Integration of Satellite Data, Physically-based Model, and Deep Neural Networks for Historical Terrestrial Water Storage Reconstruction

Terrestrial water storage (TWS) is an essential part of the global water cycle. Long-term monitoring of observed and modeled TWS is fundamental to analyze droughts, floods, and other meteorological extreme events caused by the effects of climate change on the hydrological cycle. Over the past several decades, hydrologists have been applying physically-based global hydrological model (GHM) and land surface model (LSM) to simulate TWS and the water components (e.g., groundwater storage) composing TWS. However, the reliability of these physically-based models is often affected by uncertainties in climatic forcing data, model parameters, model structure, and mechanisms for physical process representations. Launched in March 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission exclusively applies remote sensing techniques to measure the variations in TWS on a global scale. The mission length of GRACE, however, is too short to meet the requirements for analyzing long-term TWS. Therefore, lots of effort has been devoted to the reconstruction of GRACE-like TWS data during the pre-GRACE era. Data-driven methods, such as multilinear regression and machine learning, exhibit a great potential to improve TWS assessments by integrating GRACE observations and physically-based simulations. The advances in artificial intelligence enable adaptive learning of correlations between variables in complex spatiotemporal systems. As for GRACE reconstruction, the applicability of various deep learning techniques has not been well studied previously. Thus, in this study, three deep learning-based models are developed based on the LSM-simulated TWS, to reconstruct the historical TWS in the Canadian landmass from 1979 to 2002. The performance of the models is evaluated against the GRACE-observed TWS anomalies from 2002 to 2004, and 2014 to 2016. The trained models achieve a mean correlation coefficient of 0.96, with a mean RMSE of 53 mm. The results show that the LSM-based deep learning models significantly improve the match between original LSM simulations and GRACE observations

Impact of main residential locations on depressive symptoms among older adults in China: A Blinder–Oaxaca decomposition analysis

BackgroundWith the development of urbanization in China, the scale of internal migration and the number of immigrants among older adults are increasing. This requires paying attention to the living conditions and environment of immigrants. Many studies note a gap in the prevalence of depressive symptoms among older adults living in different main residential locations. However, few studies have examined the extent to which main residential locations influence depressive symptoms among older adults. This study aims to quantify the effect of main residential locations on depressive symptoms.MethodsFor this study, we used data from the 2018 Chinese Longitudinal Health and Longevity Survey and randomly selected 8,210 individuals aged 65 years and older were from the community to determine the effect of main residential locations on depressive symptoms among older adults. We further used the Blinder–Oaxaca decomposition method to quantify the explanatory factors of depressive symptom gaps among older adults and to estimate the relative effect of individual characteristics on depressive symptoms.ResultsIn this study, we noted significant differences in depressive symptoms among older adults in different main residential locations. Rural–urban migrants had higher depressive symptom scores (7.164). According to the Blinder–Oaxaca decomposition analysis, the high proportion of the depressive symptom gap can be explained by years of education, income, and exercise among different main residential locations groups. In addition, in the main parts of the explained differences, the proportions of the limitation of activities of daily living (2.28, 0.46, and −52.11%) showed opposite effects, while their share in different main residential locations groups varied widely.ConclusionUrbanization has resulted in more rural people moving to urban areas in China; Rural–urban migrants have the highest prevalence of depressive symptoms, which needs attention. Thus, there is an urgent need to integrate the health insurance and pension policy for urban and rural residents. This study provides a basis for formulating health policies and promoting the mental health of older adults in China as well as in low- and middle-income countries

Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach

Deep learning (DL) algorithms have previously demonstrated their effectiveness in streamflow prediction. However, in hydrological time series modelling, the performance of existing DL methods is often bound by limited spatial information, as these data-driven models are typically trained with lumped (spatially aggregated) input data. In this study, we propose a hybrid approach, namely the Spatially Recursive (SR) model, that integrates a lumped long short-term memory (LSTM) network seamlessly with a physics-based hydrological routing simulation for enhanced streamflow prediction. The lumped LSTM was trained on the basin-averaged meteorological and hydrological variables derived from 141 gauged basins located in the Great Lakes region of North America. The SR model involves applying the trained LSTM at the subbasin scale for local streamflow predictions which are then translated to the basin outlet by the hydrological routing model. We evaluated the efficacy of the SR model with respect to predicting streamflow at 224 gauged stations across the Great Lakes region and compared its performance to that of the standalone lumped LSTM model. The results indicate that the SR model achieved performance levels on par with the lumped LSTM in basins used for training the LSTM. Additionally, the SR model was able to predict streamflow more accurately on large basins (e.g., drainage area greater than 2000 km2), underscoring the substantial information loss associated with basin-wise feature aggregation. Furthermore, the SR model outperformed the lumped LSTM when applied to basins that were not part of the LSTM training (i.e., pseudo-ungauged basins). The implication of this study is that the lumped LSTM predictions, especially in large basins and ungauged basins, can be reliably improved by considering spatial heterogeneity at finer resolution via the SR model.</p

Mediating Factors Explaining the Associations between Solid Fuel Use and Self-Rated Health among Chinese Adults 65 Years and Older: A Structural Equation Modeling Approach

Exposure to indoor air pollution from cooking with solid fuel has been linked with the health of elderly people, although the pathway to their association is unclear. This study aimed to investigate the mediating effects between solid fuel use and self-rated health by using structural equation modeling (SEM) with the baseline data from Chinese Longitudinal Healthy Longevity Survey (CLHLS). We conducted a cross-sectional survey among 7831 elderly people aged &gt;65 years from the CLHLS. SEM was used to analyze the pathways underlying solid fuel use and self-rated health. We estimated indirect effects of sleep quality (&beta; = &minus;0.027, SE = 0.006), cognitive abilities (&beta; = &minus;0.006, SE = 0.002), depressive symptoms (&beta; = &minus;0.066, SE = 0.007), systolic blood pressure (&beta; = 0.000, SE = 0.000), and BMI (&beta; = &minus;0.000, SE = 0.000) on the association between solid fuel and the self-rated health using path analysis. Depressive symptoms emerged as the strongest mediator in the relationship between solid fuel use and self-rated health in the elderly. Interventions targeting sleep quality, cognitive abilities, depressive symptoms, systolic blood pressure, and BMI could greatly reduce the negative effects of solid fuel use on the health of the elderly population

Analysis of Sub/Super-Synchronous Oscillation of Direct-Drive Offshore Wind Power Grid-Connected System via VSC-HVDC

The system of offshore direct-drive wind farm connected to the power grid via voltage source converter based high voltage direct current (VSC-HVDC) transmission consists of several converters, which have different time scale control loops and complex dynamic characteristics. Based on an example case with two direct-drive wind farms and VSC-HVDC transmission system, the sub/super-synchronous oscillation modes of the system and its relationship with current control loops are studied by state space analysis. The research shows that there are three dominant modes related to the current control of the converter in the system, which are the oscillation mode between wind farms and the offshore converter station, the mode between the offshore wind farms, and the mode between the onshore converter station and the alternating current (AC) system. The modes at the wind farm side are decoupled from the mode between the onshore converter station and the AC system. The relevant control parameters of the converters and the operating conditions have an important impact on the stability of the three modes. The oscillation caused by the single dominant mode may spread to the other side of VSC-HVDC, which means it is necessary to identify the root cause of oscillation in order to design the suppression strategy. The research results is of guidance to the understanding of the dynamic characteristics of offshore wind power grid-connected systems via VSC-HVDC, parameter design, and oscillation suppression

RCS reduction effect based on transparent and flexible polarization conversion metasurface arrays

In recent years, radar cross section (RCS) reduction techniques based on electromagnetic absorption materials have become a hot research topic in the field of electromagnetic stealth. This paper proposes a transparent conformal encoded metasurface based on polarization rotation units. The metasurface array is optimized using the whale optimization algorithm to construct a 1-bit polarization rotation encoded unit array. The proposed metasurface array exhibits good RCS reduction and electromagnetic wave polarization conversion performance in the frequency range of 13.2–20.7 GHz. The RCS reduction effect of the metasurface array is effective at different angles and polarization states. The metasurface is composed of transparent and flexible materials, namely ITO, PET, and PVC plastic. It exhibits conformal properties while maintaining a high physical transmittance of up to 83.6%. The RCS reduction performance of the metasurface is studied under different curvatures and demonstrates good conformal scattering characteristics. The RCS variation of ITO material compared to traditional metallic materials was also analyzed. It was found that ITO with low surface resistance is an effective means to broaden the RCS bandwidth. This makes it suitable for theoretical research and the design of electromagnetic stealth for electronic devices such as radars and antennas with different curvatures

Association between the traditional Chinese medicine constitution and metabolic dysfunction-associated fatty liver disease in older people: A cross-sectional study

Background: Few studies have focused on the relationship between the traditional Chinese medicine constitution (TCMC) and metabolic dysfunction-associated fatty liver disease (MAFLD) in older populations. We sought to investigate the distribution of MAFLD and the TCMC in older people, and provide a theoretical basis for TCMC-based management of MAFLD in this population. Methods: A cross-sectional study was conducted among older (≥65 years) individuals in Zhongshan, China. Information on common sociodemographic characteristics, medical history, anthropometric measurements, and the TCMC was collected. The chi-square test, multivariable logistic regression analysis, subgroup analysis, and inverse probability weighting of the propensity score were used to explore the relationship between MAFLD and the TCMC. Results: Of 7085 participants, 1408 (19.9 %) had MAFLD. The three most common TCMC types in MAFLD patients were “phlegm-dampness”, “gentleness”, and “yin-deficiency”. After adjustment for gender, age, tobacco smoking, alcohol consumption, body mass index, abnormal waist-to-hip ratio, hypertension, diabetes mellitus, and dyslipidemia, MAFLD was positively associated with the phlegm-dampness constitution (PDC) (ORadjusted (95 % CI) = 1.776 (1.496–2.108), P < 0.001), and negatively correlated with the qi-depression constitution (0.643 (0.481–0.860), 0.003). A stronger correlation between the PDC and MAFLD was observed in men compared with women (ORadjusted = 2.04 (95%CI = 1.47–2.84) vs. 1.70 (95%CI = 1.39–2.08), Pinteraction = 0.003) as well as between people who smoked tobacco and non-tobacco-smoking individuals (2.11 (1.39–3.21) vs. 1.75 (1.45–2.12), 0.006). Conclusions: A positive relationship was observed between MAFLD and the PDC in older people living in Zhongshan. Early detection and treatment of the PDC (especially in men and smokers) could prevent the occurrence and development of MAFLD

Non-invasive transdermal delivery of biomacromolecules with fluorocarbon-modified chitosan for melanoma immunotherapy and viral vaccines

Abstract Transdermal drug delivery has been regarded as an alternative to oral delivery and subcutaneous injection. However, needleless transdermal delivery of biomacromolecules remains a challenge. Herein, a transdermal delivery platform based on biocompatible fluorocarbon modified chitosan (FCS) is developed to achieve highly efficient non-invasive delivery of biomacromolecules including antibodies and antigens. The formed nanocomplexes exhibits effective transdermal penetration ability via both intercellular and transappendageal routes. Non-invasive transdermal delivery of immune checkpoint blockade antibodies induces stronger immune responses for melanoma in female mice and reduces systemic toxicity compared to intravenous injection. Moreover, transdermal delivery of a SARS-CoV-2 vaccine in female mice results in comparable humoral immunity as well as improved cellular immunity and immune memory compared to that achieved with subcutaneous vaccine injection. Additionally, FCS-based protein delivery systems demonstrate transdermal ability for rabbit and porcine skins. Thus, FCS-based transdermal delivery systems may provide a compelling opportunity to overcome the skin barrier for efficient transdermal delivery of bio-therapeutics