bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Smart Wearable Devices in Sports Performance Analysis and Enhancement
Authors: Du Linying
Published: May 2024

Sports characteristics and physiological signals serve as critical benchmarks for analyzing athletic performance and enhancing training methodologies. This study explores the design and development of an advanced smart wearable device system tailored for monitoring sports training. This system is engineered to track athletic performance in real-time by integrating embedded wearable devices with sophisticated software. It primarily encompasses the recognition of human movement states, detection of electrocardiogram (ECG) signals, and monitoring of respiratory signals, thereby facilitating comprehensive analysis of human physiological parameters and movement metrics. This, in turn, supports athletes in optimizing their training routines. Empirical results from the study indicate that the mean-square error for both ECG and respiratory signals recorded during testing approximated ±0.8Hz, falling within the predetermined error tolerance range. Additionally, analyses of joint angle variations during running activities confirmed the efficacy of the proposed smart wearable system in improving sports performance.
Application of Automatic Driving Task Sequentialisation Monitoring for Band Operator Robots
Authors: Bai Yiming , Ruan Zhijie
Published: May 2024

Robotics is increasingly advancing across diverse sectors of industry and daily life, with particularly promising applications in autonomous driving. This research develops a robotic autopilot task serialization management system and conducts an in-depth analysis of how robot path planning influences serialization monitoring. The path planning system (PPS) has been enhanced through the integration of a behavioral tree path planning model and hierarchical decision-making processes. The performance of the newly developed PPS algorithm is evaluated through comparative simulation experiments against established path planning algorithms, such as Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms. The findings reveal that the PPS algorithm consistently achieves superior outcomes, planning paths with the shortest average length (188.673) and the lowest standard deviation (1.1547). Furthermore, it demonstrates optimal path efficiency and minimum energy consumption compared to four other migration algorithms. Additionally, the study observes the migration rates for node radii of 60 and 120 mm, which are 26% and 70%, respectively. Notably, as the number of robots and nodes increases, the migration rate stabilizes, underscoring the scalability and effectiveness of the PPS algorithm in complex environments.
Research on the Innovation of University English Teaching Mode Assisted by Mobile Technology Combined with SAMR Model
Authors: Cao Hao
Published: May 2024

With the burgeoning advancements in mobile technology, mobile learning has garnered significant interest across various sectors, emphasizing its crucial role in enhancing educational frameworks and nurturing students’ core competencies. This study uses the UTAUT model to create a research framework for the factors that affect teaching college English using mobile technology. Taking first-year students to junior students of a university as an example, the study collects relevant data through questionnaire surveys. It carries out correlation analysis, difference test, and regression analysis to explore the factors influencing college students’ English mobile learning. Then, combined with the SAMR model, the English teaching model of online integration and teacher-student synergy is proposed. The design of teaching experiments is used to study the effect of this paper’s teaching model. The analysis shows that community influence, performance expectations, effort expectations, content and resources, and perceived self-efficacy all have a positive effect on mobile technology use in English teaching (p < 0.001), with the effects of perceived self-efficacy (0.363) and performance expectations (0.331) being particularly significant. The receptive vocabulary, output vocabulary, and comprehensive test of the students in the experimental class improved by 12.34%, 20.65%, and 15.84%, respectively, and the application of mobile technology under the SAMR model has a significant contribution to the improvement of college students’ English proficiency.
Construction of English Numerical Intelligence Text Translation Data Corpus in Colleges and Universities
Authors: Zhai Xiang
Published: May 2024

Given the specialized nature of English text translation in academic settings and the frequent absence of reliable reference materials, translation processes often lack verifiable evidence, impacting both efficiency and quality. This paper addresses these challenges by first developing a basic syntactic error correction model that leverages the structural features of recurrent neural networks (RNNs) and gated recurrent unit (GRU) networks to establish a Seq2Seq syntactic error correction framework. To enhance this model, we incorporate an Attention mechanism into the Seq2Seq-based English grammar error correction model. This innovation enables the model to swiftly focus on segments most pertinent to the current context, thereby boosting operational efficiency. Subsequently, we create a college English text translation data corpus using Numerical Intelligence techniques to maintain grammatical accuracy within the corpus. Comparative analysis of the model training reveals that the Seq2Seq model with the Attention mechanism achieves an accuracy rate of 41.7%, which represents a 9.19% improvement over the basic model, underscoring its significant advantage. Furthermore, the average accuracy rate for grammatical error correction stands at 72.87%. A practical application analysis shows a minimal difference of only 0.05 points between the model’s grammar correction scores and those of human teachers. The corpus developed using this enhanced grammar error correction model scored 86 overall, outperforming other corpora. Therefore, the augmented Seq2Seq model with the Attention mechanism proves highly effective for developing English text translation corpora in collegiate environments.
Evolutionary Model of Piano Performance Teaching in Higher Education - Based on Knowledge Graph Analysis
Authors: Fan Xiaohuan
Published: May 2024

The progressive reforms in music education present new prospects and challenges for piano performance teaching in higher education institutions, necessitating the exploration of teaching models that align with contemporary developments through knowledge mapping. This study develops an evolutionary model for college piano teaching that integrates knowledge mapping, graph representation learning, and link prediction techniques. College piano majors were selected for pedagogical experiments to evaluate this model. The efficacy of the proposed piano performance teaching model in colleges was assessed by comparing student satisfaction and piano performance scores before and after the implementation of the model. The findings indicate a significant increase in student satisfaction with the piano teaching approach, with most reporting satisfaction levels above 60%. Furthermore, there was a substantial improvement in piano performance scores, with an average increase of 25.2 points, while students who initially scored high demonstrated stable improvements. This college piano teaching model offers valuable insights and serves as a significant reference for enhancing piano education practices in academic settings.
Network Security Threat Intelligence Prediction in Network Traffic Analysis Based on Machine Learning
Authors: Guan Yankui
Published: May 2024

With the increasingly complex network architecture under the development of information technology, it is more and more difficult to recognize various network traffic. Based on the direction of machine learning for network traffic anomaly detection, this paper proposes a three-stage CNN-LSTM attention mechanism model for feature extraction of original traffic and a PCA-based improvement for spatial feature learning of CNN to construct its anomaly traffic detection model. Meanwhile, based on the abnormal traffic detection, with discriminative network and generative network as the main parts, we propose the cyber security threat intelligence prediction model based on the use of a domain adaptive model to realize the shared representation of source and target domains. In the experiment of the abnormal traffic detection model, the accuracy rate of this paper’s detection model is 93.56%, the check-all rate is 99.2%, the F1 value is 84.9%, and the Kappa value is 80.66%. The detection level in the face of DOS attacks is the highest, with 98.28% and 99.63% checking full rate and checking accuracy, respectively. In the experiments of the network security threat intelligence prediction model, the prediction model of this paper reduces the time consumed by about 72% on average compared to rule file matching in dealing with large-scale network traffic. In high-risk cybersecurity threat attack types, it has an average prediction accuracy of 88.83% and a recall rate of over 90%.
High-quality Construction and Development Path of College of Finance and Economics Industry in Higher Vocational Colleges under the Perspective of Industry-Teaching Integration
Authors: Han Meng
Published: May 2024

Under the wave of digital technology, the integration of industry and education is increasingly becoming the direction of teaching construction in higher vocational colleges and universities. As the foundation of cultivating skilled talents, the construction of a financial industry college in higher vocational colleges is particularly important. Under the perspective of industry-teaching integration, the study combines the triple helix theory to carry out the high-quality construction of finance and economics colleges in higher vocational colleges, analyzes the influencing factors of the high-quality construction of finance and economics colleges in higher vocational colleges by using the DEMATEL algorithm and ISM algorithm, and explores the high-quality construction and development paths of finance and economics colleges by using the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method. The results show that the top 6 influencing factors of high-quality construction of financial and industrial colleges in higher vocational institutions are infrastructure, public services, campus supervision, campus governance, safeguards, and teaching management, and their cause degrees are all greater than 0.5. The overall coverage of innovative development paths of financial and industrial colleges in higher vocational institutions is 0.692. The overall consistency is 0.925, and a total of 3 model paths have been explored, i.e., There are supply-based paths (H1, H3), environment-based paths (H2, H5), and supply-environment synergy paths (H4).
Agricultural Pest Detection Methods and Control Measures Combining Deep Learning Algorithms
Authors: Hu Pengyu , Fang Wei , Li Jiahui
Published: May 2024

Agricultural pests and diseases critically impact the quality and yield of crops, thereby underscoring the practical importance of their automatic monitoring, identification, and timely management in agricultural production. This study develops a targeted detection model using a deep learning approach, specifically by enhancing the Faster R-CNN algorithm. Modifications were implemented in three key areas of the basic Faster R-CNN: First, the DIOU-NMS technique was employed to optimize the ancillary network during the feature extraction phase. Secondly, an attention mechanism along with an SE module was integrated within the DIOU-NMS to augment the network’s capability. During the training phase, optimization was facilitated through stochastic gradient descent. The efficacy of the refined Faster RCNN model was established via ablation studies, and its performance was benchmarked against existing methodologies for small and general target detection. Results indicate that the enhanced Faster R-CNN framework surpasses conventional small target and generic detection models in accuracy, achieving a 6.4% higher detection rate for various pest categories compared to its predecessor. The findings affirm the potential of the advanced Faster R-CNN in effective agricultural pest detection. Furthermore, this paper advocates a tripartite strategy for pest management, encompassing phytosanitary measures, agricultural interventions, and chemical controls.
Application of Adaptive Algorithms in Smart Building Design Optimisation
Authors: Li Qiang , Zhu JingJing , Li Han
Published: May 2024

How to realize the unity of safety, comfort, and economy of building structures has been a hot spot of concern in the field of construction engineering. This paper searches for optimal particles using a hybrid optimization strategy and optimizes the weights of each index in the fitness function into the same interval. Then dynamic inertia weights are used to improve the performance of the algorithm, and an enhanced adaptive particle swarm algorithm is obtained. After selecting the optimization variables for the building design, the objective function and constraints are designed, and the improved particle swarm algorithm is used to solve the optimal design of the intelligent building. The total weight of the target building structure was reduced after optimization, and 47.04% of the building materials were saved. The outer diameter of the steel pipe concrete at the lowest level of the building increases from 1.73m to 2.06m after optimization, which fulfills the law of column change in building design. It has also been found that the wind resistance of the optimized building structure has improved. This paper provides a reliable basis for the application of adaptive algorithms in building design optimization, and the proposed method also provides an effective reference for the field of construction engineering.
Application and Challenges of Virtual Reality (VR) in Art Exhibition Planning
Authors: Chen Jiahui
Published: May 2024

The combination of VR technology and art exhibition promotes a new form of art exhibition and enriches the multi-sensory experience of visitors. After analyzing the development form of VR art exhibition and the design process of VR art exhibition, this paper puts forward the solution countermeasures of using the sparse 3D map to optimize the presentation of virtual reality visualization scene, refining the 3D scene model and improving the presentation of the surface scene based on the Possion reconstruction for the lack of development of interactive experience in VR art exhibition. As well as based on the dimensions of interactive experiences, Kinect somatosensory interaction technology is used to update the interactive experience design in VR art exhibition planning. Explore the optimization effect of VR art exhibition planning, analyze the visitors’ interactive experience task completion time, participation, and interactive experience degree, and put forward effective countermeasures for the future development of VR art exhibitions. The mean value of scores of VR exhibitions and offline exhibitions are 5.887 and 5.657, respectively, with a difference of 0.23 and a total score difference of 2.07, which indicates that the art exhibition constructed on the basis of VR has a better sense of experience.
Stylistic Conversion and Linguistic Beauty Reproduction in English Translation-Based on Neurosemantic Analysis
Authors: Gong Han
Published: May 2024

The core of translation is language conversion, but it should be more of an aesthetic experience, a transformation of different ways of thinking. This paper proposes a neural semantic analysis method for English translation based on text similarity calculation. The technique uses a large-scale corpus to train the vector space model of words, establishes a concept-context matrix through the term-document matrix, and determines each value of the concept vector with a weight according to the literary translation in the knowledge base. The information extraction and evaluation of the English-translated text through semantic similarity calculation provides a theoretical basis for the subsequent analysis of style conversion and linguistic, and aesthetic reproduction of the English-translated text. The study will take the Lin Yutang translation and the Ricardian translation of The Analects of Confucius as an example to develop the analysis of style transformation and reproduction of linguistic beauty of the English-translated text from both lexical and syntactic levels. The results show that the lexical density of Lin Yutang’s translation is 0.5866, while that of Rie Jacob’s translation is 0.5334, with the former significantly larger than the latter. It shows that Lin Yutang’s translation of The Analects of Confucius adopts a naturalization strategy, i.e., To disseminate Chinese culture in a way that is authentic, familiar to English readers, and easy to understand, so as to make his linguistic expression more emotional.
Practical Exploration of Smart Classroom in Piano Teaching
Authors: Huang Xiaodong
Published: May 2024

In this paper, texture mapping technology is utilized to enhance the virtual reality piano teaching situation, and the piano classroom teaching data is integrated through big data statistical analysis methods. A deep neural network based on BERT+BiLSTM+CRF is used to train a named entity recognition model and complete the construction of a knowledge graph for piano subject data. Then, deep learning methods are used to extract the piano subject data and construct a visualized knowledge graph for the piano subject. Analyze the use of the Piano Smart Classroom teaching platform and the development of a blended teaching mode. The design requirements of the piano intelligent teaching platform are planned from two aspects: platform user roles and platform use cases, and the overall design of the piano intelligent teaching platform is carried out. The use of piano teaching video samples is a tool for calculating the teaching language ratio, analyzing the teaching interactions between teachers and students, and comparing the number of interactions between traditional teaching and smart classroom teaching. Analyze the effectiveness of piano-smart classroom teaching in three dimensions: cognition, emotion, and skill. The mean value of the specific content score of piano intelligent classroom teaching is 3.82, which is the single item with the highest mean value, and the piano teaching classroom supported by smart technology can show the piano teaching content more comprehensively.
Identification and Correction of Improved GLR Algorithm in English Translation Teaching
Authors: Li Tao
Published: May 2024

In this paper, after clarifying the common types of errors in English translation teaching, in order to achieve the improvement of English translation teaching, combined with the GLR algorithm for English phrase recognition and analysis, PCFG English syntactic analysis model and HDSM lexicalization model are introduced for the optimization of GLR algorithm, which constitutes the PCFG-HDSM model. Analyze the process of English translation error recognition and correction with an improved GLR algorithm and realize the improvement of the GLR algorithm. Compare the performance of the English translation grammar analysis generator and determine the ratio of pure grammar analysis time to total analysis time. Examine the English translation accuracy of the improved GLR algorithm by combining the training corpus and evaluating it using LP and LR metrics. Analyze practical teaching applications by classifying the structure of English translation topics and using the improved GLR algorithm. The improved GLR algorithm is able to achieve more than 80% of English translation recognition and correction rates, which enhances students’ scores on English translation topics and promotes the development of English translation teaching.
Correlation Analysis of Higher Education Music Teaching Quality and Students’ Artistic Literacy - Based on Regression Analysis Model
Authors: Lin Yushi
Published: May 2024

Music core literacy encompasses the essential skills students must acquire to form accurate concepts through music course learning. The enhancement of students’ artistic literacy within music education has emerged as a focal area of research. This study targets music majors at colleges and universities in H city, employing a questionnaire designed from dual perspectives: the quality of music teaching and the level of students’ artistic literacy. We applied open coding to the collected data, grounded in rooting theory, to formulate relevant research hypotheses. Subsequently, we assessed the reliability and validity of the questionnaire through factor analysis and conducted a preliminary analysis of the correlations using the Pearson correlation method. Furthermore, we developed a multiple regression model, positioning students’ artistic literacy as the dependent variable and music teaching quality as the independent variable, to explore and verify the interrelationships and hypotheses. The findings indicate that the equation can predict students’ artistic literacy: 0.882 + 0.255 × teaching ideology + 0.112 × teaching process + 0.176 × teaching ability + 0.225 × teaching effect. The results confirm that the quality of music teaching in colleges and universities significantly influences students’ artistic literacy levels. This research provides valuable insights for higher education institutions aiming to innovate music teaching methodologies and enhance the holistic literacy of their students.
Research on Digital Media Content Production and Dissemination Mode Based on Artificial Intelligence
Authors: Ma Shiming
Published: May 2024

In order to study the effect of digital media content production and dissemination supported by artificial intelligence technology, we aim to improve the dissemination and influence of digital media in short video platforms. This paper takes digital media as the research object and launches research on digital media content production and dissemination mode. Based on the research method of inquiry description, the core process of digital media intelligent transformation was deeply analyzed, and the overall logical framework of digital media intelligent transformation was designed. The digital media content production flow model is built by combining data integration and aggregation mining from a digital media content perspective. A graph-convolution matrix decomposition recommendation model for digital media broadcasting was developed by analyzing the performance of algorithmic recommendation in digital media applications. The results are presented: in terms of the order of influence degree size, the degree of influence on the number of likes is greater for political news (Beta = 0.2026, p < 0.01) than for military science and technology (Beta = 0.1637, p < 0.01) than for social news (Beta = 0.1225, p < 0.05), i.e.It indicates that the content theme is shifting from traditional social news to political news, which makes it easier to increase the heat of content dissemination. This study helps us think about the impact of media content production and dissemination strategies in the age of mobile Internet and provides new inspiration for communication theory research.
Research on Intelligent Optimisation Strategies for Interior Space Layout Design with the Aid of 3DsMax+AI
Authors: Liu Songlin
Published: May 2024

Indoor intelligent assistive technology has been widely used in space layout design optimization. This paper proposes a heuristic scene space layout generation method based on the smart evolution of scene space AI with WFC and deep network, joint wave function collapse algorithm, as well as two deep neural networks to generate the layout wireframe diagram while strangling reasonable boundaries and predicting functional semantic labels for the layout subspace. Applying the method of this paper to the office space layout optimization design, the results show that 95.68% of the area of the office and conference room has a lighting coefficient greater than 2%, and 85.78% of the area of the design room has a lighting coefficient greater than 3%. Ordinary white glass can be utilized in the design room to enhance the lighting quality, with a lighting coefficient of 2.87 and a compliance rate of 100%. The inset atrium space has a greater percentage of indoor thermal comfort area and a faster air flow rate. In this paper, 3DsMax+AI intelligent assistance and other technologies are used to simulate the layout design of the office space and realize the optimization of its layout design.
Academic Mobility in the Conditions of Forced Migration in Wartime (experience of Ukraine)
Authors: Boichenko Mykhailo
Published: May 2024

Forced migration during the war led to significant changes in academic mobility in Ukraine. This challenge received a worthy response thanks to the support of Ukraine from the European Union, the USA and other countries of Western democracy: many Ukrainian students and professors received greater opportunities to study and work in European and Western universities in general. This article aims to identify the main threats to inclusivity and new opportunities to provide additional resources and educational space for the development of inclusivity, which is directly related to forced migration as one of the challenges to higher education in Ukraine during this war. The methodology of this article is a philosophical approach based on the use of interrelated concepts of challenge and response. The case study of challenges for academic mobility in Ukraine is used as well. Obstacles and limitations of academic mobility during the war appear to be partially overcome, thanks to distance education. The new opportunities that have opened up for the Ukrainian higher education system provide broad and strategic prospects for the deep integration of the Ukrainian higher education system into the European and world educational space.
Specifics and Perspectives of the Third Mission of the Medical University: a Survey
Authors: Rodinkova Victoria , Kharkovenko Ruslana , Drachuk Olga , Horbenko Nataliia
Published: May 2024

Abstract:

Universities are an integral part of the communities in which they are located and linked by the practices of implementing various activities. Medical universities, whose mission is to contribute to public health, have especially tight connections with society. This paper discusses the specifics and perspectives of the third mission of the medical university in peacetime and during war using a specially designed survey.

It was determined that the social image of the medical university is provided by various socially oriented policies, primarily by providing medical aid to the population and conducting educational activities. The medical university is also a place for the continuous professional development of doctors and provides expert evaluation at the request of local authorities. Such a system of interaction has been established for years, and the process of collecting actual requests from the community needs to be adjusted and improved. Prospects for cooperation between the medical university and the community include the need to provide aid to the population that suffered as a result of russia’s armed aggression. Therefore, medical educational institutions, providing their main activity, will most likely become important centers for the rehabilitation of the wounded and providing them with psychological help. Thus, although the medical university has a lot of experience in cooperation with the community, this process could be improved by establishing a more constructive cooperation with society through the use of mechanisms developed and based on the appropriate regulatory framework that should meet the challenges of the time.
Implementation of EU Practice on the University’s Third Mission a participate project: the case of University of Genoa and Dragomanov State University
Authors: Spulber Diana , Nesterova Marja , Markus Iryna , Afuzova Hanna
Published: May 2024

The University is a key player in regional development. The third mission of universities is defined as the activities of universities aimed at solving social and economic problems, including those related to realising sustainable development goals. The manuscript aim is to describe the impact of the Erasmus+ project activities on the University aims reset, especially in the crisis period The third mission of the Dragomanov Ukrainian State University could be considered as the Faculty of Special and Inclusive Education is gearing up to launch a social-oriented initiatives aimed at enlightening the general public about the intricacies of social interaction with individuals experiencing persistent or functional disorders of psychophysical development. These vulnerable groups include individuals with special educational needs, encompassing those with disabilities, internally displaced persons, participants in military operations, and their families, all of whom will benefit from comprehensive psychological assistance and ongoing support.
Analyzing recent trends in deep-learning approaches: a review on urban environmental hazards and disaster studies for monitoring, management, and mitigation toward sustainability
Authors: Kumar Deepak , Bassill Nick P. , Ghosh Sukanya
Published: May 2024

Deep learning has changed the approach of urban environmental risk assessment and management. These methods enable solid models for large data sets, enabling early identification, prediction, and description of environmental risks. The current work analyses the advances in deep learning for urban environmental hazard assessments and disaster studies to provide monitoring, management, and mitigation measures. It reports the improvement in self-supervised learning, transformer architectures, persistent learning, attention mechanisms, adversarial robustness, associated learning, meta-learning, and multimodal learning within the domain of urban environmental hazard analysis. These approaches allow the creation of robust models for handling vast data volumes, facilitating early detection, prediction, and characterisation of diverse environmental threats. This trends analysis for urban applications will bring insights for connecting deep-learning models for effective and proactive approaches to tackle urban environmental hazards and disasters.
Firm Size Moderating Effect on Financial Performance and Dividend Policy from Indonesia
Authors: Ontorael Rizal , Saifi Muhammad , Nuzula Nila Firdausi , Z.A Zahro
Published: May 2024

Introduction: The purpose of this study is to examine the effect of financial performance on dividend policy and investigate the moderating role of firm size on the relationship between financial performance and dividend policy.
 
Literature Review: The influence of financial performance on dividend policy signaling theory Bhattacharya (1979) is about how companies should signal to report users, in the form of information about what the manager has done in realizing the owner’s desires.
 
Methods: This study was an explanatory study. The unit of analysis was the company’s property and real estate listed in Indonesian Stock Exchange and the sources of data were, annual report and financial reports of the companies. Indonesian Stock Exchange was selected as the setting of the study since Indonesian Stock Exchange is one of trading places for various types of companies in Indonesia, and it provides complete information on company’s financial data and stock price. The population was 84 companies’ property and real estate listed in Indonesian Stock Exchange between 2017 to 2022.
 
Result and Discussion: First, Financial performance has a significant and positive relationship to dividend policy; second firm size has a moderating effect on the relationship between financial performance and dividend policy.
 
Conclusion: The novelty in this study is the moderation of firm size on the relationship between financial performance and dividend policy.
The Amplified Effects of Covid-19: Analysis of Health Risks and Global Socio-Economic Conditions
Authors: Silva Jose Vinicius Bulhões da , Nunes Emanuel Nascimento , Sales Weslley Barbosa , Carvalho Amanda Carolina Nunes , Oliveira Rodrigo Ferreira , Cardenas Marjorie Yadira Jaramillo , Foggia Vicente de Brito , Viana Júnior Josvaldo da Silva , Dantas Iago Atílio Ferreira , Matos Raquel Gaio de , França Eduardo Eriko Tenório de , Morais Pollyana Soares de Abreu , Lima Jose Heriston de Morais
Published: May 2024

Introduction: The COVID-19 pandemic has emerged as an unprecedented global challenge, exposing and exacerbating existing health inequalities. The historical analysis of past pandemics and the understanding of social determinants of health during COVID-19 underscore the need for a holistic and equitable approach in responding to the pandemic, recognizing and addressing the social disparities that shape health outcomes.
 
Objective: This study aims to analyze the social health disparities exacerbated by the COVID-19 pandemic, focusing on vulnerable populations, identifying social determinants and assessing the impact of public health measures.
 
Methodology: We carried out an integrative review in the PubMed and BVS (Lilacs & Medline) databases. Systematic review studies, epidemiological studies, observational studies and original articles were selected, excluding duplicates, small samples, dissertations and theses. Studies published in the last 5 years 2018 to 2023 made available completely and free of charge. At the end of the 6 parts of the analysis, 10 articles were selected to take into account the current revision.
 
Results and Discussions: The analysis of the reviewed studies revealed substantial disparities in risk factors and health outcomes during the pandemic, highlighting the crucial influence of socioeconomic determinants. Socio-economic inequalities have been identified as playing a crucial role in the incidence and severity of the disease, with disproportionately disadvantaged and economically disadvantaged minority groups. Factors such as race, ethnicity and limited access to health care contribute to these disparities, highlighting the intersection between social determinants and health. The lack of fairness in the distribution of health resources and in the implementation of public policies may exacerbate existing disparities, making a more equitable approach to responding to the pandemic essential.
 
Conclusion: The COVID-19 pandemic has highlighted the complexity of health gaps, highlighting the need for integrated and holistic approaches to address these challenges and promote health equity.
Intaka Workshop: Innovation, Research, Interdisciplinarity, And Interculturality With The Taptana Cañari - A Novel Approach to Education
Authors: Troya-Vásquez Rosa Ildaura , Martínez-Serra José Enrique , Jaramillo-Ortiz Freddy Neptalí
Published: May 2024

Objective: This article To analyze the relevance of the INTAKA Workshop in strengthening cultural identity and preparing students for the challenges of the 21st century.   Theoretical Framework: The Ecuadorian Curriculum of 2016 seeks to integrate interculturality, innovation, and ancestral knowledge into education. However, traditional approaches still predominate.   Method: An instrumental case study was applied to the 44 participants of the workshop. A qualitative questionnaire with open-ended questions was applied, and a content analysis was carried out.   Results and Discussion: The results showed that the INTAKA Workshop promotes interdisciplinary and intercultural learning through practical activities with the Taptana Cañari, an ancestral mathematical tool. It fosters critical thinking and social responsibility. Participants positively evaluated the experience and highlighted its impact on learning and cultural identity. In the discussion, the results supported the relevance of the INTAKA Workshop as an innovative alternative to overcome the challenges of current education.   Implications of the Research: It’s interdisciplinary, intercultural, and value-oriented approach has the potential to strengthen cultural identity, promote meaningful learning, and prepare students for the 21st century.   Originality/Value: This study contributes to the educational literature by presenting the INTAKA Workshop as an unprecedented pedagogical initiative that integrates Cañari cultural richness with interdisciplinary learning. This study presents an innovative proposal to strengthen cultural identity and prepare 21st-century students, using the Taptana Cañari as a teaching tool and promoting vlues such as solidarity.
Emergency Department Recognition of Delirium: Quality Improvement Towards a Geriatric-Friendly ED
Authors: AlGharibi Mona , Rehman Mohammad , Curran David , Madott Elsa , Islam Asim , Prasad Rishi
Published: May 2024

Introduction: Delirium is a common yet often undetected condition in the elderly, particularly in the Emergency Department (ED). Its subtle presentation makes timely recognition challenging. Literature shows up to 10% of older patients presenting to the Emergency Department will have Delirium, but typically only 30% of these cases are identified in the Emergency Department.
Aims/Objectives: To implement quality improvement measures for early recognition of delirium in geriatric patients aged 65+ in a single center ED. Specific objectives include staff training on delirium identification, enhancing screening protocols, and implementing interventions to address delirium promptly.
Materials/Methods: ED staff providers underwent systematic training to optimize integration of Delirium Triage Screening (DTS) and Confusion Assessment Method (CAM), customized to the UAE patient population, into the geriatric ED workflow. A multidisciplinary team consisting of Geriatrics, Internal Medicine, ED Staff Physicians & Nurses established Quality Improvement Projects as part of a transition to a geriatric-friendly ED. Patients diagnosed with Delirium were retrospectively studied across 3 months to assess for use of DTS and CAM in ED evaluation.
Results: The collected data demonstrates a small percentage of patients with a diagnosis of Delirium. Given that the average frequency of Delirium tends to be around 10% in geriatric patients presenting to the ED, the presence of Delirium at our ED at 0.97% may represent a possible under-diagnosis of the condition. Documentation for both DTS and CAM was suboptimal, well below the target of at least 90%. While the policy prepared was comprehensive, communication of the recognition and assessment pathways could be improved.
Discussion: Following suboptimal initial results, dedicated internal departmental learning lectures were organized that focused specifically on the DTS and CAM assessments, with ample time for questions and answers with discussion to best understand and integrate these assessments into our ED workflow.
Conclusion: An improved understanding of Delirium, followed by an enhanced integration of validated screening tools will invariably improve ED recognition of Delirium, thereby improving patient-oriented outcomes for elderly individuals presenting to the ED.
dança na interdisciplinaridade com a literatura e as artes visuais
Authors: Steil Isleide
Published: May 2024

O objetivo, neste artigo, foi discutir possibilidades de relação entre dança, literatura e artes visuais, no intuito de apresentar outras viabilidades de práticas de dança na escola para além de repetições de técnicas corporais e coreografias. Foi um estudo de caráter qualitativo, cuja metodologia foi a Pesquisa Educacional Baseada em Artes (PEBA), com aporte teórico em Petit (2009, 2019), Marques (2012) e Vianna (2005). Como resultado, sinaliza-se que práticas interdisciplinares despertam outros olhares e entendimentos para as áreas envolvidas, e que a dança, sendo uma área de conhecimento, pode ser propulsora de experiências sensíveis na escola com mediações culturais adequadas.
Palavras-chave: Dança. Literatura. Artes Visuais. Grafia do movimento.
Pre- and postoperative levels of serum brain-derived neurotrophic factor in neonates with congenital heart defects
Authors: Fatalov Karim , Turan Özden , Özkan Murat , Erdoğan İlkay , Cankurtaran Tijen , Aldemir Metin , Anuk İnce Deniz , Aksu Meltem , Ecevit Ayşe Nur
Published: May 2024

Background. The objectives of this study were to assess the preoperative and postoperative serum brain- derived neurotrophic factor (BDNF) levels in neonates undergoing surgery for congenital heart defects (CHD). Also to explore the relationship between changes in BDNF levels and the impact of perioperative factors including intraoperative body temperature, aortic cross-clamp time, perfusion time, operation time, inotropic score, vasoactive inotropic score and lactate levels.
Methods. Forty-four patients with CHD and 36 healthy neonates were included in the study. Blood samples for serum BDNF levels were collected three times: preoperatively, and at 24 and 72 hours postoperatively from each patient in the operated group. Additionally, samples were collected once from each individual in the non-operated case group and the control group. Serum BDNF levels were analyzed using the Elabscience ELISA (Enzyme-Linked Immunosorbent Assay) commercial kit. Cranial ultrasonography (USG) was performed on all infants with CHD. Following cardiac surgery, patients underwent second and third cranial USG examinations at 24 and 72 hours postoperatively, respectively.
Results. Forty-four consecutive patients with CHD were divided into two groups as follows: the operated group (n=30) and the non-operated group (n=14). Although there were no differences in the baseline serum BDNF levels between the case and control groups, the preoperative serum BDNF levels were significantly lower in the patients operated compared to the non-operated patients. The serum BDNF levels at the 24th hour postoperatively were higher than the preoperative levels. However, no significant correlation was found between the serum BDNF levels at 24 and 72 hours postoperatively as well as the cranial USG findings at corresponding times.
Conclusions. Serum BDNF levels were initially lower in neonates with CHD who underwent surgery, but increased during the early postoperative period. These results suggest that serum BDNF levels are influenced by CHD and the postoperative period.
Pre-school teachers' digital concept maps and instructional design practices
Authors: Nipyrakis Argyris
Published: May 2024

Concept mapping has been a useful and effective technique for representing and assessing science content knowledge. Technological advances have also allowed the creation of user-friendly digital concept map applications. However, there appears a need to examine pre-service teachers' digital concept mapping practices in relation to their instructional design practices i.e. lesson planning. Hence, this study investigated the quality of pre-service pre-school teachers' (n = 26) digital concept maps in reference to the quality of their lesson plans. The quality of the digital concept maps was assessed based on an examination of the quality of a) structure, b) content, and c) their overall quality. Furthermore, it examined teachers' preferences and reflections on digital concept maps in relation to physical (i.e. paper-and-pencil) concept maps. Mixed methods were used including qualitative analysis and statistical correlations of the quality scores of the lesson plans and concept maps. Findings revealed no significant correlation between the quality of digital concept maps and the quality of lesson plans, while the consistency of the focus between the two correlated significantly with the quality of the digital concept maps. The number of concepts, propositions and cross-links as well as conceptual hierarchy were found as indicators of the overall quality of the digital concept maps. A comparison between digital and physical concept maps revealed that teachers' views and arguments varied between the two. The findings of the study speak to the relevance and applicability of digital concept maps for teacher training programmes.
Performance of fungus-tolerant grapevine cultivars in different production systems. Fungus-tolerant grapevine cultivars
Authors:   Department of Fruit growing, Viticulture, Horticulture and Landscape architecture, Faculty of Agriculture, Trg Dositeja Obradovi􀃼a 8, Novi Sad 21000, Serbia, IVANIŠEVIC DRAGOSLAV , KALAJDŽIC MLADEN I. ,   Department of Fruit growing, Viticulture, Horticulture and Landscape architecture, Faculty of Agriculture, Trg Dositeja Obradovi􀃼a 8, Novi Sad 21000, Serbia, BOŽOVIC PREDRAG ,   Department of Fruit growing, Viticulture, Horticulture and Landscape architecture, Faculty of Agriculture, Trg Dositeja Obradovi􀃼a 8, Novi Sad 21000, Serbia, BRZAKOVIC NEMANJA ,   Department of Fruit growing, Viticulture, Horticulture and Landscape architecture, Faculty of Agriculture, Trg Dositeja Obradovi􀃼a 8, Novi Sad 21000, Serbia
Published: May 2024

Several fungus-tolerant grapevine cultivars have been created and have already found their place in vineyards in Serbia and Hungary. The aim of this work was to investigate the differences in yield, grape quality and wine sensory properties obtained in two different production systems of pathogentolerant white grapevine cultivars Backa and Panonia over the 2015-2018 period. The paper showed differences in harvest parameters between the Conventional and NoPes&MinFert (without use of pesticides and mineral fertilizers) production systems. Fruitfulness and bud tolerance to low temperatures in these production systems were also examined. The results suggest that grape quality obtained by NoPes&MinFert was at the same level as that achieved by conventional methods, while the yield loss in NoPes&MinFert was on average <20% compared to the conventional system. Although the number of inflorescences per node and yield were higher in conventional production, NoPes&MinFert production showed satis􀂿 ed yield that exceeded 10 t/ha. Wine sensory analyses showed that production NoPes&MinFert achieved better wine score compared to the wines derived from the Conventional production.
Antitumor antibiotics: representatives, mechanisms of action and side effects
Authors:   Faculty of Biology, University of Bucharest, 030018 Bucharest, Romania, MIHAESCU GRIGORE , CONSTANTIN MARIAN ,   Institute of Biology Bucharest of Romanian Academy, 296 Splaiul Independentei, 060031 Bucharest, Romania,   Fellow of the Research Institute of the University of Bucharest, ICUB, Bucharest, Romania, ANDRONIC OCTAVIAN ,   General Surgery, University of Medicine and Pharmacy “Carol Davila”, 020021 Bucharest, Romania, BOLOCAN ALEXANDRA ,   General Surgery, University of Medicine and Pharmacy “Carol Davila”, 020021 Bucharest, Romania, VLAD ILINCA ,   Department of Pharmaceutical Chemistry, Faculty of Pharmacy, “Carol Davila” University of Medicine and Pharmacy, 6 Traian Vuia, 020956 Bucharest, Romania, FILIP ROXANA ,   Faculty of Medicine and Biological Sciences, Stefan cel Mare University of Suceava, 720229 Suceava, Romania,   Regional County Emergency Hospital, 720284 Suceava, Romania
Published: May 2024

Bacteria and fungi synthesize various compounds necessary for their own metabolism, as well as compounds that kill other microbial strains and species from the environment in which they grow, to ensure their access to sufficient supplies. Since the discovery of their antitumor effect, three main classes of antibiotics are used in cancer therapy: anthracyclines (secondary metabolites, mainly produced by members of Streptomyces group, or semisynthetic derivatives containing the 7,8,9,10-tetrahidrotetracen-5.12 quinone structure), peptide antibiotics and quinolones. In this minireview, we will present the mechanisms of action, main representatives and side effects of these anti-cancer agents.