bluuebunny/crossref_metadata_2025 huggingface dataset:
An Empirical Analysis of ESG Scores and Firm Performance Based on the CSI 300 Index
Authors: Zhang Jiahua
Published: July 2024

Environmental, Social, and Governance (ESG) criteria have emerged as pivotal factors in assessing a firm's sustainability and ethical impact. This paper investigates the relationship between ESG disclosure scores and firm performance among Chinese listed companies. Leveraging data from the CSMAR database, the study employs regression analysis to explore the impact of ESG pillars on operating performance (ROA), financial performance (ROCE), and market performance (Tobin’s Q). The findings reveal a significant positive correlation between the Social (S) pillar of ESG and firm performance, indicating that investments in social practices such as employee relations and community engagement contribute to stronger financial metrics. Conversely, the relationships with the Environmental (E) and Governance (G) pillars appear less clear, suggesting variability in ESG integration and industry-specific standards. These results underscore the evolving landscape of ESG practices in China and highlight the importance of enhancing ESG disclosures and adopting sustainable business practices in response to shifting market expectations and regulatory emphasis.
Analysis on Beijing Urban Underground Railway Operation
Authors: Yu Yi
Published: July 2024

With the acceleration of urbanization in China, large cities, especially mega cities like Beijing, are facing serious traffic congestion problems. As a key tool to alleviate urban traffic pressure and improve urban operational efficiency, the construction and operation of the Beijing subway have received widespread attention. This study adopts comparative analysis and case study methods to explore in-depth coverage and expansion of Beijing's subway network, passenger experience and service quality, safety management and emergency response, and compares with the operation of other international metropolises. Research has found that the Beijing subway has made significant achievements in improving transportation capacity, passenger experience, and safety, while also revealing issues such as congestion during peak hours, insufficient equipment updates, and the need for improved service qualities. In response to these issues, this study proposes corresponding countermeasures, such as improving transportation capacity during peak hours, accelerating equipment updates and maintenance, improving service levels to meet passenger needs, etc., aiming to provide reference for the optimization and sustainable development of Beijing Metro and even the national urban rail transit system.
Analysis of the Formulation Process of the Degree Law from the Perspective of Multi-source Flow Theory
Authors: Zhang Chunyan
Published: July 2024

This article adopts a policy perspective of multiple sources and analyzes the process of formulating the Degree Law from three aspects: problem source, policy source, and political source. The sharp increase in the number of degree awarding units and personnel, the revocation of degree points, and disputes over degree awarding standards have converged into a source of problems. The policy source is formed by the convergence of different efforts from experts, scholars, degree committees, and national legislative departments. The governance philosophy and public sentiment of the ruling party constitute the political source. The coupling of the three major sources and streams ultimately opened the "policy window" through the governance philosophy of the ruling party and the key to public sentiment in the political flow, making the Degree Law open to public and opening up a new process of Degree Law.
Etika Islami dalam Berkomentar di Instagram @Taubatters: Kajian Terhadap Fatwa Mui tentang Muamalah di Media Sosial
Authors: Ramadhani M. Kelfin Gilang
Published: July 2024

The widespread use of social media, particularly Instagram, poses new challenges in maintaining ethical communication and commenting practices, especially in the context of Islamic values. This research aims to analyze commenting practices on social media considering Islamic ethical values and the Indonesian Ulema Council (MUI) Fatwa on social interactions on the Instagram account @taubatters. The research methodology employed qualitative analysis through document analysis. Data collection techniques involved documentation, and data processing utilized reduction, data presentation, and conclusion drawing. The findings indicate that while most comments on the Instagram account @taubatters reflect Islamic muamalah principles according to the MUI Fatwa, emphasizing faith, piety, and moral values in social media interactions, the analysis also reveals comments that violate these principles, such as backbiting, slander, spreading discord, and bullying, contradicting Islamic teachings and potentially harming others. This underscores the complexity of social interactions in the digital world, where some adhere well to ethical practices while others have yet to fully embrace existing moral guidelines.
A Review of the Influence of Wu Dialect on English Pronunciation Acquisition
Authors: Zhou Yuxiang
Published: July 2024

The Wu dialect is widely spoken in Wu-speaking regions of China, which covers a considerable number of English learners. However, the phonetic system of the Wu dialect differs significantly from that of English, which greatly affects the English learning process of Wu-speaking learners, thus attracting numerous researchers to conduct related studies. This paper provides a comprehensive overview of research on the influence of Wu dialect on English phonological learning over the past two decades and presents a selection of twenty-seven papers to explore the theoretical framework, the research methodology, and the specific impacts encountered by English language learners who speak Wu dialect. Among them, the theoretical discussion centered on language transfer theory, Fleges Speech Learning Model and Bests Perceptual Assimilation Model; the research methodology consisted of qualitative analysis and empirical study; and the focus was placed on positive and negative transfer effects, i.e., the challenges posed by the absence or presence of phonological differences in the Wu dialect to the learners of English. The findings reveal significant segmental and suprasegmental influences in English pronunciation acquisition, with segmental challenges including differentiation of consonants and incomplete articulation of vowels, and suprasegmental challenges including stress placement, intonation patterns, and phonological rhythm. In addition, the discussion highlights the need for more empirical studies to supplement qualitative analyses, the consideration of regional variations within Wu dialect, and the exploration of teaching strategies informed by research findings. Therefore, the paper advocates for future research focusing on regional differences, deeper exploration of suprasegmental influences, integration of research into teaching practices, and diversified research methods.
Twitter Sentiment Analysis on Bitcoin Price
Authors: Li Mingyuan
Published: July 2024

The price of cryptocurrency can be affected by several factors these years, such as technology, social media, COVID-19, etc. One of the examples of these factors is Elon Masks tweets about cryptocurrency, which help to increase cryptocurrency prices. With the spread of the epidemic, people are restricted from meeting in person. Therefore, more and more people are active on online social media sites such as Twitter. This research wants to determine if tweets related to cryptocurrency (Bitcoin, one of the most popular cryptocurrencies nowadays) affect price. By taking 5 machine learning models and the Granger causality test, the correlation and causation relationship between sentiment analysis and bitcoin price can be determined.
Analysis of the Key Elements Contribute to the Financial Forecasting Models--Analysis of the Financial Control and the Bayesian Model in Systemic Risk Evaluation
Authors: Cai Huacheng , Ge Haoqi
Published: July 2024

Due to various factors, the performance of the financial market is always hard to predict. However, modelling, a technique based on mathematical theory and data science technology, has been an effective approach to forecast potential risks. In this article, the purpose of the research is to analyze how the Bayesian Model plays its unique role in forecasting the effect of systematic risk globally, and which is still also in use in most of financial forecasting. The essay doesnt involve solid equations and numerical relationships among different factors, but it does broadly offer the resolutions for the risks. The risk could be a detrimental factor that leads to a complete financial failure or even a crisis that influences normal peoples felicity. In this work, several ways to anticipate and decipher the risk are presented, all of which can reduce the risk effectively.
Analysis of the Digital Transformation Route and Impact on Avary Holding (Shenzhen) Co.
Authors: Liu Yixin
Published: July 2024

The digital transformation of the global economy is an inevitable trend, and Industry 4.0, based on digital transformation, has profound impacts on the global manufacturing sector. Although the manufacturing industry, as the mainstay of our country's real economy, boasts a vast scale, its infrastructure and transformation foundation are relatively weak. An effective data chain has not been fully established, facing numerous challenges in the digital transformation process. This paper selects Avary Holding (Shenzhen) Co., a leading company in the PCB manufacturing industry, as the research subject. We first outline the theoretical foundation of digital transformation, then provides a detailed introduction to the company, analyzing the motivations, pathways, and economic effects of its digital transformation. Based on this, several insights into the digital transformation of the manufacturing industry are proposed. The aim is to provide guidance for the digital transformation of manufacturing enterprises and supporting the enhancement of their competitiveness.
Analyzing the Influential Strategy on Getting out of Trouble after the COVID-19 Epidemic
Authors: Zhao Suoyi
Published: July 2024

Burberry encountered challenges within the COVID-19 pandemic, resulting in a substantial
decline in company revenue. Burberry launched a range of aggressive actions in response to the
outbreak, aiming to swiftly address the crisis. This essay examines the phenomenon of Burberry's
swift rebound during the COVID-19 pandemic and explores the factors contributing to its speedy
comeback. Burberry was able to swiftly overcome its difficulties by implementing a logo
transformation strategy. This article provides recommendations for luxury firms to modify their
logos in order to cater to the preferences of affluent consumers. An effective social media
strategy led to Burberry's swift recovery. Therefore, it is suggested that luxury firms should
offer customized online services. Burberry's effective digital strategy is a primary factor in
its successful resolution of difficulties. Given this rationale, the paper proposes that luxury
brands should create a digital platform. This article explores strategies for luxury brands to
overcome challenges and increase their commercial worth.
A Study on the Impact of Capital Structure on the Performance of Listed Companies
Authors: Tao Yiran
Published: July 2024

The paper investigates the influence of capital structure on listed companies' performance,
with a focus on the property sector, spanning 2010 to 2021. It delves into Modigliani-Miller
theorem, factors shaping capital structure decisions, and industry-specific characteristics
across various sectors like real estate, technology, and healthcare, and compares capital
structure trends in developed and developing countries. The findings reveal a nuanced
relationship between capital structure and performance, varying by industry and market maturity.
In capital-intensive sectors, like real estate, excessive leverage correlates with diminished
performance, while moderate debt levels in technology and healthcare can support innovation but
excess leverage may hinder it. Developed countries tend towards balanced capital structures,
whereas developing nations lean more towards debt financing. Notably, Chinese firms demonstrate
superior property investment efficiency and capital structure management compared to Vietnam.
Contributions include a comprehensive framework for capital structure determinants,
industry-specific insights aiding firms in optimizing capital structure, empirical evidence on
capital structure management in different developing nations, and highlighting capital
structure's multidimensional impact on firm performance, encompassing financial risk, R&D
investment, and market competitiveness. This study offers valuable guidance for firms,
particularly in emerging markets like China, in devising optimal capital structure strategies
tailored to industry dynamics and market conditions.
Navigating Modern Logistics: Innovations and Challenges in the Era of New Retail
Authors: Feng Sining
Published: July 2024

This study explores modern logistics innovations and challenges in the new retail era. With
the rapid development of science and technology, the traditional logistics model can no longer
meet the market demand. Consumers' demands for speed of product delivery, service quality and
personalization are constantly rising, and traditional logistics processes and management
methods can no longer adapt to this fast-changing market environment. As a result, companies
need to innovate and reform to improve logistics efficiency, reduce operating costs, and respond
more flexibly to the challenges of globalized competition. Through literature review and
empirical analysis, this paper provides an in-depth analysis of the problems faced by the modern
logistics industry, including the inefficiency of the traditional model, the promotion of
digital intelligence, and the need to improve the level of logistics in the new era. On this
basis, targeted recommendations include strengthening standardization, promoting digital
intelligence improvement and optimizing the supply network. This study is expected to provide
useful reference and guidance for developing the modern logistics industry.
Investigation into the Influence of Digital Financial Inclusion on Rural Renewal
Authors: Yu Yan
Published: July 2024

This research examines the pathways through which digital inclusive finance impacts rural
renewal, utilizing panel data collected from various Chinese provinces and cities between 2015
and 2020. The study utilizes panel individual fixed effects and mediation effect models for
analysis. Findings reveal that digital inclusive finance markedly advances rural revitalization
by mitigating the credit constraints faced by the "three rural" sectors (rural areas, farmers,
and agriculture), thereby creating a comprehensive framework for rural development. Furthermore,
digital inclusive finance fosters agricultural modernization, enhances the construction of
picturesque rural areas, and contributes to common prosperity. Although regional disparities
exist, with the western and eastern regions experiencing a more substantial impact compared to
the central region, no significant differences were observed between the northern and southern
regions.
Comparison of decision tree and ensemble algorithms
Authors: Chen Yihang , Chen Shuoyu , Yang Yicheng , Lu Siming
Published: July 2024

This paper presents an in-depth exploration of the Adaboost algorithm in the context of machine learning, focusing on its application in classification tasks. Adaboost, known for its adaptive boosting approach, is examined for its ability to enhance weak learners, particularly decision tree classifiers. The study delves into the theoretical underpinnings of Adaboost, emphasizing its iterative process for minimizing the exponential loss function. The role of decision trees, as integral components of this algorithm, is analyzed in detail. These trees, with their hierarchical query structure, are pivotal in categorizing items based on relevant features. The paper further compares Adaboost with random forests, another prominent machine learning algorithm, highlighting the nuances in their methodologies and applications. Significantly, the research introduces improved methods for selecting and fine-tuning these algorithms to optimize performance in various data classification scenarios. Practical applications of Adaboost and decision trees in real-world data classification tasks are demonstrated, providing insights into their operational effectiveness. This study not only elucidates the strengths of these machine learning techniques but also offers a comparative analysis, guiding practitioners in choosing the most suitable algorithm for specific classification challenges. The findings contribute to the broader understanding of machine learning algorithms, particularly in the context of data classification, and propose innovative approaches for enhancing algorithmic efficiency and accuracy. This research serves as a valuable resource for both academic and practical applications in the field of machine learning.
Optimization and comparative analysis of maze generation algorithm hybrid
Authors: Yang Kaicheng , Lin Sutong , Dai Yu , Li Wentai
Published: July 2024

The complexity of generating intricate and random mazes is a captivating challenge that finds applications in various fields, including computer science, mathematics, gaming, and simulations. This study presents an innovative approach by integrating two prominent perfect maze generation algorithms, Aldous-border (AB) and Wilson. Both are celebrated for their strong randomness and efficiency, yet their combination offers a novel way to optimize maze generation. Our research commenced with a detailed analysis of the relationship between the coverage rate, uniquely characterized by the AB algorithm, and map size. We then formulated a mechanism that transitions seamlessly into the Wilson algorithm, aiming to minimize time consumption. Through a series of carefully designed experimental trials, we hope to use a model to find the most suitable algorithm for switching to minimize the time it takes to generate a maze. These were subsequently evaluated and compared to identify the most fitting solution. Under the framework of our synthesized algorithm, an average time saving of 34.124% was achieved, demonstrating a promising enhancement in efficiency. Although still in the exploratory phase, the outcomes of this research provide foundational insights into maze generation's underlying principles and techniques. The outcomes of this research offer insights into maze generation and its applications and may serve as a useful reference for future studies and potential technological advancements.
VGG and InceptionV3 model based on CIFAR data contrast analysis
Authors: Li Yilin , Tang Zijie , Qin Miao
Published: July 2024

This paper introduces in detail the performance comparative analysis of VGG and InceptionV3 based on CIFAR-100 data set in image classification tasks. The experimental results show that the InceptionV3 model performs best on the CIFAR-100 dataset, and its high accuracy and balanced classification effect are impressive. In contrast, the VGG model, while simple in structure, is slightly less accurate. Further analysis shows that InceptionV3 model has more advantages in feature extraction and fusion design, which makes it perform well in image classification tasks. Additionally, the paper explores the broader applications and future prospects of the studied models. By doing so, it provides valuable insights into potential research directions for model comparison. This comprehensive analysis serves as a benchmark, shedding light on the strengths and weaknesses of VGG and InceptionV3 models in image classification. It stands as a valuable reference for future developments in comparative model research.
The limits of excellence: Assessing fine-tuned ChatGPTs efficacy in stock price forecasting
Authors: Huang Yiyang , Liu Xiang , Zhang Naichuan , Zhao Tianshu
Published: July 2024

In this study, we explore the ability of ChatGPT to predict stock market trends based on stock news headlines and real stock market data. In order to evaluate the performance of the fine-tuned model, we first obtain the prediction results of GPT-3.5 Turbo on specific stocks future trends as a comparison. We fine-tuned GPT-3.5 Turbo and conducted related training, testing and result evaluation. The experiments implemented on the two datasets Bigdata2022 and Cikm illustrate that fine-tuning can help the model to produce expected structured output according to user requirements, based on its more sophisticated understanding of the text and data in this field. However, although the models performance is improved significantly, GPT-3.5 Turbo does not demonstrate better performance compared to other traditional large language models in terms of integrating time series data and news headline data for stock forecasting. The fine-tuned ChatGPT model is expected to achieve excellent results in the stock market forecasting tasks through more in-depth research and become one of the mainstream research models in this field.
Analysis of classification algorithms: Insights from MNIST and WDBC datasets
Authors: Zhao Jiyue , Pan Tony Yuxiang , Yao Weibo , Lu Hongwei , Liu Zihan
Published: July 2024

Various classification algorithms applied to sophisticated datasets have seen significant development over the years, which involves dealing with the growing complexities of real-world data and providing efficient solutions for numerous domains like healthcare and data analysis. There is a critical need to identify the most effective algorithms to deliver high precision and generalizability. This study intends to assess diverse models, including Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), DTs (DT), and Random Forests (RF), on Modified National Institute of Standards and Technology (MNIST) and Wisconsin Diagnostic Breast Cancer (WDBC) datasets, utilizing metrics like Overall Accuracy (OA), Average Accuracy (AA), and Cohens kappa. The study has shown that the performance of the algorithms is mainly determined by the dataset's features. Additionally, insights into the strengths and limitations of each model are provided.
Music genre classification: Machine Learning on GTZAN
Authors: Zhao Ziyan , Xie Zixiao , Fu Jiaze , Tian Xintao
Published: July 2024

This paper explores music genre classification, aiming to enhance existing methodologies. As a crucial aspect of music information retrieval, genre classification facilitates organization and recommendation in music databases and streaming services. Our research, inspired by a Kaggle project, examines the background of music genre classification and introduces improvements. The study focuses on data preparation techniques and a novel methodology using Support Vector Machines (SVM). Utilizing the GTZAN dataset, we applied data segmentation and feature extraction, employing machine learning algorithms like Logistic Regression, Random Forest, and SVM. A significant innovation is our segmentation technique based on music's beats per minute (BPM), designed to preserve rhythmic structure, believed to be essential for accurate classification. We explored various feature extraction methods to boost classifier performance. Experimental results showed the 3-second segmented dataset performed better with SVM's linear kernel. Additionally, a 4-beat segmentation experiment suggested that finer segmentation captures richer audio features, potentially improving classification accuracy. The paper concludes with findings and future research directions, including dataset expansion, advanced segmentation based on musical theory, deep learning applications, and developing real-time classification systems.
Optimizing hospital outpatient services: A comparative study of backward induction and Q-learning techniques
Authors: Zhang Shilin
Published: July 2024

This study addresses the critical issue of optimizing outpatient services in high-capacity hospitals, focusing on developing cost-effective management strategies. Utilizing a simulated model of outpatient services, this research incorporates real data from the National Health Service (NHS) to tackle practical challenges in hospital management. The methodology encompasses the application of backward induction, Q-learning, and Deep Q-Network (DQN) algorithms to formulate solutions. The findings indicate that backward induction effectively resolves simpler scenarios within the assumed conditions. In contrast, Q-learning offers a viable approach, with DQN demonstrating superior performance in addressing more complex, realistic problems. The conclusion drawn from this study is that each algorithm exhibits unique strengths in its respective operational environment. While direct comparison between the models based on output analysis is not feasible due to the variation in environmental settings, it is evident that all three algorithms significantly contribute to resolving the targeted issues in outpatient service management. This research not only provides valuable insights into hospital outpatient service optimization but also opens avenues for further exploration in the application of advanced computational techniques in healthcare management.
Analysis of Functional Feeding Groups and Community Stability of Benthic Macroinvertebrates in Water System of Muduengsan National Park
Authors: Kim Su-Jin , Lee Jong-Eun ,   Korea National Park Service National Park Research Institute
Published: July 2024

Two surveys were conducted from May to September 2022 to analyze the functional feeding groups and community stability of benthic macroinvertebrates at 17 sites in the water system of Muduengsan National Park. Benthic macroinvertebrates belonging to 154 taxa, 71 families, 18 orders, seven classes, and five phyla were found. Community analysis showed an average dominance index of 0.56, a diversity index of 2.97, a richness index of 3.00, and an evenness index of 0.68. In the analysis of functional feeding groups, predators (P) had the highest abundance with 47 species (31.13%) owing to the appearance of Plecoptera and Odonata. In the analysis of functional habitat groups, clinger (CL) had the highest abundance at all survey sites with 66 species (43.42%). Community stability analysis showed that Group I, which included species with high relative resistance and resilience, comprised a high proportion (average of 53.7%). The BMI analysis showed “very good” (Class A) stream status at all survey sites.
Spatial Distribution of Benthic Macroinvertebrate Assemblages in Odaesan National Park, South Korea
Authors: Jun Yung Chul , Kwon Soon Jik ,   Korea National Park Service National Park Research Institute
Published: July 2024

Freshwater ecosystems are among the most threatened ecosystems on Earth and suffer from extensive human exploitation and climate change. Conservation and enhancement of freshwater biodiversity have recently become indispensable for securing ecosystem integrity and sustainability. This study aimed to confirm the biological diversity and distribution characteristics of benthic macroinvertebrates in Odaesan National Park. A total of 133 taxa belonging to 66 families, 18 orders, seven classes, and five phyla were identified during the survey period. Taxa richness ranged from 28 to 63 years with an average of 39.7 taxa. The taxa richness and abundance of Ephemeroptera, Plecoptera, and Trichoptera accounted for 60.3% and 86.0% of the total taxa, respectively. Seven endemic species had restricted spatial distributions and high conservation values. Cluster analysis classified 18 study sites into three major clusters: streams with high heterogeneity in streambeds and high taxa richness, streams located in Gaejanigol (a tributary of the Odae Stream), and three Ramsar wetlands. Indicator species analysis selected 16 important indicators, with the highest indicator value of Pisidium coreanum at 100%. Our results provide useful information on the biodiversity and habitats of benthic macroinvertebrates in the Odaesan National Park, consequently helping to establish conservation and management plans for biological resources.
Analysis of Visit Characteristics of Site where the National Park Eco Culture-Education Platform will be Built using Correspondence Analysis
Authors: Park Heon-Choon , Sim Kyu-Won , Kim Byung-Gook , Kim Dong-Hoon ,   Korea National Park Service National Park Research Institute
Published: July 2024

The Korea National Park Service will create a national park ecoculture education platform to actively respond to travel trends and revitalize leisure culture, including marine leisure sports. This study analyzed the relationship between platforms and visit characteristics using cross-analysis and correspondence analysis to establish appropriate and differentiated operational plans for future platforms. Cross-analysis showed a significant relationship between the platforms and the path to information acquisition, preferred time, stay time, and purpose of visit. According to the correspondence analysis, the marine eco-education center and marine climate response safety center showed different visit characteristics from Asiatic black bear coexistence centers and Gapsa district healing centers in terms of information acquisition, stay time, and visit purpose. The preferred time to visit was associated with weekdays in the marine climate response safety center, unlike other platforms. The results of the analysis were synthesized, and suggestions are made on how to operate each eco-culture education platform.
THE TRANSFORMATIVE ROLE OF AI IN CRITICAL DECISION-MAKING: A CORPORATE PERSPECTIVE
Authors: Turan Ondes Aybuke
Published: July 2024

In order to understand the historical development of artificial intelligence and its impact on the decision-making process in business management and to shed light on the developments in the field, the study was carried out using the literature review method.
In this context, the findings obtained in the literature review were examined in periods of 5 to 10 years from past to present and explained with historical and organizational examples (Huges,2021). AI has become an integral part of organizations structure in different ways. AI designed concepts in such as human resources, marketing, management, production and logistics is a need in today’s business life (World,2022).
'AI' applications, through coding and algorithms that can operate in integration with all areas of the industry, help create a more efficient working environment in terms of lower costs and sustainability. Innovative organizational changes also reshape the working principles of human beings and affect the critical decision-making process of managers (Van de Wetering, Mikalef, Dennehy, 2022).
In conclusion the research, aims to reveal the effect of artificial intelligence applications, which can analyze the situation by eliminating factors such as human emotions, ethics, morality or conscience, and calculate the probabilities and report the results, on decision-making in business life with exemplary applications of leading companies in their sector (Persson, 1964).
Շպիցոիդ մելանոցիտային պրոլիֆերացիաներ
Authors: Խաչիկյան Խ. Մ. , Հովհաննիսյան Հ. Ա. , Քեշիշյան Ա. Ա. , ՀակոբյաՆ Ա. Հ. , Թոփչյան Ա. Պ.
Published: July 2024

Шпицоидные меланоцитарные пролиферации – это обширная совокупность нозологических форм опухолевой патологии кожи, в числе которых – классический невус Шпица, диспластический невус Шпица, ангиоматозный невус Шпица, невус Шпица с атипией, шпицоидная меланома, меланоцитарная опухоль с неизвестным злокачественным потенциалом и другие. Наиболее распространенным и проблемным из них является классический приобретенный доброкачественный невус Шпица, морфологические и биологические особенности которого широко изучались на протяжении десятилетий. Но по сей день он продолжает оставаться одной из сложнейших проблем в дерматопатологии. Дело в том, что клинические, дерматоскопические и гистопатологические симптомы невуса Шпица и шпицоидной меланомы часто перекрываются, и обязательно возникает необходимость четкого их разграничения. Представлены клинические, гистопатологические и дерматоскопические особенности классического невуса Шпица и шпицоидной меланомы кожи, эволюция и инволюция доброкачественных и злокачественных дерматоскопических признаков невуса Шпица, дифференциальная диагностика, а также современные терапевтические подходы.
Spitzoid melanocytic proliferations are an extensive set of nosological forms of skin tumor pathology, including classic nevus Spitz, dysplastic nevus Spitz, angiomatous nevus Spitz, nevus Spitz with atypia, Spitzoid melanoma, melanocytic tumor with unknown malignant potential and others. The most common and problematic of them is the classic acquired benign nevus Spitz, the morphological and biological features of which have been widely studied for decades. But today it continues to be one of the most difficult problems in dermatopathology. The point is that the clinical, dermatoscopic and histopathological symptoms of Spitz nevus and Spitzoid melanoma often overlap, and there is a need for their clear distinction. In this article clinical, histopathological, and dermatoscopic features of the classic Spitz nevus and Spitzoid melanoma of the skin, evolution and involution of benign and malignant dermatoscopic signs of the Spitz nevus, differential diagnosis, and modern therapeutic approaches are presented.
Влияние комплексов меди Сu(LCH3)2 и Сu(LCF3)2 на организм крыс, облученных радиоизотопным технецием
Authors: Карапетян А. Г. , Григорян В. С. , Даллакян А. М. , Хачатрян Г. Г.
Published: July 2024

Բջջի վրա իոնացնող ճառագայթման (ԻՃ) ազդեցության առաջին և անմիջական նշաններից մեկը քրոմոսոմների ապակայունացումն է։ Կարիոտիպի ճառագայթահարման հետևանքով առաջացած վնասը կարևոր ցուցանիշ է ինչպես ճառագայթային վնասվածքների ծանրության կենսաբանական ցուցման, այնպես էլ ԻՃ երկարաժամկետ անբարենպաստ հետևանք-ների զարգացումը կանխատեսելու համար: Նոր, արդյունավետ ռադիոպաշտպանիչ միացությունների որոնումը ժամանակակից ռադիոկենսաբանության առաջնահերթ խնդիրն է: Այս ոլորտում առանձնահատուկ հետաքրքրություն են ներկայացնում բարձր հակաօքսիդանտ ակտիվությամբ օրգանամետաղական համալիրները։ Այս աշխատանքի նպատակն է որոշել Сu(LCH3)2 և Сu(LCF3)2 համալիրների հնարավոր ռադիոպաշտպանիչ հատկությունները:
One of the first and direct signs of the impact of ionizing radiation (IR) on a cell is the destabilization of chromosomes. Radiation-induced damage to the karyotype is an important indicator both for biological indication of the severity of radiation injuries and for predicting the development of long-term adverse effects of IR. The search for new, effective radioprotective compounds is a priority task of modern radiobiology. In this area, organometallic complexes with high antioxidant activity are of particular interest. The purpose of this work is to determine the possible radioprotective properties of the Сu(LCH3)2 and Сu(LCF3)2complexes. Determined survival, life expectancy and cytogenetic parameters: mitotic index, chromosome aberrations and % of polyploid cells in the bone marrow cells of the femur (count in 1000 cells in each preparation).
The Mediating Role of Transactional Distance on the Relationship between Course Satisfaction and Student Persistence
Authors: Ares Earl John D , Cavales Angel Hane A , Hasan Narwesa I , Doren Mylyn L
Published: July 2024

In the context of education, which is asynchronous and synchronous online learning, students’ persistence is of concern in most educational institutions. Several studies reveal many factors that influence students’ persistence. One of them is course satisfaction but hardly any research about the effect of psychological space of learners on students’ persistence. Thus, this study aimed to determine the mediating effect of transactional distance on the relationship between course satisfaction and student persistence. The study employed a descriptive-causal method of research and used an adaptive questionnaire that was contextualized by the researchers, and was participated by 239 senior high school students (grade 11 and grade 12) at the University of Mindanao Digos College; utilized stratified random sampling. The results of the study showed that the students are satisfied with their online course experience and thus students are highly likely to persist. Results also reveal that the transactional distance is low. Moreover, it also showed course satisfaction and student persistence are significantly related. However, after the insertion of transactional distance, the direct path unveiled insignificance while the indirect path revealed significant effect. Hence, the mediation analysis disclosed that transactional distance fully mediates the relationship between course satisfaction and student persistence. The paper provides evidence that in asynchronous and synchronous online learning, satisfaction should not solely be the focus in attaining students’ “intent-to-persist” but must also consider the perceived transactional distance of learners.
Outcome and Quality of Life in a Patient with Advanced Multiple Myeloma in Whom Blood Transfusion Is Not an Option: A Case Report
Authors: Asuquo Marcus , Inaku Kenneth , Usoro Nathaniel , Akaba Kingsley
Published: July 2024

Objective:
We present a case of a 58-year-old male patient with multiple myeloma who objected to blood transfusion being of the Jehovah’s Witness faith.
Methods:
The patient is from the Ejagham tribe of Cross River State, Nigeria. The presenting Hb was 2.5g/dl with signs and symptoms of heart failure and hyperviscosity syndrome. We resuscitated this patient and commenced Hb optimization using IV iron, IV vitamin C, IV Vitamin B complex, and subcutaneous human recombinant erythropoietin Beta.
Results:
The outcome was beneficial, and the quality of life significantly improved.
Conclusion:
More research is needed on managing anaemia without blood transfusion in patients with multiple myeloma.
A thyroidectomy revealing squamous metaplasia: a case report.
Authors: Eddebbarh Zineb , salhi khawla , Essafi Mohammed , Aynaou Hayat , Salhi Houda , Ouahabi Hanan
Published: July 2024

Squamous metaplasia is an exception in the normal thyroid gland and is usually caused by a tumor orinflammatory process.
To our knowledge, rare cases have been reported in the literature. Therefore, the lack of publisheddata compared to other cases in the literature was a major limitation.
We report the case of a 24-year-old patient who was admitted to the endocrinology department ofthe Hassan II University Hospital in Fez for cervical swelling, clinical examination found a WHO stageII goiter with a large nodule as confirmed by cervical ultrasound. The patient underwent totalthyroidectomy for cosmetic concerns. The histological study showed no squamous metaplasia. Thepatient was treated with replacement therapy and had a good outcome.
AI and Your Job What’s Changing and What’s Next
Authors: Du Jiaxing
Published: July 2024

Artificial Intelligence (AI) has emerged as a transformative force, significantly impacting job roles and skill requirements across various industries. This paper comprehensively analyses AI's influence on the workforce, exploring the current changes, evolving skill demands, future outlook, and practical case studies. The study highlights the automation of routine tasks, the creation of new job roles, and the redefinition of existing roles due to AI integration. It also delves into the changing skill requirements, emphasizing the growing importance of technical, soft, and hybrid skills. Additionally, the paper examines future predictions for job market evolution, educational and training implications, and policy and ethical considerations. The paper illustrates the practical implications of AI on job roles and skill requirements through industry-specific examples and success stories from leading companies. The findings underscore the need for proactive adaptation, continuous learning, and ethical practices to navigate the complexities of AI integration and create a future where humans and machines thrive.
Study on the Application of Annotation Type in Vocabulary Learning
Authors: Zhao Xin
Published: July 2024

Learning vocabulary with annotation is not a new topic in language learning research area ever since linguistics and language teachers wanted to solve the problem of low efficiency of vocabulary learning. However, controversy on whether single annotation like text annotation or multiple forms of annotation such as text plus picture annotation is more helpful still exists. This passage tries to figure out the reasons behind it, including learner differences, Vocabulary learning with different combinations of annotation type and task type and not separate vocabulary into receptive vocabulary and productive vocabulary. And we are eager to find out solutions to solve this problem.
Research on fitness training strategies of high level football players in different field positions
Authors: Peng Keshun , Li Guangye
Published: July 2024

Physical quality is one of the basic abilities necessary for each high-level athlete. Physical training is an essential and important link in the daily training activities of football teams. This paper probes into the training of physical quality of high level football players in different positions. On the football field, there are significant differences in the physical fitness requirements of players in different positions. Forward players need to have excellent speed, explosive power and agility in order to break through and shoot quickly in attack; Midfielders need excellent endurance, speed and passing ability to support full-court movement and tandem attack; Defenders need speed, stamina and physical ability to cope with defensive pressure. The goalkeeper needs quick reaction speed and excellent flexibility to ensure stability and accuracy when keeping the goal. These findings highlight the importance of developing individual fitness strategies for players in different positions. Through scientific and reasonable training, the physical quality of players can be significantly improved, and then the overall competitive level of the team can be improved. At the same time, it also provides a clear direction and reference for the physical training of college football teams. Puts forward the physical training strategies of football players in different positions on the field.
Study of Senior High School English Teaching Strategies based on the Value of Discipline Education
Authors: Zeng Tingting
Published: July 2024

This study aims to explore the senior high school English teaching strategies based on the educational value of the subject. With the deepening of educational reform, the educational value of subjects is receiving increasing attention. As an important subject, English not only teaches language knowledge in senior high school, but also carries multiple tasks of cultivating students' comprehensive quality and cross-cultural communication ability. This study uses methods such as literature review and case analysis to deeply explore the educational value of senior high school English teaching, and proposes targeted teaching strategies. The study found that reasonable teaching strategies can effectively enhance students' interest in learning, language application ability, and cross-cultural awareness, thus achieving the educational goals of the subject. This study has certain reference value for guiding senior high school English teachers in teaching practice and promoting teaching reform.
The Cultivation of Thinking Quality in English Reading Teaching in Senior High School
Authors: Zhang Ruowen
Published: July 2024

The English Curriculum Standards for Senior High School (2017 edition) put forward that the quality of thinking should be regarded as one of the core qualities of English subjects, and students should be cultivated in the aspects of logic, criticism and innovation. Therefore, the cultivation of students' thinking quality cannot be neglected in teaching. As one of the important parts of listening, speaking, reading, writing and reading, English reading plays an important role in high school English teaching, and reading is an important way to train students' thinking quality. It is suggested that teachers should integrate language learning, content learning and thinking quality development into the process of students actively exploring the meaning of the topic.
The Evolution of Western Oil Painting Styles from the Renaissance to Modern Art
Authors: Hui Wang
Published: July 2024

painting styles from the Renaissance through to modern art, exploring significant transformations in technique, thematic focus, and aesthetic values. Starting with the Renaissance, characterized by its emphasis on realism and humanistic themes, we examine the mastery of light and perspective that painters such as Leonardo da Vinci and Michelangelo brought to the canvas. As we move into the Baroque period, the focus shifts to emotional depth and dramatic intensity, exemplified by artists like Caravaggio and Rembrandt. The subsequent Neoclassical and Romantic movements reveal a divergence in styles—precision and restraint versus emotional exuberance and individualism. Transitioning into the 19th century, Impressionism marks a revolutionary departure from traditional forms, focusing instead on light and color to capture fleeting moments, leading to further explorations in Post-Impressionism, Cubism, and Surrealism. Each of these styles contributed to the pluralistic landscape of modern art, which breaks from conventional techniques and embraces abstraction. This paper provides a comprehensive analysis of these transitions, offering insights into the broader cultural and philosophical shifts that influenced these artistic developments. Through examining these historical contexts, the paper highlights how oil painting has continuously adapted to reflect changing ideas and sensibilities within Western society.
A Comprehensive Review of Total Physical Response
Authors: Yang Liming
Published: July 2024

Total Physical Response (TPR) is a teaching method proposed by American psychologist James Asher, which plays a significant role in foreign language teaching. This article mainly provides an overview of TPR. It then analyzes and summarizes its background, theoretical basis, implementation principles, and steps. It outlines the current research status of TPR and evaluates its advantages and disadvantages. Finally, the author discusses the challenges in implementing TPR in the future and provides an outlook on its future research directions in foreign language teaching.
The Legal Structure and Practical Dilemma of the Establishment of the "Review System"
Authors: Wang Zihan
Published: July 2024

In order to improve the judicial responsibility system, implement the supervision and management responsibility of the presiding judge, and improve the quality of court judgments, the Supreme People's Court has proposed the reform of the courtyard long review system for judgment documents. This proposal helps to improve the quality of case trials and alleviate the pressure on judges under the "lifelong responsibility system" in handling cases; However, if the implementation of the review system is not appropriate, it will inevitably lead to significant changes in the operation mechanism of the judicial power, and may even substantially affect the effectiveness of the reform of the judicial responsibility system. In this article, the author will explore the feasibility and implementation difficulties of the review system from two perspectives: the legal structure and practical difficulties of its establishment.