An Experiential Learning-Based Virtual Reality Approach to Foster Students’ Vocabulary Acquisition and Learning Engagement in English for Geography

EFL learners encounter a number of challenges in English for specific purposes, especially in understanding and remembering vocabulary. Therefore, exploring effective ways to improve their vocabulary and its applications is the key area of ESP. VR, as a newer type of audiovisual input on incidental vocabulary learning, is an important tool for innovation in language education. With its sense of presence and immersion, VR constructs an experiential learning process for students involving incidental vocabulary acquisition to promote their learning engagement and performance. Therefore, this study applied an experiential learning-based VR approach to an English for Geography course in a university. Thirty-six geography students participated in vocabulary acquisition on the theme of the hydrologic cycle. For the experiment, 18 students were assigned to the experimental group learning with the VR-based approach, while the other 18 were assigned to the control group learning with the video-based approach. The findings demonstrated that the experimental group outperformed the control group in terms of incidental vocabulary acquisition and cognitive, behavioral, and social engagement

Deep learning for precise diagnosis and subtype triage of drug‐resistant tuberculosis on chest computed tomography

Abstract Deep learning, transforming input data into target prediction through intricate network structures, has inspired novel exploration in automated diagnosis based on medical images. The distinct morphological characteristics of chest abnormalities between drug‐resistant tuberculosis (DR‐TB) and drug‐sensitive tuberculosis (DS‐TB) on chest computed tomography (CT) are of potential value in differential diagnosis, which is challenging in the clinic. Hence, based on 1176 chest CT volumes from the equal number of patients with tuberculosis (TB), we presented a Deep learning‐based system for TB drug resistance identification and subtype classification (DeepTB), which could automatically diagnose DR‐TB and classify crucial subtypes, including rifampicin‐resistant tuberculosis, multidrug‐resistant tuberculosis, and extensively drug‐resistant tuberculosis. Moreover, chest lesions were manually annotated to endow the model with robust power to assist radiologists in image interpretation and the Circos revealed the relationship between chest abnormalities and specific types of DR‐TB. Finally, DeepTB achieved an area under the curve (AUC) up to 0.930 for thoracic abnormality detection and 0.943 for DR‐TB diagnosis. Notably, the system demonstrated instructive value in DR‐TB subtype classification with AUCs ranging from 0.880 to 0.928. Meanwhile, class activation maps were generated to express a human‐understandable visual concept. Together, showing a prominent performance, DeepTB would be impactful in clinical decision‐making for DR‐TB

Five Rice Seed-Specific NF-YC Genes Redundantly Regulate Grain Quality and Seed Germination via Interfering Gibberellin Pathway

NF-YCs are important transcription factors with diverse functions in the plant kingdoms including seed development. NF-YC8, 9, 10, 11 and 12 are close homologs with similar seed-specific expression patterns. Despite the fact that some of the NF-YCs are functionally known; their biological roles have not been systematically explored yet, given the potential functional redundancy. In this study, we generated pentuple mutant pnfyc of NF-YC8-12 and revealed their functions in the regulation of grain quality and seed germination. pnfyc grains displayed significantly more chalkiness with abnormal starch granule packaging. pnfyc seed germination and post-germination growth are much slower than the wild-type NIP, largely owing to the GA-deficiency as exogenous GA was able to fully recover the germination phenotype. The RNA-seq experiment identified a total of 469 differentially expressed genes, and several GA-, ABA- and grain quality control-related genes might be transcriptionally regulated by the five NF-YCs, as revealed by qRT-PCR analysis. The results demonstrated the redundant functions of NF-YC8-12 in regulating GA pathways that underpin rice grain quality and seed germination, and shed a novel light on the functions of the seed-specific NF-YCs

Age at onset of major depressive disorder in Han Chinese women: Relationship with clinical features and family history☆

BACKGROUND: Individuals with early-onset depression may be a clinically distinct group with particular symptom patterns, illness course, comorbidity and family history. This question has not been previously investigated in a Han Chinese population. METHODS: We examined the clinical features of 1970 Han Chinese women with DSM-IV major depressive disorder (MDD) between 30 and 60 years of age across China. Analysis of linear, logistic and multiple logistic regression models was used to determine the association between age at onset (AAO) with continuous, binary and discrete characteristic clinical features of MDD. RESULTS: Earlier AAO was associated with more suicidal ideation and attempts and higher neuroticism, but fewer sleep, appetite and weight changes. Patients with an earlier AAO were more likely to suffer a chronic course (longer illness duration, more MDD episodes and longer index episode), increased rates of MDD in their parents and a lower likelihood of marriage. They tend to have higher comorbidity with anxiety disorders (general anxiety disorder, social phobia and agoraphobia) and dysthymia. CONCLUSIONS: Early AAO in MDD may be an index of a more severe, highly comorbid and familial disorder. Our findings indicate that the features of MDD in China are similar to those reported elsewhere in the world