131,224 research outputs found
The JCMT BISTRO Survey: Multi-wavelength polarimetry of bright regions in NGC 2071 in the far-infrared/submillimetre range, with POL-2 and HAWC+
Polarized dust emission is a key tracer in the study of interstellar medium and of star formation. The observed polarization, however, is a product of magnetic field structure, dust grain properties and grain alignment efficiency, as well as their variations in the line of sight, making it difficult to interpret polarization unambiguously. The comparison of polarimetry at multiple wavelengths is a possible way of mitigating this problem. We use data from HAWC+/SOFIA and from SCUBA-2/POL-2 (from the BISTRO survey) to analyse the NGC 2071 molecular cloud at 154, 214 and 850 μm. The polarization angle changes significantly with wavelength over part of NGC 2071, suggesting a change in magnetic field morphology on the line of sight as each wavelength best traces different dust populations. Other possible explanations are the existence of more than one polarization mechanism in the cloud or scattering from very large grains. The observed change of polarization fraction with wavelength, and the 214-to-154 μm polarization ratio in particular, are difficult to reproduce with current dust models under the assumption of uniform alignment efficiency. We also show that the standard procedure of using monochromatic intensity as a proxy for column density may produce spurious results at HAWC+ wavelengths. Using both long-wavelength (POL-2, 850 μm) and short-wavelength (HAWC+, ≲200μm) polarimetry is key in obtaining these results. This study clearly shows the importance of multi-wavelength polarimetry at submillimeter bands to understand the dust properties of molecular clouds and the relationship between magnetic field and star formation
Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting
Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statistical models that are often too costly, both computationally and budgetary, or are not applied to downstream applications. Therefore, approaches that use Machine Learning algorithms in conjunction with time-series data are being explored as an alternative to overcome these drawbacks. To this end, this study presents a comparative analysis using simplified rainfall estimation models based on conventional Machine Learning algorithms and Deep Learning architectures that are efficient for these downstream applications. Models based on LSTM, Stacked-LSTM, Bidirectional-LSTM Networks, XGBoost, and an ensemble of Gradient Boosting Regressor, Linear Support Vector Regression, and an Extra-trees Regressor were compared in the task of forecasting hourly rainfall volumes using time-series data. Climate data from 2000 to 2020 from five major cities in the United Kingdom were used. The evaluation metrics of Loss, Root Mean Squared Error, Mean Absolute Error, and Root Mean Squared Logarithmic Error were used to evaluate the models' performance. Results show that a Bidirectional-LSTM Network can be used as a rainfall forecast model with comparable performance to Stacked-LSTM Networks. Among all the models tested, the Stacked-LSTM Network with two hidden layers and the Bidirectional-LSTM Network performed best. This suggests that models based on LSTM-Networks with fewer hidden layers perform better for this approach; denoting its ability to be applied as an approach for budget-wise rainfall forecast applications
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Abnormal returns and stock price movements: some evidence from developed and emerging markets
© Infopro Digital Risk (IP) Limited (2022). All rights reserved. The published version of an article which has been published in final form at [DOI URL TBC] will be made available 12 months after publication, date to be confirmed. An electronic version of the preprint may be downloaded:
· from Brunel University London, Department of Economics and Finance working paper no. 2022: https://www.brunel.ac.uk/economics-and-finance/research/pdf/2022-Dec-GMC-Abnormal-returns-in-stock-markets1.pdf · from the SSRN website: www.SSRN.com · from the RePEc website: www.RePEc.org · from the CESifo website: https://www.cesifo.org/DocDL/cesifo1_wp8783.pdf (ISSN 2364-1428 - electronic version).CESifo Working Paper Series No 8783https://www.cesifo.org/DocDL/cesifo1_wp8783.pdfhttps://www.brunel.ac.uk/economics-and-finance/research/pdf/2022-Dec-GMC-Abnormal-returns-in-stock-markets1.pd
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Identifying Latent Variables in Dynamic Bayesian Networks with Bootstrapping Applied to Type 2 Diabetes Complication Prediction
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Metabolic adaptation drives arsenic trioxide resistance in acute promyelocytic leukemia.
Acquired genetic mutations can confer resistance to arsenic trioxide (ATO) in the treatment of acute promyelocytic leukemia (APL). However, such resistance-conferring mutations are rare and do not explain most disease recurrence seen in the clinic. We have generated stable ATO-resistant promyelocytic cell lines that are also less sensitive to ATRA and the combination of ATO and ATRA compared to the sensitive cell line. Characterization of these in-house generated resistant cell lines showed significant differences in immunophenotype, drug transporter expression, anti-apoptotic protein dependence, and PML-RARA mutation. Gene expression profiling revealed prominent dysregulation of the cellular metabolic pathways in these ATO resistant APL cell lines. Glycolytic inhibition by 2-DG was sufficient and comparable to the standard of care (ATO) in targeting the sensitive APL cell line. 2-DG was also effective in the in vivo transplantable APL mouse model; however, it did not affect the ATO resistant cell lines. In contrast, the resistant cell lines were significantly affected by compounds targeting the mitochondrial respiration when combined with ATO, irrespective of the ATO resistance-conferring genetic mutations or the pattern of their anti-apoptotic protein dependency. Our data demonstrate that the addition of mitocans in combination with ATO can overcome ATO resistance. We further show that this combination has the potential in the treatment of non-M3 AML and relapsed APL. The translation of this approach in the clinic needs to be explored further
Really proper dangerous one: Aboriginal responses to the first wave of COVID-19 in the Kimberley
https://researchonline.nd.edu.au/nulungu_reports/1002/thumbnail.jp
Journal and disciplinary variations in academic open peer review anonymity, outcomes, and length
This is an accepted manuscript of an article published by SAGE in Journal of Librarianship and Information Science on 01/03/2022, available online: https://doi.org/10.1177/09610006221079345
The accepted version of the publication may differ from the final published version.Understanding more about variations in peer review is essential to ensure that editors and
reviewers harness it effectively in existing and new formats, including for mega-journals and
when published online. This article analyses open reviews from the MDPI suite of journals to
identify commonalities and differencesfrom a simplistic quantitative perspective, focusing on
reviewer anonymity, review length and review outcomes. The sample contained 45,385 first
round open reviews from published standard journal articles in 288 MDPI journals classified
into one or more Scopus disciplinary areas (Health Sciences; Life Sciences; Physical Sciences;
Social Sciences). The eight main findings include substantial differences between journals and
disciplines in review lengths, reviewer anonymity, review outcomes, and the use of
attachments. In particular, Physical Sciences journal reviews tended to be stricter and were
more likely to be anonymous. Life Sciences and Social Sciences reviews were the longest
overall. Signed reviews tend to be 15% longer (perhaps to be more careful or polite) but gave
similar decisions to anonymous reviews. Finally, reviews with major revision outcomes
tended to be 68% longer than reviews with for minor revision outcomes, except in a few
journals. In conclusion, signing reviews does not seem to threaten the validity of peer review
outcomes and authors, editors and reviewers of multidisciplinary articles should be aware of
substantial field differences in what constitutes an appropriate review
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