2-[(4-Chloro­phen­yl)(2-hy­droxy-5-oxo­cyclo­pent-1-en-1-yl)meth­yl]-3-hy­droxy­cyclo­pent-2-en-1-one

There are two mol­ecules in the asymmetric unit of the title compound, C17H15ClO4, in which the dihedral angles between the five-membered rings are 57.3 (1) and 51.4 (1)°. An intra­molecular O—H⋯O hydrogen bond occurs in each mol­ecule. In the crystal, O—H⋯O and C—H⋯O hydrogen bonds link the moleclues into chains along the b axis

Extension of the general unit hydrograph theory for the spread of salinity in estuaries

From both practical and theoretical perspectives, it is essential to be able to express observed salinity distributions in terms of simplified theoretical models, which enable qualitative assessments to be made in many problems concerning water resource utilization (such as intake of fresh water) in estuaries. In this study, we propose a general and analytical salt intrusion model inspired by Guo's general unit hydrograph theory for flood hydrograph prediction in a watershed. To derive a simple, general and analytical model of salinity distribution, we first make four hypotheses on the longitudinal salinity gradient based on empirical observations; we then derive a general unit hydrograph for the salinity distribution along a partially mixed or well-mixed estuary. The newly developed model can be well calibrated using a minimum of three salinity measurements along the estuary axis and does converge towards zero when the along-estuary distance approaches infinity asymptotically. The theory has been successfully applied to reproduce the salt intrusion in 21 estuaries worldwide, which suggests that the proposed method can be a useful tool for quickly assessing the spread of salinity under a wide range of riverine and tidal conditions and for quantifying the potential impacts of human-induced and natural changes.51979296; 52279080; 2019ZT08G090; 440001-2023-10716; LA/P/0069/2020info:eu-repo/semantics/publishedVersio

Learn to Grasp via Intention Discovery and its Application to Challenging Clutter

Humans excel in grasping objects through diverse and robust policies, many of which are so probabilistically rare that exploration-based learning methods hardly observe and learn. Inspired by the human learning process, we propose a method to extract and exploit latent intents from demonstrations, and then learn diverse and robust grasping policies through self-exploration. The resulting policy can grasp challenging objects in various environments with an off-the-shelf parallel gripper. The key component is a learned intention estimator, which maps gripper pose and visual sensory to a set of sub-intents covering important phases of the grasping movement. Sub-intents can be used to build an intrinsic reward to guide policy learning. The learned policy demonstrates remarkable zero-shot generalization from simulation to the real world while retaining its robustness against states that have never been encountered during training, novel objects such as protractors and user manuals, and environments such as the cluttered conveyor.Comment: Accepted to IEEE Robotics and Automation Letters (RA-L

Flipbot: Learning Continuous Paper Flipping via Coarse-to-Fine Exteroceptive-Proprioceptive Exploration

This paper tackles the task of singulating and grasping paper-like deformable objects. We refer to such tasks as paper-flipping. In contrast to manipulating deformable objects that lack compression strength (such as shirts and ropes), minor variations in the physical properties of the paper-like deformable objects significantly impact the results, making manipulation highly challenging. Here, we present Flipbot, a novel solution for flipping paper-like deformable objects. Flipbot allows the robot to capture object physical properties by integrating exteroceptive and proprioceptive perceptions that are indispensable for manipulating deformable objects. Furthermore, by incorporating a proposed coarse-to-fine exploration process, the system is capable of learning the optimal control parameters for effective paper-flipping through proprioceptive and exteroceptive inputs. We deploy our method on a real-world robot with a soft gripper and learn in a self-supervised manner. The resulting policy demonstrates the effectiveness of Flipbot on paper-flipping tasks with various settings beyond the reach of prior studies, including but not limited to flipping pages throughout a book and emptying paper sheets in a box.Comment: Accepted to International Conference on Robotics and Automation (ICRA) 202

ERRA: An Embodied Representation and Reasoning Architecture for Long-horizon Language-conditioned Manipulation Tasks

This letter introduces ERRA, an embodied learning architecture that enables robots to jointly obtain three fundamental capabilities (reasoning, planning, and interaction) for solving long-horizon language-conditioned manipulation tasks. ERRA is based on tightly-coupled probabilistic inferences at two granularity levels. Coarse-resolution inference is formulated as sequence generation through a large language model, which infers action language from natural language instruction and environment state. The robot then zooms to the fine-resolution inference part to perform the concrete action corresponding to the action language. Fine-resolution inference is constructed as a Markov decision process, which takes action language and environmental sensing as observations and outputs the action. The results of action execution in environments provide feedback for subsequent coarse-resolution reasoning. Such coarse-to-fine inference allows the robot to decompose and achieve long-horizon tasks interactively. In extensive experiments, we show that ERRA can complete various long-horizon manipulation tasks specified by abstract language instructions. We also demonstrate successful generalization to the novel but similar natural language instructions.Comment: Accepted to IEEE Robotics and Automation Letters (RA-L

On the topological surface states of the intrinsic magnetic topological insulator Mn-Bi-Te family

We review recent progress in the electronic structure study of intrinsic magnetic topological insulators (MnBi$_2$Te$_4$)(Bi$_2$Te$_3$)$_n$ ($n=0,1,2,3$) family. Specifically, we focus on the ubiquitously (nearly) gapless behavior of the topological surface state Dirac cone observed by photoemission spectroscopy, even though a large Dirac gap is expected because of surface ferromagnetic order. The dichotomy between experiment and theory concerning this gap behavior is perhaps the most critical and puzzling question in this frontier. We discuss various proposals accounting for the lack of magnetic effect on the topological surface state Dirac cone, which are mainly categorized into two pictures, magnetic reconfiguration, and topological surface state redistribution. Band engineering towards opening a magnetic gap of topological surface states provides great opportunities to realize quantized topological transport and axion electrodynamics at higher temperatures

Proton and Li-Ion Permeation through Graphene with Eight-Atom-Ring Defects

Defect-free graphene is impermeable to gases and liquids but highly permeable to thermal protons. Atomic-scale defects such as vacancies, grain boundaries and Stone-Wales defects are predicted to enhance graphene's proton permeability and may even allow small ions through, whereas larger species such as gas molecules should remain blocked. These expectations have so far remained untested in experiment. Here we show that atomically thin carbon films with a high density of atomic-scale defects continue blocking all molecular transport, but their proton permeability becomes ~1,000 times higher than that of defect-free graphene. Lithium ions can also permeate through such disordered graphene. The enhanced proton and ion permeability is attributed to a high density of 8-carbon-atom rings. The latter pose approximately twice lower energy barriers for incoming protons compared to the 6-atom rings of graphene and a relatively low barrier of ~0.6 eV for Li ions. Our findings suggest that disordered graphene could be of interest as membranes and protective barriers in various Li-ion and hydrogen technologies