Encountering Christianity In Twentieth Century East Asia: A Case Study Of Jiang Wenhan And Takeda (Cho) Kiyoko

This study explores the twentieth-century Christian indigenization movement in East Asia through a case study of Jiang Wenhan of China and Takeda Kiyoko of Japan, two leading scholars and Christian activists in their respective countries. Drawing primarily on their own writings and recorded activities, both published and unpublished, my narratives include their interactions with Christian leaders and public intellectuals in six aspects – theological, missiological, political, ethical, sinological, and ecumenical – to pinpoint what social-political actions Asian Christians took in response to the unsettling changes and the ecumenical movements of their times. This study also highlights the historical encounters with Christianity in China and Japan to uncover the roles of Asian Christians in the reconstruction of Christianity in East Asia after World War II. It focuses on how Christianity, as a centerpiece of Western civilization, was perceived and received in China and Japan, each with its own distinctive culture, and how this “foreign” religion took root in Asia through confrontational encounters, including the global and the local process of cross-cultural transmission between the “universal” and the “particular” in confrontation, adaptation, competition, coexistence, and mutual influence. As part of globalization, Christian indigenization in East Asia sharpened the churches’ awareness of standing in a dynamic interaction within a multi-cultural and multi-religious society. The profound impact of state-religion hegemony in China and Japan not only created the unique characteristics of local churches and Christian communities but also made two important bases for Christianity: a non-denominational Three-Self church in China and the multi-denominational churches in Japan. From this point of view, Christianity, after repeated endeavors, has finally integrated into East Asian nations. In helping to transform Christianity into an indigenized Asian religion, Jiang Wenhan and Takeda Kiyoko, each in their own way, have made Christian faith more accessible to the common people and Christian churches more acceptable in society. Their interactions with each other and their practices in the indigenization movement, with their Sino-Japanese Christian solidarity crossing a broad terrain from Shanghai to Tokyo, stood as one of the most significant achievements of Asian Christianity in the twentieth century

A Development Study of a New Bi-directional Solenoid Actuator for Active Locomotion Capsule Robots

A new bi-directional, simple-structured solenoid actuator for active locomotion capsule robots (CRs) is investigated in this paper. This active actuator consists of two permanent magnets (PMs) attached to the two ends of the capsule body and a vibration inner mass formed by a solenoidal coil with an iron core. The proposed CR, designed as a sealed structure without external legs, wheels, or caterpillars, can achieve both forward and backward motions driven by the internal collision force. This new design concept has been successfully confirmed on a capsule prototype. The measured displacements show that its movement can be easily controlled by changing the supplied current amplitude and frequency of the solenoid actuator. To validate the new bi-directional CR prototype, various experimental as well as finite element analysis results are presented in this paper

3DPCT: 3D Point Cloud Transformer with Dual Self-attention

Transformers have resulted in remarkable achievements in the field of image processing. Inspired by this great success, the application of Transformers to 3D point cloud processing has drawn more and more attention. This paper presents a novel point cloud representational learning network, 3D Point Cloud Transformer with Dual Self-attention (3DPCT) and an encoder-decoder structure. Specifically, 3DPCT has a hierarchical encoder, which contains two local-global dual-attention modules for the classification task (three modules for the segmentation task), with each module consisting of a Local Feature Aggregation (LFA) block and a Global Feature Learning (GFL) block. The GFL block is dual self-attention, with both point-wise and channel-wise self-attention to improve feature extraction. Moreover, in LFA, to better leverage the local information extracted, a novel point-wise self-attention model, named as Point-Patch Self-Attention (PPSA), is designed. The performance is evaluated on both classification and segmentation datasets, containing both synthetic and real-world data. Extensive experiments demonstrate that the proposed method achieved state-of-the-art results on both classification and segmentation tasks.Comment: 10 pages, 5 figures, 4 table

The Construction of a Community Long-term Care Model for Home-based Elderly Individuals

With rapidly aging populations, family care functions can become weakened, and community health services often lack unified standards. A standardized and professional community home-based long-term care model (CHLCM) for the elderly is urgently needed in many regions of China and in other countries. Here, we explored the indicators of the need for a CHLCM among elderly individuals, and we constructed a CHLCM. We created and distributed a questionnaire regarding the requirement of long-term care services, based on a literature review. The two-rounds Delphi method was used, involving 20 experts who were randomly selected from among the medical universities, community health service centers, and nursing homes in Nanning, Guangxi, China. The experts’ enthusiasm rates in the questionnaire’s two rounds were 95% and 100%, respectively. The authentic coefficient of the experts’ consulting was 0.857, and that of the experts’ academic level was 0.835; the judgement coefficient was 0.880 and the familiar coefficient was 0.855. The CHLCM includes service content and an evaluation. The coordination coefficients for the two primary, eight secondary, and 29 tertiary indicators were 0.200, 0.386, and 0.184, respectively (p<0.05). The experts’ enthusiasm and authority were high. The coordination of the experts’ agreement was sufficient, and the analysis results were reliable. The CHLCM includes 29 items that provide a foundation and references for the formulation of concrete indicators and subsequent research

Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission

Sequential labeling is a task predicting labels for each token in a sequence, such as Named Entity Recognition (NER). NER tasks aim to extract entities and predict their labels given a text, which is important in information extraction. Although previous works have shown great progress in improving NER performance, uncertainty estimation on NER (UE-NER) is still underexplored but essential. This work focuses on UE-NER, which aims to estimate uncertainty scores for the NER predictions. Previous uncertainty estimation models often overlook two unique characteristics of NER: the connection between entities (i.e., one entity embedding is learned based on the other ones) and wrong span cases in the entity extraction subtask. Therefore, we propose a Sequential Labeling Posterior Network (SLPN) to estimate uncertainty scores for the extracted entities, considering uncertainty transmitted from other tokens. Moreover, we have defined an evaluation strategy to address the specificity of wrong-span cases. Our SLPN has achieved significant improvements on two datasets, such as a 5.54-point improvement in AUPR on the MIT-Restaurant dataset.Comment: 11 pages, 2 figure

NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review

Neural Radiance Field (NeRF), a new novel view synthesis with implicit scene representation has taken the field of Computer Vision by storm. As a novel view synthesis and 3D reconstruction method, NeRF models find applications in robotics, urban mapping, autonomous navigation, virtual reality/augmented reality, and more. Since the original paper by Mildenhall et al., more than 250 preprints were published, with more than 100 eventually being accepted in tier one Computer Vision Conferences. Given NeRF popularity and the current interest in this research area, we believe it necessary to compile a comprehensive survey of NeRF papers from the past two years, which we organized into both architecture, and application based taxonomies. We also provide an introduction to the theory of NeRF based novel view synthesis, and a benchmark comparison of the performance and speed of key NeRF models. By creating this survey, we hope to introduce new researchers to NeRF, provide a helpful reference for influential works in this field, as well as motivate future research directions with our discussion section