Recently, the coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Early and quick identification of the potential risk zones of COVID-19 infection is increasingly vital ...for the megacities implementing targeted infection prevention and control measures. In this study, the communities with confirmed cases during January 21–February 27 were collected and considered as the specific epidemic data for Beijing, Guangzhou, and Shenzhen. We evaluated the spatiotemporal variations of the epidemics before utilizing the ecological niche models (ENM) to assemble the epidemic data and nine socioeconomic variables for identifying the potential risk zones of this infection in these megacities. Three megacities were differentiated by the spatial patterns and quantities of infected communities, average cases per community, the percentages of imported cases, as well as the potential risks, although their COVID-19 infection situations have been preliminarily contained to date. With higher risks that were predominated by various influencing factors in each megacity, the potential risk zones coverd about 75% to 100% of currently infected communities. Our results demonstrate that the ENM method was capable of being employed as an early forecasting tool for identifying the potential COVID-19 infection risk zones on a fine scale. We suggest that local hygienic authorities should keep their eyes on the epidemic in each megacity for sufficiently implementing and adjusting their interventions in the zones with more residents or probably crowded places. This study would provide useful clues for relevant hygienic departments making quick responses to increasingly severe epidemics in similar megacities in the world.
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•COVID-19 infection still poses increasing threat to public health in the world.•We explored the feasibility of Maxent models in identifying the potential risks.•Socioeconomic factors affected the spatial distribution of potential risk zones.•Dominant influencing factors on potential risk zones varied in the megacities.•Maxent models were suitable for early identifying potential COVID-19 risk zones.
•Extend LHPM to non-stationary non-Gaussian cross-correlated fields.•Establish transformation model from non-stationary non-Gaussian CMF to the underlying Gaussian CMF.•Represent the underlying ...Gaussian cross-correlated fields by multivariate K-L expansion.•Compute eigenvalues and eigenfunctions using Nyström method.•Develop a unified simulation framework for non-stationary non-Gaussian cross-correlated fields.
In practical engineering, cross-correlated random fields are often used to model structural materials or random loads containing multiple correlations. Effective and accurate simulation of these cross-correlation fields is an important prerequisite for subsequent reliability analysis and uncertainty quantification of complex systems. Therefore, this paper proposes a new simulation method for non-stationary non-Gaussian cross-correlated random fields to satisfy realistic engineering requirements. In this new method, L-moments-based Hermite polynomials model (LHPM) is extended to non-stationary non-Gaussian cross-correlated fields. Then, a transformation model from non-stationary non-Gaussian correlation matrix function (CMF) to the underlying Gaussian CMF is explicitly given. Multivariate K-L expansion is further used to approximate the underlying Gaussian cross-correlated fields, where the eigenvalue and eigenfunctions are estimated via the Nyström method with uniform weights. The approximation permits the application of few random variables to characterize the entire Gaussian cross-correlated fields. Ultimately, the simulated underlying Gaussian cross-correlated fields are mapped back to the target non-stationary non-Gaussian cross-correlated fields based on LHPM. Three typical examples, including exponential kernel, Wiener process kernel and spatially varying non-Gaussian and nonstationary seismic ground motions, are used to validate the effectiveness of the proposed method. The source code is readily available at: https://github.com/zhaozhao23/Simulation-of-non-stationary-and-non-Gaussian-cross-correlated-fields.
•ELM, GANN and WNN models are proposed for estimation of ET0 in Southwest China.•WNN was not as efficient as ELM and GANN for estimating ET0.•The proposed ELM and GANN models were better than ...empirical models.•The ELM and GANN models can highly be recommended for estimating ET0 in Southwest China.
Reference evapotranspiration (ET0) is an essential component in hydrological ecological processes and agricultural water management. Accurate estimation of ET0 is of importance in improving irrigation efficiency, water reuse and irrigation scheduling. FAO-56 Penman–Monteith (P–M) model is recommended as the standard model to estimate ET0. Nevertheless, its application is limited due to the lack of required meteorological data. In this study, trained extreme learning machine (ELM), backpropagation neural networks optimized by genetic algorithm (GANN) and wavelet neural networks (WNN) models were developed to estimate ET0, and the performances of ELM, GANN, WNN, two temperature-based (Hargreaves and modified Hargreaves) and three radiation-based (Makkink, Priestley–Taylor and Ritchie) ET0 models in estimating ET0 were evaluated in a humid area of Southwest China. Results indicated that among the new proposed models, ELM and GANN models were much better than WNN model, and the temperature-based ELM and GANN models had better performance than Hargreaves and modified Hargreaves models, radiation-based ELM and GANN models had higher precision than Makkink, Priestley–Taylor and Ritchie models. Both of radiation-based ELM (RMSE ranging 0.312–0.332mmd−1, Ens ranging 0.918–0.931, MAE ranging 0.260–0.300mmd−1) and GANN models (RMSE ranging 0.300–0.333mmd−1, Ens ranging 0.916–0.941, MAE ranging 0.2580–0.303mmd−1) could estimate ET0 at an acceptable accuracy level, and are highly recommended for estimating ET0 without adequate meteorological data.
Background & Aims Immunoprophylaxis reduces but does not completely eradicate hepatitis B virus (HBV) transmission. This prospective study aims at assessing the rate and risk factors of maternally ...transmitted HBV infection. Methods We enrolled 303 mother-infant pairs with positive maternal hepatitis B surface antigen (HBsAg) under current immunization program. Maternal viral load was determined by a real-time PCR-based assay. The children were tested for HBsAg at 4–8 months and/or 1–3 years of age. Rates of HBV infection were estimated using a multivariate logistic regression model. Results HBeAg-positive mothers (81/303, 26.7%) had higher viral loads than HBeAg-negative mothers (7.4 ± 1.9 vs. 2.7 ± 1.4 log10 copies/ml, p <0.0001). Ten children, born to HBeAg-positive mothers with high viral load (median, 8.4; range, 6.5–9.5 log10 copies/ml), were chronically infected. After adjustment for maternal age, birth type, factors related to maternal-fetal hemorrhage, gestational age, infant gender, birth weight, timeliness of vaccination, and feeding practice, maternal viral load was significantly associated with risk of infection (adjusted odds ratio for each log10 copy/ml increase, 3.49; 95% confidence interval (CI), 1.63–7.48; p = 0.001). The predictive rates of infection at maternal viral load levels of 7, 8, and 9 log10 copies/ml were 6.6% (95% CI, 0.5–12.6%; p = 0.033), 14.6% (95% CI, 5.6–23.6%; p = 0.001), and 27.7% (95% CI, 13.1–42.4%; p <0.001), respectively. Conclusions Additional strategies to further reduce transmission should be considered in mothers with a viral load above 7–8 log10 copies/ml.
Abstract
K‐metal batteries have become one of the promising candidates for the large‐scale energy storage owing to the virtually inexhaustible and widely potassium resources. The uneven K
+
...deposition and dendrite growth on the anode causes the batteries prematurely failure to limit the further application. An integrated K‐metal anode is constructed by cold‐rolling K metal with a potassiphilic porous interconnected mediator. Based on the experimental results and theoretical calculations, it demonstrates that the potassiphilic porous interconnected mediator boosts the mass transportation of K‐metal anode by the K affinity enhancement, which decreases the concentration polarization and makes a dendrite‐free K‐metal anode interface. The interconnected porous structure mitigates the internal stress generated during repetitive deposition/stripping, enabling minimized the generation of electrode collapse. As a result, a durable K‐metal anode with excellent cycling ability of exceed 1, 000 h at 1 mA cm
−2
/1 mAh cm
−2
and lower polarization voltage in carbonate electrolyte is obtained. This proposed integrated anode with fast K
+
kinetics fabricated by a repeated cold rolling and folding process provides a new avenue for constructing a high‐performance dendrites‐free anode for K‐metal batteries.
Mortality in Older Patients with COVID‐19 Zhao, Hai‐Lu; Huang, Yan‐Mei; Huang, Yi
Journal of the American Geriatrics Society (JAGS),
August 2020, Volume:
68, Issue:
8
Journal Article
Fe(Ш)-doped graphitic carbon nitride (Fe(Ш)-CN) photocatalysts with various Fe(Ш) ions content were prepared via ultrasonic method. Detailed physical characterization indicated that Fe(Ш) ions had ...been successfully doped into the frame of g-C3N4. The photocatalytic activities were investigated, and methyl orange (MO) and tetracycline hydrochloride (TC) were used as the targeted pollutants. The as-prepared Fe(Ш)-CN materials exhibited higher photocatalytic activities than those of the pure g-C3N4. Specifically, the degradation rate of 2Fe(Ш)-CN under visible light was 2.06 times higher for MO and 2.65 times higher for TC than that of g-C3N4. The increased photocatalytic activities of Fe(Ш)-CN were mainly attributed to the enhanced light absorption ability and the rapid separation of photogenerated carriers. Moreover, the importance of active species during the reaction process was also explored, and the results indicated that •O2− is the main active species.
Evidence, demonstrating long noncoding RNAs (lncRNAs) as critical players in cancer, remains to increase. lncRNA SBF2‐AS1 was reported to be involved in several cancers, such as hepatocellular ...carcinoma. However, the role of SBF2‐AS1 in colorectal cancer (CRC) is unknown. We showed lncRNA SBF2‐AS1 expression was growing in CRC samples, especially in advanced cases. Accordingly, SBF2‐AS1 possesses higher expression in CRC cell lines than in normal cell line. Moreover, SBF2‐AS1 high expression indicated a low survival rate. Functionally, SBF2‐AS1 knockdown suppressed the proliferation, migration, and invasion of CRC cells. In terms of mechanism, SBF2‐AS1 upregulation restrained the activity of miR‐619‐5p and led to overexpression of HDAC3. Importantly, downregulation of miR‐619‐5p or HDAC3 overexpression reversed SBF2‐AS1‐silencing‐caused suppression on proliferation and metastasis. Summarily, our findings elucidated a crucial role of SBF2‐AS1 as a miR‐619‐5p sponge, shedding novel light on lncRNA‐related prognostics.
Long noncoding RNA SBF2‐AS1 promotes colorectal cancer proliferation and invasion by inhibiting miR‐619‐5p activity and facilitating HDAC3 expression.
Nitrogen‐doped carbon materials (N‐Cmat) are emerging as low‐cost metal‐free electrocatalysts for the electrochemical CO2 reduction reaction (CO2RR), although the activities are still unsatisfactory ...and the genuine active site is still under debate. We demonstrate that the CO2RR to CO preferentially takes place on pyridinic N rather than pyrrolic N using phthalocyanine (Pc) and porphyrin with well‐defined N‐Cmat configurations as molecular model catalysts. Systematic experiments and theoretic calculations further reveal that the CO2RR performance on pyridinic N can be significantly boosted by electronic modulation from in‐situ‐generated metallic Co nanoparticles. By introducing Co nanoparticles, Co@Pc/C can achieve a Faradaic efficiency of 84 % and CO current density of 28 mA cm−2 at −0.9 V, which are 18 and 47 times higher than Pc/C without Co, respectively. These findings provide new insights into the CO2RR on N‐Cmat, which may guide the exploration of cost‐effective electrocatalysts for efficient CO2 reduction.
Nitrogen‐doped carbon catalysts are presented for application in the electrochemical CO2 reduction reaction (CO2RR). Molecular probes were designed to clarify the genuine catalytically active sites. CO2RR takes place preferentially on pyridinic rather than pyrrolic nitrogen, and metallic cobalt nanoparticles enhance the CO2RR on pyridinic nitrogen significantly.
In this paper, 3D printing method and fiber Bragg grating (FBG) sensing technology were combined to fabricate a simple and small size tilt sensor. The raw material for creating different sensor ...components was Polylactic Acid (PLA) material. Bare FBG sensors were directly inscribed into PLA material using fused deposition modeling (FDM) process for complete protection. Printing test using FDM process indicate that bare optical fiber cables successfully survived the FDM process even though the melted PLA materials approached a maximum temperature of around 220°. Two FBG sensors characterized by different wavelength values were symmetrically arranged inside a sensing unit for the measurement of the tilt angle in terms of their wavelength shifts. The minimum resolution and the measurement range of this new FBG tilt sensor were 0.084° and ±75°, respectively. The measurement performance of this new tilt sensor was also verified with the conventional tilt sensor. A small slope model was built up in the laboratory to examine the measurement performance of three FBG tilt sensors which were mounted at different depths inside the slope model. The measured horizontal displacement data from FBG tilt sensors were verified with the output data of the Linear Variable Displacement Transducer (LVDT) and the obtained maximum error was less than 3% when the maximum displacements are approached.
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