•A time-domain based method for distributed dynamic load identification considering unknown-but-bounded uncertainties in structural systems.•The reconstruction method is investigated to acquire the ...envelope interval of the identified load by combining uncertainty propagation analysis and the inverse problems in dynamics.•The distributed dynamic load acting on continuous structures may be spatially approximated by Chebyshev orthogonal polynomial at each sampling time.
A time-domain based method for distributed dynamic load identification is proposed in this study considering unknown-but-bounded uncertainties in structural systems. The spatiotemporal dynamic load is further approximated by Chebyshev orthogonal polynomial in time history. Thus, the problem of distributed load reconstruction may be converted into the issue of polynomial coefficient calculation at each sampling time by utilizing a series of dynamic analysis. In accordance with the practical engineering, the acceleration response is used as the system input. In terms of the uncertainty quantification problems, the interval analysis method based on Taylor expansion (IAMBTE) is systematically developed to accomplish the envelope interval of identified load. To facilitate the analysis, two kinds of load are required to be identified, among which the nominal value of the identified load may be straightforwardly achieved through the inverse system, whereas the interval boundaries should be settled by the interval propagation analysis. Eventually, two numerical examples are investigated to demonstrate the efficiency and precision of the developed methodology.
Developing low-cost and high-performance metal-free oxygen reduction reaction (ORR) catalysts for fuel cells is highly desirable but still full of challenges. In this study, nitrogen and phosphorus ...co-functionalized three-dimensional (3D) porous carbon networks (NPCN) have been prepared by pyrolysis the zero-dimensional carbon quantum dots (CQDs) and a supermolecular gel of self-assembled melamine and amino trimethylene phosphonic acid (ATMP). The resultant NPCN catalysts possess unique 3D networks-like porous architecture, large specific surface area (743 m2 g−1) and abundant edge defects. As a catalyst for ORR, the optimized NPCN-900 (pyrolyzed at 900 °C) displays positive onset potential at 0.92 V and 0.74 V (vs. RHE) in alkaline and acidic media respectively, which are roughly close to those of Pt/C (0.93 V and 0.80 V). Additionally, the NPCN-900 exhibits longer-term stability and strong endurance to methanol over a wide pH range of aqueous media, which is much superior to that of Pt/C. Considering the outstanding activity of NPCN-900, it can be worked as a prospective metal-free catalyst to substitute commercial Pt/C for ORR in fuel cells.
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An increasing number of studies have been conducted to determine a possible linkage between maternal exposure to ambient fine particulate matter and effects on the developing human fetus that can ...lead to adverse birth outcomes, but, the present results are not consistent. A total of 23 studies published before July 2016 were collected and analyzed and the mean value of reported exposure to fine particulate matter (PM2.5) ranged from 1.82 to 22.11 We found a significantly increased risk of preterm birth with interquartile range increase in PM2.5 exposure throughout pregnancy (odds ratio (OR) = 1.03; 95% conditional independence (CI): 1.01–1.05). The pooled OR for the association between PM2.5 exposure, per interquartile range increment, and term low birth weight throughout pregnancy was 1.03 (95% CI: 1.02–1.03). The pooled ORs for the association between PM2.5 exposure per 10 increment, and term low birth weight and preterm birth were 1.05 (95% CI: 0.98–1.12) and 1.02 (95% CI: 0.93–1.12), respectively throughout pregnancy. There is a significant heterogeneity in most meta-analyses, except for pooled OR per interquartile range increase for term low birth weight throughout pregnancy. We here show that maternal exposure to fine particulate air pollution increases the risk of preterm birth and term low birth weight. However, the effect of exposure time needs to be further explored. In the future, prospective cohort studies and personal exposure measurements needs to be more widely utilized to better characterize the relationship between ambient fine particulate exposure and adverse birth outcomes.
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•The results had shorter intervals indicate and smaller heterogeneity by using IQR increment increase as selected standard.•The manuscript included the latest research results and updated the previous systematic review and meta-analysis.
Meta-analysis of preterm birth and term low birth weight of PM2.5
Since emotions play an important role in the daily life of human beings, the need and importance of automatic emotion recognition has grown with increasing role of human computer interface ...applications. Emotion recognition could be done from the text, speech, facial expression or gesture. In this paper, we concentrate on recognition of “inner” emotions from electroencephalogram (EEG) signals. We propose real-time fractal dimension based algorithm of quantification of basic emotions using Arousal-Valence emotion model. Two emotion induction experiments with music stimuli and sound stimuli from International Affective Digitized Sounds (IADS) database were proposed and implemented. Finally, the real-time algorithm was proposed, implemented and tested to recognize six emotions such as fear, frustrated, sad, happy, pleasant and satisfied. Real-time applications were proposed and implemented in 3D virtual environments. The user emotions are recognized and visualized in real time on his/her avatar adding one more so-called “emotion dimension” to human computer interfaces. An EEG-enabled music therapy site was proposed and implemented. The music played to the patients helps them deal with problems such as pain and depression. An EEG-based web-enable music player which can display the music according to the user’s current emotion states was designed and implemented.
The epidemiological evidence on relationships between long-term exposure to particulate matter and hypertension and blood pressure has been inconclusive. Limited evidence was available for ...particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) in rural areas of developing countries.
This study aimed to investigate the associations between long-term exposure to PM1 and hypertension and blood pressure among rural Chinese population.
This study included 39,259 participants who had completed the baseline survey from Henan Rural Cohort. Participants' exposure to PM1 was assessed by a satellite-based spatiotemporal model. The binary logistic regression model was used to examine the association between long-term PM1 exposure and hypertension, and multivariable linear regression model was used to investigate the associations between long-term PM1 exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). Moreover, we examined potential effect modifications by demographic, lifestyle and diet factors.
The mean concentration of PM1 for all participants during the 3-year before baseline survey was 59.98 μg/m3. Each 1 μg/m3 increase in PM1 concentration was significantly associated with an increase of 4.3% Odds ratio(OR) = 1.043, 95% confidence interval(CI): 1.033, 1.053 in odds for hypertension, an increase of 0.401 mm Hg (95% CI, 0.335, 0.467), 0.328 mm Hg (95% CI, 0.288, 0.369), 0.353 mm Hg (95% CI, 0.307, 0.399) and 0.073 mm Hg (95% CI, 0.030, 0.116) in SBP, DBP, MAP and PP, respectively. Further stratified analyses showed that the effect of PM1 on hypertension and blood pressure could be modified by sex, lifestyle and diet.
This study suggests that long-term exposure to ambient PM1 increases the risk of hypertension and is associated with elevations in blood pressure in rural Chinese adults, especially in male and those with unhealthy habits.
•Rural cohort participants were exposed to high level of PM1 during the study period.•PM1 was related to increased risk of hypertension and elevated blood pressure.•Males and those with unhealthy habits were more susceptible to the adverse effect.
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•Higher PM1, PM2.5, NO2 exposure concentrations were associated with increased odds of type 2 diabetes.•Higher levels of PM1, PM2.5, NO2 exposure were associated with an elevated ...fasting blood glucose levels.•Males and populations aged 65 years or older may susceptible to air pollution.
To evaluate the associations between long-term exposure to particulate matter with an aerodynamic diameter ≤1.0 μm and ≤2.5 μm (PM1 and PM2.5), nitrogen dioxide (NO2) and type 2 diabetes prevalence and fasting blood glucose levels in Chinese rural populations.
A total of 39, 259 participants were enrolled in The Henan Rural Cohort study. Questionnaires and medical examination were conducted from July 2015 to September 2017 in rural areas of Henan province, China. Three-year average residential exposure levels of PM1, PM2.5, NO2 for each subject were estimated by a spatiotemporal model. Logistic regression and linear regression models were applied to estimate the associations between PM1, PM2.5, NO2 exposure and type 2 diabetes prevalence and fasting blood glucose levels.
The mean 3-year residential exposure concentrations of PM1, PM2.5 and NO2 was 57.4 μg/m3, 73.4 μg/m3 and 39.9 μg/m3, respectively. Higher exposure concentrations of PM1, PM2.5, NO2 by 1 μg/m3 was positively related to a 4.0% (95%CIs: 1.026, 1.054), 6.8% (1.052, 1.084) and 5.0% (1.039, 1.061) increase in odds of type 2 diabetes in the final adjusted models. Besides, a 1 μg/m3 increase of PM1, PM2.5 and NO2 was related to a 0.020 mmol/L (95%CIs: 0.014, 0.026), 0.036 mmol/L (95%CIs: 0.030, 0.042) and 0.030 mmol/L (95%CIs: 0.026, 0.034) mmol/L higher fasting blood glucose levels.
Higher exposure concentrations of air pollutants were positively related to the increased odds of type 2 diabetes, as well as higher fasting blood glucose levels in Chinese rural populations.
•Rural residents in central China were exposed to high levels of PM1.•PM1 exposure was related to increased TC and LDL-C, and decreased TG and HDL-C.•High levels of PM1 was associated with higher ...risk of dyslipidemias.•Males, older and overweight participants were vulnerable to adverse effects of PM1.
Air pollution has been shown to be associated with blood lipid levels. However, studies on long-term ambient particulate matter with aerodynamic diameter ≤1 μm (PM1) exposure in high-exposure areas are still limited. This study aimed to explore the associations among long-term PM1 exposure, blood lipids and dyslipidemias.
Baseline data of The Henan Rural Cohort study was used in present study, including a total of 39,259 participants aged from 18 to 79 years. Daily levels of PM1 were estimated by a spatiotemporal model using ground-level measurements of PM1, satellite remote sensing data and other predictors, according to participants' home addresses. Individual exposure to PM1 was the 3-year average before baseline investigation. Linear regression and logistic regression models were applied to examine the associations among PM1, blood lipids ((total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C)), and prevalence of dyslipidemias.
The 3-year concentration of PM1 was 55.7 ± 2.1 μg/m3. Each 1 μg/m3 increment of PM1 was associated with an increase of 0.21% (95% confidence interval (CI): 0.11%–0.31%) in TC and 0.75% (95% CI: 0.61%–0.90%) in LDL-C, while decrease of 2.68% (95% CI: 2.43%–2.93%) in TG and 0.47% (95% CI: 0.35%–0.59%) in HDL-C. Each 1 μg/m3 increase in PM1 was associated with 6% (95% CI: 4%–8%), 3% (95% CI: 2%–5%) and 5% (95% CI: 3%–7%) higher risks of hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia. Sex, age and BMI statistically modified the associations between PM1 with blood lipid levels and dyslipidemias.
Higher PM1 exposure was associated with adverse changes of blood lipid levels and dyslipidemias. Males, older and overweight participants were susceptive to the adverse effects of PM1.
Abstract
We study the surface composition of asteroids with visible and/or infrared spectroscopy. For example, asteroid taxonomy is based on the spectral features or multiple color indices in visible ...and near-infrared wavelengths. The composition of asteroids gives key information to understand their origin and evolution. However, we lack compositional information for faint asteroids due to the limits of ground-based observational instruments. In the near future, the Chinese Space Survey Telescope (CSST) will provide multiple colors and spectroscopic data for asteroids of apparent magnitude brighter than 25 and 23 mag, respectively. With the aim of analyzing the CSST spectroscopic data, we applied an algorithm using artificial neural networks (ANNs) to establish a preliminary classification model for asteroid taxonomy according to the design of the survey module of CSST. Using the SMASS II spectra and the Bus–Binzel taxonomic system, our ANN classification tool composed of five individual ANNs is constructed, and the accuracy of this classification system is higher than 92%. As the first application of our ANN tool, 64 spectra of 42 asteroids obtained by us in 2006 and 2007 with the 2.16 m telescope in the Xinglong station (Observatory Code 327) of National Astronomical Observatory of China are analyzed. The predicted labels of these spectra using our ANN tool are found to be reasonable when compared to their known taxonomic labels. Considering its accuracy and stability, our ANN tool can be applied to analyze CSST asteroid spectra in the future.
Circular RNA (circRNA) is a class of endogenous non-coding RNAs that are closely related to the pathogenesis of many human diseases, particularly cancer. However, the characterization of circRNAs in ...high-grade serous ovarian cancer (HGSOC) remains unknown. This study aimed to investigate the expression profile of circRNAs in HGSOC. Expression profiles of circRNAs differential expression based on circRNAs High-throughput sequencing were identified in 3 HGSOC specimens and 3 normal ovarian tissues. A total of 710 differentially expressed circRNAs were found (354 expressions up-regulated and 356 expressions down-regulated). CircRNA sequencing data were verified by qRT-PCR in HGSOC tissue and benign ovarian lesions. Differential expression of 7 circRNAs (circRNA385, circRNA2058, circRNA3336, circRNA2606, circRNA1656, circRNA1312 and circRNA7474) in HGSOC tissue was confirmed by qRT-PCR. Among them, circRNA1656 showed the highest fold change. qRT-PCR was used to verify the expression of circRNA1656 in ovarian cancer cell lines. In order to analyze the relationship between circRNA1656 expression and clinical pathological biological characteristics of HGSOC, qRT-PCR was used to verify the expression of circRNA1656 in 60 HGSOC tissues compared with 60 benign ovarian lesions. The expression of circRNA1656 was down-regulated in HGSOC tissues and ovarian cancer cell lines, and correlated with the FIGO stage of HGSOC. circRNA1656 has the potential to serve as a novel tumor marker for HGSOC.
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