Task Allocation for Single Pilot Operations: A Role for the Ground

Researchers at NASA Ames Research Center and NASA Langley Research Center are jointly investigating issues associated with potential configurations for an environment in which a single pilot, or reduced crew, might operate. The research summarized in this document represents several of the efforts being put forth at NASA Ames Research Center. Specifically, researchers at NASA Ames Research Center coordinated and hosted a technical interchange meeting in order to gain insight from members of the aviation community. A description of this meeting and the findings are presented first. Thereafter, plans for ensuing research are presented

Lay media reporting of rosiglitazone risk: extent, messaging and quality of reporting

<p>Abstract</p> <p>Background</p> <p>A meta-analysis suggested the use of rosiglitazone was associated with an increased risk for cardiovascular (CV) events. Rosiglitazone remained available for use as more definitive safety trials were ongoing. This issue was reported in the lay media.</p> <p>Objective</p> <p>To review lay media articles to determine the extent of media coverage, the nature of the messaging, and to assess the quality of reporting.</p> <p>Methods</p> <p>The Factiva media database was used to identify articles published between May 18 and August 31, 2007. Two reviewers (a lay person and a physician) screened full text articles for eligibility, appraised the articles for their tone (worrisome, neutral, not worrisome), and for the quality of medical data reporting.</p> <p>Results</p> <p>The search identified 156 articles, 95 of which were eligible for our review. Agreement between the lay and medical reviewers in the appraisal of the article tone was 67.4%. Among those with agreement, the articles were often appraised as "worrisome" (75.3%). Among those with disagreement, the lay reviewer was significantly more likely to appraise articles as worrisome compared to the medical reviewer (77.4% vs. 3.2%, X2 = 9.11, P = 0.003). Cardiovascular risk was discussed in 91.6% of the articles, but risk was often reported in qualitative or relative terms.</p> <p>Conclusion</p> <p>There were many lay media articles addressing the safety of rosiglitazone, and the general messaging of these articles was considered "worrisome" by reviewers. Quality of risk reporting in the articles reviewed was poor. The impact of such media coverage on public anxiety and confidence in treatment should be explored.</p

NASA's Single-Pilot Operations Technical Interchange Meeting: Proceedings and Findings

Researchers at the National Aeronautics and Space Administration (NASA) Ames Research Center and Langley Research Center are jointly investigating issues associated with potential concepts, or configurations, in which a single pilot might operate under conditions that are currently reserved for a minimum of two pilots. As part of early efforts, NASA Ames Research Center hosted a technical interchange meeting in order to gain insight from members of the aviation community regarding single-pilot operations (SPO). The meeting was held on April 10-12, 2012 at NASA Ames Research Center. Professionals in the aviation domain were invited because their areas of expertise were deemed to be directly related to an exploration of SPO. NASA, in selecting prospective participants, attempted to represent various relevant sectors within the aviation domain. Approximately 70 people representing government, academia, and industry attended. A primary focus of this gathering was to consider how tasks and responsibilities might be re-allocated to allow for SPO

An AI approach to operationalise global daily PlanetScope satellite imagery for river water masking

Monitoring rivers is vital to manage the invaluable ecosystem services they provide, and also to mitigate the risks they pose to property and life through flooding and drought. Due to the vast extent and dynamic nature of river systems, Earth Observation (EO) is one of the best ways to measure river characteristics. As a first step, EO-based river monitoring often requires extraction of accurate pixel-level water masks, but satellite images traditionally used for this purpose suffer from limited spatial and/or temporal resolution. We address this problem by applying a novel Convolutional Neural Network (CNN)-based model to automate water mask extraction from daily 3 m resolution PlanetScope satellite imagery. Notably, this approach overcomes radiometric issues that frequently present limitations when working with CubeSat data. We test our classification model on 36 rivers across 12 global terrestrial biomes (as proxies for the environmental and physical characteristics that lead to the variability in catchments around the globe). Using a relatively shallow CNN classification model, our approach produced a median F1 accuracy score of 0.93, suggesting that a compact and efficient CNN-based model can work as well as, if not better than, the very deep neural networks conventionally used in similar studies, whilst requiring less training data and computational power. We further show that our model, specialised to the task at hand, performs better than a state-of-the-art Fully Convolutional Neural Network (FCN) that struggles with the highly variable image quality from PlanetScope. Although classifying rivers that were narrower than 60 m, anastomosed or highly urbanised was slightly less successful than our other test images, we showed that fine tuning could circumvent these limitations to some degree. Indeed, fine tuning carried out on the Ottawa River, Canada, by including just 5 additional site-specific training images significantly improved classification accuracy (F1 increased from 0.81 to 0.90, p < 0.01). Overall, our results show that CNN-based classification applied to PlanetScope imagery is a viable tool for producing accurate, temporally dynamic river water masks, opening up possibilities for river monitoring investigations where high temporal variability data is essential

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

The Numerical-Relativity-Analytical-Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis communities. The goal of the NRAR collaboration is to produce numerical-relativity simulations of compact binaries and use them to develop accurate analytical templates for the LIGO/Virgo Collaboration to use in detecting gravitational-wave signals and extracting astrophysical information from them. We describe the results of the first stage of the NRAR project, which focused on producing an initial set of numerical waveforms from binary black holes with moderate mass ratios and spins, as well as one non-spinning binary configuration which has a mass ratio of 10. All of the numerical waveforms are analysed in a uniform and consistent manner, with numerical errors evaluated using an analysis code created by members of the NRAR collaboration. We compare previously-calibrated, non-precessing analytical waveforms, notably the effective-one-body (EOB) and phenomenological template families, to the newly-produced numerical waveforms. We find that when the binary's total mass is ~100-200 solar masses, current EOB and phenomenological models of spinning, non-precessing binary waveforms have overlaps above 99% (for advanced LIGO) with all of the non-precessing-binary numerical waveforms with mass ratios <= 4, when maximizing over binary parameters. This implies that the loss of event rate due to modelling error is below 3%. Moreover, the non-spinning EOB waveforms previously calibrated to five non-spinning waveforms with mass ratio smaller than 6 have overlaps above 99.7% with the numerical waveform with a mass ratio of 10, without even maximizing on the binary parameters.Comment: 51 pages, 10 figures; published versio

Implementation of evidence-based multiple focus integrated intensified TB screening to end TB (EXIT-TB) package in East Africa : a qualitative study

Funding: This study was part of the EXIT-TB project funded by the European & Developing Countries Clinical Trials Partnership 2 (EDCTP2) program supported by the European Union (Grant number CSA2016S-1608).Introduction Tuberculosis (TB) remains a major cause of morbidity and mortality, especially in sub-Saharan Africa. We qualitatively evaluated the implementation of an Evidence-Based Multiple Focus Integrated Intensified TB Screening package (EXIT-TB) in the East African region, aimed at increasing TB case detection and number of patients receiving care. Objective We present the accounts of participants from Tanzania, Kenya, Uganda, and Ethiopia regarding the implementation of EXIT-TB, and suggestions for scaling up. Methods A qualitative descriptive design was used to gather insights from purposefully selected healthcare workers, community health workers, and other stakeholders. A total of 27, 13, 14, and 19 in-depth interviews were conducted in Tanzania, Kenya, Uganda, and Ethiopia respectively. Data were transcribed and translated simultaneously and then thematically analysed. Results The EXIT-TB project was described to contribute to increased TB case detection, improved detection of Multidrug-resistant TB patients, reduced delays and waiting time for diagnosis, raised the index of TB suspicion, and improved decision-making among HCWs. The attributes of TB case detection were: (i) free X-ray screening services; (ii) integrating TB case-finding activities in other clinics such as Reproductive and Child Health clinics (RCH), and diabetic clinics; (iii), engagement of CHWs, policymakers, and ministry level program managers; (iv) enhanced community awareness and linkage of clients; (v) cooperation between HCWs and CHWs, (vi) improved screening infrastructure, (vii) the adoption of the new simplified screening criteria and (viii) training of implementers. The supply-side challenges encountered ranged from disorganized care, limited space, the COVID-19 pandemic, inadequate human resources, inadequate knowledge and expertise, stock out of supplies, delayed maintenance of equipment, to absence of X-ray and GeneXpert machines in some facilities. The demand side challenges ranged from delayed care seeking, inadequate awareness, negative beliefs, fears towards screening, to financial challenges. Suggestions for scaling up ranged from improving service delivery, access to diagnostic equipment and supplies, and infrastructure, to addressing client fears and stigma. Conclusion The EXIT-TB package appears to have contributed towards increasing TB case detection and reducing delays in TB treatment in the study settings. Addressing the challenges identified is needed to maximize the impact of the EXIT-TB intervention.Publisher PDFPeer reviewe

Acceptability of woman-delivered HIV self-testing to the male partner, and additional interventions: a qualitative study of antenatal care participants in Malawi

In the era of ambitious HIV targets, novel HIV testing models are required for hard-to-reach groups such as men, who remain underserved by existing services. Pregnancy presents a unique opportunity for partners to test for HIV, as many pregnant women will attend antenatal care (ANC). We describe the views of pregnant women and their male partners on HIV self-test kits that are woman-delivered, alone or with an additional intervention. A formative qualitative study to inform the design of a multi-arm multi-stage cluster-randomized trial, comprised of six focus group discussions and 20 in-depth interviews, was conducted. ANC attendees were purposively sampled on the day of initial clinic visit, while men were recruited after obtaining their contact information from their female partners. Data were analysed using content analysis, and our interpretation is hypothetical as participants were not offered self-test kits. Providing HIV self-test kits to pregnant women to deliver to their male partners was highly acceptable to both women and men. Men preferred this approach compared with standard facility-based testing, as self-testing fits into their lifestyles which were characterized by extreme day-to-day economic pressures, including the need to raise money for food for their household daily. Men and women emphasized the need for careful communication before and after collection of the self-test kits in order to minimize the potential for intimate partner violence although physical violence was perceived as less likely to occur. Most men stated a preference to first self-test alone, followed by testing as a couple. Regarding interventions for optimizing linkage following self-testing, both men and women felt that a fixed financial incentive of approximately USD$2 would increase linkage. However, there were concerns that financial incentives of greater value may lead to multiple pregnancies and lack of child spacing. In this low-income setting, a lottery incentive was considered overly disappointing for those who receive nothing. Phone call reminders were preferred to short messaging service. Woman-delivered HIV self-testing through ANC was acceptable to pregnant women and their male partners. Feedback on additional linkage enablers will be used to alter pre-planned trial arms

Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis

Background: Epidemiological surveys of malaria currently rely on microscopy, polymerase chain reaction assays (PCR) or rapid diagnostic test kits for Plasmodium infections (RDTs). This study investigated whether mid-infrared (MIR) spectroscopy coupled with supervised machine learning could constitute an alternative method for rapid malaria screening, directly from dried human blood spots. Methods: Filter papers containing dried blood spots (DBS) were obtained from a cross-sectional malaria survey in 12 wards in southeastern Tanzania in 2018/19. The DBS were scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) spectrometer to obtain high-resolution MIR spectra in the range 4000 cm−1 to 500 cm−1. The spectra were cleaned to compensate for atmospheric water vapour and CO2 interference bands and used to train different classification algorithms to distinguish between malaria-positive and malaria-negative DBS papers based on PCR test results as reference. The analysis considered 296 individuals, including 123 PCR-confirmed malaria positives and 173 negatives. Model training was done using 80% of the dataset, after which the best-fitting model was optimized by bootstrapping of 80/20 train/test-stratified splits. The trained models were evaluated by predicting Plasmodium falciparum positivity in the 20% validation set of DBS. Results: Logistic regression was the best-performing model. Considering PCR as reference, the models attained overall accuracies of 92% for predicting P. falciparum infections (specificity = 91.7%; sensitivity = 92.8%) and 85% for predicting mixed infections of P. falciparum and Plasmodium ovale (specificity = 85%, sensitivity = 85%) in the field-collected specimen. Conclusion: These results demonstrate that mid-infrared spectroscopy coupled with supervised machine learning (MIR-ML) could be used to screen for malaria parasites in human DBS. The approach could have potential for rapid and high-throughput screening of Plasmodium in both non-clinical settings (e.g., field surveys) and clinical settings (diagnosis to aid case management). However, before the approach can be used, we need additional field validation in other study sites with different parasite populations, and in-depth evaluation of the biological basis of the MIR signals. Improving the classification algorithms, and model training on larger datasets could also improve specificity and sensitivity. The MIR-ML spectroscopy system is physically robust, low-cost, and requires minimum maintenance