29 research outputs found

    LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery

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    We introduce LOTUS, a continual imitation learning algorithm that empowers a physical robot to continuously and efficiently learn to solve new manipulation tasks throughout its lifespan. The core idea behind LOTUS is constructing an ever-growing skill library from a sequence of new tasks with a small number of human demonstrations. LOTUS starts with a continual skill discovery process using an open-vocabulary vision model, which extracts skills as recurring patterns presented in unsegmented demonstrations. Continual skill discovery updates existing skills to avoid catastrophic forgetting of previous tasks and adds new skills to solve novel tasks. LOTUS trains a meta-controller that flexibly composes various skills to tackle vision-based manipulation tasks in the lifelong learning process. Our comprehensive experiments show that LOTUS outperforms state-of-the-art baselines by over 11% in success rate, showing its superior knowledge transfer ability compared to prior methods. More results and videos can be found on the project website: https://ut-austin-rpl.github.io/Lotus/.Comment: ICRA 202

    Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients

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    Analysis linking directly genomics, neuroimaging phenotypes and clinical measurements is crucial for understanding psychiatric disorders, but remains rare. Here, we describe a multi-scale analysis using genome-wide SNPs, gene-expression, grey matter volume (GMV) and the Positive and Negative Syndrome Scale scores (PANSS) to explore the etiology of schizophrenia. With 72 drug-naive schizophrenic first episode patients (FEPs) and 73 matched heathy controls, we identified 108 genes, from schizophrenia risk genes, that correlated significantly with GMV, which are highly co-expressed in the brain during development. Among these 108 candidates, 19 distinct genes were found associated with 16 brain regions referred to as hot clusters (HCs), primarily in the frontal cortex, sensory-motor regions and temporal and parietal regions. The patients were subtyped into three groups with distinguishable PANSS scores by the GMV of the identified HCs. Furthermore, we found that HCs with common GMV among patient groups are related to genes that mostly mapped to pathways relevant to neural signaling, which are associated with the risk for schizophrenia. Our results provide an integrated view of how genetic variants may affect brain structures that lead to distinct disease phenotypes. The method of multi-scale analysis that was described in this research, may help to advance the understanding of the etiology of schizophrenia

    UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy

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    In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up objects in high-quality and diverse ways and generalize across hundreds of categories and even the unseen. Inspired by successful pipelines used in parallel gripper grasping, we split the task into two stages: 1) grasp proposal (pose) generation and 2) goal-conditioned grasp execution. For the first stage, we propose a novel probabilistic model of grasp pose conditioned on the point cloud observation that factorizes rotation from translation and articulation. Trained on our synthesized large-scale dexterous grasp dataset, this model enables us to sample diverse and high-quality dexterous grasp poses for the object point cloud.For the second stage, we propose to replace the motion planning used in parallel gripper grasping with a goal-conditioned grasp policy, due to the complexity involved in dexterous grasping execution. Note that it is very challenging to learn this highly generalizable grasp policy that only takes realistic inputs without oracle states. We thus propose several important innovations, including state canonicalization, object curriculum, and teacher-student distillation. Integrating the two stages, our final pipeline becomes the first to achieve universal generalization for dexterous grasping, demonstrating an average success rate of more than 60\% on thousands of object instances, which significantly outperforms all baselines, meanwhile showing only a minimal generalization gap.Comment: Accepted to CVPR 202

    Construction of a ternary component chip with enhanced desorption efficiency for laser desorption/ionization mass spectrometry based metabolic fingerprinting

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    Introduction:In vitro metabolic fingerprinting encodes diverse diseases for clinical practice, while tedious sample pretreatment in bio-samples has largely hindered its universal application. Designed materials are highly demanded to construct diagnostic tools for high-throughput metabolic information extraction.Results: Herein, a ternary component chip composed of mesoporous silica substrate, plasmonic matrix, and perfluoroalkyl initiator is constructed for direct metabolic fingerprinting of biofluids by laser desorption/ionization mass spectrometry.Method: The performance of the designed chip is optimized in terms of silica pore size, gold sputtering time, and initiator loading parameter. The optimized chip can be coupled with microarrays to realize fast, high-throughput (∼second/sample), and microscaled (∼1 μL) sample analysis in human urine without any enrichment or purification. On-chip urine fingerprints further allow for differentiation between kidney stone patients and healthy controls.Discussion: Given the fast, high throughput, and easy operation, our approach brings a new dimension to designing nano-material-based chips for high-performance metabolic analysis and large-scale diagnostic use

    Long-term follow-up observations of extreme coronal line emitting galaxies

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    We present new spectroscopic and photometric follow-up observations of the known sample of extreme coronal line emitting galaxies (ECLEs) identified in the Sloan Digital Sky Survey (SDSS). With these new data, observations of the ECLE sample now span a period of two decades following their initial SDSS detections. We confirm the nonrecurrence of the iron coronal line signatures in five of the seven objects, further supporting their identification as the transient light echoes of tidal disruption events (TDEs). Photometric observations of these objects in optical bands show little overall evolution. In contrast, mid-infrared (MIR) observations show ongoing long-term declines. The remaining two objects had been classified as active galactic nuclei (AGN) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up spectra. We confirm this classification, with our spectra continuing to show the presence of strong, unchanged coronal-line features and AGN-like MIR colours and behaviour. We have constructed spectral templates of both subtypes of ECLE to aid in distinguishing the likely origin of newly discovered ECLEs. We highlight the need for higher cadence, and more rapid, follow-up observations of such objects to better constrain their properties and evolution. We also discuss the relationships between ECLEs, TDEs, and other identified transients having significant MIR variability.Comment: Submitted to MNRAS. 33 pages, 15 figure

    Long-term follow-up observations of extreme coronal line emitting galaxies

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    We present new spectroscopic and photometric follow-up observations of the known sample of extreme coronal line-emitting galaxies (ECLEs) identified in the Sloan Digital Sky Survey (SDSS). With these new data, observations of the ECLE sample now span a period of two decades following their initial SDSS detections. We confirm the non-recurrence of the iron coronal line signatures in five of the seven objects, further supporting their identification as the transient light echoes of tidal disruption events (TDEs). Photometric observations of these objects in optical bands show little overall evolution. In contrast, mid-infrared (MIR) observations show ongoing long-term declines consistent with power-law decay. The remaining two objects had been classified as active galactic nuclei (AGNs) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up spectra. We confirm this classification, with our spectra continuing to show the presence of strong, unchanged coronal line features and AGN-like MIR colours and behaviour. We have constructed spectral templates of both subtypes of ECLE to aid in distinguishing the likely origin of newly discovered ECLEs. We highlight the need for higher cadence, and more rapid, follow-up observations of such objects to better constrain their properties and evolution. We also discuss the relationships between ECLEs, TDEs, and other identified transients having significant MIR variability

    Low-Profile Broadband Patch-Driven Metasurface Antenna

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    Contact Resistance between Calcareous Sand and Electrodes Based on the Two-Electrode Method

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    In the process of measuring the resistivity of calcareous sand by the two-electrode method, the contact resistance between calcareous sand and electrodes is an unavoidable problem. In this paper, the effects of the particle size, relative density, current frequency, and saturation on the contact resistance of calcareous sand samples with different electrode spacings were studied. The results show that the larger the particle size and relative density are, the greater the contact resistance. The contact resistance decreases with an increasing current frequency, and the decreasing amplitude decreases with an increasing saturation. The contact resistance decreases with an increasing saturation. The relationship between the contact resistance and current frequency and saturation is established in this paper. When the two-electrode method is used to study the resistivity of calcareous sand, the influence of contact resistance should be considered, especially for samples with low saturation

    Effect of Mg content in the La3-xMgxNi9 battery anode alloys on the structural, hydrogen storage and electrochemical properties

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    The present work is focused on the studies of structure, hydrogen storage and electrochemical properties of the La3-xMgxNi9 (x = 1.0, 1.1 and 1.2) alloys as active materials of negative electrodes in the Nickel-Metal Hydride (Ni/MH) batteries. A change of Mg content affects properties of the studied alloys such as the phase homogeneity, hydrogen storage and electrochemical capacities, cycle stability, and high-rate discharge performance. X-ray diffraction study shows that Mg substitution for La and annealing of the La3-xMgxNi9 alloys promotes the formation of more homogeneous materials, with a predominant formation of the target AB3 PuNi3 structure type intermetallics. The electrodes prepared from the annealed alloys show the maximum discharge capacities of ∼400 mAh g−1 at discharge current density of ∼60 mA/g. The high rate discharge-abilities (HRD) at the discharge current density of 350 mA g−1 keep high values of the remaining reversible discharge capacities, ∼86, 85 and 80%, for the La2MgNi9, La1·9Mg1·1Ni9 and La1·8Mg1·2Ni9 alloy electrodes, respectively. After 200 cycles with 100% depth of discharge (DOD), the La1·9Mg1·1Ni9 alloy electrode exhibits a very good cycling stability with its discharge capacity remaining at a level of ∼64% of its initial capacity
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