Exploring the Compositional Generalization in Context Dependent Text-to-SQL Parsing

In the context-dependent Text-to-SQL task, the generated SQL statements are refined iteratively based on the user input utterance from each interaction. The input text from each interaction can be viewed as component modifications to the previous SQL statements, which could be further extracted as the modification patterns. Since these modification patterns could also be combined with other SQL statements, the models are supposed to have the compositional generalization to these novel combinations. This work is the first exploration of compositional generalization in context-dependent Text-to-SQL scenarios. To facilitate related studies, we constructed two challenging benchmarks named \textsc{CoSQL-CG} and \textsc{SParC-CG} by recombining the modification patterns and existing SQL statements. The following experiments show that all current models struggle on our proposed benchmarks. Furthermore, we found that better aligning the previous SQL statements with the input utterance could give models better compositional generalization ability. Based on these observations, we propose a method named \texttt{p-align} to improve the compositional generalization of Text-to-SQL models. Further experiments validate the effectiveness of our method. Source code and data are available.Comment: Accepted to ACL 2023 (Findings), Long Paper, 11 page

RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation Extraction

How to identify semantic relations among entities in a document when only a few labeled documents are available? Few-shot document-level relation extraction (FSDLRE) is crucial for addressing the pervasive data scarcity problem in real-world scenarios. Metric-based meta-learning is an effective framework widely adopted for FSDLRE, which constructs class prototypes for classification. However, existing works often struggle to obtain class prototypes with accurate relational semantics: 1) To build prototype for a target relation type, they aggregate the representations of all entity pairs holding that relation, while these entity pairs may also hold other relations, thus disturbing the prototype. 2) They use a set of generic NOTA (none-of-the-above) prototypes across all tasks, neglecting that the NOTA semantics differs in tasks with different target relation types. In this paper, we propose a relation-aware prototype learning method for FSDLRE to strengthen the relational semantics of prototype representations. By judiciously leveraging the relation descriptions and realistic NOTA instances as guidance, our method effectively refines the relation prototypes and generates task-specific NOTA prototypes. Extensive experiments demonstrate that our method outperforms state-of-the-art approaches by average 2.61% $F_1$ across various settings of two FSDLRE benchmarks.Comment: Accepted to EMNLP 202

Molecular Dynamics Simulation and Viscosity Analysis of Red Mud–Steel Slag Glass–Ceramics

The preparation of glass–ceramics with red mud and steel slag can not only solve the pollution problem caused by industrial waste slag but also produce economic benefits. It is difficult to analyze the high-temperature melt with the existing test methods, so the simulation experiment with molecular dynamics calculation becomes an important research method. The effects of steel slag content on the microstructure of red mud glass–ceramics were studied by molecular dynamics method. The results show that the binding ability of Si-O, Al-O, and Fe-O decreases with the increase in steel slag content. The number of Si-O-Si bridge oxygen increased gradually, while the number of Al-O-Al, Al-O-Fe, and Fe-O-Fe bridge oxygen decreased significantly. The number of tetrahedrons [SiO4] increased, the number of tetrahedrons [FeO4] and [AlO4] decreased, and the total number of three tetrahedrons decreased. The mean square displacement value of Si4+ and O2− increases first and then decreases, resulting in the viscosity of the system decreasing first and then increasing. The molecular dynamics method is used to analyze the structure of red mud–steel slag glass–ceramics on the microscopic scale, which can better understand the role of steel slag and has guiding significance for the experiment of this kind of glass–ceramics

Genotype-specific reference interval of haptoglobin tests in a Chinese population on the BN II System

Abstract The distribution of Haptoglobin (HP) subtypes differs according to race and geography. It was also confirmed that the serum HP concentration was substantially affected by the HP subtypes. This study aimed to investigate the HP subtypes in northern Chinese and to establish reference intervals for the major HP subtypes using the BN II system. 1195 individuals were included in the study, grouped by haptoglobin subtype, and tested for concentrations by BN II System. Analysis of reference range was performed according to the EP28-A3c guideline. The need to establish reference ranges for subtype, gender, and age groupings was confirmed by the Z-test. The 2.5th and 97.5th percentiles were used as the upper and lower limits of the reference interval, respectively. In the population we investigated, the HP2-2 subtype had the highest proportion, accounting for 49.3%, followed by HP2-1 (38.0%), HP1-1 (7.2%). In addition, about 5.5% of individuals had HP del -related subtypes. The concentrations of the major subtypes (HP1-1, HP2-1, HP2-2) were significantly different, and it was necessary to establish reference ranges by grouping according to the results of the Z-test. The reference intervals were as follows: HP1-1, 0.37–2.19 g/L; HP2-1, 0.38–2.12 g/L; HP2-2, 0.12–1.51 g/L. Significant differences in HP concentrations between genders and ages were found, however, it was not necessary to establish separate reference interval since the results of the Z-test was negative. We have established reference ranges of serum haptoglobin concentrations based on subtypes, which are necessary for the clinical application of haptoglobin

Design of the klystron filament power supply control system for EAST LHCD

A filament is a critical component of the klystron used to heat the cathode. There are totally 44 klystrons in experimental advanced superconducting tokamak (EAST) lower hybrid current drive (LHCD) systems. All klystron filaments are powered by AC power suppliers through isolated transformers. In order to achieve better klystron preheat, a klystron filament power supply control system is designed to obtain the automatic control of all filament power suppliers. Klystron filament current is measured by PLC and the interlock between filament current and klystron high voltage system is also implemented. This design has already been deployed in two LHCD systems and proves feasible completely

Automatic Extraction of Marine Aquaculture Zones from Optical Satellite Images by R³Det with Piecewise Linear Stretching

In recent years, the development of China’s marine aquaculture has brought serious challenges to the marine ecological environment. Therefore, it is significant to classify and extract the aquaculture zone and spatial distribution in order to provide a reference for aquaculture management. However, considering the complex marine aquaculture environment, it is difficult for traditional remote sensing technology and deep learning to achieve a breakthrough in the extraction of large-scale aquaculture zones so far. This study proposes a method based on the combination of piecewise linear stretching and R3Det to classify and extract raft aquaculture and cage aquaculture zones. The grayscale value is changed by piecewise linear stretching to reduce the influence of complex aquaculture backgrounds on the extraction accuracy, to effectively highlight the appearance characteristics of the aquaculture zone, and to improve the image contrast. On this basis, the aquaculture zone is classified and extracted by R3Det. Taking the aquaculture zone of Sansha Bay as the research object, the experimental results showed that the accuracy of R3Det in extracting the number of raft aquaculture and cage aquaculture zones was 98.91% and 97.21%, respectively, and the extraction precision of the area of the aquaculture zone reached 92.08%. The proposed method can classify and extract large-scale marine aquaculture zones more simply and efficiently than common remote sensing techniques

Band gap-Tunable Porous Borocarbonitride Nanosheets for High Energy-Density Supercapacitors

Band gap-tunable porous borocarbonitride (BCN) nanosheets were successfully fabricated with cheap and readily available precursors by annealing and exfoliating. The band gap of the as-prepared BCN materials ranges from 5.5 to 1.0 eV; these samples exhibit beneficial structural features suitable for the application in supercapacitors. Especially, the BCN material with a band gap of 1.0 eV exhibits a great specific surface area (600.9 m² g^–1), massive active sites, and excellent conductivity (10.8 S m^–1). In addition, this example displays great specific capacitance (464.5 F g^–1), excellent cycle stability (98.5% performance retention after 10 000 cycles), and ultrahigh energy density (50.4 W h kg^–1, in 1 M Et₄NBF₄ electrolyte). This excellent electrochemical performance and facile effective synthesis of band gap-tunable BCN materials will provide a promising strategy for configuring nanostructured multiple compound electrodes for other energy storage and conversion devices

‘Thermal substitution’ for preparing ternary BCN nanosheets with enhanced and controllable nonlinear optical performance

This paper contains methods and expanded descriptions