bluuebunny/crossref_metadata_2025 huggingface dataset:
Nitrogen as a Tracer of Giant Planet Formation. II. Comprehensive Study of Nitrogen Photochemistry and Implications for Observing NH3 and HCN in Transmission and Emission Spectra
Authors: Ohno Kazumasa , Fortney Jonathan J.
Published: October 2023

Atmospheric nitrogen may provide important constraints on giant planet formation. Following our semianalytical work, we further pursue the relation between observable NH3 and an atmosphere’s bulk nitrogen abundance by applying the photochemical kinetics model VULCAN across planetary equilibrium temperature, mass, age, eddy diffusion coefficient, atmospheric composition, and stellar spectral type. We confirm that the quenched NH3 abundance coincides with the bulk nitrogen abundance only at sub-Jupiter-mass (≲1M
J) planets and old ages (≳1 Gyr) for solar composition atmospheres, highlighting important caveats for inferring atmospheric nitrogen abundances. Our semianalytical model reproduces the quenched NH3 abundance computed by VULCAN and thus helps to infer the bulk nitrogen abundance from a retrieved NH3 abundance. By computing transmission and emission spectra, we predict that the equilibrium temperature range of 400–1000 K is optimal for detecting NH3 because NH3 depletion by thermochemistry and photochemistry is significant at hotter planets whereas entire spectral features become weak at colder planets. For Jupiter-mass planets around Sun-like stars in this temperature range, NH3 leaves observable signatures of ∼50 ppm at 1.5, 2.1, and 11 μm in transmission spectra and >300–100 ppm at 6 and 11 μm in emission spectra. The photodissociation of NH3 leads HCN to replace NH3 at low pressures. However, the low HCN column densities lead to much weaker absorption features than for NH3. The NH3 features are readily accessible to JWST observations to constrain atmospheric nitrogen abundances, which may open a new avenue to understanding the formation processes of giant exoplanets.
Extended 3He-rich Time Periods Observed by Solar Orbiter: Magnetic Connectivity and Sources
Authors: Kouloumvakos A. , Mason G. M. , Ho G. C. , Allen R. C. , Wimmer-Schweingruber Robert F. , Rouillard A. P. , Rodriguez-Pacheco J.
Published: October 2023

Observations of Solar Energetic Particles (SEPs) using the Suprathermal Ion Spectrograph (SIS), which is part of the Energetic Particle Detector suite on the Solar Orbiter mission, present an unprecedented opportunity to investigate the composition and evolution of SEPs in close proximity to the Sun. By analyzing data from the SIS instrument, we have compiled a catalog of extended time periods during the first five orbits of the spacecraft around the Sun, which exhibit a significant abundance of 3He. We have identified 33 periods lasting over one day that show a high abundance of 3He. For each period, we examined the SEP characteristics, the magnetic connectivity of the spacecraft, and the magnetically connected regions. Our findings show that these time periods typically span seven days and consist of multiple injections of 3He, and that the peak in 3He flux is observed two days after the time periods begin. The time periods usually start (end) when the spacecraft’s magnetic connection changes to (from) an active region (AR). In most cases, we observed a stable magnetic connection between the spacecraft and one or more ARs, with an average connection time of 4.1 ± 1.8 days.
Machine-learning Inferences of the Interior Structure of Rocky Exoplanets from Bulk Observational Constraints
Authors: Zhao Yong , Ni Dongdong , Liu Zibo
Published: October 2023

Characterizing the interiors of rocky exoplanets is important to understand planetary populations and further investigate planetary habitability. New observable constraints and inference techniques have been explored for this purpose. In this work, we design and train mixture density networks (MDNs) to predict the interior properties of rocky exoplanets with large compositional diversity. In addition to measurements of mass and radius, bulk refractory elemental abundance ratios and the static Love number k
2 are used to constrain the interior of rocky exoplanets. It is found that the MDNs are able to infer the interior properties of rocky exoplanets from the available measurements of exoplanets. Compared with powerful inversion methods based on Bayesian inference, the trained MDNs provide a more rapid characterization of planetary interiors for each individual planet. The MDN model offers a convenient and practical tool for probabilistic inferences of planetary interiors.
A low-loss dual-band bandpass filter using open-loop stepped-impedance resonators and spur-lines for sub-6 GHz 5G mobile communications
Authors: Boufouss Rachida , Najid Abdellah
Published: October 2023

This article presents the design of a low-loss microstrip dual-band bandpass filter with improved inter-band isolation and selectivity for 5G sub-6 GHz mobile communications. The proposed filter utilizes the two first resonance mode frequencies provided by the stepped-impedance resonator to generate its two passbands at 3.6 GHz and 3.5 GHz, and spur-lines located before the input/output ports to improve the isolation and selectivity between passbands. The filter is designed using an RT/Duroid 5870 substrate with a relative permittivity of 2.33 and a thickness of 0.79 mm, manufactured and tested to validate the proposed design. The experimental results show that the filter operates at 3.61 GHz and 5.51 GHz with a 3-dB fractional bandwidth of 12.74% and 16.7%, respectively. Insertion losses at the two passbands center frequencies are 0.6 dB and 0.9 dB. In addition, the proposed filter has the advantage of covering the licensed and unlicensed 5G bands and provides a simple structure without using vias or DGS structures.
Advancements in AI-driven multilingual comprehension for social robot interactions: An extensive review
Authors: Dong Yanling , Zhou Xiaolan
Published: October 2023

In the digital era, human-robot interaction is rapidly expanding, emphasizing the need for social robots to fluently understand and communicate in multiple languages. It is not merely about decoding words but about establishing connections and building trust. However, many current social robots are limited to popular languages, serving in fields like language teaching, healthcare and companionship. This review examines the AI-driven language abilities in social robots, providing a detailed overview of their applications and the challenges faced, from nuanced linguistic understanding to data quality and cultural adaptability. Last, we discuss the future of integrating advanced language models in robots to move beyond basic interactions and towards deeper emotional connections. Through this endeavor, we hope to provide a beacon for researchers, steering them towards a path where linguistic adeptness in robots is seamlessly melded with their capacity for genuine emotional engagement.
Precise detection and localization of R-peaks from ECG signals
Authors: Zhai Diguo , Bao Xinqi , Long Xi , Ru Taotao , Zhou Guofu
Published: October 2023

Heart rate variability (HRV) is derived from the R-R interval, which depends on the precise localization of R-peaks within an electrocardiogram (ECG) signal. However, current algorithm assessment methods prioritize the R-peak detection's sensitivity rather than the precision of pinpointing the exact R-peak positions. As a result, it is of great value to develop an R-peak detection algorithm with high-precision R-peak localization. This paper introduces a novel R-peak localization algorithm that involves modifications to the well-established Pan-Tompkins (PT) algorithm. The algorithm was implemented as follows. First, the raw ECG signal $ X\left(i\right) $ was band-pass filtered (5–35 Hz) to obtain a preprocessed signal $ Y\left(i\right) $. Second, $ Y\left(i\right) $ was squared to enhance the QRS complex, followed by a 5 Hz low-pass filter to obtain the QRS envelope, which was transformed into a window signal $ W\left(i\right) $ by dynamic threshold with a minimum width of 200 ms to mark the QRS complex. Third, $ Y\left(i\right) $ was used to generate QRS template $ T\left(n\right) $ automatically, and then the R-peak was identified by a template matching process to find the maximum absolute value of all cross-correlation values between $ T\left(n\right) $ and $ Y\left(i\right) $. The proposed algorithm achieved a sensitivity (SE) of 99.78%, a positive prediction value (PPV) of 99.78% and data error rate (DER) of 0.44% in R-peak localization for the MIT-BIH Arrhythmia database. The annotated-detected error (ADE), which represents the error between the annotated R-peak location and the detected R-peak location, was 8.35 ms for the MIT-BIH Arrhythmia database. These results outperformed the results obtained using the classical Pan-Tompkins algorithm which yielded an SE of 98.87%, a PPV of 99.14%, a DER of 1.98% and an ADE of 21.65 ms for the MIT-BIH Arrhythmia database. It can be concluded that the algorithm can precisely detect the location of R-peaks and may have the potential to enhance clinical applications of HRV analysis.
Multi-behavioral recommendation model based on dual neural networks and contrast learning
Authors: Zhang Suqi , Wang Wenfeng , Li Ningning , Zhang Ningjing
Published: October 2023

In order to capture the complex dependencies between users and items in a recommender system and to alleviate the smoothing problem caused by the aggregation of multi-layer neighborhood information, a multi-behavior recommendation model (DNCLR) based on dual neural networks and contrast learning is proposed. In this paper, the complex dependencies between behaviors are divided into feature correlation and temporal correlation. First, we set up a personalized behavior vector for users and use a graph-convolution network to learn the features of users and items under different behaviors, and we then combine the features of self-attention mechanism to learn the correlation between behaviors. The multi-behavior interaction sequence of the user is input into the recurrent neural network, and the temporal correlation between the behaviors is captured by combining the attention mechanism. The contrast learning is introduced based on the double neural network. In the graph convolution network layer, the distances between users and similar users and between users and their preference items are shortened, and the distance between users and their short-term preference is shortened in the circular neural network layer. Finally, the personalized behavior vector is integrated into the prediction layer to obtain more accurate user, behavior and item characteristics. Compared with the sub-optimal model, the HR@10 on Yelp, ML20M and Tmall real datasets are improved by 2.5%, 0.3% and 4%, respectively. The experimental results show that the proposed model can effectively improve the recommendation accuracy compared with the existing methods.
Gender Differences in Boardroom Communications
Authors: Al-Enzi Abrar , Diab-Bahman Randa
Published: October 2023

Consumer behavior in regard to gender is often studied as business-to-consumer (B2C), especially by marketers and sales persons. Furthermore, the social science world is full of research regarding gender differences in over-the-counter purchasing matters. However, there is a dearth of information regarding the matter from a business-to-business (B2B) perspective – let alone the boardroom. It would seem rather logical to examine the matter as important observations could lead to similar benefits to those discovered from B2C research. In this chapter, the authors examine the possibility of similar findings in a boardroom setting. A survey was administered to 156 respondents of both genders in different sectors of Kuwait's workforce. Significant differences were found amongst men and women when it came to the way they perceived information in the boardroom and made final decisions accordingly. Also, there are differences between genders regarding the needs and objectives of a sales pitch meeting.
The Monastic Institution
Authors: Diab-Bahman Randa
Published: October 2023

Although workplaces have significantly evolved over the years, they continue to cling onto conventional rules and regulations. Due to the ever-changing journey of the modern-day woman, it is essential to consider their role as a multi-dimensional one in any institute they are present. Not only has the profile of the typical employee changed, the needs of students in higher education have changed tremendously as well. However, although workplaces have significantly evolved over the years, they continue to cling onto conventional rules and regulations. Therefore, the notion of the monastic institute – which is inflictive of the idea of a lack of attachments outside of the workplace, is outdated and no longer serves its stakeholders. In this chapter, critical issues revolving around feminist theories are discussed which support the need for new ideologies pertaining to the needs of the modern-day woman pursuing a job or education alike.
Historical Trends of Disabilities in African Contexts and Their Impact on the Schooling System
Authors: Mcgogo Joyce
Published: October 2023

Disability is an important aspect to consider in education development, given a long history of humiliation, stigmatization, and exclusions in terms of human attributes such as ability, race, gender, religion, etc. This chapter advocates for inclusion of students with disabilities in the education system, especially in South Africa and other parts of the continent. Its argument is that individuals with disabilities are still the most marginalized population in society despite commitments to address their plague and foster their inclusion in all spheres of life. These could be attributable to beliefs that are inherent in the models adopted to provide education and services for individuals with disabilities. The reader will be aware that beliefs about disability vary and have changed over time. The adoption of international policies globally, aiming at addressing the needs of people with disabilities, has framed a positive attitude towards education perspective.
African Theories of Disabilities in the Schooling System
Authors: Mosito Cina P.
Published: October 2023

Questions have been posed elsewhere on whether there are special theories that account for uniquely African experiences. This chapter tackles the question of African theories in relation to disability and schooling. The chapter draws from literature and subjective experiences of those who self-describe as Africans to arrive at a nuanced approach to making sense of tensions found in African contexts when theorising disability in a schooling system. The ensuing product is a collection of understandings, compiled as narratives and discourses, which demonstrate that African theories of disability are complex and evolving. Drawing from a Southern African experience that features stories from Mosa who grew up in Lesotho and Thabo who grew up in South Africa, the chapter supports the importance of theorising for action through a deconstruction of local and subjective conceptions of disability.
Understanding ADHD
Authors: Kalimaposo Kalisto
Published: October 2023

This chapter discusses attention deficit hyperactivity disorder (ADHD) as it occurs in school contexts. ADHD is one of the most common neurodevelopmental disorders in childhood that affects primary school children. ADHD impairs the social development and academic performance of an affected child and is also associated with increased risk of low self-esteem, poor interpersonal relationships, poor school performance, and conduct problems. Symptoms of ADHD include behaviours such as excessive talking, difficulty in paying close attention to details, difficulty in organizing tasks and activities, fidgeting and an inability to remain seated. Children with ADHD are also likely to have a higher absenteeism rate and a higher risk of dropping out of school than their peers without ADHD. There are diverse views of what ADHD is and what should be done about it is not conclusive. The medical model of ADHD has been criticized in some circles as ADHD could also be understood as a cultural construct.
Understanding Prader-Will Syndrome
Authors: Dada Olubukola C. , Adesokan Adedayo
Published: October 2023

Prader Willi Syndrome is a genetic disorder that causes obesity, intellectual disability, and shortness, affecting a part of chromosome 15, usually passed by father. From Nigeria's point of view, Prader Willi Syndrome is called Ara-asanju, Ode and Arara. The main purpose of this chapter is to enlighten the readers on Prader-Willi Syndrome (PWS) from African perspective. The objectives are to familiarize readers with the meaning of Prader-Willi Syndrome, symptoms, and diagnosis of Prader-Willi syndrome (PWS) from African view. It also exposes the reader to causes of Prader-Willi syndrome (PWS) and various treatment strategies that could be used in dealing with individuals with Prader-Willi syndrome (PWS).
Understanding Epilepsy
Authors: Mudzielwana Ndileleni , Mulovhedzi Shonisani Agnes
Published: October 2023

This chapter outlines aspects of understanding epilepsy from an African perspective. The chapter starts by introducing the condition of epilepsy and what research says nationally and internationally with definitions from various views. Furthermore, the chapter discusses causes, symptoms, and impact on children. This chapter highlights the definition of epilepsy and describes epilepsy from various African languages and perspectives. The chapter also shows that epilepsy in children is associated with problems in multiple areas such as their academic achievement, behavioural and emotional adjustments, and social competence. The chapter reports that students with epilepsy often experience negative social consequences due to their condition, and that teachers can do several things to help minimise and assist the children to reach their full potential. In conclusion, the chapter discusses and suggests effective strategies to manage and support the condition.
Understanding Dyspraxia
Authors: Mophosho Munyane , Sebothoma Ben
Published: October 2023

Developmental coordination disorder (DCD) is another name for dyspraxia. It is a motor ability condition characterized by a significant deficiency in the development of motor coordination skills that significantly impairs everyday activities and/or academic achievement. Dyspraxia is often referred to as a “hidden disorder,” because it can manifest itself in children who seem normal on the outside but have many challenges and difficulties. As a result, it is difficult to describe in African languages. The concepts of apraxia, symptoms, and how we can support learners and caregivers will all be discussed in this chapter. Other learning disorders such as dyslexia, autism, attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), Asperger syndrome, or dysgraphia can all be linked to dyspraxia. Anxiety and depression can result because of this. A case study is included so that students can actively participate in deducing the concepts from the example.
Advancement of Photoelectrochemical Properties of WO3-Supported Nano-Materials
Authors: Ray Debasish , Ghosh Sangeeta , Baduri Swarnendu , Sahoo Himanshu Sekhar , Bhattacharya Chinmoy
Published: October 2023

The present global concern associated with the energy crisis and environmental pollution can be addressed through semiconductor photocatalysis technology by converting solar energy into green fuels. WO3 is considered as a favorable candidate due to its durability in the oxidation reaction, primarily in acidic pH, absorption of the visible photon (λ≤480 nm), cost beneficiary, and less toxicity. However, due to the undesirable position of its conduction band, WO3 suffers from photoexcited charge-carrier recombination and shows lower photo-response for the reduction process. To improve the activity under visible light, various approaches have been implemented, such as band alignment and restriction of charge-carrier recombination. This review summarises the numerous endeavors like manipulation of crystal facets and morphologies, incorporation of dopants, and composite formation through hetero-junctions using various semiconductors.
Titanium Oxide for Photodegradation of Organic Pollutants
Authors: Nyairo Wilfrida N. , Shikuku Victor Odhiambo
Published: October 2023

Water scarcity has been exacerbated by environmental pollution caused by increasing global industrialization and urbanization. This has led to continued research for more ecologically safe and cleaner technologies for eliminating pollutants. In the recent past, nano-engineered metal oxides such as titanium oxide (TiO2) have shown promising photocatalytic effect of completely mineralizing organic pollutants to form harmless byproducts. TiO2 is the most frequently used photocatalyst, however its effectiveness is limited to light absorption within the ultra violet region due to its wide band-gap. A redshift by TiO2 has been achieved through tuning of the anatase-rutile phase transitions, doping, surface modifications and creation of multi component heterojunctions. This chapter discusses the synthesis of TiO2–based photocatalysts and photocatalytic activity enhancement of TiO2 through doping and formation of hybrids. Their application in the photo-degradation of dyes and other organic pollutants as well as their limitations and future prospects are also addressed.
From Digital Obsession to Digital Burnout in Second Language Acquisition
Authors: Kurt Ali
Published: October 2023

The COVID-19 pandemic caused an augmented reliance on technology for second language acquisition (SLA). Although digital technologies have proven beneficial in language learning, their excessive use has led to digital burnout among students. This systematic review analyzes the existing research regarding digital burnout in SLA, exploring symptoms, consequences, and coping strategies. Digital burnout has various symptoms, such as decreased motivation and performance, mental fatigue, and physical health problems. Some of the bad effects are low linguistic development, diminished engagement, and negative emotional responses. The review also suggests strategies to avoid digital burnout, such as establishing sound study plans, prioritizing self-care, and establishing clear boundaries between academic and personal physical areas. As a reverse trend, simplicity in SLA with more real-time learning and balanced digitalization should be encouraged, as it brings focus, clarity, and less stress to our lives, creating more time and freedom for personal pursuits and promoting self-sustainability.
Unpacking the Experience of Digital Burnout Among University Students Taking English Courses
Authors: Loo Daron Benjamin , Kaumpungan Margihon Bayu Putra
Published: October 2023

This chapter uses a qualitative approach to provide an in-depth examination of the experience of digital burnout. Doing this would complement existing discussion on burnout, which has typically been done through quantitative means. To this end, this chapter will examine digital burnout in a setting where English is used as a foreign language. Purposive sampling was utilized to recruit participants who reported negative experiences when taking online classes during the pandemic. Data were collected through semi-structured interviews, which were subsequently discussed based on constructs associated with academic burnout, namely being fatigued, feeling ineffective, and cynical. Findings indicate that a prominent factor that was common to the participants was their teachers' lack of competencies in managing an online learning environment, which instigated negative feelings associated with burnout. This indicates that digital burnout may stem from teaching and learning activities done online, and not necessarily a burnout from the use of digital tools or platforms.
Artificial Intelligence in Healthcare
Authors: Huarng Kun-Huang , Yu Tiffany Hui-Kuang , Huang Duen-Huang
Published: October 2023

Artificial intelligence (AI) has been applied to various domains to improve the quality of human life. This chapter outlines the recent application of AI in healthcare. A brief history of AI development is first introduced. Machine learning, one of the current AI advancements, is explained. Successful AI application in different areas of healthcare is then showcased, including different medical diagnosis and long-term care. The popular ChatGPT series of systems and their extraordinary performance are described. This chapter ends with debates and future expectations of AI.
Artificial Intelligence in Sports
Authors: Vila-Lopez Natalia , Kuster-Boluda Ines , Sarabia-Sanchez Francisco J.
Published: October 2023

In the sports industry, artificial intelligence has become a powerful tool for sports managers interested in getting private sponsorships and for DMOs interested in branding a place. In this scenario, two main objectives guide this chapter (1) to generate a ranking of the leading Spanish marathons based on their presence on the four most important social networks in Spain (Facebook, Twitter, Instagram, and YouTube) and (2) to measure the engagement on social networks generated by the first of the marathons identified in the ranking. The official profiles of the accounts of the 10 marathons with the highest number of finishers in 2022 in Spain have been monitored on the social networks listed (Facebook, Twitter, Instagram, and YouTube). As the results show, a marathon can generate high network engagements. The destination's image can be highly favoured thanks to small local events (such as marathons) capable of generating a lot of movement on social networks. However, not all social networks work equally well in promoting sporting events capable of generating engagement.
Emotional Intelligence for Entrepreneurial Success
Authors: Devi Saloni , Chauhan Vinay , Vaid Sonali
Published: October 2023

Emotions affect creativity and innovation. An entrepreneur who is emotionally intelligent encourages the team members to think out of the box whenever the situation is not on the good of the organization. This leads to higher levels of creativity and results in successful initiatives, and idea sharing is best which results in the achievement of goals in the organization. The present study is based on the inferences of literature review mainly collected from important databases like Scopus and Web of Science. The aim of this study is to construct a conceptual framework to explore the role of emotional intelligence in nurturing creativity and innovation for entrepreneurial success.
Artificial Intelligence Applications in Human Resource Management
Authors: Rani Chandni , Kajla Tanveer
Published: October 2023

Human resource is facing a transformation challenge with artificial intelligence(AI). AI's position is larger in various human resource (HR) functions where robotics companies are able to handle recruiting, employing, analyzing data, collecting data, reducing workplace workload, and improving workplace performance. To report this gap, the current study purposes to head to the digital revolution by means of various methods to streamline resources through usage of big data analytics, AI, and cloud computing. The prime role of this research is to address the ensuing research on significant journals, keywords, and affiliations, authors, countries, elevating the literature on AI in human resource management (HRM) using bibliometric content analysis approach. Four prominent themes emerged in the literature which give directions on the role of information systems in building the framework for AI, machine learning applications, decision making, and handling the recruitment process with neural networks. Further, the current research recommends several suggestions for the part of future direction AI in HRM.
Exploring the Efficacy of Artificial Intelligence Techniques in Predicting Stock Market Trends
Authors: Sood Shantnu , Gupta Yashwant Kumar , Bhushan Puneet
Published: October 2023

Stock price prediction is a challenging task, traditionally relying on fundamental, technical, and time series analysis. However, AI and ML techniques offer new opportunities for enhancing predictions in equity markets. In recent years, considerable efforts have been made to identify these patterns in stock markets, with the aim of facilitating profitable trading and investment decisions. Consequently, a wealth of studies and research endeavors have emerged in this field. This chapter explores diverse techniques used for stock market prediction, analyzing their effectiveness. The techniques examined in this study are categorized into three groups: traditional ML, deep learning, and sentiment analysis. Results show naive Bayesian and random forests as promising conventional ML models, while LSTM neural network provides accurate predictions among deep learning models. This chapter sheds light on the employed and researched ML models, offering insights into their strengths in forecasting market trends.
Virtual Experiences, Real Consequences
Authors: Kashyap Anil Kumar , Sahu Ity
Published: October 2023

According to Business Wire, the e-commerce market in India is expected to reach US$107.3 billion in 2023 and attract more players in online retailing. E-commerce is essentially backed by technology, and it can be assumed that e-commerce users are tech savvy, seek solutions in technology. VR is one of the important components of artificial intelligence transforming online retail experience to a large extent. The chapter explores the transformative effects of VR on consumer behavior. The chapter begins with the introduction and rise of VR in mitigating the limitations of online shopping and explains how VR is substituting physically examining of products, and how it empowers consumers to make more informed purchasing decisions. Later, the role of AI in virtual e-commerce is discussed followed by shopping convenience for e-commerce users and the future of VR in e-commerce. The findings of this chapter reveal that VR significantly impacts consumer behavior by fostering a sense of presence, interactivity, and immersion. At last, a conclusion is presented.
Specific Language Impairment and Autism
Authors: Zaragas Harilaos , Sarris Dimitrios , Papadimitropoulou Panagoula , Gatzoyia Dimitra , Rapti Danai
Published: October 2023

The ability to communicate through language is extremely important for social interaction and expression. Spoken language and communication develop naturally and spontaneously in many children; however, there are cases of children who experience problems and difficulties in learning and using language. In order to support children with difficulties, it is important to thoroughly determine how language terms and concepts are understood, and to explore ways of enhancing their language skills. More specifically, this text focuses on the cases of children with specific language impairment (SLI) and autism spectrum disorder (ASD).
Attention Deficit Hyperactivity Disorder (ADHD) and Deficits in Language Development
Authors: Angelidou Asimina , Argyriadis Alexandros
Published: October 2023

Children with ADHD often have difficulties in their language development. The studies concerning the language development of children with ADHD refer mainly to the field of phonology, semantics, morphosyntax, and mainly pragmatics. However, regardless of the eventual speech delay, a large percentage of children with ADHD show strong problems in oral speech as well. At a young age, children with ADHD are characterized by difficulties in phonetic perception, which may contribute to some of the children's aberrant language development. It appreciates how speech problems relate to auditory discrimination difficulties, with difficulty focusing attention on a specific auditory stimulus. The difficulties they face in their oral language are also present in their written language. This essay studies the context of ADHD and deficits in language development.
The Role of Executive Functions (EFs) in the Reading Skills of Children With ADHD and Dyslexia
Authors: Fiorentzi Krystallenia , Antoniou Alexandros-Stamatios
Published: October 2023

Reading is a complex task, where lower-level and higher-level skills interact with each other. Reading skills have been connected to academic and occupational outcomes and this motivated the present literature review. Higher-order skills, executive functions (EFs), impact various skills, including reading, and this is an area of increasing interest especially in special populations, such as ADHD and dyslexia. There is no definite conclusion regarding the EF profile and relation of EFs to reading performance in both disorders. There is evidence indicating deficits in EFs for both disorders, while there is also evidence suggesting little or no differences in relation to typically developing (TD) peers. Literature review showed that working memory (WM) is repeatedly found to influence reading skills of children with ADHD and dyslexia; inhibition and shifting are also related to reading performance. EF difficulties in both disorders and in TD children affect decoding, fluency, and reading comprehension (RC).
Developing Knowledge About Cultural and Heritage Tourism Products Through Digital Story Telling
Authors: Kulshrestha Ruchika , Pandey Ashutosh , Sharma Aanchal
Published: October 2023

Storytelling in the human world is a central aspect. The application will lead to a variety of advantages as a teaching tool. The teachers in tourism education in India are not widely used to tell a story. The responses of students as a pedagogical method are also in this sense comparatively underrepresented. Consequently, after induction into the program, this research analyzed the experiences of the faculty members who were teaching the various tourism courses in India. The study outlines a structured learning and learning process of the cultural and heritage tourism products through digital storytelling at each level. The chapter also looked into the effectiveness of digital storytelling among students. The chapter emphasizes the role of the story in studying heritage tourism products, cross-cultural connectivity, and critical reflection through digital storytelling. It is therefore suggested that during the course, it is necessary to introduce the digital storytelling concept to Indian students.
Unveiling the Buying Behaviour of Gen Z for Hospitality Products
Authors: Sharma Rakesh , Singh Gurucharan
Published: October 2023

In today's rapidly evolving hospitality landscape, the emergence of Generation Z as a prominent consumer group has transformed the way businesses, particularly in the smart hotel sector, approach their marketing and service delivery strategies. This chapter explores the intricate buying behaviors of Generation Z within the context of smart hotels, where technology-driven experiences play a central role. By delving into their preferences, motivations, and decision-making processes, this chapter offers valuable insights to guide smart hotel strategies in effectively catering to the needs of this tech-savvy generation.
Technological Transformation in Hospitality Industry
Authors: Shashwat Kiran , Rani Monika
Published: October 2023

Technology in the hospitality sector represents the convergence of innovation and service in a sector dedicated to delivering outstanding visitor experiences. Fundamentally, the goal of technology in the hospitality industry is to close the gap between traditional principles of hospitality and today's expectations of customization at all the spectrums of hospitality operations. The development of environmentally friendly and sustainable technology solutions has also improved the hospitality industry. The industry's carbon footprint is decreased through using energy-efficient technology, waste management techniques, and digital documentation. This chapter aims to review various effects of technology and its transformations on the hospitality industry. This chapter also focuses on the substantial transformation in hospitality sector with the advent of technology integration for enhancing operational effectiveness of businesses and smooth customer's experience with the sustainable approach towards its resources.
Digital Hacks, Creativity Shacks, and Academic Menace
Authors: Soubhari Tushar , Nanda Sudhansu Sekhar , Lone Tariq Ahmad , Shahanas Beegam P. P.
Published: October 2023

The creative and digital content business, among many others, is going through a significant paradigm shift as a result of advances in AI technology. AI technologies are enhancing human talents and changing the creative scene in a variety of ways, including content production and curation. The potential for innovation and expansion could appear endless, revolutionary, and forward-thinking, but difficulties like job loss, issues with originality and ethics, and the dissolution of human connections are all producing an underlying worry and anxiety across many industries. The interaction between people and AI fosters creativity and creates new opportunities for content production. Academic dishonesty undermines the educational process and undermines the reputation of academic institutions. A few cases catalogued from the educational contexts have been highlighted to evaluate the bright and dark sides of using AI affecting the academic integrity and reliability of substances used in the modern world.
Sophisticated-Sinister-Stealth Attacks
Authors: Bhardwaj Akashdeep
Published: October 2023

APTs typically involve a series of carefully planned and coordinated steps, including reconnaissance, initial compromise, establishment of a foothold, and lateral movement to other systems. To carry out their objectives, APT actors may use various techniques, including social engineering, spear-phishing, and exploitation of software vulnerabilities. APTs are often launched by nation-state actors or well-funded criminal organizations, who have the resources and expertise to carry out complex attacks. Detecting and responding to APTs requires a multi-layered approach that includes robust cybersecurity measures, such as network segmentation, intrusion detection and prevention systems, and endpoint protection. Additionally, organizations must have a strong incident response plan in place to quickly identify and contain APT attacks before they cause significant damage. These aspects are discussed in detail in this chapter.
Risk Management in the Current Digital Reality of Organizations
Authors: Ferreira Daniel Jorge , Mamede Henrique S. , Mateus-Coelho Nuno
Published: October 2023

The global overview of the challenges faced in trying to minimise the risks of organisations in the face of cyber-attacks is arduous for any organisation. Defining an appropriate risk management model that proactively minimises cybersecurity incidents is a critical challenge. Many malicious attacks occur daily, and there is only sometimes an adequate response. There is a significant investment in research to identify the main factors that may cause such incidents, always trying to have the most appropriate response and, consequently, potentiating the response capacity and success. At the same time, several different methodologies evaluate risk management and the maturity level of organisations. Due to the lack of predictive models based on data (evidence), there is a significant investment in research to identify the main factors that may cause such incidents, starting to design models based on AI - Artificial Intelligence. This research will go in the direction of developing a user-friendly model supporting the assessment of the methodological aspects of an organisation.
The Role of Blockchain Technology in Organizational Cyber Security
Authors: Sule Dauda , Ameh Jude Enenche , Abu Usman Suleiman
Published: October 2023

Distributed ledger technology (DLT), decentralized finance (DeFi), blockchain – these are terms that have been trending especially in technology circles. Today, blockchain has gained more acceptance, but sceptics continue to raise concerns about the technology's scalability, security, and long-term viability. There are also concerns regarding its being associated with crime and the dark web, which might imply it will have negative consequences if adopted. It has its own peculiar cyber security loopholes, but these can be addressed. That notwithstanding, organizations stand to gain from the blockchain in terms of cyber security; especially its qualities of decentralization and immutability. It has been successfully implemented in some sectors with positive results. This chapter seeks to illustrate how the blockchain can be used to boost and optimize cyber security for organizations.
The Dilemmas of Criminal Liability Regarding Cybercrimes on Wireless Sensor Networks (WSNs)
Authors: Nehinbe Joshua Ojo
Published: October 2023

New studies have revealed serious dilemmas that can confront investigators in the arrest and investigations of suspects of complex cybercrimes on wireless sensor networks (WSNs) and whenever they must subsequently institute criminal liability against agents of the crime. Accordingly, some investigators continue to face challenges to criminalize proven suspects and allocate compensations for negligence to lawless complainants. This chapter used mixed methods and different datasets to critically examine and explain the above issues. Datasets that were qualitatively and quantitatively analyzed with Snort IDS suggest that criminal liabilities on WSNs may be settled with concurrent negligence in the ratio of 0.27, comparative negligence in the ratio of 0.32; contributory negligence in the ratio of 0.18 and vicarious negligence in the ratio of 0.23. Similarly, employer may be criminalized for cybercrimes committed by his employee, employee can be criminalized for cybercrimes committed by his employer, and employer with his employee can be criminalized jointly for their negligence to stop cybercrimes on WSNs.
Methodologies Based on Hardware Performance Counters for Supporting Cybersecurity
Authors: Pessoa Pablo Philipe , do Monte Aline , Dantas Camila , Maciel Paulo
Published: October 2023

Cybersecurity is a critical area of information technology, where prevention, detection, and mitigation of cyberattacks are crucial to ensure system and data integrity. This chapter presents several methods and strategies that adopt hardware performance counters (HPCs) as the paramount protection utility, with the aid of analysis and advanced techniques from several areas of statistics and computing, to support cybersecurity. Furthermore, the chapter discusses the need for broader approaches, including preventive and protective measures, regular penetration testing, user awareness, implementation of robust security policies, and advanced threat detection techniques. While traditional security tools such as implementing IDSs, IPSs, firewalls, antivirus, and other solutions are critical, they must be complemented with more comprehensive approaches to deal with the increasing sophistication of cyberattacks, and HPCs provide this support with efficiency.
Cyber Criminals and Data Privacy Measures
Authors: Belmabrouk Karima
Published: October 2023

Cyber criminals pose a significant threat to data privacy, seeking to exploit weaknesses in digital security systems to gain access to sensitive information. Data privacy measures, such as antivirus software, firewalls, and employee training, are implemented to protect against unauthorized access and theft of personal and sensitive data. However, cyber criminals continue to find ways to circumvent these measures, leading to an ongoing arms race in the world of cybersecurity. To stay ahead of evolving threats, ongoing investments in research and development, as well as partnerships between government agencies, private sector organizations, and cybersecurity experts, are crucial in strengthening data privacy measures and protecting against cyber criminals.
Cybercrime and Insider Threats in Healthcare Organizations
Authors: Espinoza Michelle Denise
Published: October 2023

Cybercrime costs an estimated $575 billion per year and healthcare continues to be the most targeted sector in the world. News headlines are rife with data leaks and data breach incidents. These breaches lead to the theft of personal, financial, and health information from users who are often only notified of the breach well after it occurred, and the damage has already been done. Insider threats can be loosely categorized as malicious or negligent, based on their intent (or lack thereof). This case study focuses on one such malicious incident where a ring of hospital employees was indicted for allegedly selling patient credit card and medical information online. The authors provide practitioners with a deeper understanding of how PII is misused, motivations for its theft, and recommendations to avoid such incidents in their own organizations.
Organizational Dynamics and Complexities in Healthcare Organizations
Authors: Baez Maria D. , Burrell Darrell Norman , Richardson Kevin , Quisenberry William L. , Hines Angela , Mairs-Levy Judith , Jones Laura Ann , Daryousef Marlena , Aridi Amalisha Sabie
Published: October 2023

Research shows that 70-90% of mergers and acquisitions (M&As) fail due to culture clashes. The number of mergers and acquisitions in the healthcare industry has been increasing, driving the need for better change management practices. Hospital mergers and acquisitions are essential for financially struggling hospitals, especially rural hospitals. This chapter explores the value of management consulting interventions as tool to make mergers in healthcare more effective.
Laborera Risk Management Case Study of Artificial Intelligence for Human Resources
Authors: Hall Marie L.
Published: October 2023

Laborera is a fictional company. The company is a cloud-based software vendor that specializes in human capital management applications. Laborera is entangled in a class action discrimination suit for its artificial intelligence tools that allegedly prescreen and disqualify applicants in protected categories. Porter's five forces model and McKinsey's strategic horizons offer a framework for strategic review. Deal and Kennedy and the Denison organizational culture model are used to strengthen Laborera's organizational culture. The Bridges transition model and the McKinsey 7-S model enable transition and thoughtful organizational change management. Laborera improves ethical decision making, including decision processes involving a human-machine team, using the fairness/justice approach, and the common good approach. This case study demonstrates theoretical applications of risk management for software companies desiring to leverage artificial intelligence within innovative software applications.
Examining Security Awareness Lapses and Critical Cyber Threats Against the Department of Defense Military Supply Chain Systems
Authors: Muller S. Raschid
Published: October 2023

Cyber threats have become a major concern in today's world. As the United States Department of Defense (DoD) increasingly relies on the military supply chain systems to support the operations of their military forces, cyber threats have the potential to cause significant damage. These systems are responsible for the transportation, storage, and distribution of materials and equipment from the supplier to the end user, which includes both military personnel and civilian personnel. It is also responsible for the acquisition, maintenance, and disposal of materials and equipment. The purpose of this chapter is to examine the critical cyber threats posed to the DoD military supply chain systems and provide recommendations to address them.
Internal Control Review of Business Purchasing Card Programs
Authors: Manfreda-Foley Teresa
Published: October 2023

This chapter examined the internal control procedures for an organization's purchasing card program. Utilizing the results of the company's most recent audit, it was found that inefficiencies existed in the company's internal control processes. The data provided also indicated that processes and procedures are not currently in place for the acceptable use of the company's credit card. This lack of policies and procedures led to the misappropriation of funds. Theoretical and practical implications were discussed in this chapter. This study reveals how a risk management plan can protect the institution and the employees.