Electricity consumption is an important economic index and plays a significant role in drawing up an energy development policy for each country. Multivariate techniques and time-series analysis have ...been proposed to deal with electricity consumption forecasting, but a large amount of historical data is required to obtain accurate predictions. The grey forecasting model attracted researchers by its ability to characterize an uncertain system effectively with a limited number of samples. GM(1,1) is the most frequently used grey forecasting model, but its developing coefficient and control variable were dependent on the background value that is not easy to be determined, whereas a neural-network-based GM(1,1) model called NNGM(1,1) has been presented to resolve this troublesome problem. This study has applied NNGM(1,1) to electricity consumption and has examined its forecasting ability on electricity consumption using sample data from the Turkish Ministry of Energy and Natural Resources and the Asia–Pacific Economic Cooperation energy database. Experimental results demonstrate that NNGM(1,1) performs well.
In clinical settings, physicians tend to use corticosteroids in the most critically ill patients. ...selection bias and confounders in observational studies might contribute to any observed increased ...mortality in patient groups treated with corticosteroids. Inconclusive clinical evidence should not be a reason for abandoning corticosteroid use in 2019-nCoV pneumonia. ...there are studies supporting the use of corticosteroids at low-to-moderate dose in patients with coronavirus infection. According to the expert consensus statement, the following basic principles should be followed when using corticosteroids: (1) the benefits and harms should be carefully weighed before using corticosteroids; (2) corticosteroids should be used prudently in critically ill patients with 2019-nCoV pneumonia; (3) for patients with hypoxaemia due to underlying diseases or who regularly use corticosteroids for chronic diseases, further use of corticosteroids should be cautious; and (4) the dosage should be low-to-moderate (≤0·5–1 mg/kg per day methylprednisolone or equivalent) and the duration should be short (≤7 days).
Tourism demand forecasting has played an important role in supporting governments to devise development policies for travel and tourism. However, time series related to tourism often do not conform ...to statistical assumptions and feature significant temporal fluctuations. Because a Fourier series is often applied to oscillating sequences to remove noise, it is reasonable to develop a grey prediction model in conjunction with a Fourier series to forecast tourism demand. However, grey prediction models traditionally use one-order accumulation, treating each sample with equal weight, to identify regularities concealed in data sequences. Furthermore, when generating residuals from Fourier series, the prediction accuracy of the newly generated predicted values is not taken into account. In this study, by using fractional order accumulation to assign appropriate weights to samples, we propose a fractional grey prediction model with Fourier series that offers high prediction accuracy. Experimental results demonstrate that the proposed grey prediction model performs well compared with other considered prediction models.
Interfacial photo‐vapor conversion has been suggested as a cost‐effective and sustainable technology for seawater desalination. However, the conversion performance was still limited by some ...drawbacks, like salt accumulation and poor mechanical stability. Herein, a scalable MoS2‐based porous hydrogel (SMoS2‐PH) with good mechanical stability and salt resistance was successfully constructed through a crosslinking foaming polymerization method. With the high porosity (92.63 %), the SMoS2‐PH performed an impressive evaporation rate of 3.297 kg m−2 h−1 and photothermal conversion efficiency of 93.4 % under 1‐sun illumination. Most importantly, the SMoS2‐PH could maintain high and stable photothermal properties for 15 days on the surface of seawater. We believe that the excellent salt resistance, the high photothermal conversion efficiency, the ease of scale preparation method and the available commercial MoS2 make the SMoS2‐PH a promising device for full‐scale seawater desalination.
A scalable MoS2‐based porous hydrogel (SMoS2‐PH) was successfully constructed with a hydrophilic polyacrylamide as its skeleton and commercial MoS2 as the solar absorbent through a crosslinking foaming polymerization method. The SMoS2‐PH performed an impressive evaporation rate of 3.297 kg m−2 h−1 and solar‐to‐vapor conversion efficiency of 93.4 % under 1‐sun illumination.
Previously published equations to estimate glomerular filtration rate (GFR) have limited accuracy in Asian populations. We aimed to develop and validate a more accurate equation for estimated GFR ...(eGFR) in the Chinese population, using data from 8571 adults who were referred for direct measurement of GFR by renal dynamic imaging (mGFR) at 3 representative hospitals in China. Patients from the Third Xiangya Hospital were included in our development (n=1730) and internal validation sets (n=1042) and patients from the other hospitals comprised the external validation set (n=5799). We excluded patients who were prescribed medications known to influence the tubular secretion of creatinine, patients on dialysis, kidney transplant recipients, and patients with missing creatinine values or with creatinine >700 μmol/l. We derived a novel eGFR equation by linear regression analysis and compared the performance to 12 creatinine-based eGFR equations, including previously published equations for use in Chinese or Asian populations. In the development and internal validation sets, the novel Xiangya equation had high accuracy (accuracy within 30% P30, 79.21% and 84.33%, respectively), low bias (mean difference between mGFR and eGFR, -1.97 and -1.85 ml/min per 1.73 m2, respectively), and high precision (interquartile range of the differences, 21.13 and 18.88 ml/min per 1.73 m2, respectively). In external validation, the Xiangya equation had the highest P30 among all eGFR equations, with P30 ≤ 75% for the other 12 equations. This novel equation provides more accurate GFR estimates in Chinese adults and could replace existing eGFR equations for use in the Chinese population.
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Grey prediction models play a significant role in forecasting energy demand, particularly the GM(1,1) model. To increase the prediction accuracy of the original GM(1,1) model, the corresponding ...residual GM(1,1) model is often recommended. However, the original and residual models that form the basis of the remnant grey prediction model are usually set up independently. In this work, we use a neural network to determine the degree to which a predicted value obtained from the original GM(1,1) model can be modified. A distinctive feature of our proposed prediction model is that the residual model is leveraged by providing a new adjustment mechanism for predicted values to maximize the prediction accuracy. The independent creation of a residual model is no longer required for the proposed model. The prediction accuracy of the proposed prediction models is verified using real energy demand cases. Experimental results showed that the proposed remnant GM(1,1) models perform well in comparison with other remnant GM(1,1) variants.
It is difficult to effectively rectify or convert low power in the circuit stage of harvesters. The high-gain antenna can offer a higher level of power and is beneficial to RF power harvesting in a ...low power density environment. To extend the narrow beam of the conventional high-gain rectenna, the multiport and multibeam antenna is promising. To pursue a simple configuration and avoid extra beamforming networks, a traveling-wave grid-array antenna (GAA) with two isolated ports and two symmetrically tilted beams is proposed. A prototype is designed and fabricated after a detailed analysis of the GAA with tilted beams and the coplanar stripline-based rectifier. The measured results show that the proposed rectenna is sensitive and effective in a wide-angle range. The harvesting angle range is extended by combining two tilted beams and can be greater than 70°, where the level of dc power exceeds <inline-formula> <tex-math notation="LaTeX">100~\mu \text{W} </tex-math></inline-formula> when the power density is as low as <inline-formula> <tex-math notation="LaTeX">1~\mu \text{W} </tex-math></inline-formula>/cm 2 . A maximum dc output of 3.6-<inline-formula> <tex-math notation="LaTeX">203.8~\mu \text{W} </tex-math></inline-formula> and a maximum RF-to-dc conversion efficiency of 16.3%-45.3% are available at 2.45 GHz, under the condition that the power density ranges from 0.052 to <inline-formula> <tex-math notation="LaTeX">1~\mu \text{W} </tex-math></inline-formula>/cm 2 .
Aiming at the construction of novel platform for efficient light harvesting, the precise synthesis of a new family of AIEgen‐branched rotaxane dendrimers was successful realized from an ...AIEgen‐functionalized 2rotaxane through a controllable divergent approach. In the resultant AIE macromolecules, up to twenty‐one AIEgens located at the tails of each branches, thus making them the first successful example of AIEgen‐branched dendrimers. Attributed to the solvent‐induced switching feature of the rotaxane branches, the integrated rotaxane dendrimers displayed interesting dynamic feature upon the aggregation‐induced emission (AIE) process. Moreover, novel artificial light‐harvesting systems were further constructed based on these AIEgen‐branched rotaxane dendrimers, which revealed impressive generation‐dependent photocatalytic performances for both photooxidation reaction and aerobic cross‐dehydrogenative coupling (CDC) reaction.
A novel artificial light‐harvesting system based on AIEgen‐branched rotaxane dendrimers has been successfully constructed which displayed impressive generation‐dependent photocatalytic performances for both photooxidation reaction and aerobic cross‐dehydrogenative coupling reaction.
In terms of environmental protection, magnesium is a lightweight material that has been widely used to manufacture components for electronics. By forecasting the demand for magnesium materials, we ...can evaluate its prospects in the related industries. Grey prediction is appropriate for this study, because there is limited available data on the demand for magnesium, and it does not coincide with the statistical assumptions. Therefore, this study applies the GM(1,1) model, which is the most frequently used grey prediction model, to forecast the demand for magnesium materials. To improve the accuracy of predictions with the GM(1,1) model, its residual modification was established by the neural network. In particular, this study used grey relational analysis to estimate the weight of each sample that was required to avoid unreasonably treating each sample with equal importance in the traditional grey prediction. The forecasting ability of the proposed grey residual modification models was verified using real data regarding the demand for magnesium materials. The results showed that the proposed prediction model performed well compared with the other prediction models considered.
•A new grey prediction model is proposed for magnesium material demand forecasting.•Applying GRA to estimate the importance of each sample towards a generating sequence.•A simple residual modification mechanism was set up without building a residual model.•The proposed model performed well compared with the other grey prediction models.
Complex and dynamic networks of molecules are involved in human diseases. High-throughput technologies enable omics studies interrogating thousands to millions of makers with similar biochemical ...properties (eg, transcriptomics for RNA transcripts). However, a single layer of "omics" can only provide limited insights into the biological mechanisms of a disease. In the case of genome-wide association studies, although thousands of single nucleotide polymorphisms have been identified for complex diseases and traits, the functional implications and mechanisms of the associated loci are largely unknown. Additionally, the genomic variants alone are not able to explain the changing disease risk across the life span. DNA, RNA, protein, and metabolite often have complementary roles to jointly perform a certain biological function. Such complementary effects and synergistic interactions between omic layers in the life course can only be captured by integrative study of multiple molecular layers. Building upon the success in single-omics discovery research, population studies started adopting the multi-omics approach to better understanding the molecular function and disease etiology. Multi-omics approaches integrate data obtained from different omic levels to understand their interrelation and combined influence on the disease processes. Here, we summarize major omics approaches available in population research, and review integrative approaches and methodologies interrogating multiple omic layers, which enhance the gene discovery and functional analysis of human diseases. We seek to provide analytical recommendations for different types of multi-omics data and study designs to guide the emerging multi-omic research, and to suggest improvement of the existing analytical methods.
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