Development Of Technology Research Articles

Assessing the Different Nanoparticle-Reinforced Bonding Agents on the Shear Bond Strength of Orthodontic Brackets

ABSTRACT Background: The strength of the binding between brackets and tooth surfaces has a major impact on how well orthodontic therapy works. The shear bond strength of orthodontic brackets may be strengthened by the invention of bonding agents supplemented with nanoparticles, thanks to recent developments in nanoparticle technology. Materials and Methods: In order to perform a randomized controlled experiment, 90 human premolars were excised for orthodontic purposes. Three groups of 30 teeth were randomly assigned to each group: Group A used a bonding agent augmented with nanoparticles of titanium dioxide (TiO2), Group B used nanoparticles of zirconium dioxide (ZrO2), and Group C used a standard bonding agent as a reference. The appropriate bonding chemicals were used to attach the brackets to the teeth, and a universal testing equipment was used to measure the shear bond strength. Stereomicroscopic analysis was used to evaluate the failure mechanisms. To do statistical analysis, Tukey’s post hoc test and analysis of variance were used. Results: There were significant differences (P < 0.05) in the mean shear bond strength values across the groups. The average shear bond strength for Group A (TiO2) was 18.5 ± 2.3 MPa, that for Group B (ZrO2) was 17.2 ± 2.6 MPa, and that for Group C (control) was 14.8 ± 2.4 MPa. In comparison to Groups B and C, Group A exhibited a statistically greater bond strength, although Group B also showed an improvement over the control. According to the failure mode analysis, the control group had mostly adhesive failures, whereas the nanoparticle groups saw mixed failures. Conclusion: When TiO2 and ZrO2 nanoparticles are added to bonding agents, the shear bond strength of orthodontic brackets is greatly increased in comparison to traditional bonding agents. TiO2-reinforced materials performed better, pointing to possible benefits for orthodontic applications. It is advised that further study be done to examine the long-term impacts and therapeutic implications of these results.

Pressure induced semiconductor-like to metal transition and linear magnetoresistance in Cr2S2.88 single crystal

The transition metal chalcogenide Cr2S3-xhas unique properties, such as a lower antiferromagnetic transition temperature, semiconducting behavior, and thermoelectric properties. We focus on the effects of high pressure on the properties of electrical transport and structure in the single crystal Cr2S2.88. It is observed that the resistance drops abruptly by approximately two orders of magnitude and the temperature derivative of the resistance changes from negative to positive after 15.7 GPa. The Cr2S2.88crystal has undergone transitions from a semiconductor-like phase to a metal I phase and then to another metal II phase. Simultaneously, a structural phase transition after 16.1 GPa is confirmed by synchrotron angle dispersive x-ray diffraction. After the structural phase transition, the negative magnetoresistance becomes positive with increasing pressure and shows a linear relationship in the metal II phase. Electron-type carriers dominate in the semiconductor-like phase, but hole-type carriers dominate after the structural phase transition. Our work provides an example of the effective modulation of semiconductor-like properties by pressure, which is meaningful for the innovation and development of semiconductor technology.

Joint Classification of Hyperspectral and LiDAR Data via Multiprobability Decision Fusion Method

With the development of sensor technology, the sources of remotely sensed image data for the same region are becoming increasingly diverse. Unlike single-source remote sensing image data, multisource remote sensing image data can provide complementary information for the same feature, promoting its recognition. The effective utilization of remote sensing image data from various sources can enhance the extraction of image features and improve the accuracy of feature recognition. Hyperspectral remote sensing (HSI) data and light detection and ranging (LiDAR) data can provide complementary information from different perspectives and are frequently combined in feature identification tasks. However, the process of joint use suffers from data redundancy, low classification accuracy and high time complexity. To address the aforementioned issues and improve feature recognition in classification tasks, this paper introduces a multiprobability decision fusion (PRDRMF) method for the combined classification of HSI and LiDAR data. First, the original HSI data and LiDAR data are downscaled via the principal component–relative total variation (PRTV) method to remove redundant information. In the multifeature extraction module, the local texture features and spatial features of the image are extracted to consider the local texture and spatial structure of the image data. This is achieved by utilizing the local binary pattern (LBP) and extended multiattribute profile (EMAP) for the two types of data after dimensionality reduction. The four extracted features are subsequently input into the corresponding kernel–extreme learning machine (KELM), which has a simple structure and good classification performance, to obtain four classification probability matrices (CPMs). Finally, the four CPMs are fused via a multiprobability decision fusion method to obtain the optimal classification results. Comparison experiments on four classical HSI and LiDAR datasets demonstrate that the method proposed in this paper achieves high classification performance while reducing the overall time complexity of the method.

ANALISIS SENTIMEN PENGGUNA PADA APLIKASI BANK DIGITAL KROM DENGAN ALGORITMA SUPPORT VECTOR MACHINE

The rapid development of financial technology has driven the widespread adoption of digital banking applications, including the KROM app, among the public. This study aims to analyze user sentiment toward the KROM Digital Bank application using the Support Vector Machine (SVM) algorithm. User review data was collected from Google Play, then processed through data preprocessing steps such as text cleaning, tokenization, and removing irrelevant words. The SVM algorithm is used to classify user sentiment into positive and negative categories. The results indicate that SVM performs well in classifying user sentiment, with an accuracy of 84,38%. This analysis is expected to provide insights for app developers to improve service quality based on user perceptions and experiences.

Exploring the Optical Properties of Carotenoid-Based Nanoparticles: The Role of Terminal Groups.

Carotenoids are increasingly used as naturally occurring food colorants. For application as beverage colorants, fat-soluble carotenoids are formulated into dispersion systems via nanoparticle (NP) formation. In recent years, the antioxidant properties of carotenoids have gained immense recognition for their preventive health benefits, thereby highlighting further interest in their development as functional food ingredients. Although functional carotenoids in dispersion-based formulations are desirable, knowledge regarding the structural and optical properties of NPs of carotenoids other than those of β-carotene, and methods to efficiently produce and compare NPs of various carotenoids, remain scarce. In this study, NPs of β-carotene, lycopene, astaxanthin, and lutein were prepared using a simple reprecipitation method, with a focus on understanding the variations in the molecular self-assembly influenced by the quality of solvent used during reprecipitation. This study presents the novel finding that the terminal groups of carotenoids significantly affect the intermolecular interactions, thereby altering the structural and optical properties of the resulting NPs. Our findings are expected to contribute to the development of new technologies for controlling the color of carotenoids based on the crystal structure of the NPs.

Structure Regulation and Energy Storage Mechanisms of Bismuth‐Based Anodes for Sodium Ion Batteries

The increasing demand for eco‐friendly energy storage solutions has driven significant interest in sodium‐ion batteries (SIBs) as an alternative to lithium‐ion batteries, primarily due to sodium's abundant availability. Among various anode materials, bismuth (Bi) has emerged as a promising candidate due to its high theoretical volumetric capacity and excellent electrical conductivity. This review presents a comprehensive analysis of structural characteristics and failure mechanisms inherent to Bi‐based anode materials for SIBs, providing valuable insights into the significance of material modification methods. Structure regulation strategies for Bi‐based SIB anodes are reviewed, focusing on the challenges associated with volumetric expansion and strategies to enhance their electrochemical performance. Typically, nanostructure optimization, surface engineering, morphology modification, and composition regulation are highlighted. Furthermore, this review will discuss the underlying mechanisms that improve sodium storage capabilities and the role of bismuth in advancing the efficiency and stability of SIBs. Lastly, the prospects and imminent challenges associated with bismuth‐based materials will be presented, providing insights for future research and development in energy storage technologies.

Research on the Design of WeChat Applet of Persimmon Dye Culture from The Perspective of Scenario Construction

With the rapid development of information technology, the dissemination and preservation of traditional culture face new opportunities and challenges. This study aims to explore design strategies for a WeChat Mini Program focused on persimmon dyeing culture, to promote the inheritance and development of this intangible cultural heritage. Through user needs analysis, a user experience design framework based on contextual theory was constructed, and a Mini Program was developed that integrates cultural display, education, community interaction, and immersive experiences. The results highlight the importance of contextual construction in enhancing cultural experiences and user engagement, providing a reference for the digital transformation of other traditional cultures. The study explores the characteristics and direction of contextual construction in the design of the persimmon dyeing Mini Program, introduces key points in the program's development, and analyzes its current state and future development trends, offering support for the growth of persimmon dyeing traditional culture.

A SYSTEM OF INDICATORS FOR SELECTING INNOVATION TRIGGERS TO DRIVE SUSTAINABLE DEVELOPMENT

The foundation of sustainable development lies in innovation, technology, and entrepreneurship, which have significant positive impacts on socio-economic aspects of life. This study examines the indicators necessary for selecting innovation triggers that can lead country’s sustainable development. Innovation trigger system is mechanism that initiates and drives the development of new technologies and processes, essential for sustainable development by facilitating the transition to more sustainable practices. However, not all innovation triggers succeed or offer long-term benefits for sustainable development. This study aims to identify the indicators necessary to select effective innovation trigger for sustainable country development. It has been described hype cycle phases of main technologies in the 21-st century, and defines that there is no one duration of hype cycle phases for AI, IoT, AR and VR, blockchain technologies. It has been proposed the innovation trigger system indicators to select beneficial innovation trigger that divided into two groups, set of lagging indicators and set of leading indicators. Lagging indicators assess the effectiveness of past strategies and investments, while leading indicators provide insights into future performance and potential outcomes. By utilizing both types of indicators, a more balanced and comprehensive analysis can be achieved when selecting the most beneficial innovation trigger for a country’s development. The final choice of innovation trigger in each country will ultimately depend on its prioritized development goals. Additionally, it has been applied and modified the Bass Model to forecast the diffusion of AI among industrial enterprises in Ukraine. The basic Bass model has been extended to include a developer influence coefficient, which accounts for the role of AI developers in technology diffusion. Understanding the processes of diffusion and the effectiveness of innovation triggers, as well as the phases of the hype cycle, provides guidance for policymakers, business structures, and enterprises in technology implementation and the use of innovation for development, which determines the sustainability of national economic progress.

Epithermal neutron activation dosimetry–(n, γ) reactions under boron-based filters

Neutron activation dosimetry is the primary method for the determination of the neutron flux or fluence, and in general, it is sensitive to the thermal and resonance energy ranges (radiative capture reactions–(n,γ)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(n,\\gamma )$$\\end{document} reactions) and the fast energy range (threshold reactions). However, there are very few nuclear reactions which are sensitive specifically to neutrons in the intermediate–epithermal–energy region. This energy region, along with the fast energy range, will become particularly important in the development and deployment of new reactor technologies (Generation IV reactors and Small Modular Reactors–SMRs), which are currently being championed as technologies enabling a meaningful contribution to decarbonization and the fight against climate change, as well as nuclear fusion. The epithermal neutron energy range is also of particular importance for Boron Neutron Capture Therapy (BNCT), a neutron-based cancer therapy, particularly effective for the treatment of head and neck cancer, malignant meningioma, melanoma and hepatocellular carcinoma. This work investigates and demonstrates the applicability of a particular set of (n,γ)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(n,\\gamma )$$\\end{document} reactions in conjunction with boron-based neutron filters to achieve sensitivity in the epithermal energy region, and discusses avenues for future research in this context.

Design and research of intelligent watt hour meter fault early warning system based on data mining technology

With the rapid development of information technology and the continuous improvement of communication technology, electric energy meters are innovating and developing towards networking, informatization and intelligence. This research constructs a model design of electric energy failure early warning system based on big data mining technology under the background of big data. It analyzes and studies the intelligent electric energy meter failure early warning system. Through the analysis and comparison of the factors affected, comprehensive performance and application prospects of the intelligent electric energy meter failure early warning system under different data mining technologies, the research results show that the application of big data mining technology makes the heavy work of data collection and data analysis integrate big data mining technology, it can be popularized more widely and applied to more scenarios, thus reducing the manual workload, it makes the work efficiency more significantly improved, and can promote the reform of China’s smart grid more quickly.

Low-connectivity Educational Technology: A Case Study of Supporting Learning during Covid-19 via SMS with ‘Keep Kenya Learning’

The use of Short Messaging Service (SMS) for education has grown in recent years, drawing particular attention to supporting school-level learners, due to the Covid-19 pandemic. This renewed interest has prompted questions about how this form of educational technology could be used in the longer term. However, despite being used in many Covid-19 responses, there are few documented examples of innovative applications in this field during the pandemic, which represents a gap in the literature. As a medium for education, SMS offers potential benefits such as being cost-effective and having positive impacts on learning. In this paper, we present a case study of an educational programme rapidly implemented during the pandemic as part of the ‘Keep Kenya Learning’ program, to support learners remotely in terms of literacy, numeracy, and social and emotional learning topics. Through the case study, we describe the innovative process used to rapidly develop content for SMS, and draw upon usage statistics, quiz scores and user feedback to gain insights into its implementation with learners and caregivers in Kenya. The case study demonstrated that educational television content can be effectively adapted to mobile delivery. Furthermore, we present practical reflections on the development and implementation of SMS educational technology which will help inform future initiatives. These include considering timing in relation to school terms when planning a supporting intervention, and designing content in a modular way to allow flexibility for learners in navigating through courses.

The Impact of Pore Geometry on Frictional Properties of hBN and MoS2 Nanomaterials.

Two-dimensional (2D) nanomaterials hold significant promise for reducing energy consumption in water desalination. This study investigates the influence of pore size and shape on the slip behavior of saline water at the interface of two promising 2D nanomaterials: hexagonal boron nitride (hBN) and molybdenum disulfide (MoS2). Slip length, a key parameter governing fluid flow at the nanoscale, is highly dependent on interfacial properties. Here, we explore how the pore characteristics in these 2D nanomaterials can impact slip length, aiming to gain a fundamental understanding of the role of pore size and shape in optimizing desalination efficiency. We performed quantum mechanical calculations to compute the partial atomic charges on atoms in hBN and MoS2 containing pores. Our DFT calculations reveal a spatially varying charge distribution on these 2D nanomaterials with pores, which we then incorporate into molecular dynamic simulations to elucidate their influence on the 2D nanomaterial-water interface. Our results reveal a significant impact of pore size on friction for nanomaterials containing hexagonal pores, while pore size had no effect on nanomaterials containing triangular pores. Moreover, friction increases with pores in both materials. This research contributes to the development of efficient and energy-saving desalination technologies through the manipulation of interfacial properties in 2D nanomaterials.

The structuring of a (semi) agile-based organization: product orientation in a state agency

Purpose The purpose of the paper is to analyze how a change towards product orientation based on an agile approach challenges, contrasts and/or coexists with other principles of organization and grouping, such as development projects, the existing hierarchical line structure and process management. Design/methodology/approach This is a case study of one organization, based on an explorative appoach. Findings Taking the competing dimension of coordination and principles of grouping as the starting point, this study identify, describe and analyze the tensions that result from the introduction of product organization. The product initiative has met many obstacles and tensions along four dimensions: Process, line, information technology units and development projects. For each of these dimensions a number of challenges have been identified, that contribute to increased complexity in the organization. Research limitations/implications A limitation of the study is that the findings cannot be generalized to other organizations. Practical implications A practical implication of the study is that product organization triggers tensions with other principles of organizations and grouping. Originality/value This study mainly contributes to the knowledge of agile management and agile organization, identifying and theorizing challenges that have been neglected and/or poorly understood both in the popular literature and in organizational research. This is particularly the case in the public sector. This study is also relevant to the domain of multidimensional structures, adding an understanding of the novel opportunities and challenges of product- and agile-based grouping of activities in an organization.

Research on digital transformation of banking industry must be associated with digital economy, digital society, green economy in Vietnam

The development of banking is an important factor in the economic development of the country and there have been many changes in the banking industry. These changes can be attributed to the development of technology: the popularity of mobile phones, the ability to access the Internet anytime, anywhere, the rapidly developing digital banking system... In the past few years, the finance - banking industry has been going through an important digital transformation period. However, in the strong development trend of technology, the banking system also faces many challenges, requiring a stronger transformation to be able to grasp digital technology trends, thereby applying and improving the quality of its products and services, making financial services more available, competitive and cost-effective. The purpose of this article is to provide an overview of technology trends in banking, challenges and make some recommendations. Keywords: Digital Transformation, Banking Industry, Digital Economy.

The Influence of Cultural Heritage Digitalization on the Public Aesthetics – A Case Study of the Dunhuang Mogao Grottoes

The applications of digital technology in cultural heritage have subtly and profoundly influenced the breadth and depth of public aesthetics. The objective of the study is to explore how diverse digital technologies impact public aesthetics, taking the digital dissemination and applications of Dunhuang's Mogao Grottoes as an example. Also, it anticipates the potential influence on public aesthetics of the ongoing evolution of technology inc. AIGC and its integration with cultural heritage. The results of the study revealed that digitalization applied in cultural heritage enhances the public aesthetics, while under the rapid development of technology, there are potential concerns of the aesthetic homogeneity, preconceived notions, and the over-emphasis on entertainment value. Future generations might reduce appreciation for authentic, in-person experiences and lead to fixed stereotypes of cultural heritage. Therefore, the thoughtful and balanced integration could better foster the public aesthetics.

What Is Needed to Determine and Potentially Improve the Clinical Effectiveness and Cost-Effectiveness of Robot-Assisted Reconstructive Urinary Tract and Pelvic Floor Surgery?-ICI-RS 2024.

Robot-assisted (RA) surgery has many advantages for urinary tract and pelvic floor reconstruction (UTPFR) but its application is only slowly increasing. Studies are limited in number, patients and follow-up duration. The low-volume high-complexity nature of UTPFR warrants specific research to evaluate the potential role of the RA approach. During its 2024 meeting in Bristol, the International Consultation on Incontinence-Research Society (ICI-RS) reviewed the current literature on RA UTPFR. Priority research questions and strategies were explored in a proposal. Four different topics were discussed. (1) Large multicentre prospective studies on RA UTPFR are needed to evaluate clinical effectiveness and safety. The RA approach needs to be prioritized in specific procedures and patients, to first improve patient care where gains are highest. (2) Models for cost-utility analysis for RA UTPFR are needed to (re)direct limited resources as efficiently as possible in a quickly changing technological field. (3) A modular curriculum for training UTPFR surgeons to become RA certified needs to be developed, to allow valid interpretation and comparison of outcomes. (4) Technological improvements to address tissue handling, accessibility, efficiency and sustainability are needed. Digitalization can be a gamechanger for RA UTPFR through telesurgery (training and expertize coverage), augmented reality and artificial intelligence providing intra-operative assistance, assessment and feedback. The proposal discussed the need for studies on clinical and cost effectiveness, safety, and training curriculum development for RA UTPFR. Recent technological developments hold great promise for RA UTPFR. High-priority research questions were identified.

Application and Development of Behavioural Economics in Consumer Decision Making

Behavioural economics, as an interdisciplinary field integrating psychology and economics, offers new perspectives for understanding consumer decision-making. This paper provides an overview of the core theories of behavioural economics, its applications in consumer decision making, and its developments and challenges in market practice and policy making. First, behavioural economics challenges traditional economic assumptions about rational decision-making by revealing core concepts such as limited rationality, prospect theory and behavioural biases, providing a deeper understanding of consumer behaviour. Second, the paper explores the effectiveness of behavioural economics in practical applications, such as improving firms' market performance and policy implementation by optimising marketing strategies, utilising personalised recommendations and developing behavioural intervention policies. However, behavioural economics still faces challenges in terms of theoretical universality, cross-cultural applicability and dynamic adaptation. Future research directions include theoretical integration, cross-cultural validation, adaptation to technological developments, optimisation of policy practices and intersection studies with psychology. The review in this paper aims to provide reference for academic research and practical application, to promote the further development of behavioural economics, and to provide theoretical support for policy making and market strategies.

Twelve tips for integrating Virtual Reality Simulation into Health Professions Curricula

Virtual reality simulation (VRS) has the potential to disrupt and transform current understandings and practices in simulation-based education in health professions curricula. Recent technological developments, including AI applications, give the learner high levels of immersion into a virtual environment that even more closely mimic the real world than heretofore. At the same time, there are significant obstacles facing educators who strive to integrate VRS into their simulation curricula. We have written a VRS handbook for nurse educators, developed VR scenarios and delivered VRS workshops to undergraduate nursing students. Our twelve tips are aimed at undergraduate curriculum developers and simulation leaders, guiding them on how to support educators in integrating VRS into their curricula. The tips describe key considerations to be addressed in the development and integration of VRS into curricula. The tips are timely, as health professions education is on the cusp of entering technology-enhanced simulation, of which VRS will be a key player.

Main path analysis: a methodological framework for knowledge diffusion trajectories in scientometrics studies

Purpose The purpose of this study is to propose an analytical framework for generating main path analysis (MPA) and demonstrate the process involved in identifying, analyzing the MPA on a citation network and empirically testing in the research field chromosome anomalies (CA). Design/methodology/approach The proposed methodological structure involves five phases of the process. Search path method is used to measure the weights of each citation link from a source vertex to a sink vertex. The key route local main path and global main path are generated to identify the knowledge diffusion trajectories and validated by cross-referencing with existing literature, co-citation analysis and centrality measures of social network analysis. Findings The empirical validation of this framework within CA research demonstrates its potential for tracing knowledge diffusion and technological development trajectories over three decades. This approach elucidates two major intellectual knowledge flows. The first key-route main path identified the primary diagnostic protocols. The second key-route main path revealed that cancer or carcinogenesis is identified as one of the mainstream of CA. Research limitations/implications The limitations of the data and coverage period restrict the scope of this study. MPA was applied exclusively to the most influential sub network and disregarded other sub networks. MPA identified the seminal papers that provided a historical development in diagnostic protocol and their interconnectedness of disorders and diseases. This helps the researchers to develop targeted therapies and interventions, especially in cancer treatment. Social implications Exploiting MPA on CA research provides valuable insights to stakeholders in developing evidence-based public health policies. This is crucial for preventing the birth of children with birth defects or genetic diseases, promoting public health and reducing the socioeconomic burden on a country through enhanced surveillance and prevention efforts. Originality/value The study suggests that in addition to traditional scientometrics measures, MPA can be used to trace the evolution of knowledge and technological advancements. It also highlights the role of social network analysis measures in extracting main paths.

Optimal data-driven strategy for in-house and outsourced technological innovations by open banking APIs

AbstractOpen banking is a customer consent-driven data-sharing framework to maintain interoperability among financial and non-financial institutions through secure application programming interfaces. Traditional retail banks are losing their competitive edge against digital banks, FinTech, and BigTech firms due to a higher outflow of customer account data than inflow. These firms capitalize on open banking data to launch innovative products and introduce “ready-to-deploy” Banking-as-a-Service platforms for end-to-end banking operations without the need to build full-scale infrastructures. Therefore, banks must reshape data-driven strategies to stay competitive. This research proposes a decision-support tool to select optimal digital strategies using the Strategic Value Index (SVI), a metric derived from analyzing multiple strategic objectives of bank stakeholders. The SVI minimizes implementation time and costs while maximizing operational action importance to a balanced digital strategy that combines both in-house and outsourced technological developments. The importance of operational action is quantified using evidential reasoning with fuzzy logic to address the challenge of aggregating incomplete and ambiguous banking data and assessments from multiple stakeholders. The theoretical approach is validated through a real application in a Latin American bank, and its findings are globally transferable. Cost and time data were sourced from public repositories, as made available accessible through government-mandated disclosures. The sensitivity analysis revealed that hybrid in-house and outsourced development is more flexible in meeting tight timelines and budget constraints. The combined approach is more cost-effective, time-efficient, and aligned with the internal needs of banks compared to either entirely in-house or fully outsourced models.