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With the rapid development of solar energy plants in recent years, the accurate prediction of solar power generation has become an important and challenging problem in modern intelligent grid systems. To improve the forecasting accuracy of solar energy generation, an effective and robust decomposition-integration method for two-channel solar irradiance forecasting is proposed in this study, which uses complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), a Wasserstein generative adversarial network (WGAN), and a long short-term memory network (LSTM). The proposed method consists of three essential stages. First, the solar output signal is divided into several relatively simple subsequences using the CEEMDAN method, which has noticeable frequency differences. Second, high and low-frequency subsequences are predicted using the WGAN and LSTM models, respectively. Last, the predicted values of each component are integrated to obtain the final prediction results. The developed model uses data decomposition technology, together with advanced machine learning (ML) and deep learning (DL) models to identify the appropriate dependencies and network topology. The experiments show that compared with many traditional prediction methods and decomposition-integration models, the developed model can produce accurate solar output prediction results under different evaluation criteria. Compared to the suboptimal model, the MAEs, MAPEs, and RMSEs of the four seasons decreased by 3.51%, 6.11%, and 2.25%, respectively.

RGB1, a subunit of heterotrimeric G protein, plays important roles in regulating grain size and weight of rice. However, the molecular mechanisms underlying controlling grain filling process by G protein are still largely unclear. In the present study, we show that RGB1 controls not only the grain size but also the grain filling process. Knock-down of RGB1 significantly delayed grain development and reduced starch accumulation and grain weight, which was closely related to the delayed and the lower expression of genes encoding sucrose metabolism and starch biosynthesis related enzymes during grain filling stage. Suppression of RGB1 expression also resulted in the lower auxin content in grains, which was correlated with the lower expression of OsNF-YB1 and OsYUC11 during grain filling stage. Further biochemical evidence showed that OsYUC11 expression was under control of OsNF-YB1 by its interaction with promoter of OsYUC11 . Taken together, we propose that RGB1 controls rice grain development and grain filling process by changing auxin homeostasis in endosperm cells. OsNF-YB1, which acts as a key downstream effector of RGB1, interacts directly with the promoter of OsYUC11 and stimulates the OsYUC11 expression, thereby regulating auxin biosynthesis and starch accumulation and grain size.

With the continuous promotion of “smart cities” worldwide, the approach to be used in combining smart cities with modern advanced technologies (Internet of Things, cloud computing, artificial intelligence) has become a hot topic. However, due to the non-stationary nature of environmental sound and the interference of urban noise, it is challenging to fully extract features from the model with a single input and achieve ideal classification results, even with deep learning methods. To improve the recognition accuracy of ESC (environmental sound classification), we propose a dual-branch residual network (dual-resnet) based on feature fusion. Furthermore, in terms of data pre-processing, a loop-padding method is proposed to patch shorter data, enabling it to obtain more useful information. At the same time, in order to prevent the occurrence of overfitting, we use the time-frequency data enhancement method to expand the dataset. After uniform pre-processing of all the original audio, the dual-branch residual network automatically extracts the frequency domain features of the log-Mel spectrogram and log-spectrogram. Then, the two different audio features are fused to make the representation of the audio features more comprehensive. The experimental results show that compared with other models, the classification accuracy of the UrbanSound8k dataset has been improved to different degrees.

As a kind of hazardous solid wastes, municipal solid waste incineration (MSWI) fly ash leads to serious environmental pollution. Converting MSWI fly ash into zeolites is an economically beneficial and environmentally sound way of disposal. In this paper, the effect of different additives (kaolin, milled glass powder, Na 2 SiO 3 ) on the synthesis of zeolites by microwave-assisted hydrothermal process using MSWI fly ash was investigated through a series of single-factor experiments. The cation exchange capacity (CEC) was used to evaluate the synthesis effect and the adsorption property of zeolites. Na 2 SiO 3 was found to be an ideal additive with the optimal dosage of 30 wt%, and the optimal time of magnetic stirring process was about 8 h. Na-P1 zeolite with high absorbability was synthesized in this condition, whose CEC was about 1.70 meq/g. In addition, the effect of Na 2 SiO 3 dosage and various hydrothermal conditions on the CEC of zeolites were investigated through the orthogonal experiment and analysis of variance. It was found that the Na 2 SiO 3 dosage had the strongest impact on the CEC of zeolites, followed by hydrothermal temperature, concentration of NaOH and hydrothermal time. The work of this paper provides a reference basis for synthesizing high-performance zeolites by MSWI fly ash.

Anomalous road manhole covers pose a potential risk to road safety in cities. In the development of smart cities, computer vision techniques use deep learning to automatically detect anomalous manhole covers to avoid these risks. One important problem is that a large amount of data are required to train a road anomaly manhole cover detection model. The number of anomalous manhole covers is usually small, which makes it a challenge to create training datasets quickly. To expand the dataset and improve the generalization of the model, researchers usually copy and paste samples from the original data to other data in order to achieve data augmentation. In this paper, we propose a new data augmentation method, which uses data that do not exist in the original dataset as samples to automatically select the pasting position of manhole cover samples and predict the transformation parameters via visual prior experience and perspective transformations, making it more accurately capture the actual shape of manhole covers on a road. Without using other data enhancement processes, our method raises the mean average precision (mAP) by at least 6.8 compared with the baseline model.

Cerebral ischemia/reperfusion (I/R) injury is a critical factor leading to a poor prognosis for ischemic stroke patients. ω-3 fatty acid supplements taken as part of a daily diet have been shown to improve the prognosis of patients with ischemic stroke. In this study, we aimed to investigate the potential effects of resolvin D2 (RvD2), a derivative of ω-3 fatty acids, and its possible advantage on cerebral I/R injury in rats. Cerebral I/R caused by middle cerebral artery occlusion and reperfusion (MCAO/R) was established in Sprague-Dawley rats. First, in rats fed a regular diet, the MCAO/R stimulus led to a significant decrease in endogenous production of RvD2. Exogenous supply of RvD2 via intraperitoneal injection reversed MCAO/R-induced brain injury, including infarction, inflammatory response, brain edema, and neurological dysfunction. Meanwhile, RvD2 reversed the MCAO/R-induced decrease in the protein level of GPR18, which has been identified as a receptor for RvD2, especially in neurons and brain microvascular endothelial cells (BMVECs). Furthermore, RvD2 exerted rescue effects on MCAO/R-induced neuron and BMVEC death. Moreover, GPR18 antagonist O-1918 could block the rescue effects of RvD2, possibly at least partially though the GPR18-ERK1/2-NOS signaling pathway. Finally, compared with ω-3 fatty acid supplements, RvD2 treatment had a better rescue effect on cerebral infarction, which may be due to the MCAO/R-induced decrease in 5-lipoxygense phosphorylation and subsequent RvD2 generation. In conclusion, compared with ω-3 fatty acids, RvD2 may be an optimal alternative and complementary treatment for ischemic stroke patients with recanalization treatment.

Heterotrimeric G protein-mediated signal transduction is one of the most important and highly conserved signaling pathways in eukaryotes, which involves in the regulation of many important biological processes. As compared with those in mammals and Arabidopsis thaliana, the functions of rice heterotrimeric G protein and their molecular mechanisms are largely unknown. The rice genome contains a single Gα (RGA1) and Gβ (RGB1), and five Gγ (RGG1, RGG2, GS3, DEP1/qPE9–1, and GGC2) subunits. Recent genetic studies have shown that DEP1/qPE9–1, an atypical putative Gγ protein, is responsible for the grain size as well as the dense and erect panicles, but the biochemical and molecular mechanisms underlying the control of grain size are not well understood. Here, we report that rice plants carrying DEP1/qPE9–1 have more endosperm cells per grain than plants contain the dep1/qpe9–1 allele. The DEP1/qPE9–1 line has a higher rate and more prolonged period of starch accumulation than the dep1/qpe9–1 line. Additionally, the expression of several essential genes encoding enzymes catalyzing sucrose metabolism and starch biosynthesis is higher in the DEP1/qPE9–1 line than in the dep1/qpe9–1 line, especially from the mid to late grain-filling stage. Grains of the DEP1/qPE9–1 line also have higher contents of three phytohormones, ABA, auxin and cytokinin. Exogenous application of auxin or cytokinin enhanced the starch accumulation and the expression of genes encoding grain-filling-related enzymes in the grains of dep1/qpe9–1, whereas ABA produced no effects. Based on these results, we conclude that DEP1/qPE9–1 positively regulates starch accumulation primarily through auxin and cytokinin, which enhance the expression of genes encoding starch biosynthesis during the mid to late grain-filling stage, resulting in increased duration of the grain-filling process.

Digital elevation models (DEMs), which can provide an accurate description of planetary surface elevation changes, play an important role in scientific tasks such as long-distance path planning, terrain analysis, and planetary surface reconstruction. However, generating high-precision planetary DEMs currently relies on expensive equipment together with complex remote sensing technology, thus increasing the cost and cycle of the task. Therefore, it is crucial to develop a cost-effective technology that can produce high-quality DEMs on the surfaces of planets. In this work, we propose a global attention-based DEM generation network (GADEM) to convert satellite imagery into DEMs. The network uses the global attention mechanism (GAM) together with a multi-order gradient loss function during training to recover precise terrain. The experimental analysis on lunar and Martian datasets not only demonstrated the effectiveness and accuracy of GADEM in bright regions, but also showed its promising reconstruction ability in shadowed regions.

Maize is moderately sensitive to salt stress; therefore, soil salinity is a serious threat to its production worldwide. Here, excellent salt-tolerant maize inbred line TL1317 and extremely salt-sensitive maize inbred line SL1303 were screened to understand the maize response to salt stress and its tolerance mechanisms. Relative water content, membrane stability index, stomatal conductance, chlorophyll content, maximum photochemical efficiency, photochemical efficiency, shoot and root fresh/dry weight, and proline and water soluble sugar content analyses were used to identify that the physiological effects of osmotic stress of salt stress were obvious and manifested at about 3 days after salt stress in maize. Moreover, the ion concentration of two maize inbred lines revealed that the salt-tolerant maize inbred line could maintain low Na concentration by accumulating Na in old leaves and gradually shedding them to exclude excessive Na . Furthermore, the K uptake and retention abilities of roots were important in maintaining K homeostasis for salt tolerance in maize. RNA-seq and qPCR results revealed some Na /H antiporter genes and Ca transport genes were up-regulated faster and higher in TL1317 than those in SL1303. Some K transport genes were down-regulated in SL1303 but up-regulated in TL1317. RNA-seq results, along with the phenotype and physiological results, suggested that the salt-tolerant maize inbred line TL1317 possesses more rapidly and effectively responses to remove toxic Na ions and maintain K under salt stress than the salt-sensitive maize inbred line SL1303. This response should facilitate cell homoeostasis under salt stress and result in salt tolerance in TL1317.

The receptor for activated C kinase 1 (RACK1) is one member of the most important WD repeat-containing family of proteins found in all eukaryotes and is involved in multiple signaling pathways. However, compared with the progress in the area of mammalian RACK1, our understanding of the functions and molecular mechanisms of RACK1 in the regulation of plant growth and development is still in its infancy. In the present study, we investigated the roles of rice RACK1A gene (OsRACK1A) in controlling seed germination and its molecular mechanisms by generating a series of transgenic rice lines, of which OsRACK1A was either over-expressed or under-expressed. Our results showed that OsRACK1A positively regulated seed germination and negatively regulated the responses of seed germination to both exogenous ABA and H2O2. Inhibition of ABA biosynthesis had no enhancing effect on germination, whereas inhibition of ABA catabolism significantly suppressed germination. ABA inhibition on seed germination was almost fully recovered by exogenous H2O2 treatment. Quantitative analyses showed that endogenous ABA levels were significantly higher and H2O2 levels significantly lower in OsRACK1A-down regulated transgenic lines as compared with those in wildtype or OsRACK1A-up regulated lines. Quantitative real-time PCR analyses showed that the transcript levels of OsRbohs and amylase genes, RAmy1A and RAmy3D, were significantly lower in OsRACK1A-down regulated transgenic lines. It is concluded that OsRACK1A positively regulates seed germination by controlling endogenous levels of ABA and H2O2 and their interaction.