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Wildfires emit large amounts of black carbon and light-absorbing organic carbon, known as brown carbon, into the atmosphere. These particles perturb Earth’s radiation budget through absorption of incoming shortwave radiation. It is generally thought that brown carbon loses its absorptivity after emission in the atmosphere due to sunlight-driven photochemical bleaching. Consequently, the atmospheric warming effect exerted by brown carbon remains highly variable and poorly represented in climate models compared with that of the relatively nonreactive black carbon. Given that wildfires are predicted to increase globally in the coming decades, it is increasingly important to quantify these radiative impacts. Here we present measurements of ensemble-scale and particle-scale shortwave absorption in smoke plumes from wildfires in the western United States. We find that a type of dark brown carbon contributes three-quarters of the short visible light absorption and half of the long visible light absorption. This strongly absorbing organic aerosol species is water insoluble, resists daytime photobleaching and increases in absorptivity with night-time atmospheric processing. Our findings suggest that parameterizations of brown carbon in climate models need to be revised to improve the estimation of smoke aerosol radiative forcing and associated warming.

 

Given the robust evidence base for the efficacy of evidence‐based treatments targeting youth anxiety, researchers have advanced beyond efficacy outcome analysis to identifymechanismsof change and treatment directionality. Grounded in developmental transactional models, interventions for young children at risk for anxiety by virtue of behaviorally inhibited temperament often target parenting and child factors implicated in the early emergence and maintenance of anxiety. In particular, overcontrolling parenting moderates risk for anxiety among highly inhibited children, just as child inhibition has been shown to elicit overcontrolling parenting. Although longitudinal research has elucidated the temporal unfolding of factors that interact to place inhibited children at risk for anxiety, reciprocal transactions between these child and parent factors in the context of early interventions remain unknown.

This study addresses these gaps by examining mechanisms of change and treatment directionality (i.e., parent‐to‐child vs. child‐to‐parent influences) within a randomized controlled trial comparing two interventions for inhibited preschoolers (N = 151): the multicomponent Turtle Program (‘Turtle’) and the parent‐only Cool Little Kids program (‘CLK’). Reciprocal relations between parent‐reported child anxiety, observed parenting, and parent‐reported accommodation of child anxiety were examined across four timepoints: pre‐, mid‐, and post‐treatment, and one‐year follow‐up (NCT02308826).

Hypotheses were tested via latent curve models with structured residuals (LCM‐SR) and latent change score (LCS) models. LCM‐SR results were consistent with the child‐to‐parent influences found in previous research on cognitive behavioral therapy (CBT) for older anxious youth, but only emerged in Turtle. LCS analyses revealed bidirectional effects ofchangesin parent accommodation and child anxiety during and after intervention, but only in Turtle.

Our findings coincide with developmental transactional models, suggesting that the development of child anxiety may result from child‐to‐parent influences rather than the reverse, and highlight the importance of targeting parentandchild factors simultaneously in early interventions for young, inhibited children.

 

The authors showcase the potential of symbolic regression as an analytic method for use in materials research. First, the authors briefly describe the current state-of-the-art method, genetic programming-based symbolic regression (GPSR), and recent advances in symbolic regression techniques. Next, the authors discuss industrial applications of symbolic regression and its potential applications in materials science. The authors then present two GPSR use-cases: formulating a transformation kinetics law and showing the learning scheme discovers the well-known Johnson–Mehl–Avrami–Kolmogorov form, and learning the Landau free energy functional form for the displacive tilt transition in perovskite LaNiO 3 . Finally, the authors propose that symbolic regression techniques should be considered by materials scientists as an alternative to other machine learning-based regression models for learning from data. 

Aerosol mass extinction efficiency (MEE) is a key aerosol property used to connect aerosol optical properties with aerosol mass concentrations. Using measurements of smoke obtained during the Fire Influence on Regional to Global Environments and Air Quality (FIREX‐AQ) campaign we find that mid‐visible smoke MEE can change by a factor of 2–3 between fresh smoke (<2 hr old) and one‐day‐old smoke. While increases in aerosol size partially explain this trend, changes in the real part of the aerosol refractive index (real(n)) are necessary to provide closure assuming Mie theory. Real(n) estimates derived from multiple days of FIREX‐AQ measurements increase with age (from 1.40 – 1.45 to 1.5–1.54 from fresh to one‐day‐old) and are found to be positively correlated with organic aerosol oxidation state and aerosol size, and negatively correlated with smoke volatility. Future laboratory, field, and modeling studies should focus on better understanding and parameterizing these relationships to fully represent smoke aging.

 

This study examined the direct and interactive effects of infants’ respiratory sinus arrhythmia (RSA) and maternal depressive symptoms (MDS) during the first 6 months of life in the prediction of children's sleep problems at age 18 months. Participants included 156 children and their mothers who were followed from 3 to 18 months of age. At ages 3 and 6 months, infants’ cardiac activity was recorded at rest and during the still‐face paradigm, a mother–child social challenge task, and estimates of infant baseline RSA (RSAB) and RSA withdrawal (RSAW) were calculated. Mothers reported about their depressive symptoms at 3, 6, and 18 months, and about infants’ sleep problems at age 18 months. Less RSAW and higher levels of MDS predicted more sleep problems at age 18 months. Additionally, RSAB moderated the link between MDS and children's sleep problems such that MDS were related to more sleep problems only for infants with high levels of RSAB. Results illustrate the importance of RSA as both a direct predictor and a moderator of maternal influences in the prediction of early sleep problems.