This study aims to evaluate the validity and reliability of the Rapid Interactive Screening Test for Autism in Toddlers (RITA-T) in a cohort of Chinese toddlers aged 18 to 36 months. Screening was conducted on toddlers aged 18 to 36 months, encompassing those with ASD, language impairments, developmental delays, and typical development. Evaluations were performed using the Diagnostic and Statistical Manual of Mental Disorders (5th ed), the Autism Diagnostic Observation Schedule-2, and the Modified Checklist for Autism in Toddlers. A random sample of 25 toddlers underwent a follow-up assessment with the RITA-T two weeks later. Critical values were determined based on the sensitivity, specificity, positive and negative predictive value of the RITA-T total score in differentiating ASD diagnoses. A total of 114 toddlers were enrolled in the study. The optimal cut-off score for the RITA-T in screening for ASD was determined to be 16, yielding a sensitivity of 0.918 and a specificity of 0.981, with an area under the receiver operating characteristic (ROC) curve of 0.961 (95% CI: 0.924-0.998, p < 0.001). Additionally, the scale exhibited strong internal consistency (Cronbach's α = 0.828), high test-retest reliability (Spearman's rho coefficient = 0.962, p < 0.01), and excellent inter-rater reliability (ICC = 0.975, 95% CI: 0.970-0.979, p < 0.001). The Chinese version of the RITA-T is a robust instrument for the early identification of ASD and is highly applicable for early screening efforts in China.

Public health significantly impacts a country's progress and resilience, particularly through economic growth, human development, and social stability. Outbreaks are a serious public health issue because they can disrupt the health system, increase the burden of disease, and lead to inequity in services. This study aims to develop a health dashboard to monitor and analyze outbreaks in East Kalimantan. Data from the Central Statistics Agency (BPS) and the Satu Data Kalimantan Timur were used to develop the dashboard. The District/City Health Profile Technical Guidelines were used to assist in compiling the dashboard data sources. This research method employed action research with a quantitative descriptive approach. This study successfully developed a dashboard with three levels of analysis. The first level consisted of scorecards and controls; the second, area maps and bar charts; and the third, line charts and heatmap tables. The KPI using the scorecard showed a 0% validity tolerance in the KPI calculation accuracy test. In the interactive functionality test, cross-filtering and control filters worked as expected. From the 2024 data analysis, the rapid response ratio for areas affected by outbreaks and conducting epidemiological investigations was 1.69% in Samarinda City. Meanwhile, Balikpapan City had the highest rapid response rate, with 5.88%. This study's findings indicated a data anomaly in the Satu Data Kalimantan Timur data, as evidenced by a service coverage ratio exceeding 100%. The number of residents in the outbreak- affected areas receiving services, according to the Satu Data Kalimantan Timur standard, exceeds the population recorded in the 2024 BPS data.

A signifcant proportion of listening activities in practice are interactive in nature, as it has been proven in research studies around the world. All listening activities, except for media listening, speech listening and eavesdropping, are aimed at two-way listening and speaking in direct communication. Traditionally, however, language teaching activities have often adopted a passive approach to listening comprehension, leading learners to perceive listening as a purely receptive act. This approach emphasizes the mere reception of information rather than active synthesis or clarifcation when comprehension issues arise. If learners are placed in communicative contexts, and if they can interact with the speaker to seek understanding, the teaching and learning effectiveness of language listening activities will be enhanced. For these reasons, in this article, we study the application of the interactive approach to teaching Vietnamese listening to foreigners. We review research works on interactive listening teaching and Vietnamese listening profciency tests. Then, the concepts of interaction, interactive listening and their constituent elements are clarifed. On that basis, the methods for teaching interactive Vietnamese listening are proposed. The criteria for assessing interactive listening skills of foreigners in the teaching-learning process and in testingassessment activities are also offered. The obtained results have the potential to build interactive Vietnamese listening textbooks for foreigners as well as assessment standards for interactive Vietnamese listening profciency tests. In this chapter we research on applying interactive approach to teaching Vietnamese language listening for foreigners. We examine research works on teaching interactive listening and tests for assessing language listening competence. Then, the concepts of interactive, interactive listening, and their constituent elements are clarified. Later, methods for teaching Vietnamese interactive listening are proposed. Criteria to assess the interactive listening skills of foreigners in the teaching-learning process and in testing-assessing activities are also suggested. The results obtained have the potential basis to develop interactive Vietnamese listening course-books for foreigners as well as standards for assessing tests of Vietnamese interactive listening competence.

Quantitative Classification of Visual Field Defects in Early Glaucoma.

Purpose This study aims to explore the possibilities and implications of artificial intelligence (AI) in Educational Technology through the lens of design thinking (DT) theoretical framework. DT guides this study through five processes: emphasize, define, ideate, prototype and test. This research presents the process of developing a lesson plan with ChatGPT, an AI chatbot that uses natural language processing to respond to a user's prompts and produce humanlike conversational dialogue. Design/methodology/approach DT (Figure 2) as a human-centered approach to innovation is one of the teaching methods as well as a course design methodology in academia (Ward et al., 2009; Zupan et al., 2023). The primary reason for the usage of DT is because it is the process of seeking to understand the points of view of others such as students. DT has a total of five steps that flow as a cyclical process: empathize, define, ideate, prototype and test. During the process from empathy to test, “re-iterating and re-thinking” are extensively used to improve prototypes and to create a quality outcome. Findings This study employed DT as a framework to explore a course designed for educational leaders by utilizing ChatGPT. As an interactive iterative process, empathize, define, ideate, prototype and test were the five processes that this study followed. To empathize with educational leaders, an empathy map was used based on the categories: Says, Thinks, Does and Feels in the real-life-based scenarios that educational leaders shared. Accordingly, four real case scenarios having real issues that came from educational leaders were analyzed by the authors based on what they say, what they think, what they do and how they feel. Research limitations/implications One limitation of this study is that the feedback was received only by instructors. Instructors' feedback was extensively utilized to create the final version, but according to DT, any final product can always be improved by inviting current users, who will be both instructors and students in this case. Since the final users of the lesson included both instructors and students, it would be beneficial for future research to invite students who have learned through this lesson plan to provide their feedback. This would allow us to bring more diverse perspectives, leading to a better final outcome. Practical implications Overall, while ChatGPT provided rapid suggestions based on the prompts, the input needs to be curated by experts as the output is carefully appraised to ensure optimum applicability to the course syllabus and to ensure the students receive comprehensive training in applying the course contents. Originality/value This study suggests innovative practices by utilizing features of AI related to ChatGPT in supporting a leadership course. The study extensively used ChatGPT in the DT process: empathize, define, ideate, prototype and test. This study suggests possibilities for using AI so that practitioners can generate their ideas by leveraging ChatGPT for their benefit.

The quick progress of online education has changed how teaching is done, making the examination of new digital learning methods crucial. Although numerous studies have explored technology use in educational settings, there is a lack of research concerning how Social Studies educators modify and create new approaches within the Merdeka Curriculum, indicating a considerable gap in the existing literature. This research seeks to determine the types of digital innovations utilized by Social Studies educators and examine the factors that promote or hinder their implementation in junior high schools. Employing a qualitative case study method at SMPN 1 Jember, data were gathered through interviews, classroom observations, and document examination, and subsequently analyzed thematically to uncover significant patterns and insights. The results show that teachers use digital methods like interactive presentations, online tests, and collaborative tools to improve student involvement and learning results. These practices signify a new adjustment to the Merdeka Curriculum. The research emphasizes the significance of creative teaching and support from institutions, providing direction for professional growth and the development of curricula.

The relevance of the topic is due to large-scale changes in the automotive industry, in particular, active digitalization, transformation of communication channels and the formation of new consumer demands. The modern buyer expects not only a high-quality product, but also fast, personalized and interactive interaction with the brand in the digital environment. Promotion strategies that take into account the behavioral patterns of the online audience, the growing role of social networks, content marketing platforms and the possibilities of targeted advertising are of particular importance. The problem lies in the insufficient adaptation of strategic marketing to the modern conditions of the Ukrainian market, where traditional approaches dominate, not always effective in the digital age. The purpose of the study is to identify effective approaches to promoting the Volkswagen Caddy and Multivan models in the context of digital transformations and a competitive environment. The object is marketing in the automotive industry, the subject is promotion tools adapted to digital channels and local features of the Ukrainian market. To achieve the goal, a set of methods was used: statistical and comparative analysis of official sales data, content analysis of advertising presentations and campaigns, as well as expert surveys of automotive business specialists and marketers. Value / originality. The study covers the period 2019-2024, which allows us to trace the impact of the implemented strategies on sales dynamics and the level of recognition of models among consumers. The author analyzed the brand's marketing strategies, determined the effectiveness of various presentation formats and the role of visual content in the purchase decision-making process. The most effective promotion channels were also identified, including integrated communication platforms, video marketing, personalized email newsletters and SMM campaigns. The results of the study showed that an effective content strategy should be implemented as a flexible system that involves defining business goals, in-depth analysis of the target audience, building a content architecture, selecting relevant formats and channels, planning and regular analytical testing. It is shown that the choice of content formats should be subordinated to the dominant campaign metric: to increase traffic – use viral videos, to maintain attention – long reads and narrative series, to increase conversion – interactive content and online test drives. The conclusions provide practical recommendations for adapting marketing approaches to local conditions, digital trends and the specifics of Ukrainian consumer behavior in the automotive market segment.

Abstract This study focused on Guizhou's traditional fermented wind dried pork. Multiple analytical methods were used to understand its properties. High throughput sequencing was used to analyze microbial composition. Gas Chromatography Ion Mobility Mass Spectrometry (GC-IMS) was used to identify flavor compounds. Nutritional content like protein, amino acids, fatty acids, cholesterol, and nitrite were determined by standard biochemical assays. Physicochemical indicators such as saponification value, peroxide value, acid value, and pH were measured by established procedures. The results showed that Acinetobacter sp. HRBLi 16 , Latilactobacillus sakei , Brochothrix thermosphacta , and Pseudomonas fragi were dominant microbes. Nutritional and physicochemical changes included significant increases in saponification value, peroxide value, acid value, protein, amino acid, and fatty acid contents. Cholesterol content and pH decreased significantly, with nitrite below 1 mg/kg. Among 60 volatile flavor compounds in fermented samples, 11 were unidentifiable, including 6 aldehydes, 13 alcohols, 8 esters, 13 ketones, 6 alkanes, 2 heterocycles, and 1 acid. Multivariate interactive Mantel tests and Pearson correlation analysis revealed positive correlations: fatty acid-acid value; amino acid-cholesterol, acid value, peroxide value; protein-saponification value, pH. Also, volatile flavor compounds related to fatty acids, protein, saponification value, and microbial composition related to saponification value, protein, acid value, pH, cholesterol. These findings aid understanding of fermentation induced changes, offering insights for quality control and product development. Graphical Abstract

Generative Artificial Intelligence (AI) has emerged as a key driver of digital transformation in education, enabling instant personalization of learning and the generation of adaptive content tailored to learners’ abilities and needs. This article aims to explore the potential of such technologies in enhancing educational processes by fostering personalized learning and empowering students to develop self-assessment strategies. The central research problem lies in assessing the effectiveness of generative AI in improving learning outcomes and ensuring content reliability, while addressing ethical and technical challenges such as data protection and the digital divide. The study adopts a descriptive–applied methodology through a field experiment involving 110 primary school students. Tools such as ChatGPT and Midjourney were employed to generate texts, images, and exercises, while both quantitative and qualitative methods were used to analyze students’ interactions and performance. The article is structured around several key axes: the conceptual framework of generative AI in education, mechanisms of real-time content personalization, support for self-directed and self-assessment learning, a practical case study, and the linkage of results to motivational and cognitive comfort theories. Findings indicate that generative AI technologies effectively enhance cognitive comfort, increase student motivation, and improve academic performance, while enabling learners to design interactive self-assessment tests using platforms such as Quizizz AI. These outcomes highlight the innovative contribution of the article, which connects real-time personalized learning with self-assessment practices, opening new perspectives for the didactics of school subjects in the age of generative AI

This quasi-experimental research examined the impact of the Quizlet application on students’ English vocabulary mastery at SMPN 3 Praya Tengah, a rural junior high school located in Central Lombok, Indonesia. The study was conducted in response to students’ limited vocabulary knowledge and the insufficient use of interactive digital learning tools. Thirty seventh-grade students participated and were assigned to experimental and control groups. A 30-item vocabulary test focusing on the topic “Personality and Skills” was administered as both pre-test and post-test. The experimental group underwent five instructional sessions utilizing Quizlet’s interactive modes Flashcards, Learn, Match, and Test while the control group received conventional instruction. The test instrument was validated by expert reviewers, and its reliability coefficient, measured through Cronbach’s Alpha, was 0.87, indicating high internal consistency. Data were processed using SPSS 26, including tests of normality, homogeneity, and an independent samples t-test. Statistical analysis revealed a significant difference between the two groups (t(28) = 3.57, p = 0.002, d = 0.80), resulting in the rejection of the null hypothesis (H?) and acceptance of the alternative hypothesis (H?). These findings demonstrate that Quizlet effectively enhances students’ vocabulary mastery, learning motivation, and autonomy. The results also align with retrieval practice and gamification theories, confirming that Quizlet can serve as an effective digital medium for improving vocabulary acquisition, especially in rural educational settings with limited access to technology This suggests Quizlet can be integrated into junior high school curricula to promote autonomous vocabulary acquisition.

Teaching Pediatric Residents to Evaluate and Screen for Autism in Primary Care Clinics With the Rapid Interactive Screening Test for Autism in Toddlers (RITA-T).

Perimetry Testing in the 10th Decade of Life.

Interactive testing for evaluating the performance of collision avoidance algorithms in multi-ship encounter scenarios

ABSTRACT With the rapid advancement of the renewable energy industry, hydrogen fuel cells, known for their high energy conversion efficiency, low pollution, and minimal noise during operation, remain at the forefront of industrial research. Consequently, the production processes and performance testing methods of hydrogen fuel cells have become essential components in the curricula of relevant educational institutions. This study develops a virtual simulation engineering education software based on Unity3D, specifically designed to facilitate learning for students and educators in secondary vocational, higher vocational, and tertiary institutions regarding hydrogen fuel cell performance testing. By leveraging existing preparatory materials, the software integrates core professional knowledge, such as the working principles and system structures of hydrogen fuel cells. The theoretical and practical teaching content was determined based on course design requirements. Furthermore, the development process was outlined, including software design, model and scene construction, implementation of interactive functions, software testing, and deployment. Evaluation of the software's functionality and educational effectiveness revealed positive feedback from both teachers and students. The software enhanced students' understanding of hydrogen fuel cell performance testing, improved teaching and learning efficiency, and contributed to greater educational equity.

Interpreting naturalistic multi-vehicle interactions is vital for human-like autonomy and interactive testing. We model interactions from a group perspective, a common yet understudied phenomenon. A framework is proposed for learning spatiotemporal interaction patterns from vehicle groups. A Multi-Vehicle Interaction Directed Network (MIDN) is introduced and constructed from interaction strength (IS) and spatial relations, with influences from non-neighbouring vehicles incorporated. Patterns are analysed with an Attention Auto-encoder and k-means. Using naturalistic trajectory data, the approach is validated: groups are identified with high within-group and low between-group IS, and chained groups are found to be more prevalent than multi-lane groups. Six interpretable patterns are identified - Increasing/Decreasing Backward (IBT/DBT), Increasing Forward (IFT), Rear Decreasing (RDT), Overall Maintenance (OMT), and Multiple Fluctuations (MFT) - and are shown to correlate with speed and acceleration profiles. The findings are expected to support human-like planning in autonomous vehicles, the construction of test scenarios, and roadside traffic safety monitoring.

Contrary to earlier studies that identified national competitiveness as the chief determinant of a nation’s Gross Domestic Product (GDP) and economic growth, this research pivots towards the intricate dynamics of social and cognitive waves. We explore the social wavefunctions, especially in the context of innovation and institutional structures within cognitive waves. These wavefunctions, intricately interlinked, evolve within societies, driving social transformations and shifts. Our main thesis emphasizes the crucial roles of innovation and policy decisions. Our empirical focus is on India, a burgeoning economy, using statistical panel data from the Global Competitiveness Index (GCI) covering the years 2007 to 2018. Through comprehensive interactive testing, we present our results across 9 tables and 7 figures. The findings illustrate that societal evolution manifests through changing patterns influenced by social, economic, and political forces, often producing unexpected results. These insights highlight the pivotal interplay between innovation capacities and institutional policy choices as key drivers of economic growth. This study charts a new course for research and, from the perspective of Quantum Mechanics entanglement, provides a novel understanding of the sustainability of human societal evolution.

BackgroundTo examine the correlation between Humphrey visual field analyzer and an automated virtual reality perimetry test (Oculera visual field analyzer) in glaucoma patients and healthy individuals.MethodsThis prospective, single-center study was conducted on 93 eyes of 93 patients, 55 of whom were glaucoma patients (glaucoma group) and 38 healthy subjects (normal group). HFA II (24-2, Swedish Interactive Threshold Algorithm) and Oculera (24-2, Oculera Interactive) tests were applied to all participants. Mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI) values of both devices were obtained. The correlation between the two devices was evaluated by statistical analyses of MD, PSD, and VFI.ResultsThe MD values were -6.36 dB (-31.8 to 2.27) for HFA II and -5.80 dB (-29.1 to 2.2) for Oculera. The difference between MDs of Oculera and HFA II was -0.56 dB. Wilcoxon signed-rank test showed a statistically significant difference in MD values between Oculera and HFA II (p < 0.001). However, there was a strong correlation between MDs (r = 0.932 and p < 0.001). With this, the results of the Bland-Altman analysis evaluating the agreement between the two tests showed that the differences between the MD measurements were not within the acceptable error range and that the results of the devices could not be used interchangeably. A strong correlation was found between the two devices in terms of PSD and VFI values (r = 0.752, r = 0.910, respectively).ConclusionsThe current findings are promising for the future use of Oculera in the diagnosis and follow-up of glaucoma patients.

Parenting stress in autism spectrum disorder: A comparative analysis with other developmental disabilities.

Developing secure and well-structured web applications using Spring Boot presents a significant challenge, as it requires developers to manage multiple layers, employ framework-specific annotations, and ensure authentication, authorization, and compliance with architectural standards. These complexities often lead to errors among students and novice developers. Although current low-code platforms reduce coding effort, they frequently compromise clarity, modularity, and maintainability. This paper introduces XBoot, a lightweight framework that utilizes a straightforward XML-based domain-specific language (DSL) to automatically generate modular and secure Spring Boot applications. By providing concise specifications for entities, services, routes, and user roles, XBoot generates database entities, service classes, controllers, user interface templates, and integrated security rules. Validation rules are directly enforced from the DSL, and built-in Swagger documentation facilitates interactive API testing. The evaluation was conducted in two phases. Initially, XBoot was validated by generating applications for student–course and flight-booking domains, where less than 50 lines of DSL resulted in 950–1350 lines of Java and HTML code, complete with security and documentation. Subsequently, 10 undergraduate students utilized XBoot in practice. All participants successfully generated and deployed applications within 2–20 min (average ≈ 7), compared to 45–120 min for manual implementation. On a 5-point Likert scale, students rated the reinforcement of layered architecture at an average of 4.0. These findings suggest that XBoot effectively eliminates common structural and security errors, reduces boilerplate complexity through concise DSL specifications, and maintains modularity and transparency-limitations often observed in traditional coding and other low-code platforms.

The article deals with the analysis of research dedicated to creating multimedia training resources in the form of complexes, courses, etc. Reasonability of the creation of a multimedia training complex for learning the C# language is justified. For the purpose of determining the details and contents of the complex, an online meeting with the 2nd year students specialising in Publishing and Printing within the framework of the Programming of Multimedia Means subject has been held. This allowed us to identify the complex and incomprehensible aspects of C# syntax, code writing, creating visual interfaces, etc., that students face when learning the art of C# programming. As a result, the content presented in the training complex in the form of visualised audio and video hints and advice, interactive exercises, training video simulations and games has been determined. The structure and design of the C# Quick Leaning multimedia training complex have been suggested. Examples of pages with theoretical work material have been provided. Appearance of interactive tasks and training video simulations has been shown. Attention has been paid to the organisation of the development of interactive tests with signature scripts. This has allowed separating undergoing testing in terms of every lesson, topic and final test and showing the results of each of them. Special features of the development of three training games of various genres as powerful structural and content elements of the multimedia complex have been demonstrated. The inclusion of game elements to the complex supports the increase of the degree of understanding and consolidation of the training material by the users. Implementation of the multimedia training complex and its interactive components (interactive exercises, tasks, training video simulations, games and tests) is conducted in the Adobe Captivate environment. The developed complex is used while studying the Programming of Multimedia Means in order to simplify mastering the art of programming for students specialising in Publishing and Printing. The materials provided in the article may be used as a source of information while developing multimedia interactive training resources.