Search

Purpose: To investigate the changes in choroidal vascular structures after exercise in patients with glaucoma using an image binarisation algorithm with enhanced-depth imaging optical coherence tomography.Methods: Thirty-four eyes of 19 patients with primary open-angle glaucoma and 40 eyes of 20 normal subjects were included in the glaucoma and control groups, respectively. All subjects were evaluated before, immediately after, and 30 min after 20-min running at moderate speed. The subfoveal choroidal area was segmented into the luminal area (LA) and stromal area (SA), and the choroidal vascularity index (CVI) was measured by calculating the ratio of LA to the total choroidal area (TCA). The mean intraocular pressure (IOP), subfoveal choroidal thickness, CVI, SA, CA, and TCA were compared within and between both groups. The correlation between CVI, IOP, and other vascular indexes was investigated.Results: In the glaucoma group, a significantly lower CVI was found immediately after exercise and recovered 30 min after exercise. Higher TCA and LA levels were demonstrated 30 min after exercise compared to immediately after exercise. In both groups, IOP decreased immediately after exercise but was restored after a 30-min rest. In the glaucoma group, there was a higher correlation between CVI and other choroidal vascular parameters than in the control group. There was no difference in IOP or choroidal parameters between the groups at different time points.Conclusion: In patients with glaucoma, CVI decreased significantly immediately after exercise, indicating that the choroidal layer is affected by exercise and an unhealthy vascular regulatory mechanism.

The following topics are dealt with: power engineering computing; power grids; learning (artificial intelligence); Internet; Internet of Things; energy consumption; power supply quality; renewable energy sources; cryptography; power system security.

In view of the problem that it is impossible to deploy voltage sag monitoring devices in the whole network, resulting in the lack of basis for industrial users to enter the network, a scheme for evaluating the severity of voltage sag at the grid side in the provincial power grid is proposed. Firstly, by analyzing the characteristics of voltage sag transmission, the simulation scope of provincial power grid is determined, and the differences of fault rate and fault type proportion of different voltage grades highlighted due to the expansion of simulation scope are considered, which makes the short circuit fault simulation model based on Monte Carlo method closer to reality. Secondly, from the engineering point of view, improve the BPA data maintained by the power grid dispatching department, call the BPA parallel simulation calculation through the development interface, and analyze the calculation results to obtain the grid side voltage sag severity evaluation index.

Propranolol (PRO) is widely detected in the aquatic environment and proved to be detrimental to multifarious aquatic organisms. In view of some virtues of sulfate radicals than hydroxyl radicals, advanced oxidation technologies that involve the activation of peroxymonosulfate (PMS) have stimulated wide-ranging research on the PRO removal. In this paper, a composite (C2NOMS-2) of amino-functionalized manganese octahedral molecular sieve (NOMS-2) and binuclear cobalt phthalocyanine (Co2CPc) was synthesized easily, and utilized as a catalyzer for PMS to degrade PRO in water. The apparent rate constants of PRO degradation by PMS with C2NOMS-2 as a catalyst was found to be higher than with NOMS-2, Co2CPc and the composite of uninuclear cobalt phthalocyanine (CoCPc) and NOMS-2. The catalytic ability of C2NOMS-2 was investigated under various reaction conditions: catalyst dosages (0.5–2.0 g/L), PMS doses (50–500 mg/L), initial pH (5–11), reaction temperature (20–35 °C), and natural water constituents (Cl−, HCO3−, and sodium huminate). Radical scavenging tests and electron paramagnetic resonance spectroscopy showed that 1O2 was the most critical reactive oxygen species, and conceivable mechanisms of PMS activation with C2NOMS-2 were proposed established on the curve estimation of high-resolution XPS spectra, revealing that the generation of reactive oxygen species was mainly resulted from the cycles of Mn3+/Mn4+, Co3+/Co2+ and surface lattice oxygen/surface adsorbed oxygen. The intermediate products of propranolol degradation were identified by LC-MS/MS. Cycling experiments and ion dissolution detection suggested that C2NOMS-2 could maintain satisfactory stability in an aqueous system.

Voltage sag, as a prominent problem among many power quality problems, has always plagued power grids and users. To reduce the loss caused by the voltage sag and provide a basis for the prevention of the voltage sag, it is important to accurately and efficiently predict the risk of the voltage sag. This paper analyses the related factors of voltage sag risk from multi-directional and multi-dimensional, obtains the data of the influence factors of voltage sag risk in various information systems of the power grid, constructs voltage sag multi-source data, and uses Elman neural network to construct voltage sag risk prediction model. Through the training and learning of multi-source data, the model realizes the voltage sag risk assessment of each node in the power grid. Finally, the feasibility and validity of voltage sag risk prediction model are verified by case study of historical monitoring data in Fujian Province, which provides a method for voltage sag risk prediction.

A recursive algorithm called Bhattacharyya distance feature selection for selecting a real-optimum feature under normal multidistribution is presented. The key of this method is to change the problem of minimizing the criterion of the sum of the upper bound of error probability of every two class pairs in subspace to a problem of solving a nonlinear matrix equation in a multiclass problem under an orthonormal coordinate system. The recursive algorithm is considered as finding the optimal solution of a transformation matrix from the nonlinear matrix equation. The theoretical analysis and experimental results show that under normal multidistribution the performance of the proposed algorithm is superior to the performance of any previous one.