The spatial organization within a social insect colony is a key component of colony life. It influences individual interaction rates, resource distribution, and division of labor within the nest. Yet studies of social insect behavior are most often carried out in artificial constructions, which may change worker behavior and colony organization. We observed how workers of the ant Pheidole rhea organized brood in nests with deep chambers and textured walls that were designed to mimic their natural constructions more closely. Instead of clumping larvae into piles on the chamber floor, workers suspended fourth-instar larvae from the vertical walls and ceiling of each chamber while young larvae and pupae were clumped at the base. Fourth-instar larvae possess five rows of anchor-tipped hairs on their dorsal side, and we predicted that these hairs functioned to attach larvae to the nest walls. We gave larvae “haircuts,” where only the anchor-tipped hairs were removed, and then tested their ability to adhere to a textured surface raised to an angle of 90° and then 120° with respect to the horizontal plane. Larvae whose hairs had been clipped came unattached in almost all trials, while larvae whose hairs remained intact stayed attached. This confirmed that anchor-tipped hairs functioned to attach larvae to the walls of the nest. The presence of anchor-tipped hairs is widespread and has been documented in at least 22 genera from the ant subfamily Myrmicinae, including species that occur in a variety of environments and represent a broad range of nesting habits. Based on our results, it is likely that many species exhibit this larval hanging behavior, and this could impact colony characteristics such as spatial organization and the care of developing larvae by nurse workers.

We report the crack-free growth of a 45-pair Al_0.30Ga_0.70N/Al_0.04Ga_0.96N distributed Bragg reflector (DBR) on 2 in. diameter AlN/sapphire template by metalorganic chemical vapor deposition. To mitigate the cracking issue originating from the tensile strain of Al_0.30Ga_0.70N on GaN, an AlN template was employed in this work. On the other hand, strong compressive strain experienced by Al_0.04Ga_0.96N favors 3D island growth, which is undesired. We found that inserting an 11 nm thick GaN interlayer upon the completion of AlN template layer properly managed the strain such that the Al_0.30Ga_0.70N/Al_0.04Ga_0.96N DBR was able to be grown with an atomically smooth surface morphology. Smooth surfaces and sharp interfaces were observed throughout the structure using high-angle annular dark-field imaging in the STEM. The 45-pair AlGaN-based DBR provided a peak reflectivity of 95.4% at λ = 368 nm with a bandwidth of 15 nm.

Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios.

Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments.

Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty.

Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty.

Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope.

MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression and are implicated in the etiology of several neuropsychiatric disorders, including substance use disorders (SUDs). Using in silico genome-wide sequence analyses, we identified miR-495 as a miRNA whose predicted targets are significantly enriched in the Knowledgebase for Addiction Related Genes (ARG) database (KARG; http://karg.cbi.pku.edu.cn). This small non-coding RNA is also highly expressed within the nucleus accumbens (NAc), a pivotal brain region underlying reward and motivation. Using luciferase reporter assays, we found that miR-495 directly targeted the 3′UTRs of Bdnf, Camk2a and Arc. Furthermore, we measured miR-495 expression in response to acute cocaine in mice and found that it is downregulated rapidly and selectively in the NAc, along with concomitant increases in ARG expression. Lentiviral-mediated miR-495 overexpression in the NAc shell (NAcsh) not only reversed these cocaine-induced effects but also downregulated multiple ARG mRNAs in specific SUD-related biological pathways, including those that regulate synaptic plasticity. miR-495 expression was also downregulated in the NAcsh of rats following cocaine self-administration. Most importantly, we found that NAcsh miR-495 overexpression suppressed the motivation to self-administer and seek cocaine across progressive ratio, extinction and reinstatement testing, but had no effect on food reinforcement, suggesting that miR-495 selectively affects addiction-related behaviors. Overall, our in silico search for post-transcriptional regulators identified miR-495 as a novel regulator of multiple ARGs that have a role in modulating motivation for cocaine.

Institutions, the rules of the game that shape repeated human interactions, clearly play a critical role in helping groups avoid the inefficient use of shared resources such as fisheries, freshwater, and the assimilative capacity of the environment. Institutions, however, are intimately intertwined with the human, social, and biophysical context within which they operate. Scholars typically are careful to take this context into account when studying institutions and Ostrom’s Institutional Design Principles are a case in point. Scholars have tested whether Ostrom’s Design Principles, which specify broad relationships between institutional arrangements and context, actually support successful governance of shared resources. This article further contributes to this line of research by leveraging the notion of institutional design to outline a research trajectory focused on coupled infrastructure systems in which institutions are seen as one class of infrastructure among many that dynamically interact to produce outcomes over time.

The surprisingly large value of r, the ratio of power in tensor to scalar density perturbations in the CMB reported by the BICEP2 Collaboration, if confirmed, provides strong evidence for Inflation at the GUT scale. While the Inflationary signal remains the best motivated source, a large value of r alone would still allow for the possibility that a comparable gravitational wave background might result from a self ordering scalar field (SOSF) transition that takes place later at somewhat lower energy. We find that even without detailed considerations of the predicted BICEP signature of such a transition, simple existing limits on the isocurvature contribution to CMB anisotropies would definitively rule out a contribution of more than 5% to r = 0.2. We also present a general relation for the allowed fractional SOSF contribution to r as a function of the ultimate measured value of r. These results point strongly not only to an inflationary origin of the BICEP2 signal, if confirmed, but also to the fact that if the GUT scale is of order 10¹⁶ GeV then either the GUT transition happens before Inflation or the Inflationary transition and the GUT transition must be one and the same.

Is the mirror neuron system (MNS) used in language understanding? According to embodied accounts of language comprehension, understanding sentences describing actions makes use of neural mechanisms of action control, including the MNS. Consequently, repeatedly comprehending sentences describing similar actions should induce adaptation of the MNS thereby warping its use in other cognitive processes such as action recognition and prediction. To test this prediction, participants read blocks of multiple sentences where each sentence in the block described transfer of objects in a direction away or toward the reader. Following each block, adaptation was measured by having participants predict the end-point of videotaped actions. The adapting sentences disrupted prediction of actions in the same direction, but (a) only for videos of biological motion, and (b) only when the effector implied by the language (e.g., the hand) matched the videos. These findings are signatures of the MNS.

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format.

We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties.

Megacities are major sources of anthropogenic fossil fuel CO₂(FFCO₂) emissions. The spatial extents of these large urban systems cover areas of 10 000 km² or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO₂ emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO₂ emission product, Hestia-LA, to simulate atmospheric CO₂ concentrations across the LA megacity at spatial resolutions as fine as  ∼  1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO₂ emission products to evaluate the impact of the spatial resolution of the CO₂ emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO₂ concentrations. We find that high spatial resolution in the fossil fuel CO₂ emissions is more important than in the atmospheric model to capture CO₂ concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO₂ fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO₂ fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO₂ concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO₂ emissions monitoring in the LA megacity requires FFCO₂ emissions modelling with  ∼1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.

Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration.

Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings.

Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.

Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.