Future Trajectories Research Articles

Ultra-Fast BNN Analysis with the upgraded FINN Framework: Harnessing GoogLeNet and Contemporary Transfer Methods for deploying algorithms on NVidia GPU

By combining Binarized Neural Networks (BNNs) with the updated FINN framework and utilizing GoogLeNet with sophisticated transfer learning on Nvidia GPUs, this research presents a novel method for object detection. The goal is to decrease processing time and increase detection precision. TensorFlow optimization allows BNN architectures to balance efficiency and accuracy. Pretrained CNNs use supervised learning specific to each dataset and model architecture to handle a variety of datasets, including MNIST, CIFAR, and SVHN. Fast processing is made possible by the Nvidia Jetson Nano GPU, particularly in dynamic environments like automobile fault detection. Transfer learning adaptation of GoogLeNet's last layer achieves 93% accuracy for chairs, 94% accuracy for people, and 96% accuracy for mouse recognition, which is higher than standalone accuracy. Testing times as low as 4 seconds are possible with the combined technique, which reaches 18 FPS processing speed. This study establishes a new standard for neural network deployments by demonstrating the synergy between sophisticated neural network models, traditional topologies, and transfer learning inside the FINN framework. The Nvidia Jetson Nano GPU is essential for accelerating calculations, meeting both accuracy and speed objectives. In conclusion, this work highlights technological advancements in computer vision and plots future exploration trajectories by combining deep learning, GoogLeNet's strengths, transfer learning, and the FINN framework to promote neural network deployments in real-time applications.

Digital transformation in finance: A review of current research and future directions in FinTech

The finance sector's digital metamorphosis, catalyzed by the rise of Financial Technology (FinTech), has profoundly reshaped the financial services landscape. This manuscript embarks on a thorough exploration of contemporary research surrounding digital transformation in finance, with a keen eye on FinTech's trajectory. Commencing with an intricate dissection of the conceptual framework and evolutionary journey of FinTech, the manuscript plunges into the labyrinthine expanse of existing literature, spotlighting pivotal themes, dynamic trends, and empirical revelations. Furthermore, it navigates through the labyrinth of challenges and opportunities inherent in FinTech research, including the labyrinthine realms of regulatory compliance, the intricate tapestry of security concerns, and the ever-evolving vistas of technological advancements. By meticulously pinpointing research lacunae, the manuscript sets forth a constellation of future research trajectories aimed at deepening our comprehension of digital metamorphosis in finance. These trajectories encompass traversing interdisciplinary bridges, navigating through the enigmatic corridors of emerging trends such as blockchain and artificial intelligence, and grappling with the ethical and societal implications that loom large. Ultimately, this manuscript adds a kaleidoscopic dimension to the ongoing discourse on FinTech, offering a multifaceted prism of insights into current research trends while charting a course for future research odysseys.

Learning From Evaluation Data: Discoveries From the Inaugural Evaluation Capacity Case Challenge

Evaluation competitions, a process that has existed for more than three decades, are a mechanism to promote program evaluation and enhance evaluation capacity. Integrating these competitions into evaluation education extends traditional teaching models beyond theory-dense learning contexts. This practice note delves into the Evaluation Case Competition Challenge (EC3), a case challenge designed to advance knowledge on evaluation capacity building (ECB). Insights from an end-of-experience survey are distilled into three discoveries: successful elements of the multifaceted competition structure and exploring the case challenge as a valuable opportunity for ECB, as well as a focus on student celebrations and suggestions. These discoveries provide insight into the learner experiences and recommendations for the future trajectory of EC3. Five guiding principles for envisioning evaluation learning competitions are offered for consideration.

The Future of Fashion Retail: Virtual Experiences and E-Commerce Integration

This innovative research integrates methodologies from two distinct studies to advance our comprehension of immersive virtual experiences within the realms of fashion and e-commerce. By amalgamating insights from both methodologies, this refined approach introduces novel components, including a virtual shopping environment, post-VR shopping behavior analysis, biometric data collection, extended interviews, longitudinal study design, and control group implementation. Participants engaged in 360-degree VR fashion shows and virtual shopping experiences using the Oculus Quest 2, while their physiological responses were meticulously monitored. Following the VR encounters, participants navigated a virtual store, and their subsequent shopping behavior was methodically tracked. Extended interviews delved into enduring effects, while a longitudinal study examined the evolution of attitudes over a three-month period. The inclusion of a control group ensured the robustness of causal inferences. This sophisticated methodology promises a comprehensive exploration of the intricate interplay between immersive virtual encounters and consumer behaviors, providing nuanced insights into the evolving landscape of virtual consumption. By embracing cutting-edge elements such as biometric data and virtual shopping environments, this research aims to unravel the multifaceted effects of immersive virtual experiences, contributing to a deeper understanding of consumer interactions with virtual environments and shaping the future trajectory of fashion and e-commerce.

Navigating the metaverse: A technical review of emerging virtual worlds

AbstractThe metaverse, a burgeoning virtual reality realm, has garnered substantial attention owing to its multifaceted applications. Rapid advancements and widespread acceptance of metaverse technologies have birthed a dynamic and intricate digital landscape. As various platforms, virtual worlds, and social networks within the metaverse increase, there is a growing imperative for a comprehensive analysis of its implications across societal, technological, and business dimensions. Notably, existing review studies have, for the past decade, primarily overlooked a metaverse‐based multidomain approach. A meticulous examination encompassing 207 research studies delves into the technological innovation of the metaverse, elucidating its future trajectory and ethical imperatives. Additionally, the article introduces the term “MetaWarria” to conceptualize potential conflicts arising from metaverse dynamics. The study discerns that healthcare (45%) and education (22%) are pivotal sectors steering metaverse developments, while the entertainment sector (9%) reshapes the corporate landscape. Artificial intelligence (AI) plays a 9% role in enhancing the metaverse's marketing and user experience. Security, privacy, and policy concerns (11%) are addressed due to escalating threats, yielding practical solutions. The analysis underscores the metaverse's profound influence (57%) on the digital realm, a phenomenon accelerated by the COVID‐19 pandemic. The article culminates in contemplating the metaverse's role in future warfare and national security, introducing “MetaWarria” as a conceptual framework for such discussions.This article is categorized under: Application Areas > Health Care Application Areas > Science and Technology Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction

Revolutionizing America's Cloud Computing the Pivotal Role of AI in Driving Innovation and Security

Cloud computing represents a transformative approach to delivering IT services via an interconnected network of servers, collectively referred to as the "Cloud." This virtualized environment seamlessly integrates networks, servers, applications, storage, and services, facilitating convenient access for users with minimal administrative overhead. This comprehensive review article centers on two fundamental pillars of cloud computing: virtualization and containerization. It examines their groundbreaking influence on resource management and deployment efficiency. Additionally, the paper explores upcoming trends and challenges expected to shape the cloud computing landscape from 2025 to 2030.An emphasis is placed on the anticipated adoption of hybrid and multi-cloud strategies, providing organizations with tailored solutions while reducing the risks associated with vendor lock-in. The emergence of edge computing is highlighted as a key solution to address latency concerns and foster a competitive environment for the Internet of Things (IoT). Furthermore, the integration of artificial intelligence (AI) and machine learning within cloud frameworks is poised to unlock new avenues of innovation and optimization, propelling digital transformation. The article underscores the critical need for enhanced security measures to protect sensitive data and ensure user privacy. Ongoing price competitions among cloud providers and heightened regulatory scrutiny are also examined, underscoring the dynamic nature of cloud computing. By offering insights into the past, present, and future trajectory of cloud computing, this article affirms its pivotal role in driving digital innovation and empowering organizations to thrive in an interconnected world. In conclusion, the article provides recommendations for businesses to leverage emerging technologies and effectively navigate evolving challenges in the realm of cloud computing.

Revolutionizing America's Cloud Computing the Pivotal Role of AI in Driving Innovation and Security

Cloud computing represents a transformative approach to delivering IT services via an interconnected network of servers, collectively referred to as the "Cloud." This virtualized environment seamlessly integrates networks, servers, applications, storage, and services, facilitating convenient access for users with minimal administrative overhead. This comprehensive review article centers on two fundamental pillars of cloud computing: virtualization and containerization. It examines their groundbreaking influence on resource management and deployment efficiency. Additionally, the paper explores upcoming trends and challenges expected to shape the cloud computing landscape from 2025 to 2030.An emphasis is placed on the anticipated adoption of hybrid and multi-cloud strategies, providing organizations with tailored solutions while reducing the risks associated with vendorlock-in. The emergence of edge computing is highlighted as a key solution to address latency concerns and foster a competitive environment for the Internet of Things (IoT). Furthermore, the integration of artificial intelligence (AI) and machine learning within cloud frameworks is poised to unlock new avenues of innovation and optimization, propelling digital transformation. The article underscores the critical need for enhanced security measures to protect sensitive data and ensure user privacy. Ongoingprice competitions among cloud providers and heightened regulatory scrutiny are also examined, underscoring the dynamic nature of cloud computing. By offering insights into the past, present, and future trajectory of cloud computing, this article affirms its pivotal role in driving digital innovation and empowering organizations to thrive in an interconnected world. Inconclusion, the article provides recommendations for businesses to leverage emerging technologies and effectively navigate evolving challenges in the realm of cloud computing.

A Descriptive-Predictive–Prescriptive Framework for the Social-Media–Cryptocurrencies Relationship

The research presented in this paper is the first to introduce a thorough Descriptive-Predictive–Prescriptive (DPP) Framework for comprehending the interaction between social media and cryptocurrencies. Recognizing the underexplored domain of the social-media–cryptocurrency interaction, we delve into its many aspects, better understanding present dynamics, forecasting potential future trajectories, and prescribing best solutions for stakeholders. We evaluate social media speech and behavior connected to cryptocurrencies using big data analytics, translating raw data into meaningful insights using Natural Language Processing (NLP) techniques like sentiment analysis. When applied to an experimental dataset, the DPP nets superior results compared to the baseline approach, displaying an improvement of 3.44% of the Root Mean Square Error (RMSE) metric and 4.59% of the Mean Absolute Error (MAE) metric. The unique DPP framework enables a more in-depth assessment of social media’s influence on cryptocurrency trends, and lays the path for strategic decision-making in this nascent but rapidly developing field of study.

VesNet: A Vessel Network for Jointly Learning Route Pattern and Future Trajectory

Vessel trajectory prediction is the key to maritime applications such as traffic surveillance, collision avoidance, anomaly detection, and so on. Making predictions more precisely requires a better understanding of the moving trend for a particular vessel since the movement is affected by multiple factors like marine environment, vessel type, and vessel behavior. In this paper, we propose a model named VesNet, based on the attentional seq2seq framework, to predict vessel future movement sequence by observing the current trajectory. Firstly, we extract the route patterns from the raw AIS data during preprocessing. Then, we design a multi-task learning structure to learn how to implement route pattern classification and vessel trajectory prediction simultaneously. By comparing with representative baseline models, we find that our VesNet has the best performance in terms of long-term prediction precision. Additionally, VesNet can recognize the route pattern by capturing the implicit moving characteristics. The experimental results prove that the proposed multi-task learning assists the vessel trajectory prediction mission.

The Prospects and Challenges of Artificial Intelligence Technology in Archival Management

The evolution of information technology prompts inquiry into AI's role in archival management, emphasizing future trajectories, technological advancements, and challenges. AI promises intelligent, automated, and personalized archive management, enhancing efficiency and service quality. Potential innovations include learning-based categorization and natural language summarization, offering advanced user services. Challenges like data privacy and human-machine interaction balance also offer developmental opportunities. This discourse stresses collaborative efforts to sustainably integrate AI in archival management, fostering digitalization and intelligence transformation.

Can we project well-being? Towards integral well-being projections in climate models and beyond

Scientists have proposed many “Beyond-GDP” indicators to replace the Gross Domestic Product (GDP) in order to quantify genuine societal development. While GDP is regularly projected, research on future trajectories of Beyond-GDP indicators is lacking, failing to meet policymakers’ needs. Focusing on the Human Development Index (HDI), this paper attempts to calculate one of the first global well-being projections for 161 countries by 2100 using the shared socioeconomic pathways (SSPs), the socioeconomic inputs underlying global climate change scenarios. The results indicate a potential global well-being improvement from medium to very high level, depending on the SSPs, with most countries reaching high human development under SSPs 1&5. While serving as an initial step in well-being projection, the results highlight a crucial gap in existing climate change models which are used by the IPCC—they inadequately account for the feedback effects of climate change on well-being. This oversight results in counterintuitive or potentially misleading well-being projections. Therefore, we propose steps to improve this situation. By synthesizing climate change feedback effects on HDI determinants, this assessment delves into their implications for well-being and further underscores the necessity for interdisciplinary collaborations among well-being researchers, climate scientists and policy modelers to achieve sound integral well-being projections.

Future HIV epidemic trajectories in South Africa and projected long-term consequences of reductions in general population HIV testing: a mathematical modelling study

After successful intensive interventions to rapidly increase HIV awareness, coverage of antiretroviral therapy (ART), and viral suppression, HIV programmes in eastern and southern Africa are considering scaling back of some interventions, such as widespread general population HIV testing. We aimed to model whether scaling back of general population HIV testing in South Africa could result in a resurgence of the HIV epidemic or substantial slowing of declines in HIV incidence, resulting in increased long-term ART. In this modelling study, we used the Thembisa 4.5 model (a deterministic compartmental model of HIV transmission in South Africa) to project the South African HIV epidemic to 2100 assuming the continuation of 2022 epidemiological conditions and HIV programme implementation. We assessed how implementing reductions in general population HIV testing services in 2025 (while maintaining antenatal, symptom-based, and risk-based testing modalities and other HIV prevention services at 2022 levels) would affect HIV incidence and prevalence among people aged 15-49 years, the year in which incidence would reach one per 1000 people aged 15-49 years (the threshold for virtual elimination of HIV), and associated costs, as well as numbers of additional new HIV infections and AIDS-related deaths. We also modelled the effects of delaying reductions in general population testing services by 5-year increments. Additionally, we modelled the potential effects of reductions in general population testing services in combination with increases or decreases in ART interruption rates (ie, the annual rate at which people who are on ART discontinue ART) and condom usage in 2025-35. If general population HIV testing services and the HIV risk environment of 2022 were maintained, we projected that HIV incidence would steadily decline from 4·95 (95% CI 4·40-5·34) per 1000 population in 2025 to 0·14 (0·05-0·31) per 1000 in 2100, and that the so-called virtual elimination threshold of less than one new infection per 1000 population per year would be reached in 2055 (95% CI 2051-2060). Scaling back of general population HIV testing services by 25%, 50%, or 75% in 2025 delayed time to reaching the virtual elimination threshold by 5, 13, or 35 years, respectively, whereas complete cessation of general population testing would result in the threshold not being attained by 2100. Although the incidence of HIV continued to fall when general HIV testing services were reduced, our modelling suggested that, with reductions of between 25% and 100%, between 396 000 (95% CI 299 000-474 000) and 2·50 million (1·97 million-2·98 million) additional HIV infections and between 115 000 (94 000-135 000) and 795 000 (670 000-926 000) additional AIDS-related deaths would occur between 2025 and 2075, depending on the extent of reduction in testing. Delaying reductions in general population HIV testing services for 5-25 years mitigated some of these effects. HIV testing accounted for only 5% of total programmatic costs at baseline; reducing testing moderately reduced short-term total annual costs, but increased annual costs after 25 years. Increases in ART interruption and reductions in condom usage were projected to slow the decline in incidence and increase the coverage of general HIV testing services required to control transmission but did not cause rapid resurgence in HIV infections. Our modelling suggests that scaling back of general population HIV testing would not result in a resurgence of HIV infections, but would delay attainment of incidence-reduction targets and result in long-term increases in HIV infections, AIDS-related deaths, and costs (via increased need for ART provision). HIV programmes need to balance short-term potential resource savings with long-term epidemic control objectives. Bill & Melinda Gates Foundation.

ChatGPT’s applications in marketing: a topic modeling approach

PurposeChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing realm. To address this gap, the current study explores ChatGPT’s application in marketing by mining social media data. Additionally, the study employs the stages-of- growth model to assess the current state of ChatGPT’s adoption in marketing organizations.Design/methodology/approachThe study collected tweets related to ChatGPT and marketing using a web-scraping technique (N = 23,757). A topic model was trained on the tweet corpus using latent Dirichlet allocation to delineate ChatGPT’s major areas of applications in marketing.FindingsThe topic model produced seven latent topics that encapsulated ChatGPT’s major areas of applications in marketing including content marketing, digital marketing, search engine optimization, customer strategy, B2B marketing and prompt engineering. Further analyses reveal the popularity of and interest in these topics among marketing practitioners.Originality/valueThe findings contribute to the literature by offering empirical evidence of ChatGPT’s applications in marketing. They demonstrate the core use cases of ChatGPT in marketing. Further, the study applies the stages-of-growth model to situate ChatGPT’s current state of adoption in marketing organizations and anticipate its future trajectory.

Revolutionizing Power Systems Through Electrical Automation: Efficiency, Reliability, and Sustainability

This paper explores the transformative role of electrical automation technologies in the modernization and optimization of power systems. With a comprehensive analysis spanning power generation, distribution, and grid management, we delineate the multifaceted impacts of automation on enhancing operational efficiency, ensuring reliability, and promoting environmental sustainability. Through the lens of operational case studies and theoretical frameworks, we identify key insights into how electrical automation contributes to the streamlining of processes, reduction of human error, and integration of renewable energy sources. Moreover, we delve into the future trajectory of electrical automation, highlighting the potential integration of Artificial Intelligence (AI) and Machine Learning (ML) algorithms, the expansion of smart grid capabilities, and the paramount importance of cybersecurity in the digital era of power systems. Our discussion synthesizes these perspectives to underscore the pivotal role of electrical automation in driving the evolution of power systems towards greater adaptability, efficiency, and resilience. This paper posits that the future of power systems hinges on the strategic implementation of advanced automation technologies, guided by an overarching commitment to innovation, security, and sustainability.

Exploring ChatGPT for next-generation information retrieval: Opportunities and challenges

The rapid advancement of artificial intelligence (AI) has spotlighted ChatGPT as a key technology in the realm of information retrieval (IR). Unlike its predecessors, it offers notable advantages that have captured the interest of both industry and academia. While some consider ChatGPT to be a revolutionary innovation, others believe its success stems from smart product and market strategy integration. The advent of ChatGPT and GPT-4 has ushered in a new era of Generative AI, producing content that diverges from training examples, and surpassing the capabilities of OpenAI’s previous GPT-3 model. In contrast to the established supervised learning approach in IR tasks, ChatGPT challenges traditional paradigms, introducing fresh challenges and opportunities in text quality assurance, model bias, and efficiency. This paper aims to explore the influence of ChatGPT on IR tasks, providing insights into its potential future trajectory.

Applications of Two-Dimensional Organic Materials in the Field of Optoelectronics

This article looks into the quickly advancing landscape of two-dimensional organic products and their transformative function in optoelectronics, driven by developments in nanotechnology and chemistry. At the leading edge of this exploration are three essential materials: Graphene and its analogs, conjugated polymer nanosheets, and fullerene derivatives. Each of these materials presents unique characteristics and difficulties, offering a complex view of the potential and difficulties in this innovative domain name. Graphene and its analogs, renowned for their outstanding electric conductivity and mechanical stamina, stand as pillars in the advancement of sophisticated optoelectronic devices. Conjugated polymer nanosheets, with their flexible properties and tunable electronic characteristics, open new avenues for wearable technology and flexible displays. Fullerene derivatives, understood for their electronic flexibility, are key to creating high-efficiency solar batteries and sensing units. This extensive evaluation browses with the elaborate procedure of synthesizing these materials, emphasizing the synthesis obstacles while highlighting the techniques that have actually shown promise in conquering these barriers. The research study likewise forecasts the capacity of these materials in ushering in a brand-new period of optoelectronic devices, identified by boosted effectiveness, lowered environmental impact, and more comprehensive application scope, consisting of in renewable resource and wise innovation. In synthesizing these understandings, the research aims to offer a much deeper understanding of the current state and future trajectory of two-dimensional organic materials in optoelectronics. It emphasizes the vital of interdisciplinary collaboration in material science, engineering, and industry to utilize these innovations for useful applications, thereby forming the future landscape of modern technology and sustainability.

Microfluidics for High Throughput Screening of Biological Agents and Therapeutics

AbstractMicrofluidic devices have been widely used for gene analysis, immunoassays, organ-on-chip technology, cell engineering, and disease modeling. Their integration into high throughput screening (HTS) platforms has led to large-scale testing of various biological and chemical agents. This brief review discusses existing microfluidic HTS modalities, including the droplet mode, the perfusion mode, and the array-based platforms in active or passive designs, by exploring their fabrication methods and key design features. The main compartments are discussed, and the future trajectories of microfluidic HTS platforms, particularly in drug screening, are explained in detail. This review aims to serve as a guide for bioengineers and clinicians, offering insights to advance the development of the microfluidic toolboxes utilized in drug screening efforts.

Advances in the production of biosurfactants as green ingredients in home and personal care products.

Home and personal care industry is currently witnessing a growing demand for sustainable and eco-friendly alternatives to synthetic surfactants. This increase is fueled by concerns over the delayed degradation and environmental impact of the latter. To this, biosurfactants possess important properties such as biodegradability, low toxicity, and renewable sourcing. These qualities position them as compelling replacements of traditional synthetic surfactants. Their diverse attributes including emulsification, antimicrobial efficacy, surface tension reduction, and foaming capability, make them well-suited choices for home and personal care products. Biosurfactants can be produced through several inexpensive and renewable sources which contributes to their commercialization potential. This article discusses various microbial derived biosurfactants including rhamnolipids, sophorolipids, mannosyl-erythritol lipids, trehalolipids and lipopeptides, unraveling and comparing their distinctive roles and advantages in the home and personal care industry. It also focuses on the recent patent innovations in the production of biosurfactants which have aimed at improving their economic viability and performance attributes. Finally, the article sheds light on the challenges and future trajectories for better integration of these sustainable biosurfactants into mainstream consumer products.

Systematic Review of Socially Sustainable and Community Regeneration: Research Traits, Focal Points, and Future Trajectories

Accelerated urbanization has led to regional disruptions and exacerbated imbalances in spatial quality, social cohesion, and inequalities. Urban regeneration, as a mitigating strategy for these disruptions, faces significant social challenges, particularly at the community scale. This study addresses the existing research gap by comprehensively reviewing community regeneration (CR) from a socially sustainable perspective (SSP). Utilizing VOSviewer software, we synthesize and categorize relevant research trends and methods spanning from 2006 to 2023, retrieving 213 coded articles among 5002 relevant documents from Web of Science bibliometric datasets. The study explores the implementation trajectory of CR, considering novel scenario demands, emerging technologies, and new development paradigms and approaches. It delves into human-centric approaches to enhance the quality of life, precision, and diversification of community engagement and cultivate a sense of community equity and belonging. Moreover, the findings highlight densification as a synergistic and adaptive strategy for current regeneration actions. This scientometric review leverages new tools and innovative approaches for regeneration policy and planning decision-making, ultimately contributing to the improvement of livability. The study provides valuable insights into the challenges and opportunities associated with socially sustainable CR, offering a foundation for future research, and guiding practical urban planning and design interventions.

"Ripping Off the Band-Aid": uncovering future health care Professionals' "Fractured Knowledge" about sexual and reproductive health.

Research has shown the role of identity on future health professionals' confidence and competence in addressing the sexual and reproductive health (SRH) needs of their patients. While there has been some work in increasing the sexual health literacy of future providers via various curricular approaches and comprehensive clinical-based training, there are research gaps on how social differences around identity impact future healthcare professionals' knowledge and practices around SRH. This article presents research findings on the experiences of US undergraduate students attending a campus that provides training in the health sciences and health professions. Our study aims to understand the perspectives of these students as they pertain to their future career choices in healthcare, with a focus on how their past experiences learning about sex, sexuality, and reproduction impact their current and future professional trajectories. We present a qualitative analysis from 40 in-depth interviews with U.S. undergraduates. The interview questions were designed in collaboration with undergraduate researchers interested in sexual health education. These student researchers collected all the interview data and worked with senior researchers to analyze some of these data. The themes that emerged from the interviews were around experiences with what students perceived as "fractured" sexual and reproductive health (SRH) knowledge they received as children and adolescents. This knowledge shaped essential aspects of their identity as young adults and future healers. Data indicated unique processes implicated in how past as well as present socialization experiences learning about sex, sexuality, and reproduction positions undergraduates in health professions to see young adulthood as a journey of "catching up" on sexual knowledge but also as an ongoing experience of anticipation and planning influencing their career-building journey. The importance of sexual health literacy among healthcare professionals cannot be overstated, as it is vital in providing patient-centered and non-judgmental sexual and reproductive health (SRH) care and services. To date, there is a shortage of studies looking at the impact of sexual health knowledge on healthcare professionals. More research is needed on educational strategies that could be implemented at the intra-personal level to assist college-aged young adults in healthcare career tracks to "catch up" or "fill in the gaps" in their sexual education journey.