bluuebunny/crossref_metadata_2025 huggingface dataset:
A Impact Analysis of Digitalized Voting System on Voting Behavior and Democratic Consolidation in Nigeria
Authors: Agunyai Samuel Chukwudi , Ojakorotu Victor , Folusho Ayodeji
Published: December 2023

Election results in most African countries are hardly transmitted using digitalized devices. This has created room for suspicion and discrediting of electoral integrity in part of Africa. Citizens’ suspicion of the electoral process has not only made many African voters believe that votes hardly count, but it has significantly provoked tendencies of political apathy and indifference during elections in some African countries. Political apathy and indifference are partly responsible for the recruitment of mediocre persons to elective political offices, which in the long run, amount to bad governance. While the occupation of elective public offices by mediocre persons is antithetical to democratic consolidation, Africa’s electoral integrity largely depends on, and can only be sustained if election results are digitalized or transmitted in real time electronically. Although studies have extensively examined and identified factors such as competency, integrity, proven track records, vision, ideology, manifesto, and inducements, among others, as factors influencing voting choice or behavior, evidence is very little on how a digitalized transmission of election results, impacts on voting behavior and consolidates Africa’s democracy, using the elite theory. This article thus expanded knowledge on how a digitalized voting method influences voters’ decisions or choices using the qualitative method. Results indicated that a digitalized voting system could enhance vote count, public trust in election results, and the deepening of democracy in Africa. It concluded that a digitalized voting system has the potential to increase citizens trust in the electioneering process in Nigeria. This is a contribution to the general body of knowledge in e-voting and election administration.

Keywords: Behavior, Consolidation Democracy, Digitalize, Voting System
Integrated Effect of Organic Amendments and Chemical Fertilizers on yield of Groundnut and Soil Health Under Rainfed Condition
Authors: Arsalan Muhammad , Latif Abdul , Khan Madeeha , Syed Sairah , Ullah Rehmat , Ahmad Ijaz , Bilal Muhammad , Mahmood Muhammad Tariq , Ehsan Muhammad , Latif Rizwan , Ghaffar Abdul , Sanaullah
Published: December 2023

Although inorganic fertilizers increase the growth of crops, but their toxicity is the main concern due to their over utilization. To tackle this problem, the integrated application of organic amendment especially vermicompost, with NPK fertilizers would be a good choice. For this, the integrated effect of organic amendments including vermicompost (VC) and phosphorus solubilizing bacteria (PSB), and chemical fertilizers (NPK) on yield of groundnut and soil health, a field trial was done at the research area of Barani Agricultural Research Institute (BARI), Chakwal. The experiment was done with eight treatments in randomized complete block factorial design replicated thrice. The experimental data revealed that the treatment T8: Recommended dose of fertilizers (RDF) (NPK 20:80:60 Kg ha-1) + VC @ 4t ha-1 + PSB had superior effect on plant height (54.76.23%), number of plants per m2 (22.25%), number of pods per plant (61.90%), pod yield (83.25%) and haulem yield (86.02%) as compared to control. Similarly, a higher benefit cost ratio (BCR) was observed in T8 than rest of the treatments and control. Soil fertility indicators (OM, NO3-N, P and K) were improved, indicating the improvement in soil health with the combine application of VC, PSB and RDF. A combination of organic amendment, bio fertilizer, and inorganic fertilizer is necessary to optimize groundnut growth and yield attributes, as well as soil health.
SUSTAINABILITY IN PROPERTY TAXATION: AN APPLICATION FOR REVENUE STABILITY AND FAIRNESS PERSPECTIVES, THE CITY OF BUFFALO, NY
Authors: Ozmen Emre
Published: December 2023

The scholarly modeling of property tax has always posed a challenge, with two primary concerns to be addressed: first, maintaining sustainability in the collection, which is primarily a concern for local governments; and second, ensuring fair distribution, which is of greater concern for citizens. In today’s practices, assessment-based property tax increases unmatched expenses in bubble economies. There is a substitution problem in rapid falls, the tendency to not decrease the assessments gives way to black holes and opens the door to ghost cities. This paper proposes alternative approaches, aside from market/land value or last sold price, aimed at improving sustainability and fairness rates. The dataset examined is based on 93.7K records and 88 attributes for assessed value of properties within the City of Buffalo, the United States of America. Since the label (Total Value) is a numerical and continuous value, regression models are selected, where ensemble machine learning methods categorically work well with larger datasets, combined with weak learners, like decision trees. Stacked Ensemble led the least error for regression with 0.98 R2, followed by Gradient Boosting. Results show a 79% dominance of uncontrollable attributes, such as Land Value, Neighborhood, and Sale (last sold) Price, compared to controllable attributes, such as Total Living Area, Construction Grade, Second Story Area, and many others. This article suggests having a more balanced split between uncontrollable and controllable attributes would contribute to both sustainability and fair distribution.
RESEARCH ON FACTORS DETERMINING LOYALTY OF COSTUMERS OF COMPANIES PROVIDING ACCOMMODATION AND CATERING SERVICES IN LITHUANIA
Authors: Skačkauskienė Ilona , Jotkaitė Rūta
Published: December 2023

Changing technologies, increasing customer expectations and competition between organizations lead to the fact that the study of factors determining customer loyalty can become a suitable organizational solution for attracting, maintaining and minimizing turnover of consumers. Consumer loyalty is recognized as a strength that an organization can acquire, and at the same time, it ensures the continuity of operations due to the fact that loyal consumers significantly determine the profitability of the company’s activities. The article presents a study of the factors determining the loyalty of service users in the case of the accommodation and catering services sector, answering the problematic question – what factors determine the loyalty of consumers in the accommodation and catering services sector in Lithuania? After conducting a theoretical analysis, the factors determining the loyalty of service users were determined, and by applying the multi-criteria Analytical Hierarchy Process (AHP) method, the significance of the factors determining the loyalty of the customers used for this study in the Lithuanian accommodation and catering sector was determined.
Orbital Decay of Hot Jupiters due to Weakly Nonlinear Tidal Dissipation
Authors: Weinberg Nevin N. , Davachi Niyousha , Essick Reed , Yu Hang , Arras Phil , Belland Brent
Published: December 2023

We study tidal dissipation in hot Jupiter host stars due to the nonlinear damping of tidally driven g-modes, extending the calculations of Essick & Weinberg to a wide variety of stellar host types. This process causes the planet’s orbit to decay and has potentially important consequences for the evolution and fate of hot Jupiters. Previous studies either only accounted for linear dissipation processes or assumed that the resonantly excited primary mode becomes strongly nonlinear and breaks as it approaches the stellar center. However, the great majority of hot Jupiter systems are in the weakly nonlinear regime in which the primary mode does not break but instead excites a sea of secondary modes via three-mode interactions. We simulate these nonlinear interactions and calculate the net mode dissipation for stars that range in mass from 0.5M
⊙ ≤ M
⋆ ≤ 2.0M
⊙ and in age from the early main sequence to the subgiant phase. We find that the nonlinearly excited secondary modes can enhance the tidal dissipation by orders of magnitude compared to linear dissipation processes. For the stars with M
⋆ ≲ 1.0M
⊙ of nearly any age, we find that the orbital decay time is ≲100 Myr for orbital periods P
orb ≲ 1 day. For M
⋆ ≳ 1.2M
⊙, the orbital decay time only becomes short on the subgiant branch, where it can be ≲10 Myr for P
orb ≲ 2 days and result in significant transit time shifts. We discuss these results in the context of known hot Jupiter systems and examine the prospects for detecting their orbital decay with transit timing measurements.
First Emulsion γ-Ray Telescope Imaging of the Vela Pulsar by the GRAINE 2018 Balloon-borne Experiment
Authors: Takahashi Satoru , Aoki Shigeki , Iyono Atsushi , Karasuno Ayaka , Kodama Kohichi , Komatani Ryosuke , Komatsu Masahiro , Komiyama Masahiro , Kuretsubo Kenji , Marushima Toshitsugu , Matsuda Syota , Morishima Kunihiro , Morishita Misaki , Naganawa Naotaka , Nakamura Mitsuhiro , Nakamura Motoya , Nakamura Takafumi , Nakamura Yuya , Nakano Noboru , Nakano Toshiyuki , Nakazawa Kazuma , Nishio Akira , Oda Miyuki , Rokujo Hiroki , Sato Osamu , Sugimura Kou , Suzuki Atsumu , Torii Mayu , Yamamoto Saya , Yoshimoto Masahiro
Published: December 2023

We are developing the Gamma-Ray Astro-Imager with Nuclear Emulsion project, designed for 10 MeV–100 GeV cosmic γ-ray observations with a high angular resolution (5′/0.°08 at 1–2 GeV) and a polarization-sensitive large-aperture (∼10 m2) emulsion telescope for repeated long-duration balloon flights. In 2018, a balloon-borne experiment was carried out in Australia with a 0.38 m2 sensitive area and a flight duration of 17.4 hr, including 6.7 hr of Vela observations. Significant improvements compared with the 2015 balloon-borne experiment were achieved by a factor of 5, including both an increase in effective area × time and a reduction in the background contribution. We aimed to demonstrate the telescope’s overall performance based on detection and imaging of a known γ-ray source, the Vela pulsar. A robust detection of the Vela pulsar was achieved with a 68% containment radius of 0.°42, at a significance of 6σ, at energies above 80 MeV. The resulting angular profile is consistent with that of a pointlike source. We achieved the current best imaging performance of the Vela pulsar using an emulsion γ-ray telescope with the highest angular resolution of any γ-ray telescope to date.
Remote Work in Nursing: Facilitators and Barriers
Authors: Speroni Karen
Published: December 2023

The COVID-19 pandemic quickly accelerated the opportunity for those in many professions to work remotely. These virtual opportunities continue to be available to some nurses and other healthcare providers, but limited information exists in the literature about nurses’ perceptions of remote work. This article presents perspectives of nurses, most of whom worked remotely in some capacity, and who shared their perceptions on facilitators and barriers regarding remote work. These nurses also ranked both effectiveness of nurse’s remote work and of remote meeting participation for professional nursing governance, in their opinion. Top facilitators were organizational and technological support for both remote workers and those in the hospital setting required to interface with remote workers; time savings; and financial savings. The ability to work remotely contributed to work-life balance. Top barriers were a feeling of disconnectedness from the organization; ineffective technology; and lack of organizational support, including lack of leader presence. Opportunities exist for needs assessment of organizational support of remote workers, evidence to inform nurse types and tasks for remote and hybrid work, as well as remote leadership models.
The ANA Innovation Engine: Activating Innovation Through Education and Communities of Practice
Authors: Beaudet Oriana , Pesut Daniel , Lemberger Olivia
Published: December 2023

Nurses are leading and developing solutions to complex problems across healthcare. Through innovation, they can drive the future creation of additional innovative healthcare ecosystems and networks. The most recent Nursing Scope and Standards of Practice articulates the value of innovation to support approaches and methodologies that foster interprofessional collaborations to transform healthcare. Nurses must develop foresight and futures thinking leadership skills and advance creative ideas to design innovative 21st century healthcare systems. This article briefly reviews the vision, mission, and strategic initiatives of the ANA Enterprise Innovation Department and describes selected programs and strategies to support nurses as they actualize innovation leadership in contemporary healthcare contexts. Many opportunities for involvement are offered virtually. We conclude with a call to action to advance individual nurse-led innovation by seeking education, developing expanded skills, and joining the movement of nurses looking to reshape health, healthcare, and the nursing profession.
Belonging in Online Nursing Education
Authors: Taylor Breana , Zamaripa Christine , Stevens Jaime , Satre Maria
Published: December 2023

Belonging is a fundamental human need and prerequisite for higher-level learning. This sense of belonging in nursing begins during nursing education and coincides with the development of a professional nursing identity. Nurses who have a sense of belonging during their initial education typically develop a solidified professional nursing identity, are committed to the profession, and are less likely to experience burnout as nurses. Belonging is linked with retention; thus, fostering belonging may improve nursing retention among new graduate nurses. The extent to which online education affects a sense of belonging for nursing students and their future commitment to the nursing profession is not well understood. The purpose of this article is to explore belonging in online education, highlighting research within online nursing education where possible, and to review strategies to foster belonging in online nursing classrooms. Nurse educators are positioned to address barriers to belonging and implement strategies to foster a sense of belonging with their students. Future research is needed to examine benefits of a sense of belonging for students and professional nurses, related to educational delivery format, program level, and persistent impact on professional nursing practice.
Graduate Nurse Education Programs: Transition Pathway for Registered Nurse Employment
Authors: Russell Kylie , Coventry Tracey , Tamaliunas Sheralee , Juliff Dianne
Published: December 2023

Little is known about student nurse to graduate transition in Australia and internationally. Although countries maintain registration numbers, there is no account to distinguish between those successful or unsuccessful in attaining employment after earning the entry level degree for nursing. A recent pilot study utilised convenience sampling from two cohorts of graduating nursing students at an Australian university to understand newly qualified nurses’ employment pathways. This article describes the study methods, which included data collected via online survey to explore graduating nursing students’ engagement with the profession at the time of graduation. The study objective focused on the enablers and barriers experienced by graduating nurses to better understand graduate transition pathways for registered nurse career entry. Study findings highlighted a significant gap between graduating student numbers and employment gained, despite a looming global nursing shortage with our discussion confirming concerns supported by the literature. Registered nurse employment success mainly depended on gaining a graduate nurse program for transition to practice.
Internationally Educated Nurses’ Perceptions of Interprofessional Collaboration
Authors: Balakumaran Mahathevan , Balakumaran Jasmine , Cruz Edward , Innis Jennifer , Deer Natashia
Published: December 2023

Internationally educated nurses’ (IENs) transition to practice in a new country is facilitated by education programs, commonly known as “bridging programs.” IENs experiences and understanding of interprofessional collaboration, essential in today’s health care environment, is often overlooked in education and research. Therefore, this mixed methods study sought to understand the experiences of IENs enrolled in a practical nursing bridging program at an urban community college in Canada. Findings indicate a need to address IENs’ understanding of interprofessional collaboration in their entry-to-practice education to optimize their role in the receiving country’s health care system.
Demonstrating a Nurse-Driven Model for Interprofessional Academic-Practice Partnerships
Authors: Forcina Jill , Zomorodi Meg , Morgan Leah , Barrington Nikki
Published: December 2023

Patient surges related to the COVID-19 pandemic, combined with the pre-existing and worsening nursing workforce shortage, have exacerbated the need to implement strategies that build a pathway to expand the current and future nursing workforce. Ideal strategies connect education and practice, based on supply and demand for healthcare professional skills. NursingNow, a global campaign that includes a USA initiative, declared the mission to elevate nurses and has called for them to be agents of change by leading innovative solutions to existing problems. This article highlights two such nurse-led innovation exemplars that fostered the connection of education and practice to engage interprofessional students. We describe the development and implementation of these initiatives and accomplishments achieved. The discussion reviews issues around contracts, compliance, and accreditation; incentives for partnerships; and the development of a health professional student corps. The call to action invites nurses, as the largest healthcare workforce, to consider leadership roles in efforts to incentivize centralized solutions and ongoing academic-practice partnerships.
Représenter malgré tout
Authors: Cuvelier Alice
Published: December 2023

Les images sont inscrites dans des boucles rétroactives de production de sens et en s’intéressant à celles qui s’associent de près ou de loin à la science, on plonge dans une sémiotique qui flirte avec l’épistémologie des sciences et des techniques. Des images, certaines images, sont comme des armes dans la bataille contre l’hégémonie culturelle d’une pensée scientifique fondée sur le culte militaro-masculiniste du héros et de la compétition. Tirer les pelotes que nous offrent Lynn Margulis et les artistes qui se sont inspiré de ses recherches sur la symbiogénèse, c’est alors une tentative d’œuvrer à lutter contre l’impérialisme de la pensée néo-darwinienne et ses conséquences bio-politiques sur nos représentations de l’unicité de l’individu.
Quantifying the presymptomatic transmission of COVID-19 in the USA
Authors: Zhang Luyu , Zhang Zhaohua , Pei Sen , Gao Qing , Chen Wei
Published: December 2023

The emergence of many presymptomatic hidden transmission events significantly complicated the intervention and control of the spread of COVID-19 in the USA during the year 2020. To analyze the role that presymptomatic infections play in the spread of this disease, we developed a state-level metapopulation model to simulate COVID-19 transmission in the USA in 2020 during which period the number of confirmed cases was more than in any other country. We estimated that the transmission rate (i.e., the number of new infections per unit time generated by an infected individual) of presymptomatic infections was approximately 59.9% the transmission rate of reported infections. We further estimated that {at any point in time the} average proportion of infected individuals in the presymptomatic stage was consistently over 50% of all infected individuals. Presymptomatic transmission was consistently contributing over 52% to daily new infections, as well as consistently contributing over 50% to the effective reproduction number from February to December. Finally, non-pharmaceutical intervention targeting presymptomatic infections was very effective in reducing the number of reported cases. These results reveal the significant contribution that presymptomatic transmission made to COVID-19 transmission in the USA during 2020, as well as pave the way for the design of effective disease control and mitigation strategies.
A pavement crack synthesis method based on conditional generative adversarial networks
Authors: Yao Hui , Wu Yuhan , Liu Shuo , Liu Yanhao , Xie Hua
Published: December 2023

A Generative Adversarial Network (GAN) based asphalt pavement crack image generation method was proposed to improve the dataset size of the road images. Five open-source road crack datasets were leveraged to construct an image dataset, which contained two labels - transverse cracks and longitudinal cracks. The constructed dataset was used to facilitate crack detection and classification research by providing a diverse collection of labeled crack images derived from multiple public sources. The network structure of fully connected, convolutional and attention mechanisms based on the Conditional Generative Adversarial Network (CGAN) was used in this project. The purpose of this study was to train a generative model on selected categories of input pavement crack images and generate realistic crack images of those categories. We aim to tune the parameters of the GAN and optimize hyperparameters to improve the realism possibility of generated images. It also explored the generated images with different sizes and evaluated the performance of networks with different architectures. In particular, we analyzed the structural characteristics of conditional GAN. Results demonstrated that the Self-Attention Generative Adversarial Networks (SAGAN) model, which combines self-attention mechanisms with CGAN, can effectively address challenges related to limited crack image data and the inability to selectively generate images from specific categories. By conditioning the generator on category information, the SAGAN model was able to generate high-quality images while focusing on the target categories. Overall, the self-attention and conditional aspects of the SAGAN framework helped improve the generation of realistic pavement crack images.
Evaluation and Research on the Classification Training Mode of Animation Talents Based on Teaching Dynamics from the Perspective of New Liberal Arts
Authors: Ma Zhiyuan , Yue Xiao-Guang
Published: December 2023

The creation of new artistic forms is an important aspect of the classification of artistic construction. The training of animation talents should be based on the market demand for professionals in the animation industry. While emphasizing the training of professional characteristics, it is important to consider the cross-complementation of related disciplines. The animation major at the Zhongnan University of Economics and Law has taken the initiative to investigate the market. They started by addressing the challenges faced in the development of the animation major and focused on the classification training of animation talents within the newly established new art department. As a result, they have developed a new professional curriculum system, a system for cross-integration of different disciplines, and a practical training system. These initiatives have facilitated the classification of platforms, the integration of multiple disciplines, and the development and training of practical skills within the animation major. We are actively exploring and practicing a new training method for animation talents in the art department. Our goal is to train high-quality applied animation talents who can contribute to local economic and social development. By doing so, we aim to promote the coordinated development of the art department and the field of animation. In order to quantify the teaching effect, we introduced a dynamic method to model the teaching system. This model was mathematically established as a dynamic system. Through modeling and analysis, the data reflected the positive impact of educational innovation and reform on teaching, thereby demonstrating the effectiveness of our innovation and reform.
On Some Advantages of the Predictor-Corrector Methods
Authors: Ibrahimov Vagif , Yue Gabriel Xiao-Guang , Juraev Davron Aslonqulovich
Published: December 2023

Usually, all numerical methods are divided into two sets known as explicit and implicit methods. Explicit methods (EM) are used to find a solution to a problem directly, without requiring initial preparation. But when using the implicit method (IM), other methods can sometimes be employed. Implicit methods are known to be more accurate than explicit ones. Therefore, the question arises about finding the golden mean. To accomplish this, we utilize certain properties of the predictor and corrector methods. We take into account that in forecasting methods, we use EM. However, I will show here that in some cases, IMs can be used as correction methods. It is clear that the results obtained here are fully consistent with the theoretical ones. To address the aforementioned issues, we employ the initial value problem (IVP) for a first-order ordinary differential equation (ODE). Conventional methods compare various nanomaterials (NMs) using multi-step, extended, and hybrid approaches.
Leveraging Technology-Based Innovation for Business Model Innovation
Authors: Minz Nitish Kumar , Prakash Anshika , Shrivastava Swati , Nangia Richa
Published: December 2023

In an era marked by swift technological progress, this research delves into the pivotal role of technology-based innovation in propelling business model transformation. As businesses grapple with the need to stay competitive, traditional models are being reevaluated. Through an exhaustive exploration of case studies, theoretical frameworks, and industry trends, this chapter unravels how technology acts as a potent catalyst for reshaping business models. It dissects strategies and approaches embraced by organizations to seamlessly embed technology-driven innovations into their operational frameworks. The study rigorously assesses the potential advantages and hurdles linked with this integration and offers invaluable insights into the impending terrain of business model innovation within the digital sphere. By critically analyzing these elements, the study contributes to a heightened comprehension of how technology dynamically influences business models, charting a path for future progress, adaptability, and success in a rapidly evolving technological landscape.
“Queer English” and “Heteronormative German”
Authors: Zieglmeier Vroni
Published: December 2023

This chapter explores linguistic identity construction by L2 speakers in a multilingual context. It is based on an ethnographic field study about the indexical use of English in a queer community of practice (CofP), a queer activist group in Berlin. The chapter analyzes ethnographic interview data with members of the group, focusing on metapragmatic and metadiscursive statements. The main result is that in the group context, English and German are juxtaposed alongside a “queer” versus “heteronormative” dichotomy, leading to the use of English as constitutive of the members' and the group's cosmopolitan queer identity. More generally, the chapter combines 3rd wave variationist perspectives on linguistic indexicality with a contemporary approach to multilingualism and language contact and emphasizes the importance of including L2 speakers to the study of multilingualism and linguistic identity production in order to fully account for the plurality of multilingual experiences.
Embracing Advances in AI-Based Language Tools in EAP Programs
Authors: Danilina Elena , Le Pichon Emmanuelle
Published: December 2023

The chapter calls for a change in language teaching and learning methodologies to keep pace with recent technological advances. It acknowledges the prevalence of conversational artificial intelligence tools like Chatbots, including ChatGPT and Bing. Many students and teachers are already using these tools, albeit discreetly. Instead of ignoring or dismissing, the authors argue for their integration into teaching practices. They discuss both opportunities and challenges associated with the implementation of AI tools, considering the current debate surrounding their controversial use and the dominance of a monolingual orientation in English for Academic Purposes courses. By proposing a shift in current practices, the authors advocate for an asset-based, language-friendly, and technology-enriched pedagogy. This new pedagogical approach aims to promote learner autonomy, linguistic and cultural inclusion, and more individualized instruction. By implementing such a pedagogy, teachers can better meet the individual needs of their students leveraging the benefits of these technologies to enhance learning.
Cultivating Cultural Competence and Meaningful Bonds in the Virtual Classroom Using a Narrative Approach
Authors: Philip Selin , Mathew Shalini
Published: December 2023

The narrative theoretical approach to content delivery is a powerful tool for educators and students to cultivate their cultural competencies and meaningful connections in the virtual classroom. By utilizing this approach, students can gain a deeper understanding and appreciation for their peers' diverse perspectives and experiences while nurturing community and belonging among themselves. Drawing upon current research, the chapter focuses on exploring the significance of cultural competence and fluency in establishing meaningful connections in online education. It introduces a novel approach to cultivating cultural competence and meaningful connections in the virtual classroom by providing practical examples of narratives and cultural content. It also includes a range of assignments and a case study that highlight different cultural perspectives and experiences, further reinforcing the importance of cultural understanding and empathy in virtual educational settings.
Fostering Connections in the Online Learning Environment
Authors: Salem Fatma Ouled , Bridges Corinne W.
Published: December 2023

Student retention and success in online programs seems to be closely related to their perceived sense of connection with their faculty, peers, and institution. Using activities that create opportunities for interactions and communal learning reduces attrition rates and enhances the learner's experience. In fact, Ouled Salem identified four critical strategies that distance educators can use to foster meaningful connections in the online learning environment: intentionality, creativity, empathy, and accessibility. This chapter will go into detail about each of the four skills and outline evidence-based activities that can be used in the online classroom to create and maintain meaningful relationships.
The Attitude of Portuguese Consumers of Green Cosmetics
Authors: Oliveira Zaila , Teixeira Sara , Teixeira Sara , Teixeira Sandrina F.
Published: December 2023

Nowadays, environmental problems have been accentuated by the scarcity of natural resources, climate change, pollution levels, and waste. As a result, consumers have become more environmentally responsible and opt for green products. The research question arises: How do environmental and health concerns influence consumers' attitude towards green cosmetics? This chapter includes a survey of Portuguese consumers with green cosmetics purchasing habits. The methodology adopted was quantitative, using questionnaires via Google Forms. The data obtained were analysed using SPSS Statistical Package (n=141). The data collected helped to highlight that environmental and health concerns influence consumer attitudes towards green cosmetics. The insights produced by this chapter represent an asset for researchers, business managers, and marketing professionals, especially those working with green cosmetics.
Integrating Quality Literature With Instruction Based in the Science of Reading
Authors: Watson Tiffany , Maxwell Nicole , Barnes M. Alyssa , Berry Brian
Published: December 2023

The main focus of this chapter is to provide teachers with ideas to support students' right to read while utilizing a structured literacy approach to instruction. To address a nationwide lack of reading proficiency, many states have passed legislation mandating the use of science of reading methods, including structured literacy instruction. Critics of the science of reading argue that the focus on the core reading principles within structured literacy “kills the love and joy of reading,” and educators often use this belief to justify using reading practices that lack documented evidence of success. Yet, researchers have found that the stronger reading skills a person possesses, the more they enjoy reading. Using global books with the elements of structured literacy helps us protect children's right to read while giving them the skills necessary to develop reading proficiency.
EU's Energy Policy and Assessing Europe's Spiraling Energy Security Crises
Authors: Bharti Mukesh Shankar
Published: December 2023

This chapter analyzes the energy crisis in Europe, which has been an emerging problem in recent years. Though it has been making efforts to reduce its dependence on fossil fuels, especially on Russia, it has not been able to achieve much success. A primary reason for this is that energy demand has increased while investments in renewable resources and other forms of alternative energy have not kept pace. This chapter implies a qualitative approach to explaining empirical data of the EU's policy on energy security. The study also focuses on to what extent the EU maintains energy issues during this crisis. What is the relationship between the EU and Russia during the war on energy issues? This research also answers the following question: What are the EU measures on the energy crisis in Europe?
The Impact of Russia-Ukraine War on the Global Energy Crisis
Authors: Ateed Ejazul Haq
Published: December 2023

The Russia-Ukraine war has profoundly affected the global energy crisis, leading to significant disruptions and uncertainties in energy flows both domestically and internationally. The escalation of tensions in 2022 made crucial energy infrastructure vulnerable, causing a reduction in natural gas and energy supplies to European countries heavily reliant on Russian exports. This disruption has resulted in fluctuating energy prices and increased volatility in global markets, pushing importing nations to explore alternative sources and focus on renewable energy and domestic production. Geopolitical tensions have risen as countries compete for energy resources and prioritize their energy security, prompting efforts to enhance resilience and develop contingency plans. This chapter analyzes the multi-faceted impacts of the Russia-Ukraine war on the global energy crisis, stressing the importance of proactive measures to address vulnerabilities, enhance energy security, and foster international cooperation for a more resilient and sustainable future.
Climate Crisis and The Future of Renewable Energy in the Turkic Republics
Authors: Kazancı Baybarshan Ali , Arslan Osman Furkan Furkan , Dinçer Selin
Published: December 2023

The continuation of the worsening climate crisis and the severe environmental degradation caused by fossil fuels is not sustainable for the world. It is important for major energy suppliers and importing countries to turn to renewable energy to meet the intense demand for energy and for future generations. In addition, governments are turning to renewable energy sources and increasing their investments in order to reduce foreign dependency in an economic and political context. Therefore, renewable energy strategies offer new opportunities for competitive strategies and cooperation in the world. This study evaluates the current renewable energy studies and investments of the Turkish Republics. In addition, policy recommendations will be made within the framework of the possible economic/political effects of these resources, which will create potential in the long run for the countries.
Introduction to ChatGPT
Authors: Shafik Wasswa
Published: December 2023

This chapter provides a comprehensive overview of ChatGPT, an advanced language model that has gained significant attention in natural language processing (NLP) and artificial intelligence (AI). It outlines the underlying architecture, features, applications, benefits, and limitations of ChatGPT. The chapter highlights ChatGPT's ability to facilitate human-like conversations through its understanding and generation of human-like text. It explores its versatility across domains and languages and its potential in customer support, virtual assistants, chatbots, language translation, content generation, and creative writing. The benefits of ChatGPT, such as improved efficiency and scalability, are discussed, as are the limitations and ethical considerations. The chapter concludes with a future outlook, discussing ongoing research and the potential impact of ChatGPT on communication and human-machine interactions, emphasizing the need for responsible development and deployment of this powerful language model.
Overview of ChatGPT Model Architecture
Authors: Pandey Manoj Kumar , Upadhyay Jyoti
Published: December 2023

This chapter provides a detailed exploration of the ChatGPT model architecture, a cutting-edge natural language processing (NLP) model that has revolutionized conversational AI. Developed by OpenAI, ChatGPT is built upon the GPT-3.5 architecture, a state-of-the-art language model. This chapter presents an extensive study about ChatGPT using a comprehensive analysis of its various recent literatures. This study also focuses on ChatGPT evolution from ELIZA to ChatGPT. In this chapter various reviews of literature, related issues, its architecture, various layers, various ChatGPT versions and its specialization, comparative study of various models, and application is presented. In order to do the comprehensive study various papers from different databases like ACM digital library, Scopus, IEEE, IGI Global, and Willey have been included for the study. Papers selected for the comprehensive study have been reviewed extensively in order to get the details and comprehended information for the readers. Various issues like security, biasness, training, misuse, etc. have been mentioned.
Textual Alchemy
Authors: Deep Gagan , Verma Jyoti
Published: December 2023

This chapter explores the transformative potential of generative models for advanced text generation, focusing on leveraging structural equation modeling techniques. With the rapid advancements in deep learning and natural language processing, generative models have emerged as powerful tools for creative writing, semantic coherence, and contextual understanding. This chapter provides a comprehensive overview of the foundations, methodologies, and applications of generative models in text generation. The chapter begins with an introduction to the evolution of generative models and highlights their significance in various domains. It lays the groundwork by explaining language modeling techniques and the architectures employed in text generation using deep learning algorithms. The subsequent sections delve into the core aspects of generative models for text generation.
Light Weight Structure Texture Feature Analysis for Character Recognition Using Progressive Stochastic Learning Algorithm
Authors: Bose S. Rubin , Singh Raj , Joshi Yashodaye , Marar Ayush , Regin R. , Rajest S. Suman
Published: December 2023

Handwritten character recognition is a challenging task in the field of image processing and pattern recognition. The success of character recognition systems depends heavily on the feature extraction methods used to represent the character images. In this chapter, the authors propose a novel feature extraction method called progressive stochastic learning (PSL) algorithm. The proposed work is based on the texture and structural features of the character image and is designed to extract discriminative features that capture the essential information of the characters. The PSL algorithm is used to classify the extracted features into their respective character classes. Experimental results demonstrate that the proposed method achieves a recognition accuracy of 92.6% for correct characters predicted and 91.3% for correct words predicted. Moreover, the proposed method outperforms several state-of-the-art methods in terms of recognition accuracy, computation time, and memory requirements.
Modern Applications With a Focus on Training ChatGPT and GPT Models
Authors: Kondurkar Isha , Raj Akanksha , Lakshmi D.
Published: December 2023

Generative AI (GAI) and natural language processing (NLP) have emerged as the most exciting and rapidly growing fields in artificial intelligence (AI). This book chapter provides a comprehensive exploration of the advanced applications of GAI and NLP models, with a specific focus on the renowned ChatGPT model. The chapter commences by offering a concise historical overview of the development of GAI and NLP, highlighting crucial milestones and advancements in the field over the period. In order to understand the workings of the current technology sensation, we will take a brief look at the basic building blocks of GPT models, such as transformers. Subsequently, the chapter delves into the introduction of ChatGPT, presenting an extensive overview of the model, elucidating its underlying architecture, and emphasizing its unique capabilities. Furthermore, it will illustrate the training process of the GPT model followed by a fine-tuning process to deal with the current model's shortcomings.
Promoting Students' Writing by Using Essay Writing GPT
Authors: Inderawati Rita , Apriani Eka , Jaya Hariswan Putera , Saputri Kurnia , Wijayanti Erfin , Ifnaldi  , Muthmainnah Muthmainnah
Published: December 2023

The purpose of this study is to determine how students might enhance their essay-writing abilities and how they respond to the essay writing GPT. Explanatory sequential research was used in this mixed method study to analyze both the qualitative and quantitative data in distinct steps. In order to conduct the study quantitatively, the researcher used 60 students who were enrolled in an undergraduate English study program at IAIN Curup, Indonesia, that included an essay writing course. With 30 students of experimental and control group. The test is validated by three experts from UIN Raden Fatah Palembang, University of Bengkulu, and UIN Fatmawati Sukarno Bengkulu. The results of this research are that GPT has no significant impact on students' essay writing skill. Experimental and control groups have almost the same score in essay writing tests. GPT has made students simpler to build the idea because they do not need to think harder like traditionally writing. Instead, the students who are in control group easier to arrange the structure of the essay as what they wanted.
Deep Learning Approaches for Affective Computing in Text
Authors: Cabada Ramón Zatarain , Estrada María Lucía Barrón , Bátiz Beltrán Víctor Manuel
Published: December 2023

The field of natural language processing (NLP) is one of the first to be addressed since artificial intelligence emerged. NLP has made remarkable advances in recent years thanks to the development of new machine learning techniques, particularly novel deep learning methods such as LSTM networks and transformers. This chapter presents an overview of how deep learning techniques have been applied to NLP in the area of affective computing. The chapter examines traditional and novel deep learning architectures developed for natural language processing (NLP) tasks. These architectures comprise recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and the cutting-edge transformers. Moreover, a methodology for NLP method training and fine-tuning is presented. The chapter also integrates Python code that demonstrates two NLP case studies specializing in the educational domain for text classification and sentiment analysis. In both cases, the transformer-based machine learning model (BERT) produced the best results.
Fine-Grained Independent Approach for Workout Classification Using Integrated Metric Transfer Learning
Authors: Bose S. Rubin , Sirajudheen M. Abu Shahil , Kirupanandan G. , Arunagiri S. , Regin R. , Rajest S. Suman
Published: December 2023

Physical activity helps manage weight and stay healthy. It becomes more critical during a pandemic since outside activities are restricted. Using tiny wearable sensors and cutting-edge machine intelligence to track physical activity can help fight obesity. This study introduces machine learning and wearable sensor methods to track physical activity. Daily physical activities are typically unstructured and unplanned, and sitting or standing may be more common than others (walking stairs upstairs down). No activity categorization system has examined how class imbalance affects machine learning classifier performance. Fitness can boost cardiovascular capacity, focus, obesity prevention, and life expectancy. Dumbbells, yoga mats, and horizontal bars are used for home fitness. Home gym-goers utilise social media to learn fitness, but its effectiveness is limited.
The Influence of Green Human Resources Practices on Sustainable Performance in the Egyptian Hotels
Authors: Aboul-Dahab Sameh Abd-elMaksoud , Saied Badawy
Published: December 2023

The hotel industry is one of the sectors that largely increases the environmental burden. Therefore, due to the large number of environmental problems faced by the hotel industry, there is a growing force for the companies and their stakeholders to respond correctly to environmental concerns and to introduce sustainable business practices such as the adoption of green practices. This study used a research model to explore the relationship between green HRM practices in the Egyptian hotels. Structural equation modelling was utilised to analyse data collected from 910 hotels. The research findings revealed that green recruiting and selection, green training and development, and green compensation have a meaningful sustainable performance relationship. The study provides hotel managers with meaningful implications on how to use GHRM in improving their business performance.
Determinants of Consumer Preference for Traditional Indian Cooking Practices
Authors: Chhonker Mayanka , Kumar Dilip , Shandilya Abhinav Kumar
Published: December 2023

Food plays a vital role in the growth and development of human beings and helps fight many diseases, shaping consumers' intentions and actual behaviour. Consumers prefer a healthy lifestyle in the current COVID-19 situation, where immunity is one of the most critical factors in fighting the deadly coronavirus. The constructs of the health belief model (HBM) and the theory of planned behaviour (TPB) plays an essential role in shaping consumers' preferences for food. To identify the determinants of consumers' choice for traditional Indian cooking practices, a mixed-method approach was followed in the study. Qualitative research prepared the base for quantitative research. First, an open-ended personal interview of 12 respondents was conducted to develop a questionnaire used for the quantitative survey. Exploratory factor analysis results helped identify the seven factors, i.e., behaviour, cues in action, social influence, perceived benefits, self-efficacy, perceived susceptibility, and readiness, as determinants of consumers' preference for traditional Indian cooking practices.