HESML: A scalable ontology-based semantic similarity measures library with a set of reproducible experiments and a replication dataset

This work is a detailed companion reproducibility paper of the methods and experiments proposed by Lastra-Díaz and García-Serrano in (2015, 2016) [56–58], which introduces the following contributions: (1) a new and efficient representation model for taxonomies, called PosetHERep, which is an adaptation of the half-edge data structure commonly used to represent discrete manifolds and planar graphs; (2) a new Java software library called the Half-Edge Semantic Measures Library (HESML) based on PosetHERep, which implements most ontology-based semantic similarity measures and Information Content (IC) models reported in the literature; (3) a set of reproducible experiments on word similarity based on HESML and ReproZip with the aim of exactly reproducing the experimental surveys in the three aforementioned works; (4) a replication framework and dataset, called WNSimRep v1, whose aim is to assist the exact replication of most methods reported in the literature; and finally, (5) a set of scalability and performance benchmarks for semantic measures libraries. PosetHERep and HESML are motivated by several drawbacks in the current semantic measures libraries, especially the performance and scalability, as well as the evaluation of new methods and the replication of most previous methods. The reproducible experiments introduced herein are encouraged by the lack of a set of large, self-contained and easily reproducible experiments with the aim of replicating and confirming previously reported results. Likewise, the WNSimRep v1 dataset is motivated by the discovery of several contradictory results and difficulties in reproducing previously reported methods and experiments. PosetHERep proposes a memory-efficient representation for taxonomies which linearly scales with the size of the taxonomy and provides an efficient implementation of most taxonomy-based algorithms used by the semantic measures and IC models, whilst HESML provides an open framework to aid research into the area by providing a simpler and more efficient software architecture than the current software libraries. Finally, we prove the outperformance of HESML on the state-of-the-art libraries, as well as the possibility of significantly improving their performance and scalability without caching using PosetHERep

Correspondence Between Perceived Pubertal Development and Hormone Levels in 9-10 Year-Olds From the Adolescent Brain Cognitive Development Study.

Aim: To examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics. Methods: Cross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study—a multi-site sample of 9–10 year-olds (n = 11,875)—and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels. Results: PDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child\u27s weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample. Conclusions: Sociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes

A Critical Review on the Complex Interplay between Social Determinants of Health and Maternal and Infant Mortality

Background: U.S. maternal and infant mortality rates constitute an important public health problem, because these rates surpass those in developed countries and are characterized by stark disparities for racial/ethnic minorities, rural residents, and individuals with less privileged socioeconomic status due to social determinants of health (SDoH). Methods: A critical review of the maternal and infant mortality literature was performed to determine multilevel SDoH factors leading to mortality disparities with a life course lens. Results: Black mothers and infants fared the worst in terms of mortality rates, likely due to the accumulation of SDoH experienced as a result of structural racism across the life course. Upstream SDoH are important contributors to disparities in maternal and infant mortality. More research is needed on the effectiveness of continuous quality improvement initiatives for the maternal–infant dyad, and expanding programs such as paid maternity leave, quality, stable and affordable housing, and social safety-nets (Medicaid, CHIP, WIC), in reducing maternal and infant mortality. Finally, it is important to address research gaps in individual, interpersonal, community, and societal factors, because they affect maternal and infant mortality and related disparities. Conclusion: Key SDoH at multiple levels affect maternal and infant health. These SDoH shape and perpetuate disparities across the lifespan and are implicated in maternal and infant mortality disparities

Gender Differences in Mental Health Outcomes before, during, and after the Great Recession.

We examined gender differences in mental health outcomes during and post-recession versus pre-recession. We utilized 2005-2006, 2008-2009, and 2010-2011 data from the Medical Expenditure Panel Survey. Females had lower odds of depression diagnoses during and post-recession and better mental health during the recession, but higher odds of anxiety diagnoses post-recession. Males had lower odds of depression diagnoses and better mental health during and post-recession and lower Kessler 6 scores post-recession. We conducted stratified analyses, which confirmed that the aforementioned findings were consistent across the four different regions of the U.S., by employment status, income and health care utilization. Importantly, we found that the higher odds of anxiety diagnoses among females after the recession were mainly prominent among specific subgroups of females: those who lived in the Northeast or the Midwest, the unemployed, and those with low household income. Gender differences in mental health in association with the economic recession highlight the importance of policymakers taking these differences into consideration when designing economic and social policies to address economic downturns. Future research should examine the reasons behind the decreased depression diagnoses among both genders, and whether they signify decreased mental healthcare utilization or increased social support and more time for exercise and leisure activities

Weighted summary statistics of the sample before, during, and after the recession^†.

<p>^† Starred P-values represent comparisons of means during and after the recession compared to pre-recession. The two columns of p-values represent the results of Bonferroni tests, which are used to test the significant associations of the “during, before, and after” recession periods with the categorical variables for females and males, respectively (NS = non-significant).</p><p>* p ≤ 0.05;</p><p>** p ≤ 0.01;</p><p>*** p ≤ 0.001</p><p>Weighted summary statistics of the sample before, during, and after the recession<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124103#t001fn001" target="_blank">^†</a>.</p

Multivariate analyses of the associations between recession indicators (during and after) and mental health outcomes for females.

<p>* p ≤ 0.05;</p><p>** p ≤ 0.01;</p><p>*** p ≤ 0.001</p><p>Multivariate analyses of the associations between recession indicators (during and after) and mental health outcomes for females.</p