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Background: Differences in core or tissue‐specific ribosomal protein (Rp) composition within ribosomes contribute to ribosome heterogeneity and functional variability. Yet, the degree to which ribosome heterogeneity modulates development is unknown. The Drosophila melanogaster eRpL22 family contains structurally diverse paralogues, eRpL22 and eRpL22‐like. Unlike ubiquitously expressed eRpL22, eRpL22‐like expression is tissue‐specific, notably within the male germline and the eye. We investigated expression within the developing eye to uncover tissue/cell types where specific paralogue roles might be defined. Results: Immunohistochemistry analysis confirms ubiquitous eRpL22 expression throughout eye development. In larvae, eRpL22‐like is ubiquitously expressed, but highly enriched in the peripodial epithelium (PE). In early pupae, eRpL22‐like is broadly distributed in multiple cell types, but later, is primarily enriched in interommatidial hair cells (IoHC). Adult patterns include the ring of accessory cells around ommatidia. Adult retinae IoHC patterning phenotypes (shown by scanning electron microscopy) may be linked to RNAi‐mediated eRpL22‐like depletion within larval PE. Immunoblots and polysome profile analyses show multiple variants of eRpL22‐like across development, with the variant at the expected molecular mass co‐sedimenting with active ribosomes. Conclusion: Our data reveal differential patterns of eRpL22‐like expression relative to eRpL22 and suggest a specific role for eRpL22‐like in developmental patterning of the eye. Key Findings: Ribosomal protein paralogues eRpL22 and eRpL22‐like are co‐expressed in the developing eye.eRpL22‐like expression patterns change depending on developmental stage.eRpL22‐like is enriched in the larval peripodial epithelium (PE), the pupal interommatidial hair cell (IoHC), and the ring of accessory cells in adult ommatidia.IoHC orientation and structural phenotypes in adult retinae may be associated with RNAi‐mediated depletion of eRpL22‐like within the PE of third instar larvae, suggesting a role for eRpL22‐like in IoHC patterning.Different molecular variants of eRpL22‐like are expressed at different development stages, but not all variants associate with ribosomal components. [ABSTRACT FROM AUTHOR]

Recent robotics efforts have automated simple, repetitive tasks to increase execution speed and lessen an operator's cognitive load, allowing them to focus on higher-level objectives. However, an autonomous system will eventually encounter something unexpected, and if this exceeds the tolerance of automated solutions there must be a way to fall back to teleoperation. Our solution is a largely autonomous system with the ability to determine when it is necessary to ask a human operator for guidance. We call this approach human-guided autonomy. Our design emphasizes human-on-the-loop control where an operator expresses a desired high-level goal for which the reasoning component assembles an appropriate chain of subtasks. We introduce our work in the context of the DARPA Robotics Challenge (DRC) Finals. We describe the software architecture Team TROOPER developed and used to control an Atlas humanoid robot. We employ perception, planning, and control automation for execution of subtasks. If subtasks fail, or if changing environmental conditions invalidate the planned subtasks, the system automatically generates a new task chain. The operator is able to intervene at any stage of execution, to provide input and adjustment to any control layer, enabling operator involvement to increase as confidence in automation decreases. We present our performance at the DRC Finals and a discussion about lessons learned. [ABSTRACT FROM AUTHOR]

Recent robotics efforts have automated simple, repetitive tasks to increase execution speed and lessen an operator's cognitive load, allowing them to focus on higher-level objectives. However, an autonomous system will eventually encounter something unexpected, and if this exceeds the tolerance of automated solutions, there must be a way to fall back to teleoperation. Our solution is a largely autonomous system with the ability to determine when it is necessary to ask a human operator for guidance. We call this approach human-guided autonomy. Our design emphasizes human-on-the-loop control where an operator expresses a desired high-level goal for which the reasoning component assembles an appropriate chain of subtasks. We introduce our work in the context of the DARPA Robotics Challenge (DRC) Finals. We describe the software architecture Team TROOPER developed and used to control an Atlas humanoid robot. We employ perception, planning, and control automation for execution of subtasks. If subtasks fail, or if changing environmental conditions invalidate the planned subtasks, the system automatically generates a new task chain. The operator is able to intervene at any stage of execution, to provide input and adjustment to any control layer, enabling operator involvement to increase as confidence in automation decreases. We present our performance at the DRC Finals and a discussion about lessons learned. [ABSTRACT FROM AUTHOR]