Experiences of women with ovarian cancer during the COVID-19 pandemic: Examining intolerance of uncertainty and fear of COVID-19 in relation to psychological distress

Purpose: Our research aimed to examine the role of intolerance of uncertainty (IU) in psychological distress (PD) among women with ovarian cancer. Fear of COVID-19 (FCOV) was examined as a mediator, and participant health status and the reopening status of their geographic region were examined as moderators. Design: A cross-sectional quantitative design was employed. Participants: Participants (n ¼ 100) were recruited through various online sources and completed the study via Qualtrics. Methods: Moderated mediation models and post-hoc linear regression analyses were used to determine the role of predictor variables in PD. Results: No significant moderators or mediators were found. Despite a strong correlation between FCOV and IU, both variables explained unique variance in the anxiety and stress models, while FCOV was not significant in the depressive symptoms model. Implications for Providers: Both IU and FCOV should be considered in helping women with ovarian cancer manage their PD during the COVID-19 pandemic

Can massive stars form in low mass clouds?

The conditions required for massive star formation are debated, particularly whether massive stars must form in conjunction with massive clusters. Some authors have advanced the view that stars of any mass (below the total cluster mass) can form in clusters of any mass with some probability (random sampling). Others pointed out that the scatter in the determinations of the most massive star mass for a given cluster mass was consistent with the measurement error, such that the mass of the most massive star was determined by the total cluster mass (optimal sampling). Here we investigate the relation between cluster mass (M\textsubscript{ecl}) and the maximum stellar mass (M\textsubscript{max}) using a suite of SPH simulations. Varying cloud mass and turbulence random seed results in a range of cluster masses which we compare with their respective maximum star masses. We find that more massive clusters will have, on average, higher mass stars with this trend being steeper at lower cluster masses (M\textsubscript{max} \propto M\textsubscript{ecl}^{0.31} for M\textsubscript{ecl}<500M\,_{\odot}) and flattening at higher cluster masses (M\textsubscript{max} \propto M\textsubscript{ecl}^{0.11} for M\textsubscript{ecl}>500M\,_{\odot}). This rules out purely stochastic star formation in our simulations. Significant scatter in the maximum masses with identical initial conditions also rules out the possibility that the relation is purely deterministic (that is that a given cluster mass will result in a specific maximum stellar mass). In conclusion our simulations disagree with both random and optimal sampling of the initial mass function.Comment: Accepted in MNRA

Can massive stars form in low mass clouds?

© 2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The conditions required for massive star formation are debated, particularly whether massive stars must form in conjunction with massive clusters. Some authors have advanced the view that stars of any mass (below the total cluster mass) can form in clusters of any mass with some probability (random sampling). Others pointed out that the scatter in the determinations of the most massive star mass for a given cluster mass was consistent with the measurement error, such that the mass of the most massive star was determined by the total cluster mass (optimal sampling). Here we investigate the relation between cluster mass (M\textsubscript{ecl}) and the maximum stellar mass (M\textsubscript{max}) using a suite of SPH simulations. Varying cloud mass and turbulence random seed results in a range of cluster masses which we compare with their respective maximum star masses. We find that more massive clusters will have, on average, higher mass stars with this trend being steeper at lower cluster masses (M\textsubscript{max} \propto M\textsubscript{ecl}^{0.31} for M\textsubscript{ecl}500M\,_{\odot}). This rules out purely stochastic star formation in our simulations. Significant scatter in the maximum masses with identical initial conditions also rules out the possibility that the relation is purely deterministic (that is that a given cluster mass will result in a specific maximum stellar mass). In conclusion our simulations disagree with both random and optimal sampling of the initial mass function.Peer reviewe

Star Cluster Formation in Clouds with Externally Driven Turbulence

©The Author(s) 2022. Published by Oxford University Press on behalf of Royal Astronomical Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Star clusters are known to be formed in turbulent molecular clouds. How turbulence is driven in molecular clouds and what effect this has on star formation is still unclear. We compare a simulation setup with turbulent driving everywhere in a periodic box with a setup where turbulence is only driven around the outside of the box. We analyse the resulting gas distribution, kinematics, and the population of stars that are formed from the cloud. Both setups successfully produce a turbulent velocity field with a power law structure function, the externally driven cloud has a more central, monolithic, clump, while the fully driven cloud has many smaller, more dispersed, clumps. The star formation follows the cloud morphology producing large clusters, with high star forming efficiency in the externally driven simulations and sparse individual star formation with much lower star formation efficiency in the fully driven case. We conclude that the externally driven method, which resembles a Global Hierarchical Collapse (GHC) scenario, produces star clusters that more closely match with observations.Peer reviewe

Inadequate reporting of research ethics review and informed consent in cluster randomized trials : review of random sample of published trials

Peer reviewedPublisher PD

TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks

We present a framework for specifying, training, evaluating, and deploying machine learning models. Our focus is on simplifying cutting edge machine learning for practitioners in order to bring such technologies into production. Recognizing the fast evolution of the field of deep learning, we make no attempt to capture the design space of all possible model architectures in a domain- specific language (DSL) or similar configuration language. We allow users to write code to define their models, but provide abstractions that guide develop- ers to write models in ways conducive to productionization. We also provide a unifying Estimator interface, making it possible to write downstream infrastructure (e.g. distributed training, hyperparameter tuning) independent of the model implementation. We balance the competing demands for flexibility and simplicity by offering APIs at different levels of abstraction, making common model architectures available out of the box, while providing a library of utilities designed to speed up experimentation with model architectures. To make out of the box models flexible and usable across a wide range of problems, these canned Estimators are parameterized not only over traditional hyperparameters, but also using feature columns, a declarative specification describing how to interpret input data. We discuss our experience in using this framework in re- search and production environments, and show the impact on code health, maintainability, and development speed.Comment: 8 pages, Appeared at KDD 2017, August 13--17, 2017, Halifax, NS, Canad

The Use of Propranolol in the Treatment of Posttraumatic Stress Disorder

This article examines the rising issue of post-traumatic stress disorder (PTSD) and possible treatment options. PTSD is a behavioral disorder resulting from memory formation and association with a traumatic event. A search of the published literature reveals several positive studies and case reports suggesting that propranolol, a beta adrenergic receptor antagonist, may be useful for both treatment and prevention of PTSD. Additionally, current studies are being completed in different population groups to determine the overall effectiveness and mechanism by which propranolol is able to provide relief from certain symptoms common to the disorder. This article discusses the medical evidence and possible treatment role of propranolol for patients suffering from PTSD

Ariel - Volume 8 Number 2

Executive Editor James W. Lockard , Jr. Issue Editor Doug Hiller Business Manager Neeraj K. Kanwal University News Richard J. Perry World News Doug Hiller Opinions Elizabeth A. McGuire Features Patrick P. Sokas Sports Desk Shahab S. Minassian Managing Editor Edward H. Jasper Managing Associate Brenda Peterson Photography Editor Robert D. Lehman, Jr. Graphics Christine M. Kuhnl

Distribution of Metals in the Termite Tumulitermes tumuli (Froggatt): Two Types of Malpighian Tubule Concretion Host Zn and Ca Mutually Exclusively

The aim of this study was to determine specific distribution of metals in the termite Tumulitermes tumuli (Froggatt) and identify specific organs within the termite that host elevated metals and therefore play an important role in the regulation and transfer of these back into the environment. Like other insects, termites bio-accumulate essential metals to reinforce cuticular structures and utilize storage detoxification for other metals including Ca, P, Mg and K. Previously, Mn and Zn have been found concentrated in mandible tips and are associated with increased hardness whereas Ca, P, Mg and K are accumulated in Malpighian tubules. Using high resolution Particle Induced X-Ray Emission (PIXE) mapping of whole termites and Scanning Electron Microscope (SEM) Energy Dispersive X-ray (EDX) spot analysis, localised accumulations of metals in the termite T. tumuli were identified. Tumulitermes tumuli was found to have proportionally high Mn concentrations in mandible tips. Malpighian tubules had significant enrichment of Zn (1.6%), Mg (4.9%), P (6.8%), Ca (2.7%) and K (2.4%). Synchrotron scanning X-ray Fluorescence Microprobe (XFM) mapping demonstrated two different concretion types defined by the mutually exclusive presence of Ca and Zn. In-situ SEM EDX realisation of these concretions is problematic due to the excitation volume caused by operating conditions required to detect minor amounts of Zn in the presence of significant amounts of Na. For this reason, previous researchers have not demonstrated this surprising finding

Examining how changes in provincial policy on vape marketing impacted the distribution of vaping advertisements near secondary schools in London, Ontario

Objectives: On January 1, 2020, the Government of Ontario passed a regulation banning vaping advertisements by retailers, apart from specialty shops. A motivation for this ban was to limit youth exposure to vaping advertisements. The primary goal of this research was to evaluate the impact of this ban on the number and density of vaping advertisements surrounding secondary schools. Additionally, we examined whether the number of vaping advertisements varied by school socio-demographic characteristics. Methods: This study used a pre-post design. Audits were conducted December 2019 (pre-ban) and again January to February 2020 (post-ban), to identify vaping advertisements within 800 m surrounding secondary schools (n = 18) in London, Ontario. Results: Prior to the ban, there were 266 vaping advertisements within 800 m of secondary schools. After the ban, this was reduced to 58, a 78.2% reduction. The mean number of vaping advertisements surrounding schools significantly decreased from 18.1 before the ban to 3.6 after the ban (p \u3c 0.001). A significant positive correlation was found, prior to the ban, between the number of vaping advertisements surrounding schools and school-level residential instability (r = 0.42, p = 0.02). After the ban, no significant correlations were found between the number of vaping advertisements and school socio-demographic characteristics. Conclusion: The provincial ban of vaping advertisements in select retail settings significantly reduced the number of vaping advertisements in the areas surrounding secondary schools in London, Ontario. The ban also reduced socio-demographic inequities in youths’ potential exposure to marketing of vaping products. Continued monitoring of the geographic accessibility and promotion of vaping products is warranted