bluuebunny/crossref_metadata_2025 huggingface dataset:
A Practical Guideline for Addressing Data Trustworthiness in Qualitative Research
Authors: Kocaman Rıdvan
Published: December 2024

Qualitative research explores people's feelings, perceptions, and meaning-making processes. Therefore, researchers will document real experiences, resulting in a comprehensive understanding of occurrences. Thus, it is crucial to ensure the trustworthiness of the qualitative results, which convinces readers that the research is worthy of attention. However, qualitative research is subjective, making a feeling of trustworthiness more challenging to achieve than quantitative research. Accordingly, this chapter offers multiple strategies that consider the practical requirements and theoretical underpinnings required to ensure the trustworthiness of qualitative research. To do this, four criteria commonly employed for evaluating the caliber of qualitative research were utilized, and concerns regarding each criterion that must be addressed were identified. The chapter offers insight to help methodology instructors, doctoral supervisors, and qualitative researchers refresh prior knowledge, catch up on what they may have missed, and adapt it directly to their research settings.
Ensuring Trustworthiness in Qualitative Research
Authors: Marlina Ekawati , Purwaningsih Mardiana , Siagian Al Hafiz Akbar Maulana , Al Hakim Shidiq , Maryati Ira
Published: December 2024

One of the characteristics of qualitative research is clarifying ambiguity and discovering various realities, so the data collection method is often through unstructured interviews, in-depth interviews, and direct observation of people, places, and phenomena. This condition ensures that qualitative research always asks questions about providing the data's reliability and validity. Triangulation is an approach to increase the depth of data collected, reduce bias, and increase validity and credibility. Triangulation uses multiple techniques, including the triangulation of data sources, methods, investigators, and theories. A literature review is conducted to investigate triangulation in various research disciplines. The different forms of triangulation and their applications are then thoroughly examined. In particular, doctorate students should gain a grasp of triangulation procedures in qualitative research from this work. Therefore, this study offers valuable insights for researchers who wish to enhance their research's validity, transferability, confirmability, and dependability.
Tackling the Thorny Issue of Positionality in Participatory Action Research
Authors: Chakabwata William
Published: December 2024

The chapter explores the central place of positionality in Participatory Action Research (PAR). A background of the PAR is highlighted. The concepts of positionality in the context of interpretive research is explored. The chapter shows that reflection and reflexivity are intended to enhance the validity of interpretive research in general and in PAR in particular. The binary approach to research as epitomised by Outsider/Insider approach, which is located in a western perspective of doing research is interrogated using the intersectional, standpoint and embodiment theories. Finally, the chapter concluded that although positionality as manifested by reflexivity is vital, it must be conducted within the context of postmodern theory as opposed to modernism, by underscoring the multivocal nature of PAR.
Foucauldian Genealogy as Qualitative Research Method
Authors: Kumar Tiwari Pavan , Roy Bimal Chandra
Published: December 2024

Foucauldian genealogy, with its potential to inspire critical and creative thinking, provides a framework to expose power-knowledge constellations, often inherent in techno-scientific discourses perceived as apolitical and ahistorical. By invoking the question of whether Foucauldian genealogy is a method or methodology, this study unearths existing literature on Foucauldian genealogy to bring forth its epistemological postures. It argues that Foucauldian genealogy could not be binarized into the exclusivity of method or methodology. While it possesses methodological rhythms, it also allows for utilising theoretical tools available in genealogy and could also act as a method. For instance, in the field of history, genealogy can be used to trace the evolution of power structures, while in the field of sociology, it can be used to understand the formation of social norms. In the spirit of methodological pragmatism employed by Foucault, genealogy could be strategically employed by scholars of various disciplines, empowering them to think critically and creatively in their research.
Qualitative Instrumentation Field Tests and Expert Panel Reviews
Authors: Singha Ranjit , Yogesh Kanna S.
Published: December 2024

This chapter explores the essential methodologies of qualitative instrumentation field tests and expert panel reviews in dissertation research. It outlines the definitions and roles of qualitative instruments, the planning and execution of field tests, and the analysis of field test data. The chapter also covers organizing and analyzing expert panel reviews, synthesizing feedback, face validation and refining instruments. Highlighting the importance of these methodologies demonstrates how field tests provide practical insights, and expert reviews offer theoretical critique, ensuring the reliability and validity of research tools. The expert's validation of the Multidimensional Addiction Behaviour Scale (MABS) demonstrated the importance of experts' input in refining measurement tools. Removing certain items and dimensions and restructuring the items for scale improved focus and effectiveness, highlighting the need for iterative refinement and ongoing validation in addiction research. This chapter equips dissertation students with essential methodologies for validating research.
Moving Beyond Traditional Multiculturalism
Authors: Becton Alicia , Han Eunae , Ong Leeza , Johnson Amber , Chen Roy K. , Rangel Gabriela , Lusk Stephanie
Published: December 2024

This chapter explores the experiences of individuals with disabilities, emphasizing how they navigate educational and societal norms while balancing various identities. It emphasizes the impact of societal issues, such as racism and sexism, on individuals with disabilities. The authors delve into current multiculturalism trends, advocating for culturally responsive approaches in counselor education and rehabilitation services. The goal is to advance discussions on the future directions of multiculturalism by exploring the following key areas (a) the sociopolitical aspects of disability, (b) the inclusion of disability in counselor education, (c) accessibility and the universal design for learning (UDL), (d) culturally competent counselor education curriculum and pedagogy, and (e) implications for practice. Concepts such as intersectionality, disability, and critical race theory (DisCrit) will be examined to provide tools needed to address the complex challenges that hinder adequate service provision and counselor preparation.
Opportunities and Challenges of Leveraging Artificial Intelligence (AI) in Sport Marketing
Authors: Mohammadi Sardar , Pashaie Sajjad , Ghaffarisadr Seyyed Iman , Rayner Mike
Published: December 2024

As digital technologies continue to evolve and consumer behavior shifts, AI has become a critical tool for enhancing marketing strategies in the highly competitive sports industry. The use of artificial intelligence (AI) in sports marketing as an important innovation brings many opportunities and challenges. The emergence of AI as an effective tool in sports marketing allows for more detailed analysis of fan behavior and the creation of personalized strategies. Various AI technologies, including machine learning (ML), natural language processing (NLP), and computer vision (CV), are introduced and real-world examples of their applications in sports marketing are presented. These opportunities include personalized engagement with fans, data-driven strategies for personalization and optimization of revenue streams through predictive analytics. In this chapter, the current state of sports marketing as well as the successful implementation of AI in sports marketing are reviewed.
Enhancing Scientific Rigor With Editorial Roles and AI
Authors: Papadopoulou Paraskevi , Lytras Miltiadis D.
Published: December 2024

In the evolving landscape of open-access scientific journals, the roles of editors and reviewers are crucial in ensuring quality and integrity. This chapter analyzes the experiences of two college professors—a cell biologist/biophysicist and a computer scientist—who, in addition to various fields of study, have edited and reviewed over 50 high-impact journal manuscripts related to digital health (DH) and precision/personalized medicine (PM). Their journey underscores the importance of multi-disciplinary approaches and artificial intelligence (AI) in evaluating complex research. The chapter highlights specific cases of DH and PM illustrating how digital solutions and AI have shaped their perspectives. Key elements of robust manuscript evaluation, such as methodological rigor and clinical relevance, are discussed. The chapter explores the emerging role of AI in enhancing the editorial process, from initial screening to detailed analysis. The findings advocate for active participation in peer review and editorial roles, emphasizing their benefits.
Caring for the Carers
Authors: Yadav Saloni , Kaur Jaspreet
Published: December 2024

The integration of artificial intelligence (AI) in healthcare operations and management presents a transformative opportunity to support and alleviate the burden on healthcare providers, commonly referred to as carers. This chapter explores the multifaceted role of AI in enhancing the efficiency, effectiveness, and quality of healthcare services while prioritizing the well-being of healthcare professionals. By automating routine tasks, optimizing resource allocation, and facilitating data-driven decision-making, AI enables carers to focus more on patient care and less on administrative duties. Furthermore, AI-powered predictive analytics and personalized care algorithms empower carers to deliver proactive and individualized treatments, thereby improving patient outcomes and satisfaction.
Pioneering the Future of Mental Health With AI
Authors: Mehta Pradnya
Published: December 2024

This research delves into the potential of AI to revolutionize the delivery, diagnosis, and treatment of mental health care. By leveraging machine learning algorithms, vast amounts of data can be analyzed to identify patterns and provide personalized interventions, thereby enhancing diagnostic accuracy and treatment efficiency. AI-powered virtual assistants and chatbots offer accessible and scalable mental health support. Furthermore, technologies like natural language processing and mood analysis enable early detection and treatment monitoring. It is crucial to consider ethical issues, privacy concerns, and the appropriate use of AI, necessitating collaboration among AI researchers, mental health professionals, and policymakers to establish robust regulations. Additionally, addressing data access and diversity gaps is essential for the development of fair AI systems. Integrating AI with emerging technologies, such as wearables and neuroimaging, holds the potential to provide new insights and tailored treatments.
Economic Contributions and Social Impacts of Women Rural Entrepreneurs
Authors: Velmurugan R. , Bhuvaneswari R. , Senthilkumar S.
Published: December 2024

Rural women entrepreneurs are driving economic growth (jobs, diversified economies) and social progress (gender equality, empowered communities) through ventures in agriculture, handicrafts, and more. Despite challenges like limited access to finance and infrastructure, this proposal advocates for their support through tailored financial products, capacity building programs, infrastructure improvements, and gender-sensitive policies. By empowering these women, the authors unlock a path to sustainable and inclusive development for all.
Effects of Employee Performance on the Implementation of Total Quality Management (TQM) Tools
Authors: Rahman Nur Aqilah Adilah Hj Abd , Susanto Heru
Published: December 2024

Implementation of TQM enhances employee performance. This study seeks to examine the impact of employee performance on the application of TQM tools, focusing on the experiences of working mothers in public and private sectors. The labor force statistics do not provide a specific percentage of working mothers. Working mothers encounter challenges from workplace, organization, family, colleagues, as well as society. This chapter utilized quantitative studies. Questionnaires were distributed to 300 working mothers. The questionnaires were organized into five primary sections: demographic information, total quality management, job satisfaction, policy management, and performance evaluation. The subsections are organized into five distinct policies: breastfeeding-friendly, maternity, paternity, support, and work flexibility. The findings indicate that policies are not implemented correctly. If implemented effectively, mothers would experience enhanced performance, improved mental health, a positive environment, and a more manageable balance between caring for their child and work.
Empowering Her Voice
Authors: Dehankar Pooja , Das Susanta
Published: December 2024

The chapter explores women's increasing involvement in decision-making across various domains. It highlights persistent obstacles like institutional weaknesses and cultural norms hindering women's advancement. Gender diversity in decision-making is shown to enhance organizational performance and innovation. The importance of tearing down institutional barriers and implementing policies to support women in leadership roles is emphasized. Success stories and initiatives promoting inclusivity are discussed, alongside the transformative power of diverse perspectives in decision-making. Organizational policies, education, and mentoring are identified as key factors in advancing women's roles. It stresses the need for ongoing activism, policy changes, and cultural shifts to secure fairer distribution of leadership roles. It concludes by emphasizing the necessity of women's participation in decision-making for inclusive and efficient governance, advocating for the recognition and support of women's involvement to improve societal outcomes.
Social Entrepreneurship in Himalayas
Authors: Kumar Narendra , Sharma Swati
Published: December 2024

This chapter explores the impact of social entrepreneurship in the Himalayan region, focusing specifically on the Ladakhi Women's Travel Company (LWTC), a pioneering organization in Ladakh, India, dedicated to promoting sustainable tourism while empowering local women. The study examines the socio-economic and cultural challenges faced by the women of Ladakh and how LWTC addresses these through its innovative business model. Through qualitative analysis and case study methodology, this chapter highlights the successes and challenges of LWTC, offering insights into the broader implications of social entrepreneurship in remote and marginalized communities. The findings suggest that social enterprises like LWTC can play a crucial role in achieving sustainable development goals, particularly in regions with limited access to mainstream economic opportunities. This study contributes to the growing body of literature on social entrepreneurship by providing a detailed account of how a localized, women-led initiative can drive socio-economic transformation in the Himalayas.
The Intricacies of Women's Involvement in Rural Family Businesses
Authors: Venugopal Koppala , Sharma Astha
Published: December 2024

The aim of this study was to investigate factors influencing women's participation in rural family businesses in Srikakulam district, Andhra Pradesh, employing a descriptive design with mixed methods. Primary data was gathered through a convenience sampling approach using a cross-sectional survey method, utilizing a 5-Scale Likert questionnaire. Machine learning techniques including classification, clustering, PCA, and rank analysis were applied for comprehensive data analysis. Results highlighted significant influences such as gender roles, family support, financial constraints, cultural norms, and health issues affecting women's absenteeism in business activities. Based on these findings, recommendations include fostering supportive policies, enhancing financial accessibility, challenging cultural stereotypes, and promoting health awareness among rural women entrepreneurs. Addressing these factors can potentially enhance women's involvement and mitigate absenteeism, contributing to the economic empowerment and sustainable development of rural communities.
Thriving Amidst Challenges
Authors: John Geemol , Wani Mohammad Amin
Published: December 2024

The emergence of female entrepreneurs in rural India symbolizes a paradigm shift in the economic landscape, with women being recognized as important vehicles of innovation, creation of employment, and economic growth in general. This chapter overviews the revolutionary impact of entrepreneurship in strengthening rural women, illustrating insights from secondary data like academic literature and online sources. It emphasizes intergenerational connections, work-life balance, and family support, all of which are critical in forming women's business experiences. Additionally, this chapter also overviews the particular difficulties that midlife crisis brings about, which cause middle-aged female entrepreneurs to reflect and reevaluate their priorities and ambitions. Rural women sail through these obstacles with the help of resilience which is the capability to bounce back and prosper in the face of difficulty and entrepreneurship as a means of achieving personal development and making a positive impact on the community.
Advanced Technology for Water Treatment and Purifications
Authors: Das Himadri Sekhar
Published: December 2024

Advanced water treatment and purification technologies play a crucial role in providing clean and sustainable water. Innovations such as membrane filtration, advanced oxidation processes (AOPs), and nanotechnology have significantly improved the removal of contaminants, including pathogens and emerging pollutants. Electrochemical methods and bio-filtration systems enhance energy efficiency, while reducing the need for chemicals, making them more eco-friendly. The integration of smart sensors allows for real-time monitoring and optimization of treatment processes. These advancements are essential for addressing growing water demands and ensuring safe, reliable water supplies in an increasingly resource-constrained world.
Digital Water Transformation
Authors: Moussaoui Mohamed , Rachid Ali , Rajpoot Subhadra
Published: December 2024

Water is increasingly becoming a valuable and scarce resource. Population growth has significantly driven up demand, leading to the over-exploitation of water across domestic, agricultural, commercial, and industrial sectors. This excessive consumption, compounded by the effects of climate change and pollution, jeopardizes the long-term sustainability of our environment. To address these challenges, it is essential to fundamentally rethink traditional approaches to water management, treatment, and conservation.his chapter explores the transformative potential of digital technologies in water management, particularly within the emerging framework of Water 4.0. It examines key innovations such as cyber-physical systems (CPS), the Internet of Things (IoT), artificial intelligence (AI), digital twins, big data analytics, advanced leak detection, geographic information systems (GIS), and automation, all of which are reshaping water management practices. These technologies enhance monitoring capabilities, provide predictive insights, and enable real-time data analysis, thereby improving system efficiency, reducing water losses, and supporting informed decision-making. The chapter also discusses the challenges and risks associated with the integration of digital technologies, including cybersecurity vulnerabilities, concerns over data privacy, and the necessity for robust regulatory frameworks. Finally, it outlines future research directions and advancements in digital water management, highlighting the importance of continued innovation for sustainable water use.
Water Governance and Management in Morocco
Authors: Rachid Ali , Moussaoui Mohamed
Published: December 2024

According to the UN, by 2030, water demand will have exceeded global production by 40%. Forecasts for Morocco estimate that 80% of its water resources will be lost over the next 25 years. According to the HCP (2020), the potential of Morocco's natural water resources is estimated at 22 billion m3. According to current estimates, the average per capita supply of fresh water per year currently does not exceed 650 m3. Depending on the uncertainties related to the water issue, Morocco has set up an institutional and legislative governance mechanism! However, these structures lack financial means and human resources. This chapter will attempt to take stock of the water situation in Morocco by examining the available sources, the pressures exerted and will question the policies and mechanisms of water governance and management, Finally, the chapter will propose solutions and future opportunities for a better sustainable and competitive governance of water resources.
Applications of Artificial Intelligence in Education
Authors: Aravindh K. , Singh Brijendra
Published: December 2024

This chapter explores the transformative impact of artificial intelligence (AI) on the education sector, highlighting how AI technologies enhance teaching quality, streamline assessment processes, and support both physical and virtual learning environments. By facilitating innovative methods of lecture delivery and interactive learning, AI tools benefit educators and students alike, enabling a more engaging and efficient educational experience. The chapter provides a comprehensive review of various AI techniques and methodologies used within educational contexts, illustrating practical applications that support personalized learning, efficient evaluations, and adaptive teaching strategies. Additionally, it examines the benefits and challenges of AI from the perspectives of both educators and students, shedding light on the potential improvements AI can bring to learning outcomes. Future directions and opportunities for AI in education are also discussed, offering insights into the next steps for integrating AI into educational systems for enhanced adaptability and impact.
Exploring the Potentiality of Artificial Intelligence in the Higher Education System
Authors: Ansary Mazhar Shamsi , Mahato Indrajit , Mahanti Jayashree , Gorai Nupur , Behera Santosh Kumar
Published: December 2024

This chapter investigates undergraduate students' perceptions of the potential of artificial intelligence (AI) in higher education. Using a descriptive survey method, data were collected from 322 undergraduate students in West Bengal through random sampling and analyzed using perception scales. Additionally, unstructured interviews were conducted to explore the reasons behind low levels of perception. The study employed Mean, Standard Deviation, Kruskal-Wallis test, Mann-Whitney U test, post-hoc analysis, and percentage calculations to analyze data and test hypotheses. Findings indicate that students generally have a moderate perception of AI's potential in higher education, with significant variation observed across academic streams (Arts, Science, and Commerce) but no notable differences based on gender, caste, location, or semester. The study also uncovers factors contributing to the low perception levels among undergraduates regarding AI's role in higher education.
Generative Artificial Intelligence and the 4C Learning Skills for the 21st Century
Authors: Türker Pınar Mıhcı , Öztürk Mücahit
Published: December 2024

This chapter explores the relationship between generative artificial intelligence (AI) and the 21st-century 4C learning skills: critical thinking, creativity, collaboration, and communication. This chapter provides an overview of the core characteristics of these skills and examines research on how generative AI influences their development. Generative AI presents significant opportunities to foster 4C learning skills by stimulating students' thought processes, encouraging critical perspectives on problems, and enabling innovative solutions. Additionally, generative AI-supported platforms can enhance student communication and facilitate collaborative work. While generative AI offers transformative potential, a balanced and cautious approach is recommended to ensure it best serves students' educational interests.
Identifying the Applications of Artificial Intelligence in Educational Entrepreneurship Development
Authors: Zolfaghari Mahnaz , Salamzadeh Aidin , Afsharpour Omid
Published: December 2024

In the rapidly evolving fields of education, entrepreneurship, and artificial intelligence, understanding the applications of AI in educational entrepreneurship is essential. This chapter adopts an applied research approach, using qualitative methods such as a systematic literature review and semi-structured interviews with 14 experts from education, entrepreneurship, and AI. Through thematic analysis, 1830 initial themes were distilled into 42 first-level themes, categorized into 20 second-level themes, and ultimately consolidated into three overarching themes. These global themes reveal AI's impact on enhancing learning productivity, streamlining instructional methods, and advancing educational administration and leadership. The findings underscore AI's transformative potential in educational entrepreneurship, providing a comprehensive framework highlighting AI's diverse contributions to the education system.
AI-Based Deep Memory Alex Neural Network for Early Detection of Forest and Land Fires
Authors: Kirubanantham P. , Saranya A. , Bibin Christopher V. , Prakash B. , Anand M.  Suresh
Published: December 2024

In recent years, the National Institute of Aeronautics and Space (LAPAN) has used hotspot data derived from satellite imagery to identify and detect forest and land fires at an early stage. Hotspot data has greatly facilitated firefighting operations and enhanced enforcement activities. Nevertheless, the system has certain limitations, mostly stemming from its incapacity to differentiate between forest and land fires and other sources of heat or fires produced by typical human actions. In addition, this approach requires time-consuming verification and significantly depends on human elements for sophisticated analysis and validation. Lately, the field of deep learning has been implementing a novel strategy by making progress in the field of artificial intelligence. The algorithm has been trained to identify burnt areas by analyzing satellite images recorded between 2017 and 2019. It recognizes the pattern and tone of the image in these areas. To validate the presence of burnt areas, it compares the current imagery from the past week with the historical Sentinel-2 imagery for each cluster, specifically for forest and land fire identification. Initially, the satellite images are obtained and the noise is eliminated using a median Butterworth filter. Next, the characteristics of the area of interest may be grouped using a K-density-based agglomerative method. The hotspot may now be accurately detected utilizing the advanced deep memory Alex neural network. The outcomes of the hotspot identification procedure, which has an accuracy rate of 99.7%, may aid firefighters in promptly extinguishing flames and help law enforcement authorities in identifying the optimal target area. Hence, the recommended technology has the potential to enhance the efficacy and productivity of resources assigned by law enforcement agents, resulting in improved and more prompt public services.
Leveraging AI for Real-Time Environmental Monitoring
Authors: Mobo Froilan Delute , Garcia Ana Liza Reclozado , Miłek Katarzyna
Published: December 2024

Artificial Intelligence (AI) is transforming environmental monitoring by offering real-time, data-driven insights that can address critical ecological challenges such as deforestation, pollution, and biodiversity loss. Traditional methods, which rely on manual surveys and slow data collection processes, have proven inadequate for the fast-paced environmental crises of today. By leveraging AI tools such as machine learning (ML), deep learning (DL), computer vision (CV), and natural language processing (NLP), environmental data can now be collected, analyzed, and acted upon in real-time. AI-driven innovations enable more accurate forecasting models, enhanced data collection through IoT sensor networks, and real-time decision-making in fields like precision agriculture, climate change mitigation, and wildlife conservation. This paper explores how AI-driven systems are revolutionizing environmental management by providing timely, actionable insights that support sustainability and ecological preservation.
Impact of Credit Card Incentives on Usage Pattern
Authors: Chaturvedi Ankita , Yadav Neha , Gnanendra M. , Kumar A. V. Senthil
Published: December 2024

This study examines the influence of credit card incentives on usage patterns, specifically credit card transactions and transaction purposes, utilizing Structural Equation Modeling (SEM). It explores the historical evolution of credit cards, operational procedures, and security measures like the Card Verification Method (CVM). With a focus on India's burgeoning credit card industry, the research aims to comprehend consumer behavior and associated challenges. Employing a mixed-methods approach and Smart PLS software, the study seeks to provide detailed insights into credit card dynamics, offering practical recommendations for policymakers, financial institutions, and consumers. Through meticulous analysis, the research confirms the reliability of the measurement model, emphasizing the importance of discriminant validity and balancing rigor with practicality in model establishment.
Improving Interior Design Quality Evaluation With Advanced Cross-Entropy Technique in Triangular Fuzzy Neutrosophic Multiple-Attribute Decision-Making
Authors: Yang Lei , Chen Gang
Published: December 2024

Society is constantly developing, and people's economic level is also constantly improving. The quality of life and requirements are also increasing, and the quality of living environment is becoming more stringent. The interior design quality evaluation is viewed as the MADM. In this work, the triangular fuzzy neutrosophic number cross-entropy (TFNN-CE) technique is constructed in line with cross-entropy and triangular fuzzy neutrosophic sets (TFNSs). Then, the TFNN-CE technique is constructed to solve the MADM. Finally, a numerical example for interior design quality evaluation is constructed and serval comparisons are constructed to illustrate the advantages of put forward technique. The key contribution of this study is constructed: (1) the TFNN-CE model is put forward under TFNSs; (2) the TFNN-CE model is put forward for MADM under TFNSs; (3) the TFNN-CE model for interior design quality evaluation is put forward; (4) through employing serval comparisons, it is put forward that TFNN-CE model is effective for interior design quality evaluation.
Conhecimentos e atividades para potencializar o cálculo mental
Authors: Berticelli Danilene  Gullich Donin , Zancan Sabrina
Published: December 2024

O cálculo mental é essencial no desenvolvimento de estratégias para a solução das quatro operações, fundamentais para a Matemática. Diversos autores destacam-se por apresentar estratégias de cálculo mental, como Backheuser (1933), Albuquerque (1951), Beishuizen (1993), Parra (1996), Thompson (1999a), Threlfall (2002), Boaler (2020). Por meio de uma pesquisa bibliográfica, analisamos as estratégias sugeridas por estes autores e notamos que alguns as denominam, enquanto outros detém-se a exemplos, ambos com intenção de levar o leitor a compreendê-las. Porém, apresentar uma estratégia e nominá-la não é suficiente para que o indivíduo possa compreendê-la e utilizá-la para, posteriormente, poder ensinar. É imprescindível reconhecer quais os conhecimentos necessários para acionar uma estratégia. Nesse artigo nos propomos a analisar as estratégias de cálculo mental descritas por estes autores e elencar os conhecimentos necessários a cada uma delas, de modo a compreender o que é preciso saber para formular uma estratégia. A partir da análise, elencamos quatro grupos de conhecimentos essenciais para o desenvolvimento do cálculo mental: Fatos básicos, Decomposição, Dobros e Rede de relações numéricas do 10. Para além disso, apresentamos sugestões de atividades que podem ser ampliadas e aplicadas em sala de aula, a fim de auxiliar professores a construírem com seus alunos conhecimentos e estratégias, possibilitando o desenvolvimento do cálculo mental. Nossa pesquisa indica que, antes de apresentar uma estratégia, é necessário trabalhar os conhecimentos que embasam a mesma, caso contrário, torna-se difícil realizar cálculos mentais.
Escola normal secundária ‘Leonel Franca’ de Paranavaí (1956-1974): a formação feminina para a docência
Authors: Silva Sthefany Matheus da , Stentzler Márcia Marlene
Published: December 2024

Neste artigo analisamos a criação da Escola Normal Secundária ‘Leonel Franca’ de Paranavaí, estado do Paraná e a inserção socioeducacional de mulheres a partir da formação para a docência promovida pela escola. Essa Escola foi referência na formação de professores e na educação feminina para Paranavaí e região, entre 1956 e 1974, quando formou a última turma. A pesquisa foi organizada com suporte teórico em fontes documentais, localizadas no arquivo da escola e em arquivos particulares; em notícias veiculadas pelo periódico Diário do Noroeste (1971) e em memórias da escola, publicadas por Bana (2013). Ex-alunas e ex-professora responderam a um questionário acerca de suas experiências, evidenciando representações sobre a escola. Dialogamos também com bibliografia específica sobre a história da educação e da mulher, evidenciando que essa Escola Normal, criada poucos anos após a emancipação de Paranavaí, foi extremamente valorizada por quem nela estudou e pela comunidade na região noroeste do Paraná.
Analysis of the mother-father relations of adolescents who stayed at home during the pandemia process
Authors: Çelik Melike Yavaş , Ayar Duygu
Published: December 2024

This research has been planned in a descriptive way to examine the mother-father relationships of adolescents during the pandemic process. The data were collected with Personal Information Form and Adolescent-Mother, Father Relationship Inventory. T test, (ANOVA), Kruskal Wallis and Mann Whitney U test were used for analysis. The score average of the Mother, Father Relations Inventory filled out by adolescents for their mothers was 120.89 ± 21.68, and the average score of the Mother, Father Relations Inventory filled out by adolescents for their fathers was 136.65 ± 36.74. It was determined that the Adolescent-Mother, Father Relations Inventory scores for the mothers and fathers were statistically significant in terms of variables such as the  mother-father relationship status before the pandemic, the effect of the pandemic on the  mother-father relations, and family attitudes (p < 0.05). During the pandemic process, adolescents' mother-father relationships are interrupted and there are problems in their mother-father relationships.
A marcação de gênero no português brasileiro como uma implicatura escalar
Authors: Bevilaqua Kayron
Published: December 2024

Neste artigo, investigamos o fenômeno da marcação de gênero no Português Brasileiro (PB), com o objetivo de compreender as contribuições semântica e pragmática do morfema -o nos sintagmas nominais designadores de indivíduos humanos. O tema é controverso, de um lado há teorias morfológicas estruturalistas que analisam o morfema -o como genérico, no sentido de não carregar traço de gênero. De outro, há movimentos e diversos setores da sociedade que afirmam que o morfema -o designa o gênero masculino e que é preciso buscar maior representatividade nas formas linguísticas. Nossa proposta busca construir uma ponte entre esses dois polos. A partir da metodologia experimental, buscamos conhecer e quantificar como os falantes nativos do PB interpretam os morfemas -o e -a em sintagmas nominais definidos designando referentes femininos. Os resultados apontaram uma oscilação para o morfema -o: ora é interpretado como masculino, ora é interpretado como genérico. Por outro lado, os resultados apontaram que o morfema -a designa exclusivamente referentes femininos. À luz da Pragmática Formal, analisamos tais resultados e concluímos que o par de morfemas -o/-a dispara uma implicatura escalar. Desse modo, por implicatura, o morfema -o acaba sendo interpretado como exclusivamente masculino e não como genérico, embora morfológica e semanticamente não carregue marca de gênero.
Novel Process Approach for Extrusion-Based Metal Wire Additive Manufacturing Using Induction Heating as a Heat Source
Authors: Choubey Rahul Kumar , Jain Prashant Kumar
Published: December 2024

A growing number of additive manufacturing (AM) applications use induction heating because of its precision, affordability, safety, and cleanliness. It is widely used in many industrial processes, such as melting, welding, brazing, and preheating. Wire is a considerably more efficient material to use than powder when used as feedstock. Unfortunately, there is still much to learn about the application of induction heating as a heat source in extrusion-based metal additive manufacturing, particularly when wire feedstock is used. This gap was filled by investigating, inhouse developed metal AM system which consists of the combination of induction heating as a heat source and metal wire as a feedstock in additive manufacturing. For this kind of application, induction heating is especially useful since it produces heat inside the workpiece by creating eddy currents. Finite element analysis was initially used to analyze the suitability of extruder material for printing aluminum material. After this investigation, the ability to print aluminum alloy in an extrusion-based metal wire additive manufacturing process with a cast iron extruder has been evaluated through experimentation. Simulation and experimentation results confirm the suitability of cast iron as an extruder material for printing aluminium alloys in a semi-solid state. The tensile test results of wire samples printed through induction heated metal additive manufacturing have been comparable to those of the original wire due to printing the same in a semi-solid state. Though they did not reach the levels attained by wire arc additive manufacturing and casting processes, it was found that the new extrusion-based wire samples showed better elongation and yield strength than the original wire.
Mechanical and Flow Properties of Virgin and Recycled Low-Density Polyethylene (LDPE) Blends Using Twin Screw Extrusion
Authors: Lim Cee Kee , Mohd Pisal Mohd Hanif , Lim Kean Chong , Baddrulsham Muhamad Nurfirdaus , Adorna Jr Joemer Absalon
Published: December 2024

The utilization of recycled materials in the production of plastic products is an environmentally conscious and economically viable approach. This study delves into the mechanical and flow properties of low-density polyethylene (LDPE) blends, comparing virgin low-density polyethylene (vLDPE), recycled low-density polyethylene (rLDPE) and vLDPE/rLDPE blends with different ratio (100/0, 75/25, 50/50, 25/75, 0/100) for the purpose of reprocess into variable high-quality end products with minimal modification. Mechanical properties, such as tensile strength, elongation at break, Young’s modulus, flexural strength, and flexural modulus, were examined to assess the suitability of rLDPE in comparison to its virgin counterpart. Our results demonstrate that vLDPE/rLDPE blend exhibits mechanical properties comparable to those of vLDPE, suggesting its potential as a sustainable alternative for reprocessing. Flow properties, specifically melt flow index (MFI), were also assessed to evaluate the processability of the LDPE blends. The findings reveal that the flow properties of LDPE blends are within an acceptable range for extrusion moulding, indicating that these materials can be effectively processed without major adjustments to manufacturing processes. This research underscores the feasibility of incorporating rLDPE into vLDPE for reprocessing into variable products, offering both economic and environmental advantages. By extending the lifecycle of LDPE materials through recycling, we can contribute to reducing waste and the overall environmental footprint while maintaining the desired mechanical and flow properties for high-quality end products.
The Effect of Polymer Amendment on the Colloidal Properties of a Waste K+- Rich Bentonite for Water-Based Drilling Fluid Applications
Authors: Ramsis Youstina , Sarris Ernestos , Papaloizou Loizos , Vattis Demetris
Published: December 2024

This research is concerned with the investigation of waste bentonite produced from a quarry in Cyprus, after being polymer-amended for use as a low-density solid additive in water-based drilling fluid systems (WBFS). According to API procedures, the waste bentonite samples are mechanically processed to a size < 63 μm and then activated with soda ash under “wet & thermal” conditions. The activated material is then used in the blending of actual WBF drilling fluid systems amended with polymers to obtain the desired colloidal properties because bentonite alone was not sufficient. For this procedure, three anionic polymers, Xanthan gum, CMC, and PAC-R were considered because they are very common as drilling fluid additives and under certain concentrations can help reach the desired colloidal properties of the WBFS. Results from this work show that minor polymer addition of all three polymers assists the waste material in reaching excellent filtration control qualifying the waste material according to API. Repurposing local waste clay material for drilling applications serves as a cost-effective solution leading to the management of local resources and aligning with environmental sustainability thus contributing to the circular economy principle.
Critical Care Clinicians’ Knowledge of Post–Intensive Care Syndrome
Authors: Lobos Patricia G. , Nairon Emerson B. , Denbow Maria , Olson DaiWai M. , Wilson Jennifer E.
Published: December 2024

Background

The term post–intensive care syndrome refers to a group of symptoms that commonly occur after intensive care unit discharge, leading to worsening physical or mental health. The incidence of this syndrome is increasing. Critical care clinicians can play a pivotal role in improving patient outcomes through knowledge of post–intensive care syndrome risk factors and symptoms.

Objective

To explore critical care clinicians’ current knowledge of post–intensive care syndrome as a basis for developing critical care educational interventions.

Methods

This quantitative, cross-sectional, observational pilot study was conducted to survey critical care physicians, nurses, nurse practitioners, and physician assistants at a university hospital on their knowledge of post–intensive care syndrome symptoms and risk factors and their confidence in their ability to recognize the condition.

Results

A total of 51 clinicians completed the survey. The overall levels of knowledge and confidence regarding post–intensive care syndrome risk factors and symptoms were low, with no significant differences found by clinician role.

Conclusions

These findings support the need for interprofessional education on post–intensive care syndrome risk factors and early identification of symptoms in the critical care setting.
Healthcare waste management knowledge, attitudes and practices of laboratory workers at a regional hospital, Lesotho
Authors: Siimane Ts’aletseng M. , Nts’ihlele Motlatsi E.
Published: December 2024

Background: Safe management of healthcare waste (HW) safeguards laboratory biosafety and biosecurity. Knowledge and attitudes influence HW practices, presenting a need for evidence of the current status.Objective: This study assessed the knowledge, attitudes and practice of laboratory workers towards waste management at a regional hospital laboratory in Lesotho.Methods: The study was conducted from March 2023 to June 2023 using a mixed-methods descriptive case study design. The entire population (n = 30) of technical and non-technical laboratory workers and generated waste were sampled. A structured questionnaire and an observational checklist were used to collect data. Waste generation was assessed by weighing and measuring waste volumes. Data were analysed using descriptive statistics.Results: All respondents (26/26; 100%) can define HW and (3/3) laboratory assistants (100%) gave correct responses for three questions, namely: risk associated with HW, waste container colour-coding, and disposal requirements. Knowledge on waste management responsibilities ranged between 0% (0/4) for cleaners and 54.5% (6/11) among laboratory technicians. Attitudes were mainly positive, and practices conformed in part to standard operating procedures. Infectious solid waste comprised 77% of solid HW, while 63% of chemical liquid waste emanated from the full blood count area.Conclusion: Knowledge exists among workers and attitudes are predominantly positive; however, some unsafe practices continue, thus knowledge is not fully translated to safe practices. Regular training and measuring and recording of HW were recommended.What this study adds: The study contributes understanding of the status of HW knowledge, attitudes and management practices, highlighting the need for compliance monitoring.
Improved cholera control in Kenya: A retrospective analysis of 2017–2019 in Nairobi and Homabay
Authors: Mercy Kyeng , Pokhariyal Ganesh , Fongwen Noah T. , Ndembi Nicaise , Kivuti-Bitok Lucy
Published: December 2024

Background: Kenya has recorded at least 38 678 cases and 695 deaths over the last decade, and costing on average $2.2 million annually. From 2014 to 2016, the country experienced one of the deadliest and largest outbreak. However, between 2017 and 2020, there was a decline in the number of reported cases and deaths.Aim: This study seeks to reveal the investments made post the 2014–2016 outbreak and highlight existing gaps that need to be addressed to stop the resurgence of cholera outbreaks in Kenya.Setting: The study was conducted in two counties: Homabay and Nairobi.Methods: We used an observational study. Data were collected from 20 health facilities (involved in cholera control, during the study), 9 key informant interviews (KII) and 6 focus group discussions (FGDs).Results: We found improvement such as: dissemination of standard operating procedures, aligned reporting system, field epidemiology programme, establishment of a public health emergency operating centre and improved partner coordination. On the other hand, 12 of the selected 20 (60%) facilities had no prior training before government financing and laboratory capacity was sub-optimal: 13 (65%) facilities had no prior training, 16 (20%) had no operational laboratory plan and 10 (50%) had inadequate laboratory test kits and reagents.Conclusion: This study highlights that Kenya has experienced an improvement in specific core capacities.Contribution: For Kenya to completely flatten the curve, there is need for more sustainable investment and government’s commitment in health system strengthening.
Publishing in the Journal of Public Health in Africa: Advancing research for future pandemics
Authors: Seddu Kumba , Ndembi Nicaise
Published: December 2024

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