bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study on the Impact of COVID-19 on the Income of the General Population in Jaipur, India
Authors: Purohit Pratiksha , Purohit Tushar , Choudhary Dr. Satender , Batwal Priyanka
Published: January 2025

The COVID-19 pandemic has emerged as a critical challenge for the current generation. One of its major implications is the adverse impact on the income of the general population. Several studies and reports have documented the significant effect of the pandemic on the earnings of individuals in both formal and informal sectors. Thus, there is an urgent need to investigate the pandemic's impact on various income groups and employment sectors, including government, private, business, professionals, and informal sectors. To explore the consequences of the COVID-19 pandemic on income levels in Jaipur, a research project was conducted. The study encompassed 211 individuals from diverse occupations and income groups to provide a comprehensive understanding of the pandemic's effect on income across different backgrounds and professions. Random sampling technique was used for data collection, and a Google form was employed to design the questionnaire and distribute it to respondents via email. Data collection took place over two months, from January to March 2023. The data collected were analyzed using SPSS software, and a chi-square test was utilized to examine the relationships between different variables. The participants were asked to provide detailed information on how the COVID-19 pandemic has affected their income and work patterns. The study's findings revealed that the impact on different occupations varied and had multiple dimensions. Therefore, policymakers should acknowledge that the pandemic's impact on income levels has not been uniform across different demographics. Consequently, policy responses should be customized to address the specific needs of distinct groups.
Improving the Effectiveness of Ideological and Political Education in Colleges and Universities from a Cross-cultural Perspective
Authors: Zhang Pengpeng
Published: January 2025

At present, the content of ideological and political education in colleges and universities is diversified, aiming to cultivate students' comprehensive qualities, especially international awareness and cross-cultural communication skills. However, challenges such as cultural differences and limitations of traditional educational methods still exist. To meet these challenges, strategies such as diversified teaching methods, international exchange activities, and improving teachers' cross-cultural literacy can be adopted. In addition, improving the curriculum system and strengthening team building are also indispensable. Only by promoting the innovation and development of ideological and political education in colleges and universities can we adapt to the development needs of the era of globalization and cultivate more high-quality talents with international vision and cross-cultural communication skills.
The Path of Self-improvement for University Teachers
Authors: Wang Chunlin
Published: January 2025

In today's era of knowledge explosion, the importance of self-improvement for university teachers has become increasingly prominent. With the continuous updating of subject knowledge and the rapid changes in teaching methods, if teachers stagnate, they will find it difficult to adapt to the rapidly changing educational environment. Teachers who continuously improve themselves generally have higher teaching quality and scientific research capabilities than teachers who lack self-improvement awareness. Teachers should improve their teaching level and scientific research capabilities by regularly participating in academic seminars, publishing high-quality papers, and introducing innovative teaching methods, so as to improve students' classroom satisfaction. As disseminators and innovators of knowledge, university teachers should establish the concept of lifelong learning and constantly improve themselves to adapt to the needs of the development of the times.
Research on the Cultivation of Digital Literacy Among Students in Application-oriented Private Universities
Authors: Chen Yuzhuo
Published: January 2025

Digital literacy is a direct reflection of the ability of contemporary college students to adapt to the information society, mainly in terms of digital survival ability, digital security ability , digital innovation and practical ability, etc. Applied private colleges and universities should focus on the organic integration of college students' digital information technology capabilities and digital literacy cultivation, and then effectively implement the important task of cultivating morality and cultivating people, and cultivate all-round socialist builders and successors for the new era.
"Expansion" and "Obstacles": The New Wave of Intelligent Media Empowering the Development of Film and Television Arts with Digital Technology
Authors: Liu Yixin , Li Jiaxin
Published: January 2025

Objective: With the profound transformation and upgrading brought by the new wave of intelligent media and digital empowerment, artificial intelligence is reshaping various aspects of art, including creation, distribution platforms, dissemination channels, and feedback effects. Firstly, personalized, innovative, and diversified artistic creation processes, along with intelligent, customized, and precise artistic dissemination processes, are cultivating "new aesthetic hotspots" in the era of intelligence. Secondly, amidst the landscape of technological change, ideological and ethical issues have become increasingly prominent, revealing the risks and obstacles of the "Artificial Paradise". Methods: Using the literature review method, conduct a comprehensive discussion on the new landscape of Film and Television Arts development. Conclusions: In response to these new changes and trends, the development of film and television arts in the era of artificial intelligence requires the anchoring of new policies and measures.
A Study on Discourse Strategies of All-employee Letters Within a Model of Trust-Repair Discourse
Authors: Wang Chenjun
Published: January 2025

The all-employee letter of the enterprise is the bridge of communication between the managers and the employees of the enterprise. At the same time, enterprises can rely on this kind of discourse to repair their corporate image in times of crisis and unite their strength in order to ensure their long-term sound development. This study builds a new framework model based on the trust repair discourse model constructed by Fuoli and Paradis (2014). By means of discourse analysis, this study selects all-employee corporate letters issued by Pinduoduo, ByteDance, Huawei and Jingdong Mall in response to negative public opinion from the top ten Internet companies in China as the corpus to explore their discourse behaviours and discourse effects. This study aims to provide new insights to promote the development of trust and discourse research, and to assist enterprises in crisis contexts to facilitate effective communication with the public, alleviate the trust crisis, and repair the image of trust.
On the Motivation and Translation Techniques of Chinese and English Cooking Vocabulary
Authors: Sun An
Published: January 2025

The diversity of cooking vocabulary in both Chinese and English reflect the uniqueness of their respective cultures. This paper aims to explore the motivation and translation techniques of Chinese English cooking vocabulary, in order to help English learners better understand and use these vocabulary. Firstly, it introduces the application of lexical motivation theory in English major learning. Secondly, it is pointed out that the motivation for Chinese and English cooking vocabulary mainly comes from their respective language and culture, historical traditions, as well as differences in ingredients and cooking methods. Then, the translation techniques for cooking vocabulary are introduced, including literal translation, free translation, additional translation, and cultural transformation techniques. Finally, mastering the corresponding translation skills can help the reader accurately express the meanings of these words, thereby promoting cultural exchange.
Research on Digital Media Installations of Emotional Interaction Based on Visual Communication Design
Authors: Fu Xiaoyao
Published: January 2025

Many studies have highlighted how digital media installations encourage sensory engagement, fostering emotional connections with audiences. However, scant literature delves into the profound emotions within these installations or whether viewers can extract emotional worth from the visual components. Consequently, this study aims to explore the emotional interaction between digital media installations and viewers and how viewers can derive emotional value from them, based on the perspective of visual communication design. This study encompasses two primary objectives: firstly, analysing digital media installations that can be experienced in person, focusing on the visual elements in the installations to capture emotional interaction and value; secondly, probing the correlation between the level of visual design and the emotional interplay between viewers and the underlying concepts intended by the artist's creation. Data collection employed three techniques, with participants categorized based on artistic and non-artistic backgrounds. Firstly, using cyber ethnography on the Instagram platform, posts and comments related to the target digital media installation of the study were observed to analyse their sentiments towards the corresponding work. Subsequently, 10 local London participants were recruited on WeChat for an on-site experience of the digital media installations, followed by semi-structured interviews conducted by the researcher to explore their assessments of emotional interactions and values elicited by specific visual elements within the installations. Finally, participants engaged in a drawing workshop, providing a more direct avenue to visualize emotions and delve deeper into the emotional value of the digital media installation from the viewer's perspective. The findings reveal that visual elements in digital media installations can help viewers understand the concept of the work and interact emotionally, with generating emotional value depending more on whether the conceptual mood of the work preset by the artist is positive or not. This essay provides a comprehensive literature review concerning the connections among digital media installations, visual communication design components, emotional interactions, and emotional values. In addition, Chapter Three describes three methods of research design and data collection: cyber ethnography, semi-structured interviews and drawing workshops. Chapter Four describes the main research findings while Chapter Five merges these findings with theoretical literature for a critical discussion and analysis. Finally, Chapter Six summarises the main findings, limitations and recommendations for future research.
Current Situation and Enlightenment of Core Competence Development of Psychiatric Nurses in China
Authors: Fang Qing , Shen Yuedi
Published: January 2025

With the progress of social civilization and the improvement of mental health awareness, the public's demand for high-quality mental health services has increased significantly. The complexity and professionalism of the mental health field requires psychiatric nurses to have a set of core competencies to ensure that they can provide high quality, safe care to their patients. At present, the overall level of core competence of psychiatric nurses in China is in the middle stage, in which the ability of ethics and legal practice is more prominent, but the ability of thinking and scientific research is relatively weak. The high scores of ethics and legal practice ability reflect that nurses in psychiatric specialties in China attach great importance to industry norms and patients' rights and interests. The lack of critical thinking ability and scientific research ability means that nurses' judgment and innovative problem-solving ability in the face of complex clinical situations need to be strengthened, which also limits their participation in nursing scientific research and the promotion of disciplinary progress. Drawing on the mature experience of foreign countries and combining with China's national conditions, hospitals should clarify the responsibilities of nurses, strengthen training, especially in critical thinking and scientific research literacy, build a supportive interdisciplinary work environment, and establish a professional certification system. In order to comprehensively enhance the core competence of psychiatric nurses, improve the quality of life of patients, meet the needs of high-quality mental health services, cope with the challenges in the field of mental health, and promote the field of mental health nursing in China to a higher level.
Strategies for Optimizing the International Discourse System Tailored to China's Modernization—A Study Based on COVID-19 and Corpus-Assisted Critical Discourse Analysis
Authors: Xiong Zhiwei , Xiong Chaoqun , Ding Song
Published: January 2025

With China getting closer to the center of the world stage, it is more important and urgent to build a Chinese-style modern international discourse system. Based on the three-dimensional framework of critical discourse analysis (CDA) by Fairclough and using the corpus method, this study collected reports from December 27, 2019 to March 12, 2024. With the help of the corpus tool AntConc, this study analyzes the use of high-frequency words and modal words in reports as well as the Chinese image constructed in reports. Through comparative analysis, this study advocates for the establishment of a differentiated, multidimensional, and diversified international discourse system, so as to better tell China's stories, make China's voice heard, and present a China that is credible, appealing, and respectable.
Integration Emploration of Maritime English Teaching and Ideological & Political Education Guided by POA Theory
Authors: Huang Xian
Published: January 2025

Under the background of Maritime Power Strengthening the Nation, it is even more important to implement ideological & political education upon maritime students. Maritime English, as a core professional course of Navigation technology, the ideological & political education endows future mariners with a sense of China Mood and international horizon. The possession of a loft goal can ensure them with a non-ceasing learning drive. Currently, the Ideological and political education of Maritime courses is still lacking behind in the aspect of teaching concept, curriculum construction, ideological & political education as well as the teaching process. This paper means to explore a method to integrate curriculum ideology into maritime English teaching guided by POA theory, strengthen the learning drive of students so as to effectively attain the prescirbed educational goal.
Research on the Impact and Countermeasures of EU Battery Regulations
Authors: Zhu Chunyan
Published: January 2025

The EU battery regulations have had a profound impact internationally, and are both a challenge and an opportunity for the Chinese battery industry. They have put forward higher requirements for environmental protection, technology, and supply chain management for battery companies exporting to the EU market. By studying the key provisions of the bill, such as strengthening the sustainability of battery products, carbon footprint management, recycling rate, and raw material traceability, the article found that the bill has brought severe challenges to Chinese battery manufacturers in terms of cost, technology, and market access. Countermeasures and suggestions are proposed to fill the gaps in regulations and policies, improve green production standards, improve the recycling system, optimize supply chain management, improve battery product technology and safety standards, and accelerate international layout.
The Important Role of Natural Language Processing in Computational Communication Research
Authors: Lian Shuguo
Published: January 2025

The rapid development of information technology has made the paradigm shift in communication studies increasingly evident, leading to a growing reliance on text data mining techniques in disciplinary research. This satisfies the developmental requirements of computational communication studies. This paper explores natural language processing (NLP) techniques, analyzing their role in integrating these technologies into computational communication research. The following conclusion is drawn: In the context of global information globalization, NLP technology is advantageous in addressing disciplinary issues.
Optimizing Supply Chain Efficiency Using Cross-Efficiency Analysis and Inverse DEA Models
Authors: Ye Chen , Bao Zhengde
Published: January 2025

This article introduces cloud computing technology, analyzes the application principles of energy-saving key technologies in cloud computing for IT support systems, and dissects the practical energy efficiency of these key technologies. By examining cloud-based business scenarios and analyzing the basis and algorithms for resource scheduling, intelligent power management contributes to reducing host power consumption during data center operation. The computational demands of business operations are positively correlated with energy consumption, and these demands can vary due to business requirements. Creating an energy-saving scheduling model and implementing it within the IT support cloud platform helps address energy-saving and emission reduction issues in cloud computing. Furthermore, the key energy-saving technologies in cloud computing enable flexible implementation of resource scheduling.
Modulation of Gut Microbiota and Glucose Homeostasis through High-Fiber Dietary Intervention in Type 2 Diabetes Management
Authors: Wang Yawen , Wen Yan , Wu Xiaofeng , Wang Lilu , Cai Hongwei
Published: January 2025

This study investigates the role of dietary modulation in shaping gut microbiota and its subsequent effects on metabolic regulation in individuals with type 2 diabetes mellitus (T2DM). Over an 8-week period, participants were divided into four dietary groups (CS, TS, CE, and TE), with the TE group receiving a high-fiber diet designed to support diverse microbial growth. Analysis showed a 24% increase in microbial richness in the TE group, achieving 235 observed OTUs at a sequencing depth of 30,000 reads, in contrast to 190 OTUs in the control group (CS). The TE group also exhibited a Gini-Simpson index of 0.88, indicating a balanced microbial ecosystem with reduced dominance of specific taxa, compared to 0.72 in the CS group. Principal Coordinates Analysis (PCoA) demonstrated a distinct microbial clustering in the TE group, reflecting a community composition associated with enhanced metabolic stability. Metabolically, the TE group showed an 18% reduction in fasting blood glucose (FBG) and a 15% increase in serum insulin, underscoring the high-fiber diet’s role in promoting glucose homeostasis. These findings underscore the therapeutic potential of dietary strategies in modulating microbiota for improved metabolic outcomes in T2DM. Further investigation into these mechanistic pathways is recommended to refine dietary interventions for metabolic health.
Big Data Technology in Daily Life
Authors: Li Chenxi
Published: January 2025

In today's era of information explosion, large-scale data technology has penetrated into every aspect of our lives, and the ubiquitous "figure" of big data can be seen in almost all industries. It is like a strong driving force, opening up new development directions for various industries, not only promoting industrial transformation and upgrading, but also profoundly promoting changes in people's lifestyles. From daily online shopping to urban traffic management, from medical diagnosis to personalized education, the application of big data technology has demonstrated its enormous value and potential. This article delves into the relevant knowledge of big data technology, including key aspects such as data collection, storage, processing, and analysis, revealing how big data has become an important basis for decision-making in modern society. In the field of online shopping, big data technology has achieved precise marketing and personalized recommendations by analyzing user behavior; In the field of transportation, it helps optimize route planning and alleviate congestion problems; In the field of medicine, big data helps with disease prediction and precision medicine; In the field of education, it promotes the personalization of teaching content and precise evaluation of learning outcomes. However, the application of big data technology is not without challenges. The issues of data security, privacy protection, and data quality still need to be urgently addressed. In response to these issues, this article proposes the future development direction of big data, including strengthening the construction of data security regulations, improving data processing technology, and promoting cross industry data sharing and cooperation, in order to fully tap the potential of big data and inject new vitality into the sustainable development of the social economy while ensuring personal privacy.
Research and Application of Asynchronous Programming in JavaScript
Authors: Liu Weizhi , Li Lin
Published: January 2025

JavaScript, as a widely used scripting language in web development, did not initially include direct support for concurrent execution of multiple tasks in its design. This means that in the traditional JavaScript programming model, tasks need to be queued and executed in order, greatly limiting the efficiency and responsiveness of the program, especially when dealing with situations such as network requests, file reads and writes, or user interactions that require waiting for external resources. To address this issue, asynchronous programming patterns have emerged, allowing programs to continue executing other tasks while waiting for certain operations to complete, thereby avoiding task blocking and queuing. The core idea of asynchronous programming lies in non blocking operations, which means that when a task (such as a network request) starts, it does not block the execution of subsequent code, but immediately returns and processes the result through callback functions after the task is completed. This mode greatly improves the response speed and user experience of applications, especially in complex web applications. With the release of ECMAScript 6 (ES6 for short), JavaScript took an important step in the field of asynchronous programming by introducing Promise objects. Promise is an object that represents the final completion or failure of an asynchronous operation and carries the value of the operation result. Its emergence provides a clearer and more chained way for asynchronous programming to handle asynchronous tasks and their results, effectively avoiding the common "callback hell" problem in traditional callback functions. This article delves into the application of Promise objects in JavaScript asynchronous programming. Promise not only simplifies the structure of asynchronous code, making asynchronous logic more intuitive and understandable, but also provides powerful error handling mechanisms through its. then(),. match(), and. terminal() method chains. In addition, Promise supports parallel execution of multiple asynchronous operations and achieves finer grained control over multiple asynchronous tasks through methods such as Promise. all() and Promise. race(). The introduction of Promise objects marks a significant advancement in asynchronous programming in JavaScript. It not only improves code readability and maintainability, but also provides strong support for developers to build high-performance and highly responsive web applications. With the continuous development of technology, promises have become an indispensable part of modern JavaScript development.
Adaptive Modeling and Risk Strategies for Cross-Border Real Estate Investments
Authors: Yang Jingwen , Zhang Yi , Xu Kai , Liu Wen , Chan Shui’e
Published: January 2025

In this study, we examine predictive modeling and risk management approaches tailored for cross-border real estate investments, with a focus on adapting models to stable and volatile market conditions. Drawing on an extensive dataset spanning diverse economic environments, we evaluate the performance of linear, polynomial, and logarithmic models in capturing real estate price dynamics. Findings indicate that the linear model provides reliable accuracy in stable markets (R2=0.98), aligning well with predictable, incremental trends typical of such environments. However, in markets marked by high volatility, the polynomial model outperforms, effectively capturing non-linear fluctuations with R² values of 0.89, thus providing a more robust framework for regions subject to economic and political shifts. To address currency risk and extreme loss potential, we integrate Conditional Value-at-Risk (CVaR) and Dynamic Optimal Hedge Ratio (DOHR) methodologies. These approaches collectively reduce return volatility by approximately 15% in volatile markets, enhancing stability in high-risk environments. Furthermore, the analysis underscores the strategic value of Environmental, Social, and Governance (ESG) alignment, particularly in fostering regulatory support and community acceptance, which are vital for long-term investment sustainability. Our findings suggest a tailored strategy: linear models with simplified risk management are well-suited for stable markets, while volatile markets benefit from polynomial models paired with advanced risk measures. Prioritizing ESG-compliant projects further mitigates regulatory and reputational risks. These insights provide a foundation for optimizing investment strategies across varied economic landscapes, with future work recommended to explore adaptive machine learning techniques for real-time model adjustments.
Threat Detection Driven by Artificial Intelligence: Enhancing Cybersecurity with Machine Learning Algorithms
Authors: Chen Heyao , Shen Zepeng , Wang Yong , Ke Hu , Xu Jian
Published: January 2025

This paper aims to explore the applications of artificial intelligence (AI) and machine learning (ML) in the field of cybersecurity, particularly in the development of end-to-end solutions for threat detection. By analyzing the current challenges in cybersecurity and the limitations of traditional threat detection methods, this paper seeks to demonstrate how AI/ML technologies can enhance the efficiency, accuracy, and automation levels of threat detection. The paper begins by introducing the core concepts of cybersecurity threat detection, including traditional methods such as signature-based detection, behavior-based detection, and rule-based detection systems. It then elaborates on the applications of machine learning in anomaly detection, malware detection, network traffic analysis, intrusion detection systems (IDS) and intrusion prevention systems (IPS), as well as user behavior analytics (UBA). Following this, the paper discusses the importance of data preprocessing and feature engineering in threat detection and their practical applications, including data cleaning, feature selection, and extraction. Finally, the paper explores the training and evaluation of models, the deployment of models, and the challenges they face, along with future trends in AI-driven threat detection. The research results indicate that AI/ML technologies can significantly improve the accuracy and efficiency of threat detection, particularly in handling unknown threats and automating detection processes. Through the application of various machine learning algorithms, such as anomaly detection, malware detection, and network traffic analysis, systems can better identify and respond to various network threats. However, AI-driven threat detection still faces challenges related to data quality, algorithm performance, and system implementation.
A Multi-modal Deep Learning Approach for Predicting Type 2 Diabetes Complications: Early Warning System Design and Implementation
Authors: Xiong Ke , Cao Guanghe , Jin Meizhizi , Ye Biao
Published: January 2025

This paper presents a novel multi-modal deep learning framework for early prediction of Type 2 Diabetes (T2D) complications through an advanced early warning system. The proposed architecture integrates multiple data modalities including clinical measurements, laboratory results, and temporal patient data through a sophisticated attention-based fusion mechanism. The system implements specialized preprocessing techniques for different data modalities and employs an innovative feature extraction pipeline for comprehensive risk assessment. Experimental validation was conducted on a dataset comprising 15,847 patients collected over five years from multiple medical centres. The framework achieved 94.7% prediction accuracy with a 72-hour warning window, demonstrating superior performance compared to existing approaches. The implementation of adaptive threshold mechanisms reduced false positive rates to 4.8% while maintaining 93.8% sensitivity and 95.2% specificity. The system's effectiveness was validated through prospective testing on an independent cohort of 3,245 patients, showing robust performance across diverse patient populations. The attention-based fusion mechanism demonstrated a 15% improvement in prediction accuracy compared to conventional approaches. This research contributes to the advancement of medical artificial intelligence through interpretable deep learning models, providing healthcare practitioners with insights into the decision-making process while maintaining high prediction accuracy for early intervention in T2D complications management.
Performance Evaluation and Improvement of Blockchain Based Decentralized Finance Platforms Transaction Processing Liquidity Dynamics and Cost Efficiency
Authors: Zhu Junlin , Xu Tianyi , Liu Min , Chen Chao
Published: January 2025

Decentralized finance (DeFi) platforms need to handle increasing transaction volumes, ensure stable liquidity, and keep user costs manageable. This study evaluates the performance of a blockchain-based DeFi platform, focusing on synchronization accuracy, rendering speed, liquidity growth, and gas fee control. The platform consistently achieved high synchronization accuracy (99.2%) and low rendering latency (105ms) during peak transaction periods, demonstrating the effectiveness of its technical design. The platform’s liquidity pools grew steadily by $1.5 million per day, reaching $45 million over the study period. Price movements during large trades were kept within 5%, showing the success of its slippage management tools. Gas fees were reduced by 15% on average through transaction batching and throttling, though external factors like network congestion still caused occasional cost spikes. These findings highlight the platform’s ability to scale effectively while identifying areas for further improvement, such as integrating additional solutions to reduce gas fees and improve cost predictability. This study shows how thoughtful design can improve the performance and usability of DeFi platforms. Future work could focus on expanding cross-chain compatibility, improving gas fee management, and further optimizing the handling of liquidity and price stability. These efforts will help meet the growing demands of DeFi users and support the broader adoption of decentralized financial systems.
Deep Reinforcement Learning-based Resource Adaptive Scheduling for Cloud Video Conferencing Systems
Authors: Yan Lei , Zhou Shiji , Zheng Wenxuan , Chen Jingyi
Published: January 2025

This paper presents a new deep learning-based resource scheduling algorithm for online video chat. The framework addresses the issues of resource allocation efficiency and service efficiency in MCU environments. A comprehensive system architecture is designed, incorporating a unified resource pool and intelligent scheduling mechanisms. The deep reinforcement learning model employs an actor-critic network structure with custom-designed state space and reward functions optimized for video conferencing workloads. The framework uses adaptive resource allocation and load balancing techniques to ensure stability in heterogeneous systems. The experimental results show a significant improvement over traditional methods, achieving a 35.2% reduction in response time, a 28.7% increase in resource utilization, and a 23.5% improvement in performance. bandwidth. The system maintains consistent performance under high loads of up to 1000 users at the same time while ensuring 99.99% service. The solution provides a flexible and powerful way to control the cloud video conferencing, as well as potential applications in the delivery of large-scale business.
Comprehensive Evaluation of GLP1 Receptor Agonists in Modulating Inflammatory Pathways and Gut Microbiota
Authors: Wang Yawen , Wen Yan , Wu Xiaofeng , Cai Hongwei
Published: January 2025

This study provides a detailed examination of the anti-inflammatory effects of GLP-1 receptor agonists (GLP-1RAs), employing an integrative approach that combines multi-omics analysis with in vivo and in vitro experiments. The results showed a significant decrease in pro-inflammatory cytokines (−42%±3.5%, p<0.001) alongside a notable increase in anti-inflammatory markers (+38%±4.2%, p<0.001). Additionally, the intervention induced substantial restructuring of the gut microbiota, characterized by a 2.8-fold enrichment of Faecalibacterium prausnitzii (p<0.01) and a 2.1-fold increase in Roseburia spp. (p<0.05), together with an increase in short-chain fatty acids level, especially butyrate (+35%, p<0.01). These changes were closely related to improved cytokine regulation and enhanced metabolic activity. Comparative analyses further showed that GLP-1RAs exhibit better efficacy in reducing inflammatory markers relative to NSAIDs, as evidenced by lower cytokine levels and inflammation scores across both animal models and cell culture systems (p<0.05). Transcriptomic profiling identified 154 differentially expressed genes, with the upregulation of key anti-inflammatory pathways and the downregulation of pro-inflammatory mediators. The findings highlight the potential of GLP-1RAs as a targeted therapy for systemic inflammation, leveraging their effects on cytokine modulation, gut microbiota composition and metabolic pathways. Future studies should focus on optimizing GLP-1RA-based interventions by exploring their long-term effects and potential synergies with microbiota-directed therapies for chronic inflammatory conditions.
Precision-Engineered Nanocarriers for Targeted Treatment of Liver Fibrosis and Vascular Disorders
Authors: Wang Yawen , Wang Lilu , Wen Yan , Wu Xiaofeng , Cai Hongwei
Published: January 2025

Effective treatments for chronic diseases like liver fibrosis and vascular disorders remain challenging due to difficulties in achieving targeted drug delivery and consistent results. In this study, we developed and tested vitamin A-modified micelles and biomimetic nanoclusters as potential tools for targeted treatment. These nanocarriers were carefully studied, showing uniform size (125.4 ± 5.2 nm for micelles and 84.7 ± 3.8 nm for nanoclusters), high drug loading efficiency (>90%), and sustained release, making them suitable for therapeutic use. In vitro tests showed that the nanocarriers were effectively taken up by cells and significantly affected hepatic stellate cells and vascular smooth muscle cells. In animal studies, nanoclusters performed better than micelles in two models: a carbon tetrachloride-induced liver fibrosis model and a porcine pancreatic elastase-induced abdominal aortic aneurysm model. The nanoclusters achieved a fibrosis reduction of 78.4% and decreased aortic dilation by 45.6%, demonstrating strong therapeutic effects. Further analysis revealed clear links between drug concentration, cell uptake, and therapeutic results. Time-based tests showed that the nanoclusters maintained a steady therapeutic effect of 85% ± 3% over 72 hours. The study highlights the importance of well-designed nanocarriers in improving treatment outcomes for complex diseases. Vitamin A-modified micelles and biomimetic nanoclusters show great potential for targeted and long-lasting drug delivery. Future work will focus on large-scale production, ensuring safety, and adding imaging methods to support their use in precision medicine.
AI End-to-End Autonomous Driving
Authors: Wang Yong , Shen Zepeng , Hu Ke , Yang Junqi , Li Changlin
Published: January 2025

This study aims to explore the performance and challenges of an end-to-end autonomous driving decision model based on a deep convolutional neural network (CNN) in practical applications. Firstly, this paper introduces the basic principles of deep convolutional neural networks and their application background in autonomous driving. Subsequently, it describes in detail the spatial feature extraction models based on deep convolutional networks, including the PilotNet baseline model and the spatial feature extraction model based on transfer learning. Based on this, an end-to-end decision model for longitudinal and lateral control of intelligent vehicles is constructed. The longitudinal and lateral control models are discussed separately, and more complex decision-making capabilities in autonomous driving scenarios are achieved through a combined model. Through experiments on the Udacity and Comma2k19 datasets, this paper demonstrates the performance of the end-to-end model. The experimental results show that the end-to-end model can effectively learn driving strategies from image data and exhibits good generalization ability and robustness under different environmental conditions. Feature visualization analysis further reveals the internal mechanism and decision basis of the model. Although the end-to-end model shows great potential in autonomous driving, this study also reveals some challenges in its practical application, including the interpretability of the model, the quality and diversity of the dataset, and the decision-making ability in complex environments. Future research should focus on addressing these issues to promote the further development and application of autonomous driving technology. Overall, this study provides a comprehensive research framework and practical foundation for end-to-end autonomous driving decision models based on deep learning.
Türkiye’nin İklim Değişikliğine Yönelik Politikaları ve Kurumsal Yapısı
Authors: Özkaya Selçuk
Published: January 2025

İklim değişikliği yalnızca hava desenlerindeki değişikliklerle ilgili değildir; ekosistemleri, toplumu ve acil eylem gerektiren birçok başka alanı da etkiler. Sonuç olarak, iklim değişikliği bir kriz yaratır. Bu kriz, etkileri her geçen gün artan, en belirgin etkisi dezavantajlı gruplar üzerinde olan, karmaşık bir yapıya sahiptir. Bu durum, dezavantajlı grupların krizden daha az sorumlu olmalarına rağmen olumsuz sonuçlarına karşı daha savunmasız olmaları nedeniyle iklim adaleti kavramını ön plana çıkarır. Bu nedenle, iklim politikalarında iklim adaleti dikkate alınmalıdır. Bu bağlamda, bu çalışmanın amacı, Türkiye'nin iklim değişikliğine ilişkin politikalarını ve kurumsal yapısını iklim adaleti kapsamında değerlendirmektir. Çalışma, iklim adaletine odaklanarak Türkiye'nin iklim değişikliği politikalarını ve kurumsal çerçevesini iyileştirmeyi amaçlamaktadır. 2010-2023 ve 2024-2030 yıllarını kapsayan iklim stratejileri ve iklim eylem planları da dahil olmak üzere politika belgeleri bu çalışmanın birincil materyalini oluşturmaktadır. Daha sonra iklim değişikliğine ilişkin kurumsal yapı incelenmiştir. Çalışmanın yöntemi içerik analizidir. Çalışmada, iklim adaletinin 2024'ten itibaren önceki dönemlere kıyasla politika belgelerinde giderek daha fazla ele alındığını saptanmıştır. Ayrıca, Türkiye'nin Paris İklim Anlaşması'na taraf olduğu 2021'den sonra iklim değişikliği için kurumsal yapı artık bakanlık düzeyinde yönetilmektedir. Ancak kurumsal olarak, dezavantajlı gruplardan ziyade TÜSİAD ve MÜSİAD gibi sermaye grupları, temsil edilmektedir.
Política, afectos y virtudes. Apuntes para una reorientación “social-republicana” de la política democrática radical de Chantal Mouffe
Authors: Torre del Pozo Consuelo de la
Published: January 2025

Este ensayo apunta a una reorientación crítica del proyecto de democracia radical de Mouffe, basada en un análisis de las limitaciones de su aproximación al potencial político de los afectos. Para ello, propongo una recuperación material de las formas de identificación político-social –que en el marco discursivo de Mouffe no se integra adecuadamente–, sobre la base de una comprensión transferencial (Dean) y participativa de los partidos. Lo que defiendo es una rehabilitación social-republicana de la práctica ciudadana, regulada por las virtudes sociales necesarias para la mantención y refuerzo del compromiso democrático, frente a las amenazas de desafección, polarización y manipulación populista.
Performatividad y Ontología Social. Alcances de lo semiótico y lo lingüístico en la constitución del orden social
Authors: Paolicchi Leandro
Published: January 2025

En el presente artículo abordo una serie de teorías que han tenido a la performatividad y a la comunicación, más precisamente, como centro de indagación y como forma de explicar la constitución de las dimensiones fundamentales de la estructura social. En concreto, presentaré y discutiré aquí el llamado ‘constructivismo comunicativo’, representado por las teorías de H. Knoblauch y J. Reichertz. Luego de presentar su relevancia y algunas de sus características más destacadas (I), hago foco en el problema del alcance de lo lingüístico en estas teorías (II), así como en el fundamento del lazo social tal como ellas lo entienden (III). Finalmente (IV), esquematizo cuáles deben ser las condiciones generale
Philipp Mainländer. Fragmentos pesimistas. Selección, introducción y traducción de Sandra Baquedano Jer. Sequitur, Madrid, 2023, 135 pp.
Authors: Gajardo Jaña Paolo
Published: January 2025

En los últimos años la figura de Philipp Mainländer ha suscitado una atención renovada por las diversas traducciones de sus obras. En efecto, a través de iniciativas como Mainländeriana se ha llegado a reconocer en este joven autor pesimista mucho más que un mero sucesor de Schopenhauer y precursor de Nietzsche. Este eslabón entre ambos merece por sí mismo atención como cualquiera de estos gigantes de la filosofía. En efecto, la obra de Mainländer tiene mucho que ofrecer en materia filosófica y esta nueva entrega constituye una invitación renovada para adentrarse en sus cavilaciones.
Claves para los nuevos mapas sociopolíticos. Algunas aportaciones desde el Giro Afectivo y la Macrofilosofía
Authors: Arizmendi Mar Paula
Published: January 2025

En este artículo nos aproximaremos a dos corrientes teóricas que pueden mapear de forma crítica e innovadora los itinerarios y fenómenos sociopolíticos contemporáneos. Para ello, en primera instancia, se mostrarán las definiciones, delimitaciones y potencialidades del giro afectivo, como una herramienta eficaz para diagnosticar los cada vez más decisivos elementos emocionales de la palestra política y social. Y, en segunda instancia, examinaremos algunas estrategias de la macrofilosofía para avanzar hacia aristas transversales, holísticas, inter, post y transdisciplinares, que puedan articularse desde terrenos que suelen ser dilemáticos en la contemporaneidad. Finalmente, con la ayuda del ejemplo del cognitariado como fenómeno sociopolítico susceptible de ser mejor comprendido a partir de dichas corrientes, en este texto incidiremos en algunos aportes que ellas pueden brindarnos en los diagnósticos (¿post?)filosóficos de la realidad social.
Nicole Darat. Contraciudadanía y democracia feminista, Santiago de Chile: Metales pesados, 2023, 149 pp.
Authors: Jerade Miriam
Published: January 2025

En la introducción a Contraciudadanía y democracia feminista, Nicole Darat recuerda a Olympe de Gouges, una feminista maltratada no solo por la historia sino también por el canon de la filosofía y el feminismo. En su Declaración de los derechos de la mujer y de la ciudadana de 1971, hace un señalamiento significativo sobre cómo el masculino genérico excluye a las mujeres no solo del universal sino de la ciudadanía y los derechos. Esta no es una discusión puramente lingüística o en todo caso es una que apunta a la dimensión política del lenguaje. De Gouges señaló con su título que los derechos del hombre y del ciudadano derechamente excluían en su genérico neutro a las ciudadanas y, como escribe Darat, la ejecución de Olympe de Gouges en el cadalso muestra que la fraternidad tenía unos límites estrechos. Algo parecido ocurrió en Chile en los registros electorales de 1875, recuerda Darat, pues para votar la ley imponía como requisito saber leer y ser chileno. Un grupo de mujeres letradas intentó registrarse, pues si el masculino es genérico y sabían leer, no había herramienta para refutar dicha interpretación. La respuesta fue promulgar en 1884 una ley que prohibía expresamente el voto femenino. En este sentido, el libro de Darat tiene una posición política muy clara: no es cuestión solo de incluir a las mujeres (y a otras minorías) en la ciudadanía, o de la extensión del concepto de ‘ciudadanía’, mucho menos saldar el problema agregando como en los discursos de los políticos: ‘chilenas y chilenos’; las preguntas son mucho más radicales: 1) si la democracia, en su versión liberal o republicana, puede efectivamente albergar una ciudadanía feminista. Esto último, sin dejar de contemplar a los “populismos”, clivados en la idea de un pueblo masculino y heterosexual y, 2) cómo la política feminista irrumpe agónicamente en el espacio público y lo transforma. Ahora bien, no confundir la postura de Darat con un tipo de feminismo radical que sostiene que el Estado y el derecho son masculinos y el feminismo debe quedarse al margen o derechamente fuera, más bien la inspiración de este libro podrían ser las Bacantes de Eurípides que se autoexiliaron de la polis, pero vuelven para transformarla. En este sentido, la contraciudadanía, señala Darat, es un conjunto de prácticas subversivas de impugnación y de interrupción de las lógicas de la democracia.
Gila Sher. Logical Consequence. Cambridge Elements in Philosophy and Logic. Cambridge, Cambridge University Press, 2022, 91 páginas.
Authors: Ramírez Figueroa Alejandro
Published: January 2025

En los inicios de su libro, en la primera página, Sher plantea la cuestión central así: ¿en virtud de qué un enunciado S es consecuencia lógica de un conjunto de sentencias Γ? ¿Qué es lo que diferencia a una mera consecuencia de una consecuencia lógica, pues toda consecuencia lógica es consecuencia pero no a la inversa? ¿Por qué “2 tiene un sucesor” es consecuencia lógica de “todo número tiene un sucesor”, mientras que “x es soltero” no lo es de “x es no casado”?
Factores que inciden en la comercialización de la melcocha ecuatoriana
Authors: Pinargote Vélez Andrea Alexandra
Published: January 2025

Este estudio tiene como objetivos, determinar los factores que inciden en la comercialización de la melcocha ecuatoriana con envoltura ecológica y analizar la demanda del producto, para ello se realizó una investigación descriptiva y empírica, la muestra fue seleccionada mediante criterios de conveniencia en donde se encuestó a un total de 244 personas, entre ellos estaban personas que comercializaban el producto y también a la comunidad en general, para conocer la aceptación del producto. Los resultados permitieron conocer, que más del 50%, considera que los factores del entorno que más inciden en la comercialización del producto son los económicos. Además, se realizó un estudio de mercado, donde se pudo conocer que el 83% de los encuestados consume melcocha de manera no frecuente, por la falta de ofertantes del producto.