Robust Ellipse Fitting Based on Maximum Correntropy Criterion With Variable Center.

The presence of radically irregular data points (RIDPs), which are referred to as the subset of measurements that represents no or little information, can significantly degrade the performance of ellipse fitting methods. We develop an ellipse fitting method that is robust to RIDPs based on the maximum correntropy criterion with variable center (MCC-VC), where an adaptable Laplacian kernel is used. For single ellipse fitting, we formulate a non-convex optimization problem and divide it into two subproblems, one to estimate the kernel bandwidth and the other the kernel center. We design sufficiently accurate convex approximation to each subproblem that will lead to computationally efficient closed-form solutions. The two subproblems are solved in an alternate manner until convergence is reached. We also investigate coupled ellipses fitting. While there exist multiple ellipses fitting methods in the literature, we develop a coupled ellipses fitting method by exploiting the underlying special structure, where the associations between the data points and ellipses are absent in the problem. The proposed method first introduces an association vector for each data point and then formulates a non-convex mixed-integer optimization problem to establish the data associations, which is approximately solved by relaxing it into a second-order cone program. Using the estimated data associations, we then extend the proposed single ellipse fitting method to accomplish the final coupled ellipses fitting. The proposed method is shown to perform significantly better than the existing methods using both simulated data and real images.

mRNA based vaccines provide broad protection against different SARS-CoV-2 variants of concern.

In order to overcome the pandemic of COVID-19, messenger RNA (mRNA)-based vaccine has been extensively researched as a rapid and versatile strategy. Herein, we described the immunogenicity of mRNA-based vaccines for Beta and the most recent Omicron variants. The homologous mRNA-Beta and mRNA-Omicron and heterologous Ad5-nCoV plus mRNA vaccine exhibited high-level cross-reactive neutralization for Beta, original, Delta, and Omicron variants. It indicated that the COVID-19 mRNA vaccines have great potential in the clinical use against different SARS-CoV-2 variants.

Robust Ellipse Fitting With Laplacian Kernel Based Maximum Correntropy Criterion.

The performance of ellipse fitting may significantly degrade in the presence of outliers, which can be caused by occlusion of the object, mirror reflection or other objects in the process of edge detection. In this paper, we propose an ellipse fitting method that is robust against the outliers, and thus maintaining stable performance when outliers can be present. We formulate an optimization problem for ellipse fitting based on the maximum entropy criterion (MCC), having the Laplacian as the kernel function from the well-known fact that the l1 -norm error measure is robust to outliers. The optimization problem is highly nonlinear and non-convex, and thus is very difficult to solve. To handle this difficulty, we divide it into two subproblems and solve the two subproblems in an alternate manner through iterations. The first subproblem has a closed-form solution and the second one is cast as a convex second-order cone program (SOCP) that can reach the global solution. By so doing, the alternate iterations always converge to an optimal solution, although it can be local instead of global. Furthermore, we propose a procedure to identify failed fitting of the algorithm caused by local convergence to a wrong solution, and thus, it reduces the probability of fitting failure by restarting the algorithm at a different initialization. The proposed robust ellipse fitting method is next extended to the coupled ellipses fitting problem. Both simulated and real data verify the superior performance of the proposed ellipse fitting method over the existing methods.

[Concomitant use of immobilized uridine-cytidine kinase and polyphosphate kinase for 5'-cytidine monophosphate production].

Uridine-cytidine kinase, an important catalyst in the compensation pathway of nucleotide metabolism, can catalyze the phosphorylation reaction of cytidine to 5'-cytidine monophosphate (CMP), but the reaction needs NTP as the phosphate donor. To increase the production efficiency of CMP, uridine-cytidine kinase gene from Thermus thermophilus HB8 and polyphosphate kinase gene from Rhodobacter sphaeroides were cloned and expressed in Escherichia coli BL21(DE3). Uridine-cytidine kinase was used for the generation of CMP from cytidine and ATP, and polyphosphate kinase was used for the regeneration of ATP. Then, the D403 metal chelate resin was used to adsorb Ni²âº to form an immobilized carrier, and the immobilized carrier was specifically combined with the recombinant enzymes to form the immobilized enzymes. Finally, single-factor optimization experiment was carried out to determine the reaction conditions of the immobilized enzyme. At 30 °C and pH 8.0, 60 mmol/L cytidine and 0.5 mmol/L ATP were used as substrates to achieve 5 batches of high-efficiency continuous catalytic reaction, and the average molar yield of CMP reached 91.2%. The above method has the advantages of low reaction cost, high product yield and high enzyme utilization rate, and has good applied value for industrial production.