P-ICL: Point In-Context Learning for Named Entity Recognition with Large Language Models

In recent years, the rise of large language models (LLMs) has made it possible to directly achieve named entity recognition (NER) without any demonstration samples or only using a few samples through in-context learning (ICL). However, standard ICL only helps LLMs understand task instructions, format and input-label mapping, but neglects the particularity of the NER task itself. In this paper, we propose a new prompting framework P-ICL to better achieve NER with LLMs, in which some point entities are leveraged as the auxiliary information to recognize each entity type. With such significant information, the LLM can achieve entity classification more precisely. To obtain optimal point entities for prompting LLMs, we also proposed a point entity selection method based on K-Means clustering. Our extensive experiments on some representative NER benchmarks verify the effectiveness of our proposed strategies in P-ICL and point entity selection

Optimization of Acquisition Phase and Acquisition Time Window of Coronary Artery CT Angiography with Different Heart Rates

This study aimed to determine the optimal reconstruction phase and acquisition time window for coronary computed tomography angiography (CCTA) in patients with different heart rates, by exploring the effect of the optimized scanning time window on image quality and radiation dose. One thousand patients who underwent CCTA were divided into groups A and B and were divided into nine subgroups based on their heart rate at the time of CCTA. Group A individuals underwent CCTA within a single cardiac cycle, and the optimal reconstruction phase at each heart rate was identified based on image quality. The individuals in group B were examined using the optimized scanning window in group A. Some patients underwent digital subtraction angiography (DSA) and the results were used as the gold standard. The image quality, radiation dose, and diagnostic efficiency were compared between the two groups. The findings indicated that the A1~A9 subgroups' optimal reconstruction phases were: 61%~85% RR interval; 68%~84% RR interval; 70%~82% RR interval and 34%~46% RR interval; 70%~82% RR interval and 34%~46% RR interval; 70%~82% and 36%~48% RR interval; 65%~89% and 38%~50% RR interval; 68%~84% RR interval and 36%~56% RR interval; 38%~54% RR interval; and 38%~58% RR interval. There were no significant differences in the subjective score and sensitivity and specificity of CCTA in the assessment of coronary artery stenosis between the two groups. The average effective dose (ED) in Group B was 40.17% lower than that in Group A. Narrowing the acquisition time window can lower the radiation dose of CCTA inspection while maintaining image quality

Reshapeable, rehealable and recyclable sensor fabricated by direct ink writing of conductive composites based on covalent adaptable network polymers

Covalent adaptable network (CAN) polymers doped with conductive nanoparticles are an ideal candidate to create reshapeable, rehealable, and fully recyclable electronics. On the other hand, 3D printing as a deterministic manufacturing method has a significant potential to fabricate electronics with low cost and high design freedom. In this paper, we incorporate a conductive composite consisting of polyimine CAN and multi-wall carbon nanotubes into direct-ink-writing 3D printing to create polymeric sensors with outstanding reshaping, repairing, and recycling capabilities. The developed printable ink exhibits good printability, conductivity, and recyclability. The conductivity of printed polyimine composites is investigated at different temperatures and deformation strain levels. Their shape-reforming and Joule heating-induced interfacial welding effects are demonstrated and characterized. Finally, a temperature sensor is 3D printed with defined patterns of conductive pathways, which can be easily mounted onto 3D surfaces, repaired after damage, and recycled using solvents. The sensing capability of printed sensors is maintained after the repairing and recycling. Overall, the 3D printed reshapeable, rehealable, and recyclable sensors possess complex geometry and extend service life, which assist in the development of polymer-based electronics toward broad and sustainable applications. &nbsp;</p

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Study on the Mechanical Properties of BFRP Tube Confined Concrete Short Columns under Axial Compression

Axial compression tests were carried out on 6 square steel tube confined concrete short columns and 6 BFRP square pipe confined concrete axial compression tests. The concrete strength grades were C30, C40, and C50. The test results show that the failure modes of steel pipe and BFRP pipe are obviously different, and the BFRP pipe undergoes brittle failure. Compared with the short columns of concrete confined by BFRP pipes, the ultimate bearing capacity of axial compression is increased by -76.46%, -76.01%, and -73.06%, and the ultimate displacements are -79.20%, -80.78%, -71.71%.</jats:p

Study on the Mechanical Properties of BFRP Tube Confined Concrete Short Columns under Axial Compression

Axial compression tests were carried out on 6 square steel tube confined concrete short columns and 6 BFRP square pipe confined concrete axial compression tests. The concrete strength grades were C30, C40, and C50. The test results show that the failure modes of steel pipe and BFRP pipe are obviously different, and the BFRP pipe undergoes brittle failure. Compared with the short columns of concrete confined by BFRP pipes, the ultimate bearing capacity of axial compression is increased by -76.46%, -76.01%, and -73.06%, and the ultimate displacements are -79.20%, -80.78%, -71.71%.</jats:p

Improving Recall of Large Language Models: A Model Collaboration Approach for Relational Triple Extraction

Relation triple extraction, which outputs a set of triples from long sentences, plays a vital role in knowledge acquisition. Large language models can accurately extract triples from simple sentences through few-shot learning or fine-tuning when given appropriate instructions. However, they often miss out when extracting from complex sentences. In this paper, we design an evaluation-filtering framework that integrates large language models with small models for relational triple extraction tasks. The framework includes an evaluation model that can extract related entity pairs with high precision. We propose a simple labeling principle and a deep neural network to build the model, embedding the outputs as prompts into the extraction process of the large model. We conduct extensive experiments to demonstrate that the proposed method can assist large language models in obtaining more accurate extraction results, especially from complex sentences containing multiple relational triples. Our evaluation model can also be embedded into traditional extraction models to enhance their extraction precision from complex sentences.Comment: Accepted at LREC-COLING 2024 main conferenc

One-Pot Synthesis of 2-Arylquinolines via in situ Acid Catalysis

AbstractA simple, efficient, and practical protocol is reported, allowing quick access to diverse 2-arylquinolines from 2-vinylanilines and benzyl halides. This reaction is additive and metal catalyst-free with only solvent needed. A preliminary mechanistic investigation discloses the driving force comes from the in situ released HBr, which catalyzes the subsequent cyclization. The present synthetic route featured high functional group tolerance and simple post-processing. A variety of 2-arylquinolines were obtained up to 96% yield.</jats:p

Microstructure evolution mechanism of Al/Mg dissimilar joint during friction stir welding

A butt friction stir welding (FSW) process was performed on 6061 Al and AZ31 Mg plates. The microstructure evolutions of the three main regions in the nugget zone (NZ) retained in the FSW joint were systematically investigated to clarify the joint formation mechanism during FSW. The differential etching of these microstructural features was found to produce very vivid flow features. During FSW, the material in the shoulder affected zone (SAZ) was mainly driven by the shoulder, and only a small amount of it was driven by the pin. A strip of Al transferred by the pin from the retreating side (RS) to the advancing side (AS) contacted and reacted with Mg, thus forming intermetallic compounds (IMCs) (e.g., Mg17Al12 and Al3Mg2). Due to the stirring action and tilted angle of the threaded pin, a banded structure (BS) feature tilted at approximately 45° was produced by the alternating lamellae of IMCs. The appearance of an onion ring structure occurred in the severely deformed zone (SDZ), which could be attributed to the reflection effect of the imaginary die wall. Finally, the overall flow pattern of the joint was obtained.</jats:p