Quasi-static and dynamic crush behaviour of 3D printed thin-walled profiles reinforced with continuous carbon and glass fibres

The present paper investigates the suitability of cFF printed material and technologies for crashworthiness applications. To this end, the quasi-static and dynamic crush behaviour of 3D printed thin-walled hollow profiles reinforced with continuous carbon (cCF/PA) and glass fibres (cGF/PA), in axial and radial loading were analysed. Despite the specific microstrutural differences generated during 3D printing, the nature of the constituents (fibre and matrix) controlled the differences between the crush behaviour of both profiles. Although a stable collapse mode was observed for each profile under quasi-static and impact loading, a ductile response was only reported for the cGF/PA profiles. Under radial quasi-static conditions the cCF/PA profiles showed SEA values greater than the cGF/PAs. Nevertheless, the radial impact performance of the cGF/PA profile was greater as the material presented a strain-rate dependency. The radial SEA values obtained for steered glass fibres were lower than those values obtained for axial loading. However these SEA values are promising, in that they were at least 2–3 times higher than any values found in the literature. The results therefore indicate that concentrically printed cGF/PA reinforcements could be exploited for impact loaded hollow profile applications

The effect of cross-section geometry on crushing behaviour of 3D printed continuous carbon fibre reinforced polyamide profiles

The present study has analysed the effect of cross-section geometry and the printing pattern of continuous carbon reinforced polyamide on the axial and radial crushing behaviour. Each geometry and printing pattern generated singular defects, but the most relevant microstructural aspect resulted the fibre orientation. The geometry with the re-entrant shape and Concentrical printing pattern was identified as the best profile for axial and radial crushing loadings, with a SEA of 23.9 and 5.9 kJ/kg. In spite of axial SEA values are far from those values obtained for composite profile manufactured by conventional process, radial SEA value obtained with steered fibres was at least 2–3 times higher than the best value found in the literature. Thus, concentrically 3D printed with steered fibres layers, could be exploited for radially loaded hollow profiles applications. Despite studied cross-section are not good enough under axial loads, 3D printing allows complex geometries and exploring more sophisticated cross-sections could lead to higher axial SEA values

HPC Platform for Railway Safety-Critical Functionalities Based on Artificial Intelligence

The automation of railroad operations is a rapidly growing industry. In 2023, a new European standard for the automated Grade of Automation (GoA) 2 over European Train Control System (ETCS) driving is anticipated. Meanwhile, railway stakeholders are already planning their research initiatives for driverless and unattended autonomous driving systems. As a result, the industry is particularly active in research regarding perception technologies based on Computer Vision (CV) and Artificial Intelligence (AI), with outstanding results at the application level. However, executing high-performance and safety-critical applications on embedded systems and in real-time is a challenge. There are not many commercially available solutions, since High-Performance Computing (HPC) platforms are typically seen as being beyond the business of safety-critical systems. This work proposes a novel safety-critical and high-performance computing platform for CV- and AI-enhanced technology execution used for automatic accurate stopping and safe passenger transfer railway functionalities. The resulting computing platform is compatible with the majority of widely-used AI inference methodologies, AI model architectures, and AI model formats thanks to its design, which enables process separation, redundant execution, and HW acceleration in a transparent manner. The proposed technology increases the portability of railway applications into embedded systems, isolates crucial operations, and effectively and securely maintains system resources.The novel approach presented in this work is being developed as a specific railway use case for autonomous train operation into SELENE European research project. This project has received funding from RIA—Research and Innovation action under grant agreement No. 871467

A flexible count data model to fit the wide diversity of expression profiles arising from extensively replicated RNA-seq experiments

Background: High-throughput RNA sequencing (RNA-seq) offers unprecedented power to capture the real dynamics of gene expression. Experimental designs with extensive biological replication present a unique opportunity to exploit this feature and distinguish expression profiles with higher resolution. RNA-seq data analysis methods so far have been mostly applied to data sets with few replicates and their default settings try to provide the best performance under this constraint. These methods are based on two well-known count data distributions: the Poisson and the negative binomial. The way to properly calibrate them with large RNA-seq data sets is not trivial for the non-expert bioinformatics user. Results: Here we show that expression profiles produced by extensively-replicated RNA-seq experiments lead to a rich diversity of count data distributions beyond the Poisson and the negative binomial, such as Poisson-Inverse Gaussian or Pólya-Aeppli, which can be captured by a more general family of count data distributions called the Poisson-Tweedie. The flexibility of the Poisson-Tweedie family enables a direct fitting of emerging features of large expression profiles, such as heavy-tails or zero-inflation, without the need to alter a single configuration parameter. We provide a software package for R called tweeDEseq implementing a new test for differential expression based on the Poisson-Tweedie family. Using simulations on synthetic and real RNA-seq data we show that tweeDEseq yields P-values that are equally or more accurate than competing methods under different configuration parameters. By surveying the tiny fraction of sex-specific gene expression changes in human lymphoblastoid cell lines, we also show that tweeDEseq accurately detects differentially expressed genes in a real large RNA-seq data set with improved performance and reproducibility over the previously compared methodologies. Finally, we compared the results with those obtained from microarrays in order to check for reproducibility. Conclusions: RNA-seq data with many replicates leads to a handful of count data distributions which can be accurately estimated with the statistical model illustrated in this paper. This method provides a better fit to the underlying biological variability; this may be critical when comparing groups of RNA-seq samples with markedly different count data distributions. The tweeDEseq package forms part of the Bioconductor project and it is available for download at http://www.bioconductor.or

Automation of Simulation Based Design Validation and Reporting of a Valve Family

Valves are mechanical devices for controlling fluid-flow in pipes of different diameter and service pressures used in several industry sectors. Most demanding industry sectors add custom design requirements and require product validation reports many times even before placing valve purchase orders of varying quantities. Therefore, customer and valve developer requirements must be made compatible, design reliably completed and a design validation report created, all as soon as possible. In order to respond to these market constraints, complete valve design process from product planning to product design and validation delivery must be optimized. This paper reports a 96% time reduction in Simulation Based Design validation and reporting tasks obtained by applying Design Automation in a company that develops valves for this market. Additionally, the architecture and most remarkable features of the Simulation Based Design validation and reporting automation are described

Analysis of One-Way and Two-Way FSI Approaches to Characterise the Flow Regime and the Mechanical Behaviour during Closing Manoeuvring Operation of a Butterfly Valve

Butterfly valves are widely used industrial piping components as on-off and flow controlling devices. The main challenge in the design process of this type of valves is the correct dimensioning to ensure proper mechanical performance as well as to minimise flow losses that affect the efficiency of the system. Butterfly valves are typically dimensioned in a closed position based on mechanical approaches considering uniform hydrostatic pressure, whereas the flow losses are analysed by means of CFD simulations. The main limitation of these approaches is that they do not consider either the influence of the dynamics of the manoeuvring stage or coupled phenomena. Recent works have included the influence of the flow on the mechanical behaviour for different opening angles by means of one-way FSI approach. However, these works consider steady-state flow for the selected angles, not capturing the effect of the transient flow evolution during the manoeuvring stage. Two-way FSI modelling approach could allow overcoming such limitations providing more accurate results. Nevertheless, the use of this technique is limited due to the increase in the computational cost. In the present work, the applicability of FSI one-way and two-way approaches is evaluated for the analysis of butterfly valves, showing that not considering fluid-structure coupling involves not capturing the most critical situation for the valve disc

Determining tool/chip temperatures from thermography measurements in metal cutting

Temperature measurement in metal cutting is of central importance as tool wear and surface integrity have been demonstrated to be temperature dependent. In this context, infrared thermography is presented as a reliable technique to determine tool temperatures and thermal fields at near real-time. However, a constraint of this technique is that temperatures are measured on the tool side faces normal to the cutting edge but offset from the tool/chip contact. In the present research, tool/chip contact temperatures were calculated from the tool side based on analytical theories of heating and the principles of heat generation in cutting processes. The required inputs were commonly measurable variables (cutting and feed forces, chip thickness and tool/chip contact length). The proposed approach was combined with a new calibration method in which a calibration curve that directly relates real and radiated temperatures is obtained, instead of measuring the emissivity of the radiating surface. As a case study, the research was conducted on a set of four ferrite-pearlite steels (16MnCr5, 27MnCr, C45 and C60). The results demonstrated the effectiveness of the method to establish the real influence of the cutting conditions (cutting speed and feed) and to distinguish the effect that different work material microstructures have in tool/chip temperature. Furthermore, the results showed a high degree of accuracy and less than 12% deviation from the trends when compared with 2D cutting simulations

A Coupled Eulerian Lagrangian Model to Predict Fundamental Process Variables and Wear Rate on Ferrite-pearlite Steels

A coupled Eulerian-Lagrangian Finite Element model of the orthogonal cutting process was developed to predict the influence that ferritepearlite steel variants have on fundamental process variables and tool wear. As a case study, this paper is focused on two different ferritepearlite inclusion free alloys, where mainly the influence of ferrite-pearlite ratio was tested. Flow stress behavior based on dynamic compression tests and thermal properties function of temperature were characterized for model input parameters. The numerical model is compared with orthogonal cutting tests where the cutting and feed forces, tool temperature, chip morphology and tool wear related variables were measured. Globally, predicted tendencies match with experiments in forces and temperatures. Widest differences on predictions were found for chip thickness and tool-chip contact length. Predicted wear rates are in accordance to experimentally measured values

Protective Effect of the Hydrophilic Extract of Polypodium leucotomos, Fernblock®, against the Synergistic Action of UVA Radiation and Benzo[a]pyrene Pollutant

Oxidative stress is a harmful effect induced on the skin by polycyclic aromatic hydrocarbons Citation: Gallego-Rentero, M.; Nicolás-Morala, J.; Alonso-Juarranz, M.; Carrasco, E.; Portillo-Esnaola, M.; Rodríguez-Luna, A.; González, S. Protective Effect of the Hydrophilic Extract of Polypodium leucotomos, Fernblock®, against the Synergistic Action of UVA Radiation and Benzo[a]pyrene Pollutant. Antioxidants 2022, 11, 2185. https://doi.org/10.3390/ antiox11112185 Academic Editor: Stanley Omaye Received: 8 October 2022 Accepted: 28 October 2022 Published: 4 November 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). (PAH), including benzo[a]pyrene (BaP) air pollutants. This effect is amplified by the additive damaging effect of the sun, especially through the UVA light component. Besides being one of the main compounds that make up air pollution, BaP can also be found in tar, tobacco smoke, and various foods. In addition to its direct carcinogenic potential, BaP can act as a photosensitizer absorbing sunlight in the UVA range and thus generating ROS and 8-hydroxy-2-deoxyguanosine (8-OHdG). Fernblock® (FB) is an aqueous extract from the leaves of Polypodium leucotomos that has been proven to exert photoprotective and antioxidant effects on skin cells. In this study, we evaluate the potential of FB to prevent the damage induced by a combination of BaP and UVA light on human keratinocyte and mouse melanocyte cell lines (HaCaT and B16-F10, respectively). In particular, we have analyzed the capacity of FB to counteract the alterations caused on cellular morphology, viability, oxidative stress and melanogenic signaling pathway activation. Our data indicate that FB prevented cell damage and reduced oxidative stress and melanogenic signaling pathway activation caused by a combination of BaP and UVAlightirradiation. Altogether, our findings support the fact that FB is able to prevent skin damage caused by the exposure to a combination of UVA and the air pollutant Ba

Metformin overcomes metabolic reprogramming-induced resistance of skin squamous cell carcinoma to photodynamic therapy

Cancer metabolic reprogramming promotes resistance to therapies. In this study, we addressed the role of the Warburg effect in the resistance to photodynamic therapy (PDT) in skin squamous cell carcinoma (sSCC). Furthermore, we assessed the effect of metformin treatment, an antidiabetic type II drug that modulates metabolism, as adjuvant to PDT. Methods: For that, we have used two human SCC cell lines: SCC13 and A431, called parental (P) and from these cell lines we have generated the corresponding PDT resistant cells (10GT). Results: Here, we show that 10GT cells induced metabolic reprogramming to an enhanced aerobic glycolysis and reduced activity of oxidative phosphorylation, which could influence the response to PDT. This result was also confirmed in P and 10GT SCC13 tumors developed in mice. The treatment with metformin caused a reduction in aerobic glycolysis and an increase in oxidative phosphorylation in 10GT sSCC cells. Finally, the combination of metformin with PDT improved the cytotoxic effects on P and 10GT cells. The combined treatment induced an increase in the protoporphyrin IX production, in the reactive oxygen species generation and in the AMPK expression and produced the inhibition of AKT/mTOR pathway. The greater efficacy of combined treatments was also seen in vivo, in xenografts of P and 10GT SCC13 cells. Conclusions: Altogether, our results reveal that PDT resistance implies, at least partially, a metabolic reprogramming towards aerobic glycolysis that is prevented by metformin treatment. Therefore, metformin may constitute an excellent adjuvant for PDT in sSCCThis research was supported by Spanish grants from Instituto de Salud Carlos III MINECO and Feder Funds (FIS PI15/00974; PI18/00858 and PI18/00708) and Ministerio de Ciencia, Innovación y Universidades (PID2019-108674RB-100