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The high penetration of renewable energy resources and power electronic-based components has led to a low-inertia power grid which would bring challenges to system operations. The new model of load frequency control (LFC) must be able to handle the modern scenario where controlled areas are interconnected by parallel AC/HVDC links and storage devices are added to provide virtual inertia. Notably, vulnerabilities within the communication channels for wide-area data exchange in LFC loops may make them exposed to various cyber attacks, while it still remains largely unexplored how the new LFC in the AC/HVDC interconnected system with emulated inertia would be affected under malicious intrusions. Thus, in this article, we are motivated to explore possible effects of the major types of data availability and integrity attacks—Denial of Service (DoS) and false data injection (FDI) attacks—on such a new LFC system. By using a system-theoretic approach, we explore the optimal strategies that attackers can exploit to launch DoS or FDI attacks to corrupt the system stability. Besides, a comparison study is performed to learn the impact of these two types of attacks on LFC models of power systems with or without HVDC link and emulated inertia. The simulation results on the the exemplary two-area system illustrate that both DoS and FDI attacks can cause large frequency deviations or even make the system unstable; moreover, the LFC system with AC/HVDC interconnections and emulated inertia could be more vulnerable to these two types of attacks in many adversarial scenarios.

The direction estimation of the coherent source in a uniform circular array is an essential part of the signal processing area of the array, but the traditional uniform circular array algorithm has a low localization accuracy and a poor localization effect on the coherent source. To solve this problem, this paper proposes a two-dimensional direction of arrival (DOA) estimation for the coherent source in broadband. Firstly, the central frequency of the coherent sound source is estimated using the frequency estimation method of the delayed data, and a real-valued beamformer is constructed using the concept of the multiloop phase mode. Then, the cost function in the beam space is obtained. Finally, the cost function is searched in two dimensions to locate the sound source. In this paper, we simulate the DOA of the sound source at different frequencies and signal-to-noise ratios and analyze the resolution of the circular array. The simulation results show that the proposed algorithm can estimate the direction of arrival with high precision and achieve the desired results.

Previous studies have documented that Chlorella sorokiniana could grow well on cooking cocoon wastewater (CCW) with a maximum biomass of 0.49 g/L. In order to further enhance the biomass production and nutrient removals, a bubble-column bioreactor was designed and performed to cultivate C. sorokiniana in CCW, and two main cultivation parameters were investigated in this work. Results showed that a maximum algal biomass, specific growth rate, and biomass productivity of 2.83 g/L, 0.854 d−1, and 476.25 g/L/d, respectively, were achieved when this alga was cultivated in the bioreactor with an initial cell density of 0.8 g/L and an aeration rate of 3.34 L air/L culture/min; meanwhile, removal efficiencies of ammonium, total nitrogen, total phosphorus, and chemical oxygen demand reached 97.96, 85.66, 97.96, and 86.43%, respectively, which were significantly higher than that obtained in our previous studies. Moreover, chemical compositions in the algal cells varied with the changes of cultivation conditions (i.e., initial cell density and aeration rate). Thus, it is concluded that (1) the bubble-column bioreactor was suitable for cultivation of C. sorokiniana coupled with the CCW treatment and (2) initial cell density and aeration rate affected the biomass production, nutrient removals and chemical compositions of this alga.

Stacking order plays a crucial role in determining the crystal symmetry and has significant impacts on electronic, optical, magnetic, and topological properties. Electron-phonon coupling, which is central to a wide range of intriguing quantum phenomena, is expected to be intricately connected with stacking order. Understanding the stacking order-dependent electron-phonon coupling is essential for understanding peculiar physical phenomena associated with electron-phonon coupling, such as superconductivity and charge density waves. In this study, we investigate the effect of stacking order on electron-infrared phonon coupling in graphene trilayers. By using gate-tunable Raman spectroscopy and excitation frequency-dependent near-field infrared nanoscopy, we show that rhombohedral ABC-stacked trilayer graphene has a significant electron-infrared phonon coupling strength. Our findings provide novel insights into the superconductivity and other fundamental physical properties of rhombohedral ABC-stacked trilayer graphene, and can enable nondestructive and high-throughput imaging of trilayer graphene stacking order using Raman scattering. Via Raman and infrared spectroscopy measurements, X. Zan et al . find that rhombohedral ABC trilayer graphene has stronger electron/infrared-phonon coupling than Bernal ABA trilayer graphene.

Background The aberrant distribution of peripheral B cell subsets is associated with the pathogenesis of a variety of inflammatory and autoimmune diseases. However, the distribution of peripheral B cell subsets in patients with idiopathic dilated cardiomyopathy (DCM) remains to be elucidated. Methods Twenty-seven patients with idiopathic DCM (DCM group), 18 control patients with heart failure (HF group) and 21 healthy individuals (HC group) were included in this study. Peripheral B cell subsets were analysed using multicolour flow cytometry. The plasma β1 adrenergic receptor (β1-AR) autoantibody titre was determined using ELISA. Additionally, clinical features were also collected. Results Compared with the HF and HC groups, the percentage of B1 cells was significantly decreased, whereas the percentage of transitional B cells (Tr) was significantly increased in the DCM group. Notably, the percentage of B1 cells was significantly lower in patients with β1-AR autoantibody-positive DCM than in β1-AR autoantibody-negative patients. The correlation analysis showed that the percentage of B1 cells was negatively correlated with N-terminal pro-brain natriuretic peptide (NT-proBNP) levels and positively correlated with the left ventricular ejection fraction in patients with DCM. Conclusion As shown in the present study, the percentage of B1 cells in the peripheral blood of patients with idiopathic DCM is abnormally decreased, especially in β1-AR autoantibody-positive patients, while the percentage of Tr cells is significantly increased, indicating that B1 cells and Tr cells may be implicated in the pathogenesis of idiopathic DCM. The decrease in the percentage of B1 cells is directly related to the severity of DCM.

Two-dimensional (2D) layered material grey arsenic exhibits great potential for electronic and optoelectronics devices. Identifying the orbital texture in the electronic energy bands close to Fermi level is crucial for understanding and further manipulating the optoelectronic properties of grey arsenic. In this work, we investigate the orbital properties from bulk-state and surface-state of grey arsenic by using multidimensional angle-resolved photoemission spectroscopy, under different light polarization and crystal orientation conditions. Furthermore, by combining the experimental results with first-principles calculations based on density functional theory (DFT), we reveal that both the surface and bulk states of grey arsenic contain 4  s , 4 p x , 4 p y and 4 p z orbitals, but the orbital ratios are different. Our study offers new insight into the orbital nature of grey arsenic and also paves the way for investigation of orbital properties in other 2D materials.

Gross primary production (GPP) plays an important role in the net ecosystem exchange of CO2 between the atmosphere and terrestrial ecosystems. It is particularly important to monitor GPP in Southeast Asia because of increasing rates of tropical forest degradation and deforestation in the region in recent decades. The newly available, improved, third generation Normalized Difference Vegetation Index (NDVI3g) from the Global Inventory Modelling and Mapping Studies (GIMMS) group provides a long temporal dataset, from July 1981 to December 2011, for terrestrial carbon cycle and climate response research. However, GIMMS NDVI3g-based GPP estimates are not yet available. We applied the GLOPEM-CEVSA model, which integrates an ecosystem process model and a production efficiency model, to estimate GPP in Southeast Asia based on three independent results of the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) from GIMMS NDVI3g (GPPNDVI3g), GIMMS NDVI1g (GPPNDVI1g), and the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2 FPAR product (GPPMOD15). The GPP results were validated using ground data from eddy flux towers located in different forest biomes, and comparisons were made among the three GPPs as well as the MOD17A2 GPP products (GPPMOD17). Based on validation with flux tower derived GPP estimates the results show that GPPNDVI3g is more accurate than GPPNDVI1g and is comparable in accuracy with GPPMOD15. In addition, GPPNDVI3g and GPPMOD15 have good spatial-temporal consistency. Our results indicate that GIMMS NDVI3g is an effective dataset for regional GPP simulation in Southeast Asia, capable of accurately tracking the variation and trends in long-term terrestrial ecosystem GPP dynamics.

Ulva prolifera is the most common specie causative to green tide, and its growth is sensitive to temperature stress. However, the mechanisms of U. prolifera response to temperature stress remain elusive. In this study, high temperature (36 °C) stimulus promoted the death of unformed cell wall protoplasts and delayed the division of formed cell wall protoplasts, while low-temperature (4 °C) stimulus did not, suggesting that the mechanisms of the response of U. prolifera to high and low-temperature stresses are different. Transcriptome results show that proliferation-related genes were differentially expressed under high and low-temperature stresses, especially the proliferating cell nuclear antigen (PCNA) and cyclins (CYCs). Subsequently, the interaction between PCNA and Cyclin A was confirmed by Co-immunoprecipitation, yeast two-hybrid, and so on. Furthermore, high- and low-temperature stresses induced the expression of PCNA and Cyclin A in varying of degrees, and activated extracellular signal-regulated kinase (ERK) signal pathway. These results suggest, PCNA , Cyclin A , and ERK signal pathway played important roles in the resistance of U. prolifera to temperature stress. Interestingly, high-temperature stress induced an increase of miR-2916 in abundance, and exhibiting reverse expression of PCNA; and PCNA was target gene of miR-2916, suggesting that miR-2916 protected U. prolifera from high-temperature stress via post-transcriptionally regulation of PCNA. This study laid a foundation for understanding the function of PCNA and Cyclin A , moreover, it has a guiding significance to explore the mechanisms of the response to temperature stress from proliferation-related genes regulatory networks in U. prolifera .

Ovarian cancer (OC) is the most common gynecologic malignancy with high incidence and mortality. The present study aimed to develop approaches for determining the recurrence type and identify potential miRNA markers for OC prognosis. The miRNA expression profile of OC (the training set, including 390 samples with recurrence information) was downloaded from The Cancer Genome Atlas database. The validation sets GSE25204 and GSE27290 were obtained from the Gene Expression Omnibus database. Prescreening of clinical factors was conducted using the survival package, and the differentially expressed miRNAs (DE‑miRNAs) were identified using the limma package. Using the Caret package, the optimal miRNA set was selected to build a Support Vector Machine (SVM) classifier. The miRNAs and clinical factors independently related to prognosis were analyzed using the survival package, and the risk score system was constructed. Finally, the miRNA‑target regulatory network was built by Cytoscape software, and enrichment analysis was performed. There were 46 DE‑miRNAs between the recurrent and non‑recurrent samples. After the optimal 19‑miRNA set was selected for constructing the SVM classifier, 6 DE‑miRNAs (miR‑193b, miR‑211, miR‑218, miR‑505, miR‑508 and miR‑514) independently related to prognosis were further extracted to build the risk score system. The neoplasm cancer status was independently correlated with the prognosis and conducted with stratified analysis. Additionally, the target genes in the regulatory network were enriched in the regulation of actin cytoskeleton and the TGF‑β signaling pathway. The 6‑miRNA signature may serve as a potential biomarker for OC prognosis, particularlyfor recurrence.

Subsequently to the publication of this paper, the authors have realized that the affilitation address omitted the name of the university at which this research was conducted (Capital Medical University). Therefore, the author affiliations for this paper should have appeared as follows (changes are highlighted in bold): JINGWEI DONG and MINGJUN XU.Department of Anesthesiology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100001, P.R. China. The authors regret that the name of the university was not included with the paper prior to its publication, and apologize to the readers for any inconvenience caused. [the original article was published in Oncology Reports 41: 3233‑3243, 2019; DOI: 10.3892/or.2019.7108].