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Current cancer treatment strategies continue to face significant challenges, primarily due to tumor relapse, drug resistance, and low treatment efficiency. These issues arise because certain tumor cells adapt to the host immune microenvironment and evade the immune system. This study presents a new cancer immunotherapy strategy using serum-based antibodies from mice exposed to mouse cutaneous squamous cell carcinoma (mCSCC). The experiment was conducted in three stages. In the first stage, mCSCC cells were isolated and expanded cultured from DMBA/TPA-induced mCSCC. In the second stage, these expanded tumor cells were injected into healthy mice to stimulate the production of anti-tumor antibodies. In the final stage, therapeutic serum was extracted from these healthy mice and reintroduced into the tumor-bearing mice. An ELISA assay was utilized to analyze the levels of p53, Bcl-xL, NF-κB, and Bax. The results showed that the serum treatment not only reduced tumor volume but also reversed changes in p53, Bcl-xL, NF-κB, and Bax. In conclusion, this study developed a new immunotherapeutic strategy for treating mCSCC. However, further research is needed to fully comprehend the mechanism of this serum treatment.

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an attention mechanism can be regarded as a dynamic weight adjustment process based on features of the input image. Attention mechanisms have achieved great success in many visual tasks, including image classification, object detection, semantic segmentation, video understanding, image generation, 3D vision, multimodal tasks, and self-supervised learning. In this survey, we provide a comprehensive review of various attention mechanisms in computer vision and categorize them according to approach, such as channel attention, spatial attention, temporal attention, and branch attention; a related repository https://github.com/MenghaoGuo/Awesome-Vision-Attentions is dedicated to collecting related work. We also suggest future directions for attention mechanism research.

This paper explores the implicit thought of the “body-network” in Maurice Merleau-Ponty’s phenomenology of the body, drawing from both his earlier and later works. It demonstrates that, for Merleau-Ponty, the phenomenal body is inherently interconnected with the world through motor intentionality. Meanwhile, in his later concept of “flesh,” this interconnectedness deepens into a relationship of mutual reflection and chiasmic intertwining, where bodies and the world continuously mirror and permeate each other. The paper then introduces the Huayan Buddhist metaphor of Indra’s Net, along with Fazang’s interpretation of it. A detailed comparative analysis is conducted between Merleau-Pontian body-network and Fazang’s understanding of Indra’s Net. The paper argues for a profound resonance between the primordial characteristics of the Merleau-Pontian body-network—namely, relationality and reflectivity—and Fazang’s key concepts, such as “mutual identity” (相即), “mutual inclusion” (相入), and the contemplative idea that “the images of many bodies are reflected in one mirror” (多身入一鏡像觀). Despite their distinct cultural and philosophical vocabularies, both thinkers construct a relational ontology aimed at deconstructing entrenched dualisms. Through this in-depth comparative study using the Internet of Bodies (IoB) as a case study, this paper demonstrates that the IoB technology exhibits only superficial resemblances to the Merleau-Pontian body-network and Fazang’s interpretation of Indra’s Net. To address the ethical challenges posed by the IoB, it is imperative to integrate the shared philosophical insights of Merleau-Ponty and Fazang in constructing a critical techno-ethics capable of interrogating the ontological reduction and power asymmetries inherent in contemporary technological networks. Merleau-Ponty’s concept of reversible flesh inspires an ethics of contextual sensitivity and user agency, resisting the reduction of lived experience to data points. Meanwhile, Fazang’s Huayan Buddhism, with its principles of mutual identity and mutual inclusion, reveals the relational nature of data, challenging its treatment as neutral or absolute. Together, these philosophies advocate for a decentralized, reciprocal techno-ethics that prioritizes embodied meaning over surveillance and control.

This study, positioned at the critical juncture of China’s transition from digitalization to intelligence, explores how Internet use is associated with social trust and perceptions of social fairness, as well as how these relationships vary across different social contexts. Based on nationally representative data from the Chinese General Social Survey (CGSS) 2021, regression analysis and Bootstrap methods were employed to systematically examine the relationship between internet usage frequency and perceptions of social fairness as well as the mediating role of social trust. Urban-rural heterogeneity was identified as the primary source of variation through within-sample comparison, while Henan Province was examined as a validating case to test mechanism robustness. The research found that in the national sample, internet usage frequency was significantly negatively associated with perceptions of social fairness, and this relationship was partially mediated by the decrease in social trust, with the mediating effect accounting for 24% to 37% of the total effect depending on model specification. Notably, urban residents experience twice the negative impact compared to rural residents (β_urban = −.080 vs. β_rural = −.040, p < .01), revealing significant digital divide effects. The Henan case (n = 398) demonstrates consistent mechanism direction with the national sample, with effect sizes even larger (β = −.089) though marginally significant due to smaller sample size, validating the theoretical robustness of the identified pathways. These findings provide important implications for digital governance practice: digital inclusion policies should shift from “universality-oriented” to “quality-oriented”; mechanisms should be constructed to protect social trust in the digital era; and differentiated urban-rural digital development strategies should be implemented to promote positive interaction between digitalization and social harmony. Plain Language Summary How Internet Use Affects People’s Views on Fairness in China: The Role of Trust and Urban-Rural Differences This study examined how internet use affects people’s feelings about fairness in Chinese society. With over 1.1 billion internet users in China, understanding these effects is crucial for social harmony. We analyzed survey data from 8,000 people across China. We found that people who use the internet more frequently tend to feel society is less fair. This happens because internet use reduces their trust in others—when people trust others less, they also see society as less fair. Trust explains about one-quarter to one-third of this relationship. Importantly, this effect is much stronger for city dwellers than for rural residents. Urban internet users experience twice the negative impact compared to rural users, likely because they encounter more algorithm-driven content showing social inequalities and have weaker face-to- face community connections. These findings suggest that digital policies should go beyond simply providing internet access. Instead, they should focus on helping people use the internet wisely, protecting social trust online, and recognizing that cities and rural areas need different approaches to digital development.

With digitalization and the support of policies, the creative industries have shown rapid growth in the last 20 years. Open forms of collective learning, user engagement and social networks have become popular to generate IPs and values. Meanwhile, government policy can support the sectors through subsidies, regulations, standardization, and protections at regional and national levels. This paper aims to explore the role of government policy in the innovation of creative industries from a macro dynamic perspective. The research method combines a structured literature review, a secondary document review of industry reports and government policy, and thematic content analysis. Through in-depth studies of the UK's and China's animation sectors, the paper identifies key elements of closed innovation, social innovation, and open innovation systems in the market. Comparisons of national government policies since 2000 reveal different approaches for countries where creative sectors are well-established, and for those starting with limited knowledge resources. A dynamic model is developed to address the evolution of macro dynamic innovation systems and the role of policies as interactive mechanisms. Practical implementation and future research areas are also suggested.

The purpose of this study is to investigate the efficiency of the production-oriented approach research (POA-R) teaching approach on academic English courses. The six-week study involved thirty-nine postgraduate students from Guilin Medical University studying medical technology. These students were randomly divided into POA-R (19 participants) and non-POA-R (20 participants) groups. The process of study in the POA-R group was divided into three stages, motivating, enabling, and assisting. The instructor gave the class a task at the motivational stage that involved taking the academic IELTS exam, writing a review article and giving an oral presentation about their research topic. At this stage, students are challenged to find relevant information searching PubMed and other literature databases. The teacher served as a facilitator of learning and would not offer information related to the tasks. During the enabling phase, students were encouraged to ask their supervisor for help and guidance. Students ask questions in class, and the instructor discusses the questions with the students and guides them to solve the questions independently. During the assessment stage, students take the academic IELTS exam, finish the review article, given an oral presentation related their research project, and complete an instructional questionnaire. The non-POA-R group was instructed by the teacher lecture method, comprising six lectures and an oral presentation in addition to the completion of a review article. The final grades of course include a review article, an oral presentation, and an academic IELTS test. The results revealed that the students in the POA-R group outperformed the non-POA-R group in terms of mean scores on the IELTS exam, oral presentation, and review article. To further support and demonstrate the advantages of the POA-R teaching approach, an instructional questionnaire using Likert scales and the attitudes of their supervisors was employed. In conclusion, the POA-R teaching approach is a highly successful strategy for enhancing postgraduate students’ academic English proficiency. It greatly enhanced the participants’ academic knowledge, learning interest, and active learning.

The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Transformer (PCT) for point cloud learning. PCT is based on Transformer, which achieves huge success in natural language processing and displays great potential in image processing. It is inherently permutation invariant for processing a sequence of points, making it well-suited for point cloud learning. To better capture local context within the point cloud, we enhance input embedding with the support of farthest point sampling and nearest neighbor search. Extensive experiments demonstrate that the PCT achieves the state-of-the-art performance on shape classification, part segmentation, semantic segmentation, and normal estimation tasks.