“Their Image of Me”: A Phenomenological Study of Professional Dress Choices of Female Professors

In recent years, scholarly attention to professional dress as a form of nonverbal communication has faded into the background. However, I believe professional dress is an important area of study, considering the changing conditions in the world of work. Therefore, I decided to conduct this phenomenological study of the dress choices of female professors at a small, liberal arts college to discover what professional dress did for them internally and professionally. The analysis of the data suggests that these women try to use dress to represent themselves as who they are internally, without losing sight of their image as a professor, academic, and cultural member. Dress, for them, is a means of controlling and shaping who they view themselves to be into an appropriate external image of who they must be

A data-based stability-preserving model order reduction method for hyperbolic partial differential equations

This paper proposes a data-based approach for model order reduction that preserves incremental stability properties. Existing data-based approaches do typically not preserve such incremental system properties, especially for nonlinear systems. As a result, instability of the constructed model commonly occurs for inputs outside the training set, which seriously limits the usefulness of such models. Therefore, we propose to construct incrementally stable or incrementally ℓ2-gain stable reduced-order nonlinear models to ensure robustness for a broad class of (bounded) input signals. Hereto, nonlinear discrete-time state-space equations are fitted to input-state-output data, obtained by simulations with the original model. We conjecture that certain classes of hyperbolic partial differential equations enjoy such incremental stability properties. Given the fact that complexity reduction in such PDE models is desirable, we employ the developed data-based reduction method to the discretized version of the hyperbolic equations thereby preserving the incremental stability features of the original system. In particular, this method is applied to a linear advection equation, for which stability properties are proved analytically. Finally, simulation results show the successful application of the method to the nonlinear Burgers’ equation.</p

A Stitch in Time Saves Nine: Nexus between Critical Delay Factors, Leadership Self-Efficacy, and Transnational Mega Construction Project Success

Delay factors are frequent in the construction industry globally, resulting in significant overruns in project cost and time. In context, megaprojects can be more prone to critical delays, hence, demanding a high degree of self-confident leadership. Despite the continuous scholarly attempts to examine mega construction project success, the underlying role of critical delay factors and leadership self-efficacy has been largely overlooked. Hence, to address these rarely examined linkages, the present study empirically explored the effects of critical delay factors (CDFs) on transnational mega construction project (TMCP) success with the moderating influence of leadership self-efficacy (LSE). Based on a study sample (N = 211) extracted from the China–Pakistan Economic Corridor, the hypothesized relationships were tested through partial least squares–structural equation modeling. The study included nine critical delay factors and three subdimensions of TMCP success, derived from previous research. The findings revealed a negative relationship between CDFs and TMCP success, as a 1% increase in CDFs triggered a 28.8% negative change in TMCP success. A positive moderating effect of LSE on the relationship between CDFs and TMCP success was also empirically supported, as 1% increase in LSE resulted in 18.4% positive change in TMCP success. The present study bridges the fragmented literature on critical delay factors in the global construction industry, megaproject success, and project leadership, by providing the first empirical evidence linking these potential relationships. Moreover, the present study also provides an extension to existing studies to identify the role of CDFs and LSE in impacting multi-faceted success (i.e., management success, ownership success, and investment success) in mega construction projects

A Bayesian analysis of the 27 highest energy cosmic rays detected by the Pierre Auger Observatory

It is possible that ultra-high energy cosmic rays (UHECRs) are generated by active galactic nuclei (AGNs), but there is currently no conclusive evidence for this hypothesis. Several reports of correlations between the arrival directions of UHECRs and the positions of nearby AGNs have been made, the strongest detection coming from a sample of 27 UHECRs detected by the Pierre Auger Observatory (PAO). However, the PAO results were based on a statistical methodology that not only ignored some relevant information (most obviously the UHECR arrival energies but also some of the information in the arrival directions) but also involved some problematic fine-tuning of the correlation parameters. Here we present a fully Bayesian analysis of the PAO data (collected before 2007 September), which makes use of more of the available information, and find that a fraction F_AGN = 0.15^(+0.10)_(-0.07) of the UHECRs originate from known AGNs in the Veron-Cetty & Veron (VCV) catalogue. The hypothesis that all the UHECRs come from VCV AGNs is ruled out, although there remains a small possibility that the PAO-AGN correlation is coincidental (F_AGN = 0.15 is 200 times as probable as F_AGN = 0.00).Comment: MNRAS, accepted; 8 pages, 7 figure

Dark Matter Disc Enhanced Neutrino Fluxes from the Sun and Earth

As disc galaxies form in a hierarchical cosmology, massive merging satellites are preferentially dragged towards the disc plane. The material accreted from these satellites forms a dark matter disc that contributes 0.25 - 1.5 times the non-rotating halo density at the solar position. Here, we show the importance of the dark disc for indirect dark matter detection in neutrino telescopes. Previous predictions of the neutrino flux from WIMP annihilation in the Earth and the Sun have assumed that Galactic dark matter is spherically distributed with a Gaussian velocity distribution, the standard halo model. Although the dark disc has a local density comparable to the dark halo, its higher phase space density at low velocities greatly enhances capture rates in the Sun and Earth. For typical dark disc properties, the resulting muon flux from the Earth is increased by three orders of magnitude over the SHM, while for the Sun the increase is an order of magnitude. This significantly increases the sensitivity of neutrino telescopes to fix or constrain parameters in WIMP models. The flux from the Earth is extremely sensitive to the detailed properties of the dark disc, while the flux from the Sun is more robust. The enhancement of the muon flux from the dark disc puts the search for WIMP annihilation in the Earth on the same level as the Sun for WIMP masses < 100 GeV.Comment: 7 pages, 4 figures, added a short paragraph to the discussion section, conclusions unchanged, published versio

Development of a robust and convenient dual-reporter high-throughput screening assay for SARS-CoV-2 antiviral drug discovery.

Massive efforts on both vaccine development and antiviral research were launched to combat the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We contributed, amongst others, by the development of a high-throughput screening (HTS) antiviral assay against SARS-CoV-2 using a fully automated, high-containment robot system. Here, we describe the development of this novel, convenient and phenotypic dual-reporter virus-cell-based high-content imaging assay using the A549+hACE2+TMPRSS2_mCherry reporter lung carcinoma cell line and an ancestral SARS-CoV-2_Wuhan_mNeonGreen reporter virus. Briefly, by means of clonal selection, a host cell subclone was selected that (i) efficiently supports replication of the reporter virus with high expression, upon infection, of the NeonGreen fluorescent reporter protein, (ii) that is not affected by virus-induced cytopathogenic effects and, (iii) that expresses a strong fluorescent mCherry signal in the nucleus. The selected clone matched these criteria with an infection rate on average of 75% with limited cell death. The average (R)Z'-factors of the assay plates were all >0.8, which indicates a robust assay suitable for HTS purposes. A selection of reference compounds that inhibits SARS-CoV-2 replication in vitro were used to validate this novel dual-reporter assay and confirms the data reported in the literature. This assay is a convenient and powerful tool for HTS of large compound libraries against SARS-CoV-2

Clinical, epidemiological, and mycological features of patients with candidemia: Experience in two tertiary referral centers in Iran

Background and purpose: Candidemia is a major cause of morbidity and mortality among patients receiving immunosuppressive therapy and those hospitalized with serious underlying diseases. Here, we investigated the epidemiological, clinical, and mycological features of candidemia in Tehran, Iran. Materials and methods: A prospective observational study of all patients diagnosed with candidemia was performed at two referral teaching hospitals in Tehran, Iran, from February to December 2018. Demographic characteristics, underlying diseases, risk factors, clinical symptoms, and laboratory analyses of candidemic patients with positive culture were mined. Candida isolates were molecularly identified by sequencing of the internal transcribed spacer region (ITS1-5.8S-ITS2). The antifungal susceptibility testing for fluconazole, itraconazole, voriconazole, posaconazole, amphotericin B, caspofungin, micafungin, and anidulafungin against the isolates was performed using CLSI broth microdilution reference method (M27-A3). Results: A total of 89 episodes were identified, with an incidence of 2.1 episodes/1000 admissions. The common underling disease were malignancy (46%), renal failure/dialysis (44%), and hypertension (40%). The overall crude mortality was 47%. C. albicans (44%) was the most frequent causative agent, followed by C. glabrata (21%), C. parapsilosis complex (15%), C. tropicalis (11%), and C. lusitaniae (3.5%). All the isolates were susceptible to amphotericin B. The activity of all four azoles was low against non-albicans Candida species, especially C. tropicalis. Conclusion: The increase in non-albicans Candida species with reduced susceptibility to antifungal drugs might be alarming in high-risk patients. Therefore, accurate knowledge of predisposing factors and epidemiological patterns in candidemia are effective steps for managing and decreasing the mortality rate in candidemia.This study has been funded and supported by Tehran University of Medical Sciences, Tehran, Iran (Grant no. 99-2-99-48944).S

Transitions in Metabolic Risk and Longâ Term Cardiovascular Health: Coronary Artery Risk Development in Young Adults (CARDIA) Study

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139081/1/jah31816.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139081/2/jah31816_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139081/3/jah31816-sup-0001-TableS1-FigureS1.pd

Microplastics and nanoplastics in the marine-atmosphere environment

The discovery of atmospheric micro(nano)plastic transport and ocean-atmosphere exchange points to a highly complex marine plastic cycle, with negative implications for human and ecosystem health. Yet, observations are currently limited. In this Perspective, we quantify the processes and fluxes of the marine-atmospheric micro(nano)plastic cycle, with the aim of highlighting the remaining unknowns in atmospheric micro(nano)plastic transport. Between 0.013 and 25 million metric tons per year of micro(nano)plastics are potentially being transported within the marine atmosphere and deposited in the oceans. However, the high uncertainty in these marine-atmospheric fluxes is related to data limitations and a lack of study intercomparability. To address the uncertainties and remaining knowledge gaps in the marine-atmospheric micro(nano)plastic cycle, we propose a future global marine-atmospheric micro(nano)plastic observation strategy, incorporating novel sampling methods and the creation of a comparable, harmonized and global data set. Together with long-term observations and intensive investigations, this strategy will help to define the trends in marine-atmospheric pollution and any responses to future policy and management actions. Atmospheric transport of microplastics could be a major source of plastic pollution to the ocean, yet observations currently remain limited. This Perspective quantifies the known budgets of the marine-atmospheric micro(nano)plastic cycle and proposes a future global observation strategy.Peer reviewe

Plasma proteomic signatures of a direct measure of insulin sensitivity in two population cohorts

Aims/hypothesis: The euglycemic hyperinsulinemic clamp (EIC) is a direct measure and the reference-standard in the assessment of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-throughput plasma proteomic profiling in developing signatures correlating with the M-value derived from the EIC. Methods: We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M-value variance explained (R2 82 ). Results: A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M-value R2 85 from 0.237 (95% confidence interval: 0.178-0.303) to 0.456 (0.372-0.536) in RISC. A similar pattern was observed in ULSAM in which the M-value R2 increased from 0.443 (0.360-0.530) to 0.632 (0.569-0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R2 despite differences in baseline cohort characteristics and clamp methodology: RISC to ULSAM: 0.491 (0.433-0.539) for 51 proteins, ULSAM to RISC: 0.369 (0.331-0.416) for 67 proteins. A randomized LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins) which improved R2 92 but to a lesser degree than standard LASSO models: 0.352 (0.266-0.439) within RISC and 0.495 (0.404-0.585) within ULSAM. Differences in R2 93 explained between randomized and standard LASSO were notably reduced in the cross-cohort analyses despite the much smaller number of proteins selected: RISC to ULSAM range 0.444 (0.391-0.497) ULSAM to RISC range 0.348 (0.300-0.396). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomized LASSO. The single most consistently selected protein across all analyses and models was IGFBP2. Conclusions/interpretation: A plasma proteomic signature identified through a standard LASSO approach improves the cross-sectional estimation of the M-value over routine clinical variables. However, a small subset of these proteins identified using stability selection algorithm affords much of this improvement especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin resistant individuals at risk of IR-related adverse health consequences