MATERIALS AND METHODS: We propose a mixed-method study of mental health assessment that combines psychological questionnaires with facial emotion analysis to comprehensively evaluate the mental health of students on a large scale. The Depression Anxiety and Stress Scale-21(DASS-21) is used for the psychological questionnaire. The facial emotion recognition model is implemented by transfer learning based on neural networks, and the model is pre-trained using FER2013 and CFEE datasets. Among them, the FER2013 dataset consists of 48 × 48-pixel face gray images, a total of 35,887 face images. The CFEE dataset contains 950,000 facial images with annotated action units (au). Using a random sampling strategy, we sent online questionnaires to 400 college students and received 374 responses, and the response rate was 93.5%. After pre-processing, 350 results were available, including 187 male and 153 female students. First, the facial emotion data of students were collected in an online questionnaire test. Then, a pre-trained model was used for emotion recognition. Finally, the online psychological questionnaire scores and the facial emotion recognition model scores were collated to give a comprehensive psychological evaluation score.
RESULTS: The experimental results of the facial emotion recognition model proposed to show that its classification results are broadly consistent with the mental health survey results. This model can be used to improve efficiency. In particular, the accuracy of the facial emotion recognition model proposed in this paper is higher than that of the general mental health model, which only uses the traditional single questionnaire. Furthermore, the absolute errors of this study in the three symptoms of depression, anxiety, and stress are lower than other mental health survey results and are only 0.8%, 8.1%, 3.5%, and 1.8%, respectively.
CONCLUSION: The mixed method combining intelligent methods and scales for mental health assessment has high recognition accuracy. Therefore, it can support efficient large-scale screening of students' psychological problems.
METHODS: A competitive enzyme-linked immunosorbent assay (cELISA) using a monoclonal antibody (mAb) and recombinant NiV glycoprotein (G) was developed and laboratory evaluated using sera from experimental pigs, mini pigs and nonhuman primates. The test depends on competition between specific antibodies in positive sera and a virus-specific mAb for binding to NiV-G.
RESULTS: Based on 1,199 negative and 71 NiV positive serum test results, the cutoff value was determined as 35% inhibition. The diagnostic sensitivity and specificity of the NiV cELISA was 98.58 and 99.92%, respectively. When testing sera from animals experimentally infected with NiV Malaysia, the cELISA detected antibodies from 14 days post-infection (dpi) and remained positive until the end of the experiment (28 dpi). Comparisons using the Kappa coefficient showed strong agreement (100%) between the cELISA and a plaque reduction neutralization test (PRNT).
DISCUSSION: Because our cELISA is simpler, faster, and gives comparable or better results than PRNT, it would be an adequate screening test for suspect NiV and HeV cases, and it would also be useful for epidemiological surveillance of Henipavirus infections in different animal species without changing reagents.
SIGNIFICANCE STATEMENT: Mechanisms of species formation have always been a conundrum. Speciation between populations that are fully geographically isolated, or allopatric speciation, has been the standard solution in the last 50 years. Complete geographical isolation with no possibility of gene flow, however, is often untenable and is inefficient in generating the enormous biodiversity. By studying mangroves on the Indo-Malayan coasts, a global hotspot of coastal biodiversity, we were able to combine genomic data with geographical records on the Indo-Pacific Barrier that separates Pacific and Indian Ocean coasts. We discovered a novel mechanism of speciation that we call mixingisolation-mixing (MIM) cycles. By permitting intermittent gene flow during speciation,MIMcycles can potentially generate species at an exponential rate, thus combining speciation and biodiversity in a unified framework.
OBJECTIVE: This study aims to explore how the experience of the Chinese Great Famine from 1959 to 1961 affects the risk of depressive symptoms among the elderly. Using a mechanism analysis, the study investigates the roles of social support, socioeconomic status, and intergenerational support in this process.
METHODS: Using micro-level individual data from the China Health and Retirement Longitudinal Survey (CHARLS), combined with province-level excess mortality data, this study employs a cohort-based difference-in-differences model to identify the causal effects of the famine experience on depression levels among the elderly.
RESULTS: The study reveals that experiencing the Great Famine significantly increases the risk of depression among the elderly. This effect is more pronounced among rural residents, those who experienced the famine during adolescence, and in regions less influenced by Confucian culture. The mechanism analysis indicates that diminished social support, lower socioeconomic status, and insufficient intergenerational support are the primary pathways through which the famine experience influences depression levels in the elderly.
CONCLUSIONS: The experience of the Great Famine has exerted a long-term and profound impact on the mental health of the elderly in China, particularly in terms of depression. The findings provide new perspectives on understanding the long-term effects of major historical events on health and offer important empirical evidence for the development of mental health intervention policies for the elderly.