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"Wang, Jingyi"
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Evaluation and analysis of visual perception using attention-enhanced computation in multimedia affective computing
Facial expression recognition (FER) plays a crucial role in affective computing, enhancing human-computer interaction by enabling machines to understand and respond to human emotions. Despite advancements in deep learning, current FER systems often struggle with challenges such as occlusions, head pose variations, and motion blur in natural environments. These challenges highlight the need for more robust FER solutions. To address these issues, we propose the Attention-Enhanced Multi-Layer Transformer (AEMT) model, which integrates a dual-branch Convolutional Neural Network (CNN), an Attentional Selective Fusion (ASF) module, and a Multi-Layer Transformer Encoder (MTE) with transfer learning. The dual-branch CNN captures detailed texture and color information by processing RGB and Local Binary Pattern (LBP) features separately. The ASF module selectively enhances relevant features by applying global and local attention mechanisms to the extracted features. The MTE captures long-range dependencies and models the complex relationships between features, collectively improving feature representation and classification accuracy. Our model was evaluated on the RAF-DB and AffectNet datasets. Experimental results demonstrate that the AEMT model achieved an accuracy of 81.45% on RAF-DB and 71.23% on AffectNet, significantly outperforming existing state-of-the-art methods. These results indicate that our model effectively addresses the challenges of FER in natural environments, providing a more robust and accurate solution. The AEMT model significantly advances the field of FER by improving the robustness and accuracy of emotion recognition in complex real-world scenarios. This work not only enhances the capabilities of affective computing systems but also opens new avenues for future research in improving model efficiency and expanding multimodal data integration.
Journal Article
A systematic review of parental burnout and related factors among parents
Background
Parenting is both a complex and stressful endeavor, so parents sometimes experience parenting burnout. The main objective of this study was to provide an overview of factors related to general parental burnout (PB) among parents with at least one child based on the Ecological Systems Theory (EST).
Methods
PubMed, Web of Science, EBSCO, CNKI and WanFang were systematically searched for studies published from 2010 to July 2023 for peer-reviewed articles using keywords extracted from Medical Subject Headings such as “parenting”, “parental”, “burnout”, “psychological burnout”, “burn-out syndrome”. Studies were included if they described associations between factors and PB among parents of children aged 0-18 years old in the general population, and published in an English or Chinese language peer-reviewed journal. The Quality Assessment Tool for Studies with Diverse Designs (QATSDD) was employed to assess the risk of bias of included studies.
Results
Of 2037 articles, 26 articles met the inclusion criteria. Based on the Ecological Systems Theory (EST), we found that microsystem-individual factors such as gender, educational level, income, parental personality, internalization of maternal parental motivation, unmitigated communion, self-compassion and concern for others, alexithymia, anxiety and depressive symptoms, parental perfectionism, resilience, low self-esteem and high need for control, mother's attachment style were identified as being associated with parenting burnout. Mesosystem-interpersonal factors involve parent-child relationship and marital satisfaction. The exosystem-organizational or community factors include the number of children in the household, neighborhood and the number of hours spent with children, child's illness, child's behavior problems and social support. The macrosystem-society/policy or culture factors are mainly personal values and cultural values.
Conclusions
This systematic review found several factors that have been investigated in relation to PB. However, the majority of the factors were reported by one or two studies often implementing a cross-sectional design. Nevertheless, we still recommend that health policymakers and administrators relieve parenting burnout among parents with children by adjusting these modifiable factors.
Journal Article
Associations between loneliness and perceived social support and outcomes of mental health problems: a systematic review
Background
The adverse effects of loneliness and of poor perceived social support on physical health and mortality are established, but no systematic synthesis is available of their relationship with the outcomes of mental health problems over time. In this systematic review, we aim to examine the evidence on whether loneliness and closely related concepts predict poor outcomes among adults with mental health problems.
Methods
We searched six databases and reference lists for longitudinal quantitative studies that examined the relationship between baseline measures of loneliness and poor perceived social support and outcomes at follow up. Thirty-four eligible papers were retrieved. Due to heterogeneity among included studies in clinical populations, predictor measures and outcomes, a narrative synthesis was conducted.
Results
We found substantial evidence from prospective studies that people with depression who perceive their social support as poorer have worse outcomes in terms of symptoms, recovery and social functioning. Loneliness has been investigated much less than perceived social support, but there is some evidence that greater loneliness predicts poorer depression outcome. There is also some preliminary evidence of associations between perceived social support and outcomes in schizophrenia, bipolar disorder and anxiety disorders.
Conclusions
Loneliness and quality of social support in depression are potential targets for development and testing of interventions, while for other conditions further evidence is needed regarding relationships with outcomes.
Journal Article
Tuning excited state electronic structure and charge transport in covalent organic frameworks for enhanced photocatalytic performance
Covalent organic frameworks (COFs) represent an emerging class of organic photocatalysts. However, their complicated structures lead to indeterminacy about photocatalytic active sites and reaction mechanisms. Herein, we use reticular chemistry to construct a family of isoreticular crystalline hydrazide-based COF photocatalysts, with the optoelectronic properties and local pore characteristics of the COFs modulated using different linkers. The excited state electronic distribution and transport pathways in the COFs are probed using a host of experimental methods and theoretical calculations at a molecular level. One of our developed COFs (denoted as COF-4) exhibits a remarkable excited state electron utilization efficiency and charge transfer properties, achieving a record-high photocatalytic uranium extraction performance of ~6.84 mg/g/day in natural seawater among all techniques reported so far. This study brings a new understanding about the operation of COF-based photocatalysts, guiding the design of improved COF photocatalysts for many applications.
Covalent organic frameworks (COFs) represent an emerging class of organic photocatalysts but it remains challenging to gain insight into photocatalytic active sites and reaction mechanisms. Herein, the authors construct a family of isoreticular crystalline hydrazide-based COF photocatalysts, with the optoelectronic properties and local pore characteristics of the COFs modulated using different linkers
Journal Article
Loneliness and the onset of new mental health problems in the general population
PurposeLoneliness is associated with poor health including premature mortality. There are cross-sectional associations with depression, anxiety, psychosis, and other mental health outcomes. However, it is not known whether loneliness is causally linked with the new onset of mental health problems in the general population. Longitudinal studies are key to understanding this relationship. We synthesized evidence from longitudinal studies investigating the relationship between loneliness and new onset of mental health problems, in the general population.MethodWe systematically searched six electronic databases, unpublished sources, and hand-searched references, up to August 2021. We conducted a meta-analysis of eight independent cohorts and narrative synthesis of the remaining studies.ResultsWe included 32 studies, of which the majority focused on depression. Our narrative synthesis found most studies show loneliness at baseline which is associated with the subsequent new onset of depression. The few studies on anxiety and self-harm also showed a positive association. Our meta-analysis found a pooled adjusted odds ratio of 2.33 (95% CI 1.62–3.34) for risk of new onset depression in adults who were often lonely compared with people who were not often lonely. This should be interpreted with caution given evidence of heterogeneity.ConclusionLoneliness is a public mental health issue. There is growing evidence it is associated with the onset of depression and other common mental health problems. Future studies should explore its impact across the age range and in more diverse populations, look beyond depression, and explore the mechanisms involved with a view to better informing appropriate interventions.
Journal Article
The effects of physical activity on the mental health of typically developing children and adolescents: a systematic review and meta-analysis
Background
Physical activity has gained attention in recent years as a promising intervention for improving the mental health of children and adolescents. However, evidence supporting the effectiveness of physical activity interventions for the mental health of typically developing children and adolescents remains limited.
Methods
This study conducted a comprehensive search across five electronic databases up to July 2024. Studies were eligible for inclusion if they involved an intervention with a control group that examined the effects of physical activity on the mental health of typically developing children and adolescents. Articles focusing on participants with developmental, behavioral, or psychiatric disorders were excluded. A random-effects meta-analysis was conducted using Stata 18.0. The quality of evidence and risk of bias were assessed using the GRADE framework and the PEDro scale.
Results
The initial search yielded 27,527 articles, of which 30 met the inclusion criteria. Meta-regression analysis indicated that country and intervention frequency were significant sources of heterogeneity. Physical activity interventions were significantly more effective than the control group in improving mental health (SMD = 0.37, 95% CI: 0.20 to 0.53). These interventions showed particularly strong effects on stress reduction (SMD = 0.86, 95% CI: 0.15 to 1.56) and social competence enhancement (SMD = 0.56, 95% CI: 0.07 to 1.06). Moreover, physical activity interventions were notably more effective for male adolescents (SMD = 1.11, 95% CI: 0.34 to 1.88) and those at the secondary school level (SMD = 0.45, 95% CI: 0.23 to 1.69).
Conclusions
Physical activity is beneficial in improving various aspects of mental health, including anxiety, depression, stress, self-esteem, and social competence in typically developing children and adolescents. However, the quality of evidence in this study is low due to methodological limitations of the studies included in this review. More high-quality randomized controlled trials are needed to validate these findings. Teachers and community workers can leverage physical activity as a preventive strategy to promote the mental health of children and adolescents. Future research should also investigate how factors like socioeconomic status and the sporting environment impact the effectiveness of these interventions.
Trial registration
PROSPERO, CRD42024567153.
Journal Article
Smart city construction and urban green development: empirical evidence from China
Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions.
Journal Article
Separation of Semiconducting Carbon Nanotubes Using Conjugated Polymer Wrapping
In the past two decades, single-walled carbon nanotubes (SWNTs) have been explored for electronic applications because of their high charge carrier mobility, low-temperature solution processability and mechanical flexibility. Semiconducting SWNTs (s-SWNTs) are also considered an alternative to traditional silicon-based semiconductors. However, large-scale, as-produced SWNTs have poor solubility, and they are mixtures of metallic SWNTs (m-SWNTs) and s-SWNTs, which limits their practical applications. Conjugated polymer wrapping is a promising method to disperse and separate s-SWNTs, due to its high selectivity, high separation yield and simplicity of operation. In this review, we summarize the recent progress of the conjugated polymer wrapping method, and discuss possible separation mechanisms for s-SWNTs. We also discuss various parameters that may affect the selectivity and sorting yield. Finally, some electronic applications of polymer-sorted s-SWNTs are introduced. The aim of this review is to provide polymer chemist a basic concept of polymer based SWNT separation, as well as some polymer design strategies, influential factors and potential applications.
Journal Article
Single-pixel p-graded-n junction spectrometers
Ultra-compact spectrometers are becoming increasingly popular for their promising applications in biomedical analysis, environmental monitoring, and food safety. In this work, we report a single-pixel-photodetector spectrometer with a spectral range from 480 nm to 820 nm, based on the AlGaAs/GaAs p-graded-n junction with a voltage-tunable optical response. To reconstruct the optical spectrum, we propose a tailored method called Neural Spectral Fields (NSF) that leverages the unique wavelength and bias-dependent responsivity matrix. Our spectrometer achieves a high spectral wavelength accuracy of up to 0.30 nm and a spectral resolution of up to 10 nm. Additionally, we demonstrate the high spectral imaging performance of the device. The compatibility of our demonstration with the standard III-V process greatly accelerates the commercialization of miniaturized spectrometers.
The miniaturization of spectrometers to a submillimeter-scale footprint opens opportunities for applications in hyperspectral imaging and lab-on-a-chip systems. Here, the authors report a high-performance single-pixel photodetector spectrometer based on the III-V semiconductor p-graded-n junction, featuring a voltage-tunable optical response.
Journal Article