Apollo communications system. Task E-59B - MSFTP-2 bit synchronizer performance analysis

Mathematical model for predicting performance degradation of MSFTP-2 bit synchronizer used in MSF

Concepts of mental disorders in the United Kingdom : Similarities and differences between the lay public and psychiatrists

BACKGROUND: The lay public often conceptualise mental disorders in a different way to mental health professionals, and this can negatively impact on outcomes when in treatment. AIMS: This study explored which disorders the lay public are familiar with, which theoretical models they understand, which they endorse and how they compared to a sample of psychiatrists. METHODS: The Maudsley Attitude Questionnaire (MAQ), typically used to assess mental health professional's concepts of mental disorders, was adapted for use by a lay community sample (N = 160). The results were compared with a sample of psychiatrists (N = 76). RESULTS: The MAQ appeared to be accessible to the lay public, providing some interesting preliminary findings: in order, the lay sample reported having the best understanding of depression followed by generalised anxiety, schizophrenia and finally antisocial personality disorder. They best understood spiritualist, nihilist and social realist theoretical models of these disorders, but were most likely to endorse biological, behavioural and cognitive models. The lay public were significantly more likely to endorse some models for certain disorders suggesting a nuanced understanding of the cause and likely cure, of various disorders. Ratings often differed significantly from the sample of psychiatrists who were relatively steadfast in their endorsement of the biological model. CONCLUSION: The adapted MAQ appeared accessible to the lay sample. Results suggest that the lay public are generally aligned with evidence-driven concepts of common disorders, but may not always understand or agree with how mental health professionals conceptualise them. The possible causes of these differences, future avenues for research and the implications for more collaborative, patient-clinician conceptualisations are discussed.Peer reviewedFinal Accepted Versio

Blogging in the physics classroom: A research-based approach to shaping students' attitudes towards physics

Even though there has been a tremendous amount of research done in how to help students learn physics, students are still coming away missing a crucial piece of the puzzle: why bother with physics? Students learn fundamental laws and how to calculate, but come out of a general physics course without a deep understanding of how physics has transformed the world around them. In other words, they get the "how" but not the "why". Studies have shown that students leave introductory physics courses almost universally with decreased expectations and with a more negative attitude. This paper will detail an experiment to address this problem: a course weblog or "blog" which discusses real-world applications of physics and engages students in discussion and thinking outside of class. Specifically, students' attitudes towards the value of physics and its applicability to the real-world were probed using a 26-question Likert scale survey over the course of four semesters in an introductory physics course at a comprehensive Jesuit university. We found that students who did not participate in the blog study generally exhibited a deterioration in attitude towards physics as seen previously. However, students who read, commented, and were involved with the blog maintained their initially positive attitudes towards physics. Student response to the blog was overwhelmingly positive, with students claiming that the blog made the things we studied in the classroom come alive for them and seem much more relevant.Comment: 20 pages, 6 figure

Machine Learning Approaches to Predict Learning Outcomes in Massive Open Online Courses

With the rapid advancements in technology, Massive Open Online Courses (MOOCs) have become the most popular form of online educational delivery, largely due to the removal of geographical and financial barriers for participants. A large number of learners globally enrol in such courses. Despite the flexible accessibility, results indicate that the completion rate is quite low. Educational Data Mining and Learning Analytics are emerging fields of research that aim to enhance the delivery of education through the application of various statistical and machine learning approaches. An extensive literature survey indicates that no significant research is available within the area of MOOC data analysis, in particular considering the behavioural patterns of users. In this paper, therefore, two sets of features, based on learner behavioural patterns, were compared in terms of their suitability for predicting the course outcome of learners participating in MOOCs. Our Exploratory Data Analysis demonstrates that there is strong correlation between click steam actions and successful learner outcomes. Various Machine Learning algorithms have been applied to enhance the accuracy of classifier models. Simulation results from our investigation have shown that Random Forest achieved viable performance for our prediction problem, obtaining the highest performance of the models tested. Conversely, Linear Discriminant Analysis achieved the lowest relative performance, though represented only a marginal reduction in performance relative to the Random Forest

Effective temperatures and radii of planet-hosting stars from IR photometry

In this paper we present and analyse determinations of effective temperatures of planet-hosting stars using infrared (IR) photometry. One of our goals is the comparison with spectroscopic temperatures to evaluate the presence of systematic effects that could alter the determination of metal abundances. To estimate the stellar temperatures we have followed a new approach based on fitting the observed 2MASS IR photometry with accurately calibrated synthetic photometry. Special care has been put in evaluating all sources of possible errors and incorporating them in the analysis. A comparison of our temperature determinations with spectroscopic temperatures published by different groups reveals the presence of no systematic trends and a scatter compatible with the quoted uncertainties of 0.5-1.3%. This mutual agreement strengthens the results of both the spectroscopic and IR photometry analyses. Comparisons with other photometric temperature calibrations, generally with poorer performances, are also presented. In addition, the method employed of fitting IR photometry naturally yields determinations of the stellar semi-angular diameters, which, when combined with the distances, results in estimations of the stellar radii with remarkable accuracies of ~2-4%. A comparison with the only star in the sample with an empirically determined radius (HD 209458 -- from transit photometry) indicates excellent agreement.Comment: 4 pages, 1 figure, accepted for publication as a letter in A&

C, S, Zn and Cu abundances in planet-harbouring stars

We present a detailed and uniform study of C, S, Zn and Cu abundances in a large set of planet host stars, as well as in a homogeneous comparison sample of solar-type dwarfs with no known planetary-mass companions. Carbon abundances were derived by {EW} measurement of two C I optical lines, while spectral syntheses were performed for S, Zn and Cu. We investigated possible differences in the behaviours of the volatiles C, S and Zn and in the refractory Cu in targets with and without known planets in order to check possible anomalies due to the presence of planets. We found that the abundance distributions in stars with exoplanets are the high [Fe/H] extensions of the trends traced by the comparison sample. All volatile elements we studied show [X/Fe] trends decreasing with [Fe/H] in the metallicity range -0.8<[Fe/H]<0.5, with significantly negative slopes of -0.39+-0.04 and -0.35+-0.04 for C and S, respectively. A comparison of our abundances with those available in the literature shows good agreement in most cases.Comment: 28 pages, 13 figures, accepted for publication in A&

‘Context is King’ when Interpreting Match Physical Performances

‘I was blind, now I can see’. Thus, is it time to retire the ‘blind’ distance covered model that’s been used in football for decades and replace it with an integrated model that contextualises physical efforts during matches

Shoot growth of woody trees and shrubs is predicted by maximum plant height and associated traits

1. The rate of elongation and thickening of individual branches (shoots) varies across plant species. This variation is important for the outcome of competition and other plant-plant interactions. Here we compared rates of shoot growth across 44 species from tropical, warm temperate, and cool temperate forests of eastern Australia.2. Shoot growth rate was found to correlate with a suite of traits including the potential height of the species, xylem-specific conductivity, leaf size, leaf area per xylem cross-section, twig diameter (at 40 cm length), wood density and modulus of elasticity.3. Within this suite of traits, maximum plant height was the clearest correlate of growth rates, explaining 50 to 67% of the variation in growth overall (p p 4. Growth rates were not strongly correlated with leaf nitrogen or leaf mass per unit leaf area.5. Correlations between growth and maximum height arose both across latitude (47%, p p p p < 0.0001), reflecting intrinsic differences across species and sites