Technical Constraints Research Articles

Transcriptional and epigenetic characterization of a new in vitro platform to model the formation of human pharyngeal endoderm

BackgroundThe Pharyngeal Endoderm (PE) is an extremely relevant developmental tissue, serving as the progenitor for the esophagus, parathyroids, thyroids, lungs, and thymus. While several studies have highlighted the importance of PE cells, a detailed transcriptional and epigenetic characterization of this important developmental stage is still missing, especially in humans, due to technical and ethical constraints pertaining to its early formation.ResultsHere we fill this knowledge gap by developing an in vitro protocol for the derivation of PE-like cells from human Embryonic Stem Cells (hESCs) and by providing an integrated multi-omics characterization. Our PE-like cells robustly express PE markers and are transcriptionally homogenous and similar to in vivo mouse PE cells. In addition, we define their epigenetic landscape and dynamic changes in response to Retinoic Acid by combining ATAC-Seq and ChIP-Seq of histone modifications. The integration of multiple high-throughput datasets leads to the identification of new putative regulatory regions and to the inference of a Retinoic Acid-centered transcription factor network orchestrating the development of PE-like cells.ConclusionsBy combining hESCs differentiation with computational genomics, our work reveals the epigenetic dynamics that occur during human PE differentiation, providing a solid resource and foundation for research focused on the development of PE derivatives and the modeling of their developmental defects in genetic syndromes.

Resiliency planning of distribution network using of active distribution network partitioning

Today, micro-grids (MGs) include all kinds of energy storage systems (ESSs), wind turbines (WTs), photovoltaic (PV), combined heat and power (CHP), etc., also demand response are active on the demand side. In this paper, single-level robust methods for partitioning and planning the active distribution network (ADN) into several MGs are presented. According to the desired purpose, the objective function of the model is investment costs minimization for installing the capacity of distributed generations (DGs) and switches, the activity of responsive loads based on the forecast of the generation of non- DG, losses and the risk of the load points of the costumers. On the other hand, maximizing the income from the MGs energy sales to the upstream grid and the technical constraints include optimal power flow (OPF) equations. The mentioned problem is a complex nonlinear model, and therefore, the improved genetic algorithm (GA) is used. In order to validate the efficiency, the improved method has been used on a 25-bus ADN including five switches. The simulation results obtained from the case studies prove the fact that the use of the retrofitted model increases the investment costs of the MG, especially in the case of an island operation, in contrast to the active presence of responsive loads that significantly reduce costs.

Modeling the Intent to Interact With VR Using Physiological Features.

Mixed-Reality (XR) technologies promise a user experience (UX) that rivals the interactive experience with the real-world. The key facilitators in the design of such a natural UX are that the interaction has zero lag and that users experience no excess mental load. This is difficult to achieve due to technical constraints such as motion-to-photon latency as well as false-positives during gesture-based interaction. In this paper, we explored the use of physiological features to model the user's intent to interact with a virtual reality (VR) environment. Accurate predictions about when users want to express an interaction intent could overcome the limitations of an interactive device that lags behind the intention of a user. We computed time-domain features from electroencephalography (EEG) and electromyography (EMG) recordings during a grab-and-drop task in VR and cross-validated a Linear Discriminant Analysis (LDA) for three different combinations of (1) EEG, (2) EMG and (3) EEG-EMG features. We found the classifiers to detect the presence of a pre-movement state from background idle activity reflecting the users' intent to interact with the virtual objects (EEG: 62 % ± 10 %, EMG: 72 % ± 9 %, EEG-EMG: 69 % ± 10 %) above simulated chance level. The features leveraged in our classification scheme have a low computational cost and are especially useful for fast decoding of users' mental states. Our work is a further step towards a useful classification of users' intent to interact, as a high temporal resolution and speed of detection is crucial. This facilitates natural experiences through zero-lag adaptive interfaces.

Full-Endoscopic Spinal Surgery for Older Patients With Degenerative Spinal Pathology: A Narrative Review

The aging population worldwide is experiencing an increasing incidence of degenerative spinal disorders, leading to significant morbidity and diminished quality of life. Traditional open surgical approaches for treating these conditions in older patients often entail substantial risks and prolonged recovery times. However, recent advancements in endoscopic surgical techniques have provided promising alternatives with potentially reduced morbidity and quicker recovery. This paper reviews the current literature regarding full-endoscopic spinal surgery (FESS) for degenerative spinal pathology in older patients. We discuss the evolution of endoscopic techniques, patient selection criteria, surgical indications, outcomes, and complications associated with FESS in older adults. Several studies have reported favorable outcomes of FESS in older patients, including reduced postoperative pain, shorter hospital stays, faster recovery, and comparable or even improved clinical outcomes compared with traditional open surgery. Moreover, FESS offers the advantages of minimal tissue disruption, preservation of spinal stability, and decreased blood loss, which are particularly advantageous in older patients with multiple comorbidities. However, challenges such as a steep learning curve for surgeons, limited visualization, and technical constraints in managing complex pathologies remain significant concerns. Additionally, the long-term durability and effectiveness of FESS in older patients require further investigation. In conclusion, FESS presents a promising minimally invasive option for treating degenerative spinal pathology in older adults. Further research and technological advancements are needed to optimize patient selection, refine surgical techniques, and improve long-term outcomes in this growing demographic category of patients.

EFFECT OF NON-FLUORIDATED AND FLUORIDATED MILK ON DENTAL PLAQUE PH CHALLENGED WITH A SWEETENED DRINK AT VARIOUS TIME INTERVALS

Aim: To investigate the effect of non-fluoridated and fluoridated milk on dental plaque challenged with sweetened drink by measuring the plaque pH at various time intervals. Patients and Methods: A total of 80 children aged 6-8 years who reported to the Department of Pedodontics and Preventive Dentistry, of which 10 children who were interested to participate in the study were included. Children were asked to rinse for 2 min with following solutions: Distilled water, 10% sucrose, non-fluoridated milk, fluoridated milk, 10% sucrose followed by distilled water, 10% sucrose followed by non- fluoridated milk, 10% sucrose followed by fluoridated milk. The supragingival plaque was collected before rinsing and after 5,10,15,20,25,30 and 60 min to measure the plaque pH. The values were tabulated and subjected to statistical analysis with one way analysis (ANOVA). Results: The result of present study shows that the minimum pH drop was almost similar for non-fluoridated and fluoridated milk group at 5 min which is lower than 10% sucrose group but the recovery of pH to baseline value was at faster rate in fluoridated milk group compared to non-fluoridated milk group. Conclusion: There are parts of world where drinking water cannot be fluoridated due to lack of resources, socio-economic and technical constraints, absence of political will and national policy on oral health. Hence fluoridation of milk can be recommended where fluoride concentration in drinking water is suboptimal and caries experience is significant.

Characteristics of physical parameters and predictive modeling of mechanical properties in loess-like silty clay for engineering geology

In the middle and lower reaches of the Yellow River in China, loess-like silty clay is prevalent. This soil type exhibits considerable variability in its compression coefficient α, which can lead to differential soil settlement and consequent damage to buildings and infrastructure, thereby posing safety risks. Despite its significance, research and data on this topic are still limited. This study involves comprehensive measurement and laboratory analysis of over one thousand soil samples collected on-site. It establishes a statistical distribution model for essential parameters, including water content w, wet density ρ, void ratio e, saturation Sr, liquidity index IL, liquid limit WL, plastic limit WP, and plasticity index IP, and explores the probability distribution characteristics of the physical and mechanical parameters of loess-like silty clay. Machine learning prediction models, utilizing Random Forest (RF) and Deep Neural Network (DNN) algorithms, were developed based on an extensive database to forecast the compression coefficient α and compression modulus ES of this soil. The predictive models demonstrated higher accuracy compared to conventional methods and hold significant practical implications for the timely prediction of the mechanical and engineering characteristics of loess-like silty clay. This research provides a robust scientific foundation for engineering design, enhances understanding of the mechanical properties and engineering attributes of this special soil expanse, and reduces the high costs and time consumption associated with engineering geological surveys, as well as the subjectivity of technical and environmental constraints and data interpretation. It serves as a valuable tool for disaster prevention and prediction.

What Works for the Youth: Analysis of Youth Employment Policies in Rwanda

In Rwanda, over 75 percent of youth are not in education, employment and training (NEET). These are mostly absorbed in the informal sector that provides little or no protection to workers against shocks, and are prone to several socio-economic, technical, and financial constraints. Through desk review of existing policies and studies, key informant interviews (KIIs), and focus group discussions (FGDs), this study reviews and analyzes the existing youth employment policies (YEPs) and interventions with intent to identify the hurdles and outcomes of the actual implementation of these YEPs in Rwanda. Youths aged 18 to 30, policy makers, policy implementers, and implementing partners were the key target respondents. The study finds a multitude of YEPs and interventions to promote youth education and skilling, entrepreneurship, and business development funding; though most of them are more focused on supply than demand-side of the labor market, with limited vulnerable youth inclusivity. Common hurdles encountered during implementation of YEPs include: poor coordination among the vast YEPs causing monitoring challenges both at national and district level, and duplication of services. Difficulty to integrate education and skilling into decent youth employment, matching labor laws with youth welfare, cultural bias limiting young women from participating in some labor market activities, funding gaps, and limited youth engagement during program design. Addressing these challenges requires a well-coordinated stakeholder engagement, and strong collaboration between the public and private sector, as well as civil society organizations.

Development of E-learning Based Mechatronics Learning Module for Distance Education

In the growing context of distance education, e-learning modules for mechatronics offer great potential to increase learning flexibility and effectiveness, but face challenges related to concept understanding, student motivation, and technical constraints. This study aims to evaluate the effectiveness of mechatronics-based e-learning modules in improving students' understanding of mechatronics concepts and to identify challenges and areas of improvement needed. Using a qualitative approach, the study involved in-depth interviews with 20 students over a four-month period as well as focus group discussions and document analysis. The data obtained was analysed thematically to reveal students' views and experiences. The findings show that e-learning modules that integrate multimedia elements such as animations and interactive simulations significantly improve students' understanding and motivate them through interactive elements. However, technical constraints such as unstable internet connection and device compatibility issues, as well as the need for additional support in self-directed learning, hindered the learning experience. Student feedback indicated the need for improvements to the module navigation and user guide. In conclusion, the e-learning module was effective in improving student understanding and motivation, but requires technical improvements and additional support to optimise its benefits in distance education.

A day‐ahead energy management strategy for electric vehicles in parking lots considering multi‐scenario simulations and hydrogen storage system

AbstractThis article investigated the charge and discharge management structure of electric vehicles (EVs) in intelligent parking lots (IPLs). It seems that with the expansion of renewable energy sources (RESs) as clean energy and investigation of the effects of EVs on the operation and planning of future distribution networks around the way EVs exchange energy with each other and the upstream network operator, RESs such as solar and wind sources, along with hydrogen storage are essential. Therefore, a new stochastic multi‐scenario approach for charge/discharge management of EVs parked in IPL was proposed, in which a newly developed model for the IPL with a hydrogen storage system (HSS) consisting of a fuel cell, an electrolyzer, and a hydrogen storage tank was presented. In the proposed model, the constraints of upstream network and power balance constraints, with the operating constraints related to the IPL, including EVs, renewable energy sources, and the hydrogen storage system, were formulated as the most important objectives of the optimization problem. The optimization algorithm, Competitive Swarm Optimizer (CSO), was formulated for implementation, and its results were compared with those of the PSO and GWO algorithms. The CSO must handle a variety of practical, large‐scale optimization problems. Based on the obtained results, the excess energy purchased from the upstream network or renewable sources was used as hydrogen storage for consumption during peak hours. As expected, the technical constraints and financial goals of the system were met, and the proposed system was evaluated on a 33‐bus network. As the expected benefits will be the most beneficial with the presence of renewable sources, the final profit will be reduced by taking into account uncertainty for charge/discharge management in EVs such as the uncertainty of electric load, market price, wind turbine, and photovoltaic cell sources. Nonetheless, the profit obtained from renewable resources is preferable to losses resulting from the uncertainty of the system, and according to expectation, the performance of the system for managing the optimal charging and discharging of EVs in the IPL will be acceptable with the maximum profit for the grid.

When Prominence Overrules EminenceSubsidization of the Cultural Sectors in the Netherlands

What processes determine the allocation of state subsidies to a selection of cultural and artistic organizations? In the case of the Dutch cultural basic infrastructure (BIS) two main criteria are issued, namely quality and reputation. In this article, no attempt is made to define measures for artistic quality and reputation. Instead, it is observed by which criteria decision makers, public media, and artistic leaders refer to these concepts. The way in which the selection and granting are performed shows striking similarity with processes described in the literature. First, the theory of social comparison asserts that people in a shared activity compare opinions and abilities in a strife for growth. When technical constraints and limits impede the progress in ability, effort and attention shift to opinions on abilities of the members. In this social dimension, growth is more easily attained. This decoupling results into stagnation and inferior learning processes. Second, in an implicit elaboration of the social comparison theory, a model is proposed in which perceived quality and prominence determine which organization will receive price premiums. Perceived quality is indicated by the quality of the inputs and productivity assets. Prominence origins from media rankings and elicited preferences of intermediary organizations and affiliation with high-status actors. Prominence has more bearing in social processes in the institutional field than on quality indicators. This model provides a base for reputation bias among stakeholders of organizations. The theoretical approaches have been operationalized into an analytical framework. The framework appears to offer a powerful and accurate instrument to describe and explain courses of action and outcomes in Dutch cultural sectors. In discussion, it is questioned if it is wise to base a subsidization policy on social comparison. The strive for prominence in the institutional fields tends to overrule the search for quality and eminence. It is recommended to reconsider social comparison processes by reduction of the arbitrariness in the performance assessment and evaluation. In this respect, promising and high-quality performers are supported in their access to large audiences. It is proposed that the framework can be applied in all situations where resources and performance opportunities are allocated to a selection of executing actors. Choices will be based on a mix of past and future performances. The situations suited for application may vary from philanthropy to hard core and non-profit sectors to private business industries.

Humanitarian health education and training state-of-the-art: a scoping review.

In the past decade, humanitarian emergencies have been increasing, leading to an higher demand for humanitarian health professionalization. Education and training are critical for preparing these workers to provide effective care during crises. Understanding the current state-of-the-art in humanitarian health education is essential to inform research and development of future educational programs. This review surveys the peer-reviewed literature to provide insights into the current thinking in the field. A review was conducted in March 2023 and updated in May 2024 using PubMed, Web of Science, Scopus, and Education Resources Information Center databases for English-language peer-reviewed articles published since January 2013. The review followed the Joanna Briggs Institute methodology for scoping reviews and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Data were analyzed using qualitative content analysis and presented as a narrative descriptive summary. After screening, 32 articles met the inclusion criteria. The themes of the selected articles focus on education and training frameworks, mapping, and programs. Despite the growing opportunities, most education and training programs are based in the Global North. The gaps identified include a lack of standardized curriculum or competency frameworks and evaluation frameworks to guide the development and evaluation of further standardized training programs. Interdisciplinary and collaborative partnerships, iterative design, and mixed teaching methods and modalities, including e-learning, facilitated successful training. However, logistical and technical constraints and the lack of standardized training frameworks were barriers to developing, implementing, and evaluating such training programs. This review provides an overview of the humanitarian health education trends over the last decade and identifies key areas for future educational development and research. The findings emphasize the importance of adapting interdisciplinary and collaborative partnerships and prioritizing the training of local staff through regional centers, local leadership, and accessible e-learning, including e-simulation. The review also highlights the need for continued research and evaluation of humanitarian health education and training programs with standardized metrics to evaluate training programs and identify areas for improvement. These steps will help ensure that humanitarian health professionals receive adequate training to provide effective healthcare in crisis situations.

Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia associated with significant morbidity and mortality. Managing risk of stroke and AF burden are pillars of AF management. Atrial geometry has long been recognized as a useful measure in achieving these goals. However, traditional diagnostic approaches often overlook the complex spatial dynamics of the atria. This review explores the emerging role of three-dimensional (3D) atrial geometry in the evaluation and management of AF. Advancements in imaging technologies and computational modeling have enabled detailed reconstructions of atrial anatomy, providing insights into the pathophysiology of AF that were previously unattainable. We examine current methodologies for interpreting 3D atrial data, including qualitative, basic quantitative, global quantitative, and statistical shape modeling approaches. We discuss their integration into clinical practice, highlighting potential benefits such as personalized treatment strategies, improved outcome prediction, and informed treatment approaches. Additionally, we discuss the challenges and limitations associated with current approaches, including technical constraints and variable interpretations, and propose future directions for research and clinical applications. This comprehensive review underscores the transformative potential of leveraging 3D atrial geometry in the evaluation and management of AF, advocating for its broader adoption in clinical practice.

“When you need it quick, let us ship it right”: on the importance of port efficiency and service quality to comply with food trade standards in Ghana

AbstractAgricultural exports are especially important because of their great potential for poverty reduction among smallholder farmers. However, many African countries, such as Ghana, fail to realize their full export potential due to institutional and technical constraints. This paper examines the importance of port efficiency and service quality in complying with food trade standards in Ghana. We provide a stylized theoretical model in which exporting firms are willing to pay for improved port service quality as long as the marginal revenue derived from a reduced likelihood of (border) rejection exceeds the marginal costs for improved service quality. We test the model’s predictions using primary data from 120 agri-food exporters in Ghana. Our results show that about two-thirds of exporting firms have a positive willingness-to-pay for a reduction in the handling time at the port and the risk of spoilage due to inadequate handling. These findings emphasize the importance of trade facilitation measures in improving port efficiency and service quality to accelerate agricultural exports.

Imputing Single-Cell Protein Abundance in Multiplex Tissue Imaging.

Multiplex tissue imaging are a collection of increasingly popular single-cell spatial proteomics and transcriptomics assays for characterizing biological tissues both compositionally and spatially. However, several technical issues limit the utility of multiplex tissue imaging, including the limited number of molecules (proteins and RNAs) that can be assayed, tissue loss, and protein probe failure. In this work, we demonstrate how machine learning methods can address these limitations by imputing protein abundance at the single-cell level using multiplex tissue imaging datasets from a breast cancer cohort. We first compared machine learning methods' strengths and weaknesses for imputing single-cell protein abundance. Machine learning methods used in this work include regularized linear regression, gradient-boosted regression trees, and deep learning autoencoders. We also incorporated cellular spatial information to improve imputation performance. Using machine learning, single-cell protein expression can be imputed with mean absolute error ranging between 0.05-0.3 on a [0,1] scale. Finally, we used imputed data to predict whether single cells were more likely to come from pre-treatment or post-treatment biopsies. Our results demonstrate (1) the feasibility of imputing single-cell abundance levels for many proteins using machine learning; (2) how including cellular spatial information can substantially enhance imputation results; and (3) the use of single-cell protein abundance levels in a use case to demonstrate biological relevance.

Revealing the Impact of Viscoelastic Characteristics on Performance Parameters of UV-Crosslinked Hotmelt Pressure-Sensitive Adhesives: Insights from Time-Temperature Superposition Analysis.

This study emphasizes the influential role of rheology in decoding the viscoelastic properties of pressure-sensitive adhesives (PSAs) vital to predicting key application features such as shear, tack, and peel, depending on the flow characteristics of PSAs during bonding and debonding processes. By applying the principle of time-temperature superposition (TTS), we extend the scope of our frequency analysis, surpassing the technical constraints of the available apparatus. Our exploration aims to uncover the general correlations between PSAs' viscoelastic properties and their performance in end-use applications. Initially, the adhesive performance and viscoelastic properties of a UV-crosslinkable styrene-butadiene-styrene (SBS) model adhesive prior and subsequent to UV irradiation were examined. The subsequent crosslinking reaction increased cohesive strength and heat resistance, although tack and peel strength observed a substantial decline. We successfully demonstrated these effects by logging the viscoelastic properties, specifically the storage modulus G' at lower frequencies, which mirrors the shear strength at higher temperatures and the shift in the tan δ peak to represent each PSA's tack. These correlations were partially reflected in three commercial UV crosslinkable acrylic PSA products, although the effect of UV irradiation was less distinctive. This study also revealed the challenges in predicting tack and peel strength, which result from a complex interplay of bonding and debonding processes. Our findings reinforce the necessity for more sophisticated analysis techniques and models that can accurately predict the end-use performance of PSAs across different physical structures and chemical compositions. Further research is needed to develop these predictive models, which may reduce the need for labor-intensive testing under real-life conditions.

Local Energy Community to Support Hydrogen Production and Network Flexibility

This paper deals with the optimal scheduling of the resources of a renewable energy community, whose coordination is aimed at providing flexibility services to the electrical distribution network. The available resources are renewable generation units, battery energy storage systems, dispatchable loads, and power-to-hydrogen systems. The main purposes behind the proposed strategy are enhancement of self-consumption and hydrogen production from local resources and the maximization of the economic benefits derived from both the selling of hydrogen and the subsidies given to the community for the shared energy. The proposed approach is formulated as an economic problem accounting for the perspectives of both community members and the distribution system operator. In more detail, a mixed-integer constrained non-linear optimization problem is formulated. Technical constraints related to the resources and the power flows in the electrical grid are considered. Numerical applications allow for verifying the effectiveness of the procedure. The results show that it is possible to increase self-consumption and the production of green hydrogen while providing flexibility services through the exploitation of community resources in terms of active and reactive power support. More specifically, the application of the proposed strategy to different case studies showed that daily revenues of up to EUR 1000 for each MW of renewable energy generation installed can be obtained. This value includes the benefit obtained thanks to the provision of flexibility services, which contribute about 58% of the total.

Ship Maintenance Management Practices: Insights from Internships in Shipping Engineering

This research investigates ship maintenance management practices among senior students in shipping engineering during their internships at a vocational school in Jakarta. The study explores the challenges faced, strategies employed, and lessons learned in managing maintenance tasks onboard ships. Seven participants were interviewed, highlighting technical malfunctions, resource limitations, time constraints, environmental factors, and communication barriers as primary challenges. Participants utilized preventive maintenance, cross-training, task prioritization, collaborative problem-solving, and digital tools to enhance operational efficiency. Lessons underscored the importance of preparation, teamwork, adaptability, continuous learning, and communication skills in navigating maritime maintenance complexities. The findings emphasize the role of proactive maintenance strategies and technological integration in optimizing sustainability and operational reliability within the maritime industry. Integrating practical training into educational curricula and embracing digital innovations are recommended for preparing future professionals. Future research could explore larger sample sizes and quantitative methodologies to validate findings and quantify the impact of maintenance practices. This study contributes to enhancing vocational education in maritime sciences and informs industry practices for advancing ship maintenance management globally.

SUBTITLING MALAY TABOO LANGUAGE INTO ENGLISH: THE CASE OF THE ASSISTANT (2022)

Taboo refers to social and behavioural proscriptions which may instigate discomfort in society, both in language use and psychical behaviour. In audiovisual translation, the emphasis on taboo is often placed on its relative audience reception and the enforcement of relevant laws and regulations. Akin to the nature of audiovisual products, subtitling taboo references also warrants multimodal consideration, especially in relation to both verbal and nonverbal elements. This study, in particular, aims to probe into the taboo language of subtitling from Malay into English. The film The Assistant (2022), which was released on the online streaming platform Netflix, is selected as the corpus. To this end, a parallel corpus was developed and subsequently analysed using AntConc and AntPConc. Frequency, thematic and translation strategy patterns were mapped and descriptively analysed. In general terms, the analysis reveals that the taboo words in the source text are multifaceted, predominantly exclamatory, and markedly explicit. Many of the taboo loads are also found to be equally rendered into the target text, which corresponds to Netflix’s no-censorship policy. The study also learns the omission of some references in the translation, which can be partly linked to the technical and structural constraints of subtitling.

Morphological and molecular characterization of the European dagger nematode Xiphinema diversicaudatum on peach (Prunus persica) in Canada

Plant-parasitic nematodes (PPNs) pose a significant threat to global agriculture, leading to substantial yield losses. Managing nematode populations remains a challenging option due to financial, technical and environmental constraints. In Ontario, Canada, the presence of Xiphinema nematodes, a virus vector species, is of particular concern. This study reports the discovery of X. diversicaudatum in a peach field in Southern Ontario, Canada. The description includes morphological and molecular characterization using the 18S and 28S rDNA sequences. Morphological and molecular characterization of Ontario’s population matched those from Europe. While X. diversicaudatum was presumed eradicated from Canada, the present finding showed that the nematode could have spread beyond greenhouses. The study highlights the importance of intensive soil sampling for early nematode detection, even as strict reporting requirements may deter such efforts. We report for the first time the presence of X. diversicaudatum on peaches in Canada and in North America.

Pemanfaatan Teknologi Augmented Reality pada Sistem Pernapasan Manusia

This study explores the use of Augmented Reality (AR) technology in studying the human respiratory system using a qualitative research method of a literature approach. Augmented Reality (AR) is a technology that combines virtual objects with real environments in real-time, which can be used as a visualization tool in education. This article uses a qualitative method with a library research approach that focuses on the discussion of learning and learning. The data collection technique used in this study is reading books, recording and collecting data from various literature such as journals, documents. The stages of analysis carried out in this study include several stages, including the preparation stage, data collection stage, data reduction, data categorization, data display, and conclusion drawing. The results of the study show that the use of AR in human respiratory system education can improve students' understanding through interactive and realistic 3D visualization. In addition, AR also allows students to study the structure and function of respiratory organs in a more in-depth and engaging way. However, technical constraints, costs, and the need for training for teachers are obstacles that need to be overcome for wider implementation. This study concludes that AR has great potential as an innovative learning tool in the medical field, especially for the respiratory system, if there is adequate support in terms of technology and educational infrastructure