Search

The study examined university teachers who make choices to apply blended learning to language teaching. The samples were 15 teachers of English at the University of Foreign Languages, Hue University in Vietnam. The research instrument was interviews with semi-structured questions. Data were then analysed using inductive approach, as explained by Thomas (2006), with raw data being condensed and coded into categories. The results revealed that two of the main findings regarding the motivation for university language teachers to apply blended learning in their classes were the need to increase professional development and to keep teachers updated with new technology; whereas class size, students' self-awareness, and students' low economic background were found to be the main barriers preventing teachers from applying blended learning approach. Besides, findings also support the existing body of knowledge regarding the reasons why and why not teachers apply blended learning in their teaching practice.

The objective of this study was to construct a prediction model for early diagnosis and classification of lung cancer based on multi-dimensional clinical data. Three advanced machine learning models — Random Forest, Decision Tree, and Support Vector Machine (SVM) — were employed to predict lung cancer using features such as age, chronic disease history, and clinical symptoms. The models were optimized through various strategies to improve predictive performance. The results demonstrated that all three models achieved high accuracy and sensitivity in lung cancer prediction. Furthermore, a detailed analysis of feature importance identified key factors such as age and chronic disease history that significantly influenced prediction outcomes. Among the models, the SVM exhibited particularly strong performance, providing robust support for accurate lung cancer prediction. Future work will focus on integrating multimodal data and optimizing model architecture and hyperparameters to further enhance the predictive accuracy and clinical utility of the model, thereby contributing to the early diagnosis and treatment of lung cancer. [ABSTRACT FROM AUTHOR]

Hypoxia-induced epigenetic regulation calls for more effective therapeutic targets for esophageal cancer. We used GEPIA and UALCAN databases to screen survival-related and cancer stage-associated genes. Eca109 and KYSE450 esophageal cancer cell lines were cultured under normoxia, hypoxia, or CoCl2-induced hypoxia conditions, which were further transfected with plasmids expressing RB binding protein 7 (RBBP7), hypoxia-inducible factor 1 (HIF1)-α, or RBBP7 shRNA. Colony formation and MTT assays were used to detect cell proliferation. Tumor sphere formation and stemness marker detection were applied to assess cell stemness. RT-PCR and western blot analysis were used to detect the relative mRNA level and protein expression, respectively. Luciferase assay was utilized to detect the direct interaction between HIF1α and RBBP7. Up-regulated RBBP7 was identified as one of the most prominent survival-related genes, which is negatively correlated with the overall survival (OS), disease recurrence-free survival (DFS), and tumor stages. Hypoxia-induced HIF1α up-regulates RBBP7 expression, which promotes esophagus cancer cell viability, proliferation, and stemness with increased cyclin-dependent kinase 4 (CDK4) expression. Luciferase reporter assay verified that HIF1α transcriptionally regulates the expression of RBBP7. We conclude that hypoxia induces high expression of RBBP7 which is at least partially mediated by HIF1α, up-regulates the expression of downstream CDK4, and thereby promotes tumor progression in esophageal cancer cells.

The study aims to investigate the association of learning participation with the quality of life (QoL) in older Chinese adults, verifying how the differing types of learning activity participation may influence their QoL. We conducted two studies to gain a better understanding of learning participation and QoL among adults over 55 years of age. In the first study, we conducted five focus groups among 43 older adults about their understanding of learning benefits and their general well-being. In a second study, we assessed the QoL using the EUROHIS-QOL 8-item index, while learning participation was measured through a questionnaire addressing the frequency of involvement in educational activities among 579 Chinese older adults. The results indicate that being engaged in learning activities in old age has the potential to increase the QoL of older adults. Moreover, in contrast to nonformal learning, the results of the hierarchical linear regression model demonstrate that both informal and formal learning have a significant positive influence on QoL. The paper concludes by discussing the implications for research and practice pertaining to the encouragement of learning participation in later life.

Background: The cochlear sympathetic system plays a key role in auditory function and susceptibility to noise-induced hearing loss (NIHL). The formation of reactive oxygen species (ROS) is a well-documented process in NIHL. In this study, we aimed at investigating the effects of a superior cervical ganglionectomy (SCGx) on NIHL in Sprague-Dawley rats. Methods: We explored the effects of unilateral and bilateral Superior Cervical Ganglion (SCG) ablation in the eight-ten weeks old Sprague-Dawley rats of both sexes on NIHL. Auditory function was evaluated by auditory brainstem response (ABR) testing and Distortion product otoacoustic emissions (DPOAEs). Outer hair cells (OHCs) counts and the expression of α2A-adrenergic receptor (AR) in the rat cochlea using immunofluorescence analysis. Cells culture and treatment, CCK-8 assay, Flow cytometry staining and analysis, and western blotting were to explore the mechanisms of SCG fibers may have a protective role in NIHL. Results: We found that neither bilateral nor unilateral SCGx protected the cochlea against noise exposure. In HEI-OC1 cells, H2O2-induced oxidative damage and cell death were inhibited by the application of norepinephrine (NE). NE may prevent ROS-induced oxidative stress in OHCs and NIHL through the α2A-AR. Conclusion: These results demonstrated that sympathetic innervation mildly affected cochlear susceptibility to acoustic trauma by reducing oxidative damage in OHCs through the α2A-AR. NE may be a potential therapeutic strategy for NIHL prevention. [ABSTRACT FROM AUTHOR]

Background and aim: Even though the beneficial effects of elderly learning are widely acknowledged, many older Chinese people are still not involved. This paper aims to examine the barriers that affect the level of educational participation of older adults in China. Methodology: Using a focus group methodology, 43 older participants (aged 55 years and over) were assigned to five focus groups based on gender and (in)activity rate in Xi'an, China. The focus groups were conducted to identify the individual learning experiences including motivation, learning preferences, and, especially, participation barriers between older adults who have already participated in the Universities of the Third Age (U3As) and others who have not. Strategies to overcome or minimize these barriers were also raised in focus group interviews. Results: The results have demonstrated that barriers associated with situational factors were reported the most; informational barriers and dispositional barriers were perceived as the least obstructive. The active group was characterized by a more optimistic mood in dealing with these learning barriers. The study also suggests that the Selective Optimisation with Compensation Model of successful ageing can be useful in explaining older adults' strategy for coping with the barriers. Conclusion: The findings of the study provide policy makers and U3A practitioners an insight into the barriers to educational participation. These findings provide input to develop targeted intervention strategies and tailor-made measures to reduce these constraints and increase participation.

As a crucial determinant of urban livability, the importance of access to high-quality green spaces has long been recognized for achieving sustainable urbanization. In urban areas, higher values are usually placed in residential properties with higher accessibility to green spaces. Using housing transaction data from as many as 3388 residential communities in Shanghai coupled with high-resolution satellite data of urban green spaces, we comprehensively examine the relationship between residential property values and the accessibility of both community-owned and public green spaces. We find, in instrumental-variable estimations, that: (1) home prices, on average, increase by 0.17% if the overall green space accessibility rises by 1%; and that (2) a 1% increase in the green ratio within a community raises property values by 0.46%. Moreover, the number of accessible green spaces, area of accessible green spaces, and distance to the nearest green spaces have positive impacts on home values separately. We also find strong spatial dependence in urban green spaces and unobserved price determinants, as well as heterogeneity by location, property value, and housing type. Our empirical findings provide valuable guidance for real estate developers and local governments in valuing environmental amenities and urban planning in the context of a residential housing market. [ABSTRACT FROM AUTHOR]

The local climate zone (LCZ) system is a landscape framework defining a universal understanding of urban microclimate and urban environment and is important for the research of urban thermal environment, regional planning and carbon cycle. Currently, most existing approaches are difficult to deal with the features of built‐up area classes which are mainly related to three‐dimensional structures, resulting in poor accuracy of these classes. The convolutional block attention module (CBAM) can get meaningful context to better represent features by re‐weighting the features spatially and channel‐wise. This study proposed a Lightweight‐LCZ‐Network (LLNet) based on CBAM and depthwise separable convolution for LCZ classification from Sentinel‐2 image. The current largest LCZ classification data set So2Sat LCZ42 was employed to train and test the proposed model. Results indicated that the accuracy of the LLNet model achieved overall accuracy (OA) of 71.6% and Kappa coefficient of 0.688, realized an accuracy improvement by about 2%. In LLNet model, 65% of ordinary convolutions were displaced with depthwise separable convolutions, which decreased the amount of model parameters by 2/3 and maintained alike classification accuracy. In addition, the proposed model was applied for LCZ classification of Wuhan and Hefei cities to assess its generalization ability. The OA (Kappa coefficient) of the proposed model is 74.6% (0.72) for Wuhan and 77.5% (0.75) for Hefei, respectively. We concluded that the proposed LLNet model with strong robustness for LCZ classification from Sentinel‐2 data has an effective trade‐off between size and accuracy. [ABSTRACT FROM AUTHOR]