Opportunities For Collaboration Research Articles

Beyond the M.D.: Transdisciplinary approaches of high-volume dual degree M.D./Masters programs at U.S. allopathic medical schools

PurposeTransdisciplinarity has been described as a fusion of theories, methods, and expertise across disciplinary boundaries to address complex, global problems. This approach has coincided with an increase in US medical schools offering masters degrees along with an MD degree to equip medical students to practice in complex, interconnected health systems. This study focused on medical schools that graduate the most dual degree students per year and explored the alignment of such programs with a transdisciplinary approach.MethodsWe identified 19 allopathic medical schools that annually graduated an average of 10 or more dual-degree students from 2015–2020. We surveyed these schools and asked participants to describe the reason(s) their institutions offered dual-degree programs. Two authors coded the narrative responses from the survey.ResultsResponses were received from 17 of the 19 schools. The analysis of participants’ responses regarding their institutions’ purpose for offering dual programs revealed several themes associated with a transdisciplinary approach to training. The most common themes were expand skill sets beyond a medical degree (73%), provide opportunity for interdisciplinary collaboration (67%), expand career interest and goals (60%), develop leaders (53%), enhance residency applications (47%) and further the institution’s vision and mission (45%).ConclusionsThis study is the first comprehensive evaluation of MD/Masters programs in the United States that includes a summary of the medical schools with the largest dual degree programs and their reasons for offering them. The findings support the hypothesis that allopathic medical schools recognize the need for a transdisciplinary approach to prepare students for the complexities in healthcare. These programs provide students with opportunities for additional areas of expertise, leadership development, enhancement of competitiveness for residency application, and interdisciplinary collaboration. Medical schools without dual-degree programs may consider developing these programs to provide benefits to students and institutions.

Deep Learning - Methods to Amplify Epidemiological Data Collection and Analyses.

Deep learning is a subfield of artificial intelligence and machine learning based mostly on neural networks and often combined with attention algorithms that has been used to detect and identify objects in text, audio, images, and video. Serghiou and Rough (Am J Epidemiol. 0000;000(00):0000-0000) present a primer for epidemiologists on deep learning models. These models provide substantial opportunities for epidemiologists to expand and amplify their research in both data collection and analyses by increasing the geographic reach of studies, including more research subjects, and working with large or high dimensional data. The tools for implementing deep learning methods are not quite yet as straightforward or ubiquitous for epidemiologists as traditional regression methods found in standard statistical software, but there are exciting opportunities for interdisciplinary collaboration with deep learning experts, just as epidemiologists have with statisticians, healthcare providers, urban planners, and other professionals. Despite the novelty of these methods, epidemiological principles of assessing bias, study design, interpretation and others still apply when implementing deep learning methods or assessing the findings of studies that have used them.

“Can we not do group stuff?”: Student insights on implementing co-creation in online intensive programs

The demand for intensive educational experiences is increasing, necessitating a focus on ensuring quality and providing adequate student support. Increasing opportunities for student collaboration, including teacher/student co-creation of learning materials, has strong potential to increase engagement and support. Given increased interest in co-creation within education and research more broadly, we explored student perspectives on this novel approach within online intensive modes of teaching with a focus on feasibility and implementation. Two focus groups were conducted with students (N = 16), including discussion of their preferences and barriers for implementing co-creation initiatives in an intensive program. Thematic analysis was then conducted, generating five themes. Students see co-creation as beneficial for self-development and connections (Theme 1), but also identify barriers such as its perception as another group assignment (Theme 2). Students believe successful co-creation requires a “type” of student who is intrinsically motivated and career-driven (Theme 3). Concerns exist about co-creation being an additional workload, emphasising the need for clear roles (Theme 4). Students’ views on co-creation vary, with differing opinions on its practicality (Theme 5). The findings suggest that successful implementation of co-creation initiatives requires careful consideration of barriers while addressing student concerns and leveraging their intrinsic motivation. For educators in intensive programs, it is crucial to provide incentives, collaborate on feasible time slots, establish clear objectives and timelines, offer guidance and support, and celebrate student achievements to effectively incorporate co-creation activities. By understanding students’ perceptions and preferences, educators can better support student collaboration, which is crucial for students’ development in intensive programs.

Challenges and Opportunities of Using Metaverse Tools for Participatory Architectural Design Processes

Participatory design emerges as a proactive approach involving different stakeholders in design and decision-making processes, addressing diverse values and ensuring outcomes align with users’ needs. However, the inadequacy of engaging stakeholders with a spatial experience can result in uninformed and, consequently, unsuccessful design solutions in a built environment. This paper explores how metaverse tools can help enhance participatory design by providing new collaborative opportunities via networked 3D environments. A hybrid format (online and in situ) co-creation process was documented and analysed, targeting public space design in London, Hong Kong, and Lisbon. The participants collaborated to address a set of design requirements via a tailored metaverse space, following a six-step methodology (Tour, Discuss, Rate, Define, Action, and Show and Tell). The preliminary results indicated that non-immersive metaverse tools help strengthen spatial collaboration through user perspective simulations, introducing novel interaction possibilities within design processes. The technology’s still-existing technical limitations may be tackled with careful engagement design, iterative reviews, and participants’ feedback. The experience documented prompts a reflection on the role of architects in process design and mediating multi-stakeholder collaboration, contributing to more inclusive, intuitive, and informed co-creation.

The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends

Machine learning (ML) and deep learning (DL) have become very popular in the research community for addressing complex issues in intelligent transportation. This has resulted in many scientific papers being published across various transportation topics over the past decade. This paper conducts a systematic review of the intelligent transportation literature using a scientometric analysis, aiming to summarize what is already known, identify current research trends, evaluate academic impacts, and suggest future research directions. The study provides a detailed review by analyzing 113 journal articles from the Web of Science (WoS) database. It examines the growth of publications over time, explores the collaboration patterns of key contributors, such as researchers, countries, and organizations, and employs techniques such as co-authorship analysis and keyword co-occurrence analysis to delve into the publication clusters and identify emerging research topics. Nine emerging sub-topics are identified and qualitatively discussed. The outcomes include recognizing pioneering researchers in intelligent transportation for potential collaboration opportunities, identifying reliable sources of information for publishing new work, and aiding researchers in selecting the best solutions for specific problems. These findings help researchers better understand the application of ML and DL in the intelligent transportation literature and guide research policymakers and editorial boards in selecting promising research topics for further research and development.

Opportunities and Challenges in Cross-Country Collaboration: Insights from the Beneluxa Initiative

National pricing and reimbursement agencies face growing challenges with complex health technologies, prompting European policy advancements. Beneluxa is a cross-country collaboration involving Belgium, the Netherlands, Luxemburg, Austria, and Ireland that aims to address sustainable access to medicines. In view of the soon-to-be-implemented EU HTA Regulation, insights and experiences from stakeholders with Beneluxa cross-country collaboration could provide possible transferable learnings. Therefore, this research aims to (i) identify the opportunities and challenges faced by Beneluxa, (ii) gather insights from stakeholders, namely (possible) applicants and policymakers, within and beyond Beneluxa on the initiative and broader cross-country collaboration principles, and (iii) transfer these insights into learnings and recommendations in anticipation of the full implementation of the new HTA Regulation. Fifteen semi-structured interviews were conducted with industry and European HTA/policy stakeholders. The principal challenges discussed by stakeholders encompass hesitancy from the industry toward Beneluxa assessments, which were attributed to procedural and timeline uncertainties, legislative framework ambiguity, and challenges in terms of industry’s internal organization. Another challenge highlighted is the resource-intensive nature of the procedure due to diverse approaches among member states. In addition, industry stakeholders mentioned limited communication and procedural complexity. Despite challenges, both stakeholder groups recognized important opportunities for cross-country collaboration. Transferable insights for future cross-country collaboration include transparent communication, clear legislative embedding, internal industry restructuring to facilitate joint HTAs, and member state support for conducting collaborative assessments. The study underscores diverging views among stakeholders on cross-country collaboration’s potential to support HTA and the market access of complex health technologies. While acknowledging benefits, there still are challenges, including industry hesitancy, emphasizing the need for transparent communication and clear guidance in the evolving EU HTA landscape.

Opportunities and Challenges in Cross-Country Collaboration: Insights from the Beneluxa Initiative

National pricing and reimbursement agencies face growing challenges with complex health technologies, prompting European policy advancements. Beneluxa is a cross-country collaboration involving Belgium, the Netherlands, Luxemburg, Austria, and Ireland that aims to address sustainable access to medicines. In view of the soon-to-be-implemented EU HTA Regulation, insights and experiences from stakeholders with Beneluxa cross-country collaboration could provide possible transferable learnings. Therefore, this research aims to (i) identify the opportunities and challenges faced by Beneluxa, (ii) gather insights from stakeholders, namely (possible) applicants and policymakers, within and beyond Beneluxa on the initiative and broader cross-country collaboration principles, and (iii) transfer these insights into learnings and recommendations in anticipation of the full implementation of the new HTA Regulation. Fifteen semi-structured interviews were conducted with industry and European HTA/policy stakeholders. The principal challenges discussed by stakeholders encompass hesitancy from the industry toward Beneluxa assessments, which were attributed to procedural and timeline uncertainties, legislative framework ambiguity, and challenges in terms of industry’s internal organization. Another challenge highlighted is the resource-intensive nature of the procedure due to diverse approaches among member states. In addition, industry stakeholders mentioned limited communication and procedural complexity. Despite challenges, both stakeholder groups recognized important opportunities for cross-country collaboration. Transferable insights for future cross-country collaboration include transparent communication, clear legislative embedding, internal industry restructuring to facilitate joint HTAs, and member state support for conducting collaborative assessments. The study underscores diverging views among stakeholders on cross-country collaboration’s potential to support HTA and the market access of complex health technologies. While acknowledging benefits, there still are challenges, including industry hesitancy, emphasizing the need for transparent communication and clear guidance in the evolving EU HTA landscape.

A place for (socio)linguistics in audio deepfake detection and discernment: Opportunities for convergence and interdisciplinary collaboration

AbstractDeepfakes, particularly audio deepfakes, have become pervasive and pose unique, ever‐changing threats to society. This paper reviews the current research landscape on audio deepfakes. We assert that limitations of existing approaches to deepfake detection and discernment are areas where (socio)linguists can directly contribute to helping address the societal challenge of audio deepfakes. In particular, incorporating expert knowledge and developing techniques that everyday listeners can use to avoid deception are promising pathways for (socio)linguistics. Further opportunities exist for developing benevolent applications of this technology through generative AI methods as well.

DCP-Net: A Distributed Collaborative Perception Network for Remote Sensing Semantic Segmentation

Collaborative perception enhances onboard perceptual capability by integrating features from other platforms, effectively mitigating the compromised accuracy caused by a restricted observational range and vulnerability to interference. However, current implementations of collaborative perception overlook the prevalent issues of both limited and low-reliability communication, as well as misaligned observations in remote sensing. To address this problem, this article presents an innovative distributed collaborative perception network (DCP-Net) specifically designed for remote sensing applications. Firstly, a self-mutual information match module is proposed to identify collaboration opportunities and select suitable partners. This module prioritizes critical collaborative features and reduces redundant transmission for better adaptation to weak communication in remote sensing. Secondly, a related feature fusion module is devised to tackle the misalignment between local and collaborative features due to the multiangle observations, improving the quality of fused features for the downstream task. We conduct extensive experiments and visualization analyses using three semantic segmentation datasets, namely Potsdam, iSAID, and DFC23. The results demonstrate that DCP-Net outperforms the existing collaborative perception methods comprehensively, improving mIoU by 2.61% to 16.89% at the highest collaboration efficiency and achieving state-of-the-art performance.

DCP-Net: A Distributed Collaborative Perception Network for Remote Sensing Semantic Segmentation

Collaborative perception enhances onboard perceptual capability by integrating features from other platforms, effectively mitigating the compromised accuracy caused by a restricted observational range and vulnerability to interference. However, current implementations of collaborative perception overlook the prevalent issues of both limited and low-reliability communication, as well as misaligned observations in remote sensing. To address this problem, this article presents an innovative distributed collaborative perception network (DCP-Net) specifically designed for remote sensing applications. Firstly, a self-mutual information match module is proposed to identify collaboration opportunities and select suitable partners. This module prioritizes critical collaborative features and reduces redundant transmission for better adaptation to weak communication in remote sensing. Secondly, a related feature fusion module is devised to tackle the misalignment between local and collaborative features due to the multiangle observations, improving the quality of fused features for the downstream task. We conduct extensive experiments and visualization analyses using three semantic segmentation datasets, namely Potsdam, iSAID, and DFC23. The results demonstrate that DCP-Net outperforms the existing collaborative perception methods comprehensively, improving mIoU by 2.61% to 16.89% at the highest collaboration efficiency and achieving state-of-the-art performance.

A Qualitative Study on Talent Management in Enterprises within the Industry 4.0 Process

Purpose - This study aims to examine the effects of Industry 4.0 on talent management. It is observed that resources are allocated and training programs are organised for the transformation of the workforce in the Industry 4.0 process.Design/Methodology - Qualitative research approach was adopted in the study. Using purposive sampling method, 4 different industrial enterprises were analysed. Data collection process was carried out through face-to-face and online interviews.Findings - Organizations prioritize continuous training and fringe benefits in talent management, while employee involvement in social responsibility projects and teamwork enhances internal communication. In the Industry 4.0 era, maintaining organizational balance and providing diverse opportunities to talented employees are crucial.Practical Implications - The study suggests that implementing 28 different practices such as brand equity, collaboration, work-life balance and career opportunities to retain talent can increase awareness of the impact of Industry 4.0 on HR management. Establishing sector-based standards and models can help researchers in Turkey to implement Industry 4.0 and talent management practices.

Understanding the Role of Finance in Sustainable Development: A Qualitative Study on Environmental, Social, and Governance (ESG) Practices

This qualitative literature review investigates the multifaceted landscape of sustainable finance, aiming to provide insights into its key dimensions and implications for sustainable development. The research methodology involves a comprehensive examination of existing literature utilizing qualitative analysis techniques such as thematic analysis, content analysis, and narrative synthesis. The study explores environmental considerations, social dimensions, and governance practices within sustainable finance, drawing on diverse perspectives from academic literature, industry reports, and policy documents. Key findings reveal the pivotal role of sustainable finance in advancing environmental objectives by mobilizing capital towards environmentally sustainable projects, promoting conservation, and facilitating the transition to a low-carbon economy. Moreover, the study highlights the significance of addressing social issues such as labor rights, gender equality, and community development through sustainable finance initiatives. Additionally, effective governance practices are identified as essential for ensuring transparency, accountability, and ethical conduct within the financial sector. The implications of sustainable finance extend beyond financial markets, encompassing environmental outcomes, social equity, and governance frameworks crucial for achieving sustainable development goals. Despite challenges such as data availability, standardization, and regulatory coherence, sustainable finance presents opportunities for innovation and collaboration to address pressing global challenges. Overall, this study contributes to a deeper understanding of sustainable finance and underscores its potential to drive positive change towards a more resilient, inclusive, and sustainable global economy.

Opportunities for interprofessional collaboration between pharmacists and hearing professionals in Pennsylvania: A descriptive geographic information system study

BackgroundIn 2022, the Food and Drug Administration finalized regulations for over-the-counter (OTC) hearing aids, available without professional hearing services and without a prescription. As a result, community pharmacies now serve as locations where adults seek self-care solutions for hearing loss such as OTC hearing aids. ObjectivesWe conducted a geographic information systems (GIS) analysis to identify Pennsylvania counties served by community pharmacies and hearing aid dispensaries, the practice locations of hearing professionals. MethodsWe obtained addresses of Pennsylvania pharmacies from the National Council for Prescription Drug Programs. Hearing aid dispensaries were obtained from the Pennsylvania Department of Health. GIS software was used to plot locations of pharmacies and hearing aid dispensaries. The number of pharmacies and hearing aid dispensaries was visualized on a Pennsylvania map, by county. Mean straight-line distances, in miles, from a hearing aid dispensary to its nearest pharmacy in any county and vice versa were calculated. This analysis was performed in early 2022. ResultsIn Pennsylvania, there were more community pharmacies (2769) than hearing aid dispensaries (945). All 67 Pennsylvania counties had more pharmacies than hearing aid dispensaries. Pharmacies outnumbered hearing aid dispensaries by 1 in some rural counties to 382 in urban Philadelphia County. The mean straight-line distance from a hearing aid dispensary, starting point, to the nearest pharmacy, end point, was 0.63 miles. The mean straight-line distance from a pharmacy, starting point, to the nearest hearing aid dispensary, end point, was 3.24 miles. ConclusionThis GIS analysis supports the participation of pharmacists in initiatives such as OTC hearing aids that increase population access to hearing care.

Studying K-12 and post-secondary teachers’ reflections on the value of a citizen science project for fostering learning: The case of a winter stream project

Citizen science programs offer the public opportunities to be involved in hands-on scientific data collection and study. Despite a history of incorporating citizen science in the K-12 classroom, little research has focused on projects that are appealing to both K-12 instructors and higher education faculty. Our study investigates initial barriers and motivations for participation in citizen science at multiple education levels using a winter, stream ecology citizen science project. Our findings indicate a growing interest in citizen science programs in winter, as they provide opportunities for collaboration, encourage flexible data collection, and offer tangible results for participants to reflect on their local ecological habitats.

Preface

From 22nd to 24th December 2023, the 2023 3rd International Conference on Computational Modeling, Simulation and Data Analysis (CMSDA 2023) was held in Sanya, China via virtual form. The Conference attracted about 150 researchers, engineers, teachers and students worldwide working in or interested in the fields related to computational modeling, simulation and data analysis. The general objectives of the CMSDA 2023 were: To generate an adequate academic and scientific forum to present the work and experiences of researchers/teachers/students, contributing, in this way, to the production of new knowledge in the fields of computational modeling and data analysis. To create a path of establishing certain relationships for the speakers, authors and listeners, and providing opportunities for collaboration among the universities and institutions, in order to promote scientific research activities and develop relevant technologies. The subject areas in which the accepted papers were presented cover but are but not limited to: Perceptual Issues in Visualization and Modeling; Mathematical and Numerical Methods in Simulation and Modeling; Parallel and Distributed Computing Simulation; Big Data Visual Analysis; Data Analysis Algorithms and Systems, etc. We have invited renowned professors at home and abroad in these academic fields who shared with the attendees the latest innovations and research results in the domains of computational modeling, data mining and analysis. The Conference mainly featured keynote speeches by renowned experts and presentations of peer-reviewed papers by the authors. Among them, Prof. Daowen Qiu (Sun Yat-Sen University, China) shared his research on Distributed Quantum Algorithm for Simon’s Problem. Limited by today’s physical devices, quantum circuits are usually noisy and difficult to be designed deeply. The novel computing architecture of distributed quantum computing is expected to reduce the noise and depth of quantum circuits. And in his study, he presented the Simon’s problem in distributed scenarios and designed a distributed quantum algorithm to solve the problem. The algorithm proposed by him has the advantage of not only exponential acceleration compared with the classical distributed computing, but also square acceleration compared with the best distributed quantum algorithm proposed before. The Conference Proceedings was made so fruitful with all the excellent contributions collected from both domestic and international channels including the wonderful presentations in the Conference. It is a pleasure to thank the organizers, sponsors and all the participants and contributors for making the Conference possible and interesting. And our appreciation also to the members of Journal of Physics: Conference Series for providing us help in publishing this paper volume. The Committee of CMSDA 2023 List of Committee Member is available in this pdf.

Cultivating Resilience and Success: Support Systems for Novice Teachers in Diverse Contexts

This qualitative study explores the support systems that foster resilience and success among novice teachers in diverse sociocultural contexts within Israeli teacher training colleges. Semistructured interviews were conducted with a sample of 51 novice teachers from various educational backgrounds. The findings reveal a complex network of support encompassing formal institutional structures, such as mentorship programs and induction workshops, as well as informal networks of familial support and cultural connections. Utilizing a holistic framework that integrates social support theory, social connection theory, and self-determination theory, the study highlights the interplay between external support and novice teachers’ intrinsic motivations, which drive their pursuit of autonomy, competence, and relatedness. The key findings underscore the crucial role of comprehensive induction and mentoring programs that address novice teachers’ emotional, psychological, and professional needs. These programs should provide emotional support, opportunities for collaboration and peer learning, and personalized guidance from experienced mentors. The study also emphasizes the significance of supportive school cultures, meaningful mentoring relationships, and the strength of informal support networks in promoting novice teachers’ well-being and effectiveness. The implications of this research are far-reaching, offering valuable insights for the global educational community on developing supportive ecosystems that enhance novice teachers’ resilience, job satisfaction, and retention rates. By articulating the essential role of both formal and informal support systems, this study contributes significantly to the discourse on teacher education and addresses a crucial gap in the literature on support mechanisms across diverse educational settings.

How property relations shape experiences and transformative potential of urban growing spaces: Connecting land, food, and Earth justice perspectives

This study uses both socio-legal and theoretical methods to examine the ambivalent role of property regimes in food system transformation. Combining an Earth justice perspective with a small-scale empirical study of how property and land-use laws affected experiences of growing spaces in an English city that included some element of collective ownership or management, we argue for greater diversity in formal legal structures (e.g., tenancy models), but also in concepts of land relationships. Our discussion diverts attention from individual entitlements to allocation of responsibilities and opportunities for human and interspecies collaboration. Growers’ experiences were shaped by productivist property narratives but provide a material basis to think beyond individual entitlement, reframing issues of security of tenure and public access in terms of responsibility and connection.

Practice makes perfect: the development of a medical student-led crowdsourced question bank for self-study in undergraduate medical education

Implication Statement The development of multiple-choice questions (MCQs) for undergraduate medical education study purposes is resource intensive. Commercially available question banks are typically expensive, only available in English, and may not be aligned with medical school learning objectives. Here, we introduce The Ottawa Question Bank: a student-led, bilingual study resource curated to a Canadian undergraduate medicine curriculum (www.theottawaquestionbank.ca). In total, 205 medical students wrote and edited 4438 original MCQs linked to objectives from the University of Ottawa undergraduate medical education curriculum. The project has received positive feedback from both developers and users. Our experience suggests that involving medical students in MCQ development is feasible and can result in the rapid creation of a low-cost, high-quality study resource curated to a program’s learning objectives. The platform outlined here can be used as a model for other medical schools and professional degree programs to develop their own question banks, including pharmacy, dentistry, nursing, and physiotherapy. Interested programs are encouraged to contact our team for collaborative opportunities.

Substance Use Disorder Treatment: Opportunities for Interdisciplinary Collaboration in Neurology and Beyond.

Driving the overdose epidemic, a significant proportion of adult and adolescent patients seen in neurology practice and hospital settings has substance use disorder. Fortunately, there are effective treatments available, in particular for opioid addiction. Some elements of treatment can be delivered directly in medical office-based settings, while others are best provided from within specialized addiction treatment facilities. In this article, we review the nature of substance use disorders, and the various treatment approaches that can be utilized to stabilize patients and facilitate their building a strong recovery foundation. Some interventions discussed may be directly provided by a physician identifying the disorder, while others involve collaboration with specialized addiction treatment centers and recovery support entities.

Emerging Trends in Applied Mathematics

This research explores the emerging trends in applied mathematics and their far-reaching implications in various fields. Machine learning and artificial intelligence are revolutionizing healthcare, finance, and natural language processing. Big data analysis is enhancing decision-making in finance, healthcare, and logistics. Quantum computing promises to transform materials science and renewable energy. These trends are reshaping research and practice, offering innovative solutions and opportunities for interdisciplinary collaboration. Ethical considerations and the development of advanced algorithms are critical areas of future research. This study serves as a foundation for understanding and harnessing the potential of these trends, emphasizing the importance of continuous exploration and skill development in an evolving mathematical landscape.