Research In Field Research Articles

Prompt Engineering Paradigms for Medical Applications: Scoping Review.

Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to its specialized terminology and language technicity. Clinical natural language processing applications must navigate complex language and ensure privacy compliance. Prompt engineering offers a novel approach by designing tailored prompts to guide models in exploiting clinically relevant information from complex medical texts. Despite its promise, the efficacy of prompt engineering in the medical domain remains to be fully explored. The aim of the study is to review research efforts and technical approaches in prompt engineering for medical applications as well as provide an overview of opportunities and challenges for clinical practice. Databases indexing the fields of medicine, computer science, and medical informatics were queried in order to identify relevant published papers. Since prompt engineering is an emerging field, preprint databases were also considered. Multiple data were extracted, such as the prompt paradigm, the involved LLMs, the languages of the study, the domain of the topic, the baselines, and several learning, design, and architecture strategies specific to prompt engineering. We include studies that apply prompt engineering-based methods to the medical domain, published between 2022 and 2024, and covering multiple prompt paradigms such as prompt learning (PL), prompt tuning (PT), and prompt design (PD). We included 114 recent prompt engineering studies. Among the 3 prompt paradigms, we have observed that PD is the most prevalent (78 papers). In 12 papers, PD, PL, and PT terms were used interchangeably. While ChatGPT is the most commonly used LLM, we have identified 7 studies using this LLM on a sensitive clinical data set. Chain-of-thought, present in 17 studies, emerges as the most frequent PD technique. While PL and PT papers typically provide a baseline for evaluating prompt-based approaches, 61% (48/78) of the PD studies do not report any nonprompt-related baseline. Finally, we individually examine each of the key prompt engineering-specific information reported across papers and find that many studies neglect to explicitly mention them, posing a challenge for advancing prompt engineering research. In addition to reporting on trends and the scientific landscape of prompt engineering, we provide reporting guidelines for future studies to help advance research in the medical field. We also disclose tables and figures summarizing medical prompt engineering papers available and hope that future contributions will leverage these existing works to better advance the field.

The impact of K-beauty entrepreneurship on technical competency and business performance—Focusing on the CEO

This study investigates the relationships among entrepreneurship, technical competency, and business performance, focusing on CEOs in the beauty service industry in the Busan area. A total of 215 survey responses were collected, with 213 valid responses selected for final analysis after excluding 2 unsuitable responses. The key findings of the study are as follows: First, entrepreneurship was found to partially influence technical competency. Second, technical competency was found to influence business performance. Third, entrepreneurship was found to partially influence business performance. Fourth, technical competency was found to partially mediate the relationship between entrepreneurship and business performance. Based on these results, the study systematically analyzes and explains the causal relationships among the entrepreneurship of CEOs in the beauty service industry, their technical competency, and business performance. It also seeks to provide useful reference materials for strengthening the innovation and competitiveness of CEOs in the beauty service industry and establishing a theoretical foundation for future research in related fields.

Process of Phenomenology as Qualitative Research Method in English

Research methodology is a pronounced science that contributes to the study of research in many fields. The literature on research methodology shows how it serves in several ways as it is multi-dimensional and theoretical alongside the features of experimental literature. Based on different philosophies, it involves two significant methods of choice, qualitative and quantitative, with a range of research strategies from simple to complex. Fundamentally, the strategies of the qualitative method are of much use in the study of English literature and to some extent in the studies of English language and Applied linguistics since the latter also deal with empirical study. The current research method, phenomenology, is one of the critical approaches of the qualitative method, and it is all about philosophical experiences. The study of phenomenology in English is necessary as it has been a widely used method in the fields of medical science, philosophy, computers, and business but not still more in English and Second language acquisition studies; therefore, the main motive behind the study is to investigate how congenial the phenomenology research method is to exploit it in English language and literature studies. Concerning the abovementioned facts, the present study will include the conceptualization, periodical developments, classification, and the milestones associated with phenomenological research studies to analyze and extract as a research method in English. The study also endeavors to identify philosophy and language as two important parameters and emphasizes that they are equally necessary to use phenomenology as a research method in English.

Social assessment of the population for the transition to Value- based healthcare model

Background: The advanced experience of implementing a value-based model in the practice of Moscow healthcare allowed us to identify a number of the most significant practices of its effectiveness, among which support for making an informed decision by the patient, as well as measuring satisfaction and analyzing the needs of patients were noted. In this regard, the transition of the entire national healthcare system to a value-based model requires the development of approaches to assessing the population’s compliance with such a transformation, taking into account socio-economic, demographic and psychological criteria. Aim: To consider possible predictors of the readiness of a social group of the population older than working age to transition to a value-based model of national health care. Materials and methods: A review of fundamental and modern works in the problem field was carried out. The empirical basis of the work was made up of data from the official website of the Federal Statistics Service with geographic coverage of the entire Russian Federation. Results: Analysis of data from a subjective assessment of the population's health on a national sample of the Russian Federation demonstrates the internal readiness of the population for a value-based healthcare model, despite the negative trends of aging. In the age groups 55-59, 60-64, 65-69, 70-74, 75-79, 80 and older, there is a general trend in assessing their health - the majority of respondents rated it as “satisfactory,” while the number of ratings was “very bad” is minimal. The positive dynamics of the formation of information and technical competence of the population 65+, who are experiencing difficulties in integrating into digital health services, is shown. Conclusion: The transition of national healthcare to a value-based model involves the active involvement of the patient and the formation of patient experience in assessing the outcome of medical care. In this regard, it is necessary to take into account the patient’s personal socio-psychological compliance profile, the elements of which determine the horizons of promising research in the problem field under consideration. As a possible patient profile module, a subjective assessment of health and an assessment of information technology competencies in a social group older than working age, whose work growth is determined by demographic realities, are used.

Modeling the impact of BDA-AI on sustainable innovation ambidexterity and environmental performance

Data has evolved into one of the principal resources for contemporary businesses. Moreover, corporations have undergone digitalization; consequently, their supply chains generate substantial amounts of data. The theoretical framework of this investigation was built on novel concepts like big data analytics—artificial intelligence (BDA-AI) and supply chain ambidexterity’s (SCA) direct impacts on sustainable supply chain management (SSCM) and indirect impacts on sustainable innovation ambidexterity (SIA) and environmental performance (EP). This study selected employees of manufacturing industries as respondents for environmental performance, sustainable supply chain management, big data analytics, artificial intelligence, and supply chain ambidexterity. The results from this study show that BDA-AI and SCA significantly affect SSCM. SSCM has significant associations with SIA and EP. Finally, SIA has a significant impact on EP. According to the results indicating the indirect impacts, BDA-AI has significant indirect relationships with SIA and EP by having SSCM as the mediating variable. Furthermore, SCA has significant indirect associations with SIA and EP, with SSCM as the mediating variable. Additionally, both BDA-AI and SCA have significant indirect associations with EP, while SIA and SSCM are mediating variables. Finally, SSCM has an indirect association with EP while having SIA as a mediating variable. The findings of this paper provide several theoretical contributions to the research in sustainability and big data analytics artificial intelligence field. Furthermore, based on the suggested framework, this study offers a number of practical implications for decision-makers to improve significantly in the supply chain and BDA-AI. For instance, this paper provides significant insight for logistics and supply chain managers, supporting them in implementing BDA-AI solutions to help SSCM and enhance EP.

Advancements in Inflammatory Bowel Disease Management: From Traditional Treatments to Monoclonal Antibodies and Future Drug Delivery Systems.

Inflammatory bowel disease (IBD) is a chronic gastrointestinal inflammatory disorder with two main subtypes: ulcerative colitis (UC) and Crohn's disease (CD). The pathogenesis involves genetic predisposition, dysbiosis, and immune dysregulation. Complications include perianal lesions, strictures, fistulas, perforations, and an increased risk of colon cancer. Clinical classification ranges from mild to fulminant and recurrent disease, with common symptoms such as abdominal discomfort, rectal bleeding, diarrhea, and weight loss. Extraintestinal manifestations include arthritis, erythema nodosum, pyoderma gangrenosum, and uveitis. Conventional treatments using aminosalicylates, corticosteroids, and immunomodulators have limitations. Biologics, introduced in the 1990s, offer improved efficacy and specificity, targeting factors like TNF-α, integrins, and cytokines. Monoclonal antibodies play a crucial role in IBD management, aiming to reduce relapses, hospitalizations, and surgeries. In conclusion, this review is aimed at summarizing the latest knowledge, advantages, and drawbacks of IBD therapies, such as small molecules, biologics, and monoclonal antibodies, to provide a basis for further research in the IBD field.

Long-lived carriers-promoted photocatalytic deuteration of halides with D2O as the deuterium source over Cu doped quantum dots

Deuterium labeling is a highly valuable yet challenging subject of research in various scientific fields. Conventional deuteration methods often involve harsh reaction conditions and suffer from limited reactivity and selectivity. Herein, we report a visible light–driven C–X (X = halogen) to C–D (D = deuterium) exchange strategy over copper-doped cadmium sulfide quantum dots (Cu-CdS QDs) under mild conditions, eliminating the need for noble metal catalysts and expensive deuterium sources. The conversion of aryl halides into deuterated products using Cu-CdS QDs reaches up to 99%, which is four times higher than that achieved using pristine CdS QDs. The substantial enhancement in the photocatalytic activity of the QDs can be primarily attributed to the generation of long-lived charge carriers (approximately 6 μs) induced by Cu doping. Mechanistic studies reveal that the Cu dopants considerably retard the recombination of photoinduced carriers by creating intermediate energy levels that serve as hole trapping centers in CdS QDs, thereby improving the electron utilization efficiency in energetically demanding photoreduction reactions. Additionally, the introduction of Cu increases the energy offset between the conduction band of CdS QDs and molecular acceptors, facilitating the electron transfer process. Upon visible light irradiation, a series of aryl halides can be efficiently converted into the desired deuterated compounds using D2O as the deuterium source. This work demonstrates that regulating charge carrier dynamics in ultrasmall QD-based photocatalysts is a promising strategy for promoting organic transformations.

Obstacles of Qualitative Research in The English Language Field from the Perspective of Its Faculty Members at King Abdul Aziz University (Case Study)

The current study aimed to identify the obstacles that prevent conducting qualitative research in the English Language field at university, as well as the theoretical and philosophical premises of qualitative research. The researcher used the explanatory approach, and used the interview as one of the qualitative research methods. The study found that we need to conduct qualitative research in the English language because of the predominance of quantitative research tools and methods in an explicit omission of qualitative research, despite its importance and suitability for the study of many phenomena and problems in the field of the English language. Philosophical study of the phenomenon is more in depth in the cognitive construction, in addition to its use of a number of means to collect the data of the phenomenon such as observation, interview, document analysis, and knowledge of the social, personal and material circumstances and scenes related to the phenomenon being studied. The study also found that there are many obstacles that prevent conducting qualitative research in the field of education in general and the field of English language in particular. The researcher has developed a set of proposals to overcome the obstacles of qualitative research in the English language field.

Ethical dimensions of generative AI: a cross-domain analysis using machine learning structural topic modeling

Purpose The purpose of this study is to comprehensively examine the ethical implications surrounding generative artificial intelligence (AI). Design/methodology/approach Leveraging a novel methodological approach, the study curates a corpus of 364 documents from Scopus spanning 2022 to 2024. Using the term frequency-inverse document frequency (TF-IDF) and structural topic modeling (STM), it quantitatively dissects the thematic essence of the ethical discourse in generative AI across diverse domains, including education, healthcare, businesses and scientific research. Findings The results reveal a diverse range of ethical concerns across various sectors impacted by generative AI. In academia, the primary focus is on issues of authenticity and intellectual property, highlighting the challenges of AI-generated content in maintaining academic integrity. In the healthcare sector, the emphasis shifts to the ethical implications of AI in medical decision-making and patient privacy, reflecting concerns about the reliability and security of AI-generated medical advice. The study also uncovers significant ethical discussions in educational and financial settings, demonstrating the broad impact of generative AI on societal and professional practices. Research limitations/implications This study provides a foundation for crafting targeted ethical guidelines and regulations for generative AI, informed by a systematic analysis using STM. It highlights the need for dynamic governance and continual monitoring of AI’s evolving ethical landscape, offering a model for future research and policymaking in diverse fields. Originality/value The study introduces a unique methodological combination of TF-IDF and STM to analyze a large academic corpus, offering new insights into the ethical implications of generative AI across multiple domains.

Establishment of LC-MS/MS Methodology for the Determination of Rapamycin Concentration in Rat Whole Blood.

The establishment and validation of methods for testing biological samples are crucial steps in pharmacokinetic studies. Currently, several methodological reports have been published on the detection of rapamycin plasma concentrations. The objective of this study was to explore an effective method for detecting rapamycin in rat whole blood biological samples. In this study, we designed a rapid, sensitive, and specific liquid chromatograph-mass spectrometer/mass spectrometer (LC-MS/MS) methodology for detecting rapamycin in rat whole blood biological samples. We comprehensively validated the specificity, linear range, lower limit of quantification (LLOQ), precision, accuracy, recovery, and stability of this method. The findings of this study confirmed the successful implementation of LC-MS/MS for the detection of rapamycin, demonstrating its sensitivity, specificity, and reliability in quantitative analysis. This method ensures the accuracy and reliability of subsequent study data through our validated LC-MS/MS approach. The results demonstrated the successful implementation of an LC-MS/MS method for sensitive, specific, and reliable quantitative analysis of rapamycin in rat whole blood samples. This method ensures the accuracy and reliability of subsequent study data. The importance of this study lies in the successful establishment of a rapid, sensitive, and specific LC-MS/MS method for detecting rapamycin concentration in rat whole blood, ensuring the accuracy and reliability of subsequent research data. This provides a crucial tool and foundation for further understanding the metabolism and pharmacological effects of rapamycin in vivo, aiding in the advancement of drug research and clinical applications in related fields.

Assessing Seed Treatments to Control Sudden Death Syndrome Caused by Fusarium virguliforme and Seedling and Root Disease Caused by Rhizoctonia sp. on Mungbean (Vigna radiata)

There is growing interest in producing mungbean ( Vigna radiata L. Wilczek) in the United States, which is driven by increased consumer demand. Strategies are needed for United States farmers to take advantage of this high-value crop and its environmental sustainability. Recommendations for the management of mungbean seedling and root diseases are lacking. Preliminary research in central Iowa mungbean fields from 2019 to 2023 has shown that mungbean is particularly vulnerable to Fusarium virguliforme, the cause of soybean sudden death syndrome (SDS), and Rhizoctonia sp., the cause of damping-off, root decay, premature defoliation, and pod abortion. The purpose of this study was to screen a variety of fungicides as a seed treatment or a soil band application to control root rot in mungbean. We performed three field studies over 2 years using mungbean cultivars Berken and OK2000. Seed treatments Evergol Energy + fluopyram and Evergol Energy + pydiflumetofen showed the highest performance ( P < 0.05), with approximately 30% more healthy roots than nontreated controls. Other treatments exhibited about 20% more healthy roots than the nontreated control. Biotam in-furrow application showed the highest plant population for ‘OK2000’, but we observed no treatment differences in plant stand for ‘Berken’.

Resiliencia educativa en el pensamiento crítico de estudiantes de contabilidad de una universidad privada de Lima-Metropolitana

The objective of the research was to determine the incidence of educational resilience in the critical thinking of accounting students from a private university in Lima-Metropolitana, 2023. The methodology was quantitative, non-experimental cross-sectional research design, a questionnaire was administered to 100 accounting students from a private university through the survey, allowing information to be collected on the variables under study. The results showed that as educational resilience increases, critical thinking tends to improve, suggesting a positive association between these two variables. The findings support the idea that strengthening resilience in the educational field could be an effective strategy to enhance critical thinking skills in students. Along these lines, it was concluded that the research provides a valuable perspective that not only enriches our understanding of the study in question, but also opens new doors for additional research in the educational field, promoting the comprehensive development of students.

Revolutionizing the Digital Creative Industries: The Role of Artificial Intelligence in Integration, Development, and Innovation

Purpose - Artificial intelligence is profoundly transforming the digital creative industry, becoming a key force in industrial upgrading through technology integration, innovation drive and productivity improvement. Methods- This study uses a variety of methods, including literature review, questionnaire survey, in-depth interview and data analysis, to systematically examine the application effect of AI in the digital creative industry. The structural equation model is used to verify the hypothesized relationship, and the role of AI in promoting industrial integration, development results and innovation catalysis effect are comprehensively analyzed. Research results- The research that AI importantly promotes technological integration, development and innovation inside the digital creative industry, and improves the general overall performance of the industry. The path coefficient is incredibly substantial, and the model fit is good, which verifies the effective position of AI in industrial integration and development. The position of AI not only improves the competitiveness of the industry, but also provides robust support for the personalization and excessive quality of creative products. Originality- This paper demonstrates remarkable originality in theoretical framework construction, empirical data analysis, and exploration of practical challenges and this paper deeply analyzes the multiple mechanisms of AI in the digital creative industry, providing new ideas and specific quantitative evidence for research in related fields. Implications - Practitioners need to actively accept AI era, optimize creative workflows, and enhance production efficiency and constantly enhance their digital talents and cross-area information integration capabilities. Policymakers should formulate focused support policies to promote the vast application and deep integration of AI technologies inside the creative industries.

Survey on Optical Wireless Communication with Intelligent Reflecting Surfaces

Optical Wireless Communication (OWC) technology has gained significant attention in recent years due to its potential for providing high-data-rate wireless connections through the large license-free bandwidth available. A key challenge in OWC systems, similar to high-frequency Radiofrequency (RF) systems, is the presence of dead zones caused by obstacles like buildings, trees, and moving individuals, which can degrade signal quality or disrupt data transmission. Traditionally, relays have been used to mitigate these issues. Intelligent Reflecting Surfaces (IRSs) have recently emerged as a promising solution, enhancing system performance and flexibility by providing reconfigurable communication channels. This paper presents an overview of the application of IRSs in OWC systems. Specifically, we categorize IRSs into two main types: mirror array-based IRSs and metasurface-based IRSs. Furthermore, we delve into modeling approaches of mirror array-based IRSs in OWC and analyze recent advances in IRS control, which are classified into system power or gain optimization-oriented, system link reliability optimization-oriented, system data rate optimization-oriented, system security optimization-oriented, and system energy optimization-oriented approaches. Moreover, we present the principles of metasurface-based IRSs from a physical mechanism perspective, highlighting their application in OWC systems through the distinct roles of light signal refraction and reflection. Finally, we discuss the key challenges and potential future directions for integrating IRS with OWC systems, providing insights for further research in this promising field.

Effect of fluid flow behavior on sustainability and exergy efficiency of solar heat collectors having multiple V‐ribs with gaps

AbstractIn the current numerical study, the viability and sustainability of a solar heat collector (SHC) have been rigorously analyzed through the lens of exergy analysis. The SHC with roughness in the form of symmetrical V‐rib gaps has been selected for detailed numerical investigation. The study focuses on deriving the dominant parameters affecting the performance of the SHC, including the relative gap width (), number of gaps () in the limbs of ribs, and fluid flow Reynolds number, which varied from 4000 to 18,000. The absorber plate with roughness was thoroughly examined to evaluate the losses and irreversibility that persist in the thermal system. The results of the numerical analysis revealed the maximum exergy efficiency to be 3.87%. Furthermore, the study examined the long‐term feasibility of the system, evaluating its sustainability index at a remarkable 1.0319 value, while the magnitude of the waste–energy ratio fetched an impressive score of 0.991. Additionally, the study found that the system has a significant improvement potential of 10.04. Overall, these findings provide critical insights into the performance and sustainability of SHCs, paving the way for future research and development in this crucial field.

Graph neural network based intelligent tutoring system: A survey

Online education is developing rapidly driven by artificial intelligence technology. The massive learning resources lead to information overload and low resource utilization. Intelligent tutoring system (ITS) plays a vital role in the education platform, providing personalized learning services for students. The data obtained from the online education platform has complex correlations, which can be potentially transformed into multi-level graph structures. In recent years, graph neural networks (GNNs) have been tried to be introduced into intelligent learning services due to their superior performance in processing graph-structured data. This paper aims to provide researchers and engineers with a general overview of modeling processes and techniques for intelligent learning services based on GNNs. Through a careful review of the advanced models published between 2019 and 2023, existing research primarily focuses on four detailed areas within the smart services scenario. The GNN models involved are systematically classified, and the principles, pioneers and variants of various models are summarized in detail. Simultaneously, this paper analyzes the applications, the specific problems to be solved, and the technologies and innovations of graph-based models in the four key areas. In addition, we examine the commonly used datasets and evaluation metrics in the field of education. Finally, the current challenges and future development trends are summarized to provide comprehensive and in-depth guidance for research in related fields.

An Aesthetic Morphology Approach of Visual Identity on Dong’s Ethnic Costume

The Dong ethnic minority is one of the representative ethnic minorities in China, The Dong ethnic minority has their own unique traditional clothing, The Dongs’ clothing had a long history, they were made by hand by each Dong family throughout the entire process from planting, spinning, weaving, dyeing, sewing and embroidering and decorating. It plays an important role in the life of Dong people, especially in special occasions such as festivals. The Dongs’ clothing had been included in the fourth batch of representative items of national intangible cultural heritage in China. The purpose of this study is to investigate the Dong ethnic minority and Visual identity in Clothing. Symbolic interactionism was the Theoretical basis of this study. The study was a qualitative study that was descriptive and historical in nature. The results were written in a literary/text format. Data were gathered through inspecte of clothing, photos and video records from the library, museum and interviews. Using aesthetic morphological methods to study the components of the design elements of their clothing, A comprehensive interpretation of the role of costume in expressing and symbolising, defining and shaping identity is presented. The findings concluded that the form and style of clothing worn by the Dong people reflect their visual identity and aesthetics. It is hoped that this study will provide an important reference for future research in related fields.

Exploring the Intersection of E-commerce and Healthcare: A Visual Analysis of Research Trends.

The role of e-commercein healthcare is one of the key research areas emerging from the broader digital transformation of health services and consumer interactions. This study presents the bibliometric analysis of literature on e-commerce in healthcare based on publications from1993 to 2024 in Scopus. In particular, this analysis shows trends in the publication record that have been constantly growing, with prominent increases during the COVID-19 pandemic, now hardwiring the fact that digital technologies are key in promoting global health. The study surveys the thematic evolution of key technologies such as artificial intelligence (AI), which is transforming predictive healthcare analytics; blockchain, which is enhancing security in health data transactions; and telemedicine, which is revolutionizing remote patient care, alongside other emerging technologies that are reshaping global healthcare systems. The research also showcases global collaboration patterns, underlining the international dimensions of scholarly contributions to the area under review. These insights provide a foundation for understanding the current state of e-commerce in healthcare and suggest future directions for research and policy development in this fast-evolving field.

Becoming crisis‐ready: A systematic literature review on corporate crisis readiness and the process to achieving it

AbstractAs global crises become increasingly complex and intertwined, crisis readiness has emerged as a pivotal factor for an organisation's survival. Despite a growing, interdisciplinary corpus of research underscoring the necessity for systematic crisis management and strategic communication, a comprehensive understanding of corporate crisis readiness and methodologies for its achievement remain elusive and inadequately addressed. To bridge this knowledge gap, we conducted a systematic literature review, meticulously analysing 7287 articles to identify 40 eligible studies from 1987 to 2022. Through inductive content analysis and narrative synthesis, we have delineated the concept of crisis readiness and devised a comprehensive 10‐step process framework that organisations are advised to implement in preparation for potential crises. This investigation enriches the academic dialogue on crisis readiness by integrating insights from strategic management, crisis handling, organisational development, and learning theories. This offers a more nuanced understanding of how organisations can equip themselves for crisis situations. Additionally, our study sheds light on promising directions for future research in this vital field.

Chebyshev spectral Newton iterative analysis on unsteady oblique stagnation flow of Maxwell fluids over an oscillating-rotating disk with Cattaneo–Christov double diffusion

Oblique stagnation flow on a rotating disk is commonly observed in processes such as spinning coating and thin film deposition techniques. The investigation of the unsteady oblique stagnation point flow for Maxwell fluid over an oscillating-rotating disk embedded in a porous medium is meticulously conducted by employing the Darcy–Maxwell framework in conjunction with Cattaneo–Christov double diffusion model. A transformation of similarity is applied to reframe the governing equations into a system of non-dimensional coupled partial differential equations, whose numerical solutions are secured by the Chebyshev Spectral Newton Iterative Scheme. The outcomes underscore that an escalation in the Darcy parameter escalates the resistance within the porous medium, consequently leading to a reduction in velocity. Both the first-order slip and the second-order slip mitigate the fluid's interaction with the disk wall, leading to a retardation in flow velocity. Additionally, the presence of augmented thermal radiation parameters is observed to enhance heat transfer efficiency, resulting in a more homogenized temperature distribution. The two-dimensional and three-dimensional streamlines provide a precise depiction of the flow characteristics at the oblique stagnation point on the oscillating-rotating disk. These findings offer a theoretical foundation that can be instrumental for forthcoming research in analogous fields.