bluuebunny/crossref_metadata_2025 huggingface dataset:
Intervento di case management infermieristico per migliorare la gestione del tempo e la soddisfazione dei professionisti sanitari nelle cure palliative oncologiche: uno studio pilota pre-post di fattibilità
Authors: Fusetti Viviana , Pigni Alessandra , Alfieri Sara , Brunelli Cinzia , Lusignani Maura , Caraceni Augusto
Published: February 2025

BACKGROUND: Gestire un percorso di cure palliative oncologiche è spesso gravoso per i professionisti.
SCOPO: Valutare la fattibilità di uno studio sugli effetti del case management infermieristico per migliorare la gestione del tempo e la soddisfazione nelle attività tra il personale sanitario e amministrativo in un contesto ambulatoriale di cure palliative.
METODI: Uno studio pre-post è stato condotto da febbraio ad agosto 2023. Tutti i professionisti hanno stimato il tempo giornaliero dedicato alle proprie attività e la relativa soddisfazione, prima e sei mesi dopo l’implementazione di un servizio di case management infermieristico. Sono stati registrati dati sulle procedure di raccolta, la chiarezza delle istruzioni, la rilevanza delle misurazioni, e l’implementazione dell’intervento.
RISULTATI: Hanno partecipato undici professionisti. Tutte le misure di fattibilità sono state giudicate appropriate. Dopo l'implementazione del case management, i medici hanno registrato una riduzione del tempo per la preparazione dei piani di trattamento (-7,00 min/giorno), telefonate (-27,8 min/giorno) e documentazione (-13,7 min/giorno). Anche l'anamnesi infermieristica (-10,0 min/giorno) e il coordinamento delle cure (-15,8 min/giorno) hanno mostrato riduzioni tra T0 e T1, con soddisfazione variata da 3 a 5,5 punti.
CONCLUSIONI: Il design dello studio proposto è stato considerato fattibile e adeguato da tutti i partecipanti. L’introduzione di un case manager infermieristico ha portato a una riduzione del tempo dedicato alle telefonate e alla documentazione amministrativa per il personale medico, aumentando la soddisfazione lavorativa. Sono necessari studi più ampi e solidi per indagare l'impatto di un case manager infermieristico sulla soddisfazione e la gestione del tempo dei professionisti nelle cure palliative oncologiche.
Analisis Sistem Pembayaran Cash On Delivery (COD) pada Bisnis Online: Kajian Kesesuaian dengan Etika Bisnis Islami
Authors: Fata Zainol
Published: February 2025

In recent times, online buying and selling has become a favorite choice and is in great demand among the public, especially among young people. The reason why online buying and selling is so popular is because the payment method offered to the public in online buying and selling transactions is Cash on Delivery (COD). However, from the perspective of Islamic business ethics, the application of the COD system in online business needs to be studied further. Islam has muamalah principles that must be taken into account in every economic activity, including the practice of buying and selling so that online buying and selling business people must understand the principles of muamalah in Islam. Therefore, this research will analyze the extent to which the COD payment system in online businesses is in accordance with Islamic business ethics. The approach used in this research is a qualitative descriptive approach. This research is a qualitative descriptive research that uses library study techniques as a data collection method. Through an in-depth literature review, researchers can gain a comprehensive understanding of concepts, theories, and previous research findings related to the topic being studied. The application of ethics in COD transactions must be sourced from the teachings of the Al-Quran and Hadith as the main guideline. Several ethical principles that are relevant in muamalah and can be applied in COD-based online buying and selling transactions include justice, honesty, trustworthiness and the prohibition of usury.
A Comparative Study on the Effectiveness of Traditional and Modern Teaching Methods
Authors: Chen Xiyu
Published: February 2025

With the progress of the times, traditional teaching methods are gradually fading out of view in some developed countries, followed by modern teaching methods. Traditional teaching, often teacher-centered, focuses on knowledge transmission and memorization, while modern methods emphasize student-centered learning, active engagement, individualized instruction, and the use of technology. This study compares the effectiveness of traditional and modern teaching methods in relation to child development and educational psychology. Drawing from key theories in child development, such as Piagets cognitive development stages and Vygotskys social-cultural theory and zone of proximal development, this research explores how different methods support or hinder childrens cognitive, emotional, and social growth. Furthermore, principles from educational psychology, such as motivation and learning theories, offer a framework for evaluating the effects of these strategies on students' comprehensive academic performance and growth. The study finds that a balanced strategy, incorporating both classic and contemporary methods, yields optimal results by addressing varied learning demands and fostering critical thinking, creativity, and profound knowledge.
Research on the Impact of Gamified Instruction on Psychological Noise in Intercultural Communication and Its Optimization Strategies
Authors: Sun Wenxin
Published: February 2025

In a globalized educational environment, student populations from different cultural backgrounds have diverse communication barriers, including psychological noise, which affects teaching effectiveness and learning experiences. As an innovative teaching method, gamification instruction attempts to increase student engagement and motivation by simulating game elements and mechanisms, thus reducing the impact of psychological noise. Through a comprehensive analysis of related literature and empirical research, this paper aims to reveal the correlation between gamified teaching and psychological noise and its potential impact on reducing psychological noise. It has been found that gamified teaching can significantly affect and alleviate the problem of psychological noise; meanwhile, by enhancing learning participation and motivation, gamified teaching helps significantly reduce the negative impact of psychological noise. These findings aim to help learners better adapt to different cultural environments, improving intercultural communicative competence, and help educators adjust their gamified teaching strategies to specific cultural contexts to further optimize the teaching effect and to create a more inclusive and efficient learning environment.
Exploring the International Prospect of China-chic Culture: An Employment Potential for Chinese Foreign Language Majors
Authors: Yin Jiabeixuan
Published: February 2025

Teenagers' employment prospects are influenced by personal skills, experience, and social factors like local economics, culture, and national policies. Foreign language graduates in China face employment challenges due to numerous reasons. With intercultural communication becoming central to global development, China's emphasis on cultural confidence and soft power is creating new opportunities. China-chic culture, which arises in accordance with the demand of the era, may offer a potential outlook for foreign language majors' employment situation in the process of navigating the global market. This article mainly uses the method of case study of the Sino-Etiquette Communication with Excellent Gift project, combined with statistical analysis of research on the perspectives on employment prospects and their attitude towards the China-chic industry among foreign-language-majored undergraduates, and attempts to offer a kind of practical solution to deal with their present employment struggles. The primary conclusion the research has reached is that the thriving sunrise industrythe China-chic industrycan serve as a new employment idea for foreign language students in its navigation to the international market.
Analysis of Employment Problems in China and the United States
Authors: Zhong Chenyixin
Published: February 2025

The background of employment research in China and the United States stems from the impact of globalization and technological progress on the labor market. Close economic, technological, and trade ties between the two countries have led to interlinked employment structures and unemployment rates. Through the method of literature review, this paper discusses employment problems in China and the United States. The study found that China's industrialization and urbanization have intensified competition for jobs, while the United States faces automation and outsourcing challenges in traditional industries. In addition, China mainly faces the adjustment of labor structure under the economic transformation, while the United States suffers from the income polarization caused by industrial hollowing and technological development. Therefore, flexible policy adjustment and international cooperation are the keys to solving the employment problem.
Character Gender Fixation: The Memes of Bias and Stereotypes
Authors: Wang Siqi
Published: February 2025

With the continuous progress of people's thinking, the road to the future is no longer limited to the inherent gender model, and more will be combined with the individual's own characteristics to develop a private model, so as to maximize personal advantages and make full use of them. However, to some extent, it will be constrained by some inherent patterns, men and women put aside the stereotyped image of gender, on the single behavior pattern and individual ability, and can not directly conclude the conclusion, boys also have a gentle and delicate side, girls also have a strong, informal side, the two can be compared fairly in the certainty of gender at the same time. The purpose of this article is to describe the deviation of cognition of men and women in the social environment under the influence of fixed gender roles. All kinds of work, cultural biases and stereotypes. Gender role cognition does not exist in the traditional sense of the inherent conclusion, but about the individual behavior habits and norms of the definition of life style. Analysis breaks this way of thinking and maximizes individual development as much as possible.
Analysis of the Application of Educational Equity in Primary Education
Authors: Yan Yuanyuan
Published: February 2025

Traditional teaching modalities, which mainly feature teachers' lecturing and systematic knowledge imparting while disregarding students' initiative, have become difficult to accommodate the demands of modern education. Although the group cooperative approach is conducive to enhancing students' comprehensive capabilities, it also has deficiencies. Education equity refers to providing citizens with equal opportunities for learning and development, encompassing fair and just access to education and enjoying balanced educational resources for potential realization. This article analyzes the application of traditional and group collaboration modalities in primary school teaching, dissects the causes of educational inequality, excavates the value and patterns of both modalities and explores how to incorporate educational equity. It aims to facilitate the critical inheritance and modern transformation of traditional modalities and the improvement and development of group collaboration modalities. Eventually, it combines both with educational equity to serve primary school education and teaching.
A Brief Discussion on Women and Buddhist Education in the Northern Dynasties
Authors: Zhou Minhao
Published: February 2025

The Northern Dynasties was an era marked by significant social turmoil in Chinese history, with frequent shifts in power and ongoing warfare. This instability fostered a sense of disillusionment with the present world and a desire for a blissful afterlife. Such conditions created an ideal environment for the spread of Buddhism. As a vulnerable group in society, women, on the one hand, endure oppression under the traditional cultural background; on the other hand, it is difficult for them to build their own careers like men, and they hope to achieve personal liberation in some ways in times of unrest. During this time, women had a significant relationship with Buddhist education. The extensive propagation of Buddhism in the Northern Dynasties offered women new educational opportunities, which deeply influenced their lifestyles, family roles, and level of social involvement. In addition, during the Northern Dynasties, Buddhist education also had a profound impact on society through the enlightenment of women.
Views on Life and Death in Taoism and Ancient Greek Religion: Deities Governing Life and Death in Taoism and Ancient Greek Religion
Authors: Li Yanhui
Published: February 2025

Life and death are inevitable processes in life, and religions have unfolded rich imaginations and discussions around this topic. Taoism and ancient Greek religion, as religions of the East and West respectively, have formed their own unique views on life and death. This paper, through literature analysis and comparative analysis, studies the views on life and death reflected in the deities that govern life and death in Taoism and ancient Greek religion, compares the similarities and differences in their views on life and death, and explores the reasons behind them. The study finds that Taoism believes that human life originates from the Dao, while ancient Greek religion holds that humans were created by the gods. Taoism seeks immortality and the self-determination of fate, favoring a peaceful and tranquil life, whereas ancient Greek religion emphasizes the glory of the present life and the irresistibility of fate, advocating adventure and ambition. Additionally, in Taoism, there is a belief in an afterlife following death, while ancient Greek religion lacks a clear concept of the afterlife. These aspects show the differences in the views on life and death between the two religions. Despite all these differences, there are some similarities in their respect and appreciation for the value of life and in using the moral judgment of the afterlife to maintain social order.
The Evolution and Integration of the Chinese Dulcimer: A Study of Cross-Cultural Musical Fusion
Authors: Yang Wenbo
Published: February 2025

The Chinese dulcimer (yangqin) is an instrument of Western origin (Persian origin) that was originally known as the board zither. It was introduced to China through the Silk Road, either by land or ocean during the Ming and Qing dynasties. The Chinese dulcimer has been integrated into Chinese traditional opera as an accompaniment instrument and it is also played by local bands in various cities in China. Consequently, the Chinese dulcimer has gradually become a traditional symbol of Chinese music and has become a representative instrument of Chinese traditional music abroad, despite its Western origin. Interestingly, in the current Chinese dulcimer teaching process, many teachers will incorporate selected Western music into their curriculum because Chinese dulcimers only have a limited repertoire. The curriculum usually includes pieces such as Saint-Saens Introduction and Rondo Capriccioso and Sarasates Songs of the Wonderer, which were commonly played on the violin. There are currently efforts to develop and expand the repertoire of the Chinese dulcimer by incorporating Western musical elements. However, this work provokes questions, such as: How can Chinese and Western musical elements merge? What are the advantages and disadvantages of the yangqin when performing Western musical pieces? This article will discuss these topics here in depth.
Exploring the Restitution of Chinese Cultural Relics The Case of Tang Honglujing Carved Stone
Authors: Xu Xinyu
Published: February 2025

As an important historical artifact, the Tang Honglu Jing stone has significant historical value as a record of the interactions between the Tang Dynasty and the Bohai Kingdom. However, the theft of the stone in the course of history has triggered widespread concern about its recovery. This paper focuses on the recovery process of the Tang Honglujing stone and the dilemma and countermeasures for the restitution of cultural relics it reflects. The examination of Chinese and Japanese literature, alongside an analysis of historical events, provides an in-depth investigation into the timeline and circumstances surrounding the loss of the Tang Honglu Jing stone. At the same time, it analyses the dilemmas and reasons for the restitution of cultural relics by taking the Tang Honglu Jing stone as a concrete case. Finally, it analyses the measures that China should take in the future, such as legal improvement, practical exploration, international cooperation and cultural relics literature collation and search, in order to strengthen the recovery of lost cultural relics.
Social Media and Age-Based Stereotypes: The Reinforcement or Alleviation of Ageism
Authors: Dai Hanxi
Published: February 2025

The rapid reduction of late-life mortality rates and the drastic decline of global fertility rates have given rise to the aging population in many countries. Simultaneously, the digital revolution significantly increases the participation of digital technologies in people's daily lives. These two changes have amplified many existing problems. The social phenomenon of ageism has entered a new stage of alteration gradually, both in terms of its nature and significance. Therefore, the main purpose of this article is to investigate the current situation of age discrimination and to give an argumentative overview of how ageism is strengthened and alleviated after the prevalence of social media in people's lives. Based on the characteristics of social media, a logical discussion of whether these features would contribute to the alleviation or deterioration of ageism will be included in the third part of the article. Also, a few suggestions will be given in the article to assist in the mitigation of ageism via utilizing social media platforms. Advises are given mainly from the perspective of the government, which is related to legislation and educational reforms.
The Impact of Games on Individual Thinking and Social Atmosphere Building--A Case Study of Massive Multiplayer Online Games (MMOG)
Authors: Li Changcheng
Published: February 2025

Multiplayer Online Games (MMOGs) have taken off because this genre can influence players thinking and behavior, especially those who participate most. Nevertheless, current studies do not account for their double effect very well. This study investigates the mental and social impact of MMOGs on their capacity for strategic thinking, problem-solving, and sociality while also dealing with risks such as addiction and interpersonal conflicts. These conclusions suggest that the MMOGs develop cognitive ability through collaboration and flexibility and social bonds through cooperation and commonality of purpose. Thus, it could also be another way of socializing. Nevertheless, the addictive nature of such games has ill effects, such as overplaying, social marginalization, and behavior disputes. From these results, this paper recommends several suggestions for game design optimization: fair reward mechanisms, inclusive norms, and added aspects to reduce the chances of addiction. These proposals seek to maximize the positive side of MMOGs while considering their challenges.
A Study of the Impact of Idols and Celebrities on the Entertainment Industry
Authors: Liu Heran
Published: February 2025

Idols infiltrate into daily life, and bring positive effects in all aspects. However, it still has some negative effects on individuals, industries, and society. This research analyzes the positive impact of idols on the entertainment industry and analyzes some of its problems. This research analyzes the fan economy brought by idols has greatly increased the economic income of the entertainment industry, and has stabilized and promoted the long-term development of the entertainment industry. At the same time, idols have become a bridge for exchanging social and cultural and a condition for brand development. But at the same time, the improper behavior of idols has also hurt the development of the entertainment industry. Based on these, this research puts forward the following suggestions. First, the government and the market need to strengthen their supervision to avoid public opinion events. In addition, teachers need to do a good job of educating young fans. Finally, the entertainment industry should do a good job in self-management, improve its sense of responsibility and moral consciousness, and avoid negative events due to the pursuit of idols.
Study on the Development and Problems of Social Responsibility of Mass Media
Authors: Zhan Wenxuan
Published: February 2025

As one of the most used public communication platforms and the main source of information, mass media has always received widespread attention. However, there are still deficiencies in the research on social responsibility of the media. This paper argues that social media should provide objective and correct information for the masses, promote social diversity, promote critical thinking of the masses, and protect the rights and interests of vulnerable groups. existing defects mainly focus on the traditional media's excessive pursuit of balanced reporting, which leads to a certain degree of misleading of the audience, the proliferation of false information in various new media, and the information cocoon and other strategies adopted by media with the gradual commercialization trend of media, so that people can only receive information consistent with their original views most of the time. which make it impossible to present diversified information and to think critically. Based on this, this paper proposes the following suggestions: all aspects of society should jointly strengthen the control of false information and the media should give up making profits by constantly pushing the same views to a specific audience, and instead look for other growth points to seek revenue.
Research on the Relationship Between Design and Technology in the Design-driven Innovation Model Based on the Case Analysis of Apple
Authors: Yao Jiatong
Published: February 2025

In the research of cutting-edge design, it has been increasingly recognized that the relationship between design and technology is no longer limited to mutual reinforcement and promotion. In the current era of development, the boundaries of the design industry are constantly expanding, shifting its focus from individuals to industries, and evolving into an interdisciplinary field that integrates systematic research from various sectors. Design is fundamentally driven by innovation, characterized by the trends of the times, and requires systemic innovation that merges various technological services. It necessitates resource integration, consideration of user needs, and a fusion of fields such as technology, culture, and business. Moreover, it must comprehensively assess economic, social, ecological, and cultural impacts, while exploring potential paths for future innovation and development. Therefore, this paper aims to explore the evolving relationship between design and technology from the perspective of current trends. By analyzing the driving forces behind innovation and the changes in the relationship between design and technology, using Apple Inc. as a case study of a frontier company, this paper focuses on the design-driven model, analyzing its successes and methodologies. The goal is to explore the prospects and development potential of innovative design in the new era and propose possible suggestions for driving industrial revolutions, economic transformations, and societal progress in the future.
The Impact of Innovation Strategy on Enterprise Competitive Advantage in the Digital Economy
Authors: Zhang Siqi
Published: February 2025

In the context of the rapid development of the global digital economy, most companies are reshaping their operations and competitive strategies. The rapid development of big data, artificial intelligence, blockchain and other technologies has pushed enterprises to adopt active innovation strategies, thereby enhancing competitiveness. This paper discusses the influence of innovation strategy on the competitive advantage of enterprises from three aspects: technology driving, market orientation and sustainable development. By analyzing the practices of companies such as Google, Amazon and Tesla, the study highlights the critical role of digital technology in innovation. This study finds that companies that integrate digital technologies into their operations and services, prioritize consumer needs and offer personalized solutions, and incorporate sustainability into their core strategies contribute to long-term growth and competitiveness. This paper recommends that businesses build adaptable innovation strategies that not only address challenges but also seize future opportunities through digital transformation integration, ecosystem collaboration and sustainable practices to drive continued progress in the global economy.
The Impact of Business Model Innovation on Corporate Performance: Taking BYD as an Example
Authors: Liu Wenxi
Published: February 2025

In the context of intensified global market competition and rapid technological development, business model innovation has become a core issue in corporate strategic management. Therefore, it is of great significance to explore the impact of business model innovation on corporate performance. Taking BYD as an example, this article first summarizes BYD's business model innovation measures from the three dimensions of value discovery, value creation, and value realization. Secondly, this article analyzes the impact of its business model innovation on financial and non-financial performance. The results show that at the financial level, profitability, operating capacity, and growth capacity have been positively promoted by business model innovation. However, the accompanying debt pressure also poses a certain challenge to its debt repayment ability and increases financial risks. At the non-financial performance level, BYD's brand awareness and market share have both achieved significant improvements, reflecting the fact that its competitive position in the market has been strengthened. Based on the above analysis, this article believes that business model innovation is an important driving force for enhancing the core competitiveness of enterprises, and scientific and reasonable business model innovation has a positive impact on the performance of enterprises in all aspects.
Marketing Strategy Evaluation and Recommendations for Casetify: Personalized Phone Cases in the Chinese Market
Authors: Wu Kaiqi
Published: February 2025

Casetify specializes in personalized, fashionable, and highly protective mobile phone accessories, with markets spanning across the United States, China, South Korea, and Australia. This article analyzes Casetify's marketing strategy and proposes improvement suggestions. Market segmentation, target market, positioning, and the 4P marketing mix are based on the STP model for products, prices, channels, and promotions. By combining public data, theoretical definitions, and market reports for analysis, Casetify has been provided with a clear direction for development. Through product line expansion, market promotion, and product optimization, the brand's influence in the Chinese market has been enhanced. Casetify has successfully attracted young consumers through collaborations with celebrities and internet celebrities, collaborations, and strong social media marketing. However, there is still room for improvement in the market of Chinese Mainland. Its product line lacks coverage of brands such as Xiaomi and Huawei, which limits market expansion. To optimize the strategy, it is recommended to develop more products targeting the Chinese market, such as customized cases that support Xiaomi phones or brand collaborations to attract young users, as well as advertising on platforms such as WeChat to increase exposure.
Growth Experience Between the United States and Canada
Authors: Zhao Ziqi
Published: February 2025

In the era of globalization, the economy, employment, education, and environment are essential indicators for measuring a country's overall strength. The United States and Canada exhibit distinct characteristics in social governance and policy-making. Since its independence, the United States has gradually formed an individualistic economic model. Simultaneously, Canada, under its mixed colonial background of English and French, has placed greater emphasis on the development of collectivism and multiculturalism. These historical factors have further shaped the two countries' different policy orientations and practical achievements in the fields of economy, employment, education, and environmental protection. By analyzing the policies and practices of the two countries in these areas, this study will reveal their similarities and differences in addressing the challenges of globalization, promoting social equity and sustainable development, and providing useful historical and practical experience references for other countries.
Analyzing Diffusion Models: Transformer Integration and Prompt Optimization for Text-To-Image Generation
Authors: Tang Qiance
Published: February 2025

This paper delves into the analysis of various diffusion models, focusing on their utilization of text-conditional sampling and assessment using the contrastive language-image pre-training (CLIP) score as a metric. Leveraging Bidirectional Transformers (BERT) and Vision Transformers (ViT) within the CLIP model framework, it crucially compares models incorporating transformer blocks with those that do not. Specifically, it examines the structures of latent diffusion models and diffusion transformer models, emphasizing the use of Unet and Transformer block decoders, respectively. Additionally, the study explores different prompts to generate similar images, aiming to optimize conditioning training for text-to-image generation. Furthermore, the paper investigates the performance of the Latent Diffusion Model (LDM) and the DiT model in object generation, analyzing their interaction with text embeddings and prompt structures. The findings underscore the significance of prompt structures on model performance, with implications for future research into multimodal models and prompt optimization.
YOLOSCM: An Improved YOLO Algorithm for Cars Detection
Authors: Deng Changhui , Chen Lieyang , Liu Shinan
Published: February 2025

Detecting objects in urban traffic images presents considerable difficulties because of the following reasons: 1) These images are typically immense in size, encompassing millions or even hundreds of millions of pixels, yet computational resources are constrained. 2) The small size of vehicles in certain scenarios leads to insufficient information for accurate detection. 3) The uneven distribution of vehicles causes inefficient use of computational resources. To address these issues, we propose YOLOSCM (You Only Look Once with Segmentation Clustering Module), an efficient and effective framework. To address the challenges of large-scale images and the non-uniform distribution of vehicles, we propose a Segmentation Clustering Module (SCM). This module adaptively identifies clustered regions, enabling the model to focus on these areas for more precise detection. Additionally, we propose a new training strategy to optimize the detection of small vehicles and densely packed targets in complex urban traffic scenes. We perform extensive experiments on urban traffic datasets to demonstrate the effectiveness and superiority of our proposed approach.
Research on Stock Price Forecast of General Electric Based on Mixed CNN-LSTM Model
Authors: Hu Zixi , Shen Bao , Hu Yiwen , Zhao Chen
Published: February 2025

Accurate stock price prediction is crucial for investors and financial institutions, yet the complexity of the stock market makes it highly challenging. This study aims to construct an effective model to enhance the prediction ability of General Electric's stock price trend. The CNN - LSTM model is adopted, combining the feature extraction ability of CNN with the long - term dependency handling ability of LSTM, and the Adam optimizer is used to adjust the parameters. In the data preparation stage, historical trading data of General Electric's stock is collected. After cleaning, handling missing values, and feature engineering, features with strong correlations to the closing price are selected and dimensionality reduction is performed. During model training, the data is divided into training, validation, and testing sets in a ratio of 7:2:1. The Stochastic Gradient Descent algorithm is used with a dynamic learning rate adjustment and L2 regularization, and the Mean Squared Error is used as the loss function, evaluated by variance, R - squared score, and maximum error. Experimental results show that the model loss decreases steadily, and the predicted values align well with the actual values, providing a powerful tool for investment decisions. However, the model's performance in real - time and extreme market conditions remains to be tested, and future improvements could consider incorporating more data sources.
Research on Security Vulnerability Detection of Blockchain Smart Contracts Based on Machine Learning
Authors: Wu Yinuo
Published: February 2025

Blockchain technology, characterized by its immutability, decentralization, transparency, security, and traceability, has shown vast potential for applications in secure IoT communications and data protection through its deployed smart contracts. While machine learning-based code generation systems aim to automate high-quality programming solutions, they face significant challenges when addressing blockchain-related issues. This paper analyzes the limitations of machine learning in identifying vulnerabilities within blockchain smart contracts and proposes robust solutions. To achieve this, this paper suggests organizing multiple security experts for labeling, developing efficient labeling tools, employing semi-supervised learning to reduce dependency on labeled data, and establishing a continuous update mechanism for labeled datasets to adapt to evolving threat landscapes. To address the scarcity of training samples in the blockchain domain, this paper introduces a method for generating additional Solidity smart contract training samples using data augmentation techniques. Given that traditional data augmentation methods are not suitable for Solidity, the approach involves converting Solidity contracts into Python code for processing, then reverting them back to Solidity post-augmentation, with provided code examples. Furthermore, leveraging established non-blockchain code to train blockchain-related models enhances model performance and generalization capabilities. These strategies effectively tackle the issue of insufficient training samples in the blockchain field and offer new perspectives on the conversion between Solidity and Python.
A Review of Scheduling Deep Learning Workloads: JCT, Fairness
Authors: Wang Zhiheng
Published: February 2025

Traditional high-performance computing scheduling algorithms have been unable to satisfy the intricate demands of deep learning workloads. With advances in deep learning, tasks exhibit attributes including multi-tenancy, multi-resource consumption, and intense variability, introducing unprecedented difficulties for resource coordination. To address these challenges, scheduling approaches must be optimized regarding fairness, job completion timeframe (JCT), and hardware utilization. This review paper provides an analysis of primary deep learning scheduling algorithms, focusing on distinct techniques for improving fairness and JCT. Regarding fairness optimization, this review paper contrasts strategies dependent on runtime and non-runtime resource redistribution, including Dorm, Gandivafair, Themis, Astraea, Shockwave, Gavel and Sia, applicable in varying computing environments. For JCT optimization, the review paper examines scheduling algorithms based on heuristic functions and machine learning methods like Tiresias, E-LAS, Optimus, Sched2, Philly and Gandiva, emphasizing the impact of task priorities, resource allocation and job packing on completion time. By contrasting the strengths and limitations of these approaches, the review paper offers readers a comprehensive perspective and forecasts forthcoming directions for deep learning scheduling algorithm progress.
Applications of Multimodal Technology in Computer-Assisted Language Learning: Impacts on Cognitive Load and Attention Distribution
Authors: Chao Yang
Published: February 2025

Multimodal is disrupting CALL by blending audio, video and text to generate a more dynamic learning environment. We examine the effects of multimodal technology on cognitive load and attention at the second-language learning stage. This study involved 60 undergraduates, and the task used multimedia, virtual reality (VR) simulations and eye-tracking software to evaluate cognitive load and allocation of attention. Data demonstrated that multimodal learning spaces had lower cognitive load than unimodal settings audio, video and text pairs lowered the cognitive load most. Eye-tracking data showed that students who learned in multimodal environments allocated attention uniformly across the two modality, which enhanced comprehension and retention. The statistical results and qualitative comments supported multimodal design, allowing information to flow efficiently and without cognitive load. These results suggest that multimodal CALL systems have the ability to help language learning take place by facilitating cognitive and attentional mechanisms. This research advances the science of how multimodal technology can enhance learning and provides practical information for developing language learning systems of the future.
Artificial Intelligence in Intelligent Traffic Signal Control
Authors: Zhang Xuanning
Published: February 2025

With the rapid urbanization and the increasing traffic demand in cities, traffic congestion and accidents have become significant challenges for urban transportation systems. Traditional traffic signal control systems, which rely on fixed signal cycles, often fail to adapt to real-time traffic conditions, leading to inefficiencies and resource waste. This paper explores the application of Artificial Intelligence (AI) in intelligent traffic signal control systems. Specifically, it focuses on the use of Deep Reinforcement Learning (DRL), particularly the Deep Q-Network (DQN) model, for optimizing signal timing based on real-time traffic data. The system dynamically adjusts the signal cycles based on traffic flow, reducing congestion, improving traffic efficiency, and enhancing safety. The study also discusses the challenges AI-based systems face, such as algorithm complexity, data quality, and system integration, as well as the potential benefits of AI in managing traffic during peak hours and at complex intersections. Through simulation and real-world testing, the study demonstrates the advantages of AI-based signal control systems in improving urban traffic management. The findings suggest that AI can significantly enhance traffic flow, reduce waiting times, and optimize traffic resource allocation, offering a promising approach to solving urban traffic problems.
A Fast-Transient On-Chip LDO Based on Self-Biasing in 12-nm CMOS
Authors: Liu Weihan , Chen Xiaofei
Published: February 2025

This paper proposes a fast-transient on-chip low-dropout regulator (LDO) with high loop gain, utilizing adaptive dynamic biasing. A novel error amplifier circuit is designed, where the tail current transistor of a conventional five-transistor operational amplifier is used as the feedback amplifier transistor to participate in the amplification process, significantly improving the loop gain of the LDO and enhancing its accuracy. A current-sampling-based technique is applied to enhance the transient response at the output node, combined with adaptive dynamic biasing, to reduce output voltage undershoot and overshoot during load variations. The proposed LDO is implemented in a 12nm CMOS process. Test results show that for a 0.9V output voltage, a maximum load current of 30mA, and a loop gain of 114dB can be achieved with a 0.725V reference voltage. When the load current transitions from 100A to 30mA and back to 100A, the undershoot voltage is 5.8mV, and the overshoot voltage is 7.6mV.
A DBSCAN Anomaly Data Identification Method Driven by Data Distribution
Authors: Cui Haonan
Published: February 2025

This paper proposes a DBSCAN anomaly data identification method driven by data distribution to address the limitations of the traditional DBSCAN algorithm in parameter selection and anomaly detection. The conventional DBSCAN algorithm relies on manually set parameters, such as the neighborhood radius Eps and the minimum number of samples MinPts, which often result in inaccurate clustering outcomes. By incorporating the characteristics of data distribution, this study adopts the 3 rule to adaptively determine Eps and MinPts, thereby achieving a fully automated clustering process. Experimental results demonstrate that this method effectively identifies anomalies embedded within normal data in datasets with non-spherical clusters, achieving higher accuracy than the traditional DBSCAN algorithm.
Research on the Optimization of Quality Control Strategies for Industrial Products
Authors: Li Keliang
Published: February 2025

Quality control strategy plays an important role in the field of industrial manufacturing, which is directly related to the reliability of products and the level of operation efficiency. To address this core issue, this study groundbreaking a new framework that cleverly combines statistical process control (SPC) with Six Sigma methodology and incorporates cutting-edge technologies such as predictive analytics, real-time monitoring, and machine learning. This comprehensive strategy addresses many of the key challenges in manufacturing quality control and provides a systematic path to strengthening quality management practices through in-depth analysis of process variability, active promotion of defect rate reduction, and continuous optimization of operational efficiency. In particular, practical case studies from the automotive and electronics industries have shown that the application of the framework has brought significant results, not only significantly reducing defect rates, but also effectively improving the overall stability of the process. These valuable findings not only provide highly operational practical guidance for industry practitioners, but also greatly promote the further development of data-driven quality management methods in the academic field, and lay a solid foundation for building more robust and flexible manufacturing systems.
“常”与“变”：新中国成立以来党的政治建设的内在逻辑与现实指引
Authors: 白 雪
Published: February 2025

新时代党在政治建设上取得显著成效，为我们在深层次上认识政治建设的重要性提供了抓手。新中国成立七十多年来，中国共产党的政治建设有其自身的“常”与“变”内在逻辑。“常”主要表现在坚定政治信仰始终是我们党政治建设的灵魂、站稳人民立场始终是我们党政治建设的核心要义、坚持和维护党中央权威和集中统一领导始终是我们党政治建设的首要任务，“变”主要表现在我们党政治建设的主体、客体和环境三方面。科学把握新中国成立以来中国共产党政治建设“常”与“变”的内在逻辑，坚定政治信仰、把准政治方向，站稳人民立场、贯彻群众路线，增强“四个意识”、维护党中央权威和集中统一领导，以期在前进道路上不断指引我党政治建设向纵深方向发展。
Virtual triage reporting of mental health symptoms in Europe prior to and following the 2022 Russian invasion of Ukraine
Authors: Gellert George A. , Kabat-Karabon Aleksandra , Nowicka Anna , Price Tim , Gabrych Martyna M , Gellert Gabriel L.
Published: February 2025

Objective: Compare the reporting of 16 mental health symptoms (MHS) through AI-based virtual triage (VT) in three European countries/language user groups, including Ukrainians, Poles, and Italians, before and following the onset of the Russian invasion of Ukraine in February 2022.Methods: Frequencies of 16 MHS reported through VT were compared for 12 months prior to and after the onset of the 2022 Russia-Ukraine conflict (i.e., February 24, 2021 to February 23, 2022 pre-war and from February 24, 2022 through February 23, 2023 post-war, respectively). Italian patient-users served as a quasi-control group relative to Ukrainian and Polish language users, given the lower perception of national risk from Russian military aggression.Results: In 93,877 VT encounters, at least one MHS was reported. MHS reporting among Ukrainians and Poles increased 11.6% and 3.7%, respectively, after the first onset of the conflict (p<.05). Italian MHS reporting decreased 1.6%. Among Ukrainians, MHS reporting increased for 10 of 16 symptoms, the largest being suicidal thoughts/intent (158.7%), sleep disorder (45.7%), insomnia (32.9%), and irritability (20.7%) (all p<.05). Among Poles, reporting increased for 10 symptoms, including sleep disorder (52.2%), fear of dying (27.9%), insomnia (25.3%), and suicidal thoughts/intent (13.6%) (all p<.05).Conclusions: Individuals in nations more directly exposed to and potentially impacted by the war reported higher levels of MHS to AI-based automated VT. Virtual triage offers a new vehicle for enhancing detection of MHS, and for potentially accelerating referral to in-person or virtual/telemedical mental healthcare services among displaced populations needing care in conflict areas.
Os PPP’s de licenciatura em história como dispositivo:
Authors: Cavalcanti Erinaldo Vicente
Published: February 2025

O presente artigo é resultado das pesquisas desenvolvidas no projeto A história ensinada: saberes docentes, livro didático e narrativas e se propõe a analisar os Projetos Políticos Pedagógicos (PPPs) como um dispositivo. Para tanto, mobilizo os estudos já realizados no projeto sobre os PPPs e os diálogo com a literatura realizada. Inspirado nas análises promovidas por Michel Foucault (2004) e Giorgio Agamben (2009) acerca do que é um dispositivo, o presente texto se propõe a contribuir com o debate que tematiza a História como área de conhecimento que forma os professores para a atuação na Educação Básica. As análises sinalizam a complexidade dos PPPs, apontam para o potencial operatório do conceito dispositivo como uma chave de leitura para problematizá-los e demonstram a potencialidade desses documentos para as pesquisas no campo do Ensino de História.
Client-server architecture in smart manufacturing: A key enabler for industry 4.0
Authors: Koppichetti Ravi Kiran
Published: February 2025

The rapid evolution of manufacturing technologies under the Industry 4.0 paradigm has driven the need for efficient data management and real-time decision-making. The client-server architecture is Central to this transformation, enabling seamless communication, data sharing, and process automation across smart manufacturing environments. This literature review explores the pivotal role of client-server architecture and key communication protocols in enabling Smart Manufacturing and Industry 4.0 initiatives. The study examines the fundamental components of client-server architecture, including clients, servers, and communication protocols, and their interactions in industrial settings. It focuses on three primary protocols, MQTT, HTTP, and OPC UA, analyzing their mechanisms, benefits, and applications in smart manufacturing environments.
The research highlights how MQTT’s lightweight, publish-subscribe model facilitates efficient real-time data exchange in IoT-heavy industrial networks. HTTP’s widespread adoption and versatility in handling diverse data types are discussed, emphasizing its role in web-based dashboards and cloud integration. The review also delves into OPC UA’s platform-independent nature and advanced features, which promote interoperability and future-proofing of manufacturing systems.
This review synthesizes current knowledge of these technologies and underscores their collective importance in addressing critical requirements of smart manufacturing, including scalability, security, real-time capabilities, and cross-system compatibility. The findings suggest that integrating these communication protocols and architectures is crucial for realizing the full potential of Industry 4.0, paving the way for more agile, efficient, and data-driven production ecosystems.