Patterns of interaction in peer response: the relationship between pair dynamics and revision outcomes

Sociocultural researchers in SLA consider the interface between the social dynamics of pair interactions and language learning. Using Storch’s (2002) patterns of interaction coding scheme, studies have found that students who adopt a collaborative pattern are more successful in using language as a learning tool. SLA theorists, however, have suggested research projects that further analyze peer interaction and learning outcomes, including writing development, in ecologically valid settings (Swain, 2002; Ortega, 2012). Peer response is a pedagogical practice where focus on pair dynamics in relation to learning is particularly relevant. Despite its popularity and the theoretical argument for peer response, not all peer response is successful, and Ferris (2003) called for projects that consider both characteristics and outcomes of peer response. This study bridges the gap in these two related research areas, L2 writing and SLA, examining patterns of interaction during peer response, and considering associations between these and revision outcomes. Five pairs of non-native English speaking undergraduates were recording during peer response sessions three times, and also contributed first and second drafts of the papers they discussed. Peer response conversations were coded as exhibiting one of the four patterns (collaborative, expert/novice, dominant/dominant, and dominant/passive) identified by Storch (2002), which was enhanced by students’ perceptions of the peer response sessions that they provided in interviews. Second drafts were analyzed for improvement, and these gains were compared by pattern of interaction. Results show that two patterns (collaborative and expert/novice) are indeed associated with better revision outcomes. What is more, stimulated recall interviews with these students revealed that they become more successful at peer response when they attend to not only the task, but the interpersonal relationship. Overall, results provide classroom-based evidence on the relationship between peer-peer interaction and writing acquisition. These findings complement SLA interaction studies conducted in more experimental settings, as well as contribute to the peer response research in L2 writing by describing in detail students’ social interactions. This study also provides valuable pedagogical implications about training and pairing students for peer response. Finally, this study contributes to the emerging research trend of interfaces between SLA and L2 writing (Ortega, 2012)

DNA methylation associated with postpartum depressive symptoms overlaps findings from a genome-wide association meta-analysis of depression

Background Perinatal depressive symptoms have been linked to adverse maternal and infant health outcomes. The etiology associated with perinatal depressive psychopathology is poorly understood, but accumulating evidence suggests that understanding inter-individual differences in DNA methylation (DNAm) patterning may provide insight regarding the genomic regions salient to the risk liability of perinatal depressive psychopathology. Results Genome-wide DNAm was measured in maternal peripheral blood using the Infinium MethylationEPIC microarray. Ninety-two participants (46% African-American) had DNAm samples that passed all quality control metrics, and all participants were within 7 months of delivery. Linear models were constructed to identify differentially methylated sites and regions, and permutation testing was utilized to assess significance. Differentially methylated regions (DMRs) were defined as genomic regions of consistent DNAm change with at least two probes within 1 kb of each other. Maternal age, current smoking status, estimated cell-type proportions, ancestry-relevant principal components, days since delivery, and chip position served as covariates to adjust for technical and biological factors. Current postpartum depressive symptoms were measured using the Edinburgh Postnatal Depression Scale. Ninety-eight DMRs were significant (false discovery rate \u3c 5%) and overlapped 92 genes. Three of the regions overlap loci from the latest Psychiatric Genomics Consortium meta-analysis of depression. Conclusions Many of the genes identified in this analysis corroborate previous allelic, transcriptomic, and DNAm association results related to depressive phenotypes. Future work should integrate data from multi-omic platforms to understand the functional relevance of these DMRs and refine DNAm association results by limiting phenotypic heterogeneity and clarifying if DNAm differences relate to the timing of onset, severity, duration of perinatal mental health outcomes of the current pregnancy or to previous history of depressive psychopathology

Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hopkinson, B. M., King, A. C., Owen, D. P., Johnson-Roberson, M., Long, M. H., & Bhandarkar, S. M. Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks. PLoS One, 15(3), (2020): e0230671, doi: 10.1371/journal.pone.0230671.Coral reefs are biologically diverse and structurally complex ecosystems, which have been severally affected by human actions. Consequently, there is a need for rapid ecological assessment of coral reefs, but current approaches require time consuming manual analysis, either during a dive survey or on images collected during a survey. Reef structural complexity is essential for ecological function but is challenging to measure and often relegated to simple metrics such as rugosity. Recent advances in computer vision and machine learning offer the potential to alleviate some of these limitations. We developed an approach to automatically classify 3D reconstructions of reef sections and assessed the accuracy of this approach. 3D reconstructions of reef sections were generated using commercial Structure-from-Motion software with images extracted from video surveys. To generate a 3D classified map, locations on the 3D reconstruction were mapped back into the original images to extract multiple views of the location. Several approaches were tested to merge information from multiple views of a point into a single classification, all of which used convolutional neural networks to classify or extract features from the images, but differ in the strategy employed for merging information. Approaches to merging information entailed voting, probability averaging, and a learned neural-network layer. All approaches performed similarly achieving overall classification accuracies of ~96% and >90% accuracy on most classes. With this high classification accuracy, these approaches are suitable for many ecological applications.This study was funded by grants from the Alfred P. Sloan Foundation (BMH, BR2014-049; https://sloan.org), and the National Science Foundation (MHL, OCE-1657727; https://www.nsf.gov). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript

Measurements at low energies of the polarization-transfer coefficient Kyy' for the reaction 3H(p,n)3He at 0 degrees

Measurements of the transverse polarization coefficient Kyy' for the reaction 3H(p,n)3He are reported for outgoing neutron energies of 1.94, 5.21, and 5.81 MeV. This reaction is important both as a source of polarized neutrons for nuclear physics experiments, and as a test of theoretical descriptions of the nuclear four-body system. Comparison is made to previous measurements, confirming the 3H(p,n)3He reaction can be used as a polarized neutron source with the polarization known to an accuracy of approximately 5%. Comparison to R-matrix theory suggests that the sign of the 3F3 phase-shift parameter is incorrect. Changing the sign of this parameter dramatically improves the agreement between theory and experiment.Comment: 12 pages, RevTeX, 5 eps figures, submitted to Phys. Rev.

Prospective Longitudinal Study of the Pregnancy DNA Methylome: The US Pregnancy, Race, Environment, Genes (PREG) Study

Purpose The goal of the Pregnancy, Race, Environment, Genes study was to understand how social and environmental determinants of health (SEDH), pregnancy-specific environments (PSE) and biological processes influence the timing of birth and account for the racial disparity in preterm birth. The study followed a racially diverse longitudinal cohort throughout pregnancy and included repeated measures of PSE and DNA methylation (DNAm) over the course of gestation and up to 1 year into the postpartum period. Participants All women were between 18 and 40 years of age with singleton pregnancies and no diagnosis of diabetes or indication of assisted reproductive technology. Both mother and father had to self-identify as either African-American (AA) or European-American (EA). Maternal peripheral blood samples along with self-report questionnaires measuring SEDH and PSE factors were collected at four pregnancy visits, and umbilical cord blood was obtained at birth. A subset of participants returned for two additional postpartum visits, during which additional questionnaires and maternal blood samples were collected. The pregnancy and postpartum extension included n=240 (AA=126; EA=114) and n=104 (AA=50; EA=54), respectively. Findings to date One hundred seventy-seven women (AA=89, EA=88) met full inclusion criteria out of a total of 240 who were initially enrolled. Of the 63 participants who met exclusion criteria after enrolment, 44 (69.8%) were associated with a medical reason. Mean gestational age at birth was significantly shorter for the AA participants by 5.1 days (M=272.5 (SD=10.5) days vs M=277.6 (SD=8.3)). Future plans Future studies will focus on identifying key environmental factors that influence DNAm change across pregnancy and account for racial differences in preterm birth