Activity

L1s are transposable elements that move by a copy-and-paste mechanism that continuously increases their copy number in the genome, such that each genome has a record of the L1 history in that host lineage. They make up about 20% of the genomes of eutherian mammals and have played a major role in shaping genome evolution. Chiroptera has the lowest average genome size among mammalian orders and the only documented case of L1 extinction affecting an entire mammalian family. Herein, L1 activity and extinction are characterized in all families of the order Chiroptera using a method that enriches for the youngest lineages of L1s in the genome. In addition to the previously reported L1 extinction in Pteropodidae, L1 extinction was documented to occur in Mormoops blainvilli, but this event did not affect all species of Mormoopidae. Further, there was no evidence of concordance between the evolution of L1s and their chiropteran host. There were two L1 lineages present before the divergence of all extant bats. Both lineages are extinct in the Pteropodidae. One or the other L1 lineage is extinct in almost all bat families, but Taphozous melanopogon maintains active members of both. Most intriguingly, some families within the Rhinolophoidea retain one active L1 lineage whereas other families retain the other, creating a deep discontinuity between L1 phylogeny and chiropteran phylogeny. These results indicate that there have been numerous losses of active L1 lineages over the history of chiropteran evolution, but that all chiropteran families except Pteropodidae have retained L1 activity.This study explores how typologies of adversity and mental health/substance use disorders impact rule violations during incarceration. Data come from the 2004 cross-sectional Survey of Inmates in State and Federal Correctional Facilities (SI-SFCF). Logistic regression and structural equation modeling were used for analysis. Results link history of adverse experiences to rule violations during incarceration and demonstrate how mental health and substance use disorders mediate this relationship. Incarcerated people with severe histories of adverse experiences had the highest odds of rule violations, relative to people with low adversity, for all typologies. More severe adversity typologies predicted mental health and substance use disorders. Alcohol and substance use disorders predicted drug violations, whereas substance use and mental health disorders predicted major violations. Serious mental illness did not predict rule violations when accounting for adversity. Findings suggest that addressing adverse experiences, mental health, and substance use disorders may prevent rule violations.Recent increases in the average age at first marriage have created an extended period during which young adults frequently continue to socialize with friends, even as romantic ties typically become increasingly serious. Nevertheless, little research has focused on some of the challenges associated with navigating these two social worlds simultaneously. The current study expanded the traditional lens of social learning theory to investigate associations between a range of attitudes and behaviors of friends and a serious form of conflict-intimate partner violence (IPV). SKF-34288 concentration Analyses relied on structured survey and in-depth interview data from a longitudinal study of a large, diverse sample of male and female respondents followed across the adolescent to adult transition (n = 928). Consistent with prior work, friends’ IPV experience was significantly associated with respondents’ own IPV perpetration. Yet the social learning perspective we developed highlighted the importance of considering a broader portfolio of friends’ characteristics. Controlling for friends’ IPV experience and family background (a) involvement with friends perceived as more liberal in their attitudes toward dating and sexuality and (b) friends’ delinquent behavior were both associated with the odds of reporting IPV. Further, longitudinal analyses showed an effect of variability in friends’ delinquency on within-individual changes in IPV across the full study period, suggesting that the association is not due solely to an underlying antisocial propensity. In-depth interviews with a subset of respondents (n = 102) corroborate these results, further illuminate underlying mechanisms, and highlight the dynamic aspects of these forms of social involvement during young adulthood.Efficient water use assessment and irrigation management is critical for the sustainability of irrigated agriculture, especially under changing climate conditions. Due to the impracticality of maintaining ground instrumentation over wide geographic areas, remote sensing and numerical model-based fine-scale mapping of soil water conditions have been applied for water resource applications at a range of spatial scales. Here, we present a prototype framework for integrating high-resolution thermal infrared (TIR) and synthetic aperture radar (SAR) remote sensing data into a soil-vegetation-atmosphere-transfer (SVAT) model with the aim of providing improved estimates of surface- and root-zone soil moisture that can support optimized irrigation management strategies. Specifically, remotely-sensed estimates of water stress (from TIR) and surface soil moisture retrievals (from SAR) are assimilated into a 30-m resolution SVAT model over a vineyard site in the Central Valley of California, U.S. The efficacy of our data assimilation algorithm is investigated via both the synthetic and real data experiments. Results demonstrate that a particle filtering approach is superior to an ensemble Kalman filter for handling the nonlinear relationship between model states and observations. In addition, biophysical conditions such as leaf area index are shown to impact the relationship between observations and states and must therefore be represented accurately in the assimilation model. Overall, both surface and root-zone soil moisture predicted via the SVAT model are enhanced through the assimilation of thermal and radar-based retrievals, suggesting the potential for improving irrigation management at the agricultural sub-field scale using a data assimilation strategy.