Broad Field Research Articles

Mitigating chromatic aberration in wide-field pancake VR optics through the integration of diffractive optical elements

With the rise of the metaverse, the development of virtual reality headsets has gained significant attention in recent years. The optical architecture of VR head-mounted devices has undergone numerous transformations, with pancake optics becoming the mainstream configuration. Compared to traditional refractive designs, Pancake optics offer advantages such as compact size, high resolution, and wide viewing angle. Its catadioptric layout significantly reduces module thickness, while reflective surfaces provide greater optical power, achieving high resolution and a broad field of view. However, full-color VR headsets typically suffer from severe chromatic aberration at large viewing angles. This study adopts a two-element aspheric pancake design, incorporating a kinoform-type diffractive optical element. Due to the strong negative dispersion of the DOE, our hybrid diffractive-refractive pancake system with an FOV of 106° significantly improves lateral color shift. In the 450 to 650 nm wavelength, the multicolor root-mean-square spot radius is reduced from 142 to 30 µm. This result demonstrates that the DOE-enhanced design successfully improves full-color resolution across the entire FOV. We present simulation results for both designs with and without DOE, validating the effectiveness of our approach. This paper proposes an optical design method that includes first-order calculations and DOE principles, detailing generating the DOE profile. This innovative design not only achieves a technical breakthrough but also shows significant performance improvements in quantitative data, providing a crucial reference for the future optical design of VR headsets and laying a solid foundation for the further development of VR technology.

The role of educational tourism in Thailand: Opportunities and challenges

The discussion comprehensively debates and explores the deeper meaning that tourism for education purposes would have on the wondrous country of Thailand. It highlights many facets of opportunities and possible pitfalls lying within the broad field of educational travel abroad. With its bewildering tongue, rich culture, and skill development programs in almost every field, Thailand is emerging as one of the grand and prestigious destinations for education tourism. Besides, the economic benefits of educational tourism are surely huge, adding to national income and fostering very significant cultural exchange and understanding between nations. The following categorization is going to place educational tourism in three broad types of categories, namely academic exchange programs, culturally immersive experiences, and language learning initiatives. Each of these categories has a different and very valuable purpose, but all of them have some general problems, including infrastructural constraints, quality assurance, and, finally, the imperatives of sustainability. These challenges must be faced head-on and positive solutions found to move towards a better future, so that full potential underlying educational tourism is used. Notwithstanding all the obstacles, the wide world of educational tourism does hold enormous growth opportunities both for Thailand's educational sector and its growing economy. This would involve joint efforts among the stakeholders, for it is only in unison that the enhancing of the quality of the educational programs would be attained, leading to the sustainable development regarding the everlasting changes within the global educational arena. Synchronizing efforts and collectively addressing new and emerging educational demands, the educational sector of Thailand is likely to scale new heights to lead innovation in international educational travel. In a nutshell, education tourism is a significantly important element in Thailand. This text clearly focused on its manifold opportunities and challenges within the framework of international travel for education. It is now high time that Thailand be identified as the prime target for educational tourism and that the Department of Tourism pay full concern to changing circumstances and weigh an initiative of developing enormous opportunities within this industry. It will mean that Thailand is well on its way to being recognized as a world leader in the offering of excellent educational experiences, intercultural exchange, and growth of the minds of future generations.

Gameful Experience and Brand Loyalty: Exploring Customer Brand Engagement in Language Learning Apps

This study examines the impact of gameful experiences on brand loyalty in language learning applications mediated by customer brand engagement. With the increasing incorporation of gamification in educational tools, understanding how specific game mechanics drive user engagement and brand loyalty in language learning apps is crucial. While existing gamification research generally focuses on broader fields, this study uniquely investigates how specific gameful experiences—such as enjoyment, creative thinking, and domination—affect brand loyalty in the context of language learning applications. Data were collected from 250 active users in Indonesia using an online survey with a Likert scale of 1-5, employing purposive sampling. Structural Equation Modeling (SEM) with AMOS 26 assessed validity, reliability, and relationships among variables. The results indicate that gameful experiences significantly enhance customer brand engagement, which, in turn, positively influences brand loyalty. This study contributes new insights into how gamification affects brand loyalty, specifically in the language learning app domain, providing practical recommendations for developers to incorporate effective game mechanics to enhance customer brand engagement and foster long-term brand loyalty.

Preface: 6th International Conference on Energy Material, Chemical Engineering and Mining Engineering (EMCEME 2024)

The 2024 6th International Conference on Energy Material, Chemical Engineering and Mining Engineering (EMCEME 2024), as an international forum aiming at presenting and exchanging technological advances and research results in the broad fields of energy material, environmentally friendly materials, chemical engineering, biological chemistry, resource exploration, and mining engineering, was held during December 14-15, 2024 in Zurich, Switzerland. EMCEME 2024 brought together leading researchers, engineers, and scientists in the domain of interest from around the world. During the conference, the participants shared their research results and discussed the development and research applications. Accepted papers after proper registration and presentation will be published into conference proceedings. Finally, we would like to express our gratitude to the reviewers of these manuscripts, who provided constructive criticism, stimulated comments, and suggestions to the authors. We are extremely grateful as organizers, technical program committee and editors, and extend our most sincere thanks to all the authors for their excellent contribution and work. EMCEME Organizing Committees Zurich, Switzerland

Acceptance of advance care planning and influencing factors from the perspective of the life cycle: a cross-sectional study

BackgroundAdvance care planning is an important part of palliative care. Public acceptance is a prerequisite for the widespread development and implementation of advance care planning. However, little is known about the level of public’s acceptance and influencing factors of advance care planning across different life cycles.MethodsA cross-sectional study in mainland China was conducted from June 20 to August 31, 2022. We used multi-stage sampling strategy to recruit participators. A stepwise linear regression analysis was used to examine the influencing factors in different life cycles (nonage, mature age, middle age and old age).ResultsThe final sample size was 18,002. The average acceptance score of advance care planning of the public throughout the entire life cycle was 64.03. The average score in nonage was 67.13, which is the highest. The average score in mature age was 63.87, in middle age was 63.51, and in old age was 63.54. Multiple linear stepwise regression results indicated that death education support level, well-being index, neighbor relations, health literacy, family social status, and siblings were influencing factors in nonage. Medical insurance, injury events, multiple properties, death education support level, health literacy, family social status, neighbor relation, social support, family health, media contact, and well-being index were influencing factors in mature age. In middle age, region, living alone, depression, debt, houses, death education support level, health literacy, social support, and family social status were influencing factors. In old age, injury event, death education support level, neighbor relation, well-being index, siblings and children were influencing factors.ConclusionsThis study is the first to compare the Chinese people with different life cycles. It found that the public’s acceptance and influencing factors of advance care planning varied across different life cycles. Governments and health care personnel should emphasize autonomy and initiate advance care planning based on different life cycles and individual approaches, then introduce appropriate public health policies into newer and broader fields.

Volcanic Process Ground Deformation Using DInSAR Observations: The Case Study of the Sabancaya Volcano

Abstract. Remote sensing is one of the most useful tools when it comes to studying earth phenomena along large terrain extensions. Within this broad field, Differential Interferometric Synthetic Aperture Radar (DInSAR) has been evolving, and at this point is able to provide terrain deformation in millimetre-level precision. This analysis was conducted over the Sabancaya Volcano, in Perú, which is part of the Ampato-Sabancaya Volcanic Complex. This volcano has been active and continuously erupting since 2016, with various fault systems surrounding the volcanic complex. The main objective of this work was to map deformation caused by the volcanic system, processing Sentinel-1 products from 2016 and an interval that started in 2014 to 2017 to be able to study the effects of temporal decorrelation on interferometric products, being Sentinel-1 the first of the Copernicus Program satellite constellations conducted by the European Space Agency. The analysis showed deformation in the interval in which the eruption started and a deformation centre in the northern region of the volcanic complex, although the last one was found when studying a longer temporal baseline. Overall, the experiment shows that DInSAR is an effective tool to study volcanic systems.

Exploring the Dynamics of Canine-Assisted Interactions: A Wearable Approach to Understanding Interspecies Well-Being.

Canine-assisted interactions (CAIs) have been explored to offer therapeutic benefits to human participants in various contexts, from addressing cancer-related fatigue to treating post-traumatic stress disorder. Despite their widespread adoption, there are still unresolved questions regarding the outcomes for both humans and animals involved in these interactions. Previous attempts to address these questions have suffered from core methodological weaknesses, especially due to absence of tools for an efficient objective evaluation and lack of focus on the canine perspective. In this article, we present a first-of-its-kind system and study to collect simultaneous and continuous physiological data from both of the CAI interactants. Motivated by our extensive field reviews and stakeholder feedback, this comprehensive wearable system is composed of custom-designed and commercially available sensor devices. We performed a repeated-measures pilot study, to combine data collected via this system with a novel dyadic behavioral coding method and short- and long-term surveys. We evaluated these multimodal data streams independently, and we further correlated the psychological, physiological, and behavioral metrics to better elucidate the outcomes and dynamics of CAIs. Confirming previous field results, human electrodermal activity is the measure most strongly distinguished between the dyads' non-interaction and interaction periods. Valence, arousal, and the positive affect of the human participant significantly increased during interaction with the canine participant. Also, we observed in our pilot study that (a) the canine heart rate was more dynamic than the human's during interactions, (b) the surveys proved to be the best indicator of the subjects' affective state, and (c) the behavior coding approaches best tracked the bond quality between the interacting dyads. Notably, we found that most of the interaction sessions were characterized by extended neutral periods with some positive and negative peaks, where the bonded pairs might display decreased behavioral synchrony. We also present three new representations of the internal and overall dynamics of CAIs for adoption by the broader field. Lastly, this paper discusses ongoing options for further dyadic analysis, interspecies emotion prediction, integration of contextually relevant environmental data, and standardization of human-animal interaction equipment and analytical approaches. Altogether, this work takes a significant step forward on a promising path to our better understanding of how CAIs improve well-being and how interspecies psychophysiological states can be appropriately measured.

Welcoming the Broad Field of Vision That Is the Secular Experience

Welcoming the Broad Field of Vision That Is the Secular Experience

Molecular Mechanisms of Solvation Force for Aqueous Systems.

Solvation force, stemming from the interfacial liquid structure, dominates the short-range interfacial interaction within a few nanometers across broad fields such as battery, lubrication, and colloid. However, achieving a quantitative understanding of solvation force for an aqueous system has remained elusive for decades, with the widely used contact value theory underestimating solvation force due to inherent assumptions. In this work, inspired by the flow field of liquid when two confining surfaces approach each other, we proposed a parameter-free expression for the solvation force acting on atomically smooth surfaces, quantitatively related to the energy barrier when liquid molecules are squeezed out from confinement. The effects of temperature and wetting properties of the surface on solvation force curves are found to be different. Solvation force measured by three-dimensional atomic force microscopy (3D-AFM) validates theoretical prediction on three types of surfaces ranging from hydrophilic to hydrophobic and reveals that the energy barrier is more intrinsic than density.

Realization of Ideal Ba Promoter State by Simultaneous Incorporation with Co into Carbon‐protective Framework for Ammonia Synthesis Catalyst

AbstractDeveloping non‐noble metal catalysts with excellent NH3 synthesis activity under mild conditions is a long‐term goal. The best catalysts reported to date often require laborious fabrication methods and controlled environments to fabricate the catalysts or high temperatures and long times to activate the catalysts. This work introduces a facile one‐pot method to fabricate carbon (C)‐based, barium (Ba)‐promoted cobalt (Co) catalysts via the citric acid sol–gel method with metal nitrates as precursors and water as the solvent. This approach ensures the homogeneous incorporation of metal ions into the carbon framework. The resulting (Ba/Co)0.3/C catalyst demonstrates an outstanding NH3 synthesis activity of 34 mmol gcat−1 h−1 (350 °C, 1.0 MPa) with excellent stability. In‐depth characterizations reveal that Ba exists as barium oxide (BaO), uniformly distributed on the carbon framework and around the Co nanoparticles. It is uncovered that retarding barium carbonate (BaCO3) formation in the fresh catalyst significantly reduces the reduction temperature and time (485 °C/4 h), which is a fundamental advantage of this method. Density functional theory and molecular dynamics simulations indeed support the experimental observations. It is anticipated that this simple and economical strategy will resolve the issues in a broad field of heterogeneous catalyst research.

Analysis of Contact Wheel and Tool Interaction in Belt Grinding

The belt grinding process is gaining an increasing importance in the industrial sector. Due to its high flexibility regarding the range of workpiece materials and its adaptability to various, even geometrically complex workpiece shapes and designs, belt grinding has a broad field of applications. Typical application cases for this process include sealing surfaces on housing and engine parts, the production of camshafts and crankshafts as well as cylinders with high concentricity accuracy. Despite the extensive application of belt grinding in the manufacturing industry, the respective interactions between grinding belt and contact wheel of the process have not been holistically investigated. Therefore, this article focuses on the deformation of the contact wheel as well as the deformation during the interaction between the contact wheel and the grinding belt. This includes the flattening of the tool under grinding normal force Fn and deformation under centrifugal forces. The empirical data is intended to provide insights into the relationship between tool deformation and elastic effective depth of cut ae.

Utilization of Electric Fields to Modulate Molecular Activities on the Nanoscale: From Physical Properties to Chemical Reactions.

As a primary energy source, electricity drives broad fields from everyday electronic circuits to industrial chemical catalysis. From a chemistry viewpoint, studying electric field effects on chemical reactivity is highly important for revealing the intrinsic mechanisms of molecular behaviors and mastering chemical reactions. Recently, manipulating the molecular activity using electric fields has emerged as a new research field. In addition, because integration of molecules into electronic devices has the natural complementary metal-oxide-semiconductor compatibility, electric field-driven molecular devices meet the requirements for both electronic device miniaturization and precise regulation of chemical reactions. This Review provides a timely and comprehensive overview of recent state-of-the-art advances, including theoretical models and prototype devices for electric field-based manipulation of molecular activities. First, we summarize the main approaches to providing electric fields for molecules. Then, we introduce several methods to measure their strengths in different systems quantitatively. Subsequently, we provide detailed discussions of electric field-regulated photophysics, electron transport, molecular movements, and chemical reactions. This review intends to provide a technical manual for precise molecular control in devices via electric fields. This could lead to development of new optoelectronic functions, more efficient logic processing units, more precise bond-selective control, new catalytic paradigms, and new chemical reactions.

Representational drift in barrel cortex is receptive field dependent.

Cortical populations often exhibit changes in activity even when behavior is stable. How behavioral stability is maintained in the face of such "representational drift" remains unclear. One possibility is that some neurons are more stable than others. We examined whisker touch responses in layers 2-4 of the primary vibrissal somatosensory cortex (vS1) over several weeks in mice stably performing an object detection task with two whiskers. Although the number of touch neurons remained constant, individual neurons changed with time. Touch-responsive neurons with broad receptive fields were more stable than narrowly tuned neurons. Transitions between functional types were non-random: before becoming broadly tuned, unresponsive neurons first passed through a period of narrower tuning. Broadly tuned neurons in layers 2 and 3 with higher pairwise correlations to other touch neurons were more stable than neurons with lower correlations. Thus, a small population of broadly tuned and synchronously active touch neurons exhibits elevated stability and may be particularly important for behavior.

Integrating Spatial Computing with Clinical Pathology for Enhanced Diagnosis and Treatment Informatics in Healthcare

This paper investigates spatial computing, which is a pathological transformational modern technology that integrates the physical and digital realms and has the potential to revolutionize pathology healthcare. Pathology as a medical specialist plays a crucial role in patient care by providing essential information for diagnosis, treatment planning, and disease monitoring. It studies and diagnoses diseases by examining tissues, organs, bodily fluids, and cells. Pathology is a broad field with three main branches: Anatomic pathology, Clinical pathology, and Molecular pathology. This study investigates the possibilities of spatial computing in radiography and clinical pathology with emphasis on diagnosis accuracy, medical education, workflow efficiency, and the outcomes in the patients. Augmented Reality (AR) medical devices guide pathologists in real-time during diagnostics procedures. The digital reproduction of tissue samples to allow pathologists to examine specimens in three dimensions is a significant utilization of spatial computing in virtual microscopy. This process allows remote collaboration between pathologists and laboratories, provides health informatics as seen in electronic health records (EHRs), improves diagnosis, and presents a platform with learning experiences in the medical field. Patients can interact with three-dimensional simulations of their anatomy, which helps them make more educated treatment decisions provided via the pathology findings and treatment alternatives in an immersive format. As this technology advances, its potential to transform pathology practice and improve patient care remains high. This review describes technological perspectives and discusses the statistical methods, clinical applications, potential obstacles, and directions of spatial computing in clinical pathology.

A REVIEW OF MACHINE LEARNING TECHNIQUES APPLICATIONS IN ENVIRONMENTAL SCIENCE

Advances in Machine Learning (ML) and Data Science (DS) hold immense potential to transform various aspects of environmental science (ES). DS, a broad field focused on extracting insights from data using techniques like statistical analysis plays a crucial role in this process. Machine learning, on the other hand, specializes in creating algorithms that enable computers to learn from data and make predictions. Together, these technologies can deepen our understanding of complex environmental systems, refine predictive models for climate change, support conservation efforts, and optimize resource management practices. Such scientific discovery will enhance ES to make autonomous, real-time decisions by deriving valuable insights from extensive data. By analysing large datasets, machine learning algorithms can reveal hidden patterns and insights, empowering scientists to make data-driven decisions and tackle environmental challenges more effectively. This article offers a review of the fundamental concepts of Machine Learning, Deep Learning, and Data Analytics for two groups: individuals familiar with ML who seek to expand their knowledge, and domain scientists passionate about integrating these transformative tools into their research in the environmental science profession.

Artificial Intelligence in Arabic Linguistic Landscape: Opportunities, Challenges, and Future Directions

The widespread use of artificial intelligence applications in current era has created unique opportunities and challenges for the broad linguistic field of Arabic language and the possibility of employing these applications in learning, generating, and proofreading Arabic language. The primary research question addresses the effectiveness and challenges of AI applications in Arabic language contexts. This study tests whether AI tools enhance Arabic language more than traditional methods, despite challenges. A comprehensive literature review of studies was conducted using a focused strategy on Google scholar, employing specific keywords such as “AI” and “Arabic language” and selecting studies related to AI’s role in Arabic language education, translation and processing. This research sheds light on the relationship between AI applications and Arabic language, including a review of the research published in this field to identify the reality of using these applications and the extent of their effectiveness in serving Arabic language. A synthesis of the collected data identified the key themes, including current applications of AI in Arabic language learning, the development if natural language processing tools and the challenges of resource availability. The review highlights the considerable potential of AI in enhancing Arabic language and emphasizing their applications in understating and processing the language. Given the rapid and continuous development of these technologies, this study highlights emerging Arabic achievements in bridging the gap between Arabic language and modern technology and explores the future prospects of AI in Arabic language development. Moreover, this study contributes to the ongoing research on the intersection of Arabic language and AI addressing future research directions and promoting more effective AI-based education al tools for Arabic language.

Examining AI Use in Educational Contexts: A Scoping Meta-Review and Bibliometric Analysis

AbstractWith growing research attention in artificial intelligence in education (AIED), there is a profusion of systematic reviews that have investigated AI integration in a wide variety of educational contexts, including PreK-12 schools and higher education. Even though existing systematic reviews have explored effects of AI on education, few studies have synthesized the results of those reviews. To fill this gap, we conducted a scoping meta-review and bibliometric analysis to map the broad field of AIED and identify research gaps based on our analysis. Following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, we searched Scopus and Web of Science and collected 126 review articles from 2014 to Mid-August of 2023 that satisfied our inclusion criteria. Specifically, we used four criteria for the screening process: (1) the article’s full text was available in English; (2) the article was published in peer-reviewed journals; (3) the article was a systematic review; and (4) the article was focused on AI use in one or multiple educational context(s). Our findings revealed the key characteristics of the included reviews, such as keyword co-occurrence network, co-authorship network, geographic distribution of authorship, educational levels, and subject areas. Three major themes related to AIED were generated, encompassing AI’s impact on teaching, learning, and administration. We also identified commonalities and nuanced differences between PreK-12 education and higher education along with research areas that have been underexplored. Our study not only expanded understanding of studies on AIED, but also provided suggestions on how to strengthen future research.

Effects of micron-sized Si particles on the static and dynamic mechanical properties and fracture behavior of Al-xSi alloy sheets

In this paper, a comprehensive analysis was conducted on the effects of micron-sized Si particles on the microstructure, static and dynamic mechanical properties, and fracture behavior of wrought Al-xSi alloy sheets. The investigation employed techniques such as optical microscope, scanning electron microscope, laser scanning confocal microscope, transmission electron microscope, tensile testing and fatigue testing. The results show that when the Si content is below 12 wt%, the size of the Si particles in the alloy sheets does not exceed 3 μm, and their quantity gradually increases with higher Si content. As the Si content increases, the grain size of the alloy sheets is refined from 63 μm to 8 μm. The alloy strength initially increases and then slightly decreases with further Si addition. while elongation exhibits a general downward trend. The tensile fracture modes of Al-(1–12 wt%) Si alloy sheets are all ductile fractures. The fatigue life of Al-xSi alloy sheets first extends and then shortens as the Si content increases. With the increase of Si content, the yield strength of the alloy sheets gradually increases from 47.6 MPa to 85.7 MPa. When the Si content is 12 wt%, the tensile strength reaches the maximum value of 185.4 MPa. With the increase of Si content, the elongation of the alloy sheet first increases slightly, reaching 35.0 %, when the Si content increases to 15 wt%, the elongation gradually decreases to 17.5 %. As the Si content increases, the fatigue life of the alloy sheets gradually extends. When the Si content reaches 12 wt%, the alloy sheet achieves its maximum fatigue life, reaching 9.97 × 105–1.97 × 10⁶ cycles, approximately 11–14 times longer than that of the Al-1 wt% Si alloy sheet. However, with a further increase in Si content to 15 wt%, the fatigue life significantly decreases to 4.08 × 10⁵–4.70 × 10⁵ cycles, shortening by approximately 59–76 %. The fatigue crack source of Al-xSi alloy sheets gradually changes from the persistent slip bands on the surface of the sheet to the large-sized Si particles on the surface of the sheet. The functional relationship between the fatigue life of Al-xSi alloy sheets as the Si content changes is established, and the fatigue life influencing factor ISi is introduced to quantitatively describe the influence of the number of micron-sized eutectic Si particles on the fatigue life or fatigue properties of the alloy sheets. This study provides important scientific insights for optimizing alloy property and meeting diverse industrial demands, thereby promoting the application and development of wrought Al-Si alloy in broader fields.

Introducing fairness in network visualization

Motivated by the need for decision-making systems that avoid bias and discrimination, the concept of fairness recently gained traction in the broad field of artificial intelligence, stimulating new research also within the information visualization community. In this paper, we introduce a notion of fairness in network visualization, specifically for orthogonal and for straight-line drawings of graphs, two foundational paradigms in the field. We investigate the following research questions: (i) What is the price, in terms of global readability, of incorporating fairness constraints in graph drawings? (ii) How unfair is a graph drawing that does not optimize fairness as a primary objective? We present both theoretical and empirical results. In particular, we design and implement two optimization algorithms for multi-objective functions, one based on an ILP model for orthogonal drawings, and one based on gradient descent for straight-line drawings. In a nutshell, we experimentally show that it is possible to significantly increase the fairness of a drawing by paying a relatively small amount in terms of reduced global readability. Also, we present a use case in which we qualitatively evaluate our approach on a practical scenario.

The Funnel Transformative Model of Science Education

This theoretical paper proposes a model to address the multifaceted challenges of science education by integrating two evidence-based approaches: the Learner-Generated Digital Media (LGDM) projects framework and the Cognitive Acceleration through Science Education (CASE) framework. The Model is analogous to a funnel, with its wide top representing the broad field of science education and its narrow bottom symbolising transformative learning. It leverages LGDM’s self-regulation benefits and CASE’s structured five-stage approach – Concrete Preparation, Cognitive Conflict, Social Construction, Metacognition, and Bridging. The model categorises the complexity of science learning into six critical pillars: lack of conceptual understanding, cognitive challenges, language barriers, lack of hands-on learning, lack of robust assessments, and social issues. Applying the Funnel Model aims to develop cognitive skills, enhance learning strategies, and foster practical skills. This paper presents the Funnel Model and discusses a methodological approach to validation using Design-Based Research (DBR). The research plans to address three key questions to refine and enhance the Funnel Model in improving science education outcomes.