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Predicting digital informal learning: an empirical study among Chinese University students
Tao He,Chang Zhu,Frederik Questier 서울대학교 교육연구소 2018 Asia Pacific Education Review Vol.19 No.1
Although the adoption of digital technology has gained considerable attention in higher education, currently research mainly focuses on implementation in formal learning contexts. Investigating what factors influence students’ digital informal learning is still unclear and limited. To understand better university students’ digital informal learning (DIL), this study proposed a model based on decomposed theory of planned behavior to investigate students’ behavioral intention to DIL. Different aspects of DIL behavior were further explored, through examining behaviors of cognitive learning, metacognitive learning, and social and motivation learning. This study also integrated digital competence as a new construct into the model, along with other variables to test the proposed model. A sample of 335 students selected from three universities in China took part in this study. The partial least square structural equation modeling was applied to analyze the data. The results provide support and better understanding for the importance of motivation factors such as digital competence and compatibility to explain students’ DIL.
Huan-Huan Chen,Hao Hu,Wen Chen,Dai Cui,Xiao-Quan Xu,Fei-Yun Wu,Tao Yang 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.3
Objective: We aimed to investigate the ability of readout-segmented echo-planar imaging (rs-EPI)-based diffusion tensor imaging (DTI) in assessing the microstructural change of extraocular muscles (EOMs) and optic nerves in patients with thyroidassociated orbitopathy (TAO) as well as in evaluating disease activity. Materials and Methods: We enrolled 35 TAO patients and 22 healthy controls (HCs) who underwent pre-treatment rs-EPIbased DTI. Mean, axial, and radial diffusivity (MD, AD, and RD) and fractional anisotropy (FA) of the medial and lateral EOMs and optic nerve for each orbit were calculated and compared between TAO and HC groups and between active and inactive TAO groups. Factors such as age, sex, disease duration, mediation, and smoking history between groups were also compared. Logistic regression analysis was used to evaluate the predictive value of significant variables for disease activity. Results: Disease duration was significantly shorter in active TAOs than in inactive ones (p < 0.001). TAO patients showed significantly lower FA and higher MD, AD, and RD than HCs for both medial and lateral EOMs (p < 0.001), but not the AD value of lateral EOMs (p = 0.619). Active patients had significantly higher FA, MD, and AD than inactive patients for medial EOMs (p < 0.005), whereas only FA differed significantly in the lateral EOMs (p = 0.018). The MD, AD, and RD of optic nerves were significantly lower in TAO patients than HCs (p < 0.05), except for FA (p = 0.129). Multivariate analysis showed that the MD of medial EOMs and disease duration were significant predictors for disease activity. The combination of these two parameters showed optimal diagnostic efficiency for disease activity (area under the curve, 0.855; sensitivity, 68.4%; specificity, 96.9%). Conclusion: rs-EPI-based DTI is promising in assessing microstructural changes of EOMs and optic nerves and can help to indicate the disease activity of TAO, especially through the MD of medial EOMs.
Extraskeletal Ewing Sarcomas in Late Adolescence and Adults: A Study of 37 Patients
Tao, Hai-Tao,Hu, Yi,Wang, Jin-Liang,Cheng, Yao,Zhang, Xin,Wang, Huan,Zhang, Su-Jie Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.5
Background: Extraskeletal Ewing sarcoma (EES)/primitive neuroectodermal tumours (PNET) are rare soft tissue sarcomas. Prognostic factors and optimal therapy are still unconfirmed. Materials and Methods: We performed a retrospective analysis on patients to explore the clinic characteristics and prognostic factors of this rare disease. A total of 37 patients older than 15 years referred to our institute from Jan., 2002 to Jan., 2012 were reviewed. The characteristics, treatment and outcome were collected and analyzed. Results: The median age was 28 years (range 15-65); the median size of primary tumours was 8.2 cm (range 2-19). Sixteen patients (43%) had metastatic disease at the initial presentation. Wide surgical margins were achieved in 14 cases (38%). Anthracycline or platinum-based chemotherapy was performed on 29 patients (74%). Radiotherapy was delivered in 13 (35%). At a median follow-up visit of 24 months (range 2-81), the media event-free survival (EFS) and overall survival (OS) were 15.8 and 30.2 months, respectively. The 3-year EFS and OS rates were 24% and 43%, respectively. Metastases at presentation and wide surgical margins were significantly associated with OS and EFS. Tumour size was significantly associated with OS but not EFS. There were no significant differences between anthracycline and platinum based chemotherapy regarding EFS and OS. Conclusions: EES/PNET is a malignant tumour with high recurrence and frequent distant metastasis. Multimodality therapy featuring wide surgical margins, aggressive chemotherapy and adjuvant local radiotherapy is necessary for this rare disease. Platinum-based chemotherapy can be used as an adjuvant therapy.
( Tao Tao ),( Jianfeng Yang ),( Wei Wei ),( Marcin Woźniak ),( Rafał Scherer ),( Robertas Damaševičius ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.10
With the rapid development of the Chinese water project, the safety monitoring of dams is urgently needed. Many drawbacks exist in dams, such as high monitoring costs, a limited equipment service life, long-term monitoring difficulties. MEMS sensors have the advantages of low cost, high precision, easy installation, and simplicity, so they have broad application prospects in engineering measurements. This paper designs intelligent monitoring based on the collaborative measurement of dual MEMS sensors. The system first determines the endpoint coordinates of the sensor array by the coordinate transformation relationship in the monitoring system and then obtains the dam settlement according to the endpoint coordinates. Next, this paper proposes a dual-MEMS sensor collaborative measurement algorithm that builds a mathematical model of the dual-sensor measurement. The monitoring system realizes mutual compensation between sensor measurement data by calculating the motion constraint matrix between the two sensors. Compared with the single-sensor measurement, the dual-sensor measurement algorithm is more accurate and can improve the reliability of long-term monitoring data. Finally, the experimental results show that the dam subsidence monitoring system proposed in this paper fully meets the engineering monitoring accuracy needs, and the dual-sensor collaborative measurement system is more stable than the single-sensor monitoring system.
陶陶(Tao Tao) 아시아사회과학학회 2021 International Science Research Vol.1 No.1
Artificial Intelligence, as a great trend, has already entered into many aspects of our life. While we enjoy the convenience it brings us, we also need to bear the impact it gives. Under the impact of artificial intelligence, the number of employees in many industries has decreased sharply, and even many jobs will no longer exist. In this context, machine translation, as an important aspect of artificial intelligence, has a great impact on traditional human translation. Machine translation, can accomplish many written translation tasks in shorter time but with higher quality. Even simultaneous interpretation, the Gold collar in translation industry, has been suffered unprecedented huge impact. In the face of such a situation, what shall translation major in Colleges and Universities do is an urgent problem.