bluuebunny/crossref_metadata_2025 huggingface dataset:
Fostering Antiracist Initiatives in Online School Counseling Graduate Programs
Authors: Harrison Ariel
Published: December 2024

In online school counseling programs, school counselor educators and supervisors (SCESs) are responsible for educating future school counselors. In fostering culturally competent practices, it becomes increasingly essential for school counselor educators and supervisors to teach graduate students how to explore cultural identities, privileges, and biases while self-examining these concepts in their professional practice. This chapter will provide an overview of the antiracist lens in school counseling. Interwoven with professional experiences and grounded in the literature, the chapter will describe the goal of teaching graduate students to become leaders and advocates in their school communities, understanding the school counseling graduate students, and the need for cultural competence in the behaviors of SCESs. Additionally, the material in this chapter will involve ideas to help online graduate students and SCESs explore personal cultural identities, biases, and values while sharing proactive ways to transfer these lessons into practice with K-12 students.
Strategies to Improve Counselor Educators and Students' Cultural Engagement Skills
Authors: Hug-Phillips Rebecca L.
Published: December 2024

Providing opportunities for master's level counseling students to improve cultural competence skills in their coursework does not need to be difficult. To produce culturally competent and aware counselors, counselor educators can incorporate intentional activities into students' workload. In this chapter, the multicultural and social justice counseling competencies serve as a framework for introducing opportunities for students to grow in self and client awareness, counseling relationships, and social justice and advocacy efforts. Each section outlines and provides examples for a discussion post, a summative assessment, and a case study activity. The activities are designed for counselor educators to use within any core class of their online program, whether taught synchronously or asynchronously.
EFL Teachers' Perspectives on Leveraging Tertiary Learners' Collaborative Learning via Translanguaging
Authors: Nguyen Tu Minh
Published: December 2024

Collaborative learning performs an essential role in English language education as it encourages student involvement in group discussions. Translanguaging is seen as a tool to foster active collaboration among learners. Additionally, translanguaging demonstrates great potential to stimulate inclusive language education which values students' linguistic diversity in English classrooms. This chapter examines Vietnamese tertiary teachers' perception of deploying translanguaging to enhance students' collaborative learning. This qualitative study involved three teachers in partaking in semi-structured interviews. The thematic analysis approach was employed to analyze data. The findings disclosed that teachers believed that adopting translanguaging pedagogy could develop learners' collaborative learning, leading to ideas generation, a pleasant learning environment, and inclusiveness. Teachers' difficulties in implementing translanguaging were also uncovered. Pedagogical implications are suggested for policymakers, teachers, and students to promote translanguaging as inclusive education.
Equity and Inclusion in Business English Courses
Authors: Tran Thao Quoc , Nguyen Tuyen Kim T.
Published: December 2024

The chapter presents a study exploring Vietnamese L2 students' perceptions of translanguaging in Business English courses in which the equitable and inclusive learning environment is fosted. The mixed methods study was conducted at a higher education institution in Vietnam. semi-structured interview for data collection. A group of 108 Vietnamese L2 learners were involved in answering a closed-ended questionnaire, and nine of them were intentionally invited for semi-structured interviews. The collected data were quantitatively processed by SPSS software in terms of descriptive statistics and qualitatively analysed in terms of the content analysis approach. The findings showed that Vietnamese L2 learners showed positive perceptions of translanguaging in Business English courses. Their cognitive dimension in perception of translanguaging was higher than their emotional and behavioral dimensions. This chapter highlights translanguaging as one of the teaching approaches to instill equity and inclusion in Business English courses.
L2 Students' Identity Through Project-Based Language Learning
Authors: Tran Thao Quoc , Nguyen Thien Hong
Published: December 2024

This chapter presents a mixed-methods study exploring L2 students' identity development through project-based language learning (PBLL) using the inclusive perspective. The study recruited a cohort of 91 students from a high school in Vietnam. Two research instruments (questionnaire and interview) were employed for data collection. The findings revealed L2 students' identities were reflected via their language proficiency, learner autonomy and language practice. Specifically, PBLL could enhance L2 students' speaking abilities, self-regulation, time management, decision-making, collaboration, presentation confidence, and overall communicative skills. This chapter highlights PBLL's pivotal role in shaping students' identities within the inclusive language education.
Using Authentic Materials and Differentiated Instruction to Match EFL Learners' Motivation
Authors: Nguyen Dung
Published: December 2024

This research was conducted to examine authentic materials (AMs) and differentiated instruction (DI) in matching Vietnamese EFL learners' motivation. Thus, 48 students majoring in Accounting learning General English at a university in Vietnam were recruited. A questionnaire survey and interviews were carried out. The figures collected with the questionnaire on learners' motivation showed the differences in motivation among EFL learners, and the data gathered from interviews indicated learners' attitude towards AMs and DI. The findings revealed that there were dissimilarities in EFL learners in terms of motivation, and AMs as well DI played as powerful tools in satisfying learners' motivation. This study also suggested some implications on AMs and DI for EFL teachers.
Generating Highly Nonlinear S-Boxes Using a Hybrid Approach With Particle Swarm Optimization
Authors: Shadab Mohd , Javed MD Saqib , Sajid Mohammad , Prasad Mukesh , Lapina Maria A. , Babenko Mikhail
Published: December 2024

A substitution box (S-box) is a fundamental component in cryptographic algorithms that enhance data security by providing a complex mapping between input and output values. S-box strengthens the encryption and decryption process by introducing nonlinearity and protecting the encrypted data against various differential and linear cryptanalytic attacks. The problem of generating an S-box with optimal properties is challenging and falls under the category of NP-Hard problems. This study proposes a hybrid approach combining the Particle Swarm optimization algorithm (PSO) and the Booster algorithm to construct a highly nonlinear S-box with low computational efforts. The PSO algorithm, assisted by the Transfer function and Random Key (RK), is utilized to navigate the large permutation search space to find an S-box with acceptable cryptographic properties. The Booster algorithm works based on random applications of local operators for shuffling the elements of the S-box with each other and transforming the elements' arrangement, resulting in a modified S-box with increased nonlinearity.
A Comprehensive Review of Nature-Inspired Optimization Techniques and Their Varied Applications
Authors: Subramanian Sridhar , Bhojane Niranjan , Madhnani Harsh , Pant Sangeeta , Kumar Anuj , Kotecha Ketan
Published: December 2024

Bio-inspired optimization algorithms use natural processes and biological phenomena as a basis for solving difficult optimization issues. This article discusses state-of-the-art techniques, applications, and implementations of eleven well-known bio-inspired optimization algorithms: Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Artificial Bee Colony Algorithm (ABC), Grey Wolf Optimizer (GWO), Firefly Algorithm (FA), Shuffled Frog Learning Algorithm (SFLA), Elephant Herd Optimizer (EHO), Lion Optimization Algorithm (LOA), Genetic Algorithm (GA), Flower Pollination Algorithm (FPA) and Bat Algorithm (BAT). Accordingly, each algorithm is considered in terms of the biological principles from which it is modelled, key mechanisms in operation, and the mathematical treatment. The current article also gives an account of recent improvements and modifications of these algorithms, made in an attempt to enhance their performance, speed of convergence, and robustness along with various real-world applications.
Integrating Ant Colony Optimization With Deep Learning for Improved Kidney Disease Diagnosis and Prognosis
Authors: Singh Jagendra , Sharma Deepak , Bhavani Ch , Rahul Satyakam , Rana Manoj , Mishra Jai Prakash
Published: December 2024

Accurate and early diagnosis of kidney cancer is critical for effective treatment and improved patient outcomes, yet current methods often face challenges in precision and reliability. This research addresses these challenges by integrating Ant Colony Optimization (ACO) with advanced deep learning models—DenseNet, ResNet 50, and VGG 19—and Long Short-Term Memory (LSTM) networks to enhance the prediction and classification of kidney cancer from CT scans and medical records. The approach leverages ACO to optimise feature selection, improving the performance of these deep learning models. DenseNet, combined with ACO and LSTM, achieved the highest accuracy of 97.9%, demonstrating exceptional capability in accurately detecting and classifying kidney cancer. Res-Net 50, also optimised by ACO, followed with a notable accuracy of 96.2%, showing its robustness. VGG 19, despite substantial improvement over training epochs, attained a lower accuracy of 92.3%, indicating that further optimisation could be beneficial.
Application of Variants of Nature-Inspired Optimization for Privacy Preservation in Cyber-Physical Systems
Authors: Yogi Manas Kumar , Chakravarthy A. S. N.
Published: December 2024

The integration of Cyber-Physical Systems (CPS) into critical infrastructure demands optimization techniques that ensure both high performance and privacy preservation. This paper presents the Privacy-Preserving Hybrid Bee-Evolutionary Optimization Algorithm (PP-BEOA), a novel variant of nature-inspired optimization tailored for CPS applications. PP-BEOA synergizes the exploratory capabilities of Artificial Bee Colony (ABC) algorithms with the exploitative strength of Genetic Algorithms (GA), enhanced by advanced differential privacy mechanisms and secure multi-party computation to safeguard sensitive data. Machine learning-driven parameter adjustments further improve adaptability and robustness in dynamic environments. Comprehensive evaluations demonstrate the effectiveness of PP-BEOA, showcasing superior results in scalability, real-time optimization, and resilience compared to traditional approaches. The results affirm PP-BEOA's potential as a transformative approach to addressing complex CPS optimization challenges.
Enhancing Heart Disease Diagnosis Through Particle Swarm Optimization and Ensemble Deep Learning Models
Authors: Singh Jagendra , Kumar Vinish , Sinduja Kotha , Ekvitayavetchanukul Pongkit , Agnihotri Atul Kumar , Imran Hazra
Published: December 2024

The present research focused on combining Particle Swarm Optimization (PSO) based hybrid deep learning models to classify heart disease images and patient sequences. This study employs Convolutional Neural Networks (CNNs), including VGG 16, VGG 19 and ResNet 50, as well as Recurrent Neu-ral Networks (RNNs), whereby their performance is optimized by PSO to im-prove the accuracy in diagnosing heart disease from CT images together with associated medical history. The models experienced a significant increase in classification performance, using manual hyperparameters tuning by PSO. The combined algorithm PSO with VGG 19 and the RNN model performed best, achieving a precision of 97.78% and becoming the highest recall on testing. The model that we propose uses the modern feature extraction of VGG 19 and an RNN to take into consideration the sequential nature of data, making it very accurate while keeping loss minimal. PSO with VGG 16 and RNN model is also another robust performance with an accuracy of 94.5%.
Sleep Stage Classification
Authors: Iyer Rajiv , Saranya A. , Wagle Shivali Amit , Maralapalle Vedprakash C.
Published: December 2024

Sleep stage classification is crucial for diagnosing sleep disorders, yet traditional manual scoring methods are labor-intensive and error-prone. This chapter presents an overview of automated sleep stage classification systems, focusing on integrating nature-inspired optimization algorithms to improve classification accuracy. We will discuss various techniques, including clustering, dimensionality reduction, feature extraction, and classification algorithms, emphasizing their roles in enhancing the performance of sleep stage classification systems. The chapter will detail recent advancements in deep learning approaches, such as Long short-term memory (LSTM) networks, and their application in analyzing electroencephalogram (EEG) signals. By employing optimization algorithms like Particle Swarm Optimization (PSO) and Genetic Algorithms (GA), we aim to demonstrate how these methods can refine feature selection processes and improve overall classification outcomes.
Advanced Methodologies for Optimal Neural Network Design and Performance Enhancement
Authors: Paul Sreelekha , Ghosh Sanchita , Das Dipanjan , Sarkar Saptarshi Kumar
Published: December 2024

The overview also includes state of the art methods for enhancing and optimizing the architectural structures of neural networks for machine learning and AI. Several optimization strategies are used in training deep learning models; they include Gradient Based Approaches, Learning Rate Schedules, Architectural Enhancements, and the incorporation of new architectures such as Transformers Recurrent Neural Networks, Residual Networks, and Convolution Neural Networks. Some of the other areas dealt with are development of new hardware accelerators, aspects of computationally efficient algorithm, and various forms of regularization. Also discussed are transfer learning, meta-learning, and changing hyperparameters. The development of the new neural network architectures for the future is a significant endeavor and includes the following concepts: Integration of Neural Networks with Quantum Computing, Federated Learning, Neuromorphic Computer Systems, Symbolic Reasoning. Better, faster, and more accurate systems, expected in the future as the neural network optimization techniques are improved.
Emerging Technologies for Water Decontamination
Authors: de Souza Poliana Mendes , Mahapatra Ajit Kumar , Pablo da Silva Edson
Published: December 2024

Water is essential for life, influencing human health, agriculture, and ecosystem stability. As global demand and pollution rise, effective water treatment becomes increasingly crucial. Traditional methods like chlorination and sedimentation have been vital for providing safe water but often require high energy and chemical inputs and may not fully address the spectrum of emerging contaminants. This chapter delves into advanced water decontamination technologies, including Advanced Oxidation Processes, nanofiltration membranes, electrochemical treatments, bioremediation, nanotechnology, and solar photocatalysis. It offers a comprehensive evaluation of these technologies, focusing on their efficiency, cost-effectiveness, scalability, and sustainability. This chapter analyzes comparative advantages and limits to offer insights for optimizing water treatment systems and directing future research and development, thus improving global water quality management and ensuring a safe and clean water provision for all.
Emerging Trends in Water Treatment and Purification Techniques
Authors: Selvakumar P.
Published: December 2024

Advanced water treatment technologies are at the forefront of efforts to address the growing global challenge of ensuring clean and safe water. As populations expand and industrial activities increase, traditional water treatment methods are often insufficient to handle the complexities and contaminants present in modern water supplies. This has led to the development and deployment of advanced technologies designed to improve water quality and address specific pollutants that conventional systems struggle to manage. Among the most notable advanced treatment technologies are membrane processes, such as reverse osmosis (RO) and nanofiltration (NF). These technologies employ semi-permeable membranes to remove a wide range of contaminants, including microorganisms, organic compounds, and inorganic ions. RO, in particular, is highly effective at desalinating seawater and brackish water, making it an essential technology in arid regions where freshwater is scarce.
Ground Water Management
Authors: Rekha P. , Kamalakkannan M. K. , Selvakumar P. , Bhattacharya Sumanta
Published: December 2024

Groundwater management is a critical field that encompasses the practices and policies necessary to ensure the sustainable use and protection of groundwater resources. Groundwater, which constitutes a significant portion of the Earth's freshwater supply, is a vital resource for drinking water, agricultural irrigation, and industrial processes. The importance of effective groundwater management cannot be overstated, as it directly impacts public health, economic stability, and environmental sustainability. Proper management practices are essential to prevent over-extraction, contamination, and depletion of aquifers, which can have far-reaching consequences for ecosystems and human populations. One of the primary challenges in groundwater management is the phenomenon of over-extraction. Excessive withdrawal of groundwater for agricultural and industrial purposes can lead to a drop in the water table, resulting in decreased availability of this critical resource. Once contaminated, groundwater can be difficult and expensive to remediate, making prevention and early detection crucial.
Emerging Trends and Technologies for Conservation and Sustainable Approach in Groundwater Management
Authors: Borgohain Lisha , Gogoi Mayurakshi , Dutta Jayashri , Medhi Smitakshi
Published: December 2024

Groundwater is a natural renewable resource vital for any life on Earth. Groundwater management is of emerging concern for the conservation and protection of this resource. With the advent of innovative technologies, managing such resources become easier to some extent. This chapter illustrates some of the advanced technologies, their contribution, challenges and future prospects for the conservation and sustainable management of groundwater. AI methods have become widespread in decision-making in recent years and are accepted globally due to their cost-effectiveness, time-saving, and efficient nature. AI-driven models provide precise analytical modelling, real-time monitoring, and data integration in groundwater management. Innovative AI models can detect the vulnerable regions that are prone to pollution and depletion of groundwater level and can draw the attention of scientists, local people and policymakers for prompt intervention.
Machine Learning and Digital Innovation for Managing and Monitoring Water Resources
Authors: Khosravi Arash , Ashkpour Maryam
Published: December 2024

This chapter aims to explore the transformative potential of artificial intelligence (AI), machine learning (ML) and digital innovations in water resource management and monitoring. It discusses various AI techniques and tools that enhance the controlling, analysis and managing water resources. These techniques are designed to address challenges such as data quality, technologies integration, and real-time decision-making. There are several case studies in the chapter, demonstrating successful implementation of AI and ML in water demand prediction, water quality monitoring, optimizing irrigation, efficient utilization and detecting anomalies in water management systems. The chapter emphasizes the need for interdisciplinary collaboration, robust data governance, and ethical considerations to fully realize the benefits of digital innovations in sustainable water management.
Magnetized Water's Quantum Mechanisms and Practical Applications in Sustainable Agriculture and Environmental Remediation
Authors: Salem Haytham Mohamed , Ali Ali M.
Published: December 2024

Magnetization of water represents an innovative physical treatment method that enhances the sustainability of clean freshwater supplies.This chapter elucidates the mechanisms of water magnetization, focusing on the quantum physical and chemical principles that result in improved structural order through hydrogen-bonded networks of water molecules. It reviews the practical applications of magnetized water in agriculture, water management, and environmental remediation, drawing on the latest research findings. The chapter also provides an outlook on future research directions and practical opportunities, such as promoting more robust plant growth, helping plants cope with abiotic stresses like drought and salinity exacerbated by climate change, and reducing water usage while maintaining or enhancing crop yield and quality. Furthermore, it discusses the potential of magnetizing saline water as an alternative solution to address freshwater scarcity. These benefits collectively contribute to alleviating water shortages driven by climate change.
Data-Driven Water Governance and Monitoring in 112 Aspirational Districts of India
Authors: Parekh Pratham Prakash
Published: December 2024

This chapter examines water governance in India, with a focus on the Aspirational District Programme (ADP). The ADP seeks to address socio-economic disparities in 112 historically underdeveloped districts by promoting data-driven, competitive governance, particularly in the adoption of micro-irrigation practices. The research utilises a performance scale ranging from Over Achieved (>100%), Very Near (80% to 100%), Near (60% to 80%), Middle (40%-60%), Far (20%-40%) and Very Far (0%-20%) to assess district-level progress towards national micro-irrigation targets. The findings reveal significant variability in progress, with many districts showing gradual improvement but with notable disparities and persistent challenges, particularly in data availability and reporting. The inquiry concludes with recommending several policy measure. These measures are crucial for advancing more effective and equitable water management monitoring, and it also opens up avenues for further policy research on water management in India's aspirational districts.
Applications of ISO 14046 Water Footprint Assessment for Sustainable Water Management in Dairy Production
Authors: Hettiarachchi Umesh , Jayasooriya Varuni , Muthukumaran Shobha
Published: December 2024

This chapter provides an in-depth analysis of water footprints within the dairy industry, recognized globally as a significant consumer of water. Utilizing the ISO 14046:2014 standard, the study examines the water footprints of three dairy production units—ice cream, yoghurt, and Ultra High Temperature (UHT) milk—focusing on identifying primary water consumption and pollution hotspots. The assessment considers both the supply chain and operational water footprints, with 48 footprints calculated based on the processing of 1L of fresh milk over 12 months in 2021. The findings reveal that ice cream production has the highest water footprint variation, followed by yoghurt and UHT milk. The study highlights the substantial contribution of green water and the importance of targeting water-intensive processes to minimize water use and wastewater generation in dairy production.
Plant Disease Classification Using Deep Learning for Agricultural Applications
Authors: Jansi K. R. , Amutha A. L. , Shankar A. Bhavani , Adesh J. P. , Kant Krishna
Published: December 2024

Agriculture is of paramount importance to human existence, but, the presence of plant diseases poses a significant risk to both food safety and productivity. Although traditional techniques can be used to identify plant diseases, they are frequently time-consuming and ineffective. Thorough research can increase the early detection of problems and boost agriculture by providing accurate diagnosis and preventive solutions. This study supports worldwide efforts to achieve sustainable food production. This study use pre-trained Convolutional Neural Networks (CNN) models to classify numerous plant illnesses concurrently, surpassing the existing constraint of predicting just one disease at a time. The task involves fine-tuning the CNN and DenseNet169 models by training them on the Plant Village dataset. The DenseNet169 architecture was utilized in the proposed approach to obtain an accuracy of 99.61% in identifying and classifying diseases in pepper bell, potato, and tomato. This demonstrates the efficacy of deep learning in the classification of plant diseases.
Evaluation of Gamified Learning in Organizations
Authors: Mathew Jain , Nair Sridevi
Published: December 2024

Organisations are investigating the use of gamification to improve learning and development activities because they need tools to make learning more efficient and engaging. Additionally, because employee demographics are changing and there is a growing generation that is comfortable with and prefers technologically enhanced training methods, it is necessary to assess these methods. This study compares the effectiveness of gamified modules to regular modules using a pre-test-post-test control group design. The participants were randomly assigned to two groups. The results validate the theoretical framework of gamified learning, as evidenced by the higher scores obtained by the gamified module participants in terms of learning, reactivity, and learner motivation. The results further imply that the influence of gamification on the selected learning outcomes of learning and reaction was strongly mediated by learner motivation. The hypothesis of gamified learning is supported empirically by the current investigation.
Gamification as a Pedagogical Innovation in Architectural Education
Authors: Bayraktarlı Ömer Faruk , Selçuk Semra Arslan
Published: December 2024

Gamification has emerged as a valuable tool in addressing evolving demands within the ever-changing field of architecture education. This chapter explores its potential in higher education programs, focusing on how it complements traditional teaching. Through a literature review of studies indexed in the Web of Science, findings show that while gamification boosts motivation and learning outcomes, it also poses challenges like sustaining engagement and addressing diverse learners. Despite its benefits, such as enhanced problem-solving and hands-on learning, large-scale studies are needed to examine potential drawbacks, including oversimplification. If its effects are examined more, it will provide educators with enough material so that people can use this study to learn and apply it better. Ongoing research is crucial to fully harness gamification for developing creative, effective future architects.
Gamification for Transformative Learning
Authors: Huda Miftachul , Jailani Mohammad , Hashim Azmil
Published: December 2024

This proposal aims to examine the way of gamification with its features in enhancing the transformative learning in enabling the students' acquisition of knowledge as the strategic achievement to obtain the 21st century education. The finding revealed that the innovative concept of implementing the game scenario with the featured elements and principles could support the educational process and practices. This study will contribute into building the advancing scenario to further make the actively transformative learning interaction with the unique characteristics of enjoyable and effective basis. With the profound target of goal, the strategic orientation of gamification could foster in leveraging the learning process and practices engaged with play and competition in order to give the motivating support to the learners and thus would improve their learning outcomes. At this point of view, the gamification played a role in advancing the academic performance together with nurturing the essential skills like problem-solving and collaboration.
Gamified Success
Authors: Kachhi Zidan
Published: December 2024

Gamification has emerged as a transformative approach in education, leveraging game-like elements to enhance student engagement and motivation. This chapter attempts to present best practices, challenges and solutions for creating effective gamified experiences focused on but not limited to educational use, touching base on business and healthcare as well. Key theoretical foundations are discussed to illustrate how psychological principles can inform effective gamification strategies. The chapter highlights significant challenges such as sustaining long-term engagement, balancing game mechanics with educational goals and addressing cultural and ethical considerations. Solutions are proposed to overcome these challenges. Additionally, the role of technological advancements in reshaping gamified experiences is examined. Finally, the chapter emphasizes the importance of evaluating the effectiveness of gamified systems, providing actionable insights.
Rethinking History Teaching
Authors: Sousa João Paulo , de Faria Julio César Leal , Tavares Rogério , Lopes Rui Pedro
Published: December 2024

This work introduces a new multiplayer digital game called TimeCraX, which aims to improve history education by making it more interactive, engaging, and fun. It highlights the challenges of traditional learning and how digital games can overcome them by utilizing gamification and game-based learning. The TimeCraX game platform is designed to be cooperative, allowing students to work together to complete a challenge based on a historical timeline. The goal is to promote learning through practical experience, encouraging critical thinking, and developing collaboration and teamwork skills. The article discusses the multiplayer platform architecture of TimeCraX, which includes authentication modules, team and student rankings, matchmaking, and reporting tools, all aimed at providing teachers with the tools to monitor student progress and create balanced student groups based on specific criteria. The article concludes with a discussion of the next steps for the game's development, including a play session with students to evaluate the platform's effectiveness.
Entrepreneurial Ecosystems and Job Creation
Authors: Quttainah Majdi , Pandey Ashutosh , Yadav Amit Kumar , Chandel Ajay
Published: December 2024

This chapter turned its focus on critical elements such as access to capital, infrastructure, collaborative culture, and government policies in line with effective ecosystems. The chapter is based on case studies of the five entrepreneurial regions of Silicon Valley, Bangalore, Tel Aviv, Berlin, and Shenzhen, pointing out how each uses its unique strengths in building vivid entrepreneurial environments. A key place where the authors focus is on rising tendencies, such as models for working digitally, social entrepreneurship with a positive social impact, and the setting of technological advances to lead the way to future developments of these ecosystems. It also addresses bottlenecks other than financial constraints, which are regulatory barriers, which underline the need for strategies adapted to these constraints and collaboration. This insight that can be garnered from these dynamics could empower stakeholders to make entrepreneurial ecosystems that are much more effective at supporting sustainable innovation.
Human Factors in the Creation and Growth of Entrepreneurship Ecosystems
Authors: Vargas-Hernandez José G. , Gonzàlez-Àvila Francisco J. , Vargas-Gonzàlez Omar C.
Published: December 2024

This study aims to analyze the various human factors involved in the different processes of the entrepreneurship ecosystems. The analyses depart from the assumption that that the entrepreneurial ecosystem can be created and defined not only by broad geographies endowed by intentions but dependent of human factors. Th method employed is the meta-analytical supported by the descriptive based on the conceptual, theoretical and empirical literature review. The study concludes that human factors, such as behaviors and traits, values, attitudes and beliefs are relevant for the creation and growth of entrepreneurship ecosystems
Price Dynamics and Entrepreneurship in Africa
Authors: Niyonzima Thomas Gahamanyi , Gérard Tchouassi
Published: December 2024

The aim of this chapter is to assess the effects of price dynamics on entrepreneurship in Africa. The dynamic specification was developed by Farahadi et al (2015 and reposted by Awoa et al. (2022). Data were collected on 35 African countries for the selected period from 2006 to 2018. The results of this chapter show that price dynamics have nuanced effects on entrepreneurship in Africa depending on the model and robustness applied. The IPC has a negative impact on entrepreneurship in Africa, while energy and non-energy prices have positive effects on entrepreneurship. Commodity price index have both positive and negative effects on entrepreneurship. Policy makers should develop strategies to reduce inflation by cutting public spending, raising taxes and introducing tight monetary policies, promoting better access to non-energy commodities by framing the beverage sector, implementing policies to strengthen the entrepreneurial ecosystem, reviving access to financing by popular banks and forcing FDI to partner with local entrepreneurs.
Integrating Crowdfunding and Financial Planning for Entrepreneur Success
Authors: Murthy Krishna , Sanadi Hassan , Begum Sameena , Sethi Smriti , Karthikeyan P.
Published: December 2024

The chapter elaborates on how crowdfunding can become a powerful tool for financial growth and stability for solopreneurs. It covers strategies concerning the creation of compelling crowdfunding campaigns and therefore highlights that, before doing so, fundraising goals should align explicitly with long-term financial planning. It further shared some tips on how to assess whether there is a real need for finance, how to set realistic funding targets, and how to craft persuasive pitches that charm potential backers. It also deals with important areas of post-campaign financial management, such as budgeting, expense tracking, and how to reinvest. Integrating effective crowdfunding techniques with robust financial planning allows solopreneurs not only to raise the capital needed for the launch and scaling of ventures but also to maintain business practices and achieve long-term success. This comprehensive approach provides a solopreneur with the necessary tools and insights to turn financial challenges into growth opportunities.
Data Privacy and Security Risks in Third-Party App Integrations
Authors: Rajendran Rajesh Kanna , A. Josanth Smilan
Published: December 2024

Third-party applications frequently request access to various types of user data, such as contacts, photos, and location, to provide enhanced functionality and improve user experience. For instance, social media platforms may integrate with third-party apps that facilitate post scheduling, engagement analytics, or introduce additional features not available on the platform itself. However, enabling these capabilities often requires granting third-party apps permission to access sensitive data, which introduces potential privacy and security concerns. Once access is approved, these applications can collect, use, and occasionally share user data with other entities, increasing the risk of privacy violations if data protection measures are inadequate or the data is misused. Granting such permissions may expose users to security vulnerabilities, particularly if the third-party apps lack robust security frameworks, making user data susceptible to hacking or unauthorized access.
Surveillance and Privacy
Authors: Mannan Mamun Abdul
Published: December 2024

This chapter analyzes the tension between surveillance practices and privacy rights, focusing on how social media platforms and governments navigate this balance. By employing library and document analysis, reviewing legal documents, policy papers, and case studies related to surveillance and privacy this study adopted a Thematic Analysis. Findings show that balancing surveillance and privacy is challenging due to conflicting priorities and legal frameworks. Another major findings is that Governments often face criticism for overreach, while social media platforms must navigate complex legal and ethical issues. The chapter as discussion, highlights the need for clear and balanced policies that protect privacy while addressing security concerns. It also considers the impact of surveillance on user behavior and public trust. This chapter recommends developing balanced regulatory frameworks that address both privacy and security concerns, increasing transparency in surveillance practices, and engaging with stakeholders to ensure that privacy protections are upheld.
O Processo civilizatório no contexto da sociedade burguesa e o corpo: desafios à educação
Authors: Neuvald Luciane , Brancher Carlos Eduardo Laurentino
Published: December 2024

O texto objetiva refletir sobre o processo civilizatório na sociedade burguesa, sobre suas implicações em relação ao corpo e sobre os desafios que esse contexto apresenta à educação. O referencial teórico ampara-se na teoria crítica da sociedade, nas ideias de Theodor Adorno e Max Horkheimer. Para esses autores, o processo civilizatório promove uma razão de característica dominadora e autocrática, impassível à esfera sensível da vida, na medida em que a civilização se sobrepõe à natureza, na tentativa de proteger-se dela. O processo civilizatório exige o sacrifício e a renúncia dos sujeitos, que precisam abdicar do prazer e de sua identidade em prol dos interesses do sistema. Sendo assim, o prazer é destituído de sua forma genuína e se realiza de forma substitutiva, sob a mediação da indústria cultural. O sacrifício que o processo civilizatório exige do eu, recai sobre a relação do indivíduo com o seu corpo, sendo a indústria cultural uma referência preponderante na construção da imagem corporal, instituindo modelos de beleza, de dieta, de exercícios e de comportamentos. A dialética negativa, característica da abordagem teórica eleita, incide sobre a crítica imanente do processo civilizatório, pois este, além de implicar o sacrifício e a renúncia, também implica a exploração da heteronomia. A conscientização sobre a exploração planificada do corpo consiste no papel da educação, assim como a constituição de um imaginário corporal resistente aos modelos de corpo idealizado pela indústria cultural e a assunção da identidade corporal, própria de cada pessoa.
Association between excess peripheral, central and general adiposity and different contexts of physical activity among adolescents from Southern Brazil
Authors: Santiago Leandro Narciso , Martins Priscila Custódio , Silva Diego Augusto Santos
Published: December 2024

The aim of this study was to investigate the association between excess peripheral, central and general adiposity and different contexts of physical activity (Physical Education classes, school recess, commuting, leisure time and participation in sports teams) in adolescents from Southern Brazil. Across-sectional study was developed with 1.132 adolescents (16.50 ± 1.14 years) of both sexes. Peripheral adiposity (triceps skinfold) and central adiposity (subscapular skinfold) were classified as high based on the 90th percentile of the Centers for Disease Control and Prevention reference distribution. For excess general adiposity, triceps and subscapular skinfold thicknesses above the 90th percentile were simultaneously considered. The different contexts of physical activity were obtained through self-reported questionnaire. Covariates were: age, economic level, eating habits measured through self-administered questionnaire and sexual maturation (self-reported, following Tanner's procedures). Binary logistic regression was used with significance level < 0.05. Male adolescents little active during leisure time were 2.25 (95%CI: 1.17; 4.50) times more likely of having excess peripheral adiposity, 3.10 (95%CI: 1.56; 6.13) times more likely of having excess central adiposity and 2.38 (95% CI: 1.08; 5.26) times more likely of having general adiposity when compared to peers active during leisure time. For female adolescents, no context of physical activity was associated with excess peripheral, central and general adiposity. Male adolescents little active during leisure time are more likely of having excess peripheral, central and general adiposity. For female adolescents, no context of physical activity was associated with excess peripheral, central and general adiposity.
Não-binariedade: uma análise neomaterialista
Authors: Butturi Junior Atílio , Camozzato Nathalia Muller
Published: December 2024

Este artigo tem como objetivo analisar a linguagem não-binária segundo as próprias pessoas autoidentificadas como não-binárias e seus efeitos na constituição de práticas de si e de saberes. Para tanto, partimos da análise neomaterialista dos discursos no esforço de uma leitura intra-ativa e decolonial da não-binariedade, não restrita à língua. Metodologicamente, produzimos um corpus a partir de duas estratégias: a primeira, a criação, em 2023, de um questionário enviado a pessoas que fazem graduação da Universidade Federal de Santa Catarina e se autodesignam como NB; a segunda, a tomada de recortes de falas de uma mesa-redonda de um evento sobre linguagem inclusiva realizado, on-line, em 2023. Tendo isso em vista, inicialmente discorremos sobre nosso entendimento da não-binariedade como intra-ação material-discursiva para, então, analisarmos algumas das regularidades. De modo geral, notamos que, enquanto entre as pessoas da graduação da UFSC está presente uma exigência de visibilização pela linguagem, no evento coloca-se em xeque o papel da linguagem, do discurso e dos saberes acadêmicos na produção da binariedade, o que aponta para a relação entre variadas formas de violência, inclusive epistemológicas, por um lado, e para a demanda por invenções de si múltiplas e incorporadas das próprias pessoas que aqui ganham a cena pública e reivindicam para si mesmas outras formas de subjetividade e de corporalidade.
Resistencias al lenguaje inclusivo de género entre les estudiantes universitaries argentines: de lo simbólico a lo material
Authors: Dvoskin Gabriel , Ansaldo Sofía
Published: December 2024

En este artículo, indagamos desde el enfoque del Análisis Crítico Feminista del Discurso en las representaciones sobre el lenguaje y el género que circulan en los posicionamientos manifestados por estudiantes del nivel superior que, a partir de una encuesta realizada en el año 2021, reportaron no usar lenguaje inclusivo de género (LIG). El análisis de los datos nos permitió identificar tres argumentos principales sobre los que erigen sus posturas: 1) ‘El lenguaje es un instrumento de comunicación’; 2) ‘El LIG dificulta la comunicación’, y 3) ‘El LIG es una moda’. Estas representaciones están estrechamente vinculadas entre sí y se sustentan en otras representaciones sobre el lenguaje que, a su vez, propician: como que la lengua es homogénea, transparente y democrática. El rechazo al uso del LIG se fundamenta principalmente en que atenta contra esta supuesta homogeneidad de la lengua, por lo que perturbaría su funcionamiento como herramienta de comunicación entre las personas. Por otro lado, resulta interesante que se descalifica el LIG por no poder generar cambios materiales en la vida de los grupos minorizados, pero también se le atribuye la responsabilidad de excluir y discriminar a quienes no lo utilizan, efectos que trascienden el orden simbólico. Esta contradicción abre un hiato que refuerza la idea de que las ideologías lingüísticas no solo constituyen representaciones sobre las lenguas o variedades sino también sobre sus hablantes. Esta problematización de las relaciones entre el lenguaje y la sociedad ha estado ausente en la enseñanza formal de la lengua en el ámbito educativo en la Argentina, omisión que tuvo su impacto en el sentido común. En consecuencia, consideramos que resulta necesario promover una educación lingüística crítica en la escuela, que indague en las estrechas relaciones que mantienen el lenguaje, la sociedad y la ideología.
A utilização de pronomes não binários no português brasileiro: um estudo exploratório
Authors: Silva Elaine Rodrigues de Souza , Carvalho Danniel da Silva
Published: December 2024

O presente trabalho possui como objetivo verificar e analisar os usos de uma terceira marca de gênero no português brasileiro, realizado na utilização de neopronomes, como nos sistemas ‘elu’, ‘ile’, ‘ilu’ e ‘el’, e na ampliação de marcas distintivas de gênero na língua, tal como o uso do -e no final de nomes. A justificativa desta investigação é pautada na novidade do fenômeno na língua e, de forma consequente, nos estudos linguísticos, formando-se como uma nova problemática de investigação. Para tanto, lançamos mão de estudos sobre a categoria de gênero gramatical desenvolvidos por Câmara Jr. (1970), Rocha (1998) e Corbett (1991). Destacam-se também os estudos de Benveniste (1995) e Neves (2000) sobre a classe dos pronomes, com intuito de compreender a implementação dos neopronomes e a sua relação com um novo valor de gênero. Além do trabalho de Hall (2006) que permeia as questões de identidade dos sujeitos. Desse modo, a partir de uma coleta de dados realizada na rede social X, por meio de um procedimento de raspagem, foram analisados os usos dos neopronomes no português brasileiro. Nesse sentido, os 364 dados de neopronomes foram submetidos a uma análise estatística, utilizando a plataforma R, na qual foi observada a proporção de frequência de uso, o contexto semântico desses usos e o padrão de concordância nominal desencadeado pelos neopronomes. Assim, como resultado foi observado que o sistema ‘elu’ apresentou uma maior frequência de usos. Além disso, as utilizações de neopronomes apresentaram uma maior relevância para uma referência genérica dos sujeitos, recuperando identidades binárias e não binárias na língua, e pouco impacto no padrão de concordância da língua.
Sobre a pretensa universalidade de gênero gramatical
Authors: Cerqueira Fernanda
Published: December 2024

Resenha do Livro: Carvalho, D. S. (2021). A domesticação da gramática de gênero. São Paulo, SP: Pontes. 174p. ISBN-13 ‏ 978-6556371580
Não existe linguagem neutra? A variabilidade na expressão de gênero no português como um fenômeno linguístico contemporâneo bastante representativo da relação entre língua e sociedade
Authors: Rocha Franciane
Published: December 2024

Resenha do Livro: Freitag, R. M. K. (2024). Não existe linguagem neutra! Gênero na sociedade e na gramática do português brasileiro. São Paulo, SP: Contexto. 176p. ISBN-13 978-6555414295
As relações entre a língua portuguesa e as questões de gênero: há uma linguagem neutra?
Authors: Silva Filho Eraldo Batista da
Published: December 2024

Resenha do livro:  Freitag, R. M. K. (2024). Não existe linguagem neutra! Gênero na sociedade e na gramática do português brasileiro. São Paulo, SP: Contexto. 176p. ISBN-13 978-6555414295