Training the Foot Soldiers of Inquiry: Development and Evaluation of a Graduate Teaching Assistant Learning Community

As part of a Howard Hughes Program for Innovation in Science Education grant at Iowa State University, a series of interdisciplinary graduate teaching assistant learning communities (TALC) were developed. The purpose of these communities was to create an environment to facilitate teaching assistants\u27 pedagogical development and training to enhance the implementation of inquiry experiences in the undergraduate laboratories. The TALC evaluated in this study were held for two consecutive semesters and included teaching assistants who facilitated multi-week course-based research experiences in their respective STEM courses. Topics discussed during the TALC were based on the teaching assistants\u27 concerns related to teaching this type of course. Evaluation consisted of weekly reflection responses, a pre- and post-survey of instructional methods they consider to facilitate inquiry, pre-post definitions of inquiry-based instruction, and end-of-semester evaluations of the learning community experiences. This article outlines the development of the TALC and findings from the various forms of evaluation. [ABSTRACT FROM AUTHOR

Overlap of heritable influences between Cannabis Use Disorder, frequency of use and opportunity to use cannabis: Trivariate twin modelling and implications for genetic design

Background: The genetic component of Cannabis Use Disorder may overlap with influences acting more generally on early stages of cannabis use. This paper aims to determine the extent to which genetic influences on the development of cannabis abuse/dependence are correlated with those acting on the opportunity to use cannabis and frequency of use. Methods: A cross-sectional study of 3303 Australian twins, measuring age of onset of cannabis use opportunity, lifetime frequency of cannabis use, and lifetime DSM-IV cannabis abuse/dependence. A trivariate Cholesky decomposition estimated additive genetic (A), shared environment (C) and unique environment (E) contributions to the opportunity to use cannabis, the frequency of cannabis use, cannabis abuse/dependence, and the extent of overlap between genetic and environmental factors associated with each phenotype. Results: Variance components estimates were A = 0.64 [95% confidence interval (CI) 0.58–0.70] and E = 0.36 (95% CI 0.29–0.42) for age of opportunity to use cannabis, A = 0.74 (95% CI 0.66–0.80) and E = 0.26 (95% CI 0.20–0.34) for cannabis use frequency, and A = 0.78 (95% CI 0.65–0.88) and E = 0.22 (95% CI 0.12–0.35) for cannabis abuse/dependence. Opportunity shares 45% of genetic influences with the frequency of use, and only 17% of additive genetic influences are unique to abuse/dependence from those acting on opportunity and frequency. Conclusions: There are significant genetic contributions to lifetime cannabis abuse/dependence, but a large proportion of this overlaps with influences acting on opportunity and frequency of use. Individuals without drug use opportunity are uninformative, and studies of drug use disorders must incorporate individual exposure to accurately identify aetiology

Rapid response tools and datasets for post-fire modeling: linking Earth Observations and process-based hydrological models to support post-fire remediation

Preparation is key to utilizing Earth Observations and process-based models to support post-wildfire mitigation. Post-fire flooding and erosion can pose a serious threat to life, property and municipal water supplies. Increased runoff and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern. Remediation plans and treatments must be developed and implemented before the first major storms in order to be effective. One of the primary sources of information for making remediation decisions is a soil burn severity map derived from Earth Observation data (typically Landsat) that reflects fire induced changes in vegetation and soil properties. Slope, soils, land cover and climate are also important parameters that need to be considered. Spatially-explicit process-based models can account for these parameters, but they are currently under-utilized relative to simpler, lumped models because they are difficult to set up and require spatially-explicit inputs (digital elevation models, soils, and land cover). Our goal is to make process-based models more accessible by preparing spatial inputs before a fire, so that datasets can be rapidly combined with soil burn severity maps and formatted for model use. We are building an online database (http://geodjango.mtri.org/geowepp /) for the continental United States that will allow users to upload soil burn severity maps. The soil burn severity map is combined with land cover and soil datasets to generate the spatial model inputs needed for hydrological modeling of burn scars. Datasets will be created to support hydrological models, post-fire debris flow models and a dry ravel model. Our overall vision for this project is that advanced GIS surface erosion and mass failure prediction tools will be readily available for post-fire analysis using spatial information from a single online site

Modeling, Reduction, and Control of a Helically Actuated Inertial Soft Robotic Arm via the Koopman Operator

Soft robots promise improved safety and capability over rigid robots when deployed in complex, delicate, and dynamic environments. However, the infinite degrees of freedom and highly nonlinear dynamics of these systems severely complicate their modeling and control. As a step toward addressing this open challenge, we apply the data-driven, Hankel Dynamic Mode Decomposition (HDMD) with time delay observables to the model identification of a highly inertial, helical soft robotic arm with a high number of underactuated degrees of freedom. The resulting model is linear and hence amenable to control via a Linear Quadratic Regulator (LQR). Using our test bed device, a dynamic, lightweight pneumatic fabric arm with an inertial mass at the tip, we show that the combination of HDMD and LQR allows us to command our robot to achieve arbitrary poses using only open loop control. We further show that Koopman spectral analysis gives us a dimensionally reduced basis of modes which decreases computational complexity without sacrificing predictive power.Comment: Submitted to IEEE International Conference on Robotics and Automation, 202

3D Determination of Area-at-Risk in Acute Myocardial Infarction

MRI methods for acute myocardial infarctio

Chronic cigarette smoking is linked with structural alterations in brain regions showing acute nicotinic drug-induced functional modulations

Background Whereas acute nicotine administration alters brain function which may, in turn, contribute to enhanced attention and performance, chronic cigarette smoking is linked with regional brain atrophy and poorer cognition. However, results from structural magnetic resonance imaging (MRI) studies comparing smokers versus nonsmokers have been inconsistent and measures of gray matter possess limited ability to inform functional relations or behavioral implications. The purpose of this study was to address these interpretational challenges through meta-analytic techniques in the service of clarifying the impact of chronic smoking on gray matter integrity and more fully contextualizing such structural alterations. Methods We first conducted a coordinate-based meta-analysis of structural MRI studies to identify consistent structural alterations associated with chronic smoking. Subsequently, we conducted two additional meta-analytic assessments to enhance insight into potential functional and behavioral relations. Specifically, we performed a multimodal meta-analytic assessment to test the structural?functional hypothesis that smoking-related structural alterations overlapped those same regions showing acute nicotinic drug-induced functional modulations. Finally, we employed database driven tools to identify pairs of structurally impacted regions that were also functionally related via meta-analytic connectivity modeling, and then delineated behavioral phenomena associated with such functional interactions via behavioral decoding. Results Across studies, smoking was associated with convergent structural decreases in the left insula, right cerebellum, parahippocampus, multiple prefrontal cortex (PFC) regions, and the thalamus. Indicating a structural?functional relation, we observed that smoking-related gray matter decreases overlapped with the acute functional effects of nicotinic agonist administration in the left insula, ventromedial PFC, and mediodorsal thalamus. Suggesting structural-behavioral implications, we observed that the left insula?s task-based, functional interactions with multiple other structurally impacted regions were linked with pain perception, the right cerebellum?s interactions with other regions were associated with overt body movements, interactions between the parahippocampus and thalamus were linked with memory processes, and interactions between medial PFC regions were associated with face processing. Conclusions Collectively, these findings emphasize brain regions (e.g., ventromedial PFC, insula, thalamus) critically linked with cigarette smoking, suggest neuroimaging paradigms warranting additional consideration among smokers (e.g., pain processing), and highlight regions in need of further elucidation in addiction (e.g., cerebellum). Electronic supplementary material The online version of this article (doi:10.1186/s12993-016-0100-5) contains supplementary material, which is available to authorized users

Integrated Geothermal-CO2 Reservoir Systems: Reducing Carbon Intensity through Sustainable Energy Production and Secure CO2 Storage

AbstractLarge-scale geologic CO2 storage (GCS) can be limited by overpressure, while geothermal energy production is often limited by pressure depletion. We investigate how synergistic integration of these complementary systems may enhance the viability of GCS by relieving overpressure, which reduces pore-space competition, the Area of Review, and the risks of CO2 leakage and induced seismicity, and by producing geothermal energy and water, which can defray parasitic energy and water costs of CO2 capture

Extreme deuterium enrichment in stratospheric hydrogen and the global atmospheric budget of H_2

Molecular hydrogen (H_2) is the second most abundant trace gas in the atmosphere after methane (CH_4). In the troposphere, the D/H ratio of H_2 is enriched by 120‰ relative to the world's oceans. This cannot be explained by the sources of H_2 for which the D/H ratio has been measured to date (for example, fossil fuels and biomass burning). But the isotopic composition of H_2 from its single largest source—the photochemical oxidation of methane—has yet to be determined. Here we show that the D/H ratio of stratospheric H2 develops enrichments greater than 440‰, the most extreme D/H enrichment observed in a terrestrial material. We estimate the D/H ratio of H_2 produced from CH_4 in the stratosphere, where production is isolated from the influences of non-photochemical sources and sinks, showing that the chain of reactions producing H_2 from CH_4 concentrates D in the product H_2. This enrichment, which we estimate is similar on a global average in the troposphere, contributes substantially to the D/H ratio of tropospheric H_2