bluuebunny/crossref_metadata_2025 huggingface dataset:
The Gourava Co-Indices of Graph
Authors: Somani R.P. , Jethwani Varshiki
Published: April 2024

This Paper explores the concept of Gourava co-indices, inspired by the analogous discussions on Zagreb indices in prior literature. Gourava co-indices are a novel extension of graph theoretical concepts, focusing on the relationships and patterns within molecular structures. Moreover, we present several key relations and properties associated with Gourava co- indices, providing a comprehensive framework for further research and practical applications in areas such as drug discovery, material science, and computational chemistry.
PERFORMANCE ASSESSMENT OF SPATIAL INTERPOLATIONS FOR TRAFFIC NOISE MAPPING ON UNDULATING AND LEVEL TERRAIN
Authors: Wickramathilaka Nevil , Ujang Uznir , Azri Suhaibah , Choon Tan Liat
Published: April 2024

Traffic noise mapping frequently employs Kriging, Inverse Distance Weighted (IDW), and Triangular Irregular Networks (TIN) spatial interpolations. This study uses the Henk de Kluijver noise model to evaluate the performance of spatial interpolations. Effective traffic noise mapping requires that noise observation points (Nops) be designed as 2 m grids. The upper and lower slopes function as noise barriers to reduce sound levels. Therefore, assessment of accuracy is essential for visualising noise levels in undulating and level terrain. In addition, this work gives an accurate comparison of traffic noise interpolation in undulating areas. The elements of spatial interpolations, such as the weighting factor, variogram, radius, and number of points influence the interpolation accuracy. The Kriging with a Gaussian variogram, where the radius is 5 m and the number of points is 12 demonstrates the highest level of precision. However, there is no direct relationship between accuracy validation and cross-validation. In cross-validation, however, the accuracy of the Gaussian variogram with a 7 m radius and 18 points is more accurate. In addition, this study demonstrates that Kriging is superior for extrapolating noise levels in undulating regions. Accurate visualising traffic noise levels requires a prior understanding of spatial interpolations.
A new species of genus Monoctonus (Hymenoptera, Braconidae, Aphidiinae) from South Korea
Authors: Kim Sangjin , Čkrkić Jelisaveta , Tomanović Željko , Sohn Ju-Hyeong , Lim Jongok , Kim Hyojoong
Published: April 2024

The genus Monoctonus Haliday, 1833 is a small group which consists of 24 species worldwide. In South Korea, Chang and Youn (1983) recorded one species, M. similis Starý & Schlinger, 1967, but the evidence for identification of this species is doubtful and further confirmation is required (personal communication with Prof. Jong-Cheol Paik).

An additional Monoctonus species is recorded as new to science from South Korea. Descriptions and illustrations of the new species –Monoctonus koreanus sp. nov. – are provided, together with its mitochondrial cytochrome c oxidase subunit I (COI) data and phylogenetic position. A key to the female of the two species present in Korea is provided.
Cauca: megafaunal and felid fossils (Mammalia) from a Pleistocene site in northwest Venezuela
Authors: Carrillo-Briceño Jorge Domingo , Ruiz-Ramoni Damián , Sánchez Rodolfo , Jaimes Arturo , Chávez-Aponte Edwin , Prevosti Francisco Juan , Segura Valentina , Carlini Alfredo Armando , Garbé Lisa , Tombret Olivier , Zazzo Antoine , Sánchez-Villagra Marcelo Ricardo
Published: April 2024

Numerous surveys and three excavation and surface collection field seasons resulted in the discovery of numerous megafaunal remains and that of a medium-sized felid in a new site located on the coastal plain of the Gulf of Venezuela, in Western Falcón State. The faunal assemblage is represented by South American natives such as megatheres (cf. Eremotherium laurillardi), an indeterminate mylodontid and a glyptodont (probably related to Glyptotherium) and Nearctic representatives such as gomphotheres (Notiomastodon platensis), equids (Equus sp.) and a feline (Felidae cf. Leopardus pardalis), providing novel information for the distribution of some of these mammals. Radiocarbon indicates that this deposit is at least 40,000 years old. Lithic artefacts of a kind reported for other Pleistocene sites in the region document the presence of humans in Cauca, but as these cultural remains were found on the surface, their association with the fauna is uncertain.
Talent training practices in SME hotels
Authors: Taghi Zadeh Ansari Ehsan
Published: April 2024

Purpose: This study aims to explore and analyse the intricacies of talent management and employee development practices within the hospitality industry. By delving into various training methodologies and assessing their impact, the study seeks to unveil the strengths, challenges, and opportunities each presents.Design/methodology/approach: This study adopted a qualitative research design, utilizing an inductive and exploratory approach. Given the nuanced and dynamic nature of talent management in the hospitality industry, this methodology allowed for a comprehensive and in-depth exploration of practices, impacts, and underlying dynamics.Findings: This study highlighted the diversity in talent management within the hospitality industry. Outsourced courses and peer-to-peer learning were common, each presenting unique advantages and challenges. Coaching was valued but faced scheduling and cost issues. Notably, exclusion from talent pools resulted in employee frustration, mistrust, and increased turnover intentions, underscoring the need for inclusive and adaptive talent management strategies.
Performance analysis of insertion loss incorporated hybrid precoding for massive MIMO
Authors: Abose Tadele A. , Olwal Thomas O. , Mohammed Muna M. , Hassen Murad R.
Published: April 2024

Due to an increase in the number of users and a high demand for high data rates, researchers have resorted to boosting the capacity and spectral efficiency of the next-generation wireless communication. With a limited RF chain, hybrid analog digital precoding is an appealing alternative. The hybrid precoding approach divides the beamforming process into an analog beamforming network and a digital beamforming network of a reduced size. As a result, numerous hybrid beamforming networks have been proposed. The practical effects of signal processing in the RF domain, such as the additional power loss incurred by an analog beamforming network, were not taken into account. The effectiveness of hybrid precoding structures for massive MIMO systems was examined in this study. In particular, a viable hardware network realization with insertion loss was developed. Investigating the spectral and energy efficiency of two popular hybrid precoding structures, the fully connected structure, and the subconnected structure, it was found that in a massive MIMO, the subconnected structure always performed better than the fully connected structure. Characterizing the effect of quantized analog precoding, it was shown that the subconnected structure was able to achieve better performance with fewer feedback bits than the fully connected structure.
ANN for the prediction of isobutylene dimerization through catalytic distillation for a preliminary energy and environmental evaluation
Authors: Chuquin-Vasco Daniel , Torres-Yanacallo Geancarlo , Calderón-Tapia Cristina , Chuquin-Vasco Juan , Chuquin-Vasco Nelson , Cepeda-Godoy Ramiro
Published: April 2024

This study aimed to develop an artificial neural network (ANN) capable of predicting the molar concentration of diisobutylene (DIB), 3, 4, 4-trimethyl-1-pentene (DIM), and tert-butyl alcohol (TBA) in the distillate and residue streams within three specific columns: reactive (CDC), high pressure (ADC), and low pressure (TDC). The process simulation was conducted using DWSIM, an open-source platform. Following its validation, a sensitivity analysis was performed to identify the operational variables that influenced the molar fraction of DIB, DIM, and TBA in the outputs of the three columns. The input variables included the molar fraction of isobutylene (IB) and 2-butene (2-Bu) in the butane (C4) feed, the temperature of the C4 and TBA feeds, and the operating pressure of the CDC, ADC, and TDC columns. The network's design, training, validation, and testing were performed in MATLAB using the Neural FittinG app. The network structure was based on the Bayesian regularization (BR) algorithm, that consisted of 7 inputs and seven outputs with 30 neurons in the hidden layer. The designed, trained, and validated ANN demonstrated a high performance, with a mean squared error (MSE) of 0.0008 and a linear regression coefficient (R) of 0.9946. The statistical validation using an analysis of variance (ANOVA) (p-value > 0.05) supported the ANN's capability to reliably predict molar fractions. Future research will focus on the in-situ validation of the predictions and explore hybrid technologies for energy and environmental optimization in the process.
A delay-product-type Lyapunov functional approach for enhanced synchronization of chaotic Lur'e systems using a quantized controller
Authors: Kaviarasan Boomipalagan , Kavikumar Ramasamy , Kwon Oh-Min , Sakthivel Rathinasamy
Published: April 2024

The asymptotic synchronization problem of chaotic Lur'e systems in the master-slave framework was explored in this paper. A time-varying delay feedback controller with quantization considerations and a delay-product-type Lyapunov-Krasovskii functional technique were employed to tackle this problem. Consider an error system based on master and slave systems, for which sufficient asymptotic stability requirements are developed to assure that the addressed system achieves proper synchronization. Following that, the desired control gain was determined by finding a feasible solution to these stability requirements. The results of this paper were validated using a numerical example with simulations, which revealed that they were superior to previously published ones.
Acceleration of solving drift-diffusion equations enabled by estimation of initial value at nonequilibrium
Authors: Du Chunlin , Zhang Yu , Qu Haolan , Guo Haowen , Zou Xinbo
Published: April 2024

In this study, a novel method enabled by estimation of initial value guess at nonequilibrium was proposed to accelerate drift-diffusion equations in semiconductor device simulation. The initial value guess was obtained by solving analytical model about electrical potential with the decoupling algorithm. By obtaining the initial value directly at the target bias voltage, the proposed method eliminated time-consuming bias ramping process in the classical method starting from the equilibrium state, thereby accelerating the whole process. The method has been applied to a junction barrier Schottky (JBS) diode for validation. Numerical results showed that the proposed method achieves convergence within 10 iterations at several reverse bias voltages, achieving significant reduction of iteration number compared to the classical method using the bias ramping process. It demonstrated that the proposed method holds high feasibility to facilitate the semiconductor device property prediction in relatively regular device structure in the case of low current. With further improvements, this method can also be applied to more complex devices.
Case Studies on Detection Using mmWave FMCW RADAR System
Authors: Prakash Gummadi Surya , Chandra W. , Mehta Shilpa , Kumar Rupesh
Published: April 2024

The content of this chapter provides a thoughtful analysis of case studies that highlight the detection capabilities of FMCW radar systems operating in mmWave configurations. The case studies demonstrate how mmWave FMCW radar technology may be used to detect objects, motions, and changes in both line of sight and non-line of sight settings with accuracy, and efficiency. Each case study explores the unique difficulties presented by the application environment, which can include anything from identifying impediments in automotive safety systems to detecting minute movements for vital sign monitoring in healthcare. The steps for detecting different gesture recognition using IWR 1843 BOOST FMCW radar system and its processing are focussed upon. The document highlights the technology's excellent resolution, motion sensitivity, and adaptability to a variety of challenging environments in LoS and NLoS scenarios and with the technical details of operating mmWave radars, including signal processing methods, machine learning algorithms, and mitigating interference from surrounding objects.
Integration of Reconfigurable Intelligent Surfaces With Antennas for 6G Wireless Communications
Authors: Sapkale Pallavi , Mehta Shilpa
Published: April 2024

The evolution of wireless communication networks towards 6G demands innovative solutions to address the challenges of increasing data rates, network capacity, and energy efficiency. Reconfigurable intelligent surfaces (RIS) emerge as a promising technology that revolutionizes how wireless signals propagate and interact with the environment. In this chapter, the authors explore the integration of RIS with antennas for 6G wireless communications. RIS, comprised of programmable meta-surfaces, can dynamically manipulate electromagnetic waves to optimize signal quality, mitigate interference, and enhance network performance. By providing adaptive beam forming, beam steering, and signal enhancement capabilities, RIS-enabled antennas offer unprecedented flexibility and efficiency in communication systems. This chapter overviews RIS principles, discusses their integration with antennas, and highlights their potential to shape the future of 6G wireless communications.
Design and Analysis of Dual Band Frequency Selective Surface
Authors: Somwanshi Devendra Kumar , Bansal Payal
Published: April 2024

Recent progress in microstrip antennas has improved their size and efficiency, particularly in mobile, satellite, and Wi-Max technologies. These enhancements are crucial for advancing wireless communication systems, benefiting applications like telemedicine and GPS technology. The chapter introduces a dual-band unit cell of frequency selective surface (FSS) resonating at 4 GHz and 5.5 GHz, using a combination of I-shaped and modified I-shaped metal strips for dual-band filtering. The research focuses on individual shape analyses and aims to contribute to the development of compact and efficient dual-band FSS designs. The research introduces a dual-band FSS unit cell resonating at 4 GHz and 5.5 GHz, combining I-shaped, H shaped, and modified I-shaped and H shaped metal strips for dual-band filtering. The proposed FSS design, with a 10x10 mm2 unit cell dimension and FR-4 dielectric, exhibits broad frequency band characteristics, aligning well with simulated and measured results.
Enhance Communication With Stakeholders Through Social Media in Protected Areas as Sustainable Tourism Destinations
Authors: Mañas-Álvarez Isabel Cristina , Alonso-Cañadas Juana , Galán-Valdivieso Federico , del Carmen Caba-Pérez Mª
Published: April 2024

EUROPARC, the representative federation of protected areas, is adopting policies to disseminate information about its sustainable tourism strategies, safeguarding natural and cultural values, supporting local livelihoods and being economically viable. In this context, social networks play a key role in fostering sustainable tourism. This chapter aims to analyse the level of engagement achieved through social media (Twitter or X) in relation to sustainable tourism, and to examine the type of content disseminated. The main findings reveal notable trends in stakeholder engagement, with quick and simple actions such as “likes” and “retweets” predominating over comments. Additionally, significant differences in the level of engagement are observed between protected areas in different countries and with respect to the type of content. These findings offer valuable perspectives for protected areas managers, providing guidance on how to improve their strategies to encourage greater stakeholder engagement through social media and therefore foster the preservation of these natural areas.
IoT-Based Monitorization and Caliber Checker With Multiple Decision Making Using Faster R-CNN and Kalman Filter for Visually Impaired Elders
Authors: Sindhu S. , Sivasankari R.
Published: April 2024

In the field of healthcare, the internet of things (IoT) plays a crucial role in prediction, multiple decision-making, and alarm systems. The highest rate of death among the elderly is greater than 60%. Due to numerous COVID-19 facts, 70 percent of the overall population in India is afflicted, up from 50 percent. Around 48 percent of the elderly are plagued by the disease in Tamil Nadu, India. In tropical countries like India, handling pandemic situations is very new, and people here aren't prepared to deal with the circumstances. This chapter aims to assist in the monitoring of senior citizens in their homes rather than in hospitals. It is used to monitor their health difficulties, such as blood pressure, temperature, diabetes, a range of cardiac problems, and collapsing. Not only the health-related problems The R-CNN algorithm aids in making various decisions based on IoT data It may predict the situation and make decisions based on a variety of parameters and criteria. As a result of the essential alert to the doctor and caretaker for making the suitable decision
The Recent Developments in Biomedical Research for Improving Healthcare
Authors: Sharma Purnima , Anand Satyajit , Sharma Vikrant
Published: April 2024

This chapter presents an analysis of advancements in biomedical research for improving healthcare from bibliometric and thematic views. A literature search was carried out using the documents from the Scopus database. To conduct this study, a total of 145 research articles from 2006 - September 2023 were reviewed. Bibliometrix (R package) and SciMAT tools were used to conduct this review in terms of bibliometric and thematic analysis. The analysis presents results as contributing authors and co-author and their affiliations, leading contributing countries, main relevant sources, frequently used keywords, and major themes. The derived results provide insight into the limitations and scope of collaborative research in the area of digital healthcare utilizing smart technologies. It shows that digital health care using artificial intelligence is a growing area of exploration. In this chapter, the role of artificial intelligence in digital health is also presented. Providing data security and privacy in digital health is found to be challenging and there is a lot of oppertunity for further research is there.
Virtual and Augmented Reality Applications for Healthcare and Goodness
Authors: Dhabliya Dharmesh , Veeraiah Vivek , Dari Sukhvinder Singh , Kumar Jambi Ratna Raja , Dhabliya Ritika , Pramanik Sabyasachi , Gupta Ankur
Published: April 2024

The proposed book chapter explores the revolutionary potential of AR and VR technologies in a variety of healthcare applications by delving into the ground-breaking integration of biomedical engineering with them. As technology develops, AR and VR become more potent instruments that have a significant influence on patient care, medical practice, and healthcare education. The goal of this chapter is to provide a thorough review of the most recent advancements, difficulties, and opportunities in using the convergence of biomedical engineering and AR/VR applications. The first part of the chapter provides a solid grounding in the core ideas of biomedical engineering and explains how it is used to design, develop, and implement cutting-edge solutions for biomedical problems.
Tackling Customer Wait Times
Authors: Dwivedi Dwijendra Nath , Khashouf Shafik
Published: April 2024

In the digital age, call centers remain a pivotal touchpoint between businesses and their clientele. They offer direct human interaction that shapes customer experience. One of the primary pain points in this interaction is the wait time a customer endures before being attended to. This research delves into the challenge of minimizing customer wait times in call centers. The authors experiment a blend of traditional optimization techniques and contemporary machine learning methods for the same. By leveraging integer programming, they formulate an optimization problem to efficiently allocate calls to agents. The main objective of the chapter is to reduce the cumulative waiting time while maintaining the customer satisfaction. The authors harness the predictive power of machine learning to forecast call durations based on various parameters as well. Preliminary results indicate a significant potential in combining these approaches. It offers a robust framework for call centers to enhance their operational efficiency. This elevates the customer experience in a very competitive environment as well.
Towards an Artificial Intelligence Methodology to Evaluate the Degree of Maturity of Media and Information Literacy Skills (MIL) in Teachers
Authors: Ortiz Felipe Chibás
Published: April 2024

A pilot investigation is shown using the artificial intelligence tool to evaluate the degree of maturity of media and information literacy (MIL) competencies in Argentine teachers. The general objective of this first pilot approach is to analyze the degree of maturity of MIL competencies, according to the UNESCO Curriculum published in 2022, in teachers who participated in the MIL course developed by the Public Defender of Argentina and UNESCO, in 2022. The authors also set out to develop for this study a specific methodology with an MIL metrics system that allows evaluating the 19 competencies and six values defined by UNESCO as essential in the aforementioned Curriculum, using artificial intelligence. Starting from the UNESCO Curriculum, a quantitative questionnaire was developed with test questions and using a two-phase methodology with artificial intelligence (AI), involving the simple k-means and apriori classification algorithms. of the Weka software. This is the first phase of using AI, which is technically called business intelligence.
Blockchain and the Stock Market
Authors: Sidana Neeru
Published: April 2024

This chapter investigates how blockchain technology is revolutionizing the conventional stock market ecosystem. Blockchain is becoming a disruptive force in many industries, and the financial sector specifically. The stock market has been one area where it has attracted a lot of attention. This study investigates the possible advantages, difficulties, and effects of incorporating blockchain technology into the architecture of the stock market. The chapter starts by giving a comprehensive introduction to blockchain technology, highlighting its safe and decentralized characteristics.
Speculating About the Negative Aspects of Business-to-Business Interactions in the Modern Era of Artificial Intelligence and Blockchain
Authors: Singh Avtar , Sharma Rahul
Published: April 2024

The management of B2B interactions and the manifestation of their negative side effects can be influenced by new technologies such as artificial intelligence (AI), blockchain, and big data analytics. Additionally, despite numerous advancements in the study of the dark side of B2B connections, there have recently been questions expressed about the stream's under theorization and the fact that the focus has been on the manifestations of the dark side rather than its underlying mechanisms. In order to address these issues, the study looks at how the advent of new technologies has the potential to alter B2B interactions and result in the appearance of negative side effects through mechanisms that have not yet been investigated or understood. Through this procedure, the authors also show how theories like social dominance, organisational inertia, organisational information processing, and role theory—which have been largely ignored in this literature—can offer fresh perspectives when examining the negative aspects of B2B relationships.
Performance Evaluation of Deep Learning and Machine Learning Techniques for Opinion Mining
Authors: Saraswathi K. , N. T. Renukadevi , S. Nandhinidevi
Published: April 2024

With the technological developments in the fields of natural language processing (NLP) and opinion mining (OM), many real-time applications are concentrating on analyzing the opinions of the people. The opinions or reviews given by the people through the internet are collected for summarization or classification based on the need. The feature selection typically saves the operating time, eliminates irrelevant features and redundancy. For feature selection, a semantic based feature selection algorithm called information gain (IG) is used. Naive Bayes, bagging, support vector machines (SVM), classification and regression trees (CART), and algorithms along with optimization techniques like ant colony optimization algorithms are used to optimize and classify the opinions. Also, in this chapter, the state-of-the art machine learning technique, deep learning, is also involved with the convolution neural networks (CNN) algorithm to identify the positive and negative opinions in different fields such as movie reviews, emojis and medical data.
Neural Network and Neural Computing
Authors: Ghosh Partha , Ghosh Suradhuni
Published: April 2024

Deep learning, a subset of AI, has gained popularity in various fields, including computer vision and NLP. It is based on artificial neural networks, which process multiple layers of data and extract high-level features automatically. Unlike traditional ML algorithms, deep learning can process large unstructured data and complex algorithms better than traditional methods. The human brain inspires neural networks, which contain artificial neurons similar to biological neurons. These networks are made up of three layers: input, hidden, and output. Deep learning maps inputs to outputs and finds correlations, making it a “universal approximator.” It can be combined with other AI methods to perform more complex tasks, such as deep reinforcement learning. Top companies using ANN include Nvidia Corp., Alphabet, Salesforce.com, Amazon.com, Microsoft Corp., Twilio, IBM, and Facebook. Deep learning uses ANN to analyze data and make predictions and has found applications in almost every business sector.
The Past of Digital Government
Authors: Guo Yuanyuan
Published: April 2024

In the digital age, the progression of government models presents a nuanced problem that this study meticulously investigates. Contextually, the inception of digital government in China has transpired through three distinct phases, each marked by a characteristic emphasis: technology-oriented, mutual transparency-oriented, and people-oriented. The analysis underscores a critical shift in emphasis across these stages, from an initial concentration on technological deployment to a present focus on mutual transparency and citizen engagement. Despite the evident progress, an issue emerges around capturing and articulating these stages with precision and objectivity. In response to this problem, this study undertakes an in-depth examination of case studies pertinent to each phase, which unravels insights into their defining characteristics. The findings indicate a potential trajectory towards a digital government model that further accentuates public participation. In terms of objectives, this study endeavors to deepen the comprehension of the evolution of digital government in China and shed light on its potential future trajectory, thereby making a significant contribution to the dialogue around policy formulation and the future development of digital governance.
Enhancing Digital Literacy Among Chinese Civil Servants
Authors: Jiang Xiaodi
Published: April 2024

This chapter investigates the digital literacy of Chinese civil servants, focusing on evaluation criteria, variations across levels and departments, and improvement strategies. It proposes a tailored evaluation framework to assess digital literacy, identifying strengths, weaknesses, and influencing factors through empirical research. The study offers a comprehensive analysis and recommendations to enhance digital competencies in the public sector, structured into sections on literature review, indicator system construction, evaluation, and countermeasures. This work contributes valuable insights for advancing digital literacy among civil servants in China.
The Competency Baseline of the Digital Age
Authors: Zhang Teng
Published: April 2024

This article focuses on the digital literacy of individuals and organizations in the digital era, introducing new requirements for digital literacy among individuals and organizations in this age. Additionally, it discusses the international progress made in fostering digital literacy, with insights from the United States, Europe, and other regions, enriching the research on digital literacy. Concluding, the article offers suggestions for enhancing the digital literacy competencies of individuals and organizations, emphasizing the importance of adopting a logical and scholarly approach.
Transformation of Bureaucracy in Digital Times
Authors: Deng Yi
Published: April 2024

The wide-scale application of information and communication technology in public organizations is reshaping the structure of public organizations. This chapter expounds the impact of information and communication technology on the power structure of bureaucracy through two specific cases from China. The cases show that information and communication technology strengthens the vertical control of bureaucracy, which is mainly manifested in two aspects: first, it weakens the power of grassroots civil servants, especially the power of agenda setting; second, it strengthens the point-to-point control ability of middle and high-level managers over grassroots civil servants. Next, this chapter analyzes the possible negative impacts of these two changes.
Government Strategies for Sustainability, Socioeconomic Progress, and Gender-Biased Citizen Participation in Global Digital Governance
Authors: Bhattacharya Sumanta
Published: April 2024

To enhance global digital governance for sustainability, socioeconomic progress, and inclusive citizen participation, government digital policies should be comprehensive and forward-looking. Effective policies should prioritize data privacy, cybersecurity, and bridge technical disparities, ensuring that advancements in technology are mirrored by changes in regulations. Accessible digital literacy programs are essential for fostering ethical AI usage and overcoming barriers such as resistance to change and inadequate technological oversight, which hinder societal and economic development. Addressing ethical concerns and gender disparities in AI and computing is crucial for promoting diversity and combating stereotypes, thereby enhancing civic engagement. Moreover, to achieve meaningful progress, global collaboration and the establishment of universal digital governance standards are imperative. By focusing on creating inclusive digital ecosystems, encouraging policy innovation, and ensuring widespread digital literacy, governments can lay the foundation for sustainable, economically prosperous, and gender-inclusive digital societies.
Exploring the Multifaceted Dimensions of South Indian Gastronomy Tourism Thorugh the Eyes of International Tourists
Authors: kumar Vinod , Kulshrestha Ruchika
Published: April 2024

South Indian cuisine, renowned for its vibrant flavours, diverse ingredients, and rich cultural heritage, has increasingly captivated the attention of gourmet enthusiasts in the field of tourism. This chapter examines the complex relationship between South Indian food, gastronomy tourism, and the culinary issues abroad tourists have in seeking authentic gastronomic experiences using qualitative methods like interviews and participant observations. The chapter analyses the gastronomic issues internationally tourists face in South Indian gastronomy tourism. This study illuminates these issues and offers answers, contributing to the current discussion on improving gastronomy tourism in this culturally rich region. Tourists and local stakeholders can collaborate to improve the culinary experience, making international visitors feel more accepted and appreciated. The chapter also discusses these issues faced by the international tourists in South India and offers practical answers, contributing to the current discussion on improving gastronomy tourism in this culturally rich region.
Reinvestigating the Relationships Between the Elements of Restaurants' Servicescape and In-House Dining Behavior in the Light of COVID-19
Authors: Shandilya Abhinav Kumar , Jana Abhisek , Kumar Dilip
Published: April 2024

The present study aims to examine the relationships between physical and social servicescape elements with inhouse dining behaviour by applying the stimulus-organism-response (S-O-R) framework to overcome the challenges that arose due to the breakout of COVID-19. Smart PLS software 3.3.7 has been used to conduct statistical analysis to establish the constructs' reliability and validity and test the developed hypotheses. The study confirms the fitness of the S-O-R framework in predicting in-house dining behaviour in light of COVID-19. The diners should be communicated about the hygiene standards followed during the operation cycle, and a separate zone could be created for people who are more concerned about the health risks. The restaurants cannot afford to compromise with the ambient condition, signs, symbols and artefacts, spatial layout and functionality, perceived similarities and behaviour of other customers, and physical appearance and behaviour of the employees. These components act as stimuli to develop learning and mood, leading to in-house dining.
AVALIAÇÃO DO TEMPO DE DESIDRATAÇÃO POR MICRO-ONDAS DE BATATA YACON
Authors: Ana Carolina Vivan  , Bruna Pegoraro Savoldi  , Francisco Roberto da Silva Machado Junior  , Cristiano Reschke Lajus  , Gean Lopes da Luz  , Sideney Becker Onofre  , Dalcanton Francieli
Published: April 2024

As pesquisas relacionadas a batata yacon tem aumentado o interesse, pois esta apresenta potencial prebiótico, atividade antioxidante, melhora do sistema imune e redução da glicemia. Desenvolver alimentos que apresentem uma maior vida útil, como por exemplo os desidratados, é fundamental para aumentar a disponibilidade ao longo de todo o ano. Desse modo, o objetivo deste estudo foi avaliar o tempo de desidratação dos chips da batata yacon em forno micro-ondas. Para isso, as batatas foram higienizadas e fatiadas e submetidas a desidratação por micro-ondas nos tempos de 30 a 300 segundos, além de um comparativo a 55 ºC em desidratadora. Observou-se que em um tempo de 210 segundos em micro-ondas os chips apresentaram peso constante e na desidratadora foi necessário 2 horas, demonstrando que a desidratação por micro-ondas é um processo mais rápido e ágil. Este resultado é importante por apresentar elevada eficiência devido ao reduzido tempo de exposição ao calor, esperando com isso conferir uma redução de custo energético em escala industrial, e em consequência manter melhor os nutrientes e as propriedades sensoriais.
EFEITO DE AGENTES DE CONSERVAÇÃO NA QUALIDADE DE PRODUTO A BASE DE PALMITO PUPUNHA
Authors: Alves dos Reis Patrícia , dos Santos Souza Hellen , Dalva Godoy Danesi Eliane , Bolanho Beatriz Cervejeira
Published: April 2024

A parte basal e caulinar do palmito pupunha apresenta baixo valor comercial, por isso, propor novas alternativas de processamento pode valorizar a matéria prima. O objetivo deste trabalho foi utilizar estas porções para a produção de lâminas para lasanha, aplicando diferentes agentes de conservação. O delineamento experimental foi composto de sete tratamentos: controle, branqueamento (Br); branqueamento associado com ácido ascórbico 0,5% (BrAA), com ácido cítrico 0,5% (BrAC), com cisteína 0,5% (BrC), com cisteína 0,5% e ácido ascórbico 0,5% (BrAA+C), e com cisteína 0,5% e ácido cítrico 0,5% (BrAC+C); avaliados aos 0, 3, 6, 9 e 12 dias de refrigeração. Os resultados demonstraram que o branqueamento associado com os agentes de conservação testados contribuiu para a manutenção da vida útil do produto por 12 dias, devido a estabilidade dos valores de pH, acidez, cor e atividade enzimática, e dos parâmetros microbiológicos. Não houve perda de massa para o tratamento BrAC, enquanto as amostras BrAA+C, BrAC+C apresentaram maior potencial antioxidante. Portanto, os tratamentos realizados apresentam uma alternativa viável para o aproveitamento das partes subutilizadas de palmito pupunha (basal e caulinar), na forma de lâminas para lasanha.
DISTRIBUIÇÃO DE ESFORÇOS, DESLOCAMENTOS E TENSÕES DE CONTATO DE UM EDIFÍCIO ALTO EM RADIER CONSIDERANDO A INTERAÇÃO SOLO-ESTRUTURA
Authors: Campagnolo Gimenes Henrique Cesar
Published: April 2024

Dentre as soluções de fundações utilizadas em edifícios altos os radiers têm seu uso recorrente. A tensão de contato, deslocamento elástico e a carga vertical são fatores importantes a serem conhecidos, bem como as suas relações com a tipologia do elemento de fundação, maciço de solos e a super estrutura do edifício, tornando toda essa dinâmica complexa. A complexidade dessa interação vem das muitas variáveis envolvidas no conjunto edifício, fundação e maciço de solos. Nesse contexto, o presente artigo tem como objetivo apresentar a análise desses três fatores e suas variações de comportamento conforme a mudança da tipologia de radier, geometria, posição e formato dos pilares de um edifício alto. Para tanto, foi desenvolvido um estudo de caso com o auxílio do software SAP2000, onde o solo foi concebido as luzes do modelo de Winkler, regido pela literatura consagrada da área e a ABNT NBR 6122 (2019), um modelo de um edifício alto com radier como solução de fundação. Por fim ficou evidenciado que a tensão de contato, deslocamento elástico e a carga vertical são influenciados em grande parte pela rigidez da fundação e essa propriedade é determinante no conjunto, podendo até resultar em redistribuição de esforços dos pilares.
Forest tent caterpillar (Lepidoptera: Lasiocampidae) across Canada, 1938–2001: I. Periodic outbreaks; episodic impacts
Authors: Cooke Barry J.
Published: April 2024

I review the history of forest tent caterpillar, Malacosoma disstria (Hübner) (Lepidoptera: Lasiocampidae), occurrence from 1938 to 2001 throughout Canada, with emphasis on the insect’s impact on tree mortality. I show that forest tent caterpillar routinely kills a portion of its host tree population during outbreaks. Although the proportion killed is typically small, there are some unusual conditions during which the foliage grazer can precipitate large-scale host forest declines. These decline episodes are the result of a spatially complex pattern of outbreak spread whereby successive cycles occur asynchronously enough that there is a zone of overlap where the two cycles occur in rapid succession, leading to three to six years of defoliation, triggering a nonlinear mortality response that endures through time. One of these “cycles” is typically amplified locally to an intensity that is anomalously high and nonrecurring. Defoliation events that are periodic in aggregate may thus give rise to patterns of insect-caused forest decline that are episodic. These decline events have been shifting northwards over time and have been growing in extent. The dynamics of outbreak occurrence appears to be a complex result of interacting top–down and bottom–up forces, making it challenging to predict in advance whether or not any given outbreak will exceed the threshold required to precipitate large-scale mortality.
Enhancing risk management in hospitals: leveraging artificial intelligence for improved outcomes
Authors: Guerra Ranieri
Published: April 2024

In hospital settings, effective risk management is critical to ensuring patient safety, regulatory compliance, and operational effectiveness. Conventional approaches to risk assessment and mitigation frequently rely on manual procedures and retroactive analysis, which might not be sufficient to recognize and respond to new risks as they arise. This study examines how artificial intelligence (AI) technologies can improve risk management procedures in healthcare facilities, fortifying patient safety precautions and guidelines while improving the standard of care overall. Hospitals can proactively identify and mitigate risks, optimize resource allocation, and improve clinical outcomes by utilizing AI-driven predictive analytics, natural language processing, and machine learning algorithms. The different applications of AI in risk management are discussed in this paper, along with opportunities, problems, and suggestions for their effective use in hospital settings.
Who is Friends with Whom? Patterns of Inter- and Intraethnic Friendships of Mainstream and Immigrant Early Adolescents in Germany
Authors: Schachner Maja , Van de Vijver Fons , Brenick Alaina , Noack Peter
Published: April 2024

Multiethnic schools provide opportunities for interethnic contact and the development of positive interethnic relations. Yet, some children develop such relations more easily than others. In the present study, we were interested in patterns of inter- and intraethnic friendships and the relative likeability of certain ethnic groups in ethnically heterogeneous schools. The sample comprised 842 early adolescents (Mage = 11.50 years, SDage = .71; 53% male) from 64 countries of origin who attend multiethnic schools in Southwest Germany. In line with our expectations, interethnic friendships are to a large extent formed on the basis of cultural distance, with more friendships occurring between groups that are culturally more similar. Further, the likeability of children from different ethnic groups follows the so-called ethnic hierarchy, a rank order of different ethnic groups, which is based on perceived similarity with the mainstream group. Interventions to improve early adolescents’ interethnic friendships should aim to reduce perceptions of cultural distance and ethnic hierarchies in intergroup settings.
An Analytical Study of Imphal Adolescents Guidance Needs Across Education Streams
Authors: Valentina Laitonjam , Singh Ritu
Published: April 2024

The present study was an attempt to analyze the adolescent guidance needs in one of the most trouble-torn city of Imphal, India and to identify if they vary according to their education streams. Out of the 60 schools situated in Imphal district, Manipur, India, 30 schools were randomly drawn for the study. Further, from these list, 25% of the total adolescents studying in XI standard were randomly selected for the present study making a total of 651 respondents. The sample comprised 66.51% respondents from Science stream and 33.49% from Arts stream. A self-structured questionnaire was used to study the socio-demographic and socio-economic characteristics of the respondents as well as respondents’ future plans and general ideas on guidance. Guidance needs were assessed in five areas viz. Physical, Social, Psychological, Educational and Vocational areas using Guidance Needs Inventory developed by Dr. J.S. Grewal. The results revealed that guidance needs of the adolescents of Imphal, India didn’t vary according to their education stream. All the adolescents of the region, irrespective of their education stream, reflected extreme need for guidance in all the domains of growth and development.. The need for guidance was most preferred in vocational domain followed by educational domain. Least need for guidance was expressed in psychological domain.
Prevotella induces IL-10 production in monocytic cells
Authors: Oka A , Kanai K , Higaki T , Makihara S , Noda Y , Kariya S , Ando M , Okano M
Published: April 2024

Objective: Clinical remission after immunotherapy for allergic rhinitis is based on an increase in Interleukin-10 (IL-10) production, a regulatory cytokine. We focused on the effect of the oral microbiome on sublingual immunotherapy and investigated the IL-10 production from human monocytic cell line (THP-1 cell) stimulated by one of the commensal gram-negative Prevotella species. Methods: We measured IL-10 production in THP-1 cells stimulated by P. melaninogenica, one of the major bacteria in the Prevotella genus. Lipopolysaccharides (LPS) from Escherichia coli (E. coli) were used to confirm the validity of the experiments. Polymyxin B sulfate salt (PMB), an antibiotic that interacts with LPS, was added to counteract the effect of LPS and P. melaninogenica. Results: P. melaninogenica induced IL-10 production in THP-1 cells (P < 0.01). The IL-10 production in THP-1 cells stimulated with P. melaninogenica was substantially increased when combined with PMB (P < 0.01), whereas IL-10 induced by E. coli LPS was decre- ased when combined with PMB. Conclusion: The IL-10 production in THP-1 cells was induced by P. melaninogenica and was increased when combined with PMB. Further investigations into the mechanisms of IL-10 production induced by Prevotella are needed.
How to establish an endoscopic bariatric practice
Authors: Maselli Daniel B , Donnangelo Lauren L , Coan Brian , McGowan Christopher E
Published: April 2024

Obesity is a chronic, progressive, and relapsing disease of excess adiposity that contributes to more than two hundred medical conditions and is projected to affect more than half the adult population of the United States by the year 2030. Given the limited penetrance of traditional bariatric surgery, as well as the cost and adherence barriers to anti-obesity medications, there is growing interest in the rapidly evolving field of endoscopic bariatric therapies (EBTs). EBTs are minimally invasive, same-day, per-oral endoscopic procedures and include endoscopic sleeve gastroplasty, intragastric balloons, and endoscopic bariatric revisional procedures. This field represents an exciting and innovative subspecialty within gastroenterology. However, building a successful endoscopic bariatric practice requires intentional, coordinated, and sustained efforts to overcome the numerous obstacles to entry. Common barriers include acquisition of the technical and cognitive skillset, practice limitations including the availability of nutrition counseling, facility capabilities, direct-to-consumer marketing, and financial pressures such as facility and anesthesia fees. As the highest-volume center for metabolic and bariatric endoscopy in the United States, we provide insights into successfully establishing an endoscopic bariatric program.
How an Audit-and-Feedback-Based Educational Program Contributed to a Reduction in Environmentally Harmful Waste Anesthetic Gases Among Anesthesiology Residents
Authors: Nordin Emily J. , Dugan Shannon M. , Kusters Andrew C. , Schimek Cassandra A. , Sherman Katherine A. , Ebert Thomas J.
Published: April 2024

Background Waste anesthetic gases (WAGs) contribute to greenhouse gas emissions. US anesthesiology resident education on how to reduce WAG-associated emissions is lacking, so we developed an electronic audit-and-feedback-based program to teach residents to reduce fresh gas flow (FGF) and WAG-associated emissions.

Objective To assess the program’s effectiveness, we measured individual and combined mean FGF of residents during their first, second, and last weeks of the 4-week rotation; then, we calculated the extrapolated annual emissions based on the combined resident mean FGFs. Resident attitudes toward the program were surveyed.

Methods During 4-week rotations at a teaching hospital, anesthesia records were scanned to extract resident-assigned cases, FGF, and volatile anesthetic choice during the 2020-2021 academic year. Forty residents across 3 training years received weekly FGF data and extrapolated WAG-associated emissions data via email. Their own FGF data was compared to the low-flow standard FGF of ≤1 liter per minute (LPM) and to the FGF data of their peer residents on rotation with them. An online survey was sent to residents at the end of the project period.

Results Between their first and last weeks on rotation, residents decreased their mean FGF by 22% (1.83 vs 1.42 LPM; STD 0.58 vs 0.44; 95% CI 1.67-2.02 vs 1.29-1.56; P<.0001). Ten of 18 (56%) residents who responded to the survey reported their individual case-based results were most motivating toward practice change.

Conclusions An audit-and-feedback-based model for anesthesiology resident education, designed to promote climate-conscious practices with administration of volatile anesthetics, was effective.