Development of an Interactive Wave Drag Capability for the OpenVSP Parametric Geometry Tool

Minimizing wave drag is critical to successful and efficient transonic and supersonic flight. Area-ruling is the process of managing the cross-sectional area of an aircraft to lessen the wave drag experienced in flight. Effectively calculating the necessary areas for a given aircraft can be difficult, and existing tools for conducting a wave drag analysis often carry limitations in both functionality and availability. In this work, the author utilized an existing parametric geometry tool named OpenVSP to create an interactive design tool for approximating zero-lift wave drag. Here, the wave drag calculation methodology used in industry for decades is combined with the powerful geometry engine of OpenVSP, which was recently heavily upgraded at the start of 2015. Various visual aids allow users of this OpenVSP wave drag tool to interact with area and wave drag results and develop intuition for supersonic aircraft design using the area rule approach. OpenVSP allows geometry changes to be made quickly, enabling rapid reanalysis by the wave drag tool for expeditious comparison of results across the design space

Involving children and young adults with complex needs in game design

Involving young people with complex needs in game design can be a challenging research endeavor, particularly when working within a school context. In this paper, we discuss findings from two case studies where we worked with young adults with visual impairment, and young people with mobility disabilities. We focus on ethical challenges that emerged during the research process, and we discuss management strategies to foster the establishment of inclusive and engaging field research into video games for young people with complex needs

Impact of bidirectional relationships between streptococcus anginosus group and host tissue matrix components on cellular activity: Role in establishment of infection

This paper investigates pathogenic mechanisms of the Streptococcus anginosus group (SAG) of bacteria which influence the biological activity of periodontal ligament (PDL) cells, endothelial cells and also how matrix proteins produced by these host cells influence bacterial virulence factors. Isolates of SAG species, designated S. anginosus, S. constellatus and S. intermedius, were derived from healthy commensal and clinical pathogenic infection sites. SAG culture supernatants contained multiple protein components which differed between isolates. All SAG supernatants increased cellular proliferation and decreased decorin synthesis and collagen assembly by PDL cells and reduced endothelial cell migration. SAG isolates responded differently to extracellular matrix (ECM) components synthesised by PDL cells, but there was an overall notable increase in hydrolytic enzyme activity and in the production of the cytotoxin intermedilysin by S. intermedius. Collectively, the results indicate that both commensal and pathogenic SAG isolates were capable of impairing the ability of PDL cells and endothelial cells to make functional vascularised tissue. Reduced decorin synthesis is likely to have a major impact on cell signalling, angiogenesis and matrix assembly. Furthermore, ECM components produced by PDL cells were differentially capable of moderately increasing SAG enzymic activity, leading to subtle ECM modifications. The impact this bidirectional effect has on the tissue remodelling process is discussed

Identification of Enterobacter sakazakii from closely related species: The use of Artificial Neural Networks in the analysis of biochemical and 16S rDNA data

BACKGROUND: Enterobacter sakazakii is an emergent pathogen associated with ingestion of infant formula and accurate identification is important in both industrial and clinical settings. Bacterial species can be difficult to accurately characterise from complex biochemical datasets and computer algorithms can potentially simplify the process. RESULTS: Artificial Neural Networks were applied to biochemical and 16S rDNA data derived from 282 strains of Enterobacteriaceae, including 189 E. sakazakii isolates, in order to identify key characteristics which could improve the identification of E. sakazakii. The models developed resulted in a predictive performance for blind (validation) data of 99.3 % correct discrimination between E. sakazakii and closely related species for both phenotypic and genotypic data. Three main regions of the partial rDNA sequence were found to be key in discriminating the species. Comparison between E. sakazakii and other strains also constitutively positive for expression of the enzyme α-glucosidase resulted in a predictive performance of 98.7 % for 16S rDNA sequence data and 100% for phenotypic data. CONCLUSION: The computationally based methods developed here show a remarkable ability in reducing data dimensionality and complexity, in order to eliminate noise from the system in order to facilitate the speed and reliability of a potential strain identification system. Furthermore, the approaches described are also able to provide valuable information regarding the population structure and distribution of individual species thus providing the foundations for novel assays and diagnostic tests for rapid identification of pathogens

Factors Influencing Team Performance:What Can Support Teams in High-Performance Sport Learn from Other Industries? A Systematic Scoping Review

BACKGROUND: The primary aim of our systematic scoping review was to explore the factors influencing team function and performance across various industries and discuss findings in the context of the high-performance sport support team setting. These outcomes may also be used to inform future research into high-performance teamwork in sport. METHODS: A systematic scoping review of literature published in English since 2000 reporting team-based performance outcomes and included a performance metric that was ‘team outcome based’ was conducted using search of the Academic Search Ultimate, Medline, Business Source Ultimate, APA PsycInfo, CINAHL, SPORTDiscus, and Military database (ProQuest) using the terms: ‘team’, ‘function’ OR ‘dysfunction’, ‘Perform*’ OR ‘outcome’. RESULTS: Application of the search strategy identified a total of 11,735 articles for title and abstract review. Seventy-three articles were selected for full-text assessment with the aim to extract data for either quantitative or qualitative analysis. Forty-six of the 73 articles met our inclusion criteria; 27 articles were excluded as they did not report a performance metric. Eleven studies explored leadership roles and styles on team performance, three studies associated performance feedback to team performance, and 12 studies explored the relationship between supportive behaviour and performance. Team orientation and adaptability as key figures of team performance outcomes were explored in 20 studies. CONCLUSIONS: Our findings identified 4 key variables that were associated with team function and performance across a variety of industries; (i) leadership styles, (ii) supportive team behaviour, (iii) communication, and (iv) performance feedback. High-performance teams wishing to improve performance should examine these factors within their team and its environment. It is widely acknowledged that the dynamics of team function is important for outcomes in high-performance sport, yet there is little evidence to provide guidance. This inequality between real-world need and the available evidence should be addressed in future research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40798-021-00406-7

The spatial clustering of ultraluminous infrared galaxies over 1.5 < z < 3

We present measurements of the spatial clustering of galaxies with stellar masses 1011 M, infrared luminosities 1012 L, and star formation rates 200 M yr-1 in two redshift intervals: 1.5 &lt; z &lt; 2.0 and 2 &lt; z &lt; 3. Both samples cluster moderately strongly, with spatial correlation lengths of r0 = 6.14 B1 0.84 h-1 Mpc for the 2 &lt; z &lt; 3 sample and r0 = 5.36 B1 1.28 h-1 Mpc for the 1.5 &lt; z &lt; 2.0 sample. These clustering amplitudes are consistent with both populations residing in dark matter halos with masses of 7 C 1012 M, which is comparable to that seen for optical QSOs at the same epochs. We infer that a minimum dark matter halo mass is an important factor for all forms of luminous, obscured activity in galaxies at z &gt; 1, both starbursts and active galactic nuclei. Adopting plausible models for the growth of dark matter halos with redshift, the halos hosting the 2 &lt; z &lt; 3 sample will likely host poor to rich clusters of galaxies at z = 0, whereas the halos hosting the 1.5 &lt; z &lt; 2.0 sample will likely host L* elliptical galaxies or poor clusters at z = 0. We conclude that ultraluminous infrared galaxies (ULIRGs) at z 2.5 likely signpost stellar buildup in galaxies that will reside in clusters at z = 0 and that ULIRGs at z 1.7 signpost stellar buildup in sources that will either become L* elliptical galaxies or reside in poor clusters at z = 0

The implementation of a shared reading programme within a university : a case study

Based on research into the benefits of involvement in reading for pleasure and the operation in the US of pre-arrival shared reading schemes for those about to embark on a university education, both within the context of wider research into how to engage newly arrived students in their institution, an exploration was made of the likely response to such a shared reading scheme within a London university. A representative sample of current first years were asked about their how they spent their leisure time, their attitudes towards and involvement in reading for pleasure and their reactions to such a potential scheme. The findings were that more reading for pleasure was taking part than had been anticipated, that students were generally keen to become more involved in reading and that a shared reading scheme would be welcomed by the majority of students. The decisions made on the basis of the outcomes are discussed, along with recommendations for future associated research

An Automated System for Rapid Non-Destructive Enumeration of Growing Microbes

The power and simplicity of visual colony counting have made it the mainstay of microbiological analysis for more than 130 years. A disadvantage of the method is the long time required to generate visible colonies from cells in a sample. New rapid testing technologies generally have failed to maintain one or more of the major advantages of culture-based methods.We present a new technology and platform that uses digital imaging of cellular autofluorescence to detect and enumerate growing microcolonies many generations before they become visible to the eye. The data presented demonstrate that the method preserves the viability of the microcolonies it detects, thus enabling generation of pure cultures for microbial identification. While visual colony counting detects Escherichia coli colonies containing about 5x10(6) cells, the new imaging method detects E. coli microcolonies when they contain about 120 cells and microcolonies of the yeast Candida albicans when they contain only about 12 cells. We demonstrate that digital imaging of microcolony autofluorescence detects a broad spectrum of prokaryotic and eukaryotic microbes and present a model for predicting the time to detection for individual strains. Results from the analysis of environmental samples from pharmaceutical manufacturing plants containing a mixture of unidentified microbes demonstrate the method's improved test turnaround times.This work demonstrates a new technology and automated platform that substantially shortens test times while maintaining key advantages of the current methods

Angular clustering of galaxies at 3.6 microns from the Spitzer Wide-area Infrared Extragalactic (SWIRE) Survey

We present the first analysis of large-scale clustering from the Spitzer Wide-area Infrared Extragalactic legacy survey (SWIRE). We compute the angular correlation function of galaxies selected to have 3.6 m fluxes brighter than 32 Jy in three fields totaling 2 deg2 in area. In each field we detect clustering with a high level of significance. The amplitude and slope of the correlation function is consistent between the three fields and is modeled as w() ¼ A1 with A ¼ (0:6 0:3) ; 10 3; ¼ 2:03 0:10. With a fixed slope of ¼ 1:8, we obtain an amplitude of A ¼ (1:7 0:1) ; 10 3. Assuming an equivalent depth of K 18:7 mag we find that our errors are smaller but our results are consistent with existing clustering measurements in K-band surveys and with stable clustering models. We estimate our median redshift z ’ 0:75, and this allows us to obtain an estimate of the three-dimensional correlation function (r), for which we find r0 ¼ 4:4 0:1 h 1 Mpc