Women’s visibility in academic seminars: Women ask fewer questions than men

The attrition of women in academic careers is a major concern, particularly in Science, Technology, Engineering, and Mathematics subjects. One factor that can contribute to the attrition is the lack of visible role models for women in academia. At early career stages, the behaviour of the local community may play a formative role in identifying ingroup role models, shaping women’s impressions of whether or not they can be successful in academia. One common and formative setting to observe role models is the local departmental academic seminar, talk, or presentation. We thus quantified women’s visibility through the question-asking behaviour of academics at seminars using observations and an online survey. From the survey responses of over 600 academics in 20 countries, we found that women reported asking fewer questions after seminars compared to men. This impression was supported by observational data from almost 250 seminars in 10 countries: women audience members asked absolutely and proportionally fewer questions than male audience members. When asked why they did not ask questions when they wanted to, women, more than men, endorsed internal factors (e.g., not working up the nerve). However, our observations suggest that structural factors might also play a role; when a man was the first to ask a question, or there were fewer questions, women asked proportionally fewer questions. Attempts to counteract the latter effect by manipulating the time for questions (in an effort to provoke more questions) in two departments were unsuccessful. We propose alternative recommendations for creating an environment that makes everyone feel more comfortable to ask questions, thus promoting equal visibility for women and members of other less visible groups

Women's visibility in academic seminars: Women ask fewer questions than men

The attrition of women in academic careers is a major concern, particularly in Science, Technology, Engineering, and Mathematics subjects. One factor that can contribute to the attrition is the lack of visible role models for women in academia. At early career stages, the behaviour of the local community may play a formative role in identifying ingroup role models, shaping women's impressions of whether or not they can be successful in academia. One common and formative setting to observe role models is the local departmental academic seminar, talk, or presentation. We thus quantified women's visibility through the question-asking behaviour of academics at seminars using observations and an online survey. From the survey responses of over 600 academics in 20 countries, we found that women reported asking fewer questions after seminars compared to men. This impression was supported by observational data from almost 250 seminars in 10 countries: women audience members asked absolutely and proportionally fewer questions than male audience members. When asked why they did not ask questions when they wanted to, women, more than men, endorsed internal factors (e.g., not working up the nerve). However, our observations suggest that structural factors might also play a role; when a man was the first to ask a question, or there were fewer questions, women asked proportionally fewer questions. Attempts to counteract the latter effect by manipulating the time for questions (in an effort to provoke more questions) in two departments were unsuccessful. We propose alternative recommendations for creating an environment that makes everyone feel more comfortable to ask questions, thus promoting equal visibility for women and members of other less visible groups

Withaferin A activates TRIM16 for its anti-cancer activity in melanoma.

Although selective BRAF inhibitors and novel immunotherapies have improved short-term treatment responses in metastatic melanoma patients, acquired resistance to these therapeutics still represent a major challenge in clinical practice. In this study, we evaluated the efficacy of Withaferin A (WFA), derived from the medicinal plant Withania Somnifera, as a novel therapeutic agent for the treatment of melanoma. WFA showed selective toxicity to melanoma cells compared to non-malignant cells. WFA induced apoptosis, significantly reduced cell proliferation and inhibited migration of melanoma cells. We identified that repression of the tumour suppressor TRIM16 diminished WFA cytotoxicity, suggesting that TRIM16 was in part responsible for the cytotoxic effects of WFA in melanoma cells. Together our data indicates that WFA has potent cytopathic effects on melanoma cells through TRIM16, suggesting a potential therapeutic application of WFA in the disease

Criterion-Based Grading, Agile Goal Setting, and Course (Un)Completion Strategies

Peer reviewe

External sources of clean technology: evidence from the clean development mechanism

New technology is fundamental to sustainable development. However, inventors from industrialized countries often refuse technology transfer because they worry about reverse-engineering. When can clean technology transfer succeed? We develop a formal model of the political economy of North–South technology transfer. According to the model, technology transfer is possible if (1) the technology in focus has limited global commercial potential or (2) the host developing country does not have the capacity to absorb new technologies for commercial use. If both conditions fail, inventors from industrialized countries worry about the adverse competitiveness effects of reverse-engineering, so technology transfer fails. Data analysis of technology transfer in 4,894 projects implemented under the Kyoto Protocol’s Clean Development Mechanism during the 2004–2010 period provides evidence in support of the model

Toward the Measure of Credibility of Hospital Administrative Datasets in the Context of DRG Classification

Poor quality of coded clinical data in hospital administrative databases may negatively affect decision making, clinical and health care services research and billing. In this paper, we assessed the level of credibility of a nationwide Portuguese inpatient database concerning the codification of pneumonia, with a special emphasis on identifying suspicious cases of upcoding affecting proper APR-DRG (All-Patient Refined Diagnosis-Related Groups) classification and hospital funding. Using data on pneumonia-related hospitalizations from 2015, we compared six hospitals with similar complexity regarding the frequency of all pneumonia-related diagnosis codes in order to identify codes that were significantly overreported in a given facility relatively to its peers. To verify whether the discrepant codes could be related to upcoding, we built Support Vector Machine (SVM) models to simulate the APR-DRG system and assess its response to each discrepant code. Findings demonstrate that hospitals significantly differed in coding six pneumonia conditions, with five of them playing a major role in increasing APR-DRG complexity, being thus suspicious cases of upcoding. However, those comprised a minority of cases and the overall credibility concerning upcoding of pneumonia was above 99% for all evaluated hospitals. Our findings can not only be relevant for planning future audit processes by signalizing errors impacting APR-DRG classification, but also for discussing credibility of administrative data, keeping in mind their impact on hospital financing. Hence, the main contribution of this paper is a reproducible method that can be employed to monitor the credibility and to promote data quality management in administrative databases

The Effects of Serotonin Receptor Antagonists on Contraction and Relaxation Responses Induced by Electrical Stimulation in the Rat Small Intestine

Background: The main source of 5-HT in body is in enterchromafin cells of intestine, different studies mentioned different roles for endogenous 5-HT and receptors involved and it is not clearified the mechanism of action of endogenous 5-HT. Objectives: To study the role of endogenous 5-HT on modulation of contraction and relaxation responses induced by electrical field stimulation (EFS) in different regions of the rat intestine. Materials and Methods: Segments taken from the rat duodenum, jejunum, mid and terminal ileum were vertically mounted, connected to a transducer and exposed to EFS with different frequencies in the absence and presence of various inhibitors of enteric mediators i. e. specific 5-HT receptor antagonists. Results: EFS-induced responses were sensitive to TTX and partly to atropine, indicating a major neuronal involvement and a cholinergic system. Pre-treatment with WAY100635 (a 5-HT1A receptor antagonist) and granisetron up to 10.0 µM, GR113808 (a 5-HT4 receptor antagonist), methysergide and ritanserin up to 1.0 µM, failed to modify responses to EFS inall examined tissues. In the presence of SB258585 1.0 µM (a 5-HT6 receptor antagonist) there was a trend to enhance contraction in the proximal part of the intestine and reduce contraction in the distal part. Pre-treatment with SB269970A 1.0 µM (5-HT7 receptor antagonist) induced a greater contractile response to EFS at 0.4 Hz only in the duodenum. Conclusions: The application of 5-HT1A, 5-HT2, 5-HT3, 5-HT4, 5-HT6 and 5-HT7 receptor antagonists, applied at concentrations lower than 1.0 µM did not modify the EFS-induced contraction and relaxation responses, whichsuggests the unlikely involvement of endogenous 5-HT in mediating responses to EFS in the described test conditions. Keywords: Electric Stimulation Therapy; Serotonin 5-HT1 Receptor Antagonists; Intestine, Smal

Transit Timing and Duration Variations for the Discovery and Characterization of Exoplanets

Transiting exoplanets in multi-planet systems have non-Keplerian orbits which can cause the times and durations of transits to vary. The theory and observations of transit timing variations (TTV) and transit duration variations (TDV) are reviewed. Since the last review, the Kepler spacecraft has detected several hundred perturbed planets. In a few cases, these data have been used to discover additional planets, similar to the historical discovery of Neptune in our own Solar System. However, the more impactful aspect of TTV and TDV studies has been characterization of planetary systems in which multiple planets transit. After addressing the equations of motion and parameter scalings, the main dynamical mechanisms for TTV and TDV are described, with citations to the observational literature for real examples. We describe parameter constraints, particularly the origin of the mass/eccentricity degeneracy and how it is overcome by the high-frequency component of the signal. On the observational side, derivation of timing precision and introduction to the timing diagram are given. Science results are reviewed, with an emphasis on mass measurements of transiting sub-Neptunes and super-Earths, from which bulk compositions may be inferred.Comment: Revised version. Invited review submitted to 'Handbook of Exoplanets,' Exoplanet Discovery Methods section, Springer Reference Works, Juan Antonio Belmonte and Hans Deeg, Eds. TeX and figures may be found at https://github.com/ericagol/TTV_revie

Physics of Neutron Star Crusts

The physics of neutron star crusts is vast, involving many different research fields, from nuclear and condensed matter physics to general relativity. This review summarizes the progress, which has been achieved over the last few years, in modeling neutron star crusts, both at the microscopic and macroscopic levels. The confrontation of these theoretical models with observations is also briefly discussed.Comment: 182 pages, published version available at <http://www.livingreviews.org/lrr-2008-10

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur