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With the development of science and technology, wearable electronics are increasingly widely used in medical, environmental monitoring, and other fields. Thus, the demand for flexible electrodes is increasing. The two-dimensional material Ti3C2Tx has attracted much attention in the manufacture of flexible electrodes due to its excellent mechanical and electrical properties. However, the brittleness of pure Ti3C2Tx films has become a major obstacle for their use as flexible electrodes in wearable devices. Therefore, solving the brittleness problem of flexible electrodes based on Ti3C2Tx while maintaining the excellent performance of Ti3C2Tx has become an urgent problem. To solve this problem, Ti3C2Tx was compounded with waterborne polyurethane (WPU), and a Ti3C2Tx-WPU composite film with a hierarchical structure was constructed by evaporation-assisted self-assembly. The Ti3C2Tx-WPU composite film not only retains the excellent electrical conductivity of Ti3C2Tx (100 S m−1) but also has flexibility (20 MJ m−3). Furthermore, the Ti3C2Tx-WPU composite film is applied to functional devices such as contact pressure sensors and non-contact proximity sensors. Finally, the Ti3C2Tx-WPU composite film wearable device demonstrates its practical application potential in the field of wearable devices. [ABSTRACT FROM AUTHOR]

Background: The study aims to investigate the long-term impact of lifestyle-related factors and physical health on life satisfaction and depressive symptoms among Chinese community-dwelling older adults. Methods: Using data from the China Health and Retirement Longitudinal Study (CHARLS), the analytic sample of this study included 1,068 older adults who had participated in the surveys in both 2011 and 2018. Multivariate regression was employed to analyze both cross-sectional and longitudinal relationships between lifestyle-related factors, physical health, and subjective well-being – specifically depressive symptoms and life satisfaction. Additionally, the model tested how these factors correlate with life satisfaction across different groups of depressive symptom changes among older adults, categorized as not at risk of depression, intermittent depression, and chronic depression. Results: Multimorbidity was significantly related to baseline and follow-up depressive risk in older adults. Shorter sleep duration was associated with baseline depression risk. Current alcohol drinkers reported significantly more severe depressive symptoms than non-drinkers. At baseline, current smokers were more likely to have a lower degree of life satisfaction than nonsmokers. Among older adults with chronic depression at the 7-year follow-up, former smokers tended to have lower life satisfaction than nonsmokers. Conclusions: Our findings identified drinking alcohol and having a shorter sleep duration as modifiable lifestyle-related risk factors for late-life depression and smoking as a detrimental factor for life satisfaction in older Chinese adults. Multimorbidity was a significant predictor of more depressive symptoms. Our findings have implications for future psychosocial interventions that target the alleviation of depressive symptoms and the promotion of life satisfaction in older Chinese people based on their different long-term mental and physical health conditions. [ABSTRACT FROM AUTHOR]

With the development of information technology in modern military confrontation, specific emitter identification has become a hot and difficult topic in the field of electronic warfare, especially in the field of electronic reconnaissance. Specific emitter identification requires a historical reconnaissance signal as the matching template. In order to avoid being intercepted by enemy electronic reconnaissance equipment, modern radar often has multiple sets of working parameters, such as pulse width and signal bandwidth, which change when performing different tasks and training. At this time, the collected fingerprint features cannot fully match the fingerprint template in the radar database, making the traditional specific emitter identification algorithm ineffective. Therefore, when the working parameters of enemy radar change, that is, when there is no such variable working parameter signal template in our radar database, it is a bottleneck problem in the current electronic reconnaissance field to realize the specific emitter identification. In order to solve this problem, this paper proposes a network model based on metric learning. By learning deep fingerprint features and learning a deep nonlinear metric between different sample signals, the same individual sample signals under different working parameters can be associated. Even if there are no samples under a certain kind of working parameter signal, it can still be associated with the original individual through this network model, so as to achieve the purpose of specific emitter identification. As opposed to the situation in which the traditional specific emitter identification algorithm cannot be associated with the original individual when the signal samples of changing working parameters are not collected, the algorithm proposed in this paper can better solve the problem of changing working parameters and zero samples.

Rapid and correct estimation of driver lane change intention plays an important role in the advanced driver assistance system (ADAS), which could make the driver improve the reliability of the ADAS system and help to decrease driver workload. In this study, a method based on the long short-term memory network (LSTM) and Dempster-Shafer evidence theory is proposed. The model consists of a preliminary decision-making label and a final decision-making label. Driver visual information, head orientation, and vehicle dynamics are collected by preliminary decision-making label. Then, LSTM is used to calculate the initial probability of the driver lane change (left, right, and lane keeping) maneuver intention. The outputs of LSTM are normalized and assigned a basic probability by the Dempster-Shafer evidence theory. The final decision-making label analyzes the information and outputs the probability of each lane change intention and the decision is to identify the driver's current intention. The experimental results show that the accuracy of the model is 90.7% for the intention of changing left and 89.1% for the intention of changing right. The outcome of this work is an essential component for all levels of road vehicle automation., Author(s): Zhi-Qiang Liu [1]; Man-Cai Peng (corresponding author) [1]; Yue-Chen Sun [1] 1. Introduction Traffic crashes and collisions worldwide become increasingly complicated in terms of safety with the number of [...]

Awareness of COVID-19 infection risk and oscillation patterns ('waves') may affect older people's mental health. Empirical data from populations experiencing multiple waves of community outbreaks can inform guidance for maintaining mental health. This study aims to investigate the effects of COVID-19 infection risk and oscillations on depression among community-dwelling older people in Hong Kong. A rolling cross-sectional telephone survey method was used. Screening for depression risk was conducted among 8,163 older people (age ≥ 60) using the Patient Health Questionnaire-2 (PHQ-2) from February to August 2020. The relationships between PHQ-2, COVID-19 infection risk proxies – change in newly infected cases and effective reproductive number (Rt), and oscillations – stage of a 'wave' reported in the media, were analysed using correlation and regression. 8.4% of survey respondents screened positive for depression risk. Being female (β =.08), having a pre-existing mental health issue (β =.21), change in newly infected cases (β =.05), and screening during the latency period before the media called out new waves (β =.03), contributed to higher depression risk (R2 =.06, all p <.01). While depression risk does not appear alarming in this sample, our results highlight that older people are sensitive to reporting of infection, particularly among those with existing mental health needs. Future public health communication should balance awareness of infection risks with mental health protection. [ABSTRACT FROM AUTHOR]