Loftid Aeroshell Engineering Development Unit Structural Testing

NASAs Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology was selected for a Technology Demonstration Mission under the Space Technology Mission Directorate in 2017. HIAD is an enabling technology that can facilitate atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to avoid the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher pay-load mass and/or volume, higher landing altitude at Mars). The Low Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) is currently scheduled for late-2021. LOFTID will be launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. The flight test features a 6m diameter, 70-deg sphere-cone aeroshell and will provide invaluable high-energy orbital re-entry flight data. This data will be essential in supporting the HIAD team to mature the technology to diameters of 10m and greater. Aeroshells of this scale are applicable to potential near-term commercial applications and future NASA missions. Currently the LOFTID project has completed fabrication of the engineering design unit (EDU) inflatable structure (IS) and the flexible thermal protection system (F-TPS). These two components along with the rigid nose and center body comprise the HIAD aeroshell system. This EDU aeroshell is the precursor to the LOFTID aeroshell that will be used for flight. The EDU was built to verify the design given the subtle differences between the LOFTID aeroshell and past aeroshell designs that have been fabricated under the NASA HIAD project. To characterize the structural performance of the LOFTID aeroshell design, three structural tests will be performed. The first test to be conducted is static load testing, which will induce a uniform load across the forward surface of the aeroshell to simulate the expected pressure forces during atmospheric entry. The IS integrated with the rigid center body will first be tested alone to provide data for analytical model correlation, and then the F-TPS will be integrated for a second series of static load testing of the full aeroshell system. Instrumentation will be employed during the test series to measure component loads during testing, and a laser scanner will be used to generate a 3D map of the aeroshell surface to verify that the shape of the structure is acceptable at the simulated flight loads. After static load testing, pack and deployment testing will be conducted multiple times on the integrated system to demonstrate the aeroshells ability to fit within the required packed volume for the LOFTID mission without experiencing significant damage. Finally, the aeroshell will undergo modal testing to characterize its structural response. This presentation will discuss the setup and execution of each of the three tests that the EDU aeroshell will undergo. In addition, initial results of the testing will be presented outlining key findings as LOFTID moves for-ward with fabrication of the flight aeroshell

Contributors to the June Issue/Notes

Notes by Henry S. Romano, William C. Malone, Joseph F. Rudd, Leonard D. Bodkin, James D. Sullivan, Robert J. Callahan, Jr., William Meehan, Alphonse Spahn, Robert E. Sullivan, John F. Power, Francis J. Paulson, John Merryman, J. Barrett Guthrie, Robert T. Fanning, Robert T. Stewart, and R. L. Miller

Contributors to the June Issue/Notes

Notes by Henry S. Romano, William C. Malone, Joseph F. Rudd, Leonard D. Bodkin, James D. Sullivan, Robert J. Callahan, Jr., William Meehan, Alphonse Spahn, Robert E. Sullivan, John F. Power, Francis J. Paulson, John Merryman, J. Barrett Guthrie, Robert T. Fanning, Robert T. Stewart, and R. L. Miller

Development and application of a data-driven reaction classification model : comparison of an electronic lab notebook and the medicinal chemistry literature

Reaction classification has often been considered an important task for many different applications, and has traditionally been accomplished using hand-coded rule-based approaches. However, the availability of large collections of reactions enables data-driven approaches to be developed. We present the development and validation of a 336-class machine learning-based classification model integrated within a Conformal Prediction (CP) framework in order to associate reaction class predictions with confidence estimations. We also propose a data-driven approach for 'dynamic' reaction fingerprinting to maximise the effectiveness of reaction encoding, as well as developing a novel reaction classification system that organises labels in four hierarchical levels (SHREC: Sheffield Hierarchical REaction Classification). We show that the performance of the CP augmented model can be improved by defining confidence thresholds to detect predictions that are less likely to be false. For example, the external validation of the model reports 95% of predictions as correct by filtering out less than 15% of the uncertain classifications. The application of the model is demonstrated by classifying two reaction datasets: one extracted from an industrial ELN and the other from the medicinal chemistry literature. We show how confidence estimations and class compositions across different levels of information can be used to gain immediate insights on the nature of reaction collections and hidden relationship between reaction classes

Enhancing reaction-based de novo design using a multi-label reaction class recommender

Reaction-based de novo design refers to the in-silico generation of novel chemical structures by combining reagents using structural transformations derived from known reactions. The driver for using reaction-based transformations is to increase the likelihood of the designed molecules being synthetically accessible. We have previously described a reaction-based de novo design method based on reaction vectors which are transformation rules that are encoded automatically from reaction databases. A limitation of reaction vectors is that they account for structural changes that occur at the core of a reaction only, and they do not consider the presence of competing functionalities that can compromise the reaction outcome. Here, we present the development of a Reaction Class Recommender to enhance the reaction vector framework. The recommender is intended to be used as a filter on the reaction vectors that are applied during de novo design to reduce the combinatorial explosion of in-silico molecules produced while limiting the generated structures to those which are most likely to be synthesisable. The recommender has been validated using an external data set extracted from the recent medicinal chemistry literature and in two simulated de novo design experiments. Results suggest that the use of the recommender drastically reduces the number of solutions explored by the algorithm while preserving the chance of finding relevant solutions and increasing the global synthetic accessibility of the designed molecules

On Muddled Methods and Their Meaning

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68431/2/10.1177_048661346900100105.pd

Medicinal Plants of the Australian Aboriginal Dharawal People Exhibiting Anti-Inflammatory Activity

Chronic inflammation contributes to multiple ageing-related musculoskeletal and neurodegenerative diseases, cardiovascular diseases, asthma, rheumatoid arthritis, and inflammatory bowel disease. More recently, chronic neuroinflammation has been attributed to Parkinson's and Alzheimer's disease and autism-spectrum and obsessive-compulsive disorders. To date, pharmacotherapy of inflammatory conditions is based mainly on nonsteroidal anti-inflammatory drugs which in contrast to cytokine-suppressive anti-inflammatory drugs do not influence the production of cytokines such as tumour necrosis factoror nitric oxide. However, their prolonged use can cause gastrointestinal toxicity and promote adverse events such as high blood pressure, congestive heart failure, and thrombosis. Hence, there is a critical need to develop novel and safer nonsteroidal anti-inflammatory drugs possessing alternate mechanism of action. In this study, plants used by the Dharawal Aboriginal people in Australia for the treatment of inflammatory conditions, for example, asthma, arthritis, rheumatism, fever, oedema, eye inflammation, and inflammation of bladder and related inflammatory diseases, were evaluated for their anti-inflammatory activity in vitro. Ethanolic extracts from 17 Eucalyptus spp. (Myrtaceae) were assessed for their capacity to inhibit nitric oxide and tumor necrosis factor-production in RAW 264.7 macrophages. Eucalyptus benthamii showed the most potent nitric oxide inhibitory effect (IC 50 5.57 ± 1.4 g/mL), whilst E. bosistoana, E. botryoides, E. saligna, E. smithii, E. umbra, and E. viminali

Securing Safe Supply During COVID-19 and Beyond: Scoping Review and Knowledge Mobilization

Background Safe supply is defined as the legal and regulated provision of drugs with mind and/or body altering properties that have been typically accessible only through the illegal drug market. In response to the coronavirus disease 2019 (COVID-19) pandemic and related social/physical distancing measures, efforts have been made to scale up and increase access to safe supply programs in an effort to reduce overdose and other drug- and drug policy-related risks. However, it remains unclear whether these efforts taken thus far have meaningfully mitigated the barriers to safe supply experienced by People Who Use Drugs (PWUD), both during and beyond the context of COVID-19. We thus undertook a scoping review to identify key concepts, strategies and gaps in evidence with respect to the provision of safe supply during pandemics and other emergencies. Methods We conducted three searches across Scopus, Medline, Embase, CINAHL, and The Cochrane Central Register of Controlled Trials (CENTRAL) for peer-reviewed and grey literature articles to understand barriers/facilitators to both accessing and prescribing legal, pharmaceutical-grade drugs, including opioids, benzodiazepines, and/or stimulants during public health emergencies from January 1 2002 to June 30 2020. We also included opioid agonist therapies (OAT) during emergency conditions. All potential sources underwent title/abstract screening and duplicate full- text review to determine eligibility for inclusion. Three reviewers extracted characteristics and barriers/facilitators to accessing or prescribing drugs for each study, and these were then inductively analyzed to identify common themes. Key stakeholders (PWUD, prescribers, and policymakers/regulators) informed the search strategy and validated findings and interpretations. Input from PWUD and prescribers was gathered through Advisory Committee meetings and one-on-one consultations, respectively. Results We screened 9,839 references and included 169 studies (135 peer-reviewed articles and 36 grey literature reports). From 119 articles, we identified 35 themes related to barriers/facilitators to prescribing safe supply or OAT. Few studies (n=24) focused on emergency or pandemic contexts. Among the most frequently reported barriers were restrictive laws or policies (n= 33; 28%). The most frequently cited facilitator was temporary legal or regulatory exemptions (n= 16; 13%). Further stakeholder consultation identified barriers/facilitators to safe supply absent in the reviewed literature: PWUD reported barriers including lack of access to desired substances, concerns about child apprehension, and a lack of cultural competency within safe supply/OAT programs; prescribers reported barriers including regional differences in service delivery, colleague support, and a lack of, or disagreement between, clinical guidance documents. Conclusion We identified multiple barriers and facilitators to accessing and/or prescribing safe supply or OAT. With few peer-reviewed studies on safe supply models, particularly in the context of emergencies, input from PWUD and other stakeholders offered crucial insights not reflected in the existing literature. To address the overdose epidemic stemming from the criminalization of an unregulated drug supply, prescribers, regulators, and public health authorities should focus on scaling up, and then evaluating, diverse safe supply frameworks that address the facilitators and barriers we have identified

RENATE : a pseudo-retrosynthetic tool for synthetically accessible de novo design

Reaction-based de novo design refers to the generation of synthetically accessible molecules using transformation rules extracted from known reactions in the literature. In this context, we have previously described the extraction of reaction vectors from a reactions database and their coupling with a structure generation algorithm for the generation of novel molecules from a starting material. An issue when designing molecules from a starting material is the combinatorial explosion of possible product molecules that can be generated, especially for multistep syntheses. Here, we present the development of RENATE, a reaction-based de novo design tool, which is based on a pseudo-retrosynthetic fragmentation of a reference ligand and an inside-out approach to de novo design. The reference ligand is fragmented; each fragment is used to search for similar fragments as building blocks; the building blocks are combined into products using reaction vectors; and a synthetic route is suggested for each product molecule. The RENATE methodology is presented followed by a retrospective validation to recreate a set of approved drugs. Results show that RENATE can generate very similar or even identical structures to the corresponding input drugs, hence validating the fragmentation, search, and design heuristics implemented in the tool