bluuebunny/crossref_metadata_2025 huggingface dataset:
CMB-S4: Iterative Internal Delensing and r Constraints
Authors: Belkner Sebastian , Carron Julien , Legrand Louis , Umiltà Caterina , Pryke Clem , Bischoff Colin ,   CMB-S4 Collaboration
Published: March 2024

The tightest constraints on the tensor-to-scalar ratio r can only be obtained after removing a substantial fraction of the lensing B-mode sample variance. The planned Cosmic Microwave Background (CMB)-S4 experiment (cmb-s4.org) will remove the lensing B-mode signal internally by reconstructing the gravitational lenses from high-resolution observations. We document here a first lensing reconstruction pipeline able to achieve this optimally for arbitrary sky coverage. We make it part of a map-based framework to test CMB-S4 delensing performance and its constraining power on r, including inhomogeneous noise and two non-Gaussian Galactic polarized foreground models. The framework performs component separation of the high-resolution maps, followed by the construction of lensing B-mode templates, which are then included in a parametric small-aperture map cross-spectra-based likelihood for r. We find that the lensing reconstruction and framework achieve the expected performance, compatible with the target σ(r) ≃ 5 · 10−4 in the absence of a tensor signal, after an effective removal of 92%–93% of the lensing B-mode variance, depending on the simulation set. The code for the lensing reconstruction can also be used for cross-correlation studies with large-scale structures, lensing spectrum reconstruction, cluster lensing, or other CMB lensing-related purposes. As part of our tests, we also demonstrate the joint optimal reconstruction of the lensing potential with the lensing curl potential mode at second order in the density fluctuations.
Conditions for Relativistic Magnetic Reconnection under the Presence of Shear Flow and Guide Field
Authors: Peery Sarah , Liu Yi-Hsin , Li Xiaocan
Published: March 2024

The scaling of the relativistic reconnection outflow speed is studied in the presence of both shear flows parallel to the reconnecting magnetic fields and guide fields pointing out of the reconnection plane. In nonrelativistic reconnection, super-Alfvénic shear flows have been found to suppress reconnection. We extend the analytical model of this phenomenon to the relativistic regime and find similar behavior, which is confirmed by particle-in-cell simulations. Unlike the nonrelativistic limit, the addition of a guide field lowers the in-plane Alfvén velocity, contributing to slower outflow jets and the more efficient suppression of reconnection in strongly magnetized plasmas.
Cracking the Relation between Mass and 1P Star Fraction of Globular Clusters. I. Present-day Cluster Masses as a First Tool
Authors: Parmentier Geneviève
Published: March 2024

The phenomenon of multiple stellar populations is exacerbated in massive globular clusters, with the fraction of first-population (1P) stars a decreasing function of the cluster present-day mass. We decipher this relation in far greater detail than has been done so far. We assume (i) a fixed stellar mass threshold for the formation of second-population (2P) stars, (ii) a power-law scaling

F

1
P

∝

m

ecl

−
1

between the mass m
ecl of newly formed clusters and their 1P star fraction F
1P, and (iii) a constant F
1P over time. The F
1P(m
ecl) relation is then evolved up to an age of 12 Gyr for tidal field strengths representative of the entire Galactic halo. The 12 Gyr old model tracks cover the present-day distribution of Galactic globular clusters in the (mass, F
1P) space extremely well. The distribution is curtailed on its top right side by the scarcity of clusters at large Galactocentric distances and on its bottom left side by the initial scarcity of very high-mass clusters and dynamical friction. Given their distinct dissolution rates, “inner” and “outer” model clusters are offset from each other, as observed. The locus of Magellanic Clouds clusters in the (mass, F
1P) space is as expected for intermediate-age clusters evolving in a gentle tidal field. Given the assumed constancy of F
1P, we conclude that 2P stars do not necessarily form centrally concentrated. We infer a minimum mass of 4 · 105
M
⊙ for multiple-population clusters at secular evolution onset. This high-mass threshold severely limits the number of 2P stars lost from evolving clusters, thereby fitting the low 2P star fraction of the Galactic halo field.
Encounter Circumstances of Asteroid 99942 Apophis with the Catalog of Known Asteroids
Authors: Wiegert Paul , Hyatt Benjamin
Published: March 2024

Asteroid 99942 Apophis will pass near Earth in 2029 April. Expected to miss our planet by a safe margin, that could change if Apophis's path were perturbed by a collision with another asteroid in the interim. Though the statistical chance of such a collision is minuscule, the high risk associated with Apophis motivates us to examine even this very unlikely scenario. In this work, we identify encounters between known asteroids and Apophis up to 2029 April. Here we show that Apophis will encounter the 1300 m diameter asteroid 4544 Xanthus in 2026 December. Their minimum orbit intersection distance is less than 10,000 km, with Apophis passing that closest point just 4 hr before Xanthus. Though a direct collision is ruled out, the encounter is close enough that material accompanying Xanthus (if any) could strike Apophis. We also identify other asteroid encounters that deserve monitoring.
Four new species and one newly-recorded species of the genus Opopaea Simon, 1892 (Araneae, Oonopidae) from southern China, with a key to Chinese species
Authors: Zhou Yang , Bian Dongju , Yang Zizhong , Zhang Zhisheng , Tong Yanfeng , Li Shuqiang
Published: March 2024

Five species of the genus Opopaea Simon, 1892 from southern China are recognised, including four new species: Opopaea mangun Tong & Li, sp. nov., Opopaea taibao Tong & Yang, sp. nov., Opopaea wenshan Tong & Zhang, sp. nov. and Opopaea yuhuang Tong & Li, sp. nov. from Yunnan and one newly-recorded species: Opopaea foveolata Roewer, 1963 from Hainan. Detailed diagnoses, descriptions and photomicroscopy images of new species are provided, based on specimens of both sexes. A key to species of the genus Opopaea from China is provided.
Analyzing the Relationship Between Self-Efficacy in Protecting Against Substance Use and Loneliness in Adolescents: A Cross-Sectional Survey
Authors: Kayaoğlu Kübra , Özer Duygu
Published: March 2024

Purpose:

To analyze the relationship between self-efficacy in protecting against substance use and loneliness in adolescents.

Method:

This descriptive, cross-sectional study comprised 400 adolescents. A Sociodemographic Data Form, Self-Efficacy for Adolescents Protecting Against Substance Abuse Scale (SEAPSAS), and Short-Form UCLA Loneliness Scale (ULS-8) were used for data collection. Regression analysis and Pearson correlation analysis, as well as descriptive statistics, were used in data analysis.

Results:

Mean ULS-8 total score was 17.94 (
SD
= 5.07) and mean SEAPSAS total score was 68.78 (
SD
= 17.59). A weak significant negative relationship was found between mean ULS-8 total score and mean SEAPSAS subdimensions and total score. As a result of regression analysis, it was determined that ULS-8 total score negatively affected mean SEAPSAS total score by 24.9% (R
2
= 0.249; B = −1.713;
p
< 0.001).

Conclusion:

Loneliness in adolescents, which was observed to negatively impact self-efficacy in protecting against substance use, should be addressed by psychiatric nurses through prevention activities and support programs and services, such as early detection and intervention. [
Journal of Psychosocial Nursing and Mental Health Services, 62
(9), 29–36.]
Existence, and Ulam's types stability of higher-order fractional Langevin equations on a star graph
Authors: Chen Gang , Ni Jinbo , Fu Xinyu
Published: March 2024

A study was conducted on the existence of solutions for a class of nonlinear Caputo type higher-order fractional Langevin equations with mixed boundary conditions on a star graph with $ k+1 $ nodes and $ k $ edges. By applying a variable transformation, a system of fractional differential equations with mixed boundary conditions and different domains was converted into an equivalent system with identical boundary conditions and domains. Subsequently, the existence and uniqueness of solutions were verified using Krasnoselskii's fixed point theorem and Banach's contraction principle. In addition, the stability results of different types of solutions for the system were further discussed. Finally, two examples are illustrated to reinforce the main study outcomes.
Special major 1, 3 satisfiability logic in discrete Hopfield neural networks
Authors: Manoharam Gaeithry , Kassim Azleena Mohd , Abdeen Suad , Kasihmuddin Mohd Shareduwan Mohd , Rusdi Nur 'Afifah , Romli Nurul Atiqah , Zamri Nur Ezlin , Mansor Mohd. Asyraf
Published: March 2024

Currently, the discrete Hopfield neural network deals with challenges related to searching space and limited memory capacity. To address this issue, we propose integrating logical rules into the neural network to regulate neuron connections. This approach requires adopting a specific logic framework that ensures the network consistently reaches the lowest global energy state. In this context, a novel logic called major 1,3 satisfiability was introduced. This logic places a higher emphasis on third-order clauses compared to first-order clauses. The proposed logic is trained by the exhaustive search algorithm, aiming to minimize the cost function toward zero. To evaluate the proposed model effectiveness, we compare the model's learning and retrieval errors with those of the existing non-systematic logical structure, which primarily relies on first-order clauses. The similarity index measures the similarity benchmark neuron state with the existing and proposed model through extensive simulation studies. Certainly, the major random 1,3 satisfiability model exhibited a more extensive solution space when the ratio of third-order clauses exceeds 0.7% compared to first-order clauses. As we compared the experimental results with other state-of-the-art models, it became evident that the proposed model achieved significant results in capturing the overall neuron state. These findings emphasize the notable enhancements in the performance and capabilities of the discrete Hopfield neural network.
Global behavior of a discrete population model
Authors: Hu Linxia , Shen Yonghong , Jia Xiumei
Published: March 2024

In this work, the global behavior of a discrete population model

   \begin{document}$ \begin{equation*} \begin{cases} x_{n+1}& = \alpha x_n e^{-y_n}+\beta,\\ y_{n+1}& = \alpha x_n(1-e^{-y_n}), \end{cases}\quad n = 0,1,2,\dots, \end{equation*} $\end{document}

is considered, where $ \alpha\in (0, 1) $, $ \beta\in (0, +\infty) $, and the initial value $ (x_{0}, y_0)\in [0, \infty)\times [0, \infty) $. To illustrate the dynamics behavior of this model, the boundedness, periodic character, local stability, bifurcation, and the global asymptotic stability of the solutions are investigated.
Limiting behaviors of a bi-virus model with two interaction factors
Authors: Zhang Benjamin
Published: March 2024

Traditional compartmental models describe the evolution of a virus over a population of nodes; one common model separates the population into compartments of susceptible, infected, and removed nodes. More complex bi-virus models describe this evolution for two competing viruses in the same population, having an additional parameter known as the virus interaction factor, which defines the effect one virus has on the rate of infection of another. Although these models are generally used in the context of infectious diseases, they could also describe the spread of ideas, or competing products in a market of consumers. In this paper, a new model was proposed that added separate interaction factors for each virus, differentiating the effects of viruses on one another. Adding this additional parameter will allow for more accurate interactions to be modeled and analyzed. A focus was placed on the limiting behavior of this model, an eventual end-state equilibrium where the number of nodes in each compartment remains constant. Relationships between the virus interaction factors and the strengths of the viruses on the limiting behavior were identified. Finally, a complete numerical solution to the model and a condition for real-valued limiting behaviors was calculated and tested against the simulation data.
Managing extreme cryptocurrency volatility in algorithmic trading: EGARCH via genetic algorithms and neural networks
Authors: Alaminos David , Belén Salas M. , Callejón-Gil Ángela M.
Published: March 2024

The blockchain ecosystem has seen a huge growth since 2009, with the introduction of Bitcoin, driven by conceptual and algorithmic innovations, along with the emergence of numerous new cryptocurrencies. While significant attention has been devoted to established cryptocurrencies like Bitcoin and Ethereum, the continuous introduction of new tokens requires a nuanced examination. In this article, we contribute a comparative analysis encompassing deep learning and quantum methods within neural networks and genetic algorithms, incorporating the innovative integration of EGARCH (Exponential Generalized Autoregressive Conditional Heteroscedasticity) into these methodologies. In this study, we evaluated how well Neural Networks and Genetic Algorithms predict "buy" or "sell" decisions for different cryptocurrencies, using F1 score, Precision, and Recall as key metrics. Our findings underscored the Adaptive Genetic Algorithm with Fuzzy Logic as the most accurate and precise within genetic algorithms. Furthermore, neural network methods, particularly the Quantum Neural Network, demonstrated noteworthy accuracy. Importantly, the X2Y2 cryptocurrency consistently attained the highest accuracy levels in both methodologies, emphasizing its predictive strength. Beyond aiding in the selection of optimal trading methodologies, we introduced the potential of EGARCH integration to enhance predictive capabilities, offering valuable insights for reducing risks associated with investing in nascent cryptocurrencies amidst limited historical market data. This research provides insights for investors, regulators, and developers in the cryptocurrency market. Investors can utilize accurate predictions to optimize investment decisions, regulators may consider implementing guidelines to ensure fairness, and developers play a pivotal role in refining neural network models for enhanced analysis.
Marcadores sociodemográficos y nuevas tecnologías en las generaciones catalanas. 1926-2005.
Authors: Damoun Osama , Domingo Andreu , Bayona i Carrasco Jordi
Published: March 2024

En este artículo delimitamos y caracterizamos las generaciones catalanas contemporáneas en torno a su tamaño y a tres marcadores sociodemográficos (el lugar de nacimiento, el nivel de instrucción y su posición en la revolución digital), enmarcándolas siguiendo los acontecimientos históricos que han marcado su juventud y las diferencias de género. Con datos de censos de población y el padrón continuo, hemos confirmado que las características sociodemográficas analizadas se erigen como fronteras generacionales. Explotando la encuesta de uso de las TIC en hogares del Instituto Nacional de Estadística, encontramos indicios de diferencias generacionales. La agrupación decenal propuesta se adecua con más precisión al contexto catalán y, por extensión, español, siendo fundamento para futuras investigaciones desde una perspectiva generacional.
Developing a Data Lakehouse for a South African Government-Sector Training Authority
Authors: Mthembu Zamani Khulekani , Patel Sulaiman Saleem , Naicker Nalindren , Joseph Seena , Madamshetty Lavanya , Moonsamy Devraj , Akinola Ayotuyi Tosin , Govender Thamotharan Prinavin
Published: March 2024

The Durban University of Technology is undertaking a project to develop a data lakehouse system for a South African government-sector training authority. This system is considered critical to enhance the monitoring and evaluation capabilities of the training authority and ensure service delivery. Key to the successful deployment of the data lakehouse is the implementation of suitable data governance for the system. This chapter identifies the key components of data governance relevant to the system through a systematic literature review process. Thereafter, the components of data governance are mapped against the technical architecture of the data lakehouse and the governance mechanisms are for all lakehouse system components are defined. A practitioner expert evaluation is presented to assess the data governance mechanisms. Overall, the data governance framework and resulting mechanisms were found to be sufficient, except regarding ensuring data quality. The need for separate studies focused on ensuring data quality for the data lakehouse system was identified as future work.
Overtourism in the Himalayan Region
Authors: Mishra Shreeansh , Mishra Jitendra Mohan
Published: March 2024

Due to inadequate management practices historically associated with tourism development in the Himalayan region, significant repercussions have arisen. While studies have explored the phenomenon of over-tourism in the region, there is a need for a comprehensive understanding of the impact of over-tourism in the Himalayan region, and to revisit the existing tourism management practices and effective mitigation strategies concerning the ecological, socio-cultural, and economic impacts caused by excessive tourist influx to be evolved. This study explores sustainable visitor management practices as a means to address the challenges posed by over-tourism in the Himalayas. Existing contextual literature has been reviewed to understand the pros and cons of over-tourism in the Himalayan region. Accordingly, the study suggested measures to overcome the impacts of over-tourism through sustainable visitor management practices and offers valuable insights for policymakers, destination managers, and local communities in fostering sustainable tourism practices in the Himalayan region
Promotion of Homestay for the Sustainable Livelihood of the Local Community in the North Eastern Himalayan Region of India
Authors: Devi Hawaibam Jhalari , Biswas Soumendra Nath
Published: March 2024

Northeastern India is a region with unique culture and traditions and a varied landscape offering a greater potential to promote homestays. It is a locally owned and operated family business that provides visitors with a more enriched experience of nature as well as amenities like local cuisine, traditional culture, lifestyle, and local resources. This idea is ideal for the Northeastern Himalayan region of India. This paper will concentrate on understanding the importance of homestay in developing Community-based tourism and comprehending the potential of sustainable Community-based tourism in the Northeastern Himalayan region of India. A review was undertaken and the paper is designed to identify the key areas for the promotion of homestays and their contribution to the growth of sustainable community-based tourism and the benefits it offers in the Northeastern Himalayan Region of India.
Role and Importance of Nature-Based Health Tourism in the Himalayan Region
Authors: Parashar Arunesh , Agarwal Prachi
Published: March 2024

Himalayas are a multifaceted site of subjective, global, and metaphysical importance that are responsible in maintaining a form of tourism that satisfies the person's main motive for maintaining and strengthening the physical, spiritual, emotional, and psychological health. There are numerous opportunities that are availed in contrast with natural resources available in the Himalayan region that will help in boosting natural healing procedures and foster physical and psychic well-being of the tourists. In the circumstances of this fast-paced urbanisation, the Himalayas are the only option to get nature therapy and able to enjoy their close connection with it. Human-nature relationships have always been considered very important. So, theory of wellness in the Himalayas is supported by the research with the fact that nature has a great impact on different facets of person's physical, psychological, social, and spiritual life. This chapter seeks to shed light on the region's potential as a global wellness destination.
Strengthening Livelihoods and Empowerment
Authors: Sharma Shipra , Sarkar Paramita
Published: March 2024

The high-altitude Himalayan landscape of Lahaul-Pangi is marked by deforestation, land deterioration, diminished biodiversity, restricted agricultural productivity, and other environmental challenges. Although agriculture remains the primary occupation, handloom and handicrafts have emerged as potential revenue-generating resources, given the abundant availability of wool and the innate skills of the local artisans. NIFT conducted a field-based survey, involving 218 artisans across 09 panchayats, to grasp the region's needs and determine the most suitable skill development approaches. Following an analysis of the responses, NIFT developed and delivered training workshops to 09 panchayats in the Lahaul-Pangi region, ultimately empowering the artisans. The chapter presents key findings regarding the regional artisans, including information on their income and education levels, craft involvement and affiliations, assets, access to medical facilities, design, and technological proficiency, product pricing details, marketing and branding strategies, and training levels.
The Sustainable Development of Mountain Tourism at the Hills of Munnar in the State of Kerala
Authors: Udayakumar Prasanth
Published: March 2024

India has many mountain destinations to offer to the international mountain enthusiasts. However, these destinations are known to the outside world as holiday, leisure, and recreation destinations. But ample scopes are there to promote them and brand them as “mountain destinations.” The Munnar Hills located in the Idukki district of the state Kerala is one such destination which could be promoted as a mountain destination. The goal of this chapter is to examine and map the destination's current resources in order to create a detailed plan for re-branding Munnar as a mountain destination. To obtain information on the expectations of millennial visitors and adventure seekers visiting Munnar Hills, surveys are administered to them regarding their expectations regarding their experiences at mountain destinations. A new product line has been developed based on the data acquired from them, keeping up with global trends in the mountain tourism industry. Input from policy makers, government representatives, and community leaders is being sought for the re-branding of Munnar as a mountain destination.
Tourism Development and Environmental Conservation in the Himalayas
Authors: Misra Lalat Indu , Samal Ansuman , Chaini Susanta Ranjan , Bisoi Santosh , Gowda V. Dankan
Published: March 2024

In recent years, the Himalayas have seen an increase in tourism, which has benefited both the local economy and the region's indigenous population. Rapid tourist expansion has prompted calls for appropriate conservation measures to mitigate its effects. This research examines the pros and cons of protecting the Himalayan ecology while simultaneously growing tourism there. The course starts out with a quick survey of the Himalayas' many historical and cultural treasures. Concerns attributed to tourism's fast rise include increased resource consumption, environmental damage, waste management challenges, and the loss of indigenous knowledge and practices. The research highlights a number of socioeconomic issues encountered by local communities, including changes in individual lifestyle and the loss of a shared cultural identity. Opportunities for the preservation of the Himalayan ecology brought about by increased tourism are also highlighted in the chapter. Opportunities include the promotion of sustainable tourism practices and community-based initiatives, as well as nature-based tourist activities that raise awareness and generate support for conservation efforts. The research highlights the significance of collaborative problem-solving, community involvement, and successful policy frameworks.
Tourism Development in the West Jaintia Hills District, Meghalaya, in the Foothills of the Eastern Himalayas
Authors: Dkhar Manroilang
Published: March 2024

The Himalayas' most distinctive characteristics are the snow-covered mountains, the diverse flora, and wildlife and the breath-taking scenery. Shillong, the capital of Meghalaya, is a hill station. It is a part of the Eastern Himalayas foothills. From Shillong, Meghalaya, on bright autumn and winter mornings, one may view the Himalayan Range in the direction of north. The easternmost district in the State of Meghalaya, Jaintia Hills, is one of the States 12 Districts. East and West Jaintia are the two districts that make up Jaintia Hills. Jaintia hills is a popular tourist destination with a lot of natural, peaceful, and picturesque views. It is situated in a mountainous area. Compared to East Jaintia Hills, West Jaintia Hills District has a higher level of tourism activity. This chapter is designed based on secondary data and observation method which attempts to investigate the tourism development in West Jaintia Hills District, Meghalaya, in the foothills of Eastern Himalayas.
Motivations and Barriers to Using Digital Healthcare
Authors: Yingngam Bancha , Khumsikiew Jeerisuda , Netthong Rojjares
Published: March 2024

The digital healthcare industry offers personalized care, expanded access, and improved efficiency. Despite its potential, adoption rates vary across healthcare sectors due to different motivations and barriers. This chapter explores these factors, providing insights from empirical research, surveys, and case studies. Key motivators include convenience, cost-effectiveness, and the potential for personalized care. Data privacy, technological illiteracy, and regulatory limitations are major hurdles. A nuanced discussion explores how these motivators and barriers interact, particularly concerning broader sectional goals. The findings suggest that although digital healthcare holds the potential for transformative change across multiple sectors, targeted strategies are essential for overcoming the barriers that prevent its full-scale adoption. Addressing these issues is vital not only for the growth of the digital healthcare industry but also for enhancing global healthcare outcomes.
Improving Health Equity Through Digital Healthcare
Authors: Dhar Biswadeep , Sharma Priyanshi , Chakraborty Riya , Khanna Twesha , Ali Shahmir Hassan
Published: March 2024

This chapter is highlighted upon improving digital health equity by addressing the motivation and barriers to using digital health from a broader perspective. It focuses on digital health interventions, with digital health success stories on recent advancements such as digital literacy to digital therapeutics, with overarching goal to enhancing digital health equity and accessibility to healthcare. The authors also shared their own studies with the need for transformative digital health intervention from the behavioral medicine standpoint, using of social media-based health education among South Asians in the United States.
Regulatory Insights in Digital Health
Authors: Bharadwaj Medha Sateesh
Published: March 2024

Digital health is an all-encompassing term that includes a wide range of technologies ranging from general wellness products to medical devices, such as mobile health applications, wearable devices, telemedicine platforms, interoperable medical devices, and electronic health records (EHRs). Digital health has witnessed remarkable growth in recent years, leading to the development of various technologies with the potential to revolutionize healthcare. Regulatory affairs professionals play a crucial role in navigating the complexities of digital health regulations, enabling companies to comply with evolving requirements while fostering innovation. This chapter delves into key regulatory considerations for digital health products, including medical devices, software as a medical device (SaMD), cybersecurity, artificial intelligence (AI) and machine learning (ML)-based devices. It also highlights the importance of international collaboration in harmonizing regulatory standards and facilitating the global adoption of digital health technologies.
Globalization and the Digital Healthcare Industry
Authors: Kumar Piyush , Udayai Kirti , Rahi Pankaj
Published: March 2024

Globalization has changed digital healthcare by removing geographical barriers. Telemedicine and virtual platforms can democratize healthcare for marginalized people. Global healthcare data exchange allows research, data-driven decisions, and personalized medicine. Data security, patient privacy, and regulatory harmonization remain issues. Finding a balance between innovation and patient safety is crucial. Globalization is transforming digital healthcare in many ways. This book chapter endeavors to undertake a thorough critical analysis, delving into the profound implications of globalization on the digital healthcare industry. Its overarching goal is to illuminate the multifaceted spectrum of opportunities and challenges that this dynamic interplay brings forth, with far-reaching implications for healthcare providers, policymakers, and stakeholders on a global scale.
Attention and Perception in Social Cognition
Authors: Eapen Nitya Ann
Published: March 2024

Attention and perception form the underlying pivots around which social interactions function. This chapter explores the crucial roles of attention and perception in various clinical conditions by delving into how impairments in these domains affect individuals with conditions like autism spectrum disorder (ASD), social anxiety disorder (SAD), traumatic brain injury (TBI), attention-deficit hyperactivity disorder (ADHD), prosopagnosia, and schizophrenia. The author discusses various theoretical models such as the theory of mind (ToM), and attribution theory among others that inform one's understanding of the clinical applications of attention and perception within social cognition highlighting the importance of tailored rehabilitative programs. The author also gives examples of five-session, attention-focused, and perception-focused rehabilitative plans for various clinical conditions. Future research into the neural mechanisms and interactions between attention, perception, and higher-order functions offers potential for more effective treatments.
Cognition
Authors: Hayes Catherine
Published: March 2024

This chapter considers the concepts of truth alongside the art of representation and how mental and linguistic representation of knowledge is what encapsulates truth in practice. At the core of the chapter is the notion that all knowledge is ultimately dependent on understanding. Moving through a consideration of how the sciences were impacted upon by a systemic change in European intellectual infrastructure, discussion surrounds how the Renaissance contributed to the prevailing approach to science that actively shaped rationality and still resonates through todays' traditional approaches to empirical ‘knowing'.
Psychosocial Rehabilitation Through Social Cognitive Approaches
Authors: Singha Ranjit
Published: March 2024

This extensive chapter explores the foundational elements of social cognitive approaches within the context of psychosocial rehabilitation, focusing on their critical influence on the development of successful social interactions. The investigation encompasses fundamental principles, approaches to intervention, ethical implications, and prospective trajectories, such as interventions facilitated by technology and neurocognitive elements. The chapter culminates by urging mental health professionals to actively incorporate these transformative approaches, acknowledging their capacity to cultivate resilience and significant interpersonal relationships in patients undergoing psychosocial rehabilitation.
Unlocking Eudaimonic Well-Being
Authors: Jacob Leema , Reddy K. Jayasankara
Published: March 2024

Eudaimonic well-being (EWB) has long-lasting effects on individuals' mental health, enabling them to find purpose and meaning in life, depending on the individual and society. Social cognitive skills training constitutes a new aspect of the adolescent's social development, including three domains: cognitive ToM, affective ToM, and an inter-intra-personal understanding of social norms. This chapter identifies the effectiveness of A-SCST on eudaimonic well-being (EWB) during adolescence. A quasi-experimental research design was used in this study. The authors administrated the PWB-18 scale as a screening tool and the PWB-42 item scale as an outcome measure. Seventy-four participants and adolescents participated in this study. This study confirmed that A-SCST has a positive outcome on the eudaimonic well-being of adolescents post-training with a large effect size, t = -13.0, df = 35, p < .001, r = -2.17 in the experimental group. The A-SCST has successfully improved the eudaimonic well-being of adolescents.
Barriers and Impact of the Digital Economy
Authors: Baporikar Neeta
Published: March 2024

The digital economy is growing fast, especially in developing countries. Yet the meaning and metrics of the digital economy are both limited and divergent. The core of the digital economy is the ‘digital sector' which is the IT/ICT sector producing foundational digital goods and services. The true ‘digital economy' is that part of economic output derived solely or primarily from digital technologies with a business model based on digital goods or services consisting of the digital sector plus emerging digital and platform services. Following a review of measurement challenges, the chapter estimates the digital economy as defined here to make up around 7% to 10% of global GDP and 3% to 5% of global employment. Hence adopting a qualitative approach, the aim of the chapter is to review what is currently known of the digital economy, understand the scope and relevance, and deliberate on the barriers and impact of the digital economy in the new world order.
Between Digital Experiential Marketing and Semiotics
Authors: Piccolo Rossana , Boero Marianna
Published: March 2024

This chapter investigates the intersection of experiential marketing and semiotics within the contemporary consumption landscape of Asia, where a dynamic retail evolution places sustainability and innovation at the forefront, signaling a significant shift towards eco-conscious practices. This emphasis on sustainability deeply influences consumer decision-making, with environmental awareness now integral to purchasing choices. Moreover, the integration of physical and digital elements within retail settings is becoming increasingly prevalent, driven by technological advancements and heightened connectivity. Within this landscape, emotional marketing emerges as a crucial tool, influencing consumer behavior and fostering brand loyalty. Amidst these changes, Asian retail spaces serve as fertile ground for exploring semiotic marketing perspectives, where authentic connections and sensory experiences are valued. The technological evolution of the retail landscape underlines the importance of emotional engagement and sensory experiences in shaping consumer behaviour and brand relationships.
Examining the Impact of Gender Differences and Sustainable Urbanism on Online Consumer Buying Behavior Amidst the COVID-19 Pandemic
Authors: Johari Ahmad Huzaimi , Ahad Annie Dayani , Anshari Muhammad
Published: March 2024

The COVID-19 pandemic has resulted in an upsurge in online shopping in all contexts. This also has an effect on the buying behaviours of consumers, particularly those who do most of their shopping online, including via social media. The study's two main goals are to understand the gender disparities and customer location elements that affect consumers' online buying behaviours, as well as the factors that drive consumer behaviour in general. The research utilised qualitative methods via online interviews to collect the primary data for the study. The study revealed that consumers nowadays are capable of assessing their selections and making well-informed decisions. While the majority of factors impacting online shopping behaviour are influences from close social circles, mainly family members and friends, and virtual social constructs like social network friends,
The Digital Media Communication in Strengthening the Semarang City Branding Post COVID-19 Pandemic
Authors: Winarko Hilarius Bambang , Permadi Nahdi
Published: March 2024

Semarang City's Mayor spearheads the “Semarang Simpul Ekonomi Jawa” branding initiative, aligning with Indonesia's 2045 Golden Year vision to strengthen governance and economic equity. Employing contemporary digital media, the strategy aims to boost the city's image, attract visitors, and enhance socioeconomic well-being. Through content analysis of social media accounts managed by the Cultural and Tourism Office across platforms like Instagram, Facebook, Twitter, and YouTube, the study emphasizes Instagram's pivotal role. Targeting younger demographics aligns with collaborative efforts to attract residents, visitors, and influencers. Anholt's City Branding Index framework, emphasizing “People” and “Pulse,” continues to guide strategies. Findings reveal social media's positive influence, fostering trust, transparency, and participation, ultimately amplifying interest in Semarang's destinations. This research significantly contributes to understanding the impact of digital media promoting qualities such as trustworthiness, transparency, and participation.
Information Systems Management
Authors: Geada Nuno
Published: March 2024

This document describes an implementation based on information technology infrastructure library (ITIL) methodology carried out in a private organization. This case study that will be presented below is unique in the fact that it deals with processes with profound transformation of the company where it was developed, namely in terms of changes that took place in different time spaces and in different organizational contexts and in the economic and social environment. All the work developed and presented consists of implementing the ITIL methodology in the information systems department, with a focus essentially on the domain of infrastructures, particularly in the service desk area.
Navigating the Digital Frontier Telemedicine Compliance
Authors: Geada Nuno
Published: March 2024

Telemedicine has emerged as a transformative force in healthcare, offering convenience, accessibility, and the potential for improved patient outcomes. This chapter explores the critical pillars of telemedicine: compliance, data security, and patient consent. The security challenges in telemedicine, including data breaches and the imperative need for encryption, serve as foundational concerns. Robust security practices, alongside strategies to obtain informed patient consent, are essential to ensure that sensitive medical data is protected and used ethically. Digital transformation brings both advantages and vulnerabilities. While telemedicine enhances efficiency, decision-making, and patient experiences, it also demands a delicate balance between innovation and data protection. In conclusion, the potential of telemedicine is undeniable, but it must be navigated responsibly. This chapter sheds light on the multifaceted challenges and opportunities in telemedicine and emphasizes the importance of continuous research and adaptability in ensuring patient-centered care in the digital age.
Multiple Feature Fusion in Particle Filter Framework for Visual Tracking
Authors: Shanmugasundaram Singaravelan , Selvakumar V. , Balaganesh S. , Gopalsamy P. , Arun R.
Published: March 2024

Vision-based human activity recognition in smart homes has become a significant issue in terms of developing the next generation technologies Recently, deep learning models that aim to automatic extraction of low-level to high-level features of input data instead of using complicated conventional feature extraction methods have achieved significant improvements in the classification of a large amount of data especially vision-based datasets. Therefore, in this study, in order to recognize human action of a smart home video dataset. Convolutional neural networks (CNNs) architecture as a deep learning model has been proposed, and an architecture of CNNs has been proposed. Moreover, instead of using commonplace CNNs, a special CNN architecture to recognize human activity has been designed. Additionally, the performance of the proposed method has been compared with the other previous used methods on the same dataset.
Pyrolytic Plastic Oil Distillation Study of Five Mixed Plastic Waste Pyrolysis
Authors: Simanjuntak Janter Pangaduan , Tambunan Bisrul Hapis , Sihombing Junifa Layla , Zainon Mohd Zamri , Zulkifli Nurin Wahidin Bint Mohd , Riduwan Riduwan
Published: March 2024

This study aims to obtain an alternative fuel from plastic pyrolytic oil (PPO) that has similar properties to gasoline and diesel fuel. The process carried out is distillation, which is heating the PPO at a certain temperature so that light and heavy molecules will evaporate and turn into distillate plastic oil (DPO). The effect of temperature on the quality of the DPO was observed based on the color of the obtained DPO. Temperatures ranging from 120 to 350 °C were examined in this study. The cleaner DPO was produced at a temperature of about 120 °C, which indicated a light molecule of hydrocarbon similar to gasoline, while a little dark color was produced when the temperature was increased to 350 °C, which indicated heavy molecules of hydrocarbon similar to diesel. This research shows that distillation can produce alternative fuels with different grades depending on the applied operating temperature.
Monitoring Bambara Groundnut Canopy State Variables at Various Growth Stages Using Low-Cost Remote Sensing Technology and Machine Learning Techniques
Authors: Jewan Shaikh Yassir Yousouf , Billa Lawal , Sparkes Debbie , Murchie Erik , Pagay Vinay , Gautam Deepak , Cogato Alessia , Singh Ajit
Published: March 2024

The aim of this study was to assess the efficacy of an unmanned aerial vehicle-based remote sensing system for quantifying Bambara groundnut canopy state variables. Remotely sensed color infrared images and in-situ canopy state variables were collected during Malaysia's 2018/19 Bambara growing season at vegetative, flowering, podding, podfilling, maturity, and senescence stages. Five common vegetation indices (VIs) were derived from the images, yielding to single stage and cumulative VIs (∑VIs). The relationship between canopy state variables and single stage VIs/∑VIs was investigated using Pearson’s correlation. Linear parametric and non-linear non-parametric machine learning (ML) regressions were employed to estimate canopy state variables by using VIs/ ∑VIs as input features. The best correlation were observed at flowering stage. The ∑VIs from vegetative to senescence stage exhibited the most robust relationship with canopy state variables. CatBoostRegressor (CBR) excelled in training for all canopy state variables, however, it showed potential overfitting in testing. In contrast, Huber regression (HR) models provided consistent results in both training and testing. HR performance was comparable to that of the top-performing ML algorithms in estimation of groundnut crop variables.
Sheet Forming of Roll Cast Aluminum Alloy for Die Casting
Authors: Haga Toshio , Mori Shunpei , Ochi Hiizu , Fuse Hiroshi , Watari Hisaki , Nishida Shinichi
Published: March 2024

This study explored the capability of sheet forming of JIS ADC12 aluminum alloy, commonly used for die casting. Despite the poor ductility of ADC12, we attempted to improve this property by applying rapid solidification through an unequal diameter twin roll caster. A strip with a thickness of 3.7 mm was cast at a speed of 20 m/min. The as-cast strip was then cold rolled and annealed to investigate its sheet-formability by deep drawing, three-roll bending and V-bending. This research also investigated the elements of ADC12 that contribute to poor ductility, with a focus on the impact of Mg, Cu, Fe, and Zn during the deep drawing process.
Intelligent Identification of Chinese and Australian Merino Wool Fibers Based on Image Recognition
Authors: Wang Xiao Bo , Chen Zhan Xia , Wang Li Jing , Shan Xue Lei , Xie Zi Li , Shi Yun Long , Qian Xiao Ming
Published: March 2024

In order to promote the sustainable growth of the wool industry and protect consumers' legitimate rights, rapid identification of the country of origin for wool of the same type is deemed crucial. This research presents a computer graphic recognition training model that utilizes median and Wiener filtering techniques to effectively reduce noise in the raw wool fiber images. Employing a support vector machine as the classifier and integrating a polynomial kernel function, this model achieves swift and accurate identification of Chinese and Australian Merino wool fibers. Experimental results underscore that following image recognition training, the model attains an impressive 92.5% comprehensive and precise identification rate for Chinese and Australian Merino wool fibers, effectively distinguishing the origin of wool from the same category. This approach not only provides a valuable reference for identifying the origin of similar wool types but also holds the potential to standardizing the wool fibre material market and assuring the consumer’s confidence on wool products.
Improving Efficiency of Heat Pump Dryer Using R32 Refrigerant by Nanofluid
Authors: Somsila Prapanphong , Boonthum Eakpoom , Namkhet Aphainun , Teeboonma Umphisak
Published: March 2024

Drying process are important in many areas in the agriculture and food sectors, including increasing shelf life, improving transportability by reducing product weight or adding value to products. However, the main problem in the drying process is the relatively high energy consumption. Therefore, the development of energy-saving dryers is necessary. Based on the above reasons, this research aims to study the performance enhancement of heat pump dryers using R32 refrigerant by using heat recovery and nanofluid. The heat that is exhausted from the refrigerant by a heat exchanger. In this work, a Nano titanium dioxide (Ti2O3) was selected. Pork was dried under the conditions of drying temperature of 45, 50 and 55 °C and water flow rate in the heat exchanger at the front of the drying chamber of 2, 3 and 4 L/min. Criteria for evaluating heat pump dryer performance include drying rate, specific moisture extraction rate, specific energy consumption, heat pump dryer performance coefficient compared to heat pump dryers without nanofluid. The results showed that increasing the drying temperature and water flow rate in heat exchanger increased the drying rate, power and specific moisture extraction rate in the heat pump dryer using nanofluid. Whereas, the specific energy consumption was lower than the case without nanofluid. Increasing the drying temperature and the water flow rate in the heat exchanger had relatively little effect on the coefficient of performance (COP) of the heat pump dryer. Moreover, the study found that the coefficient of performance of heat pump dryer with nanofluid was in the range of 4.33 - 4.42.