Language in job advertisements and the reproduction of labor force gender and racial segregation.

Job advertisements (ads) represent the first point of contact between employers and job seekers. By signaling characteristics expected of an ideal candidate, job ads "gatekeep" the labor force and configure its composition. Meanwhile, labor force composition can also shape the wording of job ads.

Electrochemical Restructuring Driven Catalytic Cycle of Bi-Based Heterojunctions for High-Performance Lithium-Sulfur Batteries.

Restructuring is an important phenomenon in catalytic reactions. Conversion-type materials with suitable redox potential may undergo in situ electrochemically driven restructurings and induce highly active catalytic sites in a working lithium-sulfur battery. Herein, driven by the electrochemical conversion reaction of BiVO, a reversible catalytic cycle of Bi/amorphous LiVO (a-LiVO) and BiS/a-LiVO heterojunctions is constructed, which targets the oxidation of LiS and the conversion of polysulfide, respectively.

An investigation into the relationship between community engagement and maternal mental health in Calgary, Alberta using the All Our Families cohort.

Introduction: Existing literature shows that increased community engagement is associated with decreased depressive symptoms. To our knowledge, no existing studies have investigated the relationship between community engagement and adverse mental health among mothers in a Canadian context, nor has this relationship been studied over time. The current study aims to address these gaps by modelling the association between community engagement and anxiety and depression longitudinally using a cohort of prenatal and postnatal mothers living in Calgary, Alberta.

A method for generating synthetic longitudinal health data.

Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative health data would be to share synthetic datasets where the records do not correspond to real individuals, but the patterns and relationships seen in the data are reproduced. This paper assesses the feasibility of generating synthetic administrative health data using a recurrent deep learning model.

The HIV Restriction Factor Profile in the Brain Is Associated with the Clinical Status and Viral Quantities.

HIV-encoded DNA, RNA and proteins persist in the brain despite effective antiretroviral therapy (ART), with undetectable plasma and cerebrospinal fluid viral RNA levels, often in association with neurocognitive impairments. Although the determinants of HIV persistence have garnered attention, the expression and regulation of antiretroviral host restriction factors (RFs) in the brain for HIV and SIV remain unknown. We investigated the transcriptomic profile of antiretroviral RF genes by RNA-sequencing with confirmation by qRT-PCR in the cerebral cortex of people who are uninfected (HIV[-]), those who are HIV-infected without pre-mortem brain disease (HIV[+]), those who are HIV-infected with neurocognitive disorders (HIV[+]/HAND) and those with neurocognitive disorders with encephalitis (HIV[+]/HIVE).

Enhancing the Mechanical Properties of Waterborne Polyurethane Paint by Graphene Oxide for Wood Products.

Water-based polyurethane paint is widely used for wood furniture by virtue of the eco-friendliness, rich gloss, and flexible tailorability of its mechanical properties. However, its low solution (water or alcohol) resistance and poor hardness and wear resistance limit its application. The emerging graphene oxide has a high specific surface area and abundant functional groups with excellent mechanical properties, endowing it with great potential to modify waterborne polyurethane as a nanofiller.

Measuring re-identification risk using a synthetic estimator to enable data sharing.

Background: One common way to share health data for secondary analysis while meeting increasingly strict privacy regulations is to de-identify it. To demonstrate that the risk of re-identification is acceptably low, re-identification risk metrics are used. There is a dearth of good risk estimators modeling the attack scenario where an adversary selects a record from the microdata sample and attempts to match it with individuals in the population.

Low-Rank Plus Sparse Decomposition of fMRI Data With Application to Alzheimer's Disease.

Studying functional brain connectivity plays an important role in understanding how human brain functions and neuropsychological diseases such as autism, attention-deficit hyperactivity disorder, and Alzheimer's disease (AD). Functional magnetic resonance imaging (fMRI) is one of the most popularly used tool to construct functional brain connectivity. However, the presence of noises and outliers in fMRI blood oxygen level dependent (BOLD) signals might lead to unreliable and unstable results in the construction of connectivity matrix.

Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation.

Despite progress toward gender equality in the labor market over the past few decades, gender segregation in labor force composition and labor market outcomes persists. Evidence has shown that job advertisements may express gender preferences, which may selectively attract potential job candidates to apply for a given post and thus reinforce gendered labor force composition and outcomes. Removing gender-explicit words from job advertisements does not fully solve the problem as certain implicit traits are more closely associated with men, such as , while others are more closely associated with women, such as .

Associations between Longitudinal Gestational Weight Gain and Scalar Infant Birth Weight: A Bayesian Joint Modeling Approach.

Despite the importance of maternal gestational weight gain, it is not yet conclusively understood how weight gain during different stages of pregnancy influences health outcomes for either mother or child. We partially attribute this to differences in and the validity of statistical methods for the analysis of longitudinal and scalar outcome data. In this paper, we propose a Bayesian joint regression model that estimates and uses trajectory parameters as predictors of a scalar response.

High-Dimensional Spatial Quantile Function-on-Scalar Regression.

This article develops a novel spatial quantile function-on-scalar regression model, which studies the conditional spatial distribution of a high-dimensional functional response given scalar predictors. With the strength of both quantile regression and copula modeling, we are able to explicitly characterize the conditional distribution of the functional or image response on the whole spatial domain. Our method provides a comprehensive understanding of the effect of scalar covariates on functional responses across different quantile levels and also gives a practical way to generate new images for given covariate values.

Comparison of Prognostic Scoring Systems to Predict Durable Pain Relief After Microvascular Decompression for Trigeminal Neuralgia.

Background: Microvascular decompression (MVD) is an effective treatment for trigeminal neuralgia, but pain recurs in a substantial minority of patients. Two recently published scoring systems by Hardaway et al. and Panczykowski et al.

Estimation for the bivariate quantile varying coefficient model with application to diffusion tensor imaging data analysis.

Despite interest in the joint modeling of multiple functional responses such as diffusion properties in neuroimaging, robust statistical methods appropriate for this task are lacking. To address this need, we propose a varying coefficient quantile regression model able to handle bivariate functional responses. Our work supports innovative insights into biomedical data by modeling the joint distribution of functional variables over their domains and across clinical covariates.

Discovery of Highly Potent and Selective IRAK1 Degraders to Probe Scaffolding Functions of IRAK1 in ABC DLBCL.

MyD88 gene mutation has been identified as one of the most prevalent driver mutations in the activated B-cell-like diffuse large B-cell lymphoma (ABC DLBCL). The published literature suggests that interleukin-1 receptor-associated kinase 1 (IRAK1) is an essential gene for ABC DLBCL harboring MyD88 mutation. Importantly, the scaffolding function of IRAK1, rather than its kinase activity, is required for tumor cell survival.

Tailoring 3D Carbon Foam using CNTs and MnO to Fabricate Stable Lithium/Dissolved Lithium Polysulfide Batteries.

The lithium-sulfur (Li-S) battery is an ideal electrochemical energy storage system owing to the high theoretical energy density and acceptable cost of finance and the environment. However, some disadvantages, including low electrical conductivity, poor sulfur utilization, and rapid capacity fading, obstruct its practical application. In this work, 3D carbon foam from a melamine resin is synthesized via high-temperature calcination.

Stable Anatomy Detection in Multimodal Imaging Through Sparse Group Regularization: A Comparative Study of Iron Accumulation in the Aging Brain.

Multimodal neuroimaging provides a rich source of data for identifying brain regions associated with disease progression and aging. However, present studies still typically analyze modalities separately or aggregate voxel-wise measurements and analyses to the structural level, thus reducing statistical power. As a central example, previous works have used two quantitative MRI parameters-R2* and quantitative susceptibility (QS)-to study changes in iron associated with aging in healthy and multiple sclerosis subjects, but failed to simultaneously account for both.

Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions.

Distance weighted discrimination (DWD) is an appealing classification method that is capable of overcoming data piling problems in high-dimensional settings. Especially when various sparsity structures are assumed in these settings, variable selection in multicategory classification poses great challenges. In this paper, we propose a multicategory generalized DWD (MgDWD) method that maintains intrinsic variable group structures during selection using a sparse group lasso penalty.

Assessing IRAK4 Functions in ABC DLBCL by IRAK4 Kinase Inhibition and Protein Degradation.

The interleukin-1 receptor-activated kinase 4 (IRAK4) belongs to the IRAK family of serine/threonine kinases and plays a central role in the innate immune response. However, the function of IRAK4 in tumor growth and progression remains elusive. Here we sought to determine the enzymatic and scaffolding functions of IRAK4 in activated B-cell-like diffuse large B cell lymphoma (ABC DLBCL).

Model-robust designs for nonlinear quantile regression.

We construct robust designs for nonlinear quantile regression, in the presence of both a possibly misspecified nonlinear quantile function and heteroscedasticity of an unknown form. The asymptotic mean-squared error of the quantile estimate is evaluated and maximized over a neighbourhood of the fitted quantile regression model. This maximum depends on the scale function and on the design.

The Harbin Medical University nephrectomy score: a quantitative system for evaluating the complexity of laparoscopic retroperitoneal simple nephrectomy.

Background: Laparoscopic retroperitoneal simple nephrectomy (LRSN) has been widely accepted as a mainstay option for benign non-functioning kidney. The complexity of the procedure, however, differs and remains a subject of controversy.

Objective: To develop a standardised Harbin Medical University nephrectomy score (HMUNS) system for evaluating LRSN complexity.

A General Framework for Quantile Estimation with Incomplete Data.

Quantile estimation has attracted significant research interests in recent years. However, there has been only a limited literature on quantile estimation in the presence of incomplete data. In this paper, we propose a general framework to address this problem.