Numerous studies on blended learning have mentioned the positive impact of social support on students’ attitudes and behaviors. However, organizational support is also crucial and should not be ...ignored. Therefore, this study examined the relationships between organizational support, information and communication technology (ICT) self-efficacy, student engagement, and student satisfaction in a blended learning environment. A questionnaire survey was conducted on 245 students in China and validated with the structural equation model (SEM). The results showed that organizational support positively predicted perceived usefulness (PU) but was not significantly associated with student engagement; student engagement was positively predicted by PU and ICT self-efficacy; student satisfaction was positively predicted by ICT self-efficacy and student engagement; ICT self-efficacy complete mediated engagement, with the proportion of the indirect effect being 95.78%, and student engagement complete mediated student satisfaction, with the proportion of the indirect effect being 53.85%. Guidelines were proposed for higher education institutions to provide organizational support, increase students’ ICT self-efficacy, and improve student engagement and satisfaction in blended learning via various programs.
Plain Language Summary
Impact of Organizational Support on Students’ ICT Self-Efficacy, Engagement, and Satisfaction
Numerous studies on blended learning have mentioned the positive impact of social support on students’ attitudes and behaviors. However, organizational support is also crucial and should not be ignored. Therefore, this study examined the relationships between organizational support, information and communication technology (ICT) self-efficacy, student engagement, and student satisfaction using SEM in a blended learning environment. This proposed model focuses on examining the effects of systematic organizational support from higher education institutions on students’ intrinsic and extrinsic motivation for blended learning. This study extends previous research on the effects of OSBL on students’ attitudes and behaviors and has theoretical and practical significance, especially for providing systematic organizational support of higher education institutions. Guidelines were proposed for higher education institutions to provide organizational support, increase students’ ICT self-efficacy, and improve student engagement and satisfaction in blended learning via various programs.
As the prosperity of low-cost and easy-operating depth cameras, skeleton-based human action recognition has been extensively studied recently. However, most of the existing methods partially consider ...that all 3D joints of a human skeleton are identical. Actually, these 3D joints exhibit diverse responses to different action classes, and some joint configurations are more discriminative to distinguish a certain action. In this paper, we propose a discriminative multi-instance multitask learning (MIMTL) framework to discover the intrinsic relationship between joint configurations and action classes. First, a set of discriminative and informative joint configurations for the corresponding action class is captured in multi-instance learning model by regarding the action and the joint configurations as a bag and its instances, respectively. Then, a multitask learning model with group structure constraints is exploited to further reveal the intrinsic relationship between the joint configurations and different action classes. We conduct extensive evaluations of MIMTL using three benchmark 3D action recognition datasets. Experimental results show that our proposed MIMTL framework performs favorably compared with several state-of-the-art approaches.
In the environment, nanoplastic particles, such as nanopolystyrene, potentially cause toxicity on organisms at various aspects. We here employed endpoints of lifespan and aging-related phenotypes to ...further investigate the possible long-term effects of nanopolystyrene (100 nm) in Caenorhabditis elegans. After exposure from L1-larvae to adult day-3, nanopolystyrene at high concentrations (100 and 1000 μg/L) reduced the lifespan. Although nanopolystyrene (1 or 10 μg/L) did not affect the lifespan, nanopolystyrene (1 or 10 μg/L) could induce the more severe intestinal reactive oxygen species (ROS) production and decrease in locomotion behavior during the aging process compared with control. Moreover, nanopolystyrene exposure could cause the severe decrease in expressions of some immune response genes, hsp-6 gene, and genes encoding manganese-superoxide dismutases (Mn-SODs) during aging process, suggesting the severe suppression in innate immune response, inhibition in antioxidation defense system, and suppression in mitochondrial unfolded protein response (mt UPR) by nanopolystyrene. Our results highlight the potential of long-term nanopolystyrene exposure in reducing longevity and in affecting health state during the aging process in environmental organisms.
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•We investigated the long-term effects of nanoplastics on nematodes.•Nanopolystyrene at high concentrations reduced the lifespan.•Nanopolystyrene (1–10 μg/L) induced adverse effects during aging process.•Our results suggest that nanoplastics may affect health quality during aging process.
Vitamin D plays a critical role in calcium and phosphate metabolism and helps maintain skeletal integrity in childhood, yet vitamin D status in Chinese children and adolescents is not well ...documented. The aim of this study was to assess the vitamin D status and analyze the risk factors for vitamin D deficiency in Chinese children and adolescents aged 6-17 years. Serum 25 hydroxyvitamin D (25(OH)D) was measured with a radioimmunoassay kit in 15,000 children and adolescent participants in the Chinese national nutrition and health survey (CNNHS) 2010-2012. Age, gender, region type, ethnicity, outdoor time, and vitamin D supplementation were recorded in unified design questionnaires. The season was recorded by the date of blood taken; location was divided into north and south by China's Qinling Mountains and Huaihe River; and ambient ultraviolet B (UVB) radiation level was classified according to the corresponding dose of each participant living area from National Aeronautics and Space Administration data. 14,473 participants from the cross-sectional study of CNNHS 2010-2012 were included in this study. The median serum 25(OH)D concentration was 48.2 (35.4-63.4) nmol/L, and the concentration for males was 50.0 (36.5-65.7) nmol/L, which was statistically higher than that of females (46.7 (34.4-60.9) nmol/L) (
< 0.001). The general prevalence of vitamin D deficiency was 53.2%; 50.0% for males and 56.5% for females at the cut-off 50 nmol/L. According to the results of the log-binomial regression analysis, vitamin D deficiency in Chinese children and adolescents was specifically related to female gender (
< 0.0001), to ages 12-14 years (
< 0.0001) and 15-17 years (
< 0.0001), living in large cities (
< 0.0001) or ordinary rural areas (
< 0.0001), low ambient UVB levels (
< 0.0001) and medium ambient UVB levels (
< 0.0001), spring (
< 0.0001), autumn (
< 0.0001) and winter seasons (
< 0.0001). The data showed that vitamin D deficiency was very common among children and adolescents aged 6-17 years in China. Effective sun exposure should be encouraged in both genders aged 6-17 years, dietary vitamin D and vitamin D supplements are also recommended, especially in the seasons of spring and winter.
Recent emergence of low-cost and easy-operating depth cameras has reinvigorated the research in skeleton-based human action recognition. However, most existing approaches overlook the intrinsic ...interdependencies between skeleton joints and action classes, thus suffering from unsatisfactory recognition performance. In this paper, a novel latent max-margin multitask learning model is proposed for 3-D action recognition. Specifically, we exploit skelets as the mid-level granularity of joints to describe actions. We then apply the learning model to capture the correlations between the latent skelets and action classes each of which accounts for a task. By leveraging structured sparsity inducing regularization, the common information belonging to the same class can be discovered from the latent skelets, while the private information across different classes can also be preserved. The proposed model is evaluated on three challenging action data sets captured by depth cameras. Experimental results show that our model consistently achieves superior performance over recent state-of-the-art approaches.
Four novel aromatic diamines containing tetraphenyl fluorene (TPF) moiety were synthesized via a Suzuki coupling reaction. Then the four corresponding functional polyimides (PI(TPF-Ph), ...PI(TPF-Ph-Na), PI(TPF-2Na), and PI(TPF-Ph-OMe)) were prepared. The devices of PI(TPF-Ph) and PI(TPF-Ph-Na) displayed volatile DRAM behaviors with turn-on voltages of −1.80 and +1.62 V, as well as −1.34 and +1.36 V, respectively. The PI(TPF-2Na)-based device showed volatile SRAM behavior with turn-on voltages of −1.39 and +1.45 V. However, the PI(TPF-Ph-OMe)-based device exhibited non-volatile WORM behavior with turn-on voltage of −1.57 V.
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•Four functional polyimides (PI(TPF-Ph), PI(TPF-Ph-Na), PI(TPF-2Na), and PI(TPF-Ph-OMe)) containing tetraphenyl fluorene (TPF) moiety and different substituent moieties were synthesized and characterized.•The memory devices of PI(TPF-Ph) and PI(TPF-Ph-Na) displayed volatile DRAM behaviors, however, the PI(TPF-2Na) device showed volatile SRAM behavior. And the PI(TPF-Ph-OMe) device exhibited non-volatile WORM behavior.
Four new symmetric diamines (4,4′-(2,7-diphenyl-9H-fluorene-9,9-diyl)dianiline (TPF-Ph), 4,4′-(2,7-bis(4-(naphthalen-1-yl)phenyl)-9H-fluorene-9,9-diyl)dianiline (TPF-Ph-Na), 4,4′-(2,7-di(1,1′-binaphthalen-4-yl)-9H-fluorene-9,9-diyl)dianiline (TPF-2Na), and 4,4′-(2,7-bis(3,5-dimethoxyphenyl)-9H-fluorene-9,9-diyl)dianiline (TPF-Ph-OMe)) containing tetraphenyl fluorene (TPF) core were synthesized through Suzuki coupling reaction, the corresponding four polyimides (PI(TPF-Ph), PI(TPF-Ph-Na), PI(TPF-2Na), and PI(TPF-Ph-OMe)) were prepared through polymerization reaction. The electrical memory measurement displayed that PI(TPF-Ph) and PI(TPF-Ph-Na) exhibited volatile dynamic random access memory (DRAM) behaviors, PI(TPF-2Na) possessed volatile static random access memory (SRAM) behavior due to the more distorted structure of 1,1′-binaphthalenyl moiety, and PI(TPF-Ph-OMe) showed non-volatile write-once read-many (WORM) behavior due to the presence of deeper charge traps and higher dipole moment of 3,5-dimethoxyphenyl substituent. They possessed low turn-on switching voltages and the ON/OFF current ratios were between 103 and 105 with the retention times up 4 × 103 s. Quantum simulations about energy levels, electrostatic potential (ESP) surfaces, and dipole moment were used to demonstrate the switching mechanism. The experimental results indicated that the electrical memory behaviors of the synthesized polyimides could be tuned through rational structural modification of the electron donor moiety.
•Potential-force surface tension model is extended to simulate interface deformation between immiscible fluids.•The interface tension model is verified to reproduce contact angles.•The interface ...tension model is validated with stratification experiments.
The moving particle semi-implicit (MPS) method is employed to simulate the density stratification of immiscible fluids. For the sake of accurate prediction of immiscible fluids, the potential-force surface tension model is extended to calculate the interface tension. The interface tension model is verified by the simulation of a floating droplet and shows accurate prediction of the contact angle between immiscible fluids. In order to demonstrate the validity of the interface tension model at the solid surface, the wall contact angle with immiscible fluids is simulated and the predicted value agrees well with the theoretical value. In order to further validate the modified MPS method, the two-dimensional dam-break stratification experiment is simulated. The validation shows that the interface deformation can be accurately reproduced by the interface tension model. Finally, three-dimensional injection stratification is simulated to prove the effectiveness of implemented modification.
Cases with intussusception caused by either intestinal hemangiomas or appendiceal mucinous neoplasms are extremely rare.
In this study, we reported a 47-year-old male presented with paroxysmal ...abdominal pain and postprandial bloating for 3 days. CT results indicated a high possibility of secondary intussusception in ascending colon. Histopathology indicated a mixed type of cavernous and capillary hemangioma, combined with low-grade appendiceal mucinous neoplasms (LAMNs) and intestinal obstruction. The patient underwent laparotomy and right hemicolectomy. Finally, the patient was followed up for 4 months with no disease progression.
Rare studies reported the intestine hemangiomas coincided with appendix low-grade mucinous tumor. Its manifestations are not specific, which is a challenge in the preoperative diagnosis. For cases with intussusception that was not observed in time, it may lead to intestinal necrosis and diffuse peritonitis. Additionally, the ruptured mucinous tumor in the appendix may lead to pathogenesis of pseudomyxoma peritonei. Therefore, accurate diagnosis and appropriate surgery-based treatment contribute to the improvement of prognosis and severe outcomes among these patients.
Machine learning (ML) algorithms have been widely used in big data prediction and analysis in terms of their excellent data regression ability. However, the prediction accuracy of different ML ...algorithms varies between different regression problems and data sets. In order to construct a prediction model with optimal accuracy for fly ash concrete (FAC), ML algorithms such as genetic programming (GP), support vector regression (SVR), random forest (RF), extremely gradient boost (XGBoost), backpropagation artificial neural network (BP-ANN) and adaptive network-based fuzzy inference system (ANFIS) were selected as regression and prediction algorithms in this study; the particle swarm optimization (PSO) algorithm was also used to optimize the structure and hyperparameters of each algorithm. The statistical results show that the performance of the assembled algorithms is better than that of an NN-based algorithm. In addition, PSO can effectively improve the prediction accuracy of the ML algorithms. The comprehensive performance of each model is analyzed using a Taylor diagram, and the PSO-XGBoost model has the best comprehensive performance, with R2 and MSE equal to 0.9072 and 11.4546, respectively.
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