Evaluating Performance Persistence in US Open-End Mutual Funds

Performance persistence in US open-end mutual funds is a contentious issue. This paper examines the performance persistence by analyzing monthly returns of mutual funds under nine investment styles over the periods of January 1993 to December 2008. We find that there is some evidence to support the persistence of mutual fund performance. Albeit this, a zero-investment best-minus-worst strategy does outperform the market with a certain level of consistency

Leadership and Race: How to Develop and Support Leadership that Contributes to Racial Justice

This report explores the ways in which our current thinking about leadership often contributes to producing and maintaining racialized dynamics, and identifies a set of core competencies associated with racial justice leadership. Recommendations are included for helping leadership programs develop and support leadership that furthers racial justice in organizations, communities, and the broader society

Regridding Uncertainty for Statistical Downscaling of Solar Radiation

Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM output from their native grids and at differing spatial resolutions to a common grid in order to be comparable to observed data and (2) bias correcting RCM data, via quantile mapping, for example, for future modeling and analysis. The uncertainty associated with (1) is not always considered for downstream operations in (2). This work examines this uncertainty, which is not often made available to the user of a regridded data product. This analysis is applied to RCM solar radiation data from the NA-CORDEX data archive and observed data from the National Solar Radiation Database housed at the National Renewable Energy Lab. A case study of the mentioned methods over California is presented.Comment: 16 pages, 5 figures, submitted to: Advances in Statistical Climatology, Meteorology and Oceanograph

Experimental analysis of 3D flow structures around a floating dike

Floating dikes have several advantages over spur dikes including less influence on riverine sediment transport, bed topography, and ecosystems, and a good adaptability to fluvial conditions. Despite these advantages, floating dikes have not been used in many river regulation schemes due to the limited understanding of the 3D flow structures around floating dikes. In this study, a series of experiments were conducted to investigate the 3D flow structures around floating dikes. Results show that, after installing a floating dike on one side of a flume, the surface water flow is deflected to the opposite side of the flume, and a backflow develops around the outer and downstream side of the dike, where both the vertical turbulent intensity and the absolute magnitude of the Reynolds stress are relatively large. Due to the blocking effect of the dike, the cross-sectional area decreases, causing an increase in velocities below and alongside the dike, as well as a decrease in velocities upstream of the dike. Increasing the submerged depth or length of the dike results in an increase in flow velocity adjacent to the dike, as well as an increase in the vertical or lateral scale of the backflow. On the contrary, increasing the dike thickness leads to a weakening or disappearance of the backflow, along with a decrease in the acceleration rate of flow adjacent to the dike

BHDPC Is a Novel Neuroprotectant That Provides Anti-neuroinflammatory and Neuroprotective Effects by Inactivating NF-κB and Activating PKA/CREB.

Microglia-mediated neuroinflammatory responses are inevitable and important pathological processes in several kinds of disorder of the central nervous system (CNS). Therefore, alleviating activated microglia-induced inflammatory process might be a valuable therapeutic approach to neuroinflammation-related diseases. In the present study, we investigated BHDPC, a novel neuroprotectant discovered in our previous study that had anti-inflammatory effects under neuroinflammatory conditions. First, we found that BHDPC could inhibit neuroinflammatory responses and promote microglial M2 phenotype polarization in both lipopolysaccharide (LPS)-activated BV-2 microglia l cells. Furthermore, BHDPC provided protective actions against neuroinflammation-induced neurotoxicity in HT22 mouse hippocampal cells co-cultured with activated BV-2 microglia. Further experiments demonstrated that BHDPC could suppress LPS-induced activation of transcription factor nuclear factor kappa B (NF-κB) via interfering with the degradation of the inhibitor of kappa B (IκB) and phosphorylation of IκB, the IκB kinase (IKK). Moreover, we also found that BHDPC could induce phosphorylation of cAMP-dependent protein kinase A (PKA) and cAMP-response element-binding protein (CREB) in BV-2 microglial cells. Also, using the PKA-specific inhibitor, we found that BHDPC-induced CREB phosphorylation was dependent on PKA, which also contributed to BHDPC-mediated anti-inflammation and neuroprotection

Do psychological factors predict caesarean delivery in Australia? A cohort study

Background: The proportion of babies delivered by Cesarean Section (CS) in Australia has almost doubled over the last 25 years. Factors known to contribute to CS such as higher maternal age, mothers being overweight or obese, or having had a previous CS do not completely account for the increased rate and it is clear that other influences exist. Our study used nationally-representative data from the Longitudinal Study of Australian Children (LSAC) to identify risk factors associated with CS, with a view to identifying previously unidentified influences. Methods: Data were from the birth cohort of LSAC, a long-term prospective study of approximately 5,000 children that includes richly-detailed data regarding maternal health and exposures during pregnancy. Logistic regression was used to examine the contribution of a wide range of pregnancy, birth and social factors to CS. Results: 28% of 4,862 mothers were delivered by CS. The nal adjusted analyses revealed that use of diabetes medication (OR=3.1, 95% CI=1.7-5.5, p<0.001) and maternal mental health problems during pregnancy (OR=1.3, CI=1.1-1.6, p=0.003) were associated with increased odds of CS. Young maternal age (OR=0.6, CI=0.5-0.7, p<0.001), having two or more children (OR=0.7, CI=0.6-0.9, p<0.001), and fathers having an unskilled occupation (OR=0.7, CI=0.6-1.0, p=0.036) were associated with reduced odds of CS. Conclusion: Our findings raise the prospect that screening and intervention programs for maternal mental health problems, and attention to diabetic control in pregnancy, might be beneficial in reducing CS rates and should be studied in appropriately-constructed prospective trials.This work was supported by a project grant from the Bupa Health Foundation. The paper uses unit record data from Growing Up in Australia, the Longitudinal Study of Australian Children (LSAC). The LSAC study is conducted in partnership between the Australian Government Department of Social Services (DSS, formerly the department of Families, Housing, Community Services and Indigenous Affairs), the Australian Institute of Family Studies (AIFS) and the Australian Bureau of Statistics (ABS

Association between Self-Reported Prior Nights’ Sleep and Single-Task Gait in Healthy Young Adults: An Exploratory Study Using Machine Learning

Failure to obtain 7-9 hours of sleep has been associated with decreased gait speed in young adults. While Machine Learning (ML) has been used to identify sleep quality in young adults, there are no current studies that have used ML to identify prior night’s sleep in a sample of young adults. PURPOSE: To use ML to identify prior night’s sleep in healthy young adults using single-task walking gait. METHODS: Participants (n=126, age 24.3±4.0yrs; 65% female) completed a survey on their prior night’s sleep and performed a 2-minute walk around a 6m track. Gait data were collected using inertial sensors. Participants were split into 2 groups (\u3c7hs or \u3e9hs: poor sleepers; 7-9hs: good sleepers) and gait characteristics were used to classify participants into each group using ML models via a 10-fold cross validation. A post-hoc ANCOVA was used to assess gait differences. RESULTS: Using Random Forest Classifiers (RFC), top 9 features were extracted. Classification results suggest a 0.79 correlation between gait parameters and prior night’s sleep. The RFC models had a 65.03% mean classification accuracy rate. Top 0.3% of the models had 100% classification accuracy rate. The top 9 features were primarily characteristics that measured variance between lower limb movements. Post-hoc analyses suggest significantly greater variances between lower limb characteristics. CONCLUSION: Good sleepers had more asymmetrical gait patterns (faster gait speed, less trunk motion). Poor sleepers had trouble maintaining gait speed (increased variance in cadence, larger stride lengths, and less time spent in single leg support time). Although the mechanisms of these gait changes are unknown, these findings provide evidence that gait is different for individuals who not receive 7-9 hours of sleep the night before. As evidenced by the high correlation co-efficient of our classification models, gait may be a good way of identifying prior night’s sleep

The silver lining of COVID‐19: estimation of short‐term health impacts due to lockdown in the Yangtze River Delta region, China.

The outbreak of COVID-19 in China has led to massive lockdowns in order to reduce the spread of the epidemic and control human-to-human transmission. Subsequent reductions in various anthropogenic activities have led to improved air quality during the lockdown. In this study, we apply a widely used exposure-response function to estimate the short-term health impacts associated with PM2.5 changes over the Yangtze River Delta (YRD) region due to COVID-19 lockdown. Concentrations of PM2.5 during lockdown period reduced by 22.9% to 54.0% compared to pre-lockdown level. Estimated PM2.5-related daily premature mortality during lockdown period is 895 (95% confidential interval: 637–1,081), which is 43.3% lower than pre-lockdown period and 46.5% lower compared with averages of 2017–2019. According to our calculation, total number of avoided premature death aassociated with PM2.5 reduction during the lockdown is estimated to be 42.4 thousand over the YRD region, with Shanghai, Wenzhou, Suzhou (Jiangsu province), Nanjing, and Nantong being the top five cities with largest health benefits. Avoided premature mortality is mostly contributed by reduced death associated with stroke (16.9 thousand, accounting for 40.0%), ischemic heart disease (14.0 thousand, 33.2%), and chronic obstructive pulmonary disease (7.6 thousand, 18.0%). Our calculations do not support or advocate any idea that pandemics produce a positive note to community health. We simply present health benefits from air pollution improvement due to large emission reductions from lowered human and industrial activities. Our results show that continuous efforts to improve air quality are essential to protect public health, especially over city-clusters with dense population