for nonlinear crash models with high dimensional outputs presents important challenges. In crashworthiness, nonlinear structural behaviours with multiple hidden modes require expensive models (18 h for a single run). Surrogate models (metamodels) allow substituting the full order model, introducing a response surface for a reduced training set of numerical experiments. Moreover, uncertain input and large number of degrees of freedom result in high dimensional problems, which derives to a bottle neck that blocks the computational efficiency of the metamodels. Kernel Principal Component Analysis (kPCA) is a multidimensionality reduction technique for non-linear problems, with the advantage of capturing the most relevant information from the response and improving the efficiency of the metamodel. Aiming to compute the minimum number of samples with the full order model. The proposed methodology is tested with a practical industrial problem that arises from the automotive industry.This work is partially funded by Generalitat de Catalunya (Grant Number 1278 SGR 2017-2019 and Pla de Doctorats Industrials 2017 DI 058) and Ministerio de Economía y Empresa and Ministerio de Ciencia, Innovación y Universidades (Grant Number DPI2017-85139-C2-2-R).Peer ReviewedPostprint (author's final draft

Directional core drilling as an approach to reduce uncertainty in tunneling construction

The definition of a rock mass’s characteristics is crucial in underground construction to avoid delays and cost overruns. This study proposes a system to quantify the economic uncertainty related to a lack of knowledge of a rock mass in the tunnel construction stage, either for tunnel boring machines or for drill and blast excavation techniques. Using a back-analysis of three actual tunnels completed in Spain (Burata, Lot 3 of the Pajares variant, and Bolaños), the study assessed the directional core drilling technique (DCD) for this purpose, comparing it with conventional boreholes. In this regard, the DCD approach reduced the uncertainty by between EUR 6.7 and EUR 12.7 for every EUR 1, while the total cost of the drilling campaign remained within a widely accepted proportion of the construction budget. Overall, the uncertainty was reduced by approximately EUR 6000 per meter of the tunnel.Peer ReviewedObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

Nonintrusive Uncertainty Quantification for automotive crash problems with VPS/Pamcrash

Uncertainty Quantification (UQ) is a key discipline for computational modeling of complex systems, enhancing reliability of engineering simulations. In crashworthiness, having an accurate assessment of the behavior of the model uncertainty allows reducing the number of prototypes and associated costs. Carrying out UQ in this framework is especially challenging because it requires highly expensive simulations. In this context, surrogate models (metamodels) allow drastically reducing the computational cost of Monte Carlo process. Different techniques to describe the metamodel are considered, Ordinary Kriging, Polynomial Response Surfaces and a novel strategy (based on Proper Generalized Decomposition) denoted by Separated Response Surface (SRS). A large number of uncertain input parameters may jeopardize the efficiency of the metamodels. Thus, previous to define a metamodel, kernel Principal Component Analysis (kPCA) is found to be effective to simplify the model outcome description. A benchmark crash test is used to show the efficiency of combining metamodels with kPCA

Bathymetric map of the Gulf of Cadiz, NE Atlantic Ocean: The SWIM multibeam compilation

Marine Technology Workshop (Martech05), 17-18 November 2005, Vilanova i la Geltrú, Barcelona.-- 2 pages, 1 figurePeer Reviewe

A robust multicriteria analysis for the post-treatment of digestate from low-tech digesters. Boosting the circular bioeconomy of small-scale farms in Colombia

Low-tech digesters are sustainable technologies to produce a clean fuel (biogas), which can be used for cooking and heating. Moreover, the degradation of organic waste in the digester also produces a liquid effluent (digestate), which can be reused in agriculture as a biofertilizer. The direct application of digestate to the soil may not be either feasible due to regulations or safe due to poor quality. The study aims to apply, for the first time, a multicriteria analysis to select the most suitable solution for the post-treatment and reuse of digestate from low-tech digesters implemented in small-scale farms. The post-treatments considered are: a degassing tank, a sand filter, a vermifilter, digestate recirculation, a facultative pond, and combinations of them. Ten criteria and twenty-one sub-criteria including technical, environmental and socio-economic aspects are defined to be weighted by experts. The analysis employs triangular fuzzy numbers to consider uncertainty and increase the robustness of the results, and it is validated using three case studies in Colombia. The alternatives are designed using data collected in-situ on the design and operation of the digesters and the quality of the digestates. Results confirm the robustness of the rankings and show that vermifiltration is the best alternative for the post-treatment of digestates from low-tech digesters implemented in small-scale farms. It is due to the fact that it produces a high-quality biofertilizer, it is easy to manage and it is implemented using local materials. Other prominent alternatives are sand filtration, recirculation and a degassing tank coupled with vermifiltration.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.1 - Per a 2030, garantir l’accés universal a serveis d’energia assequibles, confiables i modernsObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.a - Per a 2030, augmentar la cooperació internacional per tal de facilitar l’accés a la investigació i a les tecnolo­gies energètiques no contaminants, incloses les fonts d’energia renovables, l’eficiència energètica i les tecnologies de combustibles fòssils avançades i menys contaminants, i promoure la inversió en infraestructures energètiques i tecnologies d’energia no contaminantObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.b - Per a 2030, ampliar la infraestructura i millorar la tecnologia per tal d’oferir serveis d’energia moderns i sos­tenibles per a tots els països en desenvolupament, en particular els països menys avançats, els petits estats insulars en desenvolupament i els països en desenvolupament sense litoral, d’acord amb els programes de suport respectiusPostprint (author's final draft

XPF-Dependent DNA Breaks and RNA Polymerase II Arrest Induced by Antitumor DNA Interstrand Crosslinking-Mimetic Alkaloids

SummaryTrabectedin and Zalypsis are two potent anticancer tetrahydroisoquinoline alkaloids that can form a covalent bond with the amino group of a guanine in selected triplets of DNA duplexes and eventually give rise to double-strand breaks. Using well-defined in vitro and in vivo assays, we show that the resulting DNA adducts stimulate, in a concentration-dependent manner, cleavage by the XPF/ERCC1 nuclease on the strand opposite to that bonded by the drug. They also inhibit RNA synthesis by: (1) preventing binding of transcription factors like Sp1 to DNA, and (2) arresting elongating RNA polymerase II at the same nucleotide position regardless of the strand they are located on. Structural models provide a rationale for these findings and highlight the similarity between this type of DNA modification and an interstrand crosslink

Clinical implications of the intrinsic molecular subtypes of breast cancer

AbstractGene-expression profiling has had a considerable impact on our understanding of breast cancer biology. During the last 15 years, 5 intrinsic molecular subtypes of breast cancer (Luminal A, Luminal B, HER2-enriched, Basal-like and Claudin-low) have been identified and intensively studied. In this review, we will focus on the current and future clinical implications of the intrinsic molecular subtypes beyond the current pathological-based classification endorsed by the 2013 St. Gallen Consensus Recommendations. Within hormone receptor-positive and HER2-negative early breast cancer, the Luminal A and B subtypes predict 10-year outcome regardless of systemic treatment administered as well as residual risk of distant recurrence after 5 years of endocrine therapy. Within clinically HER2-positive disease, the 4 main intrinsic subtypes can be identified and dominate the biological and clinical phenotype. From a clinical perspective, patients with HER2+/HER2-enriched disease seem to benefit the most from neoadjuvant trastuzumab, or dual HER2 blockade with trastuzumab/lapatinib, in combination with chemotherapy, and patients with HER2+/Luminal A disease seem to have a relative better outcome compared to the other subtypes. Finally, within triple-negative breast cancer (TNBC), the Basal-like disease predominates (70–80%) and, from a biological perspective, should be considered a cancer-type by itself. Importantly, the distinction between Basal-like versus non-Basal-like within TNBC might predict survival following (neo)adjvuvant multi-agent chemotherapy, bevacizumab benefit in the neoadjuvant setting (CALGB40603), and docetaxel vs. carboplatin benefit in first-line metastatic disease (TNT study). Overall, this data suggests that intrinsic molecular profiling provides clinically relevant information beyond current pathology-based classifications