Foundation for the Research Development and Application of Composite Materials

Abstract Aims Myocardial infarction with non-obstructive coronary arteries (MINOCA) is characterized by myocardial infarction features, troponin elevation, and coronary arteries with <50% stenosis. Over recent years, the concept of MINOCA has evolved into an umbrella term encompassing various mechanisms, rather than a single definitive diagnosis. It involves both coronary and non-coronary causes. This study aims to explore biomarker differences among these etiologies, proposing that inflammation-related biomarkers could provide a more precise approach to differentiating between them, thereby improving diagnosis and reducing mis/underdiagnosis. Currently, these biomarkers have not been specifically studied for each MINOCA etiology, but rather in a broader context. Methods This observational study included 72 MINOCA patients from a University Hospital between 2021-2023. According to ESC guidelines, MINOCA subtypes were classified as Takotsubo syndrome, myocarditis, ischemic MINOCA, type II-MINOCA, or undefined-MINOCA. IL-6, TNF-α, hs-CRP, CK and hs-troponin T levels were measured at admission, discharge, and two months later. Biomarker associations with MINOCA subtypes were evaluated using unadjusted and age- and sex-adjusted logistic regression models, with significance set at p<0.10 due sample size limitations. Results Among the 72 patients included, 17 were classified as ischemic MINOCA, 13 as type II-MINOCA, 10 as myocarditis, 8 as Takotsubo, and 24 as unknown origin. The mean age was 63 years, with 52% of patients being male. Comparing the characteristics of the five subgroups, type II-MINOCA was more common in older patients, while myocarditis was more prevalent in younger patients. The percentage of males was similar across all subtypes. Myocarditis patients had the highest peak levels of hs-Troponin T and CK at admission compared to other MINOCA groups. In Takotsubo syndrome, TNFα levels were the highest at admission. Regression models showed significant associations (see Table 1): At admission, higher IL-6, TNF-α, and hs-TnT levels were associated with Takotsubo syndrome (OR 1.7, OR 3.5, and OR 2.07, respectively). Myocarditis patients had elevated hs-Troponin T and CK levels (OR 2.04 and OR 3.57, respectively). The unknown group showed lower IL-6 and hs-Troponin T levels (OR 0.65 and OR 0.62, respectively), while ischemic MINOCA had lower TNF-α levels (OR 0.37). Type II-MINOCA was associated with higher hs-CRP and TNF-α levels at discharge (OR 1.57 and OR 6.13, respectively). No biomarker differences were observed during follow-up, except for type II-MINOCA, which continued to show elevated TNF-α levels (OR 3.06). See Figure 1. Conclusion This study identifies distinct biomarker profiles for different MINOCA subtypes, which may serve as key targets for future research, and provides important insights for subtype differentiation and diagnostic support.Tab1.Biomarkers' associations-subtypes Fig1.Biomarker levels in MINOCA subtypes

A synthetic partial discharge (PD) calibrator has been developed to qualify PD analyzers used for insulation diagnosis of HVAC and HVDC grids including cable systems, AIS, GIS, GIL, power transformers, and HVDC converters. PD analyzers that use high-frequency current transformers (HFCT) can be qualified by means of the metrological and diagnosis tests arranged in this calibrator. This synthetic PD calibrator can reproduce PD pulse trains of the same sequence as actual representative defects (cavity, surface, floating potential, corona, SF6 protrusion, SF6 jumping particles, bubbles in oil, etc.) acquired in HV equipment in service or by means of measurements made in HV laboratory test cells. The diagnostic capabilities and PD measurement errors of the PD analyzers using HFCT sensors can be determined. A new time parameter, "PD Time", associated with any arbitrary PD current pulse i(t) is introduced for calibration purposes. It is defined as the equivalent width of a rectangular PD pulse with the same charge value and amplitude as the actual PD current pulse. The synthetic PD calibrator consists of a pulse generator that operates on a current loop matched to 50 Ω impedance to avoid unwanted reflections. The injected current is measured by a reference measurement system built into the PD calibrator that uses two HFCT sensors to ensure that the current signal is the same at the input and output of the calibration cage where the HFCT of the PD analyzer is being calibrated. Signal reconstruction of the HFCT output signal to achieve the input signal is achieved by applying state variable theory using the transfer impedance of the HFCT sensor in the frequency domain.

A amora-preta (Rubus sp.) possui um elevado potencial antioxidante, principalmente pelos teores representativos de compostos fenólicos totais, flavonoides e o alto teor de antocianinas. O objetivo deste trabalho foi avaliar as características físico/químicas e atividade antioxidante da amora-preta in natura, da polpa congelada e pré-liofilizada para congelamento. Para isso os frutos foram higienizados e separados em amostras in natura, congelados por 90 dias com pré-secagem por liofilização, antes do congelamento, por 90 dias. Todas as amostras foram avaliadas quanto à sua composição físico-químicas - umidade, proteína bruta, gorduras brutas, fibra, carboidratos, minerais, sólidos solúveis totais (ºBrix), pH e acidez titulável. As polpas foram preparadas após o tempo de congelamento numa proporção 4:1 (fruta:água destilada), e posteriormente as polpas foram secas, trituradas e foi mensurada a concentração de compostos fenólicos e flavonoides. Foi observada diferença significativa para sólidos solúveis, teor de proteína bruta, carboidratos totais e flavonoides para o tratamento liofilizado comparado ao congelado, sendo que a polpa com amoras liofilizadas não diferiu dos teores da fruta in natura. Portanto, o processo de liofilização das amoras, previamente ao congelamento, mostrou-se mais apropriado, pois conservou melhor os nutrientes, podendo ser utilizado como método alternativo para evitar a perda na composição da amora pós-colheita, já que o fruto é encontrado em meados de novembro e dezembro.

<p>Advanced Rear End Manufacturing es un proyecto europeo que se engloba dentro del programa de investigación del CleanSky2. Este paquete de trabajo se centra en diseñar, fabricar y testear nuevas tecnologías para la fabricación de estructuras aeronáuticas, integrando, en la parte trasera de una aeronave, diferentes elementales.<br> El trabajo que aquí se presenta, muestra el proceso de fabricación desarrollado para obtener un demostrador a escala real de una sección trasera de fuselaje en material compuesto de fibra de carbono preimpregnada, integrándose rigidizadores, cuadernas de forma y revestimiento en un solo paso.</p> <p> </p> <p><em>This project has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No </em>945583<em>. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Clean Sky 2 JU members other than the Union.</em></p> <p><em>The results, opinions, conclusions, etc. presented in this work are those of the author(s) only and do not necessarily represent the position of the JU; the JU is not responsible for any use made of the information contained herein.</em></p>

This study presents the results of the mechanical tests carried out at the coupon and element levels for the characterization of the properties of a thermoplastic composite that will form a fuselage panel. In addition to standardized tests, tests are carried out to evaluate the behaviour of critical areas of the panel, such as the radius of the frames, the stringers, and the joint between the frame and the skin around the stringers (mouse-hole). In these latest tests, experimental procedures are developed for their execution, including the design of the necessary tools to reproduce the representative boundary conditions. As a result of this research, the allowables have been obtained for the design of the curved thermoplastic fuselage panel.<br> This work is developed as part of the European project DELTA, within the framework of the Clean Sky 2 JU program. The objective of this project is to develop and execute innovative experimental test procedures that allow the validation of thermoplastic composite aircraft fuselage panels, in order to apply these solutions in medium and long-range aircraft (LPA). The ultimate goal of this project will be achieved through the execution of a curved thermoplastic fuselage panel test under representative load conditions.

Why have European large parties lost electoral ground in recent decades? Whereas most explanations draw on theories of dealignment, this article advances a novel, institutional, argument by focusing on the introduction of direct elections to the European Parliament (EP) in 1979. Archetypes of second-order elections, EP elections are characterized by lower vote shares for (a) large and (b) incumbent parties. Bridging the second-order elections theory with theories of political socialization, we posit that voting patterns in EP elections spill over onto national elections, especially among voters not yet socialized into patterns of habitual voting. In so doing, they increase the national vote shares of small parties. This proposition is examined using an instrumental variables approach. We also derive a set of testable propositions to shed light on the underlying mechanisms of this pattern. Our findings show that EP elections decrease support for big parties at the national arena by inculcating voting habits.

Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.