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To move towards a condition-based maintenance practice for aircraft structures, design of reliable health management methodologies is required. Development of diagnostic methodologies is commonly realised on simplified sample structures with assumptions that methodologies can be adapted for application to realistic aircraft structures under in-service conditions. Yet such actual applications are not conducted. In this work, we study the development of diagnostic methodologies to training structures and their application to dissimilar testing structures. A heterogeneous population is considered, consisting of single-stiffener composite panels for methodology development and training and a multi-stiffener composite panel for application and testing. Characteristics as its composite material, lay-up, and temperature condition are constant while topologies and applied loads differ between the dissimilar structures. Damage in the structural panels is monitored on multiple diagnostic levels using a variety of structural health monitoring (SHM) techniques, including acoustic emission and distributed strain sensing. Specifically, we develop diagnostic methods for localising and monitoring disbond growth after impact using strain data collected during fatigue testing of multiple single-stiffener panels and apply these for disbond monitoring in an upscaled version of a multi-stiffener panel. In this manner, this study aids in the maturement and application of SHM methodologies to realistic aircraft structures.

Advances in diagnostics, therapeutics, vaccines, transfusion, and organ transplantation build on a fundamental understanding of glycan-protein interactions. To aid this, we developed GlyNet, a model that accurately predicts interactions (relative binding strengths) between mammalian glycans and 352 glycan-binding proteins, many at multiple concentrations. For each glycan input, our model produces 1257 outputs, each representing the relative interaction strength between the input glycan and a particular protein sample. GlyNet learns these continuous values using relative fluorescence units (RFUs) measured on 599 glycans in the Consortium for Functional Glycomics glycan arrays and extrapolates these to RFUs from additional, untested glycans. GlyNet’s output of continuous values provides more detailed results than classification models. Such continuous outputs are easily converted by a following classifier, and in this form GlyNet outperforms reported classifiers. GlyNet is the first multi-output regression model for protein-glycan interactions and will serve as an important benchmark, facilitating development of quantitative computational glycobiology.

To determine the antitumor efficacy and safety profile of temozolomide in patients with malignant astrocytoma at first relapse.This open-label, multicenter, phase II trial enrolled 162 patients (intent-to-treat [ITT] population). After central histologic review, 111 patients were confirmed to have had an anaplastic astrocytoma (AA) or anaplastic mixed oligoastrocytoma. Chemotherapy-naive patients were treated with temozolomide 200 mg/m(2)/d. Patients previously treated with chemotherapy received temozolomide 150 mg/m(2)/d; the dose could be increased to 200 mg/m(2)/d in the absence of grade 3/4 toxicity. Therapy was administered orally on the first 5 days of a 28-day cycle.Progression-free survival (PFS) at 6 months, the primary protocol end point, was 46% (95% confidence interval, 38% to 54%). The median PFS was 5.4 months, and PFS at 12 months was 24%. The median overall survival was 13.6 months, and the 6- and 12-month survival rates were 75% and 56%, respectively. The objective response rate determined by independent central review of gadolinium-enhanced magnetic resonance imaging scans of the ITT population was 35% (8% complete response [CR], 27% partial response [PR]), with an additional 26% of patients with stable disease (SD). The median PFS for patients with SD was 4.4 months, with 33% progression-free at 6 months. Maintenance of progression-free status and objectively assessed response (CR/PR/SD) were both associated with health-related quality-of-life (HQL) benefits. Adverse events were mild to moderate, with hematologic side effects occurring in less than 10% of patients.Temozolomide demonstrated good single-agent activity, an acceptable safety profile, and documented HQL benefits in patients with recurrent AA.

The successful implementation of Structural Health Monitoring (SHM) systems is confined to the capability of evaluating their performance, reliability, and durability. Although there are many SHM techniques capable of detecting, locating and quantifying damage in several types of structures, their certification process is still limited. Despite the effort of academia and industry in defining methodologies for the performance assessment of such systems in recent years, many challenges remain to be solved. Methodologies used in Non-Destructive Evaluation (NDE) have been taken as a starting point to develop the required metrics for SHM, such as Probability of Detection (POD) curves. However, the transposition of such methodologies to SHM is anything but straightforward because additional factors should be considered. The time dependency of the data, the larger amount of variability sources and the complexity of the structures to be monitored exacerbate/aggravate the existing challenges, suggesting that much work has still to be done in SHM. The article focuses on the current challenges and barriers preventing the development of proper reliability metrics for SHM, analyzing the main differences with respect to POD methodologies for NDE. It was found that the development of POD curves for SHM systems requires a higher level of statistical expertise and their use in the literature is still limited to few studies. Finally, the discussion extends beyond POD curves towards new metrics such as Probability of Localization (POL) and Probability of Sizing (POS) curves, reflecting the diagnosis paradigm of SHM.