Large, long range tensile forces drive convergence during

Indirect evidence suggests that blastopore closure during gastrulation of anamniotes, including amphibians such as Xenopus laevis, depends on circumblastoporal convergence forces generated by the marginal zone (MZ), but direct evidence is lacking. We show that explanted MZs generate tensile convergence forces up to 1.5 mN during gastrulation and over 4 mN thereafter. These forces are generated by convergent thickening (CT) until the midgastrula and increasingly by convergent extension (CE) thereafter. Explants from ventralized embryos, which lack tissues expressing CE but close their blastopores, produce up to 2 mN of tensile force, showing that CT alone generates forces sufficient to close the blastopore. Uniaxial tensile stress relaxation assays show stiffening of mesodermal and ectodermal tissues around the onset of neurulation, potentially enhancing long-range transmission of convergence forces. These results illuminate the mechanobiology of early vertebrate morphogenic mechanisms, aid interpretation of phenotypes, and give insight into the evolution of blastopore closure mechanisms. © Shook et al

Transportability without positivity: a synthesis of statistical and simulation modeling

When estimating an effect of an action with a randomized or observational study, that study is often not a random sample of the desired target population. Instead, estimates from that study can be transported to the target population. However, transportability methods generally rely on a positivity assumption, such that all relevant covariate patterns in the target population are also observed in the study sample. Strict eligibility criteria, particularly in the context of randomized trials, may lead to violations of this assumption. Two common approaches to address positivity violations are restricting the target population and restricting the relevant covariate set. As neither of these restrictions are ideal, we instead propose a synthesis of statistical and simulation models to address positivity violations. We propose corresponding g-computation and inverse probability weighting estimators. The restriction and synthesis approaches to addressing positivity violations are contrasted with a simulation experiment and an illustrative example in the context of sexually transmitted infection testing uptake. In both cases, the proposed synthesis approach accurately addressed the original research question when paired with a thoughtfully selected simulation model. Neither of the restriction approaches were able to accurately address the motivating question. As public health decisions must often be made with imperfect target population information, model synthesis is a viable approach given a combination of empirical data and external information based on the best available knowledge

Introduction to Big Data Computing for Geospatial Applications

The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization. This special issue highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates the opportunities for using big data for geospatial applications. Crucial to the advancements highlighted here is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms. This editorial first introduces the background and motivation of this special issue followed by an overview of the ten included articles. Conclusion and future research directions are provided in the last section

Spectral aerosol extinction (SpEx): a new instrument for in situ ambient aerosol extinction measurements across the UV/visible wavelength range

We introduce a new instrument for the measurement of in situ ambient aerosol extinction over the 300– 700 nm wavelength range, the spectral aerosol extinction (SpEx) instrument. This measurement capability is envisioned to complement existing in situ instrumentation, allowing for simultaneous measurement of the evolution of aerosol optical, chemical, and physical characteristics in the ambient environment. In this work, a detailed description of the instrument is provided along with characterization tests performed in the laboratory. Measured spectra of NO2 and polystyrene latex spheres (PSLs) agreed well with theoretical calculations. Good agreement was also found with simultaneous aerosol extinction measurements at 450, 530, and 630 nm using CAPS PMex instruments in a series of 22 tests including nonabsorbing compounds, dusts, soot, and black and brown carbon analogs. SpEx measurements are expected to help identify the presence of ambient brown carbon due to its 300 nm lower wavelength limit compared to measurements limited to longer UV and visible wavelengths. Extinction spectra obtained with SpEx contain more information than can be conveyed by a simple power law fit (typically represented by Ångström exponents). Planned future improvements aim to lower detection limits and ruggedize the instrument for mobile operation

Observational evidence for the convective transport of dust over the central United States

Bulk aerosol composition and aerosol size distributions measured aboard the DC-8 aircraft during the Deep Convective Clouds and Chemistry Experiment mission in May/June 2012 were used to investigate the transport of mineral dust through nine storms encountered over Colorado and Oklahoma. Measurements made at low altitudes (\u3c5 km mean sea level (MSL)) in the storm inflow region were compared to those made in cirrus anvils (altitude \u3e 9 km MSL). Storm mean outflow Ca2+ mass concentrations and total coarse (1 µm \u3c diameter \u3c 5 µm) aerosol volume (Vc) were comparable to mean inflow values as demonstrated by average outflow/inflow ratios greater than 0.5. A positive relationship between Ca2+, Vc, ice water content, and large (diameter \u3e 50 µm) ice particle number concentrations was not evident; thus, the influence of ice shatter on these measurements was assumed small. Mean inflow aerosol number concentrations calculated over a diameter range (0.5 µm \u3c diameter \u3c 5.0 µm) relevant for proxy ice nuclei (NPIN) were ~15–300 times higher than ice particle concentrations for all storms. Ratios of predicted interstitial NPIN (calculated as the difference between inflow NPIN and ice particle concentrations) and inflow NPIN were consistent with those calculated for Ca2+ and Vc and indicated that on average less than 10% of the ingested NPIN were activated as ice nuclei during anvil formation. Deep convection may therefore represent an efficient transport mechanism for dust to the upper troposphere where these particles can function as ice nuclei cirrus forming in situ

Methodological Issues of Spatial Agent-Based Models

Agent based modeling (ABM) is a standard tool that is useful across many disciplines. Despite widespread and mounting interest in ABM, even broader adoption has been hindered by a set of methodological challenges that run from issues around basic tools to the need for a more complete conceptual foundation for the approach. After several decades of progress, ABMs remain difficult to develop and use for many students, scholars, and policy makers. This difficulty holds especially true for models designed to represent spatial patterns and processes across a broad range of human, natural, and human-environment systems. In this paper, we describe the methodological challenges facing further development and use of spatial ABM (SABM) and suggest some potential solutions from multiple disciplines. We first define SABM to narrow our object of inquiry, and then explore how spatiality is a source of both advantages and challenges. We examine how time interacts with space in models and delve into issues of model development in general and modeling frameworks and tools specifically. We draw on lessons and insights from fields with a history of ABM contributions, including economics, ecology, geography, ecology, anthropology, and spatial science with the goal of identifying promising ways forward for this powerful means of modeling

Spatial video geonarratives and health: case studies in post-disaster recovery, crime, mosquito control and tuberculosis in the homeless

A call has recently been made by the public health and medical communities to understand the neighborhood context of a patient’s life in order to improve education and treatment. To do this, methods are required that can collect “contextual” characteristics while complementing the spatial analysis of more traditional data. This also needs to happen within a standardized, transferable, easy-to-implement framework. The Spatial Video Geonarrative (SVG) is an environmentally-cued narrative where place is used to stimulate discussion about fine-scale geographic characteristics of an area and the context of their occurrence. It is a simple yet powerful approach to enable collection and spatial analysis of expert and resident health-related perceptions and experiences of places. Participants comment about where they live or work while guiding a driver through the area. Four GPS-enabled cameras are attached to the vehicle to capture the places that are observed and discussed by the participant. Audio recording of this narrative is linked to the video via time stamp. A program (G-Code) is then used to geotag each word as a point in a geographic information system (GIS). Querying and density analysis can then be performed on the narrative text to identify spatial patterns within one narrative or across multiple narratives. This approach is illustrated using case studies on post-disaster psychopathology, crime, mosquito control, and TB in homeless populations. SVG can be used to map individual, group, or contested group context for an environment. The method can also gather data for cohorts where traditional spatial data are absent. In addition, SVG provides a means to spatially capture, map and archive institutional knowledge. SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses. SVG can also be used to gain near-real time insight therefore supporting applied interventions. Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.https://doi.org/10.1186/s12942-015-0014-

Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD Working Groups

Objective Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders. Methods Structural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures). Results We found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed. Conclusion Our findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders

A computational approach to understanding spatial and temporal granularities in agent-based modeling

Epidemic agent-based models simulate individuals in artificial societies capable of moving, interacting, and transmitting disease amongst themselves. Due to limitations in data and computation, epidemic models simulating tens of millions of individuals often coarsen the finest representations of space and time–termed spatial and temporal granularities in this thesis. This dissertation examines and overcomes a set of computational challenges to investigate a fundamental problem in spatially explicit epidemic agent-based modeling. This research demonstrates that coarsening spatial and temporal granularities influence both computational tractability and epidemic ABM processes. By focusing on the nexus of space, time, and process my dissertation improves understanding of the interrelationships and trade-offs between space and time as they relate to spatial processes using an epidemic modeling case study