Joint event extraction based on hierarchical event schemas from framenet

Event extraction is useful for many practical applications, such as news summarization and information retrieval. However, the popular automatic context extraction (ACE) event extraction program only defines very limited and coarse event schemas, which may not be suitable for practical applications. FrameNet is a linguistic corpus that defines complete semantic frames and frame-to-frame relations. As frames in FrameNet share highly similar structures with event schemas in ACE and many frames actually express events, we propose to redefine the event schemas based on FrameNet. Specifically, we extract frames expressing event information from FrameNet and leverage the frame-to-frame relations to build a hierarchy of event schemas that are more fine-grained and have much wider coverage than ACE. Based on the new event schemas, we propose a joint event extraction approach that leverages the hierarchical structure of event schemas and frame-to-frame relations in FrameNet. The extensive experiments have verified the advantages of our hierarchical event schemas and the effectiveness of our event extraction model. We further apply the results of our event extraction model on news summarization. The results show that the summarization approach based on our event extraction model achieves significant better performance than several state-of-the-art summarization approaches, which also demonstrates that the hierarchical event schemas and event extraction model are promising to be used in the practical applications

Dielectric Loss Tangent Extraction using Two Single-Ended Striplines of Different Width

Frequency-dependent electrical properties of dielectric materials are one of the most important factors for high-speed signal integrity design. Recently a method of accurately measuring the dielectric loss tangent ($\tan \delta$) of differential lines was proposed. By taking into account the ratio between the differential and common mode per-unit-length resistances the surface roughness contribution to the total loss is eliminated and dielectric parameters can be determined. In this article a similar method is applied to a combination of two single-ended lines. To evaluate the accuracy of the extraction, the impact of the de-embedding errors was investigated, which allows to optimize the test PCB design. The extraction method was validated in measurement using a PCB with several two-width pairs of strip lines. The extracted loss tangent of several optimal two width pairs of single-ended lines is validated by the SPDR measurements

Unlocking the Power of Large Language Models for Entity Alignment

Entity Alignment (EA) is vital for integrating diverse knowledge graph (KG) data, playing a crucial role in data-driven AI applications. Traditional EA methods primarily rely on comparing entity embeddings, but their effectiveness is constrained by the limited input KG data and the capabilities of the representation learning techniques. Against this backdrop, we introduce ChatEA, an innovative framework that incorporates large language models (LLMs) to improve EA. To address the constraints of limited input KG data, ChatEA introduces a KG-code translation module that translates KG structures into a format understandable by LLMs, thereby allowing LLMs to utilize their extensive background knowledge to improve EA accuracy. To overcome the over-reliance on entity embedding comparisons, ChatEA implements a two-stage EA strategy that capitalizes on LLMs' capability for multi-step reasoning in a dialogue format, thereby enhancing accuracy while preserving efficiency. Our experimental results affirm ChatEA's superior performance, highlighting LLMs' potential in facilitating EA tasks

Organoaluminium complexes of ortho-, meta-, para-anisidines: synthesis, structural studies and ROP of ε-caprolactone (and rac-lactide)

Reaction of Me₃Al (two equivalents) with ortho-, meta- or para-anisidine, (OMe)(NH₂)C₆H₄, affords the complexes {[1,2-(OMe),NC₆H₄(μ-Me₂Al)](μ-Me₂Al)}₂ (1), [1,3-(Me₃AlOMe),NHC₆H₄(μ-Me₂Al)]2 (2) or [1,4-(Me₃AlOMe),NHC₆H₄(μ-Me₂Al)]₂ (3), respectively. The molecular structures of 1–3 have been determined and all three complexes were found to be highly active for the ring opening polymerization (ROP) of ε-caprolactone. 1 was found highly active either with or without benzyl alcohol present; at various temperatures, the activity order 1 > 2 ≈ 3 was observed. For the ROP of rac-lactide results for 1–3 were poor

Undesired-Resonance Analysis and Modeling of Differential Signals Due to Narrow Ground Lines Without Stitching Vias

Undesired Resonances on High-Speed Differential Signals Are Studied in This Paper, which is Caused by the Adjacent Narrow Ground Line Without Stitching Vias. Due to Space Limitations in the High-Speed Channel Layouts of Certain Package Applications, the Ground (GND) Line is Often Narrow and Has Insufficient Stitching Vias, Potentially Causing Undesired Resonance in High-Speed Differential Signals. in This Study, These Undesired Resonances Were Investigated using 3D Simulations, revealing that They Can Be Modeled as Parallel-Coupled Half-Wavelength Resonance. the Resonance Frequency of the Parallel-Coupled Half-Wavelength Resonance Structure Can Be Predicted Well using the Formula based on the GND Line Length. Moreover, Three Potential Solutions to Undesired Resonance Are Proposed, Providing a Practical Guide for GND Line Routing in Specific Applications

Rethinking GNN-based Entity Alignment on Heterogeneous Knowledge Graphs: New Datasets and A New Method

The development of knowledge graph (KG) applications has led to a rising need for entity alignment (EA) between heterogeneous KGs that are extracted from various sources. Recently, graph neural networks (GNNs) have been widely adopted in EA tasks due to GNNs' impressive ability to capture structure information. However, we have observed that the oversimplified settings of the existing common EA datasets are distant from real-world scenarios, which obstructs a full understanding of the advancements achieved by recent methods. This phenomenon makes us ponder: Do existing GNN-based EA methods really make great progress? In this paper, to study the performance of EA methods in realistic settings, we focus on the alignment of highly heterogeneous KGs (HHKGs) (e.g., event KGs and general KGs) which are different with regard to the scale and structure, and share fewer overlapping entities. First, we sweep the unreasonable settings, and propose two new HHKG datasets that closely mimic real-world EA scenarios. Then, based on the proposed datasets, we conduct extensive experiments to evaluate previous representative EA methods, and reveal interesting findings about the progress of GNN-based EA methods. We find that the structural information becomes difficult to exploit but still valuable in aligning HHKGs. This phenomenon leads to inferior performance of existing EA methods, especially GNN-based methods. Our findings shed light on the potential problems resulting from an impulsive application of GNN-based methods as a panacea for all EA datasets. Finally, we introduce a simple but effective method: Simple-HHEA, which comprehensively utilizes entity name, structure, and temporal information. Experiment results show Simple-HHEA outperforms previous models on HHKG datasets.Comment: 11 pages, 6 figure

A bibliometric analysis based on hotspots and frontier trends of positron emission tomography/computed tomography utility in bone and soft tissue sarcoma

PurposeThis study aimed to analyze articles on the diagnosis and treatment of bone and soft tissue sarcoma using positron emission tomography (PET)/computed tomography (CT) published in the last 13 years. The objective was to conduct a bibliometric analysis and identify the research hotspots and emerging trends.MethodsWeb of Science was used to search for articles on PET/CT diagnosis and treatment of bone and soft tissue sarcoma published from January 2010 to June 2023. CiteSpace was utilized to import data for bibliometric analysis.ResultsIn total, 425 relevant publications were identified. Publications have maintained a relatively stable growth rate for the past 13 years. The USA has the highest number of published articles (139) and the highest centrality (0.35). The UDICE-French Research Universities group is the most influential institution. BYUN BH is a prominent contributor to this field. The Journal of Clinical Oncology has the highest impact factor in the field.ConclusionThe clinical application of PET/CT is currently a research hotspot. Upcoming areas of study concentrate on the merging of PET/CT with advanced machine learning and/or alternative imaging methods, novel imaging substances, and the fusion of diagnosis and therapy. The use of PET/CT has progressively become a crucial element in the identification and management of sarcomas. To confirm its efficacy, there is a need for extensive, multicenter, prospective studies

Optical Ranging Using Coherent Kerr Soliton Dual-microcombs with Extended Ambiguity Distance

Optical ranging is a key technology in metrology. Optical frequency combs are shown to provide several advantages in light ranging, offering high precision with high acquisition rate. However, performance of traditional ranging systems based on microcombs is limited by the short ambiguity distance and non-real-time processing. Here, we show that dual-comb ranging system using coherent Kerr soliton microcombs and optical switch realizes extended ambiguity distance and provides a route to real-time processing. The ambguity distance is extended to 3.28 m from about 1.5 mm and the uncertainty reaches about 1.05 times 10^-7, while the system is compatible with low-bandwidth detectors. Combining coherent microcomb ranging systems with special FPGA could enable comb-based real-time ranging systems for several applications such as industrial process monitoring.Comment: 9 pages, 5 figure

Comparison of 68Ga-FAP-2286 and 18F-FDG PET/CT in the diagnosis of advanced lung cancer

PurposeThe 68Ga/177Lu-FAP-2286 is a newly developed tumor imaging agent that shows potential for visualizing and treating tumor stroma. The objective of this research was to evaluate the effectiveness of 68Ga-FAP-2286 PET/CT and 18F-FDG PET/CT in diagnosing advanced lung cancer.MethodsIn this prospective study, patients with lung cancer who underwent 68Ga-FAP-2286 and 18F-FDG PET/CT examinations between September 2022 and June 2023 were analyzed. Lesion uptake was converted to SUVmax. A paired T-test was used to compare the SUVmax, and the number of positive lesions detected by the two methods was recorded.ResultsIn total, 31 participants (median age: 56 years) were assessed. The uptake of 68Ga-FAP-2286 was significantly higher than that of 18F-FDG in primary lesions (9.90 ± 5.61 vs. 6.09 ± 2.84, respectively, P < 0.001), lymph nodes (7.95 ± 2.75 vs. 5.55 ± 1.59, respectively, P=0.01), and bone metastases (7.74 ± 3.72 vs. 5.66 ± 3.55, respectively, P=0.04). Furthermore, the detection sensitivity of lymph nodes using 68Ga-FAP-2286 PET/CT was superior to that with 18F-FDG PET/CT [100% (137/137) vs. 78.8% (108/137), respectively], as well as for bone metastases [100% (384/384) vs. 68.5% (263/384), respectively]. However, the detection sensitivity for primary tumors using both modalities was comparable [100% (13/13) for both].ConclusionCompared to 18F-FDG PET/CT, 68Ga-FAP-2286 PET/CT demonstrated better lesion detection capabilities for lung cancer, particularly in lymph nodes and bone metastases, providing compelling imaging evidence for the efficacy of 177Lu-FAP-2286 treatment