Search Results (4)

Society awareness and environmental goals are forcing the aerospace industry to develop new sustainable system architectures. The components in the new system have to meet new functional requirements using alternative technologies and design solutions while ensuring that the physical performance of the component is maintained. However, design space exploration of both domains is challenging due to the intrinsic differences and nature of each: functional domain exploration deals with alternative means to solve functions, while physical exploration deals with parametric values, such as geometric dimensions and material types. Here, we present a method that enables concurrent exploration of the functional and physical design space. The method is based on a review of existing design space exploration methodologies. It has been developed in collaboration with industry and validated within a use case. We expect that this method will be useful for designers in conceptual phases where there are several functions containing multiple design alternatives and incompatibilities among them. The results of the method will allow designers to narrow down the design space to a few architectural candidates, including a baseline of physical dimensioning for each candidate. Full article

The ability to detect underwater objects accurately is important in marine environmental engineering. Although many kinds of underwater object detection algorithms with relatively high accuracy have been proposed, they involve a large number of parameters and floating point operations (FLOPs), and often fail to yield satisfactory results in complex underwater environments. In light of the demand for an algorithm with the capability to extract high-quality features in complex underwater environments, we proposed a one-stage object detection algorithm called the enhanced feature-based underwater object detection algorithm (EF-UODA), which was based on the architecture of Next-ViT, the loss function of YOLOv8, and Ultralytics. First, we developed a highly efficient module for convolutions, called efficient multi-scale pointwise convolution (EMPC). Second, we proposed a feature pyramid architecture called the multipath fast fusion-feature pyramid network (M2F-FPN) based on different modes of feature fusion. Finally, we integrated the Next-ViT and the minimum point distance intersection over union loss functions in our proposed algorithm. Specifically, on the URPC2020 dataset, EF-UODA surpasses the state-of-the-art (SOTA) convolution-based object detection algorithm YOLOv8X by 2.9% mean average precision (mAP), and surpasses the SOTA ViT-based object detection algorithm real-time detection transformer (RT-DETR) by 2.1%. Meanwhile, it achieves the lowest FLOPs and parameters. The results of extensive experiments showed that EF-UODA had excellent feature extraction capability, and was adequately balanced in terms of the number of FLOPs and parameters. Full article

Patients with acute myocardial infarction are at high risk for developing heart failure due to scar development. Although regenerative approaches are evolving, consistent clinical benefits have not yet been reported. Treatment with dutogliptin, a second-generation DPP-4 inhibitor, in co-administration with filgrastim (G-CSF) has been shown to enhance endogenous repair mechanisms in experimental models. The REC-DUT-002 trial was a phase 2, multicenter, double-blind placebo-controlled trial which explored the safety, tolerability, and efficacy of dutogliptin and filgrastim in patients with ST-elevation Myocardial Infarction (STEMI). Patients (n = 47, 56.1 ± 10.7 years, 29% female) with STEMI, reduced left ventricular ejection fraction (EF ≤ 45%) and successful revascularization following primary PCI were randomized to receive either study treatment or matching placebo. Cardiac magnetic resonance imaging (cMRI) was performed within 72 h post-PCI and repeated after 3 months. The study was closed out early due to the SARS-CoV-2 pandemic. There was no statistically significant difference between the groups with respect to serious adverse events (SAE). Predefined mean changes within cMRI-derived functional and structural parameters from baseline to 90 days did not differ between placebo and treatment (left ventricular end-diastolic volume: +13.7 mL vs. +15.7 mL; LV-EF: +5.7% vs. +5.9%). Improvement in cardiac tissue health over time was noted in both groups: full-width at half-maximum late gadolinium enhancement (FWHM LGE) mass (placebo: −12.7 g, treatment: −19.9 g; p = 0.23). Concomitant treatment was well tolerated, and no safety issues were detected. Based on the results, the FDA and EMA have already approved an adequately powered large outcome trial. Full article

Physical activity (PA) can improve children’s executive functioning (EF), which might be caused by increased levels of brain-derived neurotrophic factor (BDNF). This study investigated whether acute and/or chronic PA leads to increased BDNF levels and enhanced EF in children. Methods: In total, 47 children (mean age 9.69 ± 0.60; 46.8% boys) participated. Children performed a maximal exercise test to measure acute PA. Before and after, BDNF was collected and EF was measured. Chronic PA was proxy-reported. Repeated Measures ANOVAs were performed to study the effect of acute PA on BDNF and EF. Mediation analyses were performed to investigate the mediation effect of BDNF on the association between chronic PA and BDNF. Results: A borderline significant effect of acute PA on BDNF was found (F = 3.32, p = 0.075) with an increase in BDNF (+29.58 pg/mL) after acute PA. A significant effect was found for performance on inhibition tasks (Flanker (accuracy +5.67%, p = 0.034) and Go/No-Go (+0.15%, p = 0.022)). No effect of acute PA was found on the EF outcomes. No significant correlation between chronic PA and EFs nor BDNF was found. Conclusions: Acute PA might increase BDNF and improve some EFs (i.e., inhibition) in children. Chronic PA was not associated with EF nor BDNF. Trial Registration Number: NCT02503579. Full article