Opportunities For Transformation Research Articles

PUBLIC LIBRARY IN TODAY’S WORLD – SOCIAL AND LEGAL ASPECTS

Libraries have a long history. They existed ever since writing began. Historical transformation affected not only the contents of libraries, but also their form, mission, functions and services. With changing times and societies, evolving information and communication technologies, and contrary to predictions that libraries might lose their role and disappear altogether, they have changed along with the needs, demands and habits of society, learned to draw on new technologies, so forming a completely new understanding of libraries, their definition and role in today’s educational, cultural, political and social environment. Development of the library sector was affected also by global changes and crises, but libraries were able to respond to challenges and use them as an opportunity for development, positive changes and transformation. This was mainly thanks to a user-oriented approach pursued by libraries, putting people and their needs, demands and rights at the heart of library activities. This forms a new culture of libraries, taking the place of their old philosophy, which was collection-oriented. Libraries provide free access to information, knowledge, education, cultural heritage and cultural events, and play a key role in science, lifelong learning, developing digital skills, improving literacy and information literacy in society, strengthening democracy and ensuring civic participation, promoting the use of creative potential, and ensuring access to state and municipal services. Thus, the phenomenon of today’s library is associated with both accumulating and preserving cultural heritage and taking part in securing an individual’s social and civil rights.The article analyses the phenomenon of the public library as a cultural establishment, its role in meeting the social needs of society, and problems of legislation in the sustainable development of library activities. The focus of the article is on public libraries, as their main task is to provide services to the entire society. The analysis of the legal framework was carried out in the context of Latvia, observing the international framework. This is necessary to understand how the legal framework can ensure the development of libraries. Following the mission of libraries to act for the public good and to put people and their needs at the heart of library activities, the legal framework for libraries should reflect and protect public interests and an individual’s right to information, freedom of expression and association, diversity of opinion and belief, artistic freedom, equal treatment, culture and education. A narrow understanding of library functions can restrict the right of access to information, education, culture and social services. The legislator should introduce library functions in the legal framework by including also a social aspect, clarifying and expanding information, educational and cultural functions.

Research on Reform and Innovation of Training Mode of Civil and Hydraulic Engineering Graduate Students under the Background of “Dual Carbon” Goals

As an important part of the overall layout of ecological civilization construction, carbon peaking and carbon neutrality provide strategic opportunities for low-carbon energy transformation and innovative development of higher education. Based on the training of civil and water conservancy professional postgraduate students, this paper builds an interdisciplinary teaching system centering on the concept of “dual carbon”, and explores the relationship between energy transformation and energy conservation and emission reduction, engineering technology and green development, practical cases and analysis and other course systems through the establishment of a composite innovative teaching team of civil and water conservancy and innovative personnel training mode. In order to achieve the “dual carbon” goals of the society, this paper puts forward the model of university-enterprise cooperation and the integration of science, production and education.

Musealisation of architectural heritage for sustainable and inclusive tourism. The Yonghe Temple. Beijing

Architectural heritage is one of the best testaments to the history of civilizations, embodying multidisciplinary values that should be shared through diverse cultural offerings. To achieve this, it is crucial to select engaging themes and develop museological materials that enhance understanding and appreciation of such sites. Equally important is leveraging modern dissemination technologies to reach diverse audiences effectively. The Falun Hall of the Yonghe Temple in Beijing exemplifies this approach. By analyzing its architectural elements, materials, and decorations, specific content can be created to enrich visitors’ experiences while promoting appreciation, dissemination, and conservation. The growth of global cultural tourism underscores the importance of sustainable practices that add touristic value, educate visitors, and align with the Sustainable Development Goals (SDGs) without compromising heritage integrity. Virtual Reality (VR) offers transformative opportunities for heritage preservation. Digital models of historicalbuildings ensure their preservation for future generations, facilitating global access and overcoming physical barriers. Additionally, branding and commercial products tied to such monuments can enhance their tourist appeal and support conservation efforts. This study emphasizes the potential of these strategies in fostering sustainable cultural tourism and preserving architectural heritage.

Enhancing mechanical ventilator reliability through machine learning based predictive maintenance

Background With the advancement of Artificial Intelligence (AI), clinical engineering has witnessed transformative opportunities, enabling predictive maintenance of medical devices, optimization of healthcare workflows, and personalized patient care. Respiratory equipment plays a vital role in modern healthcare, supporting patients with compromised or impaired respiratory capacities. However, ensuring the reliability and safety of these devices is crucial to prevent adverse events and ensure patient well-being. Objective This study aims to explore machine learning techniques to enhance predictive maintenance for mechanical ventilators. Method The dataset used for this study contains information about 1350 entries of mechanical ventilators, made by 15 different manufacturers and available in 30 distinct models. Different machine learning algorithms, including Logistic Regression, Decision Trees, Random Forest, K-nearest Neighbors, Support Vector Machines, Naive Bayes, and XG Boost are developed and tested in terms of their performance in predicting mechanical ventilator failures. Results The ensemble methods, particularly Random Forest and XGBoost, have proven to be more adept at handling the complexities of the dataset. The Decision Tree and Random Forest models both showed remarkable accuracies of approximately 0.993, while K-Nearest Neighbors (KNN) performed exceptionally with near perfect accuracy. Conclusion Adoption of automated systems based on artificial intelligence will help in overcoming challenges of ensuring quality of MDs that are already being used in healthcare institutions. Implementing machine learning-based predictive maintenance can significantly enhance the reliability of mechanical ventilators in healthcare settings.

Wind Bands as Cultural Tradition and Economic Opportunities in Transformation in Sincelejo (Sucre, Colombia)

Human interactions are permeated by multiple factors, including cultural practices, where music is a fundamental element. The objective of this study was to understand the cultural identity of traditional wind band music and its organisational capacity in Sincelejo, Sucre - Colombia. The methodology was framed under the qualitativeapproach with a case study design, and interviews were used to collect the information. The results indicate that traditional wind band music constitutes the cultural identity of the inhabitants of Sincelejo, reinforcing the sense of belonging and social cohesion; in terms of organisational capacity, the bands have been financially consolidated over the years, although it is still necessary to strengthen this aspect to guarantee their sustainability. In conclusion, traditional wind band music in Sincelejo plays a fundamental role in the preservation of cultural identity and social cohesion. However, greater structuring of its financial management is required to ensure the continuity and development of this cultural tradition.

Harnessing artificial intelligence for business optimization: Enhancing efficiency and sustainability in SMEs

Small and Medium Enterprises (SMEs) play a crucial role in driving economic growth and innovation, yet they often struggle with limited resources, operational inefficiencies, and sustainability challenges. In this context, artificial intelligence (AI) presents a transformative opportunity for optimizing business processes, improving decision-making, and promoting sustainable practices. This review explores the integration of AI technologies to enhance efficiency and sustainability in SMEs, focusing on practical applications such as automation, predictive analytics, and intelligent resource management. By leveraging AI, SMEs can automate repetitive tasks, optimize supply chains, and streamline financial operations, leading to cost reductions and productivity gains. Additionally, AI-powered customer engagement tools, such as chatbots and personalized marketing systems, allow SMEs to better understand customer behavior and enhance service delivery. On the sustainability front, AI enables real-time monitoring of energy consumption, waste management, and resource utilization, helping SMEs align with environmental and regulatory standards. However, the adoption of AI in SMEs faces significant challenges, including data quality issues, limited budgets, and a lack of technical expertise. This review proposes a strategic approach to implementing AI solutions, emphasizing the need for tailored tools, effective data management, and employee training. By examining successful case studies, we highlight how AI-driven optimization has empowered SMEs to overcome operational hurdles and achieve sustainable growth. As the business landscape becomes increasingly competitive and sustainability-focused, integrating AI is not only beneficial but essential for SMEs seeking long-term resilience. This study aims to provide SMEs with actionable insights into adopting AI technologies, ultimately fostering efficiency, innovation, and sustainability in their operations. Keywords: Artificial intelligence, Small and medium enterprises (SMEs), Business Optimization, Review.

AI: A transformative opportunity in cell biology.

The success of artificial intelligence (AI) algorithms in predicting protein structure and more recently, protein interactions, demonstrates the power and potential of machine learning and AI for advancing and accelerating biomedical research. As cells are the fundamental unit of life, applying these tools to understand and predict cellular function represents the next great challenge. However, given the complexity of cellular structure and function, the diversity of cell types and the dynamic plasticity of cell states, the task will not be easy. To accomplish this challenge, AI models must scale and grow in sophistication, fueled by quantitative, multimodal data linking cell structure (their molecular composition, architecture, and morphology) to cell function (cell type and state). As cell biologists embrace the potential of AI models focused on cell features and functions, they are well positioned to contribute to their development, validate their utility, and perhaps, most importantly, play a leading role in leveraging the powers and insight emerging from the coming wave of cell-scale AI models.

Assessing the Quality of Automatic-generated Short Answers using GPT-4

Open-ended assessments play a pivotal role in enabling instructors to evaluate student knowledge acquisition and provide constructive feedback. Integrating large language models (LLMs) such as GPT-4 in educational settings presents a transformative opportunity for assessment methodologies. However, existing literature on LLMs addressing open-ended questions lacks breadth, relying on limited data or overlooking question difficulty levels. This study evaluates GPT-4’s proficiency in responding to open-ended questions spanning diverse topics and cognitive complexities in comparison to human responses. To facilitate this assessment, we generated a dataset of 738 open-ended questions across Biology, Earth Sciences, and Physics and systematically categorized it based on Bloom’s Taxonomy. Each question included eight human-generated responses and two from GPT-4. The outcomes indicate GPT-4’s superior performance over humans, encompassing both native and non-native speakers, irrespective of gender. Nevertheless, this advantage was not sustained in ’remembering’ or ’creating’ questions aligned with Bloom’s Taxonomy. These results highlight GPT-4’s potential for underpinning advanced question-answering systems, its promising role in supporting non-native speakers, and its capacity to augment teacher assistance in assessments. However, limitations in nuanced argumentation and creativity underscore areas necessitating refinement in these models, guiding future research toward bolstering pedagogical support.

Sustainable Food Revolution: The industry 5.0-Permission Marketing Convergence

The integration of Industry 5.0 technologies and permission marketing offers transformative opportunities for advancing sustainable practices in various industries, including food production. Industry 5.0 emphasizes human-machine collaboration, leveraging robotics, AI, IoT, and blockchain to enhance efficiency, transparency, and sustainability. Permission marketing complements these technologies by fostering trust and consumer engagement through opt-in communication, transparency, and personalization. In sustainable food production, Industry 5.0 enables precision agriculture, optimized supply chains, and waste minimization. Key technologies such as IoT sensors and AI-driven analytics provide actionable insights for resource conservation, while digital twins and predictive analytics streamline operational planning. Blockchain ensures traceability and accountability, empowering consumers with verifiable information about sourcing and sustainability practices. Moreover, renewable energy integration further underscores the environmental responsibility of Industry 5.0 by reducing carbon emissions and promoting energy efficiency. Permission marketing enhances these efforts by creating platforms for transparent, personalized communication with stakeholders. Opt-in systems and tailored messaging build trust, while educational campaigns empower consumers to make informed choices about sustainable products. Feedback mechanisms foster collaboration, aligning sustainability initiatives with stakeholder expectations. The convergence of Industry 5.0 and permission marketing not only addresses environmental challenges but also aligns with evolving consumer expectations for ethical practices. This integrated approach fosters trust, optimizes resources, and strengthens stakeholder relationships, presenting a robust framework for achieving long-term sustainability goals. Embracing these innovations is essential for creating resilient systems that balance productivity with ecological and societal responsibility.

The Expected Contribution of Artificial Intelligence (AI) Adoption in Supply Chain Management

In today's rapidly evolving economy, the adoption of artificial intelligence (AI) within supply chain management (SCM) has emerged as a key area of study. The integration of AI technologies into SCM systems presents a transformative opportunity for organizations seeking to enhance operational efficiency, reduce costs, and establish a competitive advantage in a dynamic market. AI technologies—ranging from machine learning algorithms to predictive analytics—serve as pivotal tools in addressing these challenges. By automating routine tasks, forecasting demand with greater accuracy, and facilitating real-time decision-making, AI enhances responsiveness and agility within supply chains. The economic benefits of incorporating AI into SCM frameworks are substantial. Implementing AI-driven solutions can lead to significant cost savings through improved inventory management, reduced waste, and enhanced resource allocation. For instance, machine learning models can predict stock requirements more accurately, minimizing excessive inventory and associated holding costs. Additionally, AI enhances supplier relationship management by analyzing vendor performance data, leading to more informed selection processes and negotiation strategies. As the field continues to evolve, it is crucial for professionals to engage with emerging technologies, ensuring that they remain competitive and responsive to the demands of an ever-changing market landscape. This study reviews the literature to determine why supply chain management (SCM) needs to adopt artificial intelligence (AI) in terms of integrative tactical planning, resource utilization and cost reduction, risk management, data management and inventory management. The aim of this study was to encourage professionals to investigate the possibilities of AI technology to enhance several elements of the supply chain.

The role of artificial intelligence in enhancing healthcare for people with disabilities

The integration of artificial intelligence (AI) in healthcare delivery represents a transformative opportunity to enhance the lives of people living with disabilities. AI-driven technologies, such as assistive devices, conversational agents, and rehabilitation tools, can mitigate health disparities, improve diagnostic accuracy, and facilitate effective communication with healthcare providers, fostering more equitable healthcare environments. This commentary explores these applications while addressing the ethical challenges and limitations associated with AI deployment. Specific challenges, such as algorithmic bias, privacy risks with patient data, and the complexity of designing inclusive technologies, are discussed to provide a balanced perspective. For example, biased diagnostic tools may lead to inequitable care, and privacy breaches can compromise sensitive data. Key areas of focus include personalised care through AI-powered systems, the design of inclusive AI technologies incorporating continuous feedback loops and partnerships with advocacy groups, and the development of AI-enabled robotics for physical assistance. This commentary paper emphasises the importance of addressing these limitations alongside advancing ethical AI practices and ensuring continuous user involvement to meet the diverse needs of people living with disabilities, ultimately promoting greater independence and participation in society. Consequently, while AI holds transformative potential in advancing equitable and inclusive healthcare for people with disabilities, addressing ethical challenges, overcoming limitations, and fostering user-centred design are essential to fully realise its benefits and ensure these innovations promote autonomy, accessibility, and well-being.

EQUAL AI: A Framework for Enhancing Equity, Quality, Understanding and Accessibility in Liberal Arts through AI for Multilingual Learners

The integration of artificial intelligence (AI) into liberal arts education offers a transformative opportunity to address the diverse needs of multilingual and multicultural learners. Consequently, this study introduces the EQUAL AI framework (Enhancing Equity, Quality, Understanding, and Accessibility in Liberal Arts through AI), a structured approach to utilizing AI to foster inclusion and innovation in liberal arts pedagogy. The framework identifies five key domains: linguistic support, cultural representation, creative expression, critical thinking, and collaborative learning. Additionally, the study underscores the necessity of systemic support, particularly through professional development programs that equip educators with technical proficiency, ethical awareness, and the ability to critically assess AI tools. By tackling challenges such as algorithmic bias, data privacy, and the digital divide, the study advocates for culturally responsive policies and inclusive practices. The EQUAL AI framework envisions liberal arts education as a space for equitable participation and cultural understanding, positioning AI as a tool to enhance rather than replace humanistic pedagogy, ensuring its relevance in a technology-driven, interconnected world.

Internet of things (IoT) for safety and efficiency in construction building site operations

Internet of Things (IoT) technologies present transformative opportunities through connectivity of intelligent devices, environmental sensors, and integrated management systems. This study aims to investigate the benefits and impact of IoT implementation on construction sites by analyzing relationships between key factors and outcomes for safety and efficiency. Hypotheses were developed proposing positive correlations between each factor and effective IoT adoption on construction sites. Structural equation modeling analysis on survey data from construction professionals and site reports strongly validated the research hypotheses. Positive path coefficients and high statistical significance confirmed environmental monitoring (0.38), equipment management (0.343), predictive analytics and maintenance (0.222) and safety monitoring (0.369) as crucial enablers for successful IoT integration leading to safer and more productive construction operations. The findings highlight imperative focus areas and provide actionable insights for construction stakeholders on strategies to effectively leverage IoT capabilities.

Art Education in the Age of Crises: Opportunities for Hope and Transformation

The culture of post-industrial societies has proven unsustainable in many ways: climate change, overconsumption of natural resources, violent conflicts, and social inequality create a looming dystopia that leaves people hopeless and without a vision for the future. Amid complex eco-social crises, it is essential to consider the role of art education as an educational and societal resource. Art education is not isolated from other sectors of society but is always connected to broader cultural and political contexts. In other words, art education can never be neutral; it either strengthens or challenges and reshapes the values and practices prevailing in society through its choices. This thematic issue, Art and a Hopeful Future, brings together studies presented in the Arts Education Special Interest Group at the 2023 FERA (Finnish Educational Research Association) Conference, focusing on the significance of art education as a builder of hope for the future.

Industrial Policy and Green Growth in a Small Island Economy: The Case of Singapore

Industrial Policy and Green Growth in a Small Island Economy: The Case of Singapore

Are They Ready to Teach? Generative AI as a Means to Uncover Pre-Service Science Teachers’ PCK and Enhance Their Preparation Program

AbstractIntegrating generative artificial intelligence (GenAI) in pre-service teachers’ education programs offers a transformative opportunity to enhance the pedagogical development of future science educators. This conceptual paper suggests applying the GenAI tool to evaluate pedagogical content knowledge (PCK) among pre-service science teachers. By holding interactive dialogues with GenAI, pre-service teachers engage in lesson planning in a way that reveals their understanding of content, pedagogy, and PCK while facilitating the practical application of theoretical knowledge. Interpretation of these interactions provides insights into teachers-to-be knowledge and skills, enabling personalized learning experiences and targeted program adjustments. The paper underscores the need to equip pre-service teachers with the necessary competencies to utilize GenAI effectively in their future teaching practices. It contributes to the ongoing discourse on technology’s role in teacher preparation programs, highlighting the potential of addressing existing challenges in evaluating and developing teacher knowledge via GenAI. The suggested future research directions aim to further investigate the GenAI usage implications in educational contexts.

ARTIFICIAL INTELLIGENCE IN THE CLASSROOM: THE FUTURE OF EDUCATION

In the wake of the digital revolution, the integration of emerging technologies in education has emerged as a powerful catalyst for promoting inclusion and breaking down barriers in education. This study investigates the transformative impact of technology on inclusive education, exploring how innovations such as artificial intelligence, virtual and augmented reality, and assistive technologies are redefining learning possibilities for all students. We adopt a qualitative methodology, based on a systematic literature review, to critically analyze the current state of technology integration in inclusive education. Our findings reveal that, when implemented effectively, these technologies have the potential to personalize learning on an unprecedented scale, adapt to individual student needs, and overcome physical, cognitive, and geographic barriers. We identify significant challenges, including the need for ongoing training of educators, issues of equity in access to technology, and concerns about privacy and data security. The study also highlights the importance of a holistic approach that considers not only the technical, but also the pedagogical, ethical, and social aspects of technology implementation. We conclude that while technology offers transformative opportunities for inclusive education, its success depends on careful and contextualized integration, supported by progressive education policies and an ongoing commitment to equity and inclusion.

Exploring the Impacts of Automation on Employment: A Qualitative Study on Machine Learning and the Future of Work

Rapid advancements in automation and machine learning technologies are transforming labor, posing advantages and challenges for jobs across all industries. In light of increased concerns about job displacement and the need for worker adaptation, this study aims to understand the multifaceted consequences of automation on employment dynamics. The purpose of this study is to investigate the qualitative effects of automation on employment, with an emphasis on how companies and workers respond to these changes. The study aims to shed light on the perspectives of those affected by automation by investigating productivity, job displacement, transformation, and governmental responses. To ensure that the benefits of automation are distributed equitably, the study addresses the critical question of how to safeguard those who face job loss. The theoretical framework of the study anaphases the interaction between labor market dynamics and technological innovation. A qualitative research methodology based on secondary data gathering is used in this study to investigate recent literature on automation and employment. The collection encompasses a diverse range of sources offering varying perspectives on automation's consequences. Key findings demonstrate that while automation poses a significant risk of job displacement, it also brings opportunities for work transformation and productivity increases. However, disparities in upskilling and support networks for workers could exacerbate inequality. Reliance on secondary data, which may not accurately reflect regional differences or individual experiences, is one of the shortcomings of the study. To completely understand worker experiences in automated systems, additional qualitative research is required, according to theoretical implications. The findings highlight the importance of targeted legislative initiatives and collaborative efforts between stakeholders to create a more equitable labor market that supports all workers' adaptation to technology innovations from a practical perspective.

Optimizing Engineering Processes with Big Data and Machine Learning in Smart Engineering

The integration of Big Data and Machine Learning (ML) in modern engineering presents transformative opportunities for enhancing operational efficiency, optimizing performance, and ensuring sustainability across various industries. As industries evolve towards more complex systems and higher demands, traditional engineering processes are often hindered by inefficiencies and high operational costs. This paper explores the intersection of Big Data and ML, highlighting their role in revolutionizing engineering practices through data-driven insights and intelligent decision-making. Big Data, characterized by its vast volume, variety, velocity, and veracity, is harnessed to optimize manufacturing, predictive maintenance, quality control, and real-time decision-making. ML, a subset of artificial intelligence, enables systems to learn from data, improving predictive capabilities and uncovering hidden patterns in large datasets. The convergence of these technologies gives rise to "Smart Engineering," offering significant potential for increased automation, enhanced decision-making, and improved sustainability across sectors such as manufacturing, energy, automotive, and civil engineering. However, challenges remain in terms of data management, infrastructure requirements, and workforce readiness, particularly for smaller organizations with limited resources. This systematic review synthesizes existing literature to examine the applications, integration, challenges, and future opportunities of Big Data and ML in engineering, providing insights that can guide industry stakeholders in navigating the complexities of implementing these technologies for optimized performance and sustainable growth.

Conceptualizing Agrifood Systems for a Healthy, Sustainable, and Just Transformation: A Systematic Scoping Review

Human and planetary health are interconnected through food and agriculture. Food production and consumption patterns continue to drive the global burden of malnutrition, diet-related disease, climate change, and environmental degradation. There is an urgent need to identify pathways for transforming agrifood systems to be increasingly healthy, sustainable, and just, but conceptual frameworks necessary for visualizing these complex relationships are limited. This systematic scoping review identified existing frameworks for analyzing human and environmental outcomes of agrifood systems and evaluated their inclusion of policy and governance. Frameworks have evolved to increasingly consider the food supply chain activities and actors, the drivers that shape them, and the outcomes of these interactions. The findings of the review were used to develop a conceptual framework specific to modern industrialized agrifood systems where policy landscape is an explicit component. The framework is tailored to researchers and policymakers with the intention of providing a foundation for analyzing and communicating agrifood system issues, including identifying facilitators and barriers to effective policy, places to intervene in the system, and windows of opportunity for successful transformation.