Numerical Simulation and Experimental Study of the Tube Receiver's Performance of Solar Thermal Power Tower

AbstractA water-vapor tube receiver is a significant component in the solar thermal power tower plant. However, the tube flow performance is much different from others. Because semi-circumference of the tube is heated with an uneven heat flux, which is into a Gaussian distribution in this paper, and the other semi-circumference is insulated. A 5kW- Xe-arc lamp was used to simulate a solar light source. In this study, the effect of different entrance velocity on the flow performance and thermal efficiency of the tube receiver are investigated with numerical and experimental methods. The results of experiment and simulation agree well. The results show that the temperature distribution of water and tube wall are very uneven both in the axial and radial directions. The thermal efficiency of the tube receiver increases with the increase of entrance velocity

Clinical value of miR-23a-3p expression in early diagnosis of diabetic kidney disease

Introduction: The objective was to observe the expression of miR-23a-3p in the serum of patients with type 2 diabetic nephropathy (T2DN) and to explore its clinical significance. Materials and methods: 112 patients with type 2 diabetes were divided into a simple diabetes mellitus (NON) group, T2DN microalbuminuria (MIC) group, and T2DN macroalbuminuria (MAC) group, according to the urinary protein-creatinine ratio (uACR). Clinical data were collected, miR-23a-3p levels in serum were measured by quantitative reverse transcription polymerase chain reaction (qRT-PCR), and clinical parameters were measured by an automatic biochemical analyser; the influencing factors of diabetic kidney disease (DKD) and the correlation between miR-23a-3p expression and clinical parameters were analysed. Results: The expression of miR-23a-3p in the serum of the DKD group was lower than that of the normal control (CON) and NON groups. Correlation analysis showed that miR-23a-3p was positively correlated with urinary albumin (Albu), glycosylated haemoglobin (HbA1c), total cholesterol (CHOL), glycated albumin (GA-L), serum creatinine (Scr), fasting blood glucose (GLU), and uric acid (UA), negatively correlated with uACR and high-density lipoprotein cholesterol (HDL-C), but not correlated with urinary creatinine (CREA). The area under the receiver operating characteristic (ROC) curve (AUC) of miR-23a-3p for the diagnosis of DKD was 0.686 [95% confidence interval (CI): 0.599–0.773], with a sensitivity of 64.5% and a specificity of 71.2%; the AUC for differentiating NON from DKD was 0.700 (95% CI: 0.598–0.802), with a sensitivity of 61.8% and a specificity of 77.8%. Multivariate logistic regression analysis showed that serum miR-23a-3plevels were not associated with the development of DKD after adjusting for other levels of influence and were not significant for the differentiation of NON and DKD. Conclusion: Serum miR-23a-3p levels are decreased in T2DN patients, and this change becomes more significant with the severity of the disease, which may be a marker for the early diagnosis and progression of T2DN

Structural Health Monitoring for Composite Materials

Computer networking & communication

Quantum-Based Feature Selection for Multi-classification Problem in Complex Systems with Edge Computing

The complex systems with edge computing require a huge amount of multi-feature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational efficiency and save the resource consumption. In this paper, a quantum-based feature selection algorithm for the multi-classification problem, namely, QReliefF, is proposed, which can effectively reduce the complexity of algorithm and improve its computational efficiency. First, all features of each sample are encoded into a quantum state by performing operations CMP and R_y, and then the amplitude estimation is applied to calculate the similarity between any two quantum states (i.e., two samples). According to the similarities, the Grover-Long method is utilized to find the nearest k neighbor samples, and then the weight vector is updated. After a certain number of iterations through the above process, the desired features can be selected with regards to the final weight vector and the threshold {\tau}. Compared with the classical ReliefF algorithm, our algorithm reduces the complexity of similarity calculation from O(MN) to O(M), the complexity of finding the nearest neighbor from O(M) to O(sqrt(M)), and resource consumption from O(MN) to O(MlogN). Meanwhile, compared with the quantum Relief algorithm, our algorithm is superior in finding the nearest neighbor, reducing the complexity from O(M) to O(sqrt(M)). Finally, in order to verify the feasibility of our algorithm, a simulation experiment based on Rigetti with a simple example is performed.Comment: 22 pages, 11 figure

A van der Waals antiferromagnetic topological insulator with weak interlayer magnetic coupling.

Magnetic topological insulators (TI) provide an important material platform to explore quantum phenomena such as quantized anomalous Hall effect and Majorana modes, etc. Their successful material realization is thus essential for our fundamental understanding and potential technical revolutions. By realizing a bulk van der Waals material MnBi4Te7 with alternating septuple [MnBi2Te4] and quintuple [Bi2Te3] layers, we show that it is ferromagnetic in plane but antiferromagnetic along the c axis with an out-of-plane saturation field of ~0.22 T at 2 K. Our angle-resolved photoemission spectroscopy measurements and first-principles calculations further demonstrate that MnBi4Te7 is a Z2 antiferromagnetic TI with two types of surface states associated with the [MnBi2Te4] or [Bi2Te3] termination, respectively. Additionally, its superlattice nature may make various heterostructures of [MnBi2Te4] and [Bi2Te3] layers possible by exfoliation. Therefore, the low saturation field and the superlattice nature of MnBi4Te7 make it an ideal system to investigate rich emergent phenomena