bluuebunny/crossref_metadata_2025 huggingface dataset:
Nexus between country governance, globalization, sustainable development policy, fair trade and economic sustainability: a mediation-moderation approach
Authors: Wang Hanning , Li Shunyi , Zhang Hongfeng
Published: August 2024

Sustainable development of the economy is the goal of every country in the world. The eco¬nomic growth of China is accepted worldwide, but the Chinese economy also suffers from an economic crisis. The role of the Chinese government is important for chinses businesses and the economic sus¬tainability of the country. The theoretical framework of this study is designed to determine the impact of globalization and sustainable development policy on fair trade and economic sustainability in China. A questionnaire based on Likert scale were employed with a random sampling technique to collect the cross-sectional data for this research and 1094 responses were collected at the rate of 55%. AMOS sta-tistics tool was employed for the findings of this study based on a research questionnaire. The research concludes that globalization and sustainable development policy have a significant impact on fair trade and economic sustainability in China. This study introduced a new framework related to economic sus¬tainability in the body of knowledge. The theoretical and practical implications of this study have signif¬icance for literature and practitioners in China to achieve sustainability in the economy. The research is novel as it highlighted the importance of globalization and sustainable development policy for fair trade and economic development in China. Accordingly, it would be helpful for the policy makers to have reli¬able decisions for sustainable development and promotion of fair trade.
Heritage and carob trees: Where the monumental and landscape intersect
Authors: Petino Gianni , Chinnici Gaetano , Privitera Donatella
Published: August 2024

We aimed to explore the significance of monumental trees as elements of heritage and their role in interpreting landscapes. Monumental carob trees, characterized by their impressive size and long lifespan, serve as valuable sources of information for understanding the territories they inhabit and the human societies that have preserved them over time. Over the centuries, these carob trees narrate the tale of Mediterranean landscapes, akin to stone monuments, making them authentic natural and cultural treasures of the Mediterranean region. Our findings, based on fields observations in Sicily (Italy) and GIS analysis, suggested that the landscape is an enabling medium through which traditional culture is preserved, local identities are transferred, and rural heritage is acknowledged. We unfold a conception of landscape based on visual, inherited traditional agricultural practices, valued rural heritage, and territorial identity.
Analyzing factors of daily travel distances in Japan during the COVID-19 pandemic
Authors: Mori Masaya , Omae Yuto , Kakimoto Yohei , Sasaki Makoto , Toyotani Jun
Published: August 2024

The global impact of the COVID-19 pandemic is widely recognized as a significant concern, with human flow playing a crucial role in its propagation. Consequently, recent research has focused on identifying and analyzing factors that can effectively regulate human flow. However, among the multiple factors that are expected to have an effect, few studies have investigated those that are particularly associated with human flow during the COVID-19 pandemic. In addition, few studies have investigated how regional characteristics and the number of vaccinations for these factors affect human flow. Furthermore, increasing the number of verified cases in countries and regions with insufficient reports is important to generalize conclusions. Therefore, in this study, a group-level analysis was conducted for Narashino City, Chiba Prefecture, Japan, using a human flow prediction model based on machine learning. High-importance groups were subdivided by regional characteristics and the number of vaccinations, and visual and correlation analyses were conducted at the factor level. The findings indicated that tree-based models, especially LightGBM, performed better in terms of prediction. In addition, the cumulative number of vaccinated individuals and the number of newly infected individuals are likely explanatory factors for changes in human flow. The analyses suggested a tendency to move with respect to the number of newly infected individuals in Japan or Tokyo, rather than the number of new infections in the area where they lived when vaccination had not started. With the implementation of vaccination, attention to the number of newly infected individuals in their residential areas may increase. However, after the spread of vaccination, the perception of infection risk may decrease. These findings can contribute to the proposal of new measures for efficiently controlling human flows and determining when to mitigate or reinforce specific measures.
Establishment of a method to measure the intracellular potassium ion concentration of brain tissue using a simple device
Authors: Iwamoto Takaya , Fujita Minori , Futamata Yukiko , Okada Teruki , Morinaga Ryuta , Nishi Airi , Kinjo Toshihiko , Kawada Koichi , Uno Kyosuke , Kuramoto Nobuyuki
Published: August 2024

Intracellular potassium ion (K+) concentration is higher than extracellular K+ concentration. Some cells maintain intracellular potassium levels by taking up extracellular potassium. However, investigating these details requires techniques to measure intracellular potassium concentrations. We established a method to easily measure intracellular potassium concentrations using a simpler electrode. The LAQUAtwin K-11 was capable of linearly quantifying potassium concentrations and was not affected by cellular constituents other than nucleic acids; however, it did not tolerate low temperatures. Interference caused by a high concentration of nucleic acids was eliminated by the addition of cations. It was also suggested that the concentration of nucleic acids in the cell suspension was not sufficiently high to interfere with the measurements. Intracellular potassium concentrations increased and decreased in response to extracellular potassium concentrations. Exposure to valinomycin did not decrease the potassium concentration, suggesting that re-uptake of the potassium released outside the cells occurred immediately. Additionally, potassium concentrations could be measured in the brain tissue homogenates using the device. This measurement method can track the relative changes in potassium concentration in cells under various conditions and in tissues of various disease models.
The Miocene (Aquitanian-Tortonian) of North-Eastern Tunisia
Authors: Ghazzay-Souli Wissal , Gaaloul Nadia
Published: August 2024

In the Mediterranean Sea, the Cenozoic corresponds to a compressive period represented by folding phases and basin filling. The Tertiary structural development of North Eastern Tunisia is characterized by two tectonic phases: the Oligo-Miocene rifting and the late Miocene compression. These tectonic events came along with global eustatic and climatic changes. In order to identify the response of the Miocene sedimentary deposits in north-eastern Tunisia to global events, five wells from the Gulf of Hammamet and three outcrops from the surrounding area, were studied. A multidisciplinary approach integrating biostratigraphy, facies analysis, interpretation of depositional environments, and structural setting has been adopted. Thus, three transgressive events were recognised during the lower to middle Miocene, and an eustatic fall is identified in the early Serravalian–late Langhian.
Generative AI in Curriculum Development
Authors: Tanweer Mariam , Ismail Aisha
Published: August 2024

Generative artificial intelligence (GAI) is becoming a crucial influence in different industries, particularly transforming education through the reshaping of curriculum creation. This chapter discusses how GAI can improve educational inclusion and comprehensiveness by providing personalized, customized and adaptive learning experiences. The framework in this chapter provides a structured approach to integrating GAI into curriculum design with the goal of creating dynamic, flexible, and personalized educational paths. By utilizing advanced machine learning and natural language processing, GAI enables educators to create personalized and tailored learning modules, promoting an inclusive educational setting. The discussion in this chapter highlights the crucial significance of GAI in developing educational methods and curriculum, establishing a new model for future learning environments.
Generative Artificial Intelligence (AI) on Sustainable Development Goal 4 for Tertiary Education
Authors: Matthew Ugochukwu Okwudili , Oyekunle David Oyewumi , Akpan Edidiong Elijah , Oladipupo Matthew Abiola , Chukwuebuka Ejiofor Stanley , Adekunle Temitope Samson , Waliu Ajibola Olaosebikan , Onumaku Victory Chibuike
Published: August 2024

Emerging themes of Society 5.0 are the coexistence of humans and robots in a collaborative work environments, particularly in education. With digital transformation and newfound collaborations between people and technology, Society 5.0 seeks to create a sustainable people-centered community. Advancements in robotics and AI research have been used in several areas of life in the modern digital society to address a wide range of problems. In spite of the large body of research on human-robot cooperation on low- and high-level tasks related to robot educational advancement, the current study concentrated on the cooperation between humans and robots in the fields of education bringing up the Research and Education Network (REN) for universities as a way to capitalize on human development. The study identified significant issues with the current REN and made an effort to resolve them through human-robot collaboration by tackling them from an organizational and pedagogical AI-robotic instructional application in light of the technological prospects highlighted in the study.
Transforming Assessments With Generative AI
Authors: Ismail Aisha , Tanweer Mariam , Farooq Sadia
Published: August 2024

The potential of generative AI is evident in every field of life and education is also experiencing a paradigm shift. Generative AI is opening new ways of assessment and the tools that can create engaging and innovative contents. Through the promotion of adaptation and customization, generative AI is positioned to bring about a significant transformation in the educational process. This chapter sheds light on the significance of generative AI in assessment of higher education. It offers valuable insights into the possibilities for change and improvement in the field of educational evaluations, indicating its capacity to revolutionize the future of education.
Analysis of Thermal Performance of Water-Based Nanofluid in a Heat Exchanger
Authors: Yadav Laxmikant , Tyagi Pranjal , Verma A. K. , Poddar Awdhesh Kumar , Singh Ramesh Kumar , Thakur N. S.
Published: August 2024

With increasing concerns about the energy efficiency and sustainability of thermal processes across various applications, it is an ideal time to focus on using compact heat exchangers. The thermo-physical characteristics of the working fluids are one of the many causes of inefficiencies in heat transfer systems. By enhancing the working fluid's thermo-physical qualities with the addition of nanoparticles, this problem can be resolved. However, this solution also introduces other undesirable phenomena, such as abrasion and clogging. The purpose of this work is to ascertain how introducing nanoparticles to the base working fluid affects the heat transfer rate and overall heat transfer coefficient in fin-and-tube heat exchangers.
Experimental Analysis of Phase Change Materials Supported With Hemp-Stem-Derived Biochar for Enhanced Solar-Thermal Energy Conversion and Storage
Authors: Ponnusamy Prasanth , Seenivasan S. , Ravivarman G. , Sathiyasekar K. , Girimurugan Ramasamy
Published: August 2024

This research focuses on converting hemp stalk into Biochars with 3-dimensional hierarchically directionally dependent pores through a controlled carbonization. These Biochars serve as bolsters for polyethylene glycol to create shape-stable composite PCMs. The research reveals that CPCMs using hierarchically directionally dependent hemp-stem-derived Biochars, attained at 1073 K, exhibit a high PEG1000 rate of loading, considerable heat transfer of latent heat and propitious thermal resistance due to their extensive area of this surface and directionally dependent pores. Furthermore, the SS-Composite PCM based on biochar on demonstrates notable photonic absorption capability, achieving a peak efficiency of solar to thermal conversion 96.77%. The distinct directionally dependent structure of SS-Composite PCMs is apparent in their various thermal conductivities in both the direction of transverse and longitudinal. This improves the effective utilization of Biochars but also provides SS-Composite PCMs with exceptional performance for solar-thermal conversion and storage systems.
Harnessing Green Composites for Energy Efficiency in the Era of Industry 4.0
Authors: Khan Ubaid Ahmad , Srivastava Anshuman , Asthana Nidhi
Published: August 2024

In Industry 4.0 era, green composites transform various industries by merging sustainability with cutting-edge technology, replacing toxic materials with biodegradable alternatives. These composites, made from natural fibers and biodegradable polymers, offer renewability, low density, and cost-effectiveness, addressing environmental concerns and uncertainties in petroleum supply. Biopolymers sourced from natural sources like plants and animals provide environmentally sustainable alternatives to traditional fossil fuel-based polymers, offering unique properties for various applications. Natural fibers, including plant-based, animal-based, and mineral-based, offer renewable and versatile options for textiles and industrial use. The global market for green composites is growing, driven by industries like construction, automotive, and packaging. Despite challenges, green composites offer economic growth and social progress, with ongoing efforts focusing on innovation and responsible resource management to drive positive change.
Green Synthesis of Calcium Carbonate-Zinc Oxide Nanocomposites (NPs) Methodology, Characterization, and Antimicrobial Property Evaluation
Authors: Sampath Kumar L. , Madhu Kumar K. , Hariharan P.
Published: August 2024

This chapter presents an innovative approach to synthesizing calcium carbonate-zinc oxide (CaCO3-ZnO) nanocomposites using a green synthesis method. Utilizing silk fibroin wash water, this environmentally friendly technique enables the formation of stable nanocomposites without harmful chemicals. Detailed characterization confirmed the successful synthesis, composition, and structural properties of the CaCO3-ZnO nanocomposites. The antimicrobial activity tests demonstrated significant antibacterial activity against common pathogens. In the MTT assay, green synthesized NPs were administered at varying concentrations, showing less than 50% inhibition, indicating no significant cytotoxicity. The findings highlight the potential of CaCO3-ZnO nanocomposites for biomedical and dental applications, offering a sustainable alternative for antimicrobial agents. This chapter underscores the importance of green synthesis in advancing nanotechnology and provides insights into the future applications of nanocomposites in healthcare.
AI Redefining Healthcare Documentation for Tomorrow
Authors: Saxena Rahul , Katage Goutami , Kumar Chandan , Pathan Nawaj Mehtab , Bargir Mohammadazar Nisar
Published: August 2024

Healthcare providers heavily rely on accurate and comprehensive documentation to ensure the best possible care for patients, plan treatments, and conduct research. However, traditional documentation methods are often time-consuming, prone to errors, and generate massive amounts of paperwork. Fortunately, AI has the potential to revolutionize healthcare documentation and streamline the process for healthcare providers. AI can automate various aspects of healthcare documentation, such as transcription, coding, and billing, by leveraging machine learning algorithms and natural language processing. AI-driven solutions can also enhance the accuracy and completeness of patient records by detecting patterns that may not be easily noticeable to healthcare providers. This can lead to more informed decision-making and personalized treatment plans for patients. AI can standardize and structure data, facilitating seamless information exchange between different healthcare systems and enhancing interoperability. Overall, the integration of AI in healthcare documentation holds significant potential for transforming healthcare delivery and offering more efficient, accurate, and integrated care.
Navigating the AI Frontier Transforming Electronic Health Records
Authors: Pathan Nawaj Mehtab , Saxena Rahul , Kumar Chandan , Bargir Mohammadazar Nisar
Published: August 2024

In today's era of rapid technological advancements, Artificial Intelligence (AI) has emerged as a transformative force across various industries, particularly in the healthcare sector. The integration of AI into Electronic Health Records (EHRs) has led to significant improvements in patient outcomes and operational efficiency. AI adoption in EHR systems has streamlined administrative tasks, allowing healthcare professionals to devote more time to patient care. This chapter explores the various applications of AI in transforming EHR systems and assesses their impact on healthcare delivery. AI enables healthcare providers to analyze large volumes of patient data to identify trends and patterns that may go unnoticed by human professionals, leading to improved patient outcomes through more accurate diagnoses and personalized treatment plans. Additionally,
Implementing a Secured Blockchain-Based EHR Management System With Remix IDE
Authors: Mahesh G. , Mishra Renu
Published: August 2024

In present era Electronic Health Record (EHR) acts very important role in medical field for maintaining a patient health record securely, efficiently, lossless which used to share the health information for the required stakeholders in the form of Insurance agents, pharmacists, medical staff, doctors where the information need to distributed only for designated people rather than trustless people such as hackers, they could use the biometric and other confidential nature of patients information for their money making businesses such as finger prints can be used for biometric duplicate, aadhar card details can be used for hacking purposes, so there required a decentralized, secured, trusted patient data management system for only trusted people, This technique can use the IPFS (InterPlanetary File System) along with the smart contracts for saving the digital information with huge integrity and also accessible globally for required person, here smart contract govern, control and used for traceable and visibility the past transaction of patient information in terms for diseases, their prescription and medical dosage took, and also recovery of disease can be noted in nodes for further decision taken by handling medical staff or can hand over to other specialist for further action to be taken in terms of changing the medicine etc. In this paper we proposed that using remix IDE how the data management of patient information can be implemented in terms of nodes and also providing proper information sharing among the stakeholders for their easy work.
Problems in the Performance Evaluation System
Authors: Kuruppu Chalani Lakshitha
Published: August 2024

This chapter aims to review the limitations encountered in performance evaluation systems, focusing on three main domains: problems with the evaluation methods, the evaluator, and the subordinate. Initially, the chapter discusses the drawbacks inherent in evaluation methods, encompassing both traditional and modern methods, such as checklist method, self-assessment method, essay appraisal method, critical incidents method, ranking method, paired comparison method, management by objectives, behaviorally anchored rating scale and computerized performance monitoring method. This chapter further carries out a comprehensive discussion on the problems related to the evaluator and subordinate while exploring various internal and external factors that influence the performance evaluation process. This chapter therefore contributes to enriching the readers' knowledge, relating to the limitations, factors, and practical aspects of performance evaluation systems, especially where organizations can strive to create fair, transparent, and effective performance evaluation.
Transforming Healthcare Research With Interoperability
Authors: Salunkhe Vishwasrao
Published: August 2024

The healthcare industry is at a transformative juncture due to the widespread adoption of electronic health records (EHR). However, interoperability between EHR systems remains a barrier, creating data silos that hinder research and compromise patient care. This chapter explores the role of interoperability standards and SMART on FHIR (fast healthcare interoperability resources) technology in revolutionizing healthcare research. By standardizing data exchange and enabling secure access to patient records, these advances unlock the potential of EHR data for research. Fragmented healthcare data impacts research and care coordination, leading to inefficiencies and potential errors. The author discusses the benefits and challenges of implementing HL7 FHIR, which facilitates seamless data sharing across systems. Key policy initiatives such as the 21st Century Cures Act and the Trusted Exchange Framework and Common Agreement (TEFCA) are crucial for promoting standardized data exchange.
The Importance of Food Care Services in Healthcare Organizations
Authors: Ramachandran Srinivasan , Seth Surabhi , Chaurasia Pratibha
Published: August 2024

The medicinal value of food has been known for many years. Intuitive eating offers satisfaction and considers the impact of food on the body. The association between genomic DNA and the impact of food on the body is called nutrigenomics. Nutrition care is central and can ensure patients' happiness, reduce duration of stay in hospitals, and prevent readmissions thereby reducing costs. Tools are available for nutritional assessment for people of all ages. Nutrition recommendations published by European Society for Clinical Nutrition and Metabolism (ESPEN), American Society for Parenteral and Enteral Nutrition (ASPEN) could guide. Health care needs a paradigm shift to person-centred care. The barriers in implementing the new methods of person-centred care need to be identified. Collectively, the engagement of hospital staff and patients' families is required for person-centred nutrition care. Interventions must be based on scientific evidence. New knowledge must be translated for application and health informatics can aid significantly. After all, healthy citizens are a nation's wealth.
Mediated by AI-Based Generative Re-Enforcement Learning and Work Attitude
Authors: Kant Shashi , Adula Metasebia
Published: August 2024

The primary goal of the chapter was to examine how, in the Ethiopian environment, an employee's work attitude and AI-based reinforcement learning function as mediators between their psychological intrinsic reward system and the perception of organisational support they receive from their employer. Based on their contribution to the GDP of the economy, the textile industries operating in Ethiopia's industrial parks were chosen as the study area. A quantitative research technique and explanatory research design were employed. A multi-phase sampling method was suggested. To assess discriminant and convergent validity, exploratory confirmatory analysis was carried out using AMOS software. It was discovered that the relationship between an employee's psychological intrinsic reward system and the organization's perceived organisational support was extremely poor in the absence of AI-based re-enforcement learning and the employee's work attitude as a mediator. Thus, the work attitude of employees and artificial intelligence (AI) function as a complete mediator.
AI in Marketing
Authors: Türkyilmaz Serap
Published: August 2024

In recent times, artificial intelligence (AI) has become an essential component in marketing, leading to the generation of large amounts of data and information, as well as advancements in management software and algorithms. The goal of artificial intelligence is to intelligently imitate human behavior. Artificial intelligence is a rapidly expanding technology, industry, and field of study. AI not only enhances existing marketing strategies, but also introduces innovative ways to deliver value to customers. AI also plays an important role in helping marketers manage marketing projects, support them, create content, and perform other tasks. Research shows that a lack of understanding of AI's capabilities and failed implementation efforts can create additional obstacles for organizations, including investment risks, ethical dilemmas, data issues, recruitment challenges, and negative environmental impacts. Despite being designed to reduce the workload of employees, human intervention is necessary in roles such as management, supervision, and innovation.
Revolutionizing Tourism
Authors: George Reena , Atluri Jaswanth
Published: August 2024

This chapter aims to explore the potential of generative (AI) in improving aspects of tourism experiences. Areas focused on include personalized recommendation systems, content generation for marketing purposes, virtual tour guides, and adaptive travel planning within the tourism industry. It focuses on customization approaches, incorporation of AR and VR technologies, and creation of real-time decision support systems. Moreover, its objective is to understand the ethical utilization of AI in the tourism industry, concerns regarding data privacy, and the incorporation of AI into current tourism infrastructure. It helps to delineate forthcoming research paths and emerging patterns, highlighting the possible influence of AI on the tourism sector and its future. Furthermore, it seeks to elucidate the socio-economic impacts of using AI in the tourist industry, examining its capacity to transform employment patterns, visitor characteristics, and methods for developing destinations. Finally, it promotes interdisciplinary discussion in influencing the future of tourism.
Accelerating Innovations
Authors: Thakur Anusha
Published: August 2024

In the hyperconnected era of accelerating demand for innovation, the need for advanced wireless technologies has gained significant traction. Smart antenna systems, regarded as the pillars of 5G technology play a pivotal role in wireless communication systems. Adaptation of the smart antenna technologies propels the optimization of costs and quality, along with the seamless realization of operational activities across the multi-technology wireless networks. Every generational advancement in wireless connectivity has led to the rise of new market players disrupting conventional technologies. With the rise of encrypted and long-range data in today's digital world, the leading players emphasize on expanding with the usage of 5G millimeter-wave radio frequencies unleashing several opportunities. The chapter discusses the key smart antenna applications and the technology landscape in different countries. It contemplates the different market entrants offering solutions paving the way for heavy reliance on the global market. The paper further discusses the revenue growth projections at the global and regional level for the smart antennas over the forecasted period.
Ultimate Deep Learning Acclimatization With Artificial Intelligence Drones for Environment Shield and Climate Change
Authors: Singh Bhupinder , Kaunert Christian , Jermsittiparsert Kittisak , Lal Sahil , Arora Manmeet Kaur , Raghav Anjali
Published: August 2024

The biggest and fast growing challenge in this era is climate change and it has been considered as a major threat that requires extraordinary remedy. AI drones as a solution to the climate crisis has been proposed in light of fast, real-time environmental data sets that it could learn from and inform better decisions. DL is a vast system made up of numerous interconnected devices that propagate data. The smart sensors can also be used in the forest zones, where they will identify temperature, humidity and sound patterns i.e., how many peoples are visiting that area by gathering data. It could also help in predictive analytics and automating sustainable practices that will lead us to a greener and cleaner future. This chapter systematically explores the integration of the deep learning and AI in defining a novel outlook to overcome environment dilution and climate change.
Advanced AI-Based System for Precision Oil Spill Detection in Marine Environments
Authors: Lalitha S. D. , Senthilkumar S. , Praveen Kumar B. , Jambulingam Umamageswaran , Anish T. P. , Kalpana A. V.
Published: August 2024

Oil spills threaten marine ecosystems, demanding precise detection methods. This paper introduces an AI-based system for accurate and timely oil spill detection in marine environments. The system integrates satellite imaging, unmanned aerial vehicles (UAVs), marine sensors, and IoT devices. It employs multispectral and hyperspectral imaging, synthetic aperture radar (SAR), and high-resolution cameras to detect oil spills. Machine learning algorithms enhance accuracy by distinguishing oil slicks from natural phenomena. Autonomous UAVs and sensor-equipped buoys provide real-time data transmission and analysis, enabling swift response efforts. This comprehensive system offers a reliable solution for monitoring and mitigating the impact of oil spills on marine ecosystems.
Issues and Challenges of Blue Economy With Reference to Marine Environment Conservation
Authors: Yashasvi Vaishnavi , Singh Ruchir
Published: August 2024

With subjects relating to the ‘blue economy' gaining in popularity, there is an increasing need for a comprehensive approach to incorporate this field of study into higher education. The term ‘blue economy' relates to all economic activities involving oceans, coasts and seas, and applies to sustainable development as well, specifically the United Nations' SDG14. This chapter delves into the exploration of India's Blue Economy analysing the opportunities and challenges it presents for fostering sustainability and resilience. As India seeks to harness the untapped potential of its coastal and marine resources, the chapter examines the various opportunities that the blue economy provides for economic development, job creation and technological innovation. Further more the paper explores policy implications and potential strategies to overcome these challenges advocating for comprehensive and integrated approach that involves collaboration between government, industry and local communities.
Educational Tourism
Authors: Selvakumar P. , Seenivasan S. , Raha Shrinwantu , Ravikumar S. , Gandhimathi S.
Published: August 2024

Educational tourism, also known as edutourism or educational travel, is a form of travel that combines learning with tourism. It involves visiting different locations to learn about their culture, history, environment, and people. This type of tourism has gained popularity in recent years as people seek more meaningful and enriching travel experiences beyond traditional sightseeing. One of the key aspects of educational tourism is its focus on learning and personal growth. Travelers engage in activities such as guided tours, workshops, lectures, and hands-on experiences that provide insights into the local way of life. For example, visiting archaeological sites with a knowledgeable guide can offer a deeper understanding of ancient civilizations and their contributions to modern society. Another significant component of educational tourism is its interdisciplinary nature. Travelers can explore a wide range of subjects including art, architecture, science, ecology, sociology, and anthropology. Additionally, educational tourism contributes to sustainable tourism practices.
Human Resource Challenges and Opportunities in the Indigenous Khadi Handloom Sector for Textile Tourism
Authors: K. Nikhilraj , Thomas Joby
Published: August 2024

The Khadi handloom sector is an integral part of India's textile industry. This chapter explores the challenges and opportunities in the Khadi handloom sector, focusing on human resource management strategies to empower local communities and promote sustainable textile tourism. To address this issue, this study investigated the challenges faced by the indigenous Khadi handloom sector in Kerala concerning textile tourism, using a qualitative research methodology. A purposive sampling method was employed to gather data, and a structured questionnaire was administered to 120 weavers from four different textile weaving centers in Northern Kerala. The findings of this study reveal that textile business hubs require effective marketing strategies to enhance textile tourism. To address these challenges and capitalize on the opportunities, the study recommends investing in skill development and training programs, modernizing infrastructure, implementing branding and marketing initiatives, and fostering collaborative efforts between the government and local communities.
Resistivity as a Witness of Local Crystal Growth Conditions
Authors: Soukhojak Andrey , Chung Gil
Published: August 2024

A detailed knowledge of the growth front geometry during physical vapor transport (PVT) growth of SiC single crystals is beneficial to achieve high quality n+ SiC substrates for power device applications. In this report we show how mapping of resistivity in SiC wafers can shed light on local growth conditions, which are very difficult-to-study in situ. We consider both thermodynamic quantities (absolute temperature T and partial pressure pN₂) and geometric characteristics of the growth surface relevant to growth kinetic parameters, namely atomic terrace width and atomic step velocity. Specifically, we show how an elevation map of the growth surface can be reconstructed from a spatially-resolved measurement of resistivity in a SiC wafer by integrating the spatial derivative of elevation with respect to the basal plane, which is assumed to be related to local resistivity through dependence of non-equilibrium nitrogen incorporation on the atomic step velocity.
High-Speed Milling of Hardened AMS 6260 Alloy Using Radius End Mill (Effect of Cutting Conditions on Flank Wear and Surface Roughness)
Authors: Kawasaki Kazumasa
Published: August 2024

AMS 6260 alloy is a nickel-chromium-molybdenum steel containing Ni, Cr, Mo, with Fe as the main component, and is one of AMS (aerospace materials specifications) in the United States. This material has high hardenability and high toughness. For this reason, it is used as a material for parts that require high toughness, such as gears in aircraft engines. However, while AMS 6260 alloy after heat-treatment has high hardness, it significantly reduced machinability. Therefore, it is extremely difficult to achieve high efficiency and high accuracy in the cutting process of AMS 6260 after heat-treatment. In this paper, the experimental milling of the hardened AMS 6260 alloy after heat-treatment is conducted under some cutting conditions using a coated cemented carbide radius end mill, and the effect of cutting conditions on the flank wear and surface roughness is investigated. As a result, optimal cutting conditions on the tool wear and surface roughness were clarified.
Vertical Current Transport in Monolayer MoS2 Heterojunctions with 4H-SiC Fabricated by Sulfurization of Ultra-Thin MoOx Films
Authors: Panasci Salvatore Ethan , Schiliro Emanuela , Cannas Marco , Agnello Simonpietro , Koos Antal , Nemeth Miklos , Pécz Béla , Roccaforte Fabrizio , Giannazzo Filippo
Published: August 2024

In this paper, we report on the growth of highly uniform MoS2 films, mostly consisting of monolayers, on SiC surfaces with different doping levels (n- SiC epitaxy, ~1016 cm-3, and n+ SiC substrate, ~1019 cm-3) by sulfurization of a pre-deposited ultra-thin MoOx films. MoS2 layers are lowly strained (~0.12% tensile strain) and highly p-type doped (≈4×1019 cm−3), due to MoO3 residues still present after the sulfurization process. Nanoscale resolution I-V analyses by conductive atomic force microscopy (C-AFM) show a strongly rectifying behavior for MoS2 junction with n- SiC, whereas the p+ MoS2/n+ SiC junction exhibits an enhanced reverse current and a negative differential behavior under forward bias. This latter observation, indicating the occurrence of band-to-band-tunneling from the occupied states of n+ SiC conduction band to the empty states of p+ MoS2 valence band, is a confirmation of the very sharp hetero-interface between the two materials. These results pave the way to the fabrication of ultra-fast switching Esaki diodes on 4H-SiC.
Confirmation of the Growth Mechanism of the Buffer Layer in Epitaxial Graphene on SiC
Authors: Prudkovskiy Vladimir S. , Templier Roselyne , Moulin Alexandre , Troutot Nicolas , Gelineau Guillaume , Huet Stéphanie , Le Van-Hoan , Mony Karine , Lapertot Gérard , Delcroix Mathieu , Caridroit Simon , Barbet Sophie , Widiez Julie
Published: August 2024

This study substantiates the epigraphene formation theory on SiC, presenting it as freestanding graphene during thermal decomposition epitaxy. It was found that cool down process is responsible for the formation of the graphene buffer layer. Additionally the capping capabilities of the buffer layer have been evaluated using Raman spectroscopy and AFM measurements.
GaN Cap UV Spectroscopy Assessment in AlGaN/GaN HEMT
Authors: Calabretta Cristiano , Piluso Nicolo , Chauveau Hyon Ju , Roy Emmanuel , Iatosti Cristophe , La Via Francesco , Severino Andrea
Published: August 2024

This work discusses the use of gallium nitride (GaN)-based solid-state devices for high-power, high-frequency, and high-temperature technology. The article presents the results of an investigation into the Al fraction of AlGaN as a function of GaN cap growth time through µ-Raman and µ-Photoluminescence (µ-PL) spectroscopy under λ=325 and 266 nm laser source. The data exhibit that the detected Al fraction decreases as the GaN cap layer size increases, consistently with the surface quantum well effect in the layer stack. The study confirms that the GaN cap layer is acting as a potential well and enables the design of a non-destructive and quantitative assessment of the grown thickness of the GaN cap layer through UV laser spectroscopy. The interpretation of the data also rules out the possibility of thermal migration of Al in the adjacent GaN layers during MOCVD growth.
Investigation on the Processability and Thermal Aspects of Date Palm Nanofiller/Polypropylene Biocomposites Processed via Melt Cast Film Extrusion
Authors: Shaikh Hamid M. , Alothman Othman Y. , Alshammari Basheer A. , Alhamidi Abdullah , Jawaid Mohammad
Published: August 2024

To preserve the environment and its resources for future generations, research must focus on alternate methods of producing materials that begin with an environmentally friendly and sustainable source. In view of this, nanosize reinforcing fillers were obtained from date palm agricultural waste without use of any toxic chemicals. Date nanofillers (DNF) with typical filler sizes ranging from 30-110 nm in width and 1-10 mm in length were obtained using rotary mechanical ball milling methods. This filler was then dry blended with the polypropylene (PP) to make a biocomposites thin film to study processability characteristics of this fillers. The loading of this filler was kept in the range of 1-5wt. % and film were melted cast through a slit height of 0.6mm. The resulting PP/DNF biocomposites films were subsequently analyzed by various analytical techniques to established structure property relationship. The change in thermal properties with loading of this filler was investigated using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). TGA study showed that the thermal stability of film samples improved up to 20 °C when compared to the neat PP, representing an 8% enhancement. While the DSC measurement indicated that the crystallinity of the highest filler loading sample reduced from 52.89% to 41.79% in comparison to the PP sample. The surface morphology of some samples shows the compact and smooth feature, indicating the incorporation of fiber fillers could improve the structure of polymer. Therefore, study gave some insight into the processing behavior of such composites, which may be useful in some packaging applications.
Doping Efficiency and Long-Term Stability of Various SiC Epitaxial Reactors and Process Chemistries
Authors: Spetik Radim , Novak Tomas , Soroka Miroslav , Vemolova Hana , Ctvrtlik Radim
Published: August 2024

Recent advances in SiC MOSFET technology allow significant reduction of on-state resistance of the active transistor cell, increasing thus relative contribution of the drift region comprised typically from epitaxial layer or stack thereof. Tight process control of thickness and doping of epitaxial layers is therefore gaining increasing importance. This paper summarizes some key factors and features of four state-of-the-art SiC epitaxial platforms and their impact on achievable epi parameters and wafer throughput.
Development of 200mm SiC Technology - Epitaxial Thickness Uniformity Observation on Different 8 Inch 4H-SiC Substrates
Authors: Anzalone Ruggero , Raciti Domenica , Arena Massimo , Calabretta Cristiano , Piluso Nicolo , Severino Andrea
Published: August 2024

The enlargement of 4H-SiC seed size from 150 mm (6 inch) to 200 mm (8 inch) is currently underway and 8 inches SiC substrate is now facing the market to switch the actual 6-inch technology to 8-inch technology. The aim of this work is to evaluate the influence on the epitaxial layer (using an epi growth campaign made of 21 consecutive runs) using substrates coming from different vendors (3 different suppliers adopted). The same epitaxial process and same reactor were adopted to grow all the samples. After the growth campaign, a difference of thickness uniformity between the three substrate suppliers was observed while no difference of doping uniformity was detected.
Floodplain Zoning and Mapping for Lower Kelani River, Sri Lanka
Authors: Iresh A. D. S. , Athapattu B. C. L. , Obeysekera Jayantha , Fernando W. C. D. K.
Published: August 2024

Flood risk mapping and floodplain zoning are emerging as practical tools to reduce flood damage. The study intended to develop floodplain zoning maps in the lower Kelani River basin using Flood frequency analysis and MIKE 11 modeling. Flood quantiles estimated for River gauging station at Hanwella and Lower Kelani basin have been used for the flood map developments. The river gauge at Hanwella to the estuary River strip has been considered for floodplain zoning using MIKE 11 modeling software. The hydrologic modeling was performed using MIKE 11 Nedbor Afstromnings Model (NAM), while the hydraulic modeling was performed using MIKE 11 Hydro-Dynamic (HD) model. MIKE 11 rainfall-runoff (RR) NAM calibration and validation Nash-Sutcliffe efficiency (NSE) results were 0.766 and 0.607, respectively. Similarly, coupled NAM and HD model on Mike-Zero platform calibration and validation NSE results were 0.917 and 0.871, respectively. The return period floods estimated to the Hanwella River gauge and Lower Kelani River basin have been availed to generate flood inundation maps. Finally, the flood plain zoning maps have been developed for the Lower Kelani River for 10-, 25-, and 50-year return periods. These maps can be use to limit cultivations and reduce crop losses during monsoons.
Use of Machine Learning Techniques to Predict the In-situ Concrete Compressive Strength using Non-Destructive Testing
Authors: Buddika H. A. D. Samith , Amarathunga A. M. R. S. , Menike D. C. D. , Dayaratna Erunika , Bandara S. , Yapa H. D.
Published: August 2024

Recently, machine learning-based prediction models have gained considerable popularity in predicting the compressive strength of concrete using results from Non-Destructive Testing (NDT) methods. This research considers NDT results from Rebound Hammer (RH) and Ultrasonic Pulse Velocity (UPV) tests for concrete samples with different concrete grades. 270 test samples were considered for the analysis using different machine learning techniques such as Multi-Layer Perceptron (MLP), Long Short-Term Memory network (LSTM), and Convolutional Neural Network (CNN). Concrete compressive strength results are obtained from Destructive Test (DT) results of the same for the purpose of labelling. Each model's performance is evaluated through the computation of the Coefficient of Determination (R²), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). The findings of this study underscore the potential of machine learning techniques in predicting concrete compressive strength based on Non-Destructive Test (NDT) results. The analysis findings suggested that employing UPV and RH data in conjunction with a trained MLP model to be an effective approach for accurately estimating the compressive strength of concrete specimens. The outcomes of the research serve as a valuable reference for researchers and industry practitioners alike when assessing in-situ concrete compressive strength through Non-Destructive Testing (NDT) methods.
Determining the Geographical Authenticity of Sri Lankan Regional Teas with Their Chemical Profile Using Artificial Neural Networks
Authors: Peiris T. U. S. , Walgampaya C. K.
Published: August 2024

Characterization of authenticity is a timely requirement in food control and safety. The geographically authenticated food products always realize high market prices and sustainable market share. The present study was conducted to investigate the potential of chemical profile in authenticating geographical differences of Sri Lankan regional black teas using artificial neural networks. Thirteen different geographical origins under eight different basses were evaluated and tea samples were chemically analyzed in monthly intervals for a period of one year. Training of feed-forward back propagation multilayer perceptrons resulted in accuracy rates ranging from 46% - 82%. Out of eleven chemical parameters considered for the study, Thea Rubigin and Total Colour are the most important discriminators of geographical origins. Other than that, Gereniol, Thea Flavin, Trans – 2 – Hexanol, Total Polyphenol and Amino Acids are also potential discriminators. The study concluded that the differentiation and classification of Geographical Origins (GOs) of Sri Lankan regional black teas is possible using the profile of chemical attributes and applying artificial neural networks. Finally, the data obtained demonstrates that it is possible to assign unknown samples according to their region of origin. Further development of this work could lead to a simple interface that could be used by brokers or exporters to identify the geographical origin of an unknown tea sample.