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  1. Free, publicly-accessible full text available July 1, 2023
  2. Unmanned aerial vehicles (UAVs) equipped with multispectral sensors offer high spatial and temporal resolution imagery for monitoring crop stress at early stages of development. Analysis of UAV-derived data with advanced machine learning models could improve real-time management in agricultural systems, but guidance for this integration is currently limited. Here we compare two deep learning-based strategies for early warning detection of crop stress, using multitemporal imagery throughout the growing season to predict field-scale yield in irrigated rice in eastern Arkansas. Both deep learning strategies showed improvements upon traditional statistical learning approaches including linear regression and gradient boosted decision trees. First, wemore »explicitly accounted for variation across developmental stages using a 3D convolutional neural network (CNN) architecture that captures both spatial and temporal dimensions of UAV images from multiple time points throughout one growing season. 3D-CNNs achieved low prediction error on the test set, with a Root Mean Squared Error (RMSE) of 8.8% of the mean yield. For the second strategy, a 2D-CNN, we considered only spatial relationships among pixels for image features acquired during a single flyover. 2D-CNNs trained on images from a single day were most accurate when images were taken during booting stage or later, with RMSE ranging from 7.4 to 8.2% of the mean yield. A primary benefit of convolutional autoencoder-like models (based on analyses of prediction maps and feature importance) is the spatial denoising effect that corrects yield predictions for individual pixels based on the values of vegetation index and thermal features for nearby pixels. Our results highlight the promise of convolutional autoencoders for UAV-based yield prediction in rice.« less
    Free, publicly-accessible full text available March 10, 2023
  3. Quorum sensing (QS) is a process of chemical communication bacteria use to transition between individual and collective behaviors. QS depends on the production, release, and synchronous response to signaling molecules called autoinducers (AIs). The marine bacterium Vibrio harveyi monitors AIs using a signal transduction pathway that relies on five small regulatory RNAs (called Qrr1-5) that post-transcriptionally control target genes. Curiously, the small RNAs largely function redundantly making it difficult to understand the necessity for five of them. Here, we identify LuxT as a transcriptional repressor of qrr1. LuxT does not regulate qrr2-5, demonstrating that qrr genes can be independently controlledmore »to drive unique downstream QS gene expression patterns. LuxT reinforces its control over the same genes it regulates indirectly via repression of qrr1, through a second transcriptional control mechanism. Genes dually regulated by LuxT specify public goods including an aerolysin-type pore-forming toxin. Phylogenetic analyses reveal that LuxT is conserved among Vibrionaceae and sequence comparisons predict that LuxT represses qrr1 in additional species. The present findings reveal that the QS regulatory RNAs can carry out both shared and unique functions to endow bacteria with plasticity in their output behaviors.« less
  4. Helium implantation in surfaces is of interest for plasma-facing materials and other nuclear applications. Vanadium as both a representative bcc material and a material relevant for fusion applications is implanted using a Helium ion beam microscope, and the resulting swelling and nanomechanical properties are quantifed. These values are put in correlation to data obtained from micro-residual stress measurements using a focused ion beam-based ring-core technique. We found that the swelling measured is similar to literature values. Further, we are able to measure the surface stress caused by the implantation and fnd that it approaches the yield strength of the materialmore »at blistering doses. The simple calculations performed in the present work, along with several geometrical considerations deduced from experimental results confrm the driving force for blister formation comes from bulging resulting mainly from gas pressure buildup, rather than solely stress-induced buckling« less
  5. Engineering design is often used to teach science, but not-yet leads to solid learning gains. We examined the relationship between science learning and engineering design using text mining. Association rule mining was applied to texts written during design to extract the relationships between solar-energy concepts and solar design performance. Findings suggest that students test concept-related factors’ effects on design outcomes to learn concepts and eliminate misconceptions. These findings have implications for future instructional design.
  6. Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hardmore »scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.« less
    Free, publicly-accessible full text available December 1, 2023