Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network

Personalized review generation (PRG) aims to automatically produce review text reflecting user preference, which is a challenging natural language generation task. Most of previous studies do not explicitly model factual description of products, tending to generate uninformative content. Moreover, they mainly focus on word-level generation, but cannot accurately reflect more abstractive user preference in multiple aspects. To address the above issues, we propose a novel knowledge-enhanced PRG model based on capsule graph neural network~(Caps-GNN). We first construct a heterogeneous knowledge graph (HKG) for utilizing rich item attributes. We adopt Caps-GNN to learn graph capsules for encoding underlying characteristics from the HKG. Our generation process contains two major steps, namely aspect sequence generation and sentence generation. First, based on graph capsules, we adaptively learn aspect capsules for inferring the aspect sequence. Then, conditioned on the inferred aspect label, we design a graph-based copy mechanism to generate sentences by incorporating related entities or words from HKG. To our knowledge, we are the first to utilize knowledge graph for the PRG task. The incorporated KG information is able to enhance user preference at both aspect and word levels. Extensive experiments on three real-world datasets have demonstrated the effectiveness of our model on the PRG task.Comment: Accepted by CIKM 2020 (Long Paper

Automated Configuration of Gripper Fingers from a Construction Kit for Robotic Applications

Gripper finger design is a complex process that requires a lot of experience, time, and effort. For this reason, automating this design process is an important area of research that has the potential to improve the efficiency and effectiveness of robotic systems. The current approaches are aimed at the automated design of monolithic gripper fingers, which have to be manufactured additively or by machining. This paper describes a novel approach for the automated design of gripper fingers. The motivation for this work stems from the increasing demand for flexible, adaptable handling systems in various industries in response to the increasing individualization of products as well as the increasing volatility in the markets. Based on the CAD data of the handling objects, the most suitable configuration of gripper fingers can be determined from the existing modules of a construction kit for the respective handling object, which can significantly reduce the provisioning time for new gripper fingers. It can be shown that gripper fingers can be effectively configured for a variety of objects and two different grippers, increasing flexibility in industrial handling processes

Metabolomics Combined with Multivariate Statistical Analysis for Screening of Chemical Markers between Gentiana scabra and Gentiana rigescens

Gentianae Radix et Rhizome (Longdan in Chinese, GRR) in Chinese Pharmacopoeia is derived from the dried roots and rhizomes of Gentiana scabra and G. rigescens, that have long been used for heat-clearing and damp-drying in the medicinal history of China. However, the characterization of the chemical components of two species and the screening of chemical markers still remain unsolved. In current research, the identification and characterization of chemical components of two species was performed using ultra-high-performance liquid chromatography (UHPLC) coupled with linear ion trap-Orbitrap (LTQ-Orbitrap) mass spectrometry. Subsequently, the chemical markers of two species were screened based on metabolomics and multivariate statistical analysis. In total, 87 chemical constituents were characterized in G. scabra (65 chemical constituents) and G. rigescens (51 chemical constituents), with 29 common chemical constituents being discovered. Thereafter, 11 differential characteristic components which could differentiate the two species were designated with orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF) iterative modeling. Finally, seven characteristic components identified as (+)-syringaresinol, lutonarin, trifloroside, 4-O-β-d-glu-trifloroside, 4″-O-β-d-glucopyranosy1-6′-O-(4-O-β-d-glucaffeoyl)-linearroside, macrophylloside a and scabraside were selected as the chemical markers for the recognition of two Gentiana species. It was implied that the results could distinguish the GRR derived from different botanical sources, and also be beneficial in the rational clinical use of GRR

Disulfide Bond: Dramatically Enhanced Assembly Capability and Structural Stability of Tobacco Mosaic Virus Nanorods

Tobacco mosaic virus (TMV) is a classical viral nanoarchitecture that has been extensively employed as a promising template for the fabrication of novel nanomaterials and nanostructures. Despite being an ideal source, the Escherichia coli-derived TMV nanorod is suffering from tenuous assembly capability and stability. Inspired by the disulfide bond widely employed in biosystems, here we rationally introduce a cysteine into TMV coat protein (TMV-CP) to enable disulfide bond formation between adjacent subunits, thereby radically altering the behaviors of original noncovalent assembling system of wild type TMV-CP. The dramatically enhanced self-assembly capability and stability of the engineered TMV nanorods are observed and the essential roles of disulfide bonds are verified, illustrating a promising strategy to obtain desired genetic-modified nanorods that are inaccessible in plants. We expect this work will benefit the development of TMV-based nanotechnology and encourage the utilization of disulfide bonds in other biomacromolecules for improved properties as nanoscaffolds

Automated Configuration of Gripper Fingers from a Construction Kit for Robotic Applications

Gripper finger design is a complex process that requires a lot of experience, time, and effort. For this reason, automating this design process is an important area of research that has the potential to improve the efficiency and effectiveness of robotic systems. The current approaches are aimed at the automated design of monolithic gripper fingers, which have to be manufactured additively or by machining. This paper describes a novel approach for the automated design of gripper fingers. The motivation for this work stems from the increasing demand for flexible, adaptable handling systems in various industries in response to the increasing individualization of products as well as the increasing volatility in the markets. Based on the CAD data of the handling objects, the most suitable configuration of gripper fingers can be determined from the existing modules of a construction kit for the respective handling object, which can significantly reduce the provisioning time for new gripper fingers. It can be shown that gripper fingers can be effectively configured for a variety of objects and two different grippers, increasing flexibility in industrial handling processes

Effective Design Strategy of Small Bipolar Molecules through Fused Conjugation toward 2.5 V Based Redox Flow Batteries

Using bipolar redox-active molecules (BRMs) as active materials is a practical way to address electrolyte crossover and resultant unpredictable side reactions in redox-flow batteries. However, the development of BRMs is greatly hindered by difficulties in finding new molecules from limited redox-active moieties and in achieving high cell voltage to compete with existing flow battery chemistries. This study proposes a strategy for design of high-voltage BRMs using fused conjugation that regulates the redox potential of integrated redox-active moieties. As a demonstration, quaternary N and ketone redox moieties are used to construct a new BRM that shows a prominent voltage gap with good electrochemical stability. A symmetrical redox-flow cell based on this molecule exhibits a high voltage of 2.5 V and decent cycling stability. This study provides a general strategy for designing new BRMs that may enrich the cell chemistries of organic redox-flow batteries