Repeatability of endocrine traits and dominance rank in female guinea pigs

Background Glucocorticoids (e.g. cortisol) are associated with variation in social behavior, and previous studies have linked baseline as well as challenge-induced glucocorticoid concentrations to dominance status. It is known that cortisol response to an acute challenge is repeatable and correlates to social behavior in males of many mammal species. However, it is unclear whether these patterns are also consistent for females. The aim of this study was to investigate whether baseline and response cortisol concentrations are repeatable in female guinea pigs (Cavia aperea f. porcellus) and whether dominance rank is stable and correlated to baseline cortisol concentration and/or cortisol responsiveness. Results Our results show that cortisol responsiveness (after 1 h: R = 0.635, 95% CI = 0.229, 0.927; after 2 h: R = 0.764, 95% CI = 0.433, 0.951) and dominance rank (R = 0.709, 95% CI = 0.316, 0.935) of females were significantly repeatable after six weeks but not correlated. Baseline cortisol was not repeatable (R = 0, 95% CI = 0, 0.690) and also did not correlate to dominance rank. Furthermore, the difference in repeatability estimates of baseline and response values was due to high within-individual variance of baseline cortisol concentration; the amount of between-individual variance was similar for baseline cortisol and the two measures of cortisol responsiveness. Conclusions Females occupying different dominance ranks did not have long-term differences in cortisol concentrations, and cortisol responsiveness does not seem to be significantly involved in the maintenance of dominance rank. Overall, this study reveals the remarkable stability of cortisol responsiveness and dominance rank in a female rodent, and it remains an open question whether the magnitude of cortisol responsiveness is adaptive in social contexts for females.

Measuring sign complexity: Comparing a theory-driven and a data-driven approach

The study of articulatory complexity has proven to yield useful insights into the phonological mechanisms of spoken languages. In sign languages, this type of knowledge is scarcely documented. The current study compares a data-driven measure and a theory-driven measure of complexity for signs in French Sign Language (LSF). The former measure is based on error rates of handshape, location, orientation, movement and sign fluidity in a repetition task administered to non-signers; the latter measure is derived by applying a feature-geometry model of sign description on the same set of signs. A significant correlation is found between the two measures for the overall complexity. When looking at the impact of individual phonemic classes on complexity, a significant correlation is found for handshape and location but not for movement. We discuss how these results indicate that a fine-grained theoretical model of sign phonology/phonetics reflects the degree of complexity as resulting from the perceptual and articulatory properties of signs.

Combining a Being Imitated Strategy With IBT Improves Basic Joint Attention Behaviors in Young Children With ASD

In the present study, we examined how an initial being imitated (BIm) strategy affected the development of initiating joint attention (IJA) among a group of children newly diagnosed with autism spectrum disorder (ASD). One group received 3 months of BIm followed by 12 months of intensive behavior treatment (IBT) which equaled treatment as usual whereas a second group received IBT for the entire 15-month study period. We utilized two measures of IJA: an eye gaze and a gesture score (point and show). IJA did not change during the first 3 months of treatment, nor were any significant between-group differences noted. However, at the end of the 15-month-long intervention period, the BIm group used eye gaze significantly more often to initiate joint attention. No significant change was noted for the gesture score. These results suggest that an early implementation of a being imitated strategy might be useful as less resource intensive but beneficial “start-up” intervention when combined with IBT treatment as a follow-up.

Racism and Older Black Americans’ Health: a Systematic Review

We reviewed research that examines racism as an independent variable and one or more health outcomes as dependent variables in Black American adults aged 50 years and older in the USA. Of the 43 studies we reviewed, most measured perceived interpersonal racism, perceived institutional racism, or residential segregation. The only two measures of structural racism were birth and residence in a “Jim Crow state.” Fourteen studies found associations between racism and mental health outcomes, five with cardiovascular outcomes, seven with cognition, two with physical function, two with telomere length, and five with general health/other health outcomes. Ten studies found no significant associations in older Black adults. All but six of the studies were cross-sectional. Research to understand the extent of structural and multilevel racism as a social determinant of health and the impact on older adults specifically is needed. Improved measurement tools could help address this gap in science.

Impact of Economic Affluence on CO2 Emissions in CEE Countries

There is huge evidence for a relationship between economic growth and environmental degradation. One of the causes of environmental degradation is CO2 emission which is added to the atmosphere through human activities and excessive industrialization. The aim of this research is to examine the relationship between CO2 emissions and measures of wealth in countries of Central and Eastern Europe between 2000 and 2019. The paper extends the research on economic affluence by taking into consideration two measures of economic growth, in addition to GDP, the HDI index is included. The basis for the investigation is the EKC concept. All analyses are based on econometric models with GDP and the HDI index as independent variables. The results are not conclusive and there is no one model which best describes the relationship between CO2 emissions and economic growth. Verification of the models indicates the better fit of models with the HDI index as the measure of affluence. Moreover, the study confirms that the key factors affecting CO2 emissions are energy consumption per capita which leads to an increase in CO2 emissions, and renewable energy consumption which reduces CO2 emissions. Therefore, technological changes and an increase in human awareness of global sustainability are required.

Community vibrancy and its relationship with safety in Philadelphia

To what extent can the strength of a local urban community impact neighborhood safety? We construct measures of community vibrancy based on a unique dataset of block party permit approvals from the City of Philadelphia. Our first measure captures the overall volume of block party events in a neighborhood whereas our second measure captures differences in the type (regular versus spontaneous) of block party activities. We use both regression modeling and propensity score matching to control for the economic, demographic and land use characteristics of the surrounding neighborhood when examining the relationship between crime and our two measures of community vibrancy. We conduct our analysis on aggregate levels of crime and community vibrancy from 2006 to 2015 as well as the trends in community vibrancy and crime over this time period. We find that neighborhoods with a higher number of block parties have a significantly higher crime rate, while those holding a greater proportion of spontaneous block party events have a significantly lower crime rate. We also find that neighborhoods which have an increase in the proportion of spontaneous block parties over time are significantly more likely to have a decreasing trend in total crime incidence over that same time period.

Nouns and Verbs Identify Different Subtypes of MCI

It is well-documented that patients with semantic dementia and Alzheimer’s disease present with difficulty in lexical retrieval and reversal of the concreteness effect in nouns and verbs. Little is known about the lexical phenomena before the onset of symptoms. We anticipate that there are linguistic signs in the speech of people who suffer from mild cognitive impairment (MCI), the prodromal stage of dementia. Here, we report the results of a novel corpus-linguistic approach to the early detection of cognitive impairment. We recorded 40 hours of natural, unconstrained speech of 188 English-speaking Singaporeans; 90 are diagnosed with MCI (51 amnestic, 39 nonamnestic), and 98 are cognitively healthy. The recordings yield 327,470 words, which are tagged for parts of speech. We calculate the per-minute speech rates and concreteness scores of nouns and verbs, and of all tagged words, in our dataset. Our analysis shows that the two measures of nouns and verbs identify different subtypes of MCI. Compared with healthy controls, subjects with amnestic MCI produce fewer but more abstract nouns, whereas subjects with nonamnestic MCI produce fewer but more concrete verbs. Cognitive impairment is manifested in ordinary language before the presentation of clinical symptoms, and can be detected through non-invasive corpus-based analysis of natural speech.

Domestic Resource Mobilization and Human Capital Development in Sub- Saharan Africa

This study investigates the nexus between domestic resource mobilization using aggregated and disaggregated taxes, and human capital accumulation as measured by the index of human capital and total factor productivity. The study explores panel Autoregressive Distributed Lag. We further explore the linear and nonlinear effects of taxes on human capital accumulation. The results from the scatterplots show that taxes at aggregate and disaggregated levels positively correlated with the two measures of human capital. On the linear analysis, the impact of aggregated and disaggregated taxes is largely negative under the index of human capital but largely positive under the second measure in the short-run. However, the long-run results indicate that aggregate and disaggregated taxes significantly amplify human capital accumulation. On nonlinearity, there is no presence of human capital laffer curve (HCLC) in the short-run under the two measures of human capital. However, there is presence of HCLC in the long-run. The net effects results show that some taxes (such as indirect taxes, taxes on goods and services) are distortionary in improving the level of human capital development while some taxes (such as total tax, direct tax, taxes on income, profit, and gains) can distort human capital development in the SSA region.

Are COVID-19 data reliable? The case of the European Union

Previous studies have used Benford's distribution to assess whether there is misreporting of COVID-19 cases and deaths. Data inaccuracies provide false information to the media, undermine global response and hinder the preventive measures taken by countries worldwide. In this study, we analyze daily new cases and deaths from all the countries of the European Union and estimate the conformance to Benford's distribution. For each country, two statistical tests and two measures of deviations are calculated to determine whether the reported statistics comply with the expected distribution. Four country-level developmental indexes are also included, the GDP per capita, health expenditures, the Universal Health Coverage index, and full vaccination rate. Regression analysis is implemented to show whether the deviation from Benford's distribution is affected by the aforementioned indexes. The findings indicate that only three countries were in line with the expected distribution, Bulgaria, Croatia, and Romania. For daily cases, Denmark, Greece, and Ireland, showed the greatest deviation from Benford's distribution, and for deaths, Malta, Cyprus, Greece, Italy, and Luxemburg had the highest deviation from Benford's law. Furthermore, it was found that the vaccination rate is positively associated with deviation from Benford's distribution. These results suggest that overall official data provided by authorities are not confirming Benford's law, yet this approach acts as a preliminary tool for data verification. More extensive studies should be made with a more thorough investigation of countries that showed the greatest deviation.