127 research outputs found
Characteristics of magnetoacoustic sausage modes
Aims: We perform an advanced study of the fast magnetoacoustic sausage oscillations of coronal loops in the context of MHD coronal seismology to establish the dependence of the sausage mode period and cut-off wavenumber on the plasma- of the loop-filling plasma. A parametric study of the ratios for different harmonics of the mode is also carried out.
Methods: Full magnetohydrodynamic numerical simulations were performed using Lare2d, simulating hot, dense loops in a magnetic slab environment. The symmetric Epstein profile and a simple step-function profile were both used to model the density structure of the simulated loops. Analytical expressions for the cut-off wavenumber and the harmonic ratio between the second longitudinal harmonic and the fundamental were also examined.
Results: It was established that the period of the global sausage mode is only very weakly dependent on the value of the plasma- inside a coronal loop, which justifies the application of this model to hot flaring loops. The cut-off wavenumber kc for the global mode was found to be dependent on both internal and external values of the plasma-, again only weakly. By far the most important factor in this case was the value of the density contrast ratio between the loop and the surroundings. Finally, the deviation of the harmonic ratio P1/2P2 from the ideal non-dispersive case was shown to be considerable at low k, again strongly dependent on plasma density. Quantifying the behaviour of the cut-off wavenumber and the harmonic ratio has significant applications to the field of coronal seismology
How do undergraduates read mathematical texts? An eye-movement study
This paper reports on an eye-movement study of undergraduate mathematical reading behaviours.
The eye movements of 38 undergraduate students were recorded as they read a multi-page textbook
section on graph theory; participants then took a short comprehension test. This abstract reports
basic results showing that neither reading time nor processing effort – measured via mean fixation
durations – predicted comprehension test performance: students who read for longer or tried harder
did not necessarily learn more. The conference report will include more detailed analysis of
participants’ eye movements: it will explore their relative attention to different parts of the text and the
extent to which they shift their attention back and forth during learning, and will analyse the extent to
which these behaviours differ across more and less effective learners
Senior Recital: Gage Fisher, trombone
This recital is presented in partial fulfillment of requirements for the degree Bachelor of Music in Performance. Mr. Fisher studies trombone with Wes Funderburk and Tom Gibson.https://digitalcommons.kennesaw.edu/musicprograms/2205/thumbnail.jp
A blueprint of state-of-the-art techniques for detecting quasi-periodic pulsations in solar and stellar flares
Quasi-periodic pulsations (QPPs) appear to be a common feature observed in the light curves of both solar and stellar ares. However, their quasi-periodic nature, along with the facts that they can be small in amplitude and short-lived, make QPPs difficult to unequivocally detect. In this paper, we test the strengths and limitations of state-of-the-art methods for detecting QPPs using a series of hare-and-hounds exercises. The hare simulated a set of ares, both with and without QPPs of a variety of forms, while the hounds attempted to detect QPPs in blind tests. We use the results of these exercises to create a blueprint for anyone who wishes to detect QPPs in real solar and stellar data. We present eight, clear recommendations to be kept in mind for future QPP detections, with the plethora of solar and stellar are data from new and future satellites. These recommendations address the key pitfalls in QPP detection, including detrending, trimming data, accounting for coloured noise, detecting stationary-period QPPs, detecting QPP with non-stationary periods, and ensuring detections are robust and false detections are minimized. We find that QPPs can be detected reliably and robustly by a variety of methods, which are clearly identied and described, if the appropriate care and due diligence is taken
Chicken astrovirus (CAstV) molecular studies reveal evidence of multiple past recombination events in sequences originated from clinical samples of white chick syndrome (WCS) in Western Canada
In this study, we aimed to molecularly characterize 14 whole genome sequences of chicken
astrovirus (CAstV) isolated from samples obtained from white chick syndrome (WCS) outbreaks
in Western Canada during the period of 2014–2019. Genome sequence comparisons showed all
these sequences correspond to the novel Biv group from which no confirmed representatives were
published in GenBank. Molecular recombination analyses using recombination detection software
(i.e., RDP5 and SimPlot) and phylogenetic analyses suggest multiple past recombination events in
open reading frame (ORF)1a, ORF1b, and ORF2. Our findings suggest that recombination events
and the accumulation of point mutations may have contributed to the substantial genetic variation
observed in CAstV and evidenced by the current seven antigenic sub-clusters hitherto described.
This is the first paper that describes recombination events in CAstV following analysis of complete
CAstV sequences originated in Canada
Environmental risk factors for respiratory infection and wheeze in young children:A multicentre birth cohort study
introduction: Respiratory infections and wheeze have a considerable impact on the health of young children and consume significant healthcare resources. We aimed to evaluate the effect of environmental factors on respiratory infections and symptoms in early childhood.Methods: Environmental risk factors including: daycare attendance; breastfeeding; siblings; damp within the home; environmental tobacco smoke (ETS); child's bedroom flooring; animal exposure; road traffic density around child's home; and solid fuel pollution within home were assessed in children recruited to the GO-CHILD multicentre prospective birth cohort study. Follow-up information on respiratory infections (bronchiolitis, pneumonia, otitis media and cold or flu), wheeze and cough symptoms, healthcare utilisation and medication prescription was collected by postal questionnaires at 12 and 24 months. Log binomial and ordered logistic regression models were fitted to the data.Results: Follow-up was obtained on 1344 children. Daycare was associated with increased odds of pneumonia (odds ratio [OR] = 2.39, 95% confidence interval [CI]: 1.04-5.49), bronchiolitis (OR = 1.40, 1.02-1.90), otitis media (OR = 1.68, 1.32-2.14) and emergency department attendance for wheeze (RR = 1.81, 1.17-2.80). Breastfeeding beyond 6 months was associated with a reduced odds of bronchiolitis (OR = 0.55, 0.39-0.77) and otitis media (OR = 0.75, 0.59-0.99). Siblings at home was associated with an increased odds of bronchiolitis (OR = 1.65, 1.18-2.32) and risk of reliever inhaler prescription (RR = 1.37, 1.02-1.85). Visible damp was associated with an increased odds of wheeze (OR = 1.85, 1.11-3.19), and risk of reliever inhaler (RR = 1.73, 1.04-2.89) and inhaled corticosteroid prescription (RR = 2.61, 1.03-6.59). ETS exposure was associated with an increased odds of primary care attendance for cough or wheeze (OR = 1.52, 1.11-2.08). Dense traffic around the child's home was associated with an increased odds of bronchiolitis (OR = 1.32, 1.08-2.29).Conclusion: Environmental factors likely influence the wide variation in infection frequency and symptoms observed in early childhood. Larger population studies are necessary to further inform and guide public health policy to decrease the burden of respiratory infections and wheeze in young children.</p
Machine Learning at Microsoft with ML .NET
Machine Learning is transitioning from an art and science into a technology
available to every developer. In the near future, every application on every
platform will incorporate trained models to encode data-based decisions that
would be impossible for developers to author. This presents a significant
engineering challenge, since currently data science and modeling are largely
decoupled from standard software development processes. This separation makes
incorporating machine learning capabilities inside applications unnecessarily
costly and difficult, and furthermore discourage developers from embracing ML
in first place. In this paper we present ML .NET, a framework developed at
Microsoft over the last decade in response to the challenge of making it easy
to ship machine learning models in large software applications. We present its
architecture, and illuminate the application demands that shaped it.
Specifically, we introduce DataView, the core data abstraction of ML .NET which
allows it to capture full predictive pipelines efficiently and consistently
across training and inference lifecycles. We close the paper with a
surprisingly favorable performance study of ML .NET compared to more recent
entrants, and a discussion of some lessons learned
Sheila, Take a Bow
Professor Sheila Whiteley passed away on 6th of June, 2015. Sheila’s ground-breaking achievements in popular culture and gender studies, alongside her bright personal triumphs are celebrated by numerous obituaries from national and international media. Here, we present the tributes of Sheila’s students, colleagues and friends.Sheila Whiteley nous a quittés le 6 juin 2015. Ses recherches pionnières sur la culture populaire et le genre, en plus de ses grands succès personnels, furent célébrés dans de nombreux médias internationaux. Nous vous présentons ici une série d’hommages de ses étudiants, collègues et amis
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