Pereira, Talmo D.; Aldarondo, Diego E.; Willmore, Lindsay; Kislin, Mikhail; Wang, Samuel S.-H.; Murthy, Mala; Shaevitz, Joshua W.
Abstract:
Recent work quantifying postural dynamics has attempted to define the repertoire of behaviors performed by an animal. However, a major drawback to these techniques has been their reliance on dimensionality reduction of images which destroys information about which parts of the body are used in each behavior. To address this issue, we introduce a deep learning-based method for pose estimation, LEAP (LEAP Estimates Animal Pose). LEAP automatically predicts the positions of animal body parts using a deep convolutional neural network with as little as 10 frames of labeled data for training. This framework consists of a graphical interface for interactive labeling of body parts and software for training the network and fast prediction on new data (1 hr to train, 185 Hz predictions). We validate LEAP using videos of freely behaving fruit flies (Drosophila melanogaster) and track 32 distinct points on the body to fully describe the pose of the head, body, wings, and legs with an error rate of <3% of the animal's body length. We recapitulate a number of reported findings on insect gait dynamics and show LEAP's applicability as the first step in unsupervised behavioral classification. Finally, we extend the method to more challenging imaging situations (pairs of flies moving on a mesh-like background) and movies from freely moving mice (Mus musculus) where we track the full conformation of the head, body, and limbs.
Geochemical and geomechanical perturbations of the subsurface caused by the injection of fluids present the risk of leakage and seismicity. This study investigated how flow of acidic fluids affects hydraulic and frictional properties of fractures using experiments with 3.8 cm-long specimens of Eagle Ford shale, a laminated shale with carbonate-rich strata. In low-pressure flow cells, one set of samples was exposed to an acidic brine and another set was exposed to a neutral brine. X-ray computed tomography and x-ray fluorescence analysis revealed that samples exposed to the acidic brine were calcite-depleted and had developed a porous altered layer, while the other set showed little evidence of alteration. After reaction, samples were compacted and sheared in a triaxial cell that supplied normal stress and differential pore pressure at prescribed sliding velocities, independently measuring friction and permeability. During the initial compaction, the porous altered layer collapsed into fine particles that filled the fracture aperture. This effectively impeded flow and sealed the fracture, resulting in a decrease in fracture permeability by 1 to 2 orders of magnitude relative to the compressed unaltered fractures. During shear, the collapsed layer of fine-grained particles prevented the formation of interlocking micro-asperities resulting in lower frictional strength. With regard to subsurface risks, this study showcases how coupled geochemical and geomechanical processes could favorably seal fractures to inhibit leakage, but also could increase the likelihood of induced seismicity. These findings have important implications for geological carbon sequestration, pressurized fluid energy storage, geothermal energy, and other subsurface technologies.
