Aerodynamic characterization of hypersonic transportation systems and its impact on mission analysis

This paper aims to provide technical insights on the aerodynamic characterization activities performed in the field of the H2020 STRATOFLY project, for the Mach 8 waverider reference configuration. Considering the complexity of the configuration to be analyzed at conceptual/preliminary design stage, a build-up approach has been adopted. The complexity of the aerodynamic model increases incrementally, from the clean external configuration up to the complete configuration, including propulsion systems elements and flight control surfaces. At each step, the aerodynamic analysis is complemented with detailed mission analysis, in which the different versions of the aerodynamic databases are used as input for the trajectory simulation. eventually, once the contribution to the aerodynamic characterization of flight control surfaces is evaluated, stability and trim analysis is carried out. The comparison of the results obtained through the different mission analysis campaigns clearly shows that the accuracy of aerodynamic characterization may determine the feasibility or unfeasibility of a mission concept

Vitamin K effects in human health: new insights beyond bone and cardiovascular health

Vitamin K is a cofactor for the function of the enzyme \u3b3-glutamyl carboxylase, necessary for the activation of multiple vitamin K dependent-proteins. Vitamin K dependent-proteins (VKDPs) have important roles in bone health, vascular health, metabolism, reproduction as well as in cancer progression. Vitamin K deficiency is common in different conditions, including kidney disease, and it may influence the activity of VKDPs. This review discusses vitamin K status in human health and the physiologic and pathologic roles of VKDPs, beyond the established effects in skeletal and cardiovascular health

Heterosexual, gay, and lesbian people’s reactivity to virtual caresses on their embodied avatars’ taboo zones

Embodying an artificial agent through immersive virtual reality (IVR) may lead to feeling vicariously somatosensory stimuli on one’s body which are in fact never delivered. To explore whether vicarious touch in IVR reflects the basic individual and social features of real-life interpersonal interactions we tested heterosexual men/women and gay men/lesbian women reacting subjectively and physiologically to the observation of a gender-matched virtual body being touched on intimate taboo zones (like genitalia) by male and female avatars. All participants rated as most erogenous caresses on their embodied avatar taboo zones. Crucially, heterosexual men/women and gay men/lesbian women rated as most erogenous taboo touches delivered by their opposite and same gender avatar, respectively. Skin conductance was maximal when taboo touches were delivered by female avatars. Our study shows that IVR may trigger realistic experiences and ultimately allow the direct exploration of sensitive societal and individual issues that can otherwise be explored only through imagination

Tribological properties of room temperature fluorinated graphite heat-treated under fluorine atmosphere

This work is concerned with the study of the tribologic properties of room temperature fluorinated graphite heat-treated under fluorine atmosphere. The fluorinated compounds all present good intrinsic friction properties (friction coefficient in the range 0.05–0.09). The tribologic performances are optimized if the materials present remaining graphitic domains (influenced by the presence of intercalated fluorinated species) whereas the perfluorinated compounds, where the fluorocarbon layers are corrugated (armchair configuration of the saturated carbon rings) present higher friction coefficients. Raman analyses reveal that the friction process induces severe changes in the materials structure especially the partial re-building of graphitic domains in the case of perfluorinated compounds which explains the improvement of μ during the friction tests for these last materials

Cost-Effective Cloud Computing: A Case Study Using the Comparative Genomics Tool, Roundup

Background Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource—Roundup—using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Methods Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. Results We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure

How often should we monitor for reliable detection of atrial fibrillation recurrence? Efficiency considerations and implications for study design

OBJECTIVE: Although atrial fibrillation (AF) recurrence is unpredictable in terms of onset and duration, current intermittent rhythm monitoring (IRM) diagnostic modalities are short-termed and discontinuous. The aim of the present study was to investigate the necessary IRM frequency required to reliably detect recurrence of various AF recurrence patterns. METHODS: The rhythm histories of 647 patients (mean AF burden: 12±22% of monitored time; 687 patient-years) with implantable continuous monitoring devices were reconstructed and analyzed. With the use of computationally intensive simulation, we evaluated the necessary IRM frequency to reliably detect AF recurrence of various AF phenotypes using IRM of various durations. RESULTS: The IRM frequency required for reliable AF detection depends on the amount and temporal aggregation of the AF recurrence (p<0.0001) as well as the duration of the IRM (p<0.001). Reliable detection (>95% sensitivity) of AF recurrence required higher IRM frequencies (>12 24-hour; >6 7-day; >4 14-day; >3 30-day IRM per year; p<0.0001) than currently recommended. Lower IRM frequencies will under-detect AF recurrence and introduce significant bias in the evaluation of therapeutic interventions. More frequent but of shorter duration, IRMs (24-hour) are significantly more time effective (sensitivity per monitored time) than a fewer number of longer IRM durations (p<0.0001). CONCLUSIONS: Reliable AF recurrence detection requires higher IRM frequencies than currently recommended. Current IRM frequency recommendations will fail to diagnose a significant proportion of patients. Shorter duration but more frequent IRM strategies are significantly more efficient than longer IRM durations. CLINICAL TRIAL REGISTRATION URL: Unique identifier: NCT00806689

The Potential of Accelerating Early Detection of Autism through Content Analysis of YouTube Videos

Abstract Autism is on the rise, with 1 in 88 children receiving a diagnosis in the United States, yet the process for diagnosis remains cumbersome and time consuming. Research has shown that home videos of children can help increase the accuracy of diagnosis. However the use of videos in the diagnostic process is uncommon. In the present study, we assessed the feasibility of applying a gold-standard diagnostic instrument to brief and unstructured home videos and tested whether video analysis can enable more rapid detection of the core features of autism outside of clinical environments. We collected 100 public videos from YouTube of children ages 1–15 with either a self-reported diagnosis of an ASD (N = 45) or not (N = 55). Four non-clinical raters independently scored all videos using one of the most widely adopted tools for behavioral diagnosis of autism, the Autism Diagnostic Observation Schedule-Generic (ADOS). The classification accuracy was 96.8%, with 94.1% sensitivity and 100% specificity, the inter-rater correlation for the behavioral domains on the ADOS was 0.88, and the diagnoses matched a trained clinician in all but 3 of 22 randomly selected video cases. Despite the diversity of videos and non-clinical raters, our results indicate that it is possible to achieve high classification accuracy, sensitivity, and specificity as well as clinically acceptable inter-rater reliability with nonclinical personnel. Our results also demonstrate the potential for video-based detection of autism in short, unstructured home videos and further suggests that at least a percentage of the effort associated with detection and monitoring of autism may be mobilized and moved outside of traditional clinical environments