Interactive Applications Research Articles

Development Of Interactive Learning Applications For English Subjects

The use of technology in learning is used as a means of learning. Learning media is anything that is used in the process of learning activities and can stimulate students' thoughts, feelings, interests and attention when learning, so that the process of interaction, communication and education between teachers and students can take place in accordance with the learning objectives. This research aims to produce a product in the form of a web-based interactive multimedia learning application, which is of good quality and highly suitable for use as a learning medium for students in English subjects. The research location was conducted at UPT SMP Negeri. 35 Medan. This multimedia learning product has gone through a strict review and revision process, based on suggestions from teachers and supervisors. This product was tested in a class with 31 students. The results show that learning management at UPT SMP Negeri 35 Medan using this interactive application has achieved learning management well, this can be seen from the acquisition section to the retrieval system of existing information/learning. Thus, this product can be used in the learning process to provide new, more meaningful experiences to students. In addition to this multimedia product, the teaching materials can be studied anywhere and at any time, which can increase students' learning motivation.

HAIviz: an interactive dashboard for visualising and integrating healthcare-associated genomic epidemiological data.

Existing tools for phylogeographic and epidemiological visualisation primarily provide a macro-geographic view of epidemic and pandemic transmission events but offer little support for detailed investigation of outbreaks in healthcare settings. Here, we present HAIviz, an interactive web-based application designed for integrating and visualising genomic epidemiological information to improve the tracking of healthcare-associated infections (HAIs). HAIviz displays and links the outbreak timeline, building map, phylogenetic tree, patient bed movements, and transmission network on a single interactive dashboard. HAIviz has been developed for bacterial outbreak investigations but can be utilised for general epidemiological investigations focused on built environments for which visualisation to customised maps is required. This paper describes and demonstrates the application of HAIviz for HAI outbreak investigations.

Dura-Europos Stories: Developing interactive storytelling applications using knowledge graphs for cultural heritage exploration

We introduce Dura-Europos Stories, a multimedia application for viewing artifacts and places related to the Dura-Europos archaeological excavation. We describe the process of mapping data to the Wikidata data model as well as the process of contributing data to Wikidata. We provide an overview of the functionality of an interactive application for viewing images of the artifacts in the context of their metadata. We contextualize this project as an example of using knowledge graphs in research projects in order to leverage technologies of the Semantic Web in such a way that data related to the project can be easily combined with other data on the web. Presenting artifacts in this story-based application allows users to explore these objects visually, and provides pathways for further exploration of related information.

Physics-informed differentiable method for piano modeling

Numerical emulations of the piano have been a subject of study since the early days of sound synthesis. High-accuracy sound synthesis of acoustic instruments employs physical modeling techniques which aim to describe the system’s internal mechanism using mathematical formulations. Such physical approaches are system-specific and present significant challenges for tuning the system’s parameters. In addition, acoustic instruments such as the piano present nonlinear mechanisms that present significant computational challenges for solving associated partial differential equations required to generate synthetic sound. In a nonlinear context, the stability and efficiency of the numerical schemes when performing numerical simulations are not trivial, and models generally adopt simplifying assumptions and linearizations. Artificial neural networks can learn a complex system’s behaviors from data, and their application can be beneficial for modeling acoustic instruments. Artificial neural networks typically offer less flexibility regarding the variation of internal parameters for interactive applications, such as real-time sound synthesis. However, their integration with traditional signal processing frameworks can overcome this limitation. This article presents a method for piano sound synthesis informed by the physics of the instrument, combining deep learning with traditional digital signal processing techniques. The proposed model learns to synthesize the quasi-harmonic content of individual piano notes using physics-based formulas whose parameters are automatically estimated from real audio recordings. The model thus emulates the inharmonicity of the piano and the amplitude envelopes of the partials. It is capable of generalizing with good accuracy across different keys and velocities. Challenges persist in the high-frequency part of the spectrum, where the generation of partials is less accurate, especially at high-velocity values. The architecture of the proposed model permits low-latency implementation and has low computational complexity, paving the way for a novel approach to sound synthesis in interactive digital pianos that emulates specific acoustic instruments.

Dashing Growth Curves: a web application for rapid and interactive analysis of microbial growth curves

BackgroundRecording and analyzing microbial growth is a routine task in the life sciences. Microplate readers that record dozens to hundreds of growth curves simultaneously are increasingly used for this task raising the demand for their rapid and reliable analysis.ResultsHere, we present Dashing Growth Curves, an interactive web application (http://dashing-growth-curves.ethz.ch/) that enables researchers to quickly visualize and analyze growth curves without the requirement for coding knowledge and independent of operating system. Growth curves can be fitted with parametric and non-parametric models or manually. The application extracts maximum growth rates as well as other features such as lag time, length of exponential growth phase and maximum population size among others. Furthermore, Dashing Growth Curves automatically groups replicate samples and generates downloadable summary plots for of all growth parameters.ConclusionsDashing Growth Curves is an open-source web application that reduces the time required to analyze microbial growth curves from hours to minutes.

Growth Response of Mucuna bracteata with the Application of Local Micro Organisms (LMO) of Banana Weevil

This research aims to determine the effect of concentration and duration immersion giving LOM banana weevil against the gowth of Mucuna bracteata. The research was conducted in the garden of Jalan Setia Bangun Pasar III, Sei Beras Sekata, Kecamatan sunggal, Kabupaten Deli Serdang, Sumatra utara and continued in the laboratory of the Indonesian Oil Palm Research Institute (IOPRI). This research was started in April-June 2020. This study used a randomized complete block design (RCBD) factorial. The first factor was the concentration of local microorganisms (LMO) of Banana Weevil consisting of 4 levels, namely: Without treatment, 15%, 30%, 45%. The second factor. The duration of immersion consists of 4 levels, namely: No immersion time, 15 minutes, 30 minutes, 45 minutes. Observation data were analyzed usingDuncan's Multiple Range Test with a significant 5%. The results showed that the LMO concentration of banana weevil was effective in increasing the gowth of the number of leaves 39.77, tendril length 83.14 cm, shoot fresh weight 28.54 g, and shoot dry weight 6.03 g. The duration of soaking had a significant effect on the highest number of leaves at week 3 (9.63 pieces). The interaction application of banana weevil concentration and soaking time affected the number of root nodules (40.50 gains) and root dry weight (0.73) g of theplant Mucuna bracteata.

Assessing women's and health professionals' views on developing a midwifery‐led mobile health app intervention in pregnancy: A descriptive qualitative study

AbstractAimsTo explore women's and health professionals' views on the development of a midwifery‐led mHealth app intervention in antenatal care and their demands for app functionality.DesignDescriptive qualitative research was utilized.MethodsIn total, 15 pregnant or postpartum women were interviewed via in‐depth interviews and 10 health professionals including obstetricians, midwives and obstetric nurses were invited to participate in a focus group discussion (FGD). All interviews and the FGD were analysed using qualitative content analysis.ResultsFour key themes emerged from the data, including (1) limitations of current maternity care services; (2) potential benefits for mHealth app‐based midwifery care; (3) possible challenges for providing midwifery care through mHealth apps and (4) suggestions and needs for developing a midwifery‐led mHealth app. Participants agreed on the potential need of developing a midwifery‐led mHealth app in antenatal care to increase access to midwifery care services and to meet women's diverse needs. Participants preferred to develop professional, reliable, full‐featured and interactive mobile applications. The main functions of midwifery‐led mHealth apps included personalized assessment and health education, self‐monitoring and feedback, data sharing and interactive functions. Women mentioned that online communication and consultation with midwives could help them receive continuous support outside facilities. Health professionals expressed it would be of great convenience and timeliness to send personalized messages to women and to inform them of healthy lifestyles during pregnancy. The challenges included a shortage of human resources, medico‐legal risks associated with mHealth and data security risks.ConclusionsThis study explores the individual views and functional needs of target users and healthcare providers for developing a midwifery‐led mHealth app in antenatal care, which will serve as a reference for future application development.ImpactOur study has important and practical implications for guiding the development of future midwifery‐led mHealth app interventions.Patient or Public ContributionNo patient or public contribution.

Human-computer interaction based on speech recognition

With the rapid change of The Times, language is no longer limited only in books, but gradually dedicates itself to reality. Speech recognition, in recent years, the cause of artificial intelligence and human-computer interaction continues to develop, all levels of life have its footprint, speech human-computer interaction leaf slowly began to integrate into the mainstream team of artificial intelligence. In general, speech recognition technology brings more convenience and naturalness to human-computer interaction, The benefits of human-computer interaction are not only reflected in improving the performance and efficiency of technical systems, but also in improving the user experience, fostering innovation, and promoting inclusive and sustainable development of society, and it has a positive impact in many fields, and with the continuous progress of technology, its application prospects will be broader. This paper makes a simple analysis and introduction of the role of speech recognition in human-computer interaction, expounds the key technologies, main algorithms and working principles of speech human-computer interaction, And some applications of human-computer interaction based on speech recognition in life and production fields. At the same time, the hidden problems and solutions are discussed, and includes the prospect of future speech human-computer interaction. Hope that this paper can bring some inspiration to relevant scientific research teams, assisting them to broaden a bright future.

Robust Fiber-Shaped Flexible Temperature Sensors for Safety Monitoring with Ultrahigh Sensitivity.

Flexible temperature sensors capable of detecting and transmitting temperature data from the human body, environment, and electronic devices hold significant potential for applications in electronic skins, human-machine interactions, and disaster prevention systems. Nonetheless, fabricating flexible temperature sensors with exceptional sensing performance remains a formidable task, primarily due to the intricate process of constructing an intrinsically flexible sensing element with high sensitivity. In this study, a facile in situ two-step synthetic method is introduced for fabricating flexible fiber-shaped NiO/carbon nanotube fiber (CNTF) composites. The resulting NiO/CNTF flexible temperature sensors demonstrate outstanding deformability and temperature sensing characteristics, encompassing a broad working range (-15 to 60°C) and high sensitivity (maximum TCR of -20.2%°C-1 and B value of 3332 K). Importantly, the mechanical and thermal behaviors of the sensor in various application conditions are thoroughly examined using finite element analysis simulations. Moreover, the temperature sensors can effectively capture diverse thermal signals in wearable applications. Notably, a temperature monitoring and warning system is developed to prevent fire accidents resulting from abnormal thermal runaway in electronic devices.

Elliptically polarized high-order harmonic generation of Ar atom in an intense laser field

Abstract We have conducted experimental investigations on the high-order harmonic generation (HHG) of Ar atom in an elliptically polarized intense laser field. Interestingly, we observe an anomalous dependence on the laser ellipticity (ε) in the lower-order harmonics, specifically in the 13rd-order, which displayed maximal harmonic intensity at ε ≈ 0.1, rather than at ε = 0 as expected. This contradicts the general trend of harmonic yield, which typically decreases with the increase of laser ellipticity. In this study, we attribute this phenomenon to the disruption of the symmetry of the wave function by the Coulomb effect, leading to the generation of a harmonic with high ellipticity. This finding provides valuable insights into the behavior of elliptically polarized harmonics and offers a potential avenue for exploring new applications in ultrafast spectroscopy and light-matter interactions.

Flexible capacitive pressure sensors and their applications in human-machine interactions

Flexible pressure sensors offer more significant advantages than rigid sensors in various applications, including human-computer interaction, medical health, and robot touch. However, this also places more stringent demands on the materials used. For example, the materials must be thin and soft enough to fit onto the surface of the human skin or be implanted into the body while also exhibiting good biocompatibility and matching the mechanical properties of biological tissues. Regarding device performance, flexible pressure sensor design primarily focuses on enhancing sensitivity, response time, detection limit, and stability. Researchers have recently been expanding these sensors' pressure response range, pressure resolution, spatial resolution, and tensile performance, which will further broaden their potential applications. This review provides an overview of the recent classification of flexible pressure sensors, covering their sensing principle, sensing performance, and future application prospects.

Building information modeling (BIM) in project management: a bibliometric and science mapping review

PurposeThe impact of building information modeling (BIM) on various aspects of project management has attracted much attention in the past decade. However, previous studies have focused on a particular facet of project management (e.g., safety, quality, facility management) and within identified target journals. Despite numerous existing studies, there is limited research on the mainstream research topics, gaps and future research directions on BIM in project management. This study aims to conduct a bibliometric and science mapping review of published articles on BIM in project management and to identify mainstream research topics, research gaps and future research directions in this domain.Design/methodology/approachA science mapping approach consisting of bibliometric search, scientometric analysis and qualitative discussion was used to analyze 521 journal articles that were retrieved from the Scopus database and related to BIM in project management. In the scientometric analysis, keyword co-occurrence analysis and document analysis were performed. This was followed by a qualitative discussion that seeks to propose a framework summarizing the interconnection between the mainstream research topics, research gaps and future research directions.FindingsSix mainstream research topics were found including (1) BIM-enabled advanced digital technologies, (2) BIM-based reinforcement and enhancement, (3) BIM and project composition, (4) BIM project elements and attributes, (5) BIM-based collaboration and communication and (6) BIM-based information and data. Moreover, this study discussed six research gaps, namely, (1) integration of BIM and other digital technologies, (2) future maturity of BIM applications in project management, (3) application of BIM in project components and processes, (4) role of BIM application in project elements and attributes, (5) impact of collaboration and communication in BIM application and (6) stability of information and data interaction. Furthermore, future research directions were discussed.Originality/valueThe findings and proposed framework contribute to providing a deeper understanding to researchers, policymakers and practitioners in the development of related research and practice in the domain of BIM in project management, thus, promoting digital transformation in project management. Overall, it adds to the global knowledge domain in BIM and promotes the need for digital and data integration, BIM maturity and BIM collaboration.

ShinyTempSignal: an R shiny application for exploring temporal and other phylogenetic signals

The molecular clock model is fundamental for inferring species divergence times from molecular sequences. However, its direct application may introduce significant biases due to sequencing errors, recombination events, and inaccurately labeled sampling times. Improving accuracy necessitates rigorous quality control measures to identify and remove potentially erroneous sequences. Furthermore, while not all branches of a phylogenetic tree may exhibit a clear temporal signal, specific branches may still adhere to the assumptions, with varying evolutionary rates. Supporting a relaxed molecular clock model better aligns with the complexities of evolution. The root-to-tip regression method has been widely used to analyze the temporal signal in phylogenetic studies and can be generalized for detecting other phylogenetic signals. Despite its utility, there remains a lack of corresponding software implementations for broader applications. To address this gap, we present shinyTempSignal, an interactive web application implemented with the shiny framework, available as an R package and publicly accessible at https://github.com/YuLab-SMU/shinyTempSignal. This tool facilitates the analysis of temporal and other phylogenetic signals under both strict and relaxed models. By extending the root-to-tip regression method to diverse signals, shinyTempSignal helps in the detection of evolving features or traits, thereby laying the foundation for deeper insights and subsequent analyses.

Cirscan: a shiny application to identify differentially active sponge mechanisms and visualize circRNA–miRNA–mRNA networks

BackgroundNon-coding RNAs represent a large part of the human transcriptome and have been shown to play an important role in disease such as cancer. However, their biological functions are still incompletely understood. Among non-coding RNAs, circular RNAs (circRNAs) have recently been identified for their microRNA (miRNA) sponge function which allows them to modulate the expression of miRNA target genes by taking on the role of competitive endogenous RNAs (ce-circRNAs). Today, most computational tools are not adapted to the search for ce-circRNAs or have not been developed for the search for ce-circRNAs from user’s transcriptomic data.ResultsIn this study, we present Cirscan (CIRcular RNA Sponge CANdidates), an interactive Shiny application that automatically infers circRNA–miRNA–mRNA networks from human multi-level transcript expression data from two biological conditions (e.g. tumor versus normal conditions in the case of cancer study) in order to identify on a large scale, potential sponge mechanisms active in a specific condition. Cirscan ranks each circRNA–miRNA–mRNA subnetwork according to a sponge score that integrates multiple criteria based on interaction reliability and expression level. Finally, the top ranked sponge mechanisms can be visualized as networks and an enrichment analysis is performed to help its biological interpretation. We showed on two real case studies that Cirscan is capable of retrieving sponge mechanisms previously described, as well as identifying potential novel circRNA sponge candidates.ConclusionsCirscan can be considered as a companion tool for biologists, facilitating their ability to prioritize sponge mechanisms for experimental validations and identifying potential therapeutic targets. Cirscan is implemented in R, released under the license GPL-3 and accessible on GitLab (https://gitlab.com/geobioinfo/cirscan_Rshiny). The scripts used in this paper are also provided on Gitlab (https://gitlab.com/geobioinfo/cirscan_paper).

Adaptive control for shape memory alloy actuated systems with applications to human-robot interaction.

Shape memory alloy (SMA) actuators are attractive options for robotic applications due to their salient features. So far, achieving precise control of SMA actuators and applying them to human-robot interaction scenarios remains a challenge. This paper proposes a novel approach to deal with the control problem of a SMA actuator. Departing from conventional mechanism models, we attempt to describe this nonlinear plant using a gray-box model, in which only the input current and the output displacement are measured. The control scheme consists of the model parameters updating and the control law calculation. The adaptation algorithm is founded on the multi-innovation concept and incorporates a dead-zone weighted factor, aiming to concurrently reduce computational complexities and enhance robustness properties. The control law is based on a PI controller, the gains of which are designed by the pole assignment technique. Theoretical analysis proves that the closed-loop performance can be ensured under mild conditions. The experiments are first conducted through the Beckhoff controller. The comparative results suggest that the proposed adaptive PI control strategy exhibits broad applicability, particularly under load variations. Subsequently, the SMA actuator is designed and incorporated into the hand rehabilitation robot. System position tracking experiments and passive rehabilitation training experiments for various gestures are then conducted. The experimental outcomes demonstrate that the hand rehabilitation robot, utilizing the SMA actuator, achieves higher position tracking accuracy and a more stable system under the adaptive control strategy proposed in this paper. Simultaneously, it successfully accommodates hand rehabilitation movements for multiple gestures. The adaptive controller proposed in this paper takes into account both the computational complexity of the model and the accuracy of the control results, Experimental results not only demonstrate the practicality and reliability of the controller but also attest to its potential application in human-machine interaction within the field of neural rehabilitation.

MedConnect PLUS: Health Management System

Abstract: The utilization of mobile applications in healthcare represents a frontier of innovation with the potential, to significantly enhance patients' daily healthcare management. These applications have the capacity to improve the efficiency of healthcare delivery, ultimately leading to cost reduction, and play a pivotal role in disease prevention by influencing behavior change. The paper introduces a model for an interactive healthcare application designed to meet the collaborative needs of both doctors and patients. The envisioned mobile application seeks to optimize communication among various stakeholders in the healthcare sector, including doctors, pharmacists and patients, thereby enhancing overall healthcare service and delivery. Object Oriented Analysis is employed in the software development process. This proposed mobile application is geared towards facilitating effective communication by incorporating advanced technologies to streamline processes such as appointment scheduling, health record management, and patient-doctor interactions. Emphasis is placed on the application's commitment to data security and compliance with healthcare regulations, ensuring the protection of sensitive patient information within a secure environment. The user-friendly interfaces tailored for both patients and doctors highlight the application's intention to cultivate a more interconnected and accessible healthcare ecosystem.

Structural and Functional Analysis of Groundnut bud necrosis virus (GBNV) Using Computational and Biochemical Approaches.

Groundnut bud necrosis virus (GBNV) belonging to the genus Orthotospovirus is transmitted by its vector Thrips palmi. It is a tri-segmented RNA virus that consists of L, M, and S RNA segments. We analysed the secondary structure features of GBNV proteins through various software and predicted the transmembrane helix, glycosylation, and signal peptidase sites within the GBNV protein sequences (GN, GC, N, NSm, and NSs). In glycoprotein sequence, extended strands are predominant (52.87%) whereas the N protein sequence mostly contains alpha helices (47.46%). The random coils are present in movement protein (43.97%) and structural protein (39.41%). We generated the 3D structure of GN and N protein using SWISS MODEL software and quality is validated through PROCHECK and PDBsum software. We also expressed the GBNV proteins (GN, GC, N, NSm, and NSs) in bacterial expression system. The recombinant proteins were used to raise polyclonal antibodies in mice. Our study will be useful in understanding GBNV protein structures in further detail by analysing the important domains that interact with the thrips proteins. This will further aid us in understanding virus-vector relationship through the application of protein-protein interaction and other immunodiagnostic techniques.

Effectiveness of Non-Pharmacological Therapy on Physical Symptoms in Patients With Persistent Concussion Symptoms: A Systematic Review.

This systematic review provides a comprehensive overview on the effectiveness of rehabilitation on physical symptoms in patients of all ages with persistent concussion symptoms. PubMed, MEDLINE®, Cochrane library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Embase were searched from January 1, 2012 to September 1, 2023 using terms related to physical post-concussion symptoms. Eligible articles were critically appraised using the Scottish Intercollegiate Guidelines Network (SIGN) and the Quality Assessment Tool. The Grading of Recommendations Assessment, Development, and Evaluation system was applied to rate the quality of evidence. Thirty-two articles were included. Preliminary evidence suggests that transcranial magnetic stimulation improves symptoms in adults, specifically headaches. Young adults reported a significant decrease in physical symptoms following sub-symptom aerobic training as well as cervical spine manual therapy. Tentatively, adults demonstrated improvements in headache symptoms following neurofeedback sessions, and progressive muscle relaxation resulted in a decrease in monthly headaches. Multimodal therapy in adults produced significant change in physical symptoms when compared with usual care. However, no further reduction in physical symptoms was observed when adult patients received a program of care that afforded cervicovestibular rehabilitation with symptom-limited exercise compared with a symptom-limited exercise program alone. Cognitive behavioral therapy demonstrated inconsistent findings for its effects on physical symptoms, specifically headaches. Veterans had a significant change in post-concussive symptoms, specifically headaches, following 3-month use of an interactive smartphone application as compared with standard care. Finally, in a pediatric population, the use of melatonin did not produce any changes in physical persistent concussion symptoms as compared with placebo. Preliminary evidence suggests that various forms of rehabilitative therapies can improve persistent physical concussive symptoms. However, given the methodological limitations in the majority of trials, the results need to be interpreted with caution.

EXPLORING FACTORS ASSOCIATED WITH SEROLOGICAL RESPONSE TO SARS-COV-2 VACCINES IN INDIVIDUALS WITH INFLAMMATORY BOWEL DISEASE: INTERACTIVE VISUALIZATION METHODS FOR MULTIDIMENSIONAL DATA

Abstract BACKGROUND SARS-CoV-2 vaccine response may be reduced in seniors (age 65+) with inflammatory bowel disease (IBD) and those on anti-TNF therapy. A challenge of the COVID-19 era has been conveying rapid-evolving health information, especially for groups with higher risk of poor outcomes of COVID-19 such as seniors and immunocompromised individuals. AIM To develop sharable, interactive 3D models of the relationship of age and days from vaccine dose on serological responses to SARS-CoV-2 vaccines in people with IBD who are either on or not on anti-TNF therapy. METHODS A prospective cohort study of individuals with IBD (n=528) who received 1–4 doses of a COVID-19 vaccine were assessed for serological responses 1–8 weeks and 8–16 weeks following each dose using the SARS-CoV-2 IgG II Quant assay. The cohort was stratified into those on and not on anti-TNF therapy at vaccination. We created 3D models with the plotly R package. Data were plotted as days from vaccine dose on the x-axis, age at the time of serology on the y-axis, and spike-protein antibody levels on the z-axis. Linear regressions were run with Anti-Spike IgG levels (AU/mL) as the outcome, and days from vaccine and age at serology as continuous exposures. Results were visualized as regression planes in 3D models. To share our visualizations, we built an open-access, online, interactive dashboard (https://covid19-sero.shinyapps.io/dashboard/). RESULTS The dashboard allows knowledge users to make selections based on desired data stratifications, and then zoom, pan, and rotate the plot to inspect the data or download an image of the plot they generate. Post-2nd dose samples comprised the largest dose subset in our study (n=658). Our model for post-2nd dose data shows that antibody levels significantly decrease by 20.9 (AU/mL) per day from a dose (p<0.001) and by 116.6 (AU/mL) per year increase in age (p=0.002) (Figure 1). As age increases, antibody levels significantly decrease by 107.5 (AU/mL) for those on anti-TNFs (p=0.026) and by 124.8 (AU/mL) for those not on anti-TNFs (p=0.002) (Figure 2). Those not on anti-TNFs experienced a decrease of 31.1 (AU/mL) (p<0.001) per day after 2nd vaccine dose; we did not find a significant decrease over time for those on anti-TNFs (p=0.927) (Figure 2). DISCUSSION In people with IBD, advancing age is associated with lower antibody responses to SARS-CoV-2 vaccines; however, antibody response does not significantly decrease over time for those on anti-TNF therapy. Integrating visualizations of quantitative data with participant demographics and medical therapy in open-access, interactive web applications promotes rapid release of research findings in a format that is accessible by a maximum number of knowledge users, which is of continued importance for those with a high risk of complications resulting from COVID-19. Figure 1 A scatterplot with post-2nd dose data for all possible data stratifications, downloaded from our online dashboard. The plot depicts decreasing trends in Anti-Spike IgG levels (AU/mL) as days from dose and participant age increase. Figure 2 Scatterplots with post-2nd dose data comparing Anti-Spike IgG levels (AU/mL) for participants either on or not on anti-TNF therapy. Plots depict lower antibody levels for individuals with IBD on anti-TNF therapy. Panel A shows no change in antibody levels for those on anti-TNF therapy as days from vaccine dose increase and Panel B shows that antibody levels in those not on anti-TNF therapy decrease as both days from vaccine dose and age increase.

Interactive PAI Science Quiz to Increase Students' Competitive Power through Kodular Applications

This research aims to increase student involvement in Islamic Religious Education (PAI) subjects by utilizing a mobile learning application equipped with an interactive quiz feature built using the Kodular platform. The basis of this research was inspired by the results of previous research which showed that the use of technology can be effective in increasing students' motivation and level of participation in the PAI learning process. In order to achieve this goal, this research adopts a research and development (R&D) approach to design and implement a PAI interactive quiz application that utilizes the Kodular platform. The application is aimed at junior high school (SMP) students. In the development stage, the research team designed and developed the PAI interactive quiz application using the Kodular platform which allows creating mobile applications visually without requiring complex programming. This application is equipped with an interactive quiz feature that supports PAI learning. The result of this research is a Kodular-based learning media application. In conclusion, the integration of mobile learning technology offers an interactive, flexible and interesting learning experience for students, which contributes to increasing student motivation and participation in PAI learning. This research contributes to the development ofinnovative and effective PAI teaching methods through the use of technology.