bluuebunny/crossref_metadata_2025 huggingface dataset:
Applications of Machine Learning in Education and Skill Developments
Authors: SivaPadmini P. , Beulah Viji Christiana M. , Pitchai R. , Kumar Santosh , MurthyRaju Kommisetti
Published: December 2023

The integration of machine learning (ML) techniques in education and skill development has revolutionized traditional teaching and learning paradigms. This chapter explores transformative applications of ML in education and skill development, focusing on experimental approaches to enhance learning outcomes and skill acquisition. It reviews literature on ML-driven personalized learning, intelligent tutoring systems, educational data mining, and predictive analytics, while discussing challenges and ethical considerations in implementing ML in educational settings. This chapter explores experimental methodologies for evaluating the effectiveness of ML-driven interventions, analyzing case studies and real-world examples. It highlights the design, implementation, and outcomes of these experiments, providing insights into ML's impact on student engagement, knowledge retention, skill advancement, and overall educational quality.
Fostering Sustainability Education Through Cross-Disciplinary Collaborations and Research Partnerships
Authors: Das Simanchala , Lekhya Gudla , Shreya Kodukula , Lydia Shekinah Karyamsetty , Babu Katuri Khadar , Boopathi Sampath
Published: December 2023

This book chapter delves into the essential principles and empirical research surrounding cross-disciplinary collaborations and partnerships in the realm of sustainability education. It explores how the convergence of diverse academic disciplines can synergistically advance sustainability education, creating a holistic learning environment that addresses complex global challenges. Through case studies and theoretical frameworks, this chapter sheds light on the fundamentals of establishing successful cross-disciplinary collaborations and offers insights into their pedagogical and research dimensions. By examining the interplay between various disciplines and their contributions to sustainability education, this chapter contributes to the broader discourse on innovative educational approaches for a more sustainable future.
Utilizing Generative AI With Second-Language Users and Bilingual Students
Authors: Billingsley Frank , Gardner Stephanie
Published: December 2023

The growth of generative artificial intelligence (for purposes of this chapter, “AI”) has created endless systems to utilize modern technological assistance in the educational arena. AI has the potential to significantly impact higher education by facilitating personalized development and knowledge sharing. There are many ways that AI can be leveraged to enhance the education process. This chapter will focus on second-language users and bilingual students learning new language concepts. Second language users can be defined as students in the language acquisition process. A bilingual student is any student who has already acquired a second language but needs to build on terminology in their field of study. AI can provide a functional teaching tool for educators to assist with building the required knowledge base. The premise is to embrace the tool—versus forbidding its use by students—to assist them in their educational growth.
AI and Blockchain Fundamentals
Authors: Samantaray Rashmi Rani , Tabassum Zahira , Azeez Abdul
Published: December 2023

This chapter explores the intersection of artificial intelligence (AI) and blockchain technologies in the realm of industrial robotics. The integration of AI and blockchain has the potential to revolutionize various aspects of the manufacturing sector, from enhancing robotic capabilities to optimizing supply chain management. This chapter delves into the key applications, benefits, challenges, and future prospects of combining AI and blockchain in industrial robotics. Both blockchain and artificial intelligence have generated a lot of excitement in the technology industry for a number of years. AI and blockchain applications for robotics applications thus provides productive, energy-efficient outcome and thus ease the process of automation and maintenance.
Enhancing Industrial Robotics Performance and Security With AI and Blockchain Technologies
Authors: Varadam Deepak , Shankar Sahana P. , Bharadwaj Aryan , Saxena Tanvi , Agrawal Sarthak , Dayananda Shraddha
Published: December 2023

Industrial robotics are becoming more widely used, but their performance and security must be urgently enhanced to satisfy the needs of contemporary industrial contexts. This chapter focuses on how AI and blockchain technology might improve industrial robotic systems' performance while guaranteeing strong security precautions. The capabilities of industrial robots are greatly enhanced by AI technologies. Robots may improve their performance, gain new abilities, and adapt to changing circumstances by utilising cutting-edge machine learning techniques. Robots may learn from their experiences thanks to the incorporation of AI, which improves their operational effectiveness, precision, and decision-making abilities. AI enables robots to optimise their performance, spot anomalies, and proactively resolve potential difficulties, resulting in increased production and less downtime. This is done through real-time data analysis and predictive analytics. Incorporating blockchain technology also provides an industrial robotics system with a safe and open framework.
Apple Leaf Disease Identification and Segmentation Using Enhanced Learning-Driven Feature Representation Model
Authors: Raju Harsha , Narasimhaiah Veena Kalludi , Alagirisamy Mukil
Published: December 2023

The field of automatic segmentation and identification of plant diseases from leaf images has become increasingly significant in recent years. There are a number of fungal diseases that affect apple quality and yield, including apple scab, cedar rust, and black rot. In order to prevent crop losses, it is essential to identify these diseases quickly as possible. Despite many approaches being discussed, segmenting the diseased part of leaves with high accuracy and low false positive rates remains a challenging task. This study suggests that by isolating the color background and highlighting the area of interest, a substantial feature set can be constructed to enhance deep learning generalization capability for disease classification. An algorithm for fitness function is developed to represent the features that are relevant to disease classes and optimally adjusts the weights and biases in the training phase. Based on visual outcome and comparative analysis in terms of precision, recall rate, and F1-scores, the efficacy of the proposed work is justified.
Development and Application of Machine Learning Algorithms for Sentiment Analysis in Digital Manufacturing
Authors: Jain Vishal , Mitra Archan
Published: December 2023

Customer input has increased as digital manufacturing and smart factories advance. However, standard analysis methods struggle to turn this feedback into useful insights. This research study examined the use of machine learning (ML) sentiment analysis algorithms to improve digital manufacturing customer feedback interpretation. Machine learning, sentiment analysis, and digital industrialization theories underpin the research. Sentiment analysis may reveal nuanced consumer feedback insights that traditional methods miss, according to customer experience management and complex data analytics theories. A specially constructed ML system for sentiment analysis was used to real-world customer feedback data from numerous digital manufacturing enterprises in a case study. This method classified feedback sentiment using natural language processing. The program picked up small changes in client emotions that previous methods missed. These findings imply that machine learning-based sentiment analysis improves digital manufacturing customer feedback interpretation.
Applications of 4D Printing Technology
Authors: Jha Udai Chandra
Published: December 2023

4D printing technology is destined to revolutionize the industrial world. These are some of its possible achievements and applications: 1) Medicine and surgery: in 2015, a medical team from Michigan University saved the lives of three babies with respiratory problems by inserting a 4D printed implant. This polycaprolactone device, designed to fit each patient, was designed to adapt its size to the child's growth and to dissolve itself when no longer necessary. 2) Clothing and footwear: 4D printing technology allows the manufacturing of clothing that adapts to the body's shape and movement. 3) Aeronautics and automotive: the NASA has developed an intelligent metallic fabric with 4D printing technology. Various applications of 4D printing are discussed in this chapter.
Internet of Things and Sensor Networks in Industry 5.0
Authors: Singh Akhilesh Kumar , Sharma Ajeet , Singh Pradeep kumar , Kesarwani Surabhi , Singh Amit Pratap
Published: December 2023

In the era of Industry 5.0, the seamless integration of the internet of things (IoT) and sensor networks has become a revolutionary force that plays a crucial role in connecting devices and machines, allowing for a level of connectivity that enhances efficiency and sustainability in industrial processes. The chapter begins by underlining IoT's vital role in Industry 5.0. As the adoption of smart sensors, IoT devices, and edge computing technologies has grown, the sector has evolved into a digital ecosystem. This integration provides valuable insights by enabling data-driven decision-making and optimizing decision-making processes, resulting in a more flexible and responsive industry environment with less downtime and improved overall efficiency. The chapter then explores deeper into the many types of sensors used in industry, including temperature, pressure, vision, and audio sensors. These sensors allow for continuous monitoring of important parameters, allowing for predictive maintenance and early warning of potential problems.
Emerging Tech Analysis of Intellectual Property and Data Ownership in Smart Factories
Authors: Mitra Ankita , Bhattacharya Sanjay , Gupta Subir
Published: December 2023

Integrating emerging technologies in smart factories has ushered in a new manufacturing era. These technologies have transformed how data is generated, stored, and utilised, raising critical questions about intellectual property (IP) and data ownership. This study comprehensively analyses the challenges and implications associated with IP and data ownership within the context of smart factories. By reviewing the existing literature and conducting empirical research, this project aims to shed light on the multifaceted issues surrounding these concepts, offering valuable insights for industry professionals and policymakers.
Fortifying the Digital Forge
Authors: Dodiya Kiranbhai Ramabhai , Jha Mukul , Jha Sammi
Published: December 2023

In our interconnected world, cybersecurity is paramount due to IoT, cloud computing, and automation's impact on manufacturing. This chapter underscores digital manufacturing's dependence on interconnected systems and cloud infrastructure, acknowledging risks like data breaches, IP theft, and operational disruptions. It advocates a comprehensive cybersecurity approach encompassing technical measures, organizational policies, staff training, and incident response. The chapter delves into threats like malware, phishing, ransomware, and supply chain attacks, emphasizing continuous monitoring, threat intelligence, and vulnerability management. Additionally, it explores emerging trends like AI and machine learning in cybersecurity, legacy system security, and collaborative efforts among industry players, government agencies, and cybersecurity experts to safeguard digital manufacturing. This chapter aids manufacturers, security experts, and researchers in building secure systems in our connected digital landscape.
Promoting Critical Thinking Disposition Through Virtual Reality Serious Games
Authors: Jiayuan Su , Jingru Zhang
Published: December 2023

The new VR technology is used in various fields such as medicine, military, and especially in education. A teaching methodology based on logical reasoning in a serious virtual reality game was designed and developed in the study. Through a pre-test and post-test laboratory experiment approach, the California Critical Thinking Disposition Questionnaire was used to detect changes in critical thinking dispositions of a class of 37 students including experimental and control groups. The experimental data were analysed for component gaps by means of independent samples t-tests. Ultimately, through significance data, the instructional model proved to be more effective in developing students' critical thinking than the traditional lecture model.
Multifactor Method of Design of an Effective Corporate Culture
Authors: Ceesay Adja R.
Published: December 2023

Understanding corporate culture is vital to stand out in the market industries. Some companies like to run a business but struggle to reduce absenteeism, turnover, and retention. Organizations that do not have a noticeable corporate culture tend to face challenges due to poor management and a lack of resources to properly train their employees and provide them with the resources required to perform their jobs. Absenteeism, turnover, and retention have increased due to poor management, lack of support, and a toxic environment. Organizations that do not develop multi-level strategies, create implementation plans, and provide a healthy environment face challenges in creating a functional place. Leaders should work closely to formulate robust beliefs and values to shape their mission statement and make the corporate culture transparent by setting excellent communication channels to communicate the culture. Also, leaders who effectively share the business strategy have positive outcomes in building relationships and trust with their employees.
Transformational Leadership Juncture With Perspectives of Diversity and Inclusion
Authors: Diene Amdy
Published: December 2023

This research focuses on the intersection of transformational leadership and diversity and inclusion within a global and African context. Where does Africa fit in? Researchers conducted a qualitative case study on managing a diverse workforce in two West African organizations using interviews and surveys to collect participant data. A total of 15 high-level managers and their subordinates were interviewed, and a survey was conducted. Several qualitative analytical software packages were used for data analysis, including NVivo, SPSS, and SAS. The study's findings indicate how transformational leadership impacts the management of a diverse workforce and the participants' perspectives. Regardless of geographic boundaries, the results confirm the complexities diversity and inclusion bring to organizations worldwide.
Managing Gender and Sexual Diversity in the Workplace
Authors: Haitembu Rauna Keshemunhu
Published: December 2023

This chapter, taking account of the personal and organizational benefits of effective management of diversity in the workplace, focuses on the management of gender and sexual diversity. Management of gender and sexual diversity in the workplace is one of the crucial strategies to foster inclusive workplaces and increase employee and organizational productivity. In line with the growing popularity of qualitative inquiry in sexuality research, this chapter utilizes a qualitative methodology and an intersectionality approach to provide reflections of gender and sexually diverse employees on their experiences in the workplace. In response to the evidence of gender and sexually diverse employees experiencing discrimination and stigmatization, this chapter establishes strategies and practices for effectively managing gender and sexual diversity. Management of gender and sexual diversity requires the implementation of inclusive initiatives and practices. It further requires organizations to acknowledge employees' experiences at the intersections of their multiple identities.
Explaining the Challenges of Accountability in Machine Learning Systems Beyond Technical Obstacles
Authors: Palvadi Srinivas Kumar
Published: December 2023

The ability to make a note regarding machine learning systems decisions for people is becoming increasingly sought after, particularly in situations where decisions have significant repercussions for those affected and where capability in terms of maintaining is required. To increase comprehension based on referred to as “black box” mechanism, explaining ability is frequently cited as a technical obstacle in the design of ML systems and decision procedures. The quantities that ML systems aim to optimize must be specified by their users. This leads to the revealing of policy trade-offs that may have previously been hidden or implicit. Important decisions, as well as judgments, help what may need to be explicitly discussed in public debate as ML's use in policy expands.
Impact of Pairwise Electrode Features in the Classification of Emotions for EEG Signal Analysis
Authors: Suchetha M. , Rama Raghavan V. V. , Fardeen Shaik , Nithish P. V. S. , Preethi S. , Edwin Dhas D.
Published: December 2023

Emotion recognition is the capacity to recognize and interpret an individual's emotional state through a variety of techniques, one of which is the detection and interpretation of patterns of brain activity linked to specific emotional states. Applications for emotion recognition are numerous and include human-computer interaction, marketing research, and mental health diagnosis. Electroencephalography (EEG) signals are another name for the patterns of brain activity. To extract features from EEG waves, many techniques have been used. The wavelet transform (WT), differential entropy (DE), statistical features (SF), and convolutional neural network (CNN) are some of the feature extraction techniques performed. This proposed method utilizes a custom CNN model to train and test on the preprocessed SEED data.
Infected Plant Leaves Detection Using Multilayered Convolutional Neural Network and Quantum Classifier
Authors: Kaur Damandeep , Singh Shamandeep , Kaur Simarjeet , Singh Gurpreet , Kumari Rani
Published: December 2023

The objective of this chapter is to establish an accurate and efficient approach to diagnosing symptoms of disease, and therefore develop an optimal method to solve the problem efficiently and cost-effectively. Quantum-based classifiers also play an essential role in detecting the leaf profile features in recognizing leaves using a computer vision system that can be used with a quantum computer. Enhanced double quantum images encryption (EDQRCI) enables automation to produce and create quantum pictures that transform color pixels into well-defined shapes ways. Therefore, a novel model is proposed to identify and diagnose the mango leaves that are infected with Anthracnose fungal disease with the help of a multi-layer convolution neural network (MCNN). The images of unhealthy and healthy leaves of mango trees are taken from a dataset, namely, Plant Village, to determine the efficacy of the model. The simulation of the proposed model is implemented with the help of MATLAB software, and shows a higher classification accuracy of the proposed model MCNN.
Quantum Machine Learning for Biomedical Data Analysis
Authors: V. Dankan Gowda , Patil Harshali Yogesh , Abidin Shafiqul , Panda Ribhu Abhusan , Suneetha Sampathirao
Published: December 2023

The emerging and novel field of utilizing quantum physics in the world of machine learning, with applications customized for biomedical data, is explored in detail in this chapter. The discussion begins with an introduction to quantum physics and machine learning, before going on to explain how the two fields can work together to revolutionize biomedical data processing. Quantum-enhanced algorithms and their ability to process massive and intricate biomedical datasets are discussed in depth. In applications such as protein folding prediction, genomic data processing, and real-time diagnostics, the inherent parallelism and superposition capabilities of quantum machine learning are on full display. Finally, the technical and ethical difficulties of combining quantum machine learning with biomedical data are assessed in depth. The authors also provide an outlook on the promising interdisciplinary subject of quantum-powered machine learning and its potential to radically alter the field of biomedical research and healthcare solutions.
Smart Detection and Removal of Artifacts in Cognitive Signals Using Biomedical Signal Intelligence Applications
Authors: Kishore Kanna R. , Yamuna Devi K. , Gomalavalli R. , Ambikapathy A.
Published: December 2023

A complete and detailed literature evaluation concentrating on the detection and elimination of artifacts from EEG data was described in the preceding chapter. Issue-wise solution suggestions and their limitations were also studied, which eventually led to finding the gaps in the recommended task and scope of the study activity. In this chapter, the complete explanation of system design and its implementation is addressed. The principal objective of the proposed research is to identify and eliminate the undesired signals known as artifacts from the collected EEG data. This chapter spoke about the design of the system and its implementation. In this chapter specifics of EEG acquisition methods have been discussed. The initial stage in EEG signal processing is recording EEG data from the individuals. It also looks into the categorization of EEG data by sort. The obtained EEG data was sorted into two categories: normal and epileptic.
Sustainability-Driven Finance
Authors: Taneja Sanjay , Reepu
Published: December 2023

Green finance covers a wide range of financial products and services, which can be broadly divided into banking, investment, and insurance products. Examples of these include green bonds, green investment funds, and climate risk insurance and constitute green finance. Green finance is central to the overall discussion on sustainability of economic growth. Rapid economic development is often achieved at the cost of environment. In this study, the authors discuss the basics of green finance: green finance policy in the public domain, best practices from throughout the world, public policy in India, India's progress and challenges in the field of environmental finance, green bonds, green finance as an effective tool for sustainability, areas covered by green finance, green banking, green insurance, benefits of green finance, limitations of green finance, the status quo of green finance in the field of renewable energy, the market mechanism of green finance, types of green financial products, the role of policies in green finance, and the impact of green bonds on environmental protection.
The Impact of Corruption on Economic Growth in Tunisia
Authors: Kaddachi Hayet , Benzina Naceur
Published: December 2023

This chapter aims to examine the impact of corruption on economic growth in Tunisia between the years 1998 and 2018.Using time series data to obtain relationships of an empirical nature. The processing of time series data starts with checking individual series, and ADF and Zivot and Andrews tests help identify variables' stationarity. The mixed order of integration levels recommends using ARDL to obtain the long-run relationships between the variables. The estimation results confirm that corruption demoralizes and discourages private investment in the short and long run. In both the long and short run, the indirect impact of corruption is negative and insignificant for public spending. However, the interaction between human capital and the corruption perception index is positive and insignificant in the short run but negative and significant in the long run.
Organizational Citizenship Behavior and Employee Retention
Authors: Arora Shaina , Arora Nilesh
Published: December 2023

The study measures organizational citizenship to retain bank employees. The banking sector is a crucial growth driver in our service-based economy. Young bankers work in a proper environment, so they can handle their obligations and responsibilities successfully. Banks plan a large functional outlay based on growth, retention, and performance. This study collected data from 322 public and private bank employees using irregular examinations. Smart PLS Software 3.3.3 employed partial least squares for reliable review results. The model shows a positive relationship between employee retention and altruism, courtesy, conscientiousness, sportsmanship, and civic virtue. This study covered solely bank employees; thus, findings may vary. More research is needed to help companies retain top talent. Today, it's important to keep employees pleased and from looking elsewhere. Retention and organizational citizenship increase representational performance. The results show the impact of organizational citizenship on banking employee retention and performance growth.
Earthquake Multi-Class Detection Using Artificial Intelligence
Authors: P. Kavitha , B. Gopinathan , K. Roslin Dayana , G. Rathinasabapathi
Published: December 2023

The goal of the chapter on earthquake multi-magnificence detection and the use of synthetic intelligence is to discover and exhibit the usage of device learning and AI techniques for appropriately and efficiently detecting different lessons of earthquakes. The chapter seeks to offer a complete understanding of earthquake detection strategies and spotlight the capability of AI in advancing this subject. The goal is to present a detailed analysis of existing techniques and recommend novel AI-primarily based techniques that could enhance earthquake detection and category accuracy and timeliness. Conventional seismology strategies commonly focus on detecting earthquakes based on an unmarried seismic event. However, AI algorithms can investigate a significant quantity of information, which includes ancient earthquake facts, geological capabilities, and actual-time seismic signals, to become aware of patterns and classify earthquakes into multiple instructions.
State of Mental Health of Students in Universities
Authors: Ochanda Damaris Auma
Published: December 2023

This chapter presents the state of mental health of students in higher education institutions, help seeking behaviors, and available mental health support. Mental health problems have a profound impact on all aspects of the student's life at the individual, interpersonal, and even institutional level. The chapter also presents factors that have been associated with seeking help, including the social environment within the college/university. Colleges and universities offer a unique setting to address mental health problems among students, and therefore should develop programmes for mental health promotion and disease prevention for their students before they grow in severity and cause long-term problems.
Maladaptive Coping Mechanisms
Authors: Opotamutale Daniel Opotamutale , Albanus Fillemon Shekutamba
Published: December 2023

Mental health problems can affect many areas of students' lives, reducing their quality of life, academic achievement, physical health, and satisfaction with the college experience; as well as negatively impacting relationships with friends and family members. These issues can also have long-term consequences for students, affecting their future employment, earning potential and overall health. Stress is a commonly used concept in today's world due to the rapid advancements in almost everything (technologies and human evolution), and the world is becoming increasingly stressful. Unfortunately, students who struggle with depression and anxiety are reluctant to seek help. Higher education institutions can use the content of this chapter to develop appropriate targeted coping mechanisms and strategies which can be used by student counsellors to alleviate stressors among students thereby assisting in the enhancement of holistical health and wellness, and the academic excellence of students worldwide.
The Wellbeing Van
Authors: Paul Rithu , Kumar Aneesh , Suresh Sruthi
Published: December 2023

This book chapter takes a proactive approach to address stress by introducing a preventive measure, a relatively new approach implemented on college students in Bangalore, India called the “wellbeing van.” The chapter emphasizes the importance of not only managing and coping with stress, but also implementing strategies that promote overall well-being by tapping into the intrinsic factors of the student. The well-being van has shown promising results in reducing stress levels among students in academic institutions. Additionally, the chapter delves into the difficulties students face in maintaining social relationships, conforming to societal expectations, and finding their place. It provides valuable insights on how to foster healthy social dynamics and create supportive environments for students.
Emotional Burden Among Student Mothers
Authors: Oyoo Monica Anne Achieng
Published: December 2023

This study aimed to find out the emotional burden among student mothers, coping strategies, and measures that can be taken to reduce the emotional burden. This is qualitative study adopted a feminist and interpretive paradigm approach. Purposive and snowball sampling techniques were used to select 13 student mothers of ages between 14-26 years. A structured interview was used to collect data for the study. The findings showed that student mothers suffered emotional burden due to the overwhelming responsibilities and lack of understanding. The data also revealed that the student mothers coped with the emotional burden through acceptance, avoidance, sharing with friends and spiritual leaders, and planning. The implications and recommendations are discussed.
Mental Health Crisis at Higher Education Institutions
Authors: Hako Anna Niitembu
Published: December 2023

Mental health of students in higher education is a public concern and its impacts have heightened awareness of this issue. A conceptual review has been carried out to address the central question of this chapter—what are the mental health disorders that affect students in higher education institutions? Improved knowledge of aspects associated with mental health crises and also those that increase the mental well-being of students can provide a foundation for designing plans and specific interventions that can prevent poor mental health and ensure targeted support is available for students at increased risk. Therefore, the chapter recommends that universities adopt a proactive approach and implement innovative programs that can preempt students' misery
Mental Health Challenges in HigherEd Students
Authors: Ahuja Vivek
Published: December 2023

This chapter explores challenges faced by higher education students related to adjustment, stress, and mental health. It focuses on stress's impact on students' well-being and academic, physical, social, and psychological aspects during their university journey. The transitional phase from secondary school to higher education is examined, shedding light on unique challenges. Additionally, a conceptual framework is introduced, offering structured insights into these challenges within the higher education context. Implications for institutions, management, students, and parents are discussed. This chapter aims to comprehensively analyze stress and mental health challenges among higher education students, raising awareness and promoting strategies for a supportive environment, guided by the presented conceptual framework.
First-Aid Mental Health for the Pre-Medical Student
Authors: Lubin Robert , Katz Benjamin , Marants Michelle , Medney Mia , Rosin Charles , Sandler Dean , Schonberger Sophie , Sharabani Jamie R. , Sherry Jacqueline , Shteyman Gary , Tran Theodore , Weiss Elana , Zeltner Edward , Zisu Matthew
Published: December 2023

College is intended to prepare students to become successful members of society. However, the academic demands of college can trigger stress and mental health problems. College students are in a unique position where they have to juggle academics, a social life, and, often, part-time jobs. As a result, college students are a particularly vulnerable group when it comes to stress and mental health issues. One subset of students facing the struggles of college achievements are pre-med students. Pre-med students face numerous challenges that can negatively impact their mental health. The academic pressures, financial stress, lack of social support, and relationship challenges, among others, can increase the risk of depression, anxiety, and other mental health disorders. The team of contributing authors on this chapter will address mental health in the higher education environment. This chapter will present a program for educators, peer students, and staff to provide mental health assistance for the premedical student.
Teaching Students to Harness Their Anxiety and Maintain Well-Being in the Period Leading to and During Important Exams
Authors: Delange Ingrid R. C.
Published: December 2023

Standard-based tests are a common form of final assessment in secondary education worldwide, but they pose many challenges for students. They require not only academic competence, but also mental resilience, which is rarely instructed in school. This chapter argues for the inclusion of strong mental training during revision. for this, it will review the history and rationale of standard-based assessments, and how they relate to the political and social aspects of different countries. It will also examine the controversies and criticisms of this form of evaluation, and how it affects the students' emotions and perspectives. The chapter will then suggest some practical strategies that teachers can use in the classroom to foster a holistic approach to learning. These strategies include mindfulness exercises, collaboration activities, feedback mechanisms, and the facilitation of healthy habits.
Emotional Wellbeing of Students in Higher Education Institutions
Authors: Ajayi Oluwakemi Bolanle
Published: December 2023

The emotional well-being of students at higher education institutions was examined in this chapter. The study used a conceptual review as its framework, and data from published results presented in this chapter showed that most students in higher education institutions faced emotional challenges as a result of their new environment, financial challenges, academic-related stress, anxiety, and depression. Furthermore, many students in higher education are still adjusting to their new experiences and finding their fit in order to achieve in their academic pursuits. It is recommended that higher education institutions adopt innovative techniques to increase students' emotional wellbeing, such as boosting student awareness, building and designing a culture of wellbeing, and providing digital mental services.
Application of QGA-BP Neural Network in Debt Risk Assessment of Government Platforms
Authors: Li Qingping , Liu Ming , Zhang Yao
Published: December 2023

How to correctly understand the existence of local government debt, study its risk classification and impact, give full play to the “dual nature” of debt with a full-caliber indicator system, and avoid debt risks to the greatest extent. That is the research direction of this article. In order to improve the accuracy and efficiency of risk assessment and effectively reduce the debt risk of government platform companies, a risk assessment method based on optimized back-propagation (BP) neural network is proposed. First, the method uses quantum genetic algorithm (quantum genetic algorithm, QGA) to adjust and determine the initial weight and threshold of BP neural network and realize the optimization of BP neural network model parameter setting. Then, the QGA-BP debt risk assessment of government platforms is verified that it performs well in the debt risk prediction of government platform companies, and its prediction accuracy and prediction speed are improved.
Quality Characteristics of Cashew Apple Juice as Affected by Pre-Treatment Techniques
Authors: Babarinde G. O. , Afolabi F. O. , Balogun G. B. , Lawal Z.
Published: December 2023

Cashew apples deteriorate easily when kept for a few hours after plucking. The astringency of cashew apples has also limited its utilization and overall acceptability. This study, therefore, evaluated the effect of pretreatments on the quality of cashew juice. Fresh cashew apples were cleaned and pre-treated by blanching at 50 °C, 60 °C, 70 °C and 80 °C for 20 minutes and another batch of cashew apples was dipped in a brine of 5% concentration (w/v) at 80 °C for 20 minutes. Then, cashew juice was extracted from pre-treated apples and subjected to physicochemical, vitamins, minerals, anti-nutrient, and sensory analysis. The cashew apple blanched at 70 °C had the highest total solid, pH, and brix with the values 14.16%, 4.27, and 11.30 respectively. All these values differed significantly from the untreated samples except the brix. Samples blanched at 80 °C had the highest vitamins A and B1 (0.192 and 0.26 mg/100 g) and cashew apples blanched at 50 °C had the highest vitamins B2, B3, and C (0.68, 0.29, and 69.00 mg/100 g) which differed significantly from the untreated sample. The potassium, calcium, iron, and zinc ranged from 137.27 to 312.14 mg/100 g, 235.78 to 510.32 mg/100 g, 17.86 to 40.77 mg/100 g, and 0.22 to 0.55 mg/100 g, respectively. All treated samples had significantly higher mineral composition than the untreated cashew apple juice. The anti-nutritional factor ranged from 1.12 to 1.39 mg/100 g for total phenol, 0.12 to 0.28 mg/100 g for flavonoid, and 0.67 to 0.83 mg/100 g for tannin. Both treated and untreated cashew apple juice had no coliform. The result of the sensory evaluation showed that brine-treated juice had a higher acceptability value than other samples. Hence, pre-treatments of cashew apples enhanced the mineral and vitamin contents of the juice and increased the general acceptability.
Impact of Entrepreneurial Marketing on Performances of Small-scale Food Processing Firms in Kalutara District, Sri Lanka
Authors: Anjalee G. H. I. , Perera G. A. S. N. T.
Published: December 2023

Entrepreneurial Marketing (EM) represents an unconventional marketing strategy tailored for small businesses with limited resources. This research aimed to empirically investigate the impact of various entrepreneurial marketing dimensions (such as proactiveness, opportunity focus, calculated risk-taking, innovativeness, customer intensity, value creation, and resource leveraging) on the overall performance (a collective measure of efficiency, growth, profit, and owners’ personal goals) of small-scale food processing firms in the Kalutara District, Sri Lanka. Moreover, the study also intended to assess the impact of human capital variables (gender, age, experience, and education level) on the dimensions of EM in these small businesses. The data were gathered through simple random sampling from 100 small businesses operational for more than a year. The findings indicate that opportunity focus, innovativeness, customer intensity, value creation, and resource leveraging positively affected overall small business performance, whereas proactiveness and calculated risk-taking had a negative influence. Moreover, all human capital variables exhibited a significant and positive association with different EM dimensions at varying levels of significance. Notably, owners' experience and education level were positively linked to dimensions such as innovativeness, customer intensity, and resource leveraging. The study recommends the application of entrepreneurial marketing by small businesses to enhance sustainability and performance. Furthermore, enhancing the education and experience of business owners is advised, as it fosters the adoption of EM at the organizational level, thereby contributing to improved performance.
Hierarchical Component Model Approach on Tax Fairness, Public Governance Quality and Tax Compliance: A Mediating Role of Tax Morale
Authors: Bello U. , Dandago K. I. , Samaila I. A.
Published: December 2023

This study assesses the effect of tax fairness, public governance quality on tax compliance of MSEs in North-Eastern States of Nigeria through tax morale. The study population is 124,231 registered MSEs in North-Eastern states of Nigeria where sample of 527 MSEs was used. PLS-SEM was employed to ensure data analysis and hypotheses testing. Internal consistency reliability and validity checks were carried out to ensure that the measurement instrument is reliable and valid for data collection. The findings of the study revealed that direct assessment tax compliance is found to have been positively influenced by public governance quality and tax morale while, tax compliance was not significantly explained by tax fairness. Moreover, tax morale mediated the effect of public governance quality on tax compliance while no mediation was experience on tax system fairness and direct assessment tax compliance. Hence, the study contributed to the existing body of literature and tax authorities were adequately provided with an insight into improving tax compliance of direct assessment taxpayers through tax morale by public governance quality .
The Role of Social Entrepreneurs in Sri Lanka
Authors: Nimeshi G. K. S. , Surangi H. A. K. N. S.
Published: December 2023

In recent years, there has been a growing body of literature on social entrepreneurship, yet researchers in developing countries have not adequately explored this field. This qualitative study delves into the role of social entrepreneurs in Sri Lanka, examining how they operate and the factors influencing their choices. Grounded in social reality and aligned with social constructionist philosophy, the research engaged ten selected social entrepreneurs through interviews and applied thematic analysis to interpret the data. The findings reveal valuable insights into the strategies employed by social entrepreneurs in starting and managing their enterprises. Individual and social factors such as family background, experience, social networks, and religion significantly influence the decision to become a social entrepreneur. The study's developed model bridges subjective experiences of social entrepreneurs with existing literature, contributing to a deeper understanding of how social entrepreneurship is practiced and constructed.
Insights from Japanese Community-Supported Agriculture (CSA) for Building Resilient Local Food Systems in Sri Lanka
Authors: Esham M.
Published: December 2023

No abstract available
Standard Manufacturing Process of Agnipaka Guduchi Taila: A Sneha Kalpna
Authors: Bala Anku , Devi Abha , Kotecha Mita , Chaudhary Krutika Suhas
Published: December 2023

ABSTRACT

Background:

Nowadays, the use of herbal medicine is increasingly finding more relevance, especially when we are facing more challenges in the management of some chronic disease. The traditional herbal medical knowledge is scattered around the world at different levels and more in the indigenous people. The knowledge of traditional medicine is continuously being lost; hence, it needs scientific documentation of herbal medicine. The concept of Agnipaka is to enhance more potency in oil by Samskar and extract the fat-soluble active principle from drug to sneha.

Aim and Objective:

The objective of this study was to document step-by-step procedure of Agnipaka Guduchi Taila and to document preparation and pharmaceutical observations of Agnipaka Guduchi Taila using scientific methods.

Materials and Methods:

Agnipaka Guduchi taila was prepared using Chakrdutta Aaditypaka guduchi taila reference. It was a modified process of Aaditypaka guduchi taila.

Results:

The oil prepared from Agnipaka vidhi is light brown, odor is pleasant, and having greasy consistency.

Conclusion:

The current study reflects standardization and it was an attempt to describing standard procedure where Aaditypaka guduchi taila is modified as Agnipaka guduchi taila.
Management of Gridhrasi (Sciatica) using Ayurvedic Panchakarma Therapies
Authors: Narine Avvinish , Chandrakar Vinita , Vedpathak Surendra
Published: December 2023

ABSTRACT

Gridhrasi is one of the most common Vata disorders usually characterized by low back pain and discomfort with pain radiating to the lower limbs, the symptoms closely relate to those associated with the sciatic nerve. The treatment in modern medicine is only symptomatic and provides temporary relief in the symptoms of pain, etc. A 36-year-old male came to the Ayurvedic hospital with lower back pain radiating to bilateral lower limbs for 8 days and was diagnosed with having Gridhrasi. The treatment plan included Shamana Aushadi of Ashwagandha, Shatavari Churna, Shankha Bhasma, Trayodashang Guggulu, Dashmool Kwath, Vatavidwans Rasa, Mahanarayan Taila, and Panchakarma procedures including Sarvanga Abhyanga and Swedana, Patra Pinda Potali Swedana, and Erandmuladi Niruha Basti. The Shamana Aushadi was given for 1 month duration while the procedures were done for 16 days. A symptomatic assessment of the patient was conducted at the onset, in the middle and at the end of the treatment and the outcome was satisfactory with quality of life of the patient significantly improved, from being able to walk 100 m in 10 min with pain, he was able to walk the 100 m in 3 min without stopping and there was the absence of pain radiating from the low back to lower limbs, also the Visual Analog Scale improved from 6\10 to 1\10. The Ayurvedic Panchakarma therapies and the internal medicines are effective in the management of Gridhrasi (Sciatica), but since this is a single successful case study, it can be conducted on a larger population to create a baseline.
Individualized Homeopathy in the Treatment of Diabetic Neuropathy with Hyperuricemia: An Evidence-based Clinical Case Report
Authors: Nahar Laijun , Choubey Gurudev
Published: December 2023

ABSTRACT

Diabetic neuropathy (DN) is a common complication of long-standing cases of diabetes mellitus. If this condition is not treated in time, it may lead to clawing of the toes, neuropathic ulcers, Charcot foot, erectile dysfunction, etc., which are more dangerous for health. The prevalence of hyperuricemia was quite high in type 2 diabetes patients. Homeopathy offers safe and effective management of these cases with its holistic approaches. This article presents a case of DN associated with hyperuricemia, reported with complaints of tingling, prickling, and numbness sensations on both sides of the extremities, mainly the left hand and left leg, for the last 4 months. She has also suffered from pain in both knee joints for the last 4 months. The laboratory report of the case at baseline and after treatment was taken as objective evidence. The outcome was assessed using the DN symptom score, the Measure Yourself Medical Outcome Profile 2 score, and the outcome related to the impact on daily living (ORIDL) score. This case report demonstrates a positive result of individualized homeopathic medicine in the management of DN with hyperuricemia within a plausible time frame.
Ayurvedic Management of Polycystic Ovarian Disease
Authors: Anshul  , Bhola Sonal , Vashisht Rishi , Mehta Ashish
Published: December 2023

ABSTRACT

Polycystic ovary disease (PCOD) is an endocrinal disturbance affecting 4%–20% of females of reproductive age worldwide. A 35-year-old female patient presented with irregular and painful menstruation along with other symptoms such as hyperacidity and laziness for 9 months. The patient was diagnosed with PCOD based on Rotterdam criteria and the International Federation of Gynecology and Obstetrics (FIGO) criteria. Aim was to manage patients with Ayurvedic medications. Medicated water of Shunthi (Zingiber officinale Rosc.), Dhanyaka (Coriandrum sativum Linn.), and Guduchi (Tinospora cordifolia Wall. ex Seringe) was given for 10 days, Shankha Bhasma 500 mg and Arogyavardhini vati 500 mg ½ h before meals with water three times a day, and stomed tablet 1 g after 15 min of meals thrice a day for 10 days. After 10 days, menstruation happened. Slowly, all symptoms were completely relieved. Final follow-up was done after 3½ months of treatment at which ultrasonography finding has no abnormalities detected. It can be concluded that PCOD can be successfully managed by Ayurvedic management.