Implementation Of Framework Research Articles

On Integrating Mixed Reality within University Curricula

<span id="docs-internal-guid-b917b8d8-7fff-3bd4-23e3-5fc79a729e14"><span>The paper describes the architecture and implementation of an experimental framework based on a software platform for enhancing practical and theoretical learning capacities among students in different fields of specialisation by using mixed reality. This platform allows students’ effective interaction with a set of experimental models in two ways: by using interactive augmented reality based mobile applications or by using complete immersion. A case study on using this platform within a target group of students from University of Bacău, Romania is provided and some implications of this teaching approach are analysed. The results have empirically proved that using a learning environment based on mixed reality in teaching improves participatory culture, technical knowledge, and learning satisfaction degree of students. This study also emphasises the need for improvements in the integration of this framework to ensure that the technology's use is not limited to specific courses or user groups. </span></span>

Implementation of the children and young people’s health partnership model of paediatric integrated care: a mixed-methods process evaluation

ObjectiveA process evaluation of the Children and Young People’s Health Partnership (CYPHP) model of integrated care for the interpretation of trial findings and building evidence on the implementation of integrated...

Disparities in Diabetes Distress and Nutrition Management Among Black and Hispanic Adults: A Mixed Methods Exploration of Social Determinants.

The purpose of this study was to explore self-reported diabetes management strategies, social determinants of health (SDOH), and barriers to care among people with diabetes receiving care in a safety-net setting to identify factors contributing to disparities in outcomes for Black and Hispanic adults and inform future interventions. Sequential, explanatory, mixed methods study comprised a survey of adults with diabetes seen in primary care at a safety-net hospital in New England, followed by qualitative semistructured interviews with a subset of the Black and Hispanic respondents. Descriptive statistics, chi-square and t tests were used to analyze quantitative data. The health equity implementation framework was used to guide qualitative data collection and directed content analysis. A total of 496 respondents completed the survey; 48 Black and Hispanic adults participated in interviews. Diabetes-related distress was significantly higher among Black and Hispanic participants compared to White participants. Nutrition management use was significantly lower among Black and Hispanic participants. Qualitative findings suggest that SDOH and lack of education and support, specifically, nutrition and access to self-management resources, contributed to diabetes-related distress and prevented optimal self-management. High rates of diabetes-related distress and low rates of nutrition management were identified in Black and Hispanic adults in a safety-net setting. Qualitative interviews demonstrated a relationship between adverse SDOH and lack of nutrition education with diabetes distress and challenges to self-management, potentially contributing to disparities in outcomes. Findings suggest that increased uptake of nutrition therapy and self-management education and support may be critical for improving diabetes outcomes and promoting health equity.

Cooperation Between Universities and Public Schools Within the Framework of Acceleration-Deceleration Curriculum Implementation

Cooperation Between Universities and Public Schools Within the Framework of Acceleration-Deceleration Curriculum Implementation

Del relato a la conversión: El poder del Storytelling en el marketing digital en Ecuador

Storytelling has become a key tool in digital marketing, capable of significantly influencing brand perception and the customer conversion process. This article aims to analyze the impact of storytelling in digital marketing strategies in Ecuador, a country with a growing adoption of digital technologies and social networks. A qualitative-descriptive approach is employed based on a review of recent literature and success stories of local brands. It discusses the essential components of storytelling, such as authenticity, consistency and the ability to generate emotions, and how these factors enhance connection with consumers and promote engagement. Key metrics for measuring the effectiveness of storytelling campaigns and their impact on the conversion funnel are also examined. The findings highlight that brands that integrate storytelling into their digital strategies achieve greater loyalty and differentiation in the market. Finally, a framework for the effective implementation of storytelling in Ecuadorian digital marketing is proposed, considering the cultural and technological particularities of the environment.

Physics-based numerical implementation framework towardsmuti-scale contact problem

This paper establishes a general computational framework to solve the muti-scale contact problem by integrating the statistical contact model with the finite element format. Compared to existing models, the proposed method is applicable to most geometric configurations and can effectively evaluate the pressure distribution. In this work, a modified Karush-Kuhn-Tucker (KKT) condition is proposed by the assumption that asperity height obeys the Gaussian distribution. Therefore, in the variational formula, the contact contribution is decomposed into body contribution and asperity contribution, corresponding to the nominal smooth surface and roughness, respectively. Then the linearization and constraint enforcement of these two components are derived, followed by a nonlinear Newton-Raphson-based iterative algorithm. The contact patch test and Hertz contact test are conducted, and the predicted results are consistent with the theoretical and experimental values, confirming the effectiveness and accuracy of the proposed approach. It is worth noting that in the Hertz contact test, the contact pressure distribution varies progressively with the roughness level and external force, tending to the Hertz limit or Gaussian limit. This means that the proposed method can be applied to any roughness and load. Finally, the contact behaviors of the transmission interface of a piezoelectric actuator, i.e., a typical multi-scale contact problem, are studied as an engineering application case.

A New Control Approach for a Multi-Controlled Wheelchair Utilizing Deep Learning Framework and Raspberry Pi

This article describes the construction and control mechanisms of a multiple control wheelchair (MCW) aimed to aid individuals with amyotrophic lateral sclerosis (ALS) and lower limb disabilities. The MCW has been tested in the laboratory on a total of 10 patients, among them 3 with lower limb disabilities, 6 elderly patients, and 1 patient with ALS. The proposed wheelchair can navigate in any direction using object detection techniques powered by OpenCV. Employing a deep learning algorithm, it performs real-time object detection and tracks its current position in various environmental conditions. The MCW can be controlled using a joystick, internet of things (IoT), or a combination of both. A novel aspect of this work is the implementation of a deep learning framework on a Raspberry Pi processor, allowing the wheelchair to navigate in any direction based on the user’s needs. The Raspberry Pi interfaces with all sensors, camera, and additional peripherals through serial communication, enabling monitoring and control via an android mobile application. This setup effectively reduces the physical distance between the user and the caregiver. During the test, a range of functional measurements were taken, including assessments of the object detection process and the performance of hardware components such as sensors and motors connected to the system. The current system is unable to precisely determine an object’s position during detection, but ongoing research is focused on enhancing the system’s capability to accurately map objects in 3D space for improved wheelchair navigation.

Designing a Data Governance Framework for Cybersecurity Risk Reporting: A Model for Business Intelligence Teams

In the rapidly evolving digital landscape, the integration of robust data governance practices is crucial for enhancing cybersecurity risk reporting within organizations. This abstract presents a model for designing a data governance framework tailored specifically for Business Intelligence (BI) teams. The proposed framework emphasizes the intersection of data governance and cybersecurity, ensuring that data management practices support comprehensive risk reporting and decision-making processes. Key elements of the framework include data quality management, data access controls, and data lineage tracking, which collectively contribute to more accurate and timely cybersecurity risk assessments. By embedding these elements into the governance structure, BI teams can better manage and mitigate data-related risks, ensuring that cybersecurity threats are identified and addressed proactively. The model also incorporates advanced analytics and machine learning techniques to automate the detection of potential vulnerabilities, thereby enhancing the efficiency and effectiveness of risk reporting. Furthermore, the framework advocates for a collaborative approach, involving stakeholders from IT, security, compliance, and business units to ensure that data governance policies align with the organization's overall cybersecurity strategy. This interdisciplinary collaboration is essential for fostering a culture of cybersecurity awareness and accountability across the enterprise. In addition to technical considerations, the framework addresses the need for clear governance policies and procedures, regular audits, and continuous monitoring to maintain data integrity and compliance with regulatory requirements. The model is designed to be adaptable, allowing organizations to customize their data governance practices based on their specific industry, regulatory environment, and risk profile. The implementation of this data governance framework is expected to significantly improve the accuracy and reliability of cybersecurity risk reporting, providing BI teams with the tools and insights necessary to support informed decision-making and safeguard organizational assets against emerging threats.

A Guide for Implementing DPYD Genotyping for Systemic Fluoropyrimidines into Clinical Practice.

The safety of systemic fluoropyrimidines (e.g., 5-fluorouracil, capecitabine) is impacted by germline genetic variants in DPYD, which encodes the dihydropyrimidine dehydrogenase (DPD) enzyme that functions as the rate-limiting step in the catabolism of this drug class. Genetic testing to identify those with DPD deficiency can help mitigate the risk of severe and life-threatening fluoropyrimidine-induced toxicities. Globally, the integration of DPYD genetic testing into patient care has varied greatly, ranging from being required as the standard of care in some countries to limited clinical use in others. Thus, implementation strategies have evolved differently across health systems and countries. The primary objective of this tutorial is to provide practical considerations and best practice recommendations for the implementation of DPYD-guided systemic fluoropyrimidine dosing. We adapted the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework to cover topics including the clinical evidence supporting DPYD genotyping to guide fluoropyrimidine therapy, regulatory guidance for DPYD genotyping, key stakeholder engagement, logistics for DPYD genotyping, development of point-of-care clinical decision support tools, and considerations for the creation of sustainable and scalable DPYD genotype-integrated workflows. This guide also describes approaches to counseling patients about DPYD testing and result disclosure, along with examples of patient and provider educational resources. Together, DPYD testing and clinical practice integration aim to promote safe prescribing of fluoropyrimidine therapy and decrease the risk of severe and life-threatening fluoropyrimidine toxicities.

Precision Medical Education: Institutional Strategies for Successful Implementation.

Precision medical education (PME) represents a transformative approach in medical education, systematizing individualized and efficient learner competency development for enhanced patient care. While implementing PME has been described conceptually using the P4 medical education framework (proactive, personalized, participatory, predictive), many programs and institutions face implementation questions on navigating data integration complexities, resource constraints, cultural risk aversion to innovation, and more.To address such challenges, the authors of this Commentary propose 5 concrete, concurrent strategies for institutions and training programs to implement PME successfully. Of these strategies, 4 are aligned with the P4 framework. Strategy 1: Curate educational data, adhering to 8 foundational data principles (relevant, trusted, consistent, timely, accessible, connected, interactive, actionable), and integrate it into an education data warehouse to create a comprehensive learner profile. Strategy 2: Build institutional analytic capabilities, including leveraging existing resources and tools, such as artificial intelligence, to turn data into actionable insights. Strategy 3: Establish transparent, accountable governance structures with broad stakeholder engagement, emphasizing principled co-production of PME by learners, faculty, and educational leaders. Strategy 4: Continuously collect and evaluate outcomes tied to PME interventions, building validity evidence through predictive linkages. Strategy 5: Lead change to drive PME forward. This strategy cuts across all 4 other strategies to promote the effective adoption of systems and processes that drive PME into institutional culture.When successfully operationalized, PME enables precise, evidence-informed decision-making about and by learners, while benefiting faculty, coaches, and educational leaders. Through these strategies, programs and institutions can overcome implementation pitfalls and harness the full potential of PME to improve educational and patient care outcomes.

AI-Powered Predictive Analytics for Dynamic Cloud Resource Optimization: A Technical Implementation Framework

This article explores the transformative impact of AI-driven predictive analytics on cloud resource optimization, presenting a comprehensive technical implementation framework. The article shows how artificial intelligence and machine learning architectures revolutionize traditional cloud management approaches through advanced predictive capabilities and dynamic resource allocation. It examines the evolution from static threshold-based systems to sophisticated AI-driven solutions, analyzing their implementation strategies across various organizational contexts. The article delves into multiple optimization domains, including capacity provisioning, cost management, performance enhancement, and energy efficiency, while presenting real-world applications and impact analyses across different industries. Through extensive case studies and empirical evidence, the article demonstrates how organizations leverage AI-powered solutions to address complex cloud resource management challenges, achieve operational efficiencies, and maintain competitive advantages in the digital marketplace. The article also explores future developments and provides strategic recommendations for organizations implementing cloud optimization frameworks, emphasizing the importance of standardized approaches, stakeholder engagement, and sustainable practices in cloud resource management.

Enhancing Decision-Making Capacity through Data Governance Framework Implementation

Enhancing Decision-Making Capacity through Data Governance Framework Implementation

Navigating ethical dilemmas in Generative AI Development: A framework for responsible innovation

This comprehensive article explores the evolving landscape of ethical challenges and solutions in generative AI development, focusing on key areas, including data privacy, algorithmic bias, and implementation frameworks. Through detailed analysis of case studies and research findings, the study examines successful approaches to ethical AI implementation across various sectors, particularly in content generation and code development. The article presents a structured framework for ethical decision-making, emphasizing the importance of proactive assessment, stakeholder engagement, and continuous monitoring. By investigating cultural integration strategies and technical safeguards, this study provides valuable insights into establishing and maintaining ethical AI systems while balancing innovation with responsible development practices in an increasingly complex technological landscape.

Quantum computing-Enhanced AI systems for advanced business intelligence applications

The convergence of quantum computing and artificial intelligence represents a transformative technological paradigm with unprecedented potential for business intelligence applications. This comprehensive review critically examines the revolutionary capabilities of quantum computing-enhanced AI systems in addressing complex computational challenges across multiple business domains. Through systematic analysis of emerging research, implementation frameworks, and interdisciplinary case studies, we investigate how quantum computing's unique computational mechanisms can fundamentally reshape data analysis, strategic decision-making, and predictive modeling. Our comprehensive examination reveals that quantum AI systems demonstrate remarkable potential to reduce computational complexity by up to 90%, enhance predictive accuracy by 60-75%, and provide unprecedented insights across financial, logistical, and strategic business intelligence domains. The research synthesizes evidence from multiple technological domains, highlighting the transformative potential of quantum-enhanced AI in solving previously intractable computational problems. By exploring technological capabilities, implementation challenges, and future research directions, this review provides a critical framework for understanding the emerging intersection of quantum computing and artificial intelligence in advanced business intelligence applications.

Lessons from AI in finance: Governance and compliance in practice

This article examines the evolution and implementation of AI governance frameworks in financial institutions, focusing on the critical aspects of regulatory compliance and risk management. The article investigates how financial institutions have transformed their operations through AI adoption, particularly in areas such as fraud detection, customer data privacy, and regulatory compliance. By analyzing current governance practices, success factors, and implementation challenges, the article demonstrates the significant impact of AI on operational efficiency, risk management, and customer service delivery. The article highlights the importance of early compliance integration, transparent documentation, and continuous monitoring in successful AI governance frameworks, while also addressing future considerations including enhanced regulatory scrutiny, evolving privacy regulations, and the growing emphasis on ethical AI implementation.

P-1810. Implementation of the Core Elements of Hospital Antibiotic Stewardship Programs and the Priorities for Hospital Core Element Implementation in Long-term Acute Care Hospitals Reporting to the National Healthcare Safety Network, 2014 and 2023

Abstract Background The Centers for Disease Control and Prevention (CDC) defines the 7 Core Elements of Hospital Antibiotic Stewardship Programs as a framework for antibiotic stewardship implementation. In 2022, CDC released 6 Priorities for Hospital Core Element Implementation to enhance the quality and impact of existing antibiotic stewardship programs. Acute care hospitals reported 97% uptake of the 7 Core Elements and 10% uptake of the 6 Priorities in 2022 as per reporting to the National Healthcare Safety Network (NHSN) Annual Hospital Survey. However, stewardship implementation in long-term acute care (LTAC) hospitals has not been widely assessed. The objective of this analysis was to assess the uptake of the 7 Core Elements and 6 Priorities in LTAC facilities in 2023 and compare Core Elements uptake to 2014.Table 1.Facility Characteristics of Long-Term Acute Care (LTAC) Hospitals Reporting to the National Healthcare Safety Network Annual Facility Survey for LTAC, 2014 and 2023 Methods We used the NHSN Annual Facility Surveys for LTAC hospitals (4/1/2024 data pull) for survey years 2014 and 2023 to characterize facility characteristics and self-reported responses to antibiotic stewardship program survey questions. We mapped stewardship survey questions to corresponding Core Elements and Priorities to describe the reported uptake of the 7 Core Elements and 6 Priorities.Figure 1.Reported Implementation of the Priorities for Hospital Core Element Implementation by Priority in Long-Term Acute Care (LTAC) Hospitals (N=337), 2023 Results In 2014 and 2023, 489 and 337 LTAC hospitals completed the annual survey. In 2023, most LTAC facilities were for-profit (79%), free-standing (58%), part of multi-facility organizations (47%), and in the South (50%) (Table 1). From 2014 to 2023, the number of facilities reporting uptake of all 7 Core Elements in LTAC hospitals increased from 60% to 98%. In 2023, 2% of LTAC hospitals reported meeting the 6 Priorities and 44% reported meeting 4-5 Priorities. The highest reported uptake of Priorities across LTAC hospitals was Pharmacy Expertise (81%) and Leadership (77%). The lowest reported uptake of Priorities was Tracking (7%) and Reporting (42%) (Figure 1). Conclusion LTAC hospitals reported uptake of the Core Elements of Antibiotic Stewardship increased from 2014 to 2023, on par with the increase acute care hospitals reported for Core Elements implementation. Engagement with LTAC hospital leadership and leveraging pharmacy expertise are important to support antibiotic stewardship Priorities, especially tracking & reporting of antibiotic use. Disclosures All Authors: No reported disclosures

Infrastructure Investments under Pillar Two: A Substitute for Tax Payments?

Governments often offer tax incentives to multinational enterprises to encourage the development of large infrastructure projects, creating a mutually beneficial arrangement that fosters investment and economic growth. However, the introduction of the OECD’s Pillar Two framework and subsequent implementation of legislation in many countries, which mandates a global minimum tax rate of 15%, has placed these tax incentives under scrutiny. This article explores whether infrastructure investments could be classified as a substitute for tax payments under the new Pillar Two rules. Through practical examples and analysis, the authors examine the challenges and opportunities for businesses navigating this shifting landscape, offering insights into how multinational enterprises can align their strategies to meet compliance while continuing to support infrastructure development in host countries.

Optimization and Implementation Framework for Connected Demand Responsive Transit (DRT) Considering Punctuality

Demand Responsive Transit (DRT) is gaining attention as a flexible and efficient solution for connecting urban transit hubs, but challenges such as travel time variability and punctuality remain significant barriers. This study develops a robust optimization framework with variable travel speed to address these issues, minimizing user and operator costs while reducing transfer waiting times. The framework incorporates variable travel speeds and employs a genetic algorithm to optimize routes and operations compared to many studies using constant commercial speed. Experiments conducted in Hwaseong, South Korea, analyzed scenarios with varying service rates, vehicle capacities, and detour ratios. Results show that implementing punctuality-constrained DRT reduces total travel times by 14% compared to subways and 36% compared to buses, highlighting its potential to significantly improve user convenience and operational efficiency. The findings suggest that carefully designed DRT systems with highly reliable punctuality can enhance urban mobility by integrating seamlessly with existing transit networks, providing a cost-effective and reliable alternative to traditional public transport.

Effectiveness of using implementation frameworks to facilitate the implementation of a stroke management guideline in the traditional Chinese medicine hospitals in China: protocol for a factorial randomised controlled trial

IntroductionTraditional Chinese medicine (TCM) is commonly used alongside Western medicine for stroke management in China. However, there is significant variation in TCM practice, and the utilisation of evidence-based clinical practice...

Initiating agri‐environmental collaboration at landscape scale requires bridging structures, regional facilitators and addressing the expectations of actors

Abstract To increase the effectiveness of agri‐environmental schemes, innovative approaches that focus on the landscape scale beyond individual fields and farms are widely discussed and tested. Central to these approaches is collaboration between several farmers and other actors in agricultural landscapes. The effectiveness of collaborative agri‐environmental initiatives is strongly related to the motivation of actors. Administrative and social issues might hamper actor decisions to join an initiative. Based on our experience in implementing a participatory landscape‐scale project in Germany, we raise the question in which ways actors can be motivated and empowered to participate in such initiatives and how collaborative approaches can stimulate and maintain the exchange of participants. We find that establishing bridging structures (for an equal exchange of ideas and experiences), identifying and involving regional facilitators (to promote the participation of farmers and other actors) and addressing the expectations of actors (e.g. regarding administrative burden) can jointly support the establishment of collaborative initiatives in agriculture. This is particularly relevant when local actors have little experience with joint measure implementation and institutional framework conditions for collaborative governance are limited or not provided. Read the free Plain Language Summary for this article on the Journal blog.