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The present study employed the draw-a-picture technique and epistemic network analysis (ENA) to reveal university students' viewpoints on ChatGPT-supported learning, as well as the conceptions, roles, and educational objectives of ChatGPT-supported learning among university students with different learning attitudes. The results showed that university students' conceptions of ChatGPT-supported learning were diverse and interrelated. Most students agreed that ChatGPT could facilitate learning anytime and anywhere, and held positive emotions and attitudes. In the conceptions of ChatGPT-supported learning, there were significant differences in the four categories of locations, learning content, learning activities, and objects between the low learning attitude (LLA) and the high learning attitude (HLA) groups. Besides, the HLA group preferred to use ChatGPT for specific learning content, and showed higher levels of engagement in discussions and consultations. The LLA group was inclined to use ChatGPT at home or in places with traditional classroom equipment for completing reports or assignments. Most students in the HLA group regarded ChatGPT as a tutor, while those in the LLA group viewed it as a tool. Based on the above findings, this study puts forward some suggestions for how to implement ChatGPT-supported learning in higher education as a reference for educators, researchers and training developers. [ABSTRACT FROM AUTHOR]

Researchers have indicated the importance of engaging learners in self-regulated learning (SRL) states when situated in game-based learning contexts; however, it remains a challenge for both educational and educational technology researchers to effectively integrate both. To this end, this study investigated how SRL strategies are interwoven with game-based learning in higher education by searching the web of science database to systematically review the papers published between 2009 and 2020 in academic journals. The encoded dimensions ranged from the primary research purpose to research issues, including application domains, research methods, duration of the studies, SRL strategies, game types, and game genres. It was found that since 2015, the research purposes have become increasingly diverse, with skills acquisition in game-based learning being regarded as the most important goal, followed by knowledge acquisition and behavior change. Such games took goal orientation, peer learning, and regulating as the main SRL strategies, which exerted a positive effect on learning performance, self-efficacy/confidence, attitudes/effort, satisfaction/interest, and learning behavior. Meanwhile, these SRL strategies were well embedded into problem-solving, simulation, multi-type, and RPG game types against the setting of the real-life-related storyline as the main game genre. Since previous studies lacked the systematic application of all SRL strategies within a game-based learning environment, they could not uncover the dynamic and cyclic processes of SRL in game-based learning environments. Hence, this study proposed corresponding suggestions for future research issues as a reference for researchers, teachers, and decision-makers. [ABSTRACT FROM AUTHOR]

The present study employed the draw-a-picture technique and epistemic network analysis (ENA) to reveal university students’ viewpoints on ChatGPT-supported learning, as well as the conceptions, roles, and educational objectives of ChatGPT-supported learning among university students with different learning attitudes. The results showed that university students’ conceptions of ChatGPT-supported learning were diverse and interrelated. Most students agreed that ChatGPT could facilitate learning anytime and anywhere, and held positive emotions and attitudes. In the conceptions of ChatGPT-supported learning, there were significant differences in the four categories of locations, learning content, learning activities, and objects between the low learning attitude (LLA) and the high learning attitude (HLA) groups. Besides, the HLA group preferred to use ChatGPT for specific learning content, and showed higher levels of engagement in discussions and consultations. The LLA group was inclined to use ChatGPT at home or in places with traditional classroom equipment for completing reports or assignments. Most students in the HLA group regarded ChatGPT as a tutor, while those in the LLA group viewed it as a tool. Based on the above findings, this study puts forward some suggestions for how to implement ChatGPT-supported learning in higher education as a reference for educators, researchers and training developers. [ABSTRACT FROM AUTHOR]

Background and purpose: This study was undertaken to investigate the longitudinal impact of type 2 diabetes mellitus (T2DM) on the prodromal and dementia stages of Alzheimer disease (AD), focusing on diabetes duration and other comorbidities. Methods: A total of 1395 dementia‐free individuals aged 55–90 years with maximum 15‐year follow‐up data were enrolled from the Alzheimer's Disease Neuroimaging Initiative database. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) of the incidence of prodromal or dementia stages of AD. Results: Longer T2DM duration (≥5 years; multiadjusted HR = 2.19, 95% confidence interval [CI] = 1.05–4.58), but not shorter T2DM duration (<5 years), was associated with a significantly increased risk of incident prodromal AD over a mean follow‐up of 4.8 years. APOE ε4 allele (HR = 3.32, 95% CI = 1.41–7.79) and comorbid coronary artery disease (CAD; HR = 3.20, 95% CI = 1.29–7.95) further increased the risk of incident prodromal AD in patients with T2DM. No significant association was observed between T2DM and the risk of progression from prodromal AD to AD dementia. Conclusions: T2DM, which is characterized by a longer duration, increases the incidence risk of prodromal AD but not AD dementia. APOE ε4 allele and comorbid CAD strengthen the relationship between T2DM and prodromal AD. These findings highlight T2DM characteristics and its comorbidities as predictors for accurate prediction of AD and screening of at‐risk populations. [ABSTRACT FROM AUTHOR]

Mesembryanthemum crystallinum L. (ice plant) develops salt tolerance during the transition from the juvenile to the adult stage through progressive morphological, physiological, biochemical, and molecular changes. Myo -inositol is the precursor for the synthesis of compatible solute D-pinitol and promotes Na+ transport in ice plants. We previously showed that supplying myo -inositol to 9-day-old seedlings alleviates salt damage by coordinating the expression of genes involved in inositol synthesis and transport, affecting osmotic adjustment and the Na/K balance. In this study, we examined the effects of myo -inositol on physiological parameters and inositol-related gene expression in early- and late-stage juvenile plants. The addition of myo -inositol to salt-treated, hydroponically grown late juvenile plants had no significant effects on growth or photosynthesis. In contrast, supplying exogenous myo -inositol to salt-treated early juvenile plants increased leaf biomass, relative water content, and chlorophyll content and improved PSII activity and CO2 assimilation. The treatment combining high salt and myo -inositol synergistically induced the expression of myo -inositol phosphate synthase (INPS), myo -inositol O -methyltransferase (IMT), and inositol transporters (INTs), which modulated root-to-shoot Na/K ratio and increased leaf D-pinitol content. The results indicate that sufficient myo -inositol is a prerequisite for high salt tolerance in ice plant. Ice plant (Mesembryanthemum crystallinum L.) increases salt tolerance as it grows and develops. Supplying myo -inositol to ice plant in its early juvenile stage helps it grow and photosynthesise in a high-salt environment. The roles of myo -inositol in osmotic adjustment and sodium compartmentation should be further explored in both glycophytes and halophytes. [ABSTRACT FROM AUTHOR]

Background: With the wide application of QCT in the clinical assessment of osteoporosis and sarcopenia, the characteristics of musculoskeletal degeneration in middle-aged and elderly people need to be further revealed. We aimed to investigate the degenerate characteristics of lumbar and abdominal muscles in middle-aged and elderly people with varying bone mass. Methods: A total of 430 patients aged 40–88 years were divided into normal, osteopenia, and osteoporosis groups according to quantitative computed tomography (QCT) criteria. The skeletal muscular mass indexes (SMIs) of five muscles [abdominal wall muscles (AWM), rectus abdominis (RA), psoas major muscle (PMM), posterior vertebral muscles (PVM), and paravertebral muscles (PM)] included in lumbar and abdominal muscles were measured by QCT. Differences in SMIs among three groups, as well as the correlation between SMIs and volumetric bone mineral density (vBMD) were analyzed. The areas under the curves (AUCs) for SMIs for prediction of low bone mass and osteoporosis were calculated. Results: In male group, SMIs of RA and PM in osteopenia group were significantly lower than those in the normal group (P = 0.001 and 0.023, respectively). In female group, only SMI of RA in osteopenia group was significantly lower than that in the normal group (P = 0.007). SMI of RA was positively correlated with vBMD with the highest coefficients in male and female groups (r = 0.309 and 0.444, respectively). SMIs of AWM and RA had higher AUCs varying from 0.613 to 0.737 for prediction of low bone mass and osteoporosis in both genders. Conclusions: The changes of SMIs of the lumbar and abdominal muscles in patients with varying bone mass are asynchronous. SMI of RA is expected to be a promising imaging marker for predicting abnormal bone mass. Trial registration: ChiCTR1900024511 (Registered 13–07-2019). [ABSTRACT FROM AUTHOR]

Background: With the wide application of QCT in the clinical assessment of osteoporosis and sarcopenia, the characteristics of musculoskeletal degeneration in middle-aged and elderly people need to be further revealed. We aimed to investigate the degenerate characteristics of lumbar and abdominal muscles in middle-aged and elderly people with varying bone mass. Methods: A total of 430 patients aged 40–88 years were divided into normal, osteopenia, and osteoporosis groups according to quantitative computed tomography (QCT) criteria. The skeletal muscular mass indexes (SMIs) of five muscles [abdominal wall muscles (AWM), rectus abdominis (RA), psoas major muscle (PMM), posterior vertebral muscles (PVM), and paravertebral muscles (PM)] included in lumbar and abdominal muscles were measured by QCT. Differences in SMIs among three groups, as well as the correlation between SMIs and volumetric bone mineral density (vBMD) were analyzed. The areas under the curves (AUCs) for SMIs for prediction of low bone mass and osteoporosis were calculated. Results: In male group, SMIs of RA and PM in osteopenia group were significantly lower than those in the normal group (P = 0.001 and 0.023, respectively). In female group, only SMI of RA in osteopenia group was significantly lower than that in the normal group (P = 0.007). SMI of RA was positively correlated with vBMD with the highest coefficients in male and female groups (r = 0.309 and 0.444, respectively). SMIs of AWM and RA had higher AUCs varying from 0.613 to 0.737 for prediction of low bone mass and osteoporosis in both genders. Conclusions: The changes of SMIs of the lumbar and abdominal muscles in patients with varying bone mass are asynchronous. SMI of RA is expected to be a promising imaging marker for predicting abnormal bone mass. Trial registration: ChiCTR1900024511 (Registered 13–07-2019). [ABSTRACT FROM AUTHOR]

Learning analytics and educational data mining aim to enhance teaching and learning outcomes by utilizing data and analytical methods. Online learning systems provide a wealth of data that enable educators to understand students’ needs and offer appropriate support. This study used bibliometric analysis to examine the distribution of research subjects, educational stages, pedagogical approaches, machine learning algorithms, algorithm evaluation, and keywords in online learning from 2013 to 2022, encompassing the pre-pandemic, mid-pandemic, and post-pandemic periods. The findings indicated that the analyzed studies primarily focused on analyzing students’ experiences in online learning systems, while paying limited attention to teachers’ perspectives. Additionally, the majority of research concentrated on higher education, with insufficient attention given to pre-college education. Regarding pedagogical approaches in online learning environments, there was a notable absence of detailed descriptions of teaching processes, with greater emphasis placed on the interaction between students and online learning platforms. The study also examined the evolution of keywords across three periods: the pre-pandemic (2013–2018), the mid-pandemic (2019–2020), and the post-pandemic (2021–2022) periods. Finally, several recommendations for future research are provided. [ABSTRACT FROM AUTHOR]

Due to the rapid changes in global economic environments, enterprises have to continually enhance their business competitiveness. To improve business, planning educational training has been regarded as a channel to educate outstanding employees. Recently, most of the companies in the securities industry in Taiwan have adopted web-based educational training as a form of employee training. However, low e-learning acceptance on the part of employees is the essential obstacle when enterprises attempt to promote web-based continuing learning. Previous studies have shown that hardiness and Internet self-efficacy may be important factors that influence whether an individual will continue with web-based learning when facing pressure. Securities practitioners are required to deal with high pressure and persist in enhancing their professional knowledge in their working environment; therefore, continuing learning is crucial to maintaining the quality of professional service. The present study recruited securities practitioners as the research participants, and examined the effects of hardiness and Internet self-efficacy on their attitudes towards web-based learning when they were participating in web-based learning. The findings revealed that securities practitioners' hardiness and Internet self-efficacy both had direct positive effects on their attitudes towards web-based continuing learning. Meanwhile, their Internet self-efficacy had a mediating effect on the relationships between hardiness and attitudes towards web-based continuing learning. [ABSTRACT FROM AUTHOR]

People are constantly exposed to blue light while engaging in work. It is thus crucial to understand if vast exposure to blue light influences cognitive control, which is essential for working efficiently. Previous studies proposed that the stimulation of intrinsically photosensitive retinal ganglion cells (ipRGCs), a newly discovered photoreceptor that is highly sensitive to blue light, could modulate non-image forming functions. Despite studies that showed blue light (or ipRGCs) enhances brain activations in regions related to cognitive control, how exposure to blue light changes our cognitive control behaviorally remains elusive. We examined whether blue light influences cognitive control through three behavioral tasks in three studies: the sustained attention to response task (SART), the task-switching paradigm, and the Stroop task. Classic effects of the SART, switch cost, and the Stroop effect were found, but no differences were observed in results of different background lights across the six experiments. Together, we conclude that these domains of cognitive control are not influenced by blue light and ipRGCs, and whether the enhancement of blue light on brain activities extends to the behavioral level should be carefully re-examined. [ABSTRACT FROM AUTHOR]

The means through which the university libraries provide access to electronic resources (e-resources) for their patrons and the way they operate could be enhanced through an authentication system. Such a system can help address the challenges of seamless access to e-resources for patrons, and can also provide information for university librarians to further understand and explore patrons' demands. The purpose of this study was to investigate the perception gap (i.e., importance and satisfaction) of university librarians regarding authentication services, and their attitudes towards the visualization of online libraries' usage logs. Moreover, this study developed a dashboard platform to visualize readers' behavior when using online resources and to understand university librarians' attitudes towards the library statistics dashboard. As a result, it was found that one system quality attribute and two information quality attributes were identified as high priorities for the intervention. University librarians gave positive feedback on the library statistics dashboard that can present visualizations of the authentication logs to further explore patron behavior of using e-resources. This also shows that the results can help identify strategic focus areas to evaluate authentication systems and library statistics dashboard as alternative technologies to assist university librarians in exploring patrons' e-resource usage behaviors. • To investigate university librarians' perceived gaps of authentication services and their attitudes towards the log visualization. • This study was conducted within the framework of importance-performance analysis (IPA). • One system quality attribute and two information quality attributes were identified as the focus of the intervention. • The dashboards of the authentication system could further explore patron behavior of using e-resources. [ABSTRACT FROM AUTHOR]

Background: Due to declining birthrates and an increasing aging population, shortage of the caregiving labor force has become a global issue. Among various efforts toward the solution, introducing robotic products for assistance could provide an effective way to help older adults in their daily lives. As previous studies have indicated that older adults' acceptance of robots is lower than that of younger adults, enhancing older adults' acceptance of robots is imperative. Because older adults' first impressions based on a robot's appearance might affect their acceptance of the robot, we investigated the uncanny valley effect (UVE) here. The UVE refers to the phenomenon that people rate robots more positively as robots become more humanlike, but only up to a certain point; as robots approach a near-perfect similarity to human appearance, likeability drops and forms the uncanny valley. Nevertheless, evidence for the UVE came mainly from younger adults.Objective: The present study aimed to examine whether the UVE varies across different age groups and whether a robot's appearance would affect participants' acceptance of the robot's service or companionship.Methods: An online questionnaire study was conducted with 255 participants, including younger (n = 77, age 18-39 years), middle-aged (n = 87, age 40-59 years), and older (n = 91, age 60-87 years) adults. Participants were asked to view each picture in a set selected from a total of 83 robot pictures and evaluate their impressions of each robot and the intention of use regarding robot function as a service provider or a companion.Results: The UVE was found in younger and middle-aged adults; however, older adults did not show the UVE. Older adults preferred humanlike over non-humanlike robots, regardless of robot function.Conclusion: The design of assistive robots should take the UVE into consideration by customizing robot appearance based on the age group of the intended user. [ABSTRACT FROM AUTHOR]

This study conducted a systematic review to identify the mainstreams of contemporary digital reading research. We performed a co-citation network analysis to examine the streams and features of key topics in digital reading research. We also performed content analysis and used the bibliometrix R-package to map digital reading research themes and identify several trends in the field. In this study, we (a) identified three mainstreams of research within the digital reading co-citation network (namely, differences in reading comprehension between print books and e-books, adolescents' habits and preferences related to digital reading and their digital reading literacy, and the analysis of reading behaviors as well as the use of interactive learning books); (b) determined that most studies on digital reading have employed quantitative or mixed methods, involved the use of tests and questionnaires to evaluate learners' performance, and have not focused on specific application domains or learning strategies; and (c) discovered that most studies on digital reading had investigated the affective aspects of learners' experiences, followed by cognition, learning behavior, and correlation or cause-and-effect analysis. We identified "engagement," "digital media," and "digital literacy" as key topics in research on digital reading. Directions for future research and digital reading education are provided.. [ABSTRACT FROM AUTHOR]

Based on the Technology-based Learning model, the present study reviews the published papers on mobile technologies in Hospitality, Leisure, Sport and Tourism (HLST) education in the Scopus database from 2002 to 2017. Various dimensions, including application domains, research issues, research sample groups, research methods, adopted technologies, and learning strategies are taken into account. It was found that, since 2010, the research issues of mobile technology-supported HLST education have become increasingly diverse. Most of the studies investigated learners' affect issues, while there was also a focus on learners' attitudes, motivation and learning experiences. Moreover, wireless Internet locating (e.g. Bluetooth or Zigbee) was adopted more frequently in mobile technology-supported HLST education, while sensing technologies were seldom adopted. As for mobile devices, with the development of technologies, smart phones and tablet computers became the main devices. In addition, such extensively adopted mobile learning strategies as synchronous sharing, issue-based discussion, computers as mindtools, and game-based learning were not adopted in the studies, indicating that most previous studies focused more on learners' learning perceptions, knowledge delivery and skills training, while less effort has been made to cultivate learners' higher order thinking, such as problem solving, critical thinking and collaborative competences. Accordingly, potential research issues and practitioner notes of mobile technology-supported HLST education are proposed as a reference for researchers, teachers and decision-makers. [ABSTRACT FROM AUTHOR]

In recent years, smart healthcare technologies used to facilitate precision medicine in clinical practice have increasingly become a topic of discussion. Nurses and nurse preceptors are critical professionals in hospitals, and are also the frontline staff using smart healthcare. The purpose of this study was to investigate nurses' and nurse preceptors' perceptions of smart healthcare (including learning motivation, learning attitudes, and personal innovativeness) and the differences in their conceptions of learning in smart healthcare technology contexts. The research findings showed that nurse preceptors had higher mean scores than nurses for learning motivation, learning attitudes, and personal innovativeness in smart healthcare, especially for learning attitudes and personal innovativeness. The nurse preceptors' conceptions of learning in smart healthcare technology contexts were also more diverse than those of nurses. The main differences are that nurses' drawings showed a healthcare setting where learners (both patients and nurses) use computers to connect to cloud services for online visits, and where patients can engage in online health education learning activities via computers or mobile devices. The nurse preceptors' drawings focused on the delivery of nursing knowledge and skills to learners via VR technologies, helping diagnose patients, analyzing medical data, and predicting healthcare through smart healthcare technologies. [ABSTRACT FROM AUTHOR]

Inappropriate clamping force in bolted flange joints operated at high temperatures has been regarded as the main issue that endangers the reliability and safety of a plant. In order to accurately and reliably measure the bolt clamping force, an innovative technique is proposed using metal-packaged fiber Bragg grating (RFBG) sensors. A metal-packaged RFBG sensor is developed by a combination of magnetron sputtering and electroplating followed by spot-welding on a bolt, and calibrated by uniaxial tensile and thermal tests. The clamping force in a bolted steel-steel joint is monitored by the metal-packaged RFBG sensor spot-welded on the bolt and analyzed by a finite element model. The sensor exhibits good linear response to axial loads applied to the bolt when exposed to constant high temperatures up to 500 °C, as well as good stability and repeatability. Its thermal response is non-linear and can be expressed as a cubic-polynomial function of temperature. The variation of the clamping force in the bolted joint subjected to thermal loading is then monitored by the sensor, which is further verified by a comparison of the experimental results and the numerical predictions showing a satisfactory agreement. The results demonstrate that this technique provides a new possibility for real-time monitoring of bolt clamping force and structural health monitoring of bolt joint structures operating in high-temperature environments. [ABSTRACT FROM AUTHOR]

As one of the most important economic fishes, largemouth bass (Micropterus salmoides) is being widely farmed around the world. With the improper expansion and high-density culture, largemouth bass is susceptible to an increasing number of pathogens. Particularly, co-infection of multiple pathogens is ubiquitous, which has become a main obstacle to the development of largemouth bass industry. In the study, a co-infected case caused by Aeromonas dhakensis (A. dhakensis) and Chryseobacterium indologenes (C. indologenes) in largemouth bass was firstly reported. Diseased fish with clinical signs such as exophthalmia, hemorrhage on gill cover, rot or ulceration on gill, skin and fin were collected for further diagnostics. Tissue lesions of liver, spleen and kidney were observed, such as necrosis, hemorrhage, vacuolization and disintegration. Two bacteria strains were isolated from liver, one appeared as a white or yellowish colony, and the other was characterized by golden yellow color. Based on the conjoint analysis of 16S rRNA and gyrB gene sequences, the isolated strains were identified as A. dhakensis and C. indologenes , respectively. Antibiotic sensitivity testing indicated that both A. dhakensis and C. indologenes were sensitive to flumequine, enrofloxacin, ceftazidime and minocycline, and resistant to penicillin, sulfamethoxine sodium, ampicillin and cefamezin. Largemouth bass showed similar clinical signs and tissue lesions to naturally diseased fish following co-infection with the isolated strains, indicating that the isolated strains fulfill Koch's postulates. Besides, a slightly increased pathogenicity was observed following co-infection compared with single infection. The data firstly reveal a co-infected case caused by A. dhakensis and C. indologenes in largemouth bass, not only enriching the relevant information of largemouth bass diseases, but also promoting the diagnosis, prevention and control of A. dhakensis and C. indologenes co-infection. • Co-infection of A. dhakensis and C. indologenes in largemouth bass is firstly reported. • Conjoint analysis of 16S rRNA and gyrB is performed to identify the isolated strains. • Both A. dhakensis and C. indologenes show sensitive to flumequine, enrofloxacin, ceftazidime and minocycline. • The isolated A. dhakensis and C. indologenes fulfill Koch's postulates. [ABSTRACT FROM AUTHOR]

This research reviews 56 robots in science education (RSE) research articles published in SSCI (Social Sciences Citation Index) journals in the Web of Science (WoS) database. The analysis results showed that there were three clusters of RSE studies: robots in elementary science education, robot-based STEM activities, and robot-facilitated computational thinking. In terms of the research issues, more studies were conducted across-disciplines. Regarding thematic classifications, "general benefits of educational robots" was the most frequently investigated issue, while "diversity and broadening participation," and "creativity and motivation" were less frequently discussed. The most adopted research methods were quantitative and mixed methods, focusing on measuring learners' cognition and affect. Most of the interventions in the empirical studies adopted pedagogical interventions. In terms of the interaction issue, LEGO was adopted the most, followed by self-made robots; moreover, robots frequently played the role of tools in science education. From the perspective of specific robotics content knowledge, "control" (e.g. programming) comprised the majority. The most adopted learning strategy was project-based learning, followed by issue-based discussion. Regarding assessment issues, the most adopted evaluation approaches to evaluating students' performance were questionnaires, observation, verbal interviews, and artifacts to assess the quality of learning activities. [ABSTRACT FROM AUTHOR]

In recent years, the application of the metaverse in higher education has attracted the attention of numerous educators and researchers. It allows students to engage in immersive experiential learning and to experience a variety of real human interaction modes. Researchers have pointed out that although the introduction of emerging technologies may bring a sense of novelty, it cannot sustain student learning for a long time. Learners' learning performance still depends on their learning motivation. The present study aimed to explore the conceptions and perceptions (i.e., growth mindset, learning attitudes, and self-efficacy) of students with different motivation levels regarding the metaverse in higher education. A draw-a-picture analysis and surveys were conducted. The results indicated that most students believed that with the metaverse, they could learn the knowledge of unspecified subject domains in any location, realizing the idea of studying for practical application. In the drawings of students with low motivation levels, they still conducted static learning activities (i.e., reading/studying, and searching for sources) in the metaverse learning environment. On the other hand, students with high motivation levels focused on experiential learning, operation, or practice (i.e., hands-on practicing/performance and observing/experiencing). Moreover, the students with high motivation levels generally show better growth mindsets, learning attitudes, and self-efficacy than those with low motivation levels. This implies that learning motivation could be an important factor affecting students' growth mindsets, learning attitudes, and self-efficacy of learning with the metaverse. The findings of this study serve as a foundation for future research, and provide preliminary evidence for understanding the conceptions of students with different motivation levels regarding the metaverse in higher education. Lastly, based on the analytic results, this study puts forward suggestions for the learning approaches of students in the metaverse as a reference for future researchers and teachers in higher education to design related activities. • Students' conceptions and perceptions of learning with the metaverse are analyzed. • The subjects are university students with different motivation levels. • A draw-a-picture analysis and surveys are employed in this study. • Most students believed that the metaverse would help them learn better. • High motivation students had better growth mindsets, attitudes, and self-efficacy. [ABSTRACT FROM AUTHOR]

• A shadowless lighting approach improves performance of solar optical reflection lighting system. • A fast and simple parameter design method is developed for shadowless lighting. • Effectiveness of shadowless lighting approach is verified by the application in real tunnel. A solar optical reflection (SOR) lighting system has been developed to illuminate the threshold zone of short freeway tunnel in the premise of zero energy consumption. To improve the limited illumination performance of SOR lighting system due to the obstruction of moving vehicles on reflected sunlight rays, this study develops a fast and simple parameter design method for shadowless lighting based on an array of multiple SOR lighting systems that makes reflected sunlight emit to the threshold zone from different angles. The effectiveness of shadowless lighting is verified by the application on a two-lane freeway of Shaanxi Province, China. Results show that the shadowless lighting can significantly improve the illuminance in threshold zone, and the improvement rate is higher for the area farther from the tunnel entrance inside the tunnel. In order to achieve shadowless lighting avoid both the vehicle and inter-system blocking on reflected sunlight, the systems should be installed roadside in a staggered array that: 1) their heights descend and lateral distances from the curb shrink in turn from near to far from the tunnel entrance, with as small vertical and horizontal deflection angles of the reflectors as possible, or 2) their heights remain identical with a reduction in the vertical deflection angles of the reflectors from near to far from the tunnel entrance. [ABSTRACT FROM AUTHOR]

Collaborative argumentation supported by argumentation mapping is important for developing college students’ argumentation ability. However, in conventional argumentation mapping-supported collaborative argumentation (AM-CA) activities, learners tend to quickly reach consensus without sufficient discussion and negotiation, or fail to spontaneously assess and integrate the group’s ideas, thus failing to develop more comprehensive and in-depth arguments. Therefore, this study proposed a six thinking hats strategy-based dialogic peer feedback approach to support AM-CA activities, which was expected to support students’ iterative negotiation and deeper interactions through dialogic peer feedback, thus enhancing the quality of argumentation. To show the effectiveness of the proposed approach, this study used a quasi-experimental method to test the proposed strategy in a freshman seminar class at a university. The control group (22 students) used the conventional AM-CA (C-AM-CA) approach, while the experimental group (22 students) used the six thinking hats strategy-based AM-CA (STH-AM-CA) approach. The findings showed that STH-AM-CA improved the quality of argumentation mapping compared to C-AM-CA, but it also significantly increased the learners’ cognitive load. In addition, a thematic inductive qualitative analysis of the interview data demonstrated the strengths and weaknesses of each strategy. [ABSTRACT FROM AUTHOR]

This study provides research-based evidence to profile: (1) the roles of artificial intelligence in nursing, (2) its research applications, and (3) the research trends for future study. On the basis of the PRISMA statement, a series of AI and nursing education related keywords from the literature were used to retrieve high-quality journal articles from the Web of Science. A total of 112 AI-supported nursing education research articles were analyzed based on a three-dimensional framework, including interaction (e.g. the roles of AI, types of AI systems), research (e.g. methods and fields), and performance (e.g. research groups and measurement foci). The results revealed that AI played a primary role in profiling and prediction in nursing research (63%), and the most used AI system in nursing was intelligent agents (53%). The quantitative approach (87%) was the dominant research method, and the most relevant studies concerned health and medicine (92%). Regarding sample and measurement matters, patients and medical staff (75%) were the two primary research samples, and the performance evaluation of AI-related tools and systems (90%) was the core measurement focus. Additional content analysis across the three research interests was performed and discussed. Directions for future studies are provided. [ABSTRACT FROM AUTHOR]

AbstractWith its increasing popularity, understanding learners’ perceptions of online education has become more important. The present study employed drawing analysis to examine university students’ conceptions of online learning and how students with different self-regulation statuses conveyed their ideas through drawing. A total of 58 Taiwanese university students were recruited in the present study. In order to explore their conceptions of realistic and idealistic online learning, they were required to produce two drawings based on the guiding questions. Besides, this study employed a questionnaire to understand university students’ online learning self-regulation. Based on the analysis of the drawings of realistic and idealistic online learning, it was found that students intended to shift their attention from individual (realistic) to group participation (including peers and teachers) (idealistic); they also cared about the learning spaces, windows and facilities (e.g. air conditioning), and a comfortable and quiet learning environment (idealistic). In addition, students with a higher level of self-regulation believed that an idealistic online learning context should include doors/windows, while those with a lower level of self-regulation drew symbols or words related to negative emotions in realistic online learning contexts. These results mean that the higher self-regulated students could better control and manage their learning time and progress independently, so they needed more flexibility and control to manage their learning environment. Finally, the implications and directions for future research are provided based on the findings. [ABSTRACT FROM AUTHOR]

This research reviewed the publications in the Scopus database in the museum-based mobile learning field based on the technology-based learning review model from 2008 to 2019. The aim of this study was to investigate trends in the field of museum-based mobile learning from the main journals and papers, including countries and areas, participants, research methods, learning domains, the orientation of adopted sensing or location-based technologies, learning strategies, and research topics. The cluster and co-occurrence analysis methods were used to analyze the main key terms and the relationships between them. Three thematic clusters, namely strategies and media for mobile-based museum learning, personalized supports for mobile-based museum learning, and applications of mobile-based museum learning were identified. The results show that inquiry-based learning was the most adopted learning strategy for higher education, while contextual mobile learning was the most frequently employed strategy for elementary school students; such extensively adopted mobile learning strategies as peer assessment, project-based learning, video sharing, and synchronous sharing were not adopted in the studies. In addition, an important finding in the literature of the main research purpose of museum-based mobile learning research is the affective domain, followed by the influence of learner characteristics and the effects of mobile learning. [ABSTRACT FROM AUTHOR]

This study reviewed the mobile technology-supported music education (MTSME) studies published in several academic databases, namely Scopus, WOS, ERIC, and RILM, from 2008-2019. Based on the technology-based learning model, the application domains, research issues, sample groups, research methods, adopted devices, and learning strategies were examined. In addition, visual categorization analysis was conducted to further analyze the keywords adopted in the studies. The results show that the number of MTSME studies increased in the time period. It was also found that a majority of studies mainly focused on learner perceptions (e.g. learning reception, learning attitude, and learning motivation). Tablet computers were the most frequently adopted mobile devices. In terms of learning strategies, guided learning, project-based learning, and inquiry-based learning were extensively used in the MTSME studies. In addition, the results of the keyword analysis showed three thematic clusters of MTSME studies, namely "mobile technology-supported teaching management and learning design," "developing appropriate music educational resources for different educational levels," and "mobile technology facilitated learning motivation in music education." According to the research results, several suggestions for future research are proposed. [ABSTRACT FROM AUTHOR]

Abstract: A series of nano-gold catalysts supported on binary oxides MO x –CeO2 (atomic ratio M/Ce=1:1, M=Mn, Fe, Co, Ni) are prepared by deposition–precipitation (DP). An innovative and rather convenient ultrasonic pretreatment of the support is employed for Au/MnO x –CeO2 preparation. It is found that for preferential CO oxidation Au/MnO x –CeO2 is more active than Au/CeO2. Ultrasonic pretreatment of MnO x –CeO2 further promotes the performance of Au/MnO x –CeO2, with CO conversion increased by 24 % at 120°C. Meanwhile, the selectivity of oxygen to CO2 is promoted in the whole temperature range, especially in 80–120°C, the selectivity is increased by 15–21%. HR-TEM and XRD results indicate that ultrasonic pretreatment is favorable to the formation of much smaller gold nanoparticles (<5nm). The characterization of XPS, UV–vis DRS, H2-TPR and CO-TPR confirms that the strong interaction between Au and the support effectively inhibits the dissociation and oxidation of H2 over the ultrasonically pretreated catalyst Au/MnO x –CeO2, making it highly selective to CO oxidation. [Copyright &y& Elsevier]

Purpose: To explore the genetic heritability of a shallow anterior chamber (AC) in families with primary angle closure glaucoma (PACG) and to provide a theoretical basis for the identification of candidate genes responsible for PACG. Methods: Genetic analyses included familial and segregation analysis, tests for multifactorial inheritance and thresholds. The data was used to determine heritability. The relative risk rate and the possible genetic pattern of a shallow AC were examined in 114 pedigrees with PACG probands. Results: The estimated heritability value of a familial shallow AC was 92.6% ± 5.9%; the relative risk rate of a shallow AC was 7.91. The rate of affected female siblings to affected males was 2.87:1, which was statistically higher than that of affected male siblings (χ2 = 9.75, P < 0.01). In two different mating types, the segregation ratios of U × U (parents unaffected) and U × A (one parent affected) were 0.11 and 0.426 respectively. The result of segregation analyses suggested that the genetic pattern of U× U did not possess the characteristics of a monogenetic model and the genetic pattern of U × A exhibited autosomal dominant inheritance traits. Conclusions: We have shown that there is a higher heritability and a higher relative risk rate in the Chinese population of familial shallow ACs. The inheritance of a shallow AC may be a genetically heterogeneous trait and influenced by gender with autosomal dominant inheritance in subgroups. These results provide a theoretical basis for the identification of candidate genes responsible for Chinese PACG. [ABSTRACT FROM AUTHOR]

A recombinant plasmid, pRP-GFP, harboring the green fluorescent protein (GFP) gene from the broad-host-range mobilizable plasmid pRK415 of the RK2 family was constructed and transferred by conjugation from Escherichia coli S17-1 to Sorangium cellulosum So ce90. The results of Southern blot analysis showed that the plasmid replicated autonomously without being integrated into the chromosome of the bacterium. In pRP-GFP, gfp was driven by a So ce90 DNA fragment called EpoPro, which is an 890-bp DNA segment spanning from -890 to -1 relative to the start codon (GTG) of epoA, a gene that encodes EPOS A, which is presumed to be involved in the initiation of epothilone biosynthesis. The GFP in the transformed S. cellulosum So ce90 was detected by fluorescence microscopy, which suggests that the EpoPro fragment had the function of promoter. Because the green fluorescent bacilli could be directly observed by fluorescence microscopy, the stable expression of GFP was rapid and convenient for conjugation screening in addition to the antibiotic resistance genes within the constructed plasmid. This is the first report on an exogenous plasmid that can be stably maintained as an extrachromosomal element in S. cellulosum. [Copyright &y& Elsevier]

A total of six amplified fragment length polymorphism (AFLP) primer combinations were used to detect genetic variation of pooled DNA in a sample of 12 chicken breeds indigenous to China, and AFLP DNA fingerprinting of each chicken breed was constructed. Polymorphic bands, specific bands and genetic similarity coefficients of 12 chicken breeds were calculated from AFLP data. A total of 279 polymorphic bands were generated by the six primer combinations, giving, on average, 46.5 polymorphic markers detected per primer combination. Nine specific bands were produced in the pooled DNA of Jiuyuan black and Dongxiang black chickens. However, one specific band was produced in the pooled DNA of Wenchang and Xingyi bantam chickens. An unweighted-pair-group method using average linkages (UPGMA) cluster analysis revealed that the 12 chicken breeds could be divided into three groups. Genetic similarity coefficients and the UPGMA tree of the 12 chicken breeds were consistent with their breeding history as well as their geographical distribution. Based on AFLP DNA fingerprinting, genetic diversity, genetic relationship and identification of chicken breeds can be analysed. [ABSTRACT FROM AUTHOR]

Teachers' instructional design skills influence their teaching practices and student learning performances. However, researchers have found that the traditional one-to-many model of preservice teacher education prevents preservice teachers from receiving timely and individualized feedback, making it difficult to fill in theoretical knowledge gaps to achieve better instructional design. In order to address this issue, a chatbot-based 5E learning approach developed on the constructivist 5E (engage, explore, explain, elaborate, and evaluate) learning model was proposed in this study.To investigate the effects of this learning approach, we conducted a quasi-experimental study at a university (31 in the experimental group and 37 in the control group). The chatbot-based 5E learning approach was applied by one class as the experimental group, while the control group applied the conventional 5E learning approach. The results showed that students in the experimental group reported more significant increases in learning performance, learning attitudes, and extrinsic motivation. In addition, learners were generally satisfied with the information quality supplied by the chatbot. The interview results showed that the approach could help students create a clarified learning framework and thus improve their learning performance. [ABSTRACT FROM AUTHOR]

The game-based learning approach to developing students' computational thinking (CT) current has received attention from researchers. However, the compatibility between games and instruction is often insufficient to accommodate the entertaining and educational nature of the curriculum entirely, and the benefits of game-based learning could be compromised. Therefore, this study proposed a role-playing-based micro-game strategy for developing students' CT in a Python programming course, and designed a quasi-experiment to verify the effectiveness of the role-playing-based micro-game strategy. A total of 133 eighth-grade students from schools in eastern China were randomly divided into experimental and control groups. The experimental group used a role-playing-based micro-game strategy, and the control group used a traditional instructional strategy. The results showed that the experimental group scored significantly higher than the control group on the CT test, especially in the dimensions of computational concepts and computational practices. The learning engagement of the experimental group was significantly higher than that of the control group, and the learning motivation of the experimental group was significantly improved before and after the experiment. In addition, qualitative analysis of the interview data indicated that micro-game strategy on role-playing could promote classroom learning and meet the needs of the course knowledge system. [ABSTRACT FROM AUTHOR]

Information literacy is an essential twenty-first-century skill for students. Most students face difficulty in discerning online information while searching, evaluating, and utilizing it effectively. Appropriate information evaluating framework, such as RADAR (relevance, authority, date, appearance, and reason for writing), has been recommended to enhance students' accuracy in identifying information. Research suggests that the effectiveness of the learning framework can be enhanced in the gamification context by using graphic organizers (e.g. concept maps) to help students organize and analyze information. Therefore, this study proposed a concept mapping-based information evaluating framework in the gamification context to teach information identification skills in an elementary school. A quasi-experimental study was conducted with the experimental group class (35 students) using the concept mapping-based information evaluating framework (CM-IEF), and the control group (35 students) using the conventional information evaluating framework (C-IEF). According to the study's findings, students in the experimental group had more significant increases in learning achievement, self-efficacy, and information discernment skills. However, there was no significant difference in learning motivation. Furthermore, the learning behavior of both groups was analyzed from the lag sequential analysis and interview. The study suggests that larger sample sizes and longer durations could be explored in the future. [ABSTRACT FROM AUTHOR]

Learning mathematics has been considered as a great challenge for many students. The advancement of computer technologies, in particular, artificial intelligence (AI), provides an opportunity to cope with this problem by diagnosing individual students' learning problems and providing personalized supports to maximize their learning performances in mathematics courses. However, there is a lack of reviews from diverse perspectives to help researchers, especially novices, gain a whole picture of the research of AI in mathematics education. To this end, this research aims to conduct a bibliometric mapping analysis and systematic review to explore the role and research trends of AI in mathematics education by searching for the relevant articles published in the quality journals indexed by the Social Sciences Citation Index (SSCI) from the Web of Science (WOS) database. Moreover, by referring to the technology-based learning model, several dimensions of AI in mathematics education research, such as the application domains, participants, research methods, adopted technologies, research issues and the roles of AI as well as the citation and co-citation relationships, are taken into account. Accordingly, the advancements of AI in mathematics education research are reported, and potential research topics for future research are recommended. [ABSTRACT FROM AUTHOR]

To compare the value of adipose tissues in abdomen and lumbar vertebra for predicting Crohn's disease (CD) activity based on chemical shift encoded magnetic resonance imaging (CSE-MRI). 84 CD patients were divided into remission, mild, and moderate-severely groups based on CD activity index (CDAI). Differences in different adipose parameters [subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), mesenteric fat index (MFI), and bone marrow fat fraction (BMFF)] and blood inflammatory indicators among three groups, as well as the correlation of above parameters and CDAI were analyzed. The areas under the receiver-operating characteristic curves (AUCs) for the parameters selected by multivariate logistic regression analysis for predicting active CD were calculated. There were no significant differences in VAT and MFI among three groups (both P > 0.05). The cross-sectional areas of SAT in moderate-severe group were significantly lower than those in remission group (P = 0.014). BMFF values of remission group were significantly higher than those in the mild and moderate-severe groups (both P < 0.001). BMFF was negatively correlated with CDAI (r = −0.595, P < 0.001). SAT exhibited no significant correlation with CDAI. Erythrocyte sedimentation rate (ESR) and BMFF were the independent predictors of CDAI. Both combined had a higher diagnostic efficacy for active CD with an AUC of 0.895. BMFF is the best marker for predicting CD activity in fat parameters of abdomen and lumbar vertebra based on CSE-MRI. The model based on BMFF and ESR has a high efficiency in predicting active CD. No. 22 K164 (Registered 18-07-2022). [ABSTRACT FROM AUTHOR]

As a critical component in industrial production, pipelines face the risk of failure due to long-term corrosion. In recent years, acoustic emission (AE) technology has demonstrated significant potential in online pipeline monitoring. However, the interference of flow-induced noise seriously hinders the application of acoustic emission technology in pipeline corrosion monitoring. Therefore, a pattern-recognition model for online pipeline AE monitoring signals based on blind source separation (BSS) and a convolutional neural network (CNN) is proposed. First, the singular spectrum analysis (SSA) was employed to transform the original AE signal into multiple observed signals. An independent component analysis (ICA) was then utilized to separate the source signals from the mixed signals. Subsequently, the Hilbert–Huang transform (HHT) was applied to each source signal to obtain a joint time–frequency domain map and to construct and compress it. Finally, the mapping relationship between the pipeline sources and AE signals was established based on the CNN for the precise identification of corrosion signals. The experimental data indicate that when the average amplitude of flow-induced noise signals is within three times that of corrosion signals, the separation of mixed signals is effective, and the overall recognition accuracy of the model exceeds 90%. [ABSTRACT FROM AUTHOR]

In Chinese, writing is a basic competency that pupils should possess. But it is still challenging for teachers to improve pupils' writing abilities. Therefore, this study proposes an intelligence-based cognitive diagnostic feedback strategy to improve pupils' writing ability and writing learning quality by analyzing their writing performance, epistemic network structure, and learning engagement. Thepupils are randomly divided into an experimental group (N = 28) and a control group (N = 28). The experimental group adopts the ICDF strategy, while the control group adopts the WS-TF strategy. The results showed that the I-CDF strategy improved the pupil's writing scores and learning engagement. In addition, the results of the epistemic network analysis showed that the pupils using the ICDF strategy focused on dynamic descriptions such as action, psychology, and environmental changes in vocabulary use, and the epistemic network structure was more complex than the control group. The interviews showed that the pupils in the experimental group were highly satisfied with I-CDF strategy. [ABSTRACT FROM AUTHOR]

Reading comprehension is critical and challenging for the English learning process. EFL (English as Foreign Language) learners often do not understand the meaning of the text due to the lack of an authentic learning context. This easily leads learners to read literally without deeply understanding. To address this issue, an article-structure strategy-based SVVR (short for ASS-SVVR) approach was proposed in the study, in which spherical video-based virtual reality (SVVR) was employed to immerse EFL learners in a real environment, and the article-structure strategy was introduced as step-by-step reading scaffolding to improve reading efficiency, accuracy, and comprehension. To verify the effectiveness of the proposed approach, a quasi-experiment was conducted in an English reading class at a university with two classes of 63 EFL learners. Among them, 33 learners were randomly distributed to the experimental group, conducting the ASS-SVVR approach, while the remaining 30 were assigned to the control group, conducting the conventional SVVR (C-SVVR) approach. The research findings showed that EFL students conducting the ASS-SVVR approach had positive performance in reading comprehension, extrinsic learning motivation, and metacognitive awareness of reading strategy. Moreover, cognitive load and sense of presence were not shown to have a significant difference between the two groups. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to examine the critical factors influencing university teachers' use of a mobile technology-enhanced teaching (MTT) platform during the new coronavirus (COVID-19) epidemic. An integrated model with multiple factors drawing from the theoretical models and learning theories was proposed in this study to examine university teachers' intentions to use an MTT platform. The multiple factors included the individual factor (e.g., growth mindset, help seeking, and self-efficacy), the social factor (e.g., social norms), and the technological acceptance factor (e.g., perceived usefulness and perceived ease of use). The survey method was used to collect data on university teachers' perceptions of the MTT platform use, and a two-step structural equation modeling approach was used for the data analysis. Based on the path analysis of a total of 214 valid responses, the results identified that growth mindset, help seeking, and self-efficacy from the individual factor, as well as perceived usefulness from the technology acceptance factor were the significant determinants of university teachers' intentions to adopt the MTT. The contributions of this study are twofold. First, the proposed model was derived from multiple literature sources, providing a sound theoretical foundation to understand MTT platform use from an academic angle. Second, university teachers' viewpoints are a unique observation of their actual platform use, providing practical insights into the improvement and maintenance of MTT-related platforms for all educators. The findings are especially valuable during the post-COVID-19 era. [ABSTRACT FROM AUTHOR]

In the artificial intelligence (AI) era, K-12 AI education has attracted great attention. With the increasing prevalence of AI, students are likely to have misconceptions about AI starting in elementary school. Hence, it is crucial to explore an effective approach to change elementary students' misconceptions and facilitate their scientific understanding of AI. The two-tier test is an effective method to diagnose students' misconceptions, but it needs to be combined with specific learning models to further promote conceptual change in teaching practice. The dual-situated learning model (DSLM) is an instructional approach used to facilitate students' conceptual change. Therefore, this study proposed a DSLM-based two-tier test (DSLM-TT) approach for AI courses, and explored its effects on elementary students' conceptual change, learning motivation, and self-efficacy in AI courses. 160 sixth-grade students participated in this experiment: the experimental group adopted the DSLM-TT approach, while the control group adopted the conventional learning model-based two-tier test approach (CLM-TT). Results showed that the DSLM-TT group performed better on conceptual change of AI, learning motivation, and self-efficacy than the CLM-TT group. Moreover, the interview results revealed two groups' learning experiences and perceptions. Accordingly, this study can provide a baseline for future research on conceptual change in AI education. [ABSTRACT FROM AUTHOR]

Leaf senescence is a highly‐programmed developmental process during the plant life cycle. Cytokinin (CK) has been widely acknowledged as a negative regulator to delay leaf senescence. MiRNAs play key roles in a variety of developmental and physiological processes through negatively regulating their target gene expression. However, to date, the roles of microRNAs (miRNAs) in CK biosynthesis remain unclear, and the knowledge on miRNA regulation of leaf senescence is still very limited. Isopentenyltransferases (IPTs) catalyze the initial and rate‐limiting step of CK biosynthesis in higher plants. Our previous work uncovered that silencing of SlIPT4 expression in tomato resulted in premature leaf senescence. Here, we identified a novel tomato miRNA, SlymiR208, which regulates the expression of SlIPT2 and SlIPT4 at the post‐transcriptional level. SlymiR208 expression is ubiquitous in tomato and exhibits an opposite transition to its target transcripts in aged leaf. SlymiR208 overexpression in tomato sharply reduced the transcript levels of SlIPT2 and SlIPT4, and the concentrations of endogenous CKs in leaves. The early leaf senescence caused by SlymiR208 overexpression was consistent with the phenotype of SlIPT4‐silenced lines. The data demonstrated that SlymiR208 is a positive regulator in leaf senescence through negatively regulating CK biosynthesis via targeting SlIPT2 and SlIPT4 in tomato. This study indicated that post‐transcriptional regulation via miRNA is a control point of CK biosynthesis and added a new layer to the understanding of the regulation of CK biosynthesis in tomato and a new factual proof to support that miRNAs are involved in leaf senescence. [ABSTRACT FROM AUTHOR]

AbstractProgramming is an indispensable ability in the current era of artificial intelligence. It has become a topic of interest for educators and researchers to explore the effective instructional strategies to improve students’ programming knowledge and skills. Cognitive and metacognitive scaffolding have proven to have the potential to facilitate programming performance. However, their comparative effects on programming performance have received scant attention. To fill this research gap, the current study aimed to explore how cognitive and metacognitive scaffolding influence elementary school students’ Scratch programming knowledge and skills in an information technology course based on a quasi-experimental design. Three intact classes, including 126 fifth graders, were randomly assigned to a control group and two experimental groups: a cognitive scaffolding and a metacognitive scaffolding group. The findings indicated that the metacognitive scaffolding group showed significantly better scores in programming knowledge and skills than the non-scaffolding group. However, no significant differences were found between the metacognitive and cognitive scaffolding groups, or between the cognitive scaffolding and non-scaffolding groups. This study provides implications for the design and development of scaffolding based on Vygotsky’s theory of cognitive and metacognitive mediation, and also contributes to our comprehension of how scaffolding types influence students’ programming knowledge and skills. [ABSTRACT FROM AUTHOR]

By integrating fiber-reinforced composites (FRCs) with Three-dimensional (3D) printing, the flexibility of lightweight structures was promoted while eliminating the mold's limitations. The design of the I-beam configuration was performed according to the equal-strength philosophy. Then, a multi-objective optimization analysis was conducted based on the NSGA-II algorithm. 3D printing was utilized to fabricate I-beams in three kinds of configurations and seven distinct materials. The flexural properties of the primitive (P-type), the designed (D-type), and the optimized (O-type) configurations were verified via three-point bending testing at a speed of 2 mm/min. Further, by combining different reinforcements, including continuous carbon fibers (CCFs), short carbon fibers (SCFs), and short glass fibers (SGFs) and distinct matrices, including polyamides (PAs), and polylactides (PLAs), the 3D-printed I-beams were studied experimentally. The results indicate that designed and optimized I-beams exhibit a 14.46% and 30.05% increase in the stiffness-to-mass ratio and a 7.83% and 40.59% increment in the load-to-mass ratio, respectively. The CCFs and SCFs result in an outstanding accretion in the flexural properties of 3D-printed I-beams, while the accretion is 2926% and 1070% in the stiffness-to-mass ratio and 656.7% and 344.4% in the load-to-mass ratio, respectively. For the matrix, PAs are a superior choice compared to PLAs for enhancing the positive impact of reinforcements. [ABSTRACT FROM AUTHOR]

Skin and its cell components continuously subject to extrinsic and intrinsic mechanical forces and are mechanical sensitive. Disturbed mechanical homeostasis may lead to changes in skin functions. Gravity is the integral mechanical force on the earth, however, how gravity contributes to the maintenance of skin function and how microgravity in space affects the wound healing are poorly understood. Here, using microgravity analogs, we show that simulated microgravity (SMG) inhibits the healing of cutaneous wound and the accumulation of dermal fibroblasts in the wound bed. In vitro, SMG inhibits the migration of human foreskin fibroblast cells (HFF‐1), and decreases the F‐actin polymerization and YAP (yes‐associated protein) activity. The SMG‐inhibited migration can be recovered by activating YAP or F‐actin polymerization using lysophosphatidic acid (LPA) or jasplakinolide (Jasp), suggesting the involvement of F‐actin/YAP signaling pathway in this process. In SMG rats, LPA treatment improves the cutaneous healing with increased dermal fibroblasts in the wound bed. Together, our results demonstrate that SMG attenuates the cutaneous wound healing by inhibiting dermal fibroblast migration, and propose the crucial role of F‐actin/YAP mechano‐transduction in the maintenance of skin homeostasis under normal gravity, and YAP as a possible therapeutic target for the skin care of astronauts in space. [ABSTRACT FROM AUTHOR]

Teachers’ instructional design skills influence their teaching practices and student learning performances. However, researchers have found that the traditional one-to-many model of preservice teacher education prevents preservice teachers from receiving timely and individualized feedback, making it difficult to fill in theoretical knowledge gaps to achieve better instructional design. In order to address this issue, a chatbot-based 5E learning approach developed on the constructivist 5E (engage, explore, explain, elaborate, and evaluate) learning model was proposed in this study.To investigate the effects of this learning approach, we conducted a quasi-experimental study at a university (31 in the experimental group and 37 in the control group). The chatbot-based 5E learning approach was applied by one class as the experimental group, while the control group applied the conventional 5E learning approach. The results showed that students in the experimental group reported more significant increases in learning performance, learning attitudes, and extrinsic motivation. In addition, learners were generally satisfied with the information quality supplied by the chatbot. The interview results showed that the approach could help students create a clarified learning framework and thus improve their learning performance. [ABSTRACT FROM AUTHOR]

Ethylene signaling converges on the ETHYLENE-INSENSITIVE3 (EIN3)/EIN3-like (EIL) transcription factors to regulate a wide range of developmental processes in plants. EBF1/2 (EIN3-binding F-box protein 1 and 2) negatively regulate the ethylene signaling pathway by mediating the degradation of EIN3/EIL proteins. We uncovered previously that SlEBF1 and SlEBF2 are involved in ethylene response, plant senescence, and fruit ripening in tomato. The present study reports on the identification of a novel tomato F-box gene, designated as SlEBF2-like due that its encoded protein is greater similarity to SlEBF2. The SlEBF2-like promoter region contains three ethylene-response elements (EREs). SlEBF2-like is upregulated by ethylene and downregulated by ethylene inhibitors in tomato seedlings. It is dynamically expressed in flowers during bud-to-anthesis and anthesis-to-post-anthesis transitions, and at the onset of fruit ripening, suggesting its role in these situations where ethylene is required for flower opening and fruit ripening. SlEBF2-like overexpression leaded to fruit elongation, caused ripening and color change to start from fruit bottom and expand gradually to the pedicel, and strongly delayed fruit development and ripening in tomato. Our study indicates that the novel EBF gene, SlEBF2-like , is involved in fruit development and ripening via regulating the ethylene response in tomato. [ABSTRACT FROM AUTHOR]

Ganoderma is classified as a top grade traditional Chinese medicine for promoting human health by regulating ‘vital energy’. Its potency towards metabolism and energy homeostasis, particularly, metabolic adaptations of adipocytes, needs to be re‐evaluated through an evidence‐based study. Here, the triterpenoid‐rich Ganoderma tsugae ethanol extract (GTEE) was found to contribute towards adipogenesis accompanied with elevated intracellular lipid metabolic flux. Additionally, proteomic profiling revealed GTEE‐upregulated mitochondrial remodeling and chemical energy redox modifications, which display UCP1‐positive browning fat‐selective features and a NADH‐mediated adaptive mechanism. GTEE‐treated mice with diet‐induced obesity also resulted in the amelioration of white adipocyte hypertrophy and the appearance of UCP1‐positive browning adipocytes. Our novel findings unravel that GTEE could promote intracellular metabolic flexibility and plasticity followed by the induction of adipocyte browning. [ABSTRACT FROM AUTHOR]

Misregulation of spermatogenesis transcription factors (TF) in hybrids can lead to misexpression, which is a mechanism for hybrid male sterility (HMS). We used dzo (male offspring of Bos taurus ♂ × Bos grunniens ♀) in bovines to investigate the relationship of the key TF with HMS via RNA sequencing and assay for transposase-accessible chromatin with high-throughput sequencing analyses. RNA sequencing showed that the widespread misexpression in dzo was associated with spermatogenesis-related genes and somatic or progenitor genes. The transition from leptotene or zygotene spermatocytes to pachytene spermatocytes may be the key stage for meiosis arrest in dzo. The analysis of TF-binding motif enrichment revealed that the male meiosis-specific master TF MYB proto-oncogene like 1 (MYBL1 , known as A-MYB) motif was enriched on the promoters of downregulated pachytene spermatocyte genes in dzo. Assay for transposase-accessible chromatin with high-throughput sequencing revealed that TF-binding sites for MYBL1, nuclear transcription factor Y, and regulatory factor X were enriched in the low-chromatin accessibility region of dzo. The target genes of the MYBL1-binding motif were associated with meiosis-specific genes and significantly downregulated in dzo testis. The transcription factor MYBL1 may be the candidate master regulator for pachytene spermatocyte genes dysregulated in interspecific HMS dzo. This study reported that a few upstream TF regulation changes might exert a cascading effect downstream in a regulatory network as a mechanism for HMS. [ABSTRACT FROM AUTHOR]

At present, with the rapid development of the internet and the gradual promotion of online collaborative learning, the social regulation of learning is receiving increasing attention, which involves socially shared metacognition, one facet of social metacognition. To date, social regulation of learning or socially shared metacognition have been widely studied using qualitative approaches. Although a variety of scales have been developed to measure metacognition in traditional individual learning, little work has been done to develop a scale to measure social metacognition in collaborative learning contexts. This study originally developed a social metacognition inventory consisting of 24 indicators by referring to the literature for assessing beliefs of other persons (BOP), awareness of other persons' thinking (AOPT), judgment of other persons' emotions (JOPE), co-regulation of each other's thinking (CREOT), and evaluation of other persons' thinking (EOPT). After EFA using 218 undergraduates' questionnaires of social metacognition in collaborative argumentation on a social psychological issue from a Sino-Foreign Cooperative Educational Institution, 17 indicators showed good factorability and reliability. After CFA using another 300 questionnaires on social metacognition in collaborative argumentation about the pandemic received from undergraduates who come from 52 countries in the International College of Education, among the 17 indicators derived from the first sample's EFA, three indicators had high correlation with others. Finally, based on the reviews of three experts, these three indicators were deleted. The remaining 14 indicators formed good construct validity with acceptable convergent and discriminant validities. In addition, the multi-group invariance test demonstrated that the structural model of the Social Metacognition Inventory has better configural invariance, which indicates that it can be generalized to other online collaborative argumentation contexts. The Social Metacognition Inventory can be used to quantify social metacognition in online collaborative argumentation when administering a large-scale experiment. [ABSTRACT FROM AUTHOR]