bluuebunny/crossref_metadata_2025 huggingface dataset:
Digital Innovation of Red Cultural Resource Management Mode in Shanxi
Authors: Sun Chang
Published: May 2024

In this paper, we explore the mechanism of managing red cultural resources enabled by digital technology. We developed a digital communication model for red culture and proposed an innovative pathway for the management of digitally-enabled red cultural resources. Then, a regression analysis model was established to assess the effects of digital management of cultural resources through model estimation and significance testing. Based on the one-way ANOVA model, we explored the differences in the evaluation of digital management of red culture in Shanxi by different students’ genders. We tested and regressed the correlation between digital red resource management and students’ sense of political efficacy and political emotion. The results show that the correlation coefficients between digital red education and intrinsic political efficacy and extrinsic political efficacy are between (0.5 and 0.6). The correlation coefficients of digitalized red resource management with students’ sense of intrinsic political efficacy and extrinsic political efficacy r are all greater than 0, p=0.000. They are significantly positively correlated under the condition of α=0.01. This study effectively promotes the high-quality development of digital transformation in red culture and builds a new pattern of digital inheritance and innovation in red culture.
E-commerce Live Streaming Interaction Quality, Immersion Experience and Consumer Purchase Intention
Authors: Wang Dongfeng
Published: May 2024

With the rapid development of the digital economy, the wave of e-commerce live broadcasting has swept all walks of life and become the new force of online shopping. Based on the S-O-R model, this paper establishes a theoretical model affecting consumers’ purchase intention. It puts forward relevant research hypotheses from the dimensions of seller-consumer interaction, anchor-consumer interaction, and consumer-to-consumer interaction of e-commerce live broadcast interaction. Then, effective sample data are collected through the questionnaire survey method, and multiple regression analysis and correlation analysis models are used to explore the interrelationship between interactive quality, immersion experience, and consumers’ purchase intention in e-commerce live broadcasting. The analysis shows that the interactive quality, perceived usefulness, responsiveness, and mutual assistance of e-commerce live broadcast positively affect consumers’ immersion experience and purchase intention (Sig. <0.05), consumers’ immersion experience has a positive and significant effect on purchase intention (Sig. <0.05), and immersion experience has an important mediating role between perceived usefulness, mutual assistance, and purchase intention. This paper centers on the interactive quality and immersion experience. It puts forward corresponding enhancement suggestions for live e-commerce, which provides a basis for the development of marketing strategies for live merchants and has certain theoretical significance and practical significance.
A Study of the Impact of Integrating Artificial Intelligence with the Archival Profession under Data Mining
Authors: Wang Yue , Li Wenjie , Wu Changjing , Wang Zhen
Published: May 2024

This paper integrates data mining technology into the technical processing layer of the “Artificial Intelligence +” archive intelligent service system to provide technical support for massive archive data. Using association rules, archive classification, Mean-Shift clustering, and other techniques to reveal the relationship between archives and users, archives, archives, and various practical activities so as to play the role of the information of these archive data at a deeper level. Applying the “Artificial Intelligence +” archive wisdom service system to the actual operation of the business management of college archive professional teachers, the results show that the speed of “Artificial Intelligence +” database entry (4.83s) is significantly higher than that of the traditional database (38.62s) the speed is higher. The contour coefficients of the classification results of the experimental group are all above 0.80, realizing high-precision classification of text data, image data, and audio data in digitized archives.2018-2023 The number of business declarations is rising, the total score of the scientific research type varies considerably, and the total score of the teaching type is concentrated in the distribution, with most of them being between 70-80. Mean-shift clustering algorithms can make the scientific research type, the teaching type, and the Research and Teaching and heavy type three data types to achieve a good clustering effect.
Empirical analysis of the stability of labor contract relationship and its influencing factors from the perspective of civil law
Authors: Zhang Haoyue , Qiu Xiaofan
Published: May 2024

Stable employment is a pivotal foundation for contemporary economic development and transformation. The enhancement of labor contract relationship stability is crucial for the great rejuvenation of the Chinese nation. Drawing from civil law and various research materials, this study identifies key factors influencing labor contract stability and posits several research hypotheses. This paper constructs a regression analysis model to examine the relationships between these factors and labor contract stability, where the influencing factors serve as independent variables and the stability of the labor contract relationship acts as the dependent variable. The model’s fit is rigorously evaluated. A preliminary analysis employing Pearson’s correlation coefficient reveals significant correlations between all 14 identified factors and the stability of labor contract relationships, supporting the use of regression analysis. Empirical results from the regression analysis indicate a significant positive impact of education level on labor contract stability (p = 0.031 < 0.05). Similarly, employment income is shown to positively influence labor contract stability (p = 0.009 < 0.05). Apart from education level and urban integration challenges, other identified factors also significantly affect the stability of labor contracts. This research not only advances our understanding of the dynamics influencing labor contract stability but also provides a robust empirical basis for shaping relevant civil law regulations and policies.
The Practice and exploration of deep learning algorithm in the creation and realization of intangible cultural heritage animation
Authors: Tao Ran
Published: May 2024

The rapid development of modern technology and civilization has made the survival of non-heritage culture more and more serious, and the protection and inheritance of intangible cultural heritage is a heavy task and a long way to go. This paper takes the feasibility of non-heritage animation creation as an entry point, analyzes the ideological mechanism in the process of non-heritage animation creation, and explores the economic realization brought by deep learning technology assisting non-heritage animation creation. For the lens scene switching in the process of non-heritage animation creation, this paper utilizes the CNN network for the initial positioning of the lens boundary. It establishes the tangent detection model of a non-heritage animation lens by combining it with the 3D-CNN network. To understand the diversity of non-heritage animation creation styles, this paper establishes a model for style migration of non-heritage cultural images based on the VGG-Net network and conducts experimental investigations. The results show that when the hyperparameter value of the model is set to λ = 3, γ = 1.2, the model retains only 5.19% of the candidate boundary frames, and the accuracy of the detection of the non-heritage animation creation tangent shots is 0.939. The total loss value in the process of style migration fluctuates around 0.005, and the subjective evaluation score of the images generated by the style migration network is 4.82. The deep learning algorithm that promotes the creation of non-heritage animation can expand the content and characteristics of non-heritage animation creation and can also realize the economic realization of non-heritage animation.
Practical Application of Professional Group Curriculum Resource Library in Art Design Teaching
Authors: Zhang Ying , Luo Xiaobo
Published: May 2024

This paper studies the relevant functions and contents of the professional group course resource library and constructs the architecture of the professional group course resource library. In the specific construction, the Lian Li VSM model and LDA topic model establish the domain ontology of the resource library, retrieve the content of educational resources from the resource document based on the retrieval request for resource filtering, extraction, and integration, and through the information mining algorithm to browse the degree of interest in the learning resources to calculate, to achieve the personalized recommendation of educational resources. Finally, the satisfaction of teachers and students with the professional group course resource library was analyzed respectively, and the effect of the application of the professional group course resource library in art and design teaching practice was studied using t-test and regression analysis. The results show that the regression coefficient values of the professional group course resource library on teachers’ concept of teaching, teaching content, and teaching effect are 0.148, 0.145, and 0.059, respectively. The t-values are 2.342, 2.644, and 1.212, respectively, with p<0.05, and the professional group course resource library has a significant positive effect on the teaching of art design. This study provides a new direction for the development of art design teaching, and it offers important reference content for universities to build a professional group course resource library.
Heat transfer and flow characterisation of aircraft heat exchangers considering manufacturing constraints
Authors: Lei Mingjun , Wan Shuting , Yu Xiaoying
Published: May 2024

With the progress and development of the times, the traditional aircraft power system and difficult to meet the needs of the current aviation development, for the aircraft power and heat exchanger research has been more and more extensive attention. This study takes the heat exchanger of the aircraft loop control system as an example, constructs the thermal management system of the aircraft according to the mechanism of its heat transfer and flow characteristics, and optimizes it under the consideration of manufacturing constraints. Based on the theory of fluid mechanics, the aircraft heat exchanger is simulated, and control equations based on heat transfer and flow characteristics are established. In this paper, the temperature difference of the heat exchanger is increased by 6.5°C and 5.4°C, respectively, and the heat transfer coefficient is between 11 and 14 kW/m²k. Furthermore, the fluid temperature has risen from 0.05 to 0.5 to 0.30 to 0.87 with the increase in flow rate. The maximum deviation values were 8.3%, 6.7%, and 8.6%, respectively, and the confidence intervals were all above 90%. This study can effectively improve the efficiency of aircraft heat exchangers compared to traditional heat exchangers and has more advantages in heat transfer performance, which provides a reference value for the development of the aviation field.
Application of automatic driving task serialisation monitoring for operating robots
Authors: Bai Yiming , Ruan Zhijie , Peng Zhenhua , Ruan Dabing , Liang Shaoming , Zhang Bingsheng , Liu Xinsheng
Published: May 2024

With the increasing application of industrial robots, more and more simple and repetitive operations in industrial automated production lines are replaced by industrial robots. In this study, a path planning algorithm is proposed for the autopilot task of an operating robot to find the optimal path from the start point to the goal point under the constraints of safe obstacle avoidance, shortest distance, and fastest time. Forward kinematics is used to detect whether it will collide with environmental obstacles until the first feasible result is detected as the end position for navigation. Serialized monitoring is used to obtain the activity information of each computational node, the hardware state information of the system, and the state of the autopilot task processing. Finally, obstacle avoidance navigation experiments on a mobile operating robot are conducted to verify the effectiveness and feasibility of the obstacle avoidance navigation algorithm. The results show that the maximum error of the autopilot task of the operating robot is 2.91cm, and the average error is 0.13 2cm, which is in line with the trajectory tracking error requirements of the operating machine control method and verifies the validity and practicability of this study.
Research on Improved Particle Swarm Computational Intelligence Algorithm and Its Application to Multi-Objective Optimisation
Authors: Chen Lifei , Xiong Fang
Published: May 2024

Due to the pervasive generalization challenges in optimization technology, there is a noticeable trend toward planning and diversifying optimization techniques. This paper focuses on particle swarm optimization algorithms, particularly their application in multi-objective optimization scenarios. Initially, the study examines basic particle swarm, standard particle swarm, and particle swarm algorithms with a shrinkage factor. Subsequently, an enhanced particle swarm optimization algorithm is proposed, incorporating a hybridization model and a convergence factor model tailored to the specific characteristics of particle swarm algorithms. This improved algorithm is then applied to multi-objective optimization problems, establishing a novel algorithm based on the fusion of the enhanced particle swarm approach with constrained optimization. Simulation experiments conducted on this model reveal significant findings. In low-dimensional settings, the algorithm achieves a 100% optimization success rate, marking an average improvement of 53.80%, 40.78%, and 24.76% over competing algorithms. Moreover, in multi-objective optimization simulation experiments, this algorithm generates 142 and 135 optimal solutions, outperforming traditional algorithms by 112 and 107 solutions, respectively. These results validate the efficiency and enhanced performance of the improved particle swarm-based multi-objective optimization algorithm, demonstrating its potential as an effective tool for addressing real-world optimization challenges.
The Practice of SPSS-based Correlation Analysis in English Teaching Research: An Exploration of the Relationship between Classroom Teaching and Student Achievement
Authors: Gao Jie , Borras Dolores D. , Caiga Beverly T.
Published: May 2024

The quality of English language instruction in the classroom is a pivotal factor influencing students’ learning outcomes and performance in English. Grounded in this research context, this study draws upon relevant theoretical frameworks and examines a cohort of 80 students from the 2023 English class at Anhui Medical College. A multiple regression model was constructed using various dimensions of classroom instruction—namely, content, methodology, organization, teacher competence, instructional attitude, and linguistic features—as independent variables, with students’ English achievements serving as the dependent variable. Utilizing SPSS statistical software, both multiple regression and principal component analyses were employed to investigate the correlations between classroom teaching practices and student performance. The main conclusions of the article after the test are: in the rating of English teaching classroom performance, the teacher’s teaching ability (5.0952) scores high, and the teaching method (3.0324) scores the lowest, and the teacher’s teaching ability has a close relationship with the students’ English achievement. English achievement = 2.136 + 0.223*Teaching content + 0.41*Teaching style + 0.129*Classroom organization + 0.227*Teaching competence + 0.189*Teaching attitude + 0.449Language characteristics. There is a need to improve the performance related to classroom teaching and thus improve the performance of students.
Constructing an innovative system of management and education in colleges and universities based on artificial intelligence technology
Authors: Ge Shuangshuang , Zhu Peipei , Hao Huijuan
Published: May 2024

At this stage, the information literacy of teachers and students is constantly improving, and the “digital campus” represented by artificial intelligence is landing in various regions and schools. This paper accurately constructs a college management and education innovation system based on artificial intelligence technology, including institutional mechanisms, a one-stop service platform, and an early warning mechanism. The early warning mechanism has an early warning model constructed. The construction of an academic early warning model for students is based on multivariate linear regression. A model for early warning of student activity safety was constructed using multiclassification logistic regression. The impact of fusing the two models was evaluated, as well as the impact of practical application. The ROC value of the first-level warning is 0.9533, and the ROC value of the second-level warning is 0.9428, and both values are close to 1, which verifies that the model can be practically applied. By analyzing the F1-score value through practical application, the average value of the F1-score throughout the semester was as high as 84.68%, and the number of warnings of the early warning model was higher than the number of feedback from teachers. It has been verified that the early warning model in this study can effectively and efficiently manage student activities and academic anomalies in colleges and universities.
Big Data User Behaviour Prediction Model Incorporating Deep Learning
Authors: Huang Xiang
Published: May 2024

With the improvement of the quality of human life, various industries utilize deep learning technology to meet the needs of users. In this paper, after exploring the deep temporal model and deep forest algorithm (DF) model in extracting the characteristics of user behavior features, we propose a user behavior prediction model based on CNN-LSTM and add a front embedding layer as well as a feature fusion layer to improve it and increase the prediction accuracy. The weighted average method is used to integrate CNN-LSTM with DF for algorithmic model fusion, aiming to improve the robustness and stability of the model and achieve accurate predictions of user behavior. In the empirical analysis, the correct rate of the fusion model proposed in this paper exceeds the proper rate of several other models by 11.75-15.73%, and it can reach 11.2% recall at k=20. Meanwhile, the lower the user behavior level is, the higher the prediction accuracy of the CNNLSTM+DF algorithm is, which can reach up to 95.20%. The lower the average relative error and average absolute error are, which can reach 13.45% and 3.92min respectively, which verifies the validity of the fusion model proposed in this paper, and provides a reference for the research in the related fields.
The Role and Strategy of Big Data in Promoting Local Tourism Development
Authors: Du Yanyan
Published: May 2024

As science and technology advance, the tourism industry is increasingly pivoting towards digital and intelligent transformation. The pivotal role of big data in shaping tourism trends is becoming more apparent. This study leverages big data to explore its impact on tourism development and proposes a big data-based model for this purpose. An influence mechanism model tailored to local tourism’s unique characteristics was developed to guide this analysis. Employing data mining techniques, this research utilizes the association rule model to forecast local tourism trends. Additionally, it applies heat evaluation and hotspot analysis models to examine local tourism activities. Spatial characteristics of local tourism are investigated using the nearest neighbor algorithm. An empirical study conducted in Province H illustrates these concepts in action. Here, the entertainment and leisure segment aligns most closely with the overall clustering characteristics, achieving a Z-score of -200.01. The peak hotness months in Province H are May and October, with hotness indices of 0.0438 and 0.0468, respectively. Entertainment and leisure activities make the most significant contribution to this metric, with an average value of 0.0235. Moreover, the prediction error does not exceed 5%, underscoring the validity and practical utility of this study’s methodological approach in analyzing local tourism development. This provides a robust scientific basis for harnessing data to foster local tourism growth.
Research on the Impact of Digital Trade Barriers on International Business and Countermeasures
Authors: Guo Xiaping
Published: May 2024

In the contemporary digital economy, digital trade barriers have emerged as significant external risks for enterprises engaging in international business despite the digital economy’s role as a critical driver of international commerce. This study examines the relationship between digital trade barriers and international business through a theoretical model, investigating the influence mechanisms of digital trade barriers alongside other factors. Utilizing data from several countries spanning from 2015 to 2022, this research employs correlation analysis, benchmark regression, and robustness tests within a constructed benchmark regression model to explore the impact of digital trade barriers on international business. The findings indicate a significant negative correlation between digital trade barriers and international commerce, with a 1% increase in the trade restriction index of digital services resulting in a 0.217% decrease in international commerce (p<0.01). Additionally, while R&D intensity and total trade have positive effects on the development of international commerce, trade openness appears to have a negative impact. Given these results, it is recommended that governments enhance the construction of digital service trade systems and actively engage in the formulation and convergence of international regulations. Simultaneously, enterprises should elevate their technological capabilities related to digitization to effectively navigate and mitigate the impacts of digital trade barriers.
Research on Knowledge Sharing and Innovation Capacity Enhancement of Heterogeneous Research Institutes under the Construction of Knowledge Mapping
Authors: Hua Zhilei , Zhao Yingtao , Liu Yiying
Published: May 2024

Enhancing research efficiency by managing related knowledge and forming standardized applications has always been an effort to optimize the work of off-site research institutes, and knowledge sharing is one of the most important methods in many practices. In this paper, the entity matching algorithm is used to identify and match the nodes in the knowledge graph, the connection algorithm is used to calculate and sort the data volume of each node, and all the nodes in the knowledge graph are connected in series. After introducing the update mechanism to establish the decentralized global knowledge graph, the knowledge graph has been integrated into the knowledge-sharing system to enable knowledge sharing between off-site research institutes. In this paper, the accuracy of the full-text search for knowledge graphs can reach 87%, which meets the demand for knowledge sharing. The speed of researchers’ research plan formulation in heterogeneous research institutes has been accelerated by 85.40%, and the efficiency of the research institutes has significantly improved. At the same time, the institute’s innovation ability also increased significantly, with a relative increase of 57.21% in the average number of patents filed annually. This paper provides a reference path for the realization of knowledge sharing among heterogeneous research institutes. It establishes a foundation for significant improvements in the efficiency and innovation ability of research institutes.
Interior Space Design and Modelling Methods for Smart Homes - Integrating BIM and VR Technologies
Authors: Huang Rui , Wang Xiaowei , Zhou Suting
Published: May 2024

In this study, the integration of Building Information Modeling (BIM) and Virtual Reality (VR) technologies with performance analysis software facilitates the selection of optimal indoor space layouts for settlement buildings. This is achieved through the use of information modeling and visualization tools to assess various aspects such as sunlight exposure, lighting conditions, architectural parameters, and energy consumption across different building layouts. A virtual environment was created using BIM and VR, within which the collision detection algorithm was refined using a chime-playing test scenario to enhance the quality control of 3D models. At 5000 triangular slices, the detection algorithm optimized in this study demonstrated a real-time performance that is 19 milliseconds faster than that of the comparative algorithm. Furthermore, in scenarios involving micro-speed air exchange, an open window area of 30 square meters facilitated an air volume of 250,168, indicating both economic and practical benefits. The overall satisfaction with interior design and spatial arrangement achieved through BIM and VR integration consistently exceeds 80%, underscoring the synergistic potential and future-oriented trajectory of combining these technologies.
Three-dimensional Visualisation of Cultural Landscape under the Perspective of Culture and Tourism Integration
Authors: Lai Yanlin
Published: May 2024

The three-dimensional visualization evaluation of cultural landscape has practical needs and theoretical significance in today’s world. Based on the perspective of cultural and tourism integration, the study adopts the method of stepwise regression analysis to explore the factors influencing the satisfaction of cultural landscape with a historical and cultural neighborhood landscape as the research sample. On this basis, it discusses the 3D visualization modeling process of cultural landscapes. It realizes the 3D visualization construction of a historical and cultural park, uses a questionnaire survey to collect relevant data, combines the principal component analysis method and IPA model to evaluate its visualization results, and divides different elemental functions. As a result, nine influencing factors with significant impact on the satisfaction of cultural landscape were obtained, with architectural style, traffic accessibility, and landscape scope being the most prominent, and the regression coefficients were 0.589, 0.435, and 0.367, respectively. The key performance elements of the three-dimensional visualization of the cultural landscape need to be improved, such as the reasonableness of the historical inference, the applicability of the technology, the sense of place, the sense of reality, the sense of aesthetics, the interactivity, and so on. The research presented in this paper can offer insights and lessons for the future design of cultural landscapes and their 3D visualization process.
Digital Intelligent Innovative Teaching Mode of Curriculum Civics and Politics Integration
Authors: Li Jiajia
Published: May 2024

The primary objective of Civics education in higher education institutions is to guide students toward acquiring appropriate political identities and values. To achieve this, we advocate for the incorporation of a knowledge-tracking model in Civics curriculum instruction, highlighting that the practical application of in-depth knowledge tracking manifests throughout the educational process. Addressing the challenges inherent in the Civic Politics teaching model that integrates knowledge tracking, we propose solutions focused on the dimensions of student performance behavior and learning capabilities within the Civic Politics course. This involves the use of clustering grouping and attention mechanisms to refine the construction of the knowledge tracking model for Civics teaching. Building on this foundation, we define the research subjects and tools and provide an illustrative case study of the implemented knowledge-tracking model in Civic Politics education. The results are presented in terms of t-value and p-value, political identity (t=-6.351, p=0.009), moral quality (t=-4.528, p=0.002), and learning interest (t=-4.444, p=0.005), the p-value is less than the critical value of 0.05, and all three have significant differences. This study can effectively improve students’ political identity, moral quality, and learning interest, and promote digital innovation and the development of college curriculum in Civics.
Research on evaluation system and method of MES system for intelligent manufacturing
Authors: Li Muhan , Jiang Yusheng , Liang Ni
Published: May 2024

With the development of informatization and digitalization, the transformation of intelligent manufacturing has become the focus. This paper builds an evaluation system based on the scientific evaluation method of the development level of smart manufacturing and the real demand situation. It establishes an evaluation model of intelligent manufacturing MES systems by combining the GA-BP algorithm. Then, a SeqGAN generative adversarial network is used to expand the real samples. The evaluation model was trained and validated by constructing a training model through the BP neural network, taking the sample data of evaluation indexes as the network input and the seven labels from Industry 1.0 to Industry 4.0 as the network output. The results show that the classification accuracy of the model is above 98%, and all of them have achieved good results. In the actual case evaluation, it is judged that the intelligent manufacturing MES system of Company Z is in the range of industry 3.0 to 3.5, and this result is very close to the manual evaluation of the factory field survey. The synthesis shows that the model is reasonable and effective and has important guiding significance for the evaluation of enterprise intelligent manufacturing MES systems.
Historical Evolution and Modern Development of Piano Performance - A Visual Analysis Based on Cite space
Authors: Li Songkun
Published: May 2024

Piano performance represents a refined artistic expression characterized by its expressive and emotive qualities. This study focuses on research papers related to piano performance indexed in the Chinese literature database, utilizing the CiteSpace visualization tool to conduct an analysis. Employing the tool’s capabilities for word frequency, thematic, and cluster analysis, we investigate the temporal and spatial distributions, key terms, research trends, and emergent themes in the literature on piano performance. This multifaceted approach enables a deeper understanding of the developmental stages and overarching trends in the field. Our findings reveal significant shifts in thematic focus and research intensity, with notable increases in themes related to the transformation of piano performance and theoretical exploration post-2017.50, achieving an impact score exceeding 0.425. Prominent emergent keywords include “piano art” (4.9948), “piano certificate” (3.8833), “style” (3.4721), “accompaniment” (3.3155), “piano technique” (2.8888), “piano teaching” (2.6997), “emotional expression” (2.6129), and “intelligence” (2.2193). These findings indicate a trend towards the integration of modern technology and intellectual approaches in piano performance. This study provides a comprehensive overview of the evolution and current trends in piano performance research, offering insights into its future trajectory.
Retirement: strengths and weaknesses for a full and healthy old age
Authors: Amoretti Guido
Published: May 2024

Retirement is a coveted goal for working people. Although it is seen as a period of relaxation and tranquillity, retirement from work, also because it is associated with other relevant changes in an individual’s life related to family relationships, brings with it a number of potential risks that may trigger problems of a psychosocial nature (identity crisis, change of parental role, adaptation to new marital relationships, possible marital crisis and divorce, depressive symptoms and suicidal ideas) which, in turn, may be facilitators of fragility also on the physical side. The attention of the various governments is generally focused on the health problems of those who are retired with a view to containing public expenditure, without considering the fact that the main problems for this particular segment of the population may come from problems of reintegration into social life and occupation of leisure time. When there is no adequate adaptation to the changed conditions of life in the transition from worker to pensioner one fatally exposes oneself to the risk of progressive isolation. the reduction of social contracts, the contraction of the use of one’s cognitive functions with possible consequences in the medium to long term on one’s ability to remain self-sufficient. This would ultimately turn into a socio-medical problem, with the associated costs, when an appropriate policy of psycho-social interventions could delay the effects.
Shared Endeavours: Universities and Communities Join Efforts for Ukraine’s Post-War Recovery
Authors: Sikorska Iryna , Gerasymchuk Tamila
Published: May 2024

This article explores the pivotal role that university-community partnerships can play in fostering sustainable development and resilience within Ukraine in wartime and in its path to recovery and rebuilding the country. By leveraging the intellectual resources, research capabilities, and community engagement initiatives of universities, this collaborative approach seeks to address multifaceted challenges ranging from infrastructure rehabilitation to social cohesion. The article examines the potential impact of such collaborations on educational advancement and the well-being of communities affected by conflict and displacement drawing valuable insights and lessons applicable to Ukraine’s unique context. It also highlights the significance of fostering interdisciplinary collaboration among academic institutions, governmental bodies, non-governmental organizations, and local communities to create holistic and sustainable solutions. Key themes include the importance of knowledge transfer, capacity building, and inclusive community participation in Ukraine’s rebuilding process. Moreover, the article explores potential hurdles and challenges that may arise in implementing such partnerships, offering strategic recommendations for overcoming these obstacles. Ultimately, the article advocates for a comprehensive and integrated university-community partnership model as a catalyst for Ukraine’s recovery, emphasizing the transformative potential of education, research, and community engagement in shaping a resilient and prosperous future for the nation.
Third Mission of Universities: Regulatory Frameworks in a Comparative Perspective
Authors: Holovko-Havrysheva Oksana , Krayevska Oksana , Sas Svitlana
Published: May 2024

This contribution focuses on the EU, national and institutional practices of HEIs’ third mission regulation with a particular attention to the experiences of Ukrainian HEIs, which they developed in response to the challenges caused by the ongoing Russian aggression against Ukraine. It is argued that currently the regulatory frameworks for the third mission are more established at the intra-institutional level about ensuring the entrepreneurial aspects of the HEIs engagement, whereas the third mission social engagement models still remain on margins of the university life.
The War of Vladimir. Nationalism, Narcissism, and Childhood Battles
Authors: García-García Juan
Published: May 2024

The war in Ukraine has had enormous media coverage in the West, generating a wide-ranging debate concerning its origins, responsibilities, and consequences. The debate in the media raises an interesting question seldom explored in the study of nations and nationalism, specifically, the scarce incidence or penetration by expert knowledge into the theories of common sense and profane knowledge. In fact, despite the current consolidation in the scientific literature of the constructionist and modernist paradigm – of a sociological nature – other visions and interpretations of the past continue to be widely accepted and popularized beyond academia. This article analyzes the weight and influence of psychology, psychiatry, and psychoanalysis in the social representation of nationalism. The persistence of psychopathological language in the profane interpretation of the conflict is explored using the discourse of the press and, in particular, the opinion columns published in various Western countries during the first weeks of the war. The article shows that the criticism and denunciation of nationalism are still being formulated nowadays with the voices of psychology and psychiatry, the psychodynamic vision of the authoritarian, and the vulgarized portrayal of Adolf Hitler.
Design Practices for Sustainability in Micro Enterprises in Brazil Through the Innovation Route
Authors: Matheus Ricardo , Ferreira Denise Helena Lombardo , Mariosa Duarcides Ferreira , Georges Marcos Ricardo Rosa , Falsarella Orandi Mina
Published: May 2024

Objective: The research aims to map the concept of Design for Environment (DfE) and propose a plan of guidelines for implementation and use in Research, Development, and Innovation (RD&I) teams focused on packaging. It also aims to identify DfE elements, where they are being used and results produced, as well as proposing a checklist to guide sustainable practices in product and/or packaging designs.
 
Method: The research is qualitative, developed through a bibliographic review, when evaluating the scenario of micro-enterprises that use DfE practices in Brazil through innovation processes. As for nature, it is applied by proposing a checklist to guide best practices to position micro-enterprises in the sustainability scenario. In relation to the objectives, the approach is exploratory in explaining the scenario in which micro-enterprises in Brazil are involved in innovation for Sustainability.
 
Results and Discussion: It was found that for most authors, companies have difficulty innovating due to the challenges and uncertainties that surround them. The study finds a panorama that shows fear on the part of micro and small companies regarding take risks inherent to the innovation process. In this context, it is suggested that in future studies, the approach for knowledge of causes that corroborate this scenario, especially those that are directly related to the innovation process for Sustainability.
 
Research Implications: This study collaborates by sharing the scenario that permeates among micro-enterprises in the national scenario, with regard to investments in innovation for sustainability, fears and risks, signaling to those active microentrepreneurs current projects as well as for those with plans for future micro-enterprises.
 
Originality/Value: At the end, a check list was proposed suggesting the main practices based on DfE based on Product Life Cycle Assessment (LCA).
Approaching Statistics as a Distinct Subject and Its Impact on Reasoning and Conceptual Errors
Authors: Rosal José Carlos Casas del , Machado Alexander Maz , Ñungo Oneida Muñoz , Gómez Astrid Cuida
Published: May 2024

Objective: This study aims to determine the level of statistical reasoning and misconceptions expressed by ninth-grade students in two schools. In one of the schools, statistics is taught as a specific subject, while in the other, it is included within the mathematics curriculum.
 
Theoretical Framework: Students are taught statistics throughout their primary education, so by secondary school, they are expected to have developed a good level of statistical reasoning. However, classroom experience suggests this may not be the case. Additionally, this topic often receives less attention in favor of other subjects included in the mathematics curriculum.
 
Method: The methodology adopted for this research includes descriptive and inferential analyses to compare the rate of correct reasoning responses and conceptual errors. Data collection was carried out using the Statistical Reasoning Assessment (SRA) test.
 
Results and Discussion: The results showed different behaviors between the two groups. This suggests that teaching statistics separately from mathematics can influence the learning of this subject.
 
Research Implications: The advantages offered by separating statistics from the rest of mathematics suggest that this approach should be considered in the future teaching of the subject.
 
Originality/Value: This study contributes to the literature by demonstrating that the separation of statistics from mathematics teaching should be considered. The relevance and value of this research are evidenced by the need to improve students' statistical reasoning abilities.
Food Culture: Identification of Typical Food and Dishes of a Municipality in the Northeast Region of Brazil
Authors: Souza Milene de Abreu , Sena Júnior Ailton Santos , Nascimento Bárbara Melo Santos do
Published: May 2024

Objective: The aim was to map among the interviewed population of Lagarto/SE which savory and sweet typical foods and preparations are considered characteristic of the city.
 
Theoretical Framework: The relationship between travel, cuisine, and culture highlights their economic potential by transforming gastronomy and tourism into strategic ventures. Emphasizing the preservation of gastronomic legacies as cultural expressions and the adaptation of dining spaces to reflect this perspective. Additionally, cultural tourism enriches visitors' experiences and promotes economic development. Therefore, regional cuisine is an essential element of daily life and a tourist attraction, connecting people and reflecting local culture. However, the influence of globalization and fast-food chains has impacted eating habits, raising concerns about health and the decline of communal dining.
 
Method: Cross-sectional study, conducted qualitatively, involving the administration of a questionnaire with questions related to the population's profile and the municipality's food identity. The data were evaluated using Microsoft Excel, presenting absolute and relative values.
 
Results and Discussion: There was a predominance of women (63.4%) and the dominant age group was 18 to 25 years old (27.2%). How much to marital status, there was a predominance of singles (45.5%). Regarding education, 29.5% had incomplete primary education and most of the interviewees received less than 1 minimum wage (44.1%). The typical food reported was cassava (39.2%), followed by jackfruit (15.4%). The salty preparation was maniçoba (27.4%), accompanied by rice with chicken (17%) and couscous (16.2%) and the sweet preparation, was milk sweet (33.7%), followed by rice sweet (11.4%). The research highlights the Lizard gastronomic culture, in a way that rescues, values and, above all, enhances this local cultural element so that it is not forgotten either by the residents or by its visitors.
 
Research Implications: Generating scientific data from the Brazilian Northeast region to support discussions around the gastronomic approach. Therefore, it is necessary to invest in knowledge production about gastronomy linked to technical development.
 
Originality/Value: It is justified by the need for scientific studies that contribute data on gastronomy and its relationship with tourism and culture in order to broaden the knowledge of Brazilian population's gastronomic practices, aiming to encourage and valorize them.
Not Every Anosmia is COVID, a Case of Nasal Mass
Authors: Gunay Erkan
Published: May 2024

Anosmia is a frequent symptom for COVID infection. It was experienced by almost 53% of those affected, sometimes persisting longer periods. Nasal blockage is common symptom for emergency patients and frequently associated with allergic rhinitis. 25-year-old male presented with persistent bilateral nasal blockage, blood-stained nasal discharge, anosmia and headache. During the beginning of the pandemic, he was diagnosed with COVID and complaining of anosmia and nasal blockage. He was treated with antihistaminic medicine for allergic rhinitis, but his symptoms
persisted. He had breathing, bleeding and smelling problems in the last 2 years and started complaining of left sided proptosis for 3-4 weeks. He was referred from ophthalmology. He denied other prior disease or medication. On examination he has nasal voice, left side exophthalmos, without diplopia or vision problem. The right tympanic membrane was intact, left side dull with effusion. Other system evaluations were unremarkable.
Nasal endoscopy revealed fungating mass with blood clots and engorged vessels filling both cavities. MRI report described soft tissue mass, infiltrating the nasal cavity, paranasal sinuses with intracranial extension, to involve the left sub frontal region (figure 1). Epicenter of the mass was likely to be the ethmoid sinuses. Biopsy was taken and patient was followed up for surgical intervention. Smell and taste disorders emerge during COVID infection. Allergic rhinitis is also common amongst emergency patients. Rhinitis can be differentiated from sinus problems by the increased response of nasal obstruction to treatment, clear nasal discharge, and absence of pain or fever. Rhinitis does not lead to ostial obstruction, and patients do not complain of facial pain or headache. For suspected rhinitis or acute sinusitis, routine radiographic examination is not recommended. For persistent cases axial and coronal CT is the imaging of choice. Our patient was investigated for sinusitis complications and additional further imaging was necessary for proper management. Nasal blockage and upper respiratory problems may be overseen by patients or physicians. Repeated admissions and persistent symptoms should be suspicious for emergency physicians. Additional imaging might be needed, and emergency physicians should be careful of diagnosing common symptoms like nasal blockage especially for patients with persistent admissions.
Fındık İşletmelerinin Ekonomik Sürdürülebilirliğine Etki Eden Faktörlerin Belirlenmesi
Authors: Meral Hüseyin , Aydoğan Mehmet , Esen Alpay , Ergün Ekrem
Published: May 2024

Bu çalışma, fındık tarım işletmelerinin ekonomik sürdürülebilirliğini ve sürdürülebilirliği etkileyen faktörleri belirlemeyi amaçlamaktadır. Araştırmanın ana materyalini 2021 yılında, 380 fındık üreticisi ile yüz yüze yapılan anketlerden elde edilen veriler oluşturmaktadır. Fındık tarım işletmelerinin sosyo-ekonomik özelliklerinin karşılaştırılmasında tek yönlü Varyans analizi ve Kruskal Wallis testi analiz yöntemlerinden yararlanılmıştır. Ekonomik sürdürülebilirliği etkileyen faktörlerin belirlenmesinde çoklu doğrusal regresyon modelinden faydalanılmıştır. Araştırma sonucunda fındık tarım işletmelerinin ekonomik sürdürülebilirlik endeksi ortalaması 0,48 olarak hesaplanmıştır. Trabzon (0,37), Giresun (0,43) ve Ordu (0,46) illerindeki işletmeler ortalamanın altında ekonomik sürdürülebilirliğe; Samsun (0,58), Sakarya (0,61) ve Düzce (0,64) illerindeki fındık işletmeleri ise ortalamanın üstünde ekonomik sürdürülebilirliğe sahiptirler. İşletmelerin ekonomik sürdürülebilirliğini çiftçinin yaşı negatif; eğitim süresi, hanehalkı büyüklüğü, köyde ikamet etme, tarımsal örgütlere üyelik, fındık verimi ve satış fiyatı pozitif etkilemektedir. Çiftçilerin bilgi düzeylerinin artırılmasına yönelik eğitim çalışmaları yapılması, kırsal göçü önleyici politikaların uygulanması ve verim artışına yönelik yayım çalışmalarının gerçekleştirilmesi ekonomik sürdürülebilirliğe katkı sağlayacaktır.