Cultural Values and Gender Equity on National Olympic Committee Boards

International Journal of Exercise Science 10(6): 857-874, 2017. Women are under-represented in leadership positions throughout sport, and researchers have largely explored organizational, group, and individual antecedents of this phenomenon. The purpose of the current study was to expand on this understanding by investigating the influence of a country’s cultural values on the representation of women on National Olympic Committees. Drawing from Hofstede’s cultural dimensions theory, the authors included five cultural values: power distance, uncertainty avoidance, individualism-collectivism, masculinity-femininity, and long-term orientation. Results indicate that women constituted only 19.7 percent of the positions on the boards. Regression analysis, controlling for size of the Olympics program in the country, indicate that cultural values accounted for 41.8 percent of the variance in board gender diversity. Countries with lower power distance, lower masculinity, and lower uncertainty avoidance all had a higher proportion of women on the board. The authors discuss practical and theoretical implication

Simultaneous measurement and reconstruction tailoring for quantitative phase imaging

We propose simultaneous measurement and reconstruction tailoring (SMaRT) for quantitative phase imaging; it is a joint optimization approach to inverse problems wherein minimizing the expected end-to-end error yields optimal design parameters for both the measurement and reconstruction processes. Using simulated and experimentally-collected data for a specific scenario, we demonstrate that optimizing the design of the two processes together reduces phase reconstruction error over past techniques that consider these two design problems separately. Our results suggest at times surprising design principles, and our approach can potentially inspire improved solution methods for other inverse problems in optics as well as the natural sciences.Singapore-MIT Alliance. BioSystems and Micromechanics (BioSyM) Inter-Disciplinary Research GroupSingapore. National Research Foundatio

Invasion of the central nervous system by Cryptococcus neoformans requires a secreted fungal metalloprotease.

UnlabelledCryptococcus spp. cause life-threatening fungal infection of the central nervous system (CNS), predominantly in patients with a compromised immune system. Why Cryptococcus neoformans has this remarkable tropism for the CNS is not clear. Recent research on cerebral pathogenesis of C. neoformans revealed a predominantly transcellular migration of cryptococci across the brain endothelium; however, the identities of key fungal virulence factors that function specifically to invade the CNS remain unresolved. Here we found that a novel, secreted metalloprotease (Mpr1) that we identified in the extracellular proteome of C. neoformans (CnMpr1) is required for establishing fungal disease in the CNS. Mpr1 belongs to a poorly characterized M36 class of fungalysins that are expressed in only some fungal species. A strain of C. neoformans lacking the gene encoding Mpr1 (mpr1Δ) failed to breach the endothelium in an in vitro model of the human blood-brain barrier (BBB). A mammalian host infected with the mpr1Δ null strain demonstrated significant improvement in survival due to a reduced brain fungal burden and lacked the brain pathology commonly associated with cryptococcal disease. The in vivo studies further indicate that Mpr1 is not required for fungal dissemination and Mpr1 likely targets the brain endothelium specifically. Remarkably, the sole expression of CnMPR1 in Saccharomyces cerevisiae resulted in a robust migration of yeast cells across the brain endothelium, demonstrating Mpr1's specific activity in breaching the BBB and suggesting that Mpr1 may function independently of the hyaluronic acid-CD44 pathway. This distinct role for Mpr1 may develop into innovative treatment options and facilitate a brain-specific drug delivery platform.ImportanceCryptococcus neoformans is a medically relevant fungal pathogen causing significant morbidity and mortality, particularly in immunocompromised individuals. An intriguing feature is its strong neurotropism, and consequently the hallmark of cryptococcal disease is a brain infection, cryptococcal meningoencephalitis. For C. neoformans to penetrate the central nervous system (CNS), it first breaches the blood-brain barrier via a transcellular pathway; however, the identities of fungal factors required for this transmigration remain largely unknown. In an effort to identify extracellular fungal proteins that could mediate interactions with the brain endothelium, we undertook a proteomic analysis of the extracellular proteome and identified a secreted metalloprotease (Mpr1) belonging to the M36 class of fungalysins. Here we found that Mpr1 promotes migration of C. neoformans across the brain endothelium and into the CNS by facilitating attachment of cryptococci to the endothelium surface, thus underscoring the critical role of M36 proteases in fungal pathogenesis

Accelerating L 1 -penalized expectation maximization algorithm for latent variable selection in multidimensional two-parameter logistic models

© 2023 Shang et al. 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/One of the main concerns in multidimensional item response theory (MIRT) is to detect the relationship between observed items and latent traits, which is typically addressed by the exploratory analysis and factor rotation techniques. Recently, an EM-based L1-penalized log-likelihood method (EML1) is proposed as a vital alternative to factor rotation. Based on the observed test response data, EML1 can yield a sparse and interpretable estimate of the loading matrix. However, EML1 suffers from high computational burden. In this paper, we consider the coordinate descent algorithm to optimize a new weighted log-likelihood, and consequently propose an improved EML1 (IEML1) which is more than 30 times faster than EML1. The performance of IEML1 is evaluated through simulation studies and an application on a real data set related to the Eysenck Personality Questionnaire is used to demonstrate our methodologies.Peer reviewe

Standing on a glass cliff? A case study of FIFA’s gender initiatives

Rationale/Purpose: The Fédération Internationale de Football Association (FIFA) has taken gender equalityFootnote1 initiatives by inaugurating a female leadership development programme (FLDP)Footnote2 as well as appointing womenFootnote3 in leadership positions. As such, we draw from a new theoretical notion, glass cliff to explore why FIFA started FLDP and assigned women to leadership ranks. Methodology/Approach: Semi-structured interviews were conducted with 16 women who accomplished FLDP. Findings and Implications: There was no direct evidence to support the glass cliff phenomenon in FIFA’s gender-related actions. Although the results are inconclusive, some evidence showed that FIFA’s gender initiatives emerged during their reforming processes in 2015. Our findings demonstrated that FIFA’s historic appointments of women to leadership positions after the corruption and the continuance of FLDP are concerned with the glass cliff effect, as women have never been sought as leaders in football governance. We addressed practical and theoretical implications and suggestions for future research

Approaching Conformality with Ten Flavors

We present first results for lattice simulations, on a single volume, of the low-lying spectrum of an SU(3) Yang-Mills gauge theory with ten light fermions in the fundamental representation. Fits to the fermion mass dependence of various observables are found to be globally consistent with the hypothesis that this theory is within or just outside the strongly-coupled edge of the conformal window, with mass anomalous dimension consistent with 1 over the range of scales simulated. We stress that we cannot rule out the possibility of spontaneous chiral-symmetry breaking at scales well below our infrared cutoff. We discuss important systematic effects, including finite-volume corrections, and consider directions for future improvement.Comment: 7 pages, 3 figures. Submitted to Physical Review Letters. v2: corrected global fits. v3: corrected estimation of confidence interval

Prediction of residual stresses in girth welded pipes using an artificial neural network approach

Management of operating nuclear power plants greatly relies on structural integrity assessments for safety critical pressure vessels and piping components. In the present work, residual stress profiles of girth welded austenitic stainless steel pipes are characterised using an artificial neural network approach. The network has been trained using residual stress data acquired from experimental measurements found in literature. The neural network predictions are validated using experimental measurements undertaken using neutron diffraction and the contour method. The approach can be used to predict through-wall distribution of residual stresses over a wide range of pipe geometries and welding parameters thereby finding potential applications in structural integrity assessment of austenitic stainless steel girth welds