Process and machine system development for the forming of miniature/micro sheet metal products

This paper reports on the current development of the process for the forming of thin sheet-metal micro-parts (t < 50µm) and the corresponding machine system which is part of the research and technological development of an EU funded integrated project - MASMICRO ("Integration of Manufacturing Systems for the Mass-Manufacture of Miniature/Micro-Products" (/www.masmicro.net/). The process development started with qualification of the fundamentals related to the forming of thin sheet-metals in industrial environment, for which a testing machine and several sets of the testing tools were developed. The process was further optimised, followed by new tool designs. Based on the experience gained during the process development, a new forming press which is suitable for industrial, mass-customised production, has been designed

A Finite Element based Deep Learning solver for parametric PDEs

We introduce a dynamic Deep Learning (DL) architecture based on the Finite Element Method (FEM) to solve linear parametric Partial Differential Equations(PDEs). The connections between neurons in the architecture mimic the Finite Element connectivity graph when applying mesh refinements. We select and discuss several losses employing preconditioners and different norms to enhance convergence. For simplicity, we implement the resulting Deep-FEM in one spatial domain (1D), although its extension to 2D and 3D problems is straightforward. Extensive numerical experiments show in general good approximations for both symmetric positive definite (SPD) and indefinite problems in parametric and non-parametric problems. However, in some cases, lack of convexity prevents us from obtaining high-accuracy solutions.This work has received funding from: the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 777778 (MATHROCKS); the European Regional Development Fund (ERDF) through the Interreg V-A Spain-France-Andorra program POCTEFA 2014-2020 Project PIXIL (EFA362/19); the Spanish Ministry of Science and Innovation projects with references PID2019-108111RB-I00 (FEDER/AEI) and PDC2021-121093-I00, the "BCAM Severo Ochoa" accreditation of excellence (SEV-2017-0718); and the Basque Government through the BERC 2018-2021 program, the three Elkartek projects 3KIA (KK-2020/00049), EXPERTIA (KK-2021/00048), and SIGZE (KK-2021/00095), and the Consolidated Research Group MATHMODE (IT1294-19) given by the Department of Education

The emerging oral pathogen, Filifactor alocis, modulates antimicrobial responses of primed human neutrophils.

Almost 50% of the adult population older than 30 years of age suffers from some form of periodontitis, a chronic inflammatory disease of the periodontal tissue caused by microbial subversion of the host immune response. Neutrophils are the most abundant leukocyte present in the oral mucosa. In periodontitis, periodontal pathogens have developed strategies to evade neutrophil antimicrobial responses and promote bacterial growth. Among these oral pathogens is Filifactor alocis which can modulate neutrophils’ antimicrobial responses by preventing phagosome maturation. During inflammation, neutrophils that reach the gingival tissue are primed by cytokines and chemokines. However, the response of primed human neutrophils to F. alocis is currently unknown. To address this gap in knowledge, human neutrophils were primed with TNF-α, an established priming agent, and the kinetics of phagocytosis and intracellular ROS production in response to serum opsonized F. alocis were tested. Our results showed a significant increase in phagocytosis of F. alocisby TNF-α-primed neutrophils compared to unprimed cells. However, the significant increase in bacteria uptake was not accompanied by increased ROS production. F. alocis significantly downregulated the respiratory burst response in human neutrophils independently of priming with TNF-α. Interestingly, priming of neutrophils with IL-8 did not result in a significant increase in phagocytosis of F. alocis, but IL-8-primed neutrophils did have a similar ROS phenotype to TNF-α-primed neutrophils. This suggests dome ability of F. alcois to modulate the phagocytic ability of IL-8-primed neutrophils. Future studies will aim to characterize F. alocis’ virulence factors that modulate neutrophil responses

A Deep Double Ritz Method (D2RM) for solving Partial Differential Equations using Neural Networks

Residual minimization is a widely used technique for solving Partial Differential Equations in variational form. It minimizes the dual norm of the residual, which naturally yields a saddle-point (min–max) problem over the so-called trial and test spaces. In the context of neural networks, we can address this min–max approach by employing one network to seek the trial minimum, while another network seeks the test maximizers. However, the resulting method is numerically unstable as we approach the trial solution. To overcome this, we reformulate the residual minimization as an equivalent minimization of a Ritz functional fed by optimal test functions computed from another Ritz functional minimization. We call the resulting scheme the Deep Double Ritz Method (DRM), which combines two neural networks for approximating trial functions and optimal test functions along a nested double Ritz minimization strategy. Numerical results on different diffusion and convection problems support the robustness of our method, up to the approximation properties of the networks and the training capacity of the optimizers

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning

Background: Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. Methods: We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. Results: The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). Conclusions: This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice

Editorial: Infectious Diseases Affecting Reproduction and the Neonatal Period in Cattle

Editorial on the Research TopicEven with the global scenario after the SARS CoV-2 pandemic, human population keeps growing, and therefore food safety and quality demand is increasing. So, it is required to improve the efficiency in most livestock production systems including the cattle industry. Because the efficiency of cattle industry is far away from optimum (1?3), the intensification of the production systems emerges as a challenge. Currently, over 1 billion heads are raised in our planet. Countries like Argentina, Australia, Brazil, China, and United States extensively raise their cattle on pastures, which represents over 50% of the productive cattle stock worldwide. The main objective of cow-calf systems is to produce the largest quantity of calves per bred cow. Nevertheless, top beef producing countries in some cases achieve only above 50% of weaning rate. Common causes of this low weaning rate usually occur during the breeding season. In this period, cows are usually under suboptimal body condition, exposed to environmental stress and/or infectious diseases, and therefore low pregnancy rates are recorded. The diagnosis of the cause of this early reproductive failure is challenging, unless they are related with infectious diseases. Many research articles reports abortion and perinatal mortality varying from 5 to 12% and 2 to 5%, respectively (4?8) representing a huge loss of calves. During the period from pregnancy diagnosis to calf delivery, the efficiency of detecting the aetiological agents or diseases is still below 50% even though several studies and experimental models on this topic have been developed.Fil: Moore, Dadin Prando. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible. - Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Buenos Aires Sur. Estacion Experimental Agropecuaria Balcarce. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible.; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; ArgentinaFil: Cantón, Germán J.. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Departamento de Producción Animal; ArgentinaFil: Louge Uriarte, Enrique Leopoldo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Departamento de Producción Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

The sound of waves in the Mutriku wave energy plant

Peer Reviewe

Phylogenetic analyses of typical bovine rotavirus genotypes G6, G10, P[5] and P[11] circulating in Argentinean beef and dairy herds

Group A rotavirus (RVA) is one of the main causes of neonatal calf diarrhea worldwide. RVA strains affecting Argentinean cattle mainly possess combinations of the G6, G10, P[5] and P[11] genotypes. To determine RVA diversity among Argentinean cattle, representative bovine RVA strains detected in diarrheic calves were selected from a survey conducted during 1997–2009. The survey covered the main livestock regions of the country from dairy and beef herds. Different phylogenetic approaches were used to investigate the genetic evolution of RVA strains belonging to the prevalent genotypes. The nucleotide phylogenetic tree showed that all genotypes studied could be divided into several lineages. Argentinean bovine RVA strains were distributed across multiple lineages and most of them were distinct from the lineage containing the vaccine strains. Only the aminoacid phylogenetic tree of G6 RVA strains maintained the same lineages as observed at the nucleotide level, whereas a different clustering pattern was observed for the aminoacid phylogenetic trees of G10, P[5] and P[11] suggesting that the strains are more closely related at the aminoacid level than G6 strains. Association between P[5] and G6(IV), prevalent in beef herd, and between P[11] and G6(III) or G10 (VI and V), prevalent in dairy herds, were found. In addition, Argentinean G6(III), G10, P[5] and P[11] bovine RVA strains grouped together with human strains, highlighting their potential for zoonotic transmission. Phylogenetic studies of RVA circulating in animals raised for consumption and in close contact with humans, such as cattle, contribute to a better understanding of the epidemiology of the RVA infection and evolution.Fil: Badaracco, Alejandra. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Garaicoechea, Lorena Laura. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Matthijnssens, J.. University of Leuven. Rega Institute for Medical Research; BélgicaFil: Louge Uriarte, Enrique Leopoldo. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce. Área de Investigación en Producción y Sanidad Animal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Odeón, Anselmo Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce. Área de Investigación en Producción y Sanidad Animal; ArgentinaFil: Bilbao, Gladys Noemí. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Veterinarias; ArgentinaFil: Fernandez, Fernando. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Virología; ArgentinaFil: Parra, G. I.. National Institutes of Health; Estados UnidosFil: Parreño, Gladys Viviana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin