Is Collective Efficacy Age Graded? The Development and Evaluation of a New Measure of Collective Efficacy for Older Adults

Objectives. Community processes are key determinants of older adults' ability to age in place, but existing scales measuring these constructs may not provide accurate, unbiased measurements among older adults because they were designed with the concerns of child-rearing respondents in mind. This study examines the properties of a new theory-based measure of collective efficacy (CE) that accounts for the perspectives of older residents. Methods. Data come from the population-based Chicago Neighborhood Organization, Aging and Health study (N = 1,151), which surveyed adults aged 65 to 95. Using descriptive statistics, correlations, and factor analysis, we explored the acceptability, reliability, and validity of the new measure. Results. Principal component analysis indicated that the new scale measures a single latent factor. It had good internal consistency reliability, was highly correlated with the original scale, and was similarly associated with neighborhood exchange and disorder, self-rated health, mobility, and loneliness. The new scale also showed less age-differentiated nonresponse compared to the original scale. Discussion. The older adult CE scale has reliability and validity equivalent to that of the existing measure but benefits from a more developed theoretical grounding and reduced likelihood of age-related differential nonresponse

Improving neural network models for natural language processing in Russian with synonyms

© 2016 FRUCT.Recent advances in deep leaming for natural language processing achieve and improve over state of the art results in many natural language processing tasks. One problem with neural network models, however, is that they require large datasets, including large labeled datasets for the corresponding problems. In this work, we suggest a dala augmentation method based on extending a given dataset with synonyms for the words appearing there. We apply this approach to the morphologically rich Russian language and show improvements for modem neural network NLP models on standard tasks such as sentiment analysis

A Systematic Review of Magnesium Sulfate for Perinatal Neuroprotection: What Have We Learnt From the Past Decade?

There is an important unmet need to improve long term outcomes of encephalopathy for preterm and term infants. Meta-analyses of large controlled trials suggest that maternal treatment with magnesium sulfate (MgSO4) is associated with a reduced risk of cerebral palsy and gross motor dysfunction after premature birth. However, to date, follow up to school age has found an apparent lack of long-term clinical benefit. Because of this inconsistency, it remains controversial whether MgSO4 offers sustained neuroprotection. We systematically reviewed preclinical and clinical studies reported from January 1 2010, to January 31 2020 to evaluate the most recent advances and knowledge gaps relating to the efficacy of MgSO4 for the treatment of perinatal brain injury. The outcomes of MgSO4 in preterm and term-equivalent animal models of perinatal encephalopathy were highly inconsistent between studies. None of the perinatal rodent studies that suggested benefit directly controlled body or brain temperature. The majority of the studies did not control for sex, study long term histological and functional outcomes or use pragmatic treatment regimens and many did not report controlling for potential study bias. Finally, most of the recent preterm or term human studies that tested the potential of MgSO4 for perinatal neuroprotection were relatively underpowered, but nevertheless, suggest that any improvements in neurodevelopment were at best modest or absent. On balance, these data suggest that further rigorous testing in translational preclinical models of perinatal encephalopathy is essential to ensure safety and best regimens for optimal preterm neuroprotection, and before further clinical trials of MgSO4 for perinatal encephalopathy at term are undertaken

R/Bioconductor software for Illumina's Infinium whole-genome genotyping BeadChips

Summary: Illumina produces a number of microarray-based technologies for human genotyping. An Infinium BeadChip is a two-color platform that types between 105 and 106 single nucleotide polymorphisms (SNPs) per sample. Despite being widely used, there is a shortage of open source software to process the raw intensities from this platform into genotype calls. To this end, we have developed the R/Bioconductor package crlmm for analyzing BeadChip data. After careful preprocessing, our software applies the CRLMM algorithm to produce genotype calls, confidence scores and other quality metrics at both the SNP and sample levels. We provide access to the raw summary-level intensity data, allowing users to develop their own methods for genotype calling or copy number analysis if they wish

Dissipative Dynamics of Collisionless Nonlinear Alfven Wave Trains

The nonlinear dynamics of collisionless Alfven trains, including resonant particle effects is studied using the kinetic nonlinear Schroedinger (KNLS) equation model. Numerical solutions of the KNLS reveal the dynamics of Alfven waves to be sensitive to the sense of polarization as well as the angle of propagation with respect to the ambient magnetic field. The combined effects of both wave nonlinearity and Landau damping result in the evolutionary formation of stationaryOA S- and arc-polarized directional and rotational discontinuities. These waveforms are freqently observed in the interplanetary plasma.Comment: REVTeX, 6 pages (including 5 figures). This and other papers may be found at http://sdphpd.ucsd.edu/~medvedev/papers.htm

Identifying the favored mutation in a positive selective sweep.

Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations