Thoracic Gas Volume in Athletes and Non-Athletes

The purpose of this study was to analyze the predicted thoracic gas volume versus measured thoracic gas volume in college students, comparing NCAA collegiate athletes versus non-athletes using the Bod Pod. Forty-four college students, both males and females, athletes and non-athletes, completed a body composition test to obtain the predicted thoracic gas volume. The participants were then instructed by the Bod Pod software through the measured thoracic gas volume test. Due to low statistical power, athletes and non-athletes were unable to be compared, however, results of a two sample t-test showed that there was a statistically significant difference between measured thoracic gas volume and predicted thoracic gas volume within the population as a whole. The average predicted thoracic gas volume was 3.66 liters ± 0.103 while the measured thoracic gas volume was 4.02 liters ± 0.165. The significance level for the test was p ≤ 0.05 and the p-value obtained from the statistical analysis was p ≤ 0.001. It was concluded that within this study, there was a significant difference between the predicted and measured thoracic gas volumes of the population

A Zoomable Mapping of a Musical Parameter Space Using Hilbert Curves

The final publication is available at Computer Music Journal via http://dx.doi.org/10.1162/COMJ_a_0025

Independent prognostic value of fascin immunoreactivity in stage I nonsmall cell lung cancer

Fascin-1, the most expressed form of fascin in vertebrate tissues, is an actin-bundling protein that induces cell membrane protrusions and increases motility of normal and transformed epithelial cells. Very few data are available on the role of this protein in nonsmall cell lung cancer (NSCLC). Two hundred and twenty patients with stage I NSCLC and long-term follow-up were evaluated immunocytochemically for fascin expression. Overall, variable fascin immunoreactivity was detected in 98% of 116 squamous cell carcinomas, in 78% of 96 adenocarcinomas, in 83% of six large cell carcinomas, and in the two adenosquamous carcinomas under study. Neoplastic emboli were commonly decorated by the antifascin antibody (P<0.001), also when the surrounding invasive carcinoma was unreactive. Fascin immunoreactivity correlated with high tumour grade (P=0.017) and, in adenocarcinomas, with high Ki-67 labelling index (P=0.021). Adenocarcinomas with a prevalent bronchiolo-alveolar in situ component were less commonly immunoreactive for fascin than invasive tumours (P=0.005). Contralateral thoracic or distant metastases were associated significantly with diffuse (>60% immunoreactive tumour cells) fascin expression in adenocarcinomas (P=0.043), and marginally with strong fascin immunostaining in squamous cell carcinomas (P=0.13). No associations were noted with any other clinicopathological variables tested. Patients with tumours showing diffuse (>60% immunoreactive neoplastic cells) and/or strong immunoreactivity for fascin had a shorter survival (P=0.006 for adenocarcinomas and P=0.026 for squamous cell carcinomas), even after multivariate analysis (P=0.014 and 0.050, respectively). The current study documents for the first time that fascin is upregulated in invasive and more aggressive NSCLC, being an independent prognostic predictor of unfavourable clinical course of the disease. Targetting the fascin pathway could be a novel therapeutic strategy of NSCLC

Scenario-based requirements elicitation for user-centric explainable AI

Explainable Artificial Intelligence (XAI) develops technical explanation methods and enable interpretability for human stakeholders on why Artificial Intelligence (AI) and machine learning (ML) models provide certain predictions. However, the trust of those stakeholders into AI models and explanations is still an issue, especially domain experts, who are knowledgeable about their domain but not AI inner workings. Social and user-centric XAI research states it is essential to understand the stakeholder’s requirements to provide explanations tailored to their needs, and enhance their trust in working with AI models. Scenario-based design and requirements elicitation can help bridge the gap between social and operational aspects of a stakeholder early before the adoption of information systems and identify its real problem and practices generating user requirements. Nevertheless, it is still rarely explored the adoption of scenarios in XAI, especially in the domain of fraud detection to supporting experts who are about to work with AI models. We demonstrate the usage of scenario-based requirements elicitation for XAI in a fraud detection context, and develop scenarios derived with experts in banking fraud. We discuss how those scenarios can be adopted to identify user or expert requirements for appropriate explanations in his daily operations and to make decisions on reviewing fraudulent cases in banking. The generalizability of the scenarios for further adoption is validated through a systematic literature review in domains of XAI and visual analytics for fraud detection

Phytolith Analysis for Differentiating between Foxtail Millet (Setaria italica) and Green Foxtail (Setaria viridis)

Foxtail millet (Setaria italica) is one of the oldest domesticated cereal crops in Eurasia, but identifying foxtail millets, especially in charred grains, and differentiating it from its wild ancestor, green foxtail (Setaria viridis), in the archaeobotanical remains, is still problematic. Phytolithic analysis provides a meaningful method for identifying this important crop. In this paper, the silicon structure patterns in the glumes, lemmas, and paleas from inflorescence bracts in 16 modern plants of foxtail millet and green foxtail from China and Europe are examined using light microscopy with phase-contrast and a microscopic interferometer. Our research shows that the silicon structure of ΩIII from upper lemmas and paleas in foxtail millet and green foxtail can be correspondingly divided into two groups. The size of ΩIII type phytolith of foxtail millet is bigger than that from green foxtail. Discriminant function analysis reveals that 78.4% of data on foxtail millet and 76.9% of data on green foxtail are correctly classified. This means certain morphotypes of phytoliths are relatively reliable tools for distinguishing foxtail millet from green foxtail. Our results also revealed that the husk phytolith morphologies of foxtail millets from China and Eastern Europe are markedly different from those from Western Europe. Our research gives a meaningful method of separating foxtail millet and green foxtail. The implications of these findings for understanding the history of foxtail millet domestication and cultivation in ancient civilizations are significant

Single-dose administration and the influence of the timing of the booster dose on immunogenicity and efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine: a pooled analysis of four randomised trials.

BACKGROUND: The ChAdOx1 nCoV-19 (AZD1222) vaccine has been approved for emergency use by the UK regulatory authority, Medicines and Healthcare products Regulatory Agency, with a regimen of two standard doses given with an interval of 4-12 weeks. The planned roll-out in the UK will involve vaccinating people in high-risk categories with their first dose immediately, and delivering the second dose 12 weeks later. Here, we provide both a further prespecified pooled analysis of trials of ChAdOx1 nCoV-19 and exploratory analyses of the impact on immunogenicity and efficacy of extending the interval between priming and booster doses. In addition, we show the immunogenicity and protection afforded by the first dose, before a booster dose has been offered. METHODS: We present data from three single-blind randomised controlled trials-one phase 1/2 study in the UK (COV001), one phase 2/3 study in the UK (COV002), and a phase 3 study in Brazil (COV003)-and one double-blind phase 1/2 study in South Africa (COV005). As previously described, individuals 18 years and older were randomly assigned 1:1 to receive two standard doses of ChAdOx1 nCoV-19 (5 × 1010 viral particles) or a control vaccine or saline placebo. In the UK trial, a subset of participants received a lower dose (2·2 × 1010 viral particles) of the ChAdOx1 nCoV-19 for the first dose. The primary outcome was virologically confirmed symptomatic COVID-19 disease, defined as a nucleic acid amplification test (NAAT)-positive swab combined with at least one qualifying symptom (fever ≥37·8°C, cough, shortness of breath, or anosmia or ageusia) more than 14 days after the second dose. Secondary efficacy analyses included cases occuring at least 22 days after the first dose. Antibody responses measured by immunoassay and by pseudovirus neutralisation were exploratory outcomes. All cases of COVID-19 with a NAAT-positive swab were adjudicated for inclusion in the analysis by a masked independent endpoint review committee. The primary analysis included all participants who were SARS-CoV-2 N protein seronegative at baseline, had had at least 14 days of follow-up after the second dose, and had no evidence of previous SARS-CoV-2 infection from NAAT swabs. Safety was assessed in all participants who received at least one dose. The four trials are registered at ISRCTN89951424 (COV003) and ClinicalTrials.gov, NCT04324606 (COV001), NCT04400838 (COV002), and NCT04444674 (COV005). FINDINGS: Between April 23 and Dec 6, 2020, 24 422 participants were recruited and vaccinated across the four studies, of whom 17 178 were included in the primary analysis (8597 receiving ChAdOx1 nCoV-19 and 8581 receiving control vaccine). The data cutoff for these analyses was Dec 7, 2020. 332 NAAT-positive infections met the primary endpoint of symptomatic infection more than 14 days after the second dose. Overall vaccine efficacy more than 14 days after the second dose was 66·7% (95% CI 57·4-74·0), with 84 (1·0%) cases in the 8597 participants in the ChAdOx1 nCoV-19 group and 248 (2·9%) in the 8581 participants in the control group. There were no hospital admissions for COVID-19 in the ChAdOx1 nCoV-19 group after the initial 21-day exclusion period, and 15 in the control group. 108 (0·9%) of 12 282 participants in the ChAdOx1 nCoV-19 group and 127 (1·1%) of 11 962 participants in the control group had serious adverse events. There were seven deaths considered unrelated to vaccination (two in the ChAdOx1 nCov-19 group and five in the control group), including one COVID-19-related death in one participant in the control group. Exploratory analyses showed that vaccine efficacy after a single standard dose of vaccine from day 22 to day 90 after vaccination was 76·0% (59·3-85·9). Our modelling analysis indicated that protection did not wane during this initial 3-month period. Similarly, antibody levels were maintained during this period with minimal waning by day 90 (geometric mean ratio [GMR] 0·66 [95% CI 0·59-0·74]). In the participants who received two standard doses, after the second dose, efficacy was higher in those with a longer prime-boost interval (vaccine efficacy 81·3% [95% CI 60·3-91·2] at ≥12 weeks) than in those with a short interval (vaccine efficacy 55·1% [33·0-69·9] at <6 weeks). These observations are supported by immunogenicity data that showed binding antibody responses more than two-fold higher after an interval of 12 or more weeks compared with an interval of less than 6 weeks in those who were aged 18-55 years (GMR 2·32 [2·01-2·68]). INTERPRETATION: The results of this primary analysis of two doses of ChAdOx1 nCoV-19 were consistent with those seen in the interim analysis of the trials and confirm that the vaccine is efficacious, with results varying by dose interval in exploratory analyses. A 3-month dose interval might have advantages over a programme with a short dose interval for roll-out of a pandemic vaccine to protect the largest number of individuals in the population as early as possible when supplies are scarce, while also improving protection after receiving a second dose. FUNDING: UK Research and Innovation, National Institutes of Health Research (NIHR), The Coalition for Epidemic Preparedness Innovations, the Bill & Melinda Gates Foundation, the Lemann Foundation, Rede D'Or, the Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca