Design and analysis of multi-ring microstructured-core optical fibers

A novel design of single-mode large-mode-area optical fiber is presented. The core is composed of alternate high and low-index regions to form an effectively low-index contrast between the core and the cladding. The proposed fiber is investigated by the finite-element method with anisotropic perfect matched layer boundary conditions. In addition, the bending losses of the fibers are calculated and compared with those of the step-index optical fibers. In particular, numerical simulations demonstrate that single-mode operation can be achieved in one such fiber with mode area larger than 600 μm² at the wavelength of 1.55 μm and bending loss lower than 0.02 dB/m for bending radius greater than 20 cm.     

Fundamental uncertainty in the BAO scale from isocurvature modes

Small fractions of isocurvature perturbations correlated with the dominant adiabatic mode are shown to be a significant primordial systematic for Baryon Acoustic Oscillation (BAO) surveys which must be accounted for in future surveys. Isocurvature modes distort the standard ruler distance by broadening and shifting the peak in the galaxy correlation function. While a single isocurvature mode does not significantly degrade dark energy constraints, the general case with multiple isocurvature modes leads to biases that exceed 7σ on average in the dark energy parameters even for isocurvature amplitudes undetectable by Planck. Accounting for all isocurvature modes corrects for this bias but degrades the dark energy figure of merit by at least 50% in the case of the Boss experiment. However the BAO data in turn provides significantly stronger constraints on the nature of the primordial perturbations. Future large galaxy surveys will thus be powerful probes of exotic physics in the early Universe in addition to helping pin down the nature of dark energy.     

大冷量分置式低温制冷机的研究与分析

叙述了大冷量低温制冷机系统的设计要求、设计计算、结构特点和测试结果,对影响制冷机的可靠性各类因素进行了分析,目前该制冷机与红外探测器组件的联试已取得成功,制冷机各项设计指标已满足组件要求.     

Effect of multi-frequency ultrasound assisted thawing on the quality of large yellow croaker (Larimichthys crocea)

The effects of mono-, dual- and tri-frequency ultrasound-assisted thawing (UAT) on the physicochemical quality, water-holding capacity, moisture migration and distribution and myofibrillary structure of frozen large yellow croaker (Larimichthys crocea) were detected. The results indicated that multifrequency UAT treatment significantly increased the thawing rate, maintained the stability of myofibrils and reduced the lipid oxidation. The multifrequency UAT samples had better water-holding capacity (higher water-holding capacity values, lower thawing loss and cooking loss) and physicochemical quality (higher hardness, springiness, resilience, chewiness and lower total volatile basic nitrogen (TVB-N) values, thiobarbituric acid reactive substances (TBARS) values), higher immobilized water content, and lower free water content. Therefore, the results provide a further understanding of the quality stability of frozen large yellow croaker treated by the multifrequency UAT.     

URLLC occasional large time delay prediction based on unbalanced regression and LSTM

Occasional large time delay is one of the bottlenecks for 5G applied to the industrial field. Accurate measurement, analysis, and prediction of communication network latency are of great significance. Due to the strong randomness and small number of samples in ultra-reliable and low latency communication (URLLC), the prediction task of occasional large time delay is very challenging. This paper proposes an URLLC occasional large time delay prediction method based on unbalanced regression algorithms and long–short term memory (LSTM). We first decompose the original sequence by using the variational mode decomposition (VMD) to obtain relatively stable component sequences. The parameters of the VMD are automatically optimized by grasshopper optimization algorithm (GOA). In order to improve the prediction effect of URLLC occasional large time delay, we introduce unbalanced regression algorithms. Before the VMD decomposition of data samples, the SMOGN is introduced to balance the number of large-time delay samples and common-time delay samples. Next we calculate the weight of each sample based on the rarity of each sample point and our proposed LDSWeight. Finally, LSTM is used to complete cost-sensitive learning. The experimental results show that the URLLC occasional large time delay prediction method proposed in this paper has better prediction accuracy than other methods.     

Multimagic rectangles based on large sets of orthogonal arrays

Large sets of orthogonal arrays (LOAs) have been used to construct resilient functions and zigzag functions by Stinson. In this paper, an application of LOAs in constructing multimagic rectangles is given. Further, some recursive constructions for multimagic rectangles are presented, and some infinite families of bimagic rectangles are obtained.     

Covariance selection by thresholding the sample correlation matrix

This article shows that when the nonzero coefficients of the population correlation matrix are all greater in absolute value than (_C1logp/n)^1/2${(C_{1}logp/n)}^{1/2}$ for some constant _C1$C_1$, we can obtain covariance selection consistency by thresholding the sample correlation matrix. Furthermore, the rate (logp/n)^1/2${(logp/n)}^{1/2}$ is shown to be optimal.