Challenges in Additive Manufacturing of space parts: Powder feedstock cross-contamination and its impact on end products

This work studies the tensile properties of Ti-6Al-4V samples produced by laser powder bed based Additive Manufacturing (AM), for different build orientations. The results showed high scattering of the yield and tensile strength and low fracture elongation. The subsequent fractographic investigation revealed the presence of tungsten particles on the fracture surface. Hence, its detection and impact on tensile properties of AM Ti-6Al-4V were investigated. X-ray Computed Tomography (X-ray CT) scanning indicated that these inclusions were evenly distributed throughout the samples, however the inclusions area was shown to be larger in the load-bearing plane for the vertical specimens. A microstructural study proved that the mostly spherical tungsten particles were embedded in the fully martensitic Ti-6Al-4V AM material. The particle size distribution, the flowability and the morphology of the powder feedstock were investigated and appeared to be in line with observations from other studies. X-ray CT scanning of the powder however made the high density particles visible, where various techniques, commonly used in the certification of powder feedstock, failed to detect the contaminant. As the detection of cross contamination in the powder feedstock proves to be challenging, the use of only one type of powder per AM equipment is recommended for critical applications such as Space parts. 2017 by the authors

THE MATERNAL-FETAL MEDICINE: AN UPDATE

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Dupilumab in the treatment of severe uncontrolled chronic rhinosinusitis with nasal polyps (CRSwNP): A multicentric observational Phase IV real-life study (DUPIREAL)

Background Chronic rhinosinusitis with nasal polyps (CRSwNP) is associated with significant morbidity and reduced health-related quality of life. Findings from clinical trials have demonstrated the effectiveness of dupilumab in CRSwNP, although real-world evidence is still limited. Methods This Phase IV real-life, observational, multicenter study assessed the effectiveness and safety of dupilumab in patients with severe uncontrolled CRSwNP (n = 648) over the first year of treatment. We collected data at baseline and after 1, 3, 6, 9, and 12 months of follow-up. We focused on nasal polyps score (NPS), symptoms, and olfactory function. We stratified outcomes by comorbidities, previous surgery, and adherence to intranasal corticosteroids, and examined the success rates based on current guidelines, as well as potential predictors of response at each timepoint. Results We observed a significant decrease in NPS from a median value of 6 (IQR 5–6) at baseline to 1.0 (IQR 0.0–2.0) at 12 months (p < .001), and a significant decrease in Sino-Nasal Outcomes Test-22 (SNOT-22) from a median score of 58 (IQR 49–70) at baseline to 11 (IQR 6–21; p < .001) at 12 months. Sniffin' Sticks scores showed a significant increase over 12 months (p < .001) compared to baseline. The results were unaffected by concomitant diseases, number of previous surgeries, and adherence to topical steroids, except for minor differences in rapidity of action. An excellent-moderate response was observed in 96.9% of patients at 12 months based on EPOS 2020 criteria. Conclusions Our findings from this large-scale real-life study support the effectiveness of dupilumab as an add-on therapy in patients with severe uncontrolled CRSwNP in reducing polyp size and improving the quality of life, severity of symptoms, nasal congestion, and smell

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Fatigue Life Predictions of Friction Stir Welded Joints by Using Fracture Mechanics Methods

The deterioration of the airframe due to fatigue loading and corrosion attack should be monitored by scheduled periodic inspections to assure the appropriate detection of the damaged area. In the present investigation an exploratory test program has been carried out to improve the general understanding of the fatigue behaviour of undamaged and corrosion damaged joints. Also the sequence effects in FSW joints are studied. The aim is to offer a basis both for a better experimental documentation as well as for an evaluation of existing crack propagation prediction models. Moreover specifically existent fracture mechanics principles are applied to friction stir welded structures. The objective is to elaborate an easy, practical and reliable engineering approach to perform life predictions of friction stir welded structures under in-service loading and in the presence of corrosion attack