RGAT: A Deeper Look into Syntactic Dependency Information for Coreference Resolution

Although syntactic information is beneficial for many NLP tasks, combining it with contextual information between words to solve the coreference resolution problem needs to be further explored. In this paper, we propose an end-to-end parser that combines pre-trained BERT with a Syntactic Relation Graph Attention Network (RGAT) to take a deeper look into the role of syntactic dependency information for the coreference resolution task. In particular, the RGAT model is first proposed, then used to understand the syntactic dependency graph and learn better task-specific syntactic embeddings. An integrated architecture incorporating BERT embeddings and syntactic embeddings is constructed to generate blending representations for the downstream task. Our experiments on a public Gendered Ambiguous Pronouns (GAP) dataset show that with the supervision learning of the syntactic dependency graph and without fine-tuning the entire BERT, we increased the F1-score of the previous best model (RGCN-with-BERT) from 80.3% to 82.5%, compared to the F1-score by single BERT embeddings from 78.5% to 82.5%. Experimental results on another public dataset - OntoNotes 5.0 demonstrate that the performance of the model is also improved by incorporating syntactic dependency information learned from RGAT.Comment: 8 pages, 5 figure

Infrared Imaging of Magnetic Octupole Domains in Non-collinear Antiferromagnets

Magnetic structure plays a pivotal role in the functionality of antiferromagnets (AFMs), which not only can be employed to encode digital data but also yields novel phenomena. Despite its growing significance, visualizing the antiferromagnetic domain structure remains a challenge, particularly for non-collinear AFMs. Currently, the observation of magnetic domains in non-collinear antiferromagnetic materials is feasible only in Mn$_{3}$Sn, underscoring the limitations of existing techniques that necessitate distinct methods for in-plane and out-of-plane magnetic domain imaging. In this study, we present a versatile method for imaging the antiferromagnetic domain structure in a series of non-collinear antiferromagnetic materials by utilizing the anomalous Ettingshausen effect (AEE), which resolves both the magnetic octupole moments parallel and perpendicular to the sample surface. Temperature modulation due to the AEE originating from different magnetic domains is measured by the lock-in thermography, revealing distinct behaviors of octupole domains in different antiferromagnets. This work delivers an efficient technique for the visualization of magnetic domains in non-collinear AFMs, which enables comprehensive study of the magnetization process at the microscopic level and paves the way for potential advancements in applications.Comment: National Science Review in pres

NtMYB4 and NtCHS1 Are Critical Factors in the Regulation of Flavonoid Biosynthesis and Are Involved in Salinity Responsiveness

High levels of salinity induce serious oxidative damage in plants. Flavonoids, as antioxidants, have important roles in reactive oxygen species (ROS) scavenging. In the present study, the tobacco R2R3 MYB type repressor, NtMYB4, was isolated and characterized. The expression of NtMYB4 was suppressed by salinity. Overexpression of NtMYB4 reduced the salt tolerance in transgenic tobacco plants. NtMYB4 repressed the promoter activity of NtCHS1 and negatively regulated its expression. Rutin accumulation was significantly decreased in NtMYB4 overexpressing transgenic plants and NtCHS1 RNAi silenced transgenic plants. Moreover, high H2O2 and O2− contents were detected in both types of rutin-reduced transgenic plants under high salt stress. In addition, exogenous rutin supplementation effectively scavenged ROS (H2O2 and O2−) and improved the salt tolerance of the rutin-reduced transgenic plants. In contrast, NtCHS1 overexpressing plants had increased rutin accumulation, lower H2O2 and O2− contents, and higher tolerance to salinity. These results suggested that tobacco NtMYB4 acts as a salinity response repressor and negatively regulates NtCHS1 expression, which results in the reduced flavonoid accumulation and weakened ROS-scavenging ability under salt stress

Modeling the Hysteresis Characteristics of Transformer Core under Various Excitation Level via On-Line Measurements

In this paper, the hysteresis characteristics of a transformer core are determined from limited on-line measured voltages and currents under certain excitations. A method for calculating the magnetization curve and hysteresis loops of the transformer core under various excitation is developed based on limited excitation conditions, and using the deep neural network, support vector regressor and the Wlodarski model. The coercivity and the amplitude of magnetic field strength of hysteresis loops can be captured with high accuracy based on this method. Then, a finite element model of the transformer core is constructed to predict the distributed magnetic flux density and the excitation current using the calculated hysteresis loops. The currents from various excitation voltages on two different transformer structures are also measured to compared with simulated currents. The outcome indicates that the overall hysteresis loops and magnetization curve of the transformer core may be useful for modeling the magnetic field and excitation current under any voltage excitation

An Engineering Model of Magnetic Flux Density and Electromagnetic Force Density at the Structural Discontinuity within Transformer Cores

The structural discontinuities in the form of air gaps in transformer cores cause the concentration of electromagnetic force, which is an important source of transformer vibration and noise. In this paper, an engineering model of magnetic flux density and electromagnetic force density on transformer core discontinuities is analytically developed. Based on a reasonable structural simplification and assumptions, magnetic flux density and electromagnetic force density are deduced as explicit functions of the geometric, material, and electrical excitation characteristics of the gap region and the transformer core. The accuracy of the established model is validated by the finite element method (FEM) combined with a magnetic measurement experiment. According to this engineering model, the electromagnetic force density can be reduced by decreasing the gap ratio and increasing the gap thickness to a reasonable level. The outcome of this paper can help to understand the physical mechanism of the electromagnetic force generated by core air gap discontinuities, which is meaningful for noise control and the condition monitoring of transformers

Association Analysis of Arsenic-Induced Straighthead in Rice (Oryza sativa L.) Based on the Selected Population with a Modified Model

A rice physiological disorder makes mature panicle keep erect with empty grains termed as “straighthead.” Straighthead causes yield losses and is a serious threat to rice production worldwide. Here, a new study of association mapping was conducted to identify QTL involved in straighthead. A subset of 380 accessions was selected from the USDA rice core collection and genotyped with 72 genome-wide SSR markers. An optimal model implemented with principle components (PCs) was used in this association mapping. As a result, five markers were identified to be significantly associated with straighthead. Three of them, RM263, RM169, and RM224, were consistent with a previous study. Three markers, RM475, RM263, and RM19, had a resistant allele associated with a decrease in straighthead rating (straighthead rating ≤ 4.8). In contrast, the two other marker loci RM169 and RM224 had a few susceptible alleles associated with an increase in straighthead rating (straighthead rating ≥ 8.7). Interestingly, RM475 is close to QTL “qSH-2” and “AsS” with straighthead resistance, which was reported in two studies on linkage mapping of straighthead. This finding adds to previous work and is useful for further genetic study of straighthead

Distributed Magnetic Flux Density on the Cross-Section of a Transformer Core

In this paper, the magnetic flux density distribution on the cross-sections of a transformer core is studied. The core for this study consists of two identical U-shaped cores joint at their open surfaces with known air gaps. The magnetic flux density at one of their joint boundary surfaces was measured for different air gaps. A finite element model (FEM) was built to simulate the magnetic flux density and compared with experiment data. Using the validated FEM, the distributed magnetic flux density on the cross-section of the core structure can be obtained when the air gap approaches zero. An engineering model of the density based on the Ampere’s circuit law was also developed and used to explain the relationship between air gap and mean magnetic flux density on the cross-section. The magnetic flux density on the cross-section was found to have a convex-shaped distribution and could be described by an empirical formula. Using this approach, the magnetic flux density distribution in cores with different interlayer insulation was obtained and discussed. This method could also examine the leakage of magnetic flux density in the air gap region when the distance is non-zero, and the relationship between the leakage field and the field in the core structure. The proposed method and model can provide a more detailed understanding for the magnetic field of transformer cores and potential application in designing quiet transformers and condition monitoring

MicroRNA-873 Promotes Cell Proliferation, Migration, and Invasion by Directly Targeting TSLC1 in Hepatocellular Carcinoma

Background/Aims: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and has the third highest mortality rate among all cancers. MicroRNAs are a class of endogenous, single-stranded short noncoding RNAs. The purpose of this study was to study the role of microRNA-873 in HCC. Methods: The expression of miRNA-873 and tumor suppressor in lung cancer 1 (TSLC1) in HCC tissues and cell lines was detected by real-time quantitative RT-PCR (RT-qPCR) or western blot. A CCK-8 assay was used to examine cell proliferation; flow cytometry was used to assess the cell cycle; the Transwell migration assay was used to test for metastasis. Luciferase assays were performed to assess whether TSLC1 was a novel target of miRNA-873. Results: We showed that miRNA-873 was upregulated in HCC tissues and cell lines compared with the normal control. Knockdown of miRNA-873 inhibited the growth and metastasis of HepG2 and accelerated G1 phase arrest, while overexpression of miRNA-873 had the opposite effect. The dual-luciferase reporter assays revealed that TSLC1 was a novel target of miRNA-873. Further study showed that TSLC1 was decreased in HCC tissues and cell lines. There was a negative correlation between the expression levels of TSLC1 and miRNA-873. The effect of miRNA-873 overexpression was neutralized by TSLC1. We also found that miRNA-873 activated the PI3K/AKT/mTOR signaling pathway and promoted HCC. Conclusions: Our data demonstrated that miRNA-873 promoted HCC progression by targeting TSLC1 and provided a new target for the therapy of HCC