In order to build a better understanding of the relationship between depositing mode and porosity, microstructure, and properties in wire + arc additive manufacturing (WAAM) 2319-Al components, several Al-6.3%Cu deposits were produced by WAAM technique with cold metal transfer (CMT) variants, pulsed CMT (CMT-P) and advanced CMT (CMT-ADV). Thin walls and blocks were selected as the depositing paths to make WAAM samples. Porosity, microstructure and micro hardness of these WAAM samples were investigated. Compared with CMT-P and thin wall mode, CMT-ADV and block process can effectively reduce the pores in WAAM aluminum alloy. The microstructure varied with different depositing paths and CMT variants. The micro hardness value of thin wall samples was around 75 HV from the bottom to the middle, and gradually decreased toward the top. Meanwhile, the micro hardness value ranged around 72–77 HV, and varied periodically in block samples. The variation in micro hardness is consistent with standard microstructure characteristics.

Taking photos by mobile phones has become an indispensable part of people's daily life with the popularity of smartphones. However professional photography content is also needed for taking high-quality photos by mobile phones as ones taken by professional cameras. Existing learning tools for photography can't provide photographic practice while presenting theoretical content, nor give real-time photography guidance according to the environment. Mobile augmented reality (AR) technology provides a new way to solve these problems by creating a real learning situation. Therefore, an innovative AR-based mobile photography application (ARMPA) is designed and developed as a method to connect theory and practice. Based on Learning-by-Doing instructional strategy, the ARMPA can timely and synchronously display the theoretical content of photography in the form of text and images corresponding to learners' practical operation. Moreover, it can provide learners real-time interaction and guidance by using AR environment sensing technology. The effect of ARMPA on learning gain and cognitive load is assessed by traditional methods of pre/post-test and questionnaires. To objectively explore the effectiveness of ARMPA from a cognitive and emotional perspective, we measure and extract four emotional state indexes of electroencephalogram (EEG) including engagement (ENG), relaxation (MED), interest (INT) and focus (FOC). Compared to traditional two-dimension (2 D) application (APP), ARMPA improves learners’ learning gains, decreases learners’ cognitive loads. The participants in the AR group achieve better emotional states than those in the 2 D group. This study provides some empirical evidence for AR technology to boost mobile phone photography.

Gang Zhao, Guanting Dong, Yidong Shi, Haolong Yan, Weiran Xu, Si Li. Findings of the Association for Computational Linguistics: EMNLP 2022. 2022.

The objective of few-shot named entity recognition is to identify named entities with limited labeled instances. Previous works have primarily focused on optimizing the traditional token-wise classification framework, while neglecting the exploration of information based on NER data characteristics. To address this issue, we propose a Multi-Task Semantic Decomposition Framework via Joint Task-specific Pre-training (MSDP) for few-shot NER. Drawing inspiration from demonstration-based and contrastive learning, we introduce two novel pre-training tasks: Demonstration-based Masked Language Modeling (MLM) and Class Contrastive Discrimination. These tasks effectively incorporate entity boundary information and enhance entity representation in Pre-trained Language Models (PLMs). In the downstream main task, we introduce a multi-task joint optimization framework with the semantic decomposing method, which facilitates the model to integrate two different semantic information for entity classification. Experimental results of two few-shot NER benchmarks demonstrate that MSDP consistently outperforms strong baselines by a large margin. Extensive analyses validate the effectiveness and generalization of MSDP.

The bolt connection structure is widely used in the connection of aeroengine parts, and its connection quality is very important, as it can directly affect the geometric and dynamic performance of the aeroengine. Taking the bolt preload as the entry point, the research status of bolted aeroengine connections in recent years is summarized based on the bolt preload formation mechanism and control technology in this review. For the research of the preload formation mechanism, single and multiple bolts of aeroengine bolt arrays are analyzed. According to the characteristics of aeroengine bolt connections, the research of aeroengine bolt preload control technology is divided into two parts: bolt tightening technology, and bolt tightening equipment. Finally, based on the summarization of the research, the future research prospects are evaluated and discussed.