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  1. Fallen logs acting as a seedbed for trees to aid the regeneration of vegetation is a common ecological strategy in modern forests. However, the origin, occurrence, and evolution of this nurse log strategy in the geological time is unclear. Here we report a ca. 310-millionyear-old permineralized cordaitalean tree trunk from the Moscovian (Pennsylvanian, upper Carboniferous) Benxi Formation in Yangquan City, Shanxi Province, North China, with evidence of probable cordaitalean rootlets growing inside the trunk. The specimen is interpreted as a nurse log for regeneration of cordaitaleans in coastal lowlands. It provides the first glimpse of plant-plant facilitative interaction between Pennsylvanian cordaitaleans in Cathaysia. We interpret that the Moscovian cordaitalean seedlings preferentially established on the fallen log owing to the ability of the rotting wood to store fresh water. The nurse log provided a stable substrate in an environment with episodic salinity and/or water table variations. In combination with previous records, it is suggested that a sophisticated terrestrial ecosystem with multiple interactions between plants and other organisms have developed on the central North China Craton no later than the Middle Pennsylvanian. 
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    Free, publicly-accessible full text available August 31, 2024
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  4. Liu, H. ; Yin, Z. ; Liu, L. ; Jiang, L. ; Gu, G. ; Wu, X. ; Ren, W. (Ed.)
    Variable stiffness grippers can adapt to objects with different shapes and gripping forces. This paper presents a novel variable stiffness gripper (VSG) based on the Fin Ray effect that can adjust stiffness discretely. The main structure of the gripper includes the compliant frame, rotatable ribs, and the position limit components attached to the compliant frame. The stiffness of the gripper can be adjusted by rotating the specific ribs in the frame. There are four configurations for the gripper that were developed in this research: a) all ribs OFF (Flex) mode; b) upper ribs ON and lower ribs OFF (Hold) mode; c) upper ribs OFF and lower ribs ON (Pinch) mode; d) all ribs ON (Clamp) mode. Different configurations can provide various stiffness for the gripper’s finger to adapt the objects with different shapes and weights. To optimize the design, the stiffness analysis under various configurations and force conditions was implemented by finite element analysis (FEA). The 3-D printed prototypes were constructed to verify the feature and performance of the design concept of the VSG compared with the FEA results. The design of the VSG provides a novel idea for industrial robots and collaborative robots on adaptive grasping. 
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  5. 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, we 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. 
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  6. Tensegrity robots, which are composed of compressive elements (rods) and flexible tensile elements (e.g., cables), have a variety of advantages, including flexibility, low weight, and resistance to mechanical impact. Nevertheless, the hybrid soft-rigid nature of these robots also complicates the ability to localize and track their state. This work aims to address what has been recognized as a grand challenge in this domain, i.e., the state estimation of tensegrity robots through a markerless, vision-based method, as well as novel, onboard sensors that can measure the length of the robot's cables. In particular, an iterative optimization process is proposed to track the 6-DoF pose of each rigid element of a tensegrity robot from an RGB-D video as well as endcap distance measurements from the cable sensors. To ensure that the pose estimates of rigid elements are physically feasible, i.e., they are not resulting in collisions between rods or with the environment, physical constraints are introduced during the optimization. Real-world experiments are performed with a 3-bar tensegrity robot, which performs locomotion gaits. Given ground truth data from a motion capture system, the proposed method achieves less than 1~cm translation error and 3 degrees rotation error, which significantly outperforms alternatives. At the same time, the approach can provide accurate pose estimation throughout the robot's motion, while motion capture often fails due to occlusions. 
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  7. null (Ed.)
    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 controlled 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. 
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