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From the perspective of liquor brewing technology, the quality of liquor yeast undoubtedly determines the quality of liquor products, but the problems such as inconvenient storage, difficult transportation and easy deterioration of liquid liquor yeast greatly restrict the development of liquor industry. Aiming at this problem, the author firstly summarized the research status of drying technology, damage mechanism and protection strategy of white spirit yeast. Then, on the basis of studying the damage mechanism of yeast in the drying process of yeast, the optimization of drying process and the formulation of protective strategies of yeast were discussed. Finally, new research methods are proposed from three perspectives: optimal design of drying process, damage mechanism and protection strategy

Childhood asthma has substantial effects on children's health. It is important to identify influencing factors in early life in the development of childhood asthma. We aim to evaluate the effects of early-life factors and indoor environmental exposure on childhood asthma in Chongqing, China.We designed a case-control study to enrol children with asthma aged 3 to 14 years old and controls in Chongqing, China. The "Children's Early Life and Indoor Environment Survey" was used to collect the early-life factors and indoor environmental exposure of foetuses in utero and of infants during the first 3 years of life. A multivariate logistic regression model was used to evaluate the association between independent variables and childhood asthma and the interaction of early-life factors and environmental exposure.A total of 160 asthma cases and 247 controls were included in this study. The mean ages of the cases and controls were 5.53 ± 1.88 and 5.72 ± 2.34 years, respectively (P = 0.192). Early-life factors and indoor environmental exposure were independently associated with childhood asthma. Infectious diseases of the respiratory system in children under 3 years old [adjusted odds ratio (OR) = 5.76, 95% confidence interval (CI) 2.49-13.30], bedroom air conditioner use (adjusted OR = 4.61, 95% CI 1.45-14.64), and bedroom dampness/mould (adjusted OR = 2.98, 95% CI 1.54-5.75) ranked as the three most significant exposures associated with the risk of childhood asthma. Other factors associated with an increased risk of childhood asthma included second-hand smoke exposure in early life (adjusted OR = 1.93, 95% CI 1.24-3.00), neonatal pneumonia (adjusted OR = 1.90, 95% CI 1.05-3.42) and maternal allergic diseases during pregnancy (adjusted OR = 2.13, 95% CI 1.10-4.10). The interaction effects of child second-hand smoke exposure with other covariates were not found to be statistically significant.Early-life factors and indoor environmental exposure are closely related to childhood asthma in Chongqing, China. Further interventions and management in the early life of children should be considered to prevent and control childhood asthma in Chongqing and similar cities.

As a nonlinear similarity measure defined in the kernel space, the correntropic loss (C-Loss) can address the stability issues of second-order similarity measures thanks to its ability to extract high-order statistics of data. However, the kernel adaptive filter (KAF) based on the C-Loss uses the stochastic gradient descent (SGD) method to update its weights and, thus, suffers from poor performance and a slow convergence rate. To address these issues, the conjugate gradient (CG)-based correntropy algorithm is developed by solving the combination of half-quadratic (HQ) optimization and weighted least-squares (LS) problems, generating a novel robust kernel correntropy CG (KCCG) algorithm. The proposed KCCG with less computational complexity achieves comparable performance to the kernel recursive maximum correntropy (KRMC) algorithm. To further curb the growth of the network in KCCG, the random Fourier features KCCG (RFFKCCG) algorithm is proposed by transforming the original input data into a fixed-dimensional random Fourier features space (RFFS). Since only one current error information is used in the loss function of RFFKCCG, it can provide a more efficient filter structure than the other KAFs with sparsification. The Monte Carlo simulations conducted in the prediction of synthetic and real-world chaotic time series and the regression for large-scale datasets validate the superiorities of the proposed algorithms in terms of robustness, filtering accuracy, and complexity.

The hyperbolic cosine function with high-order errors can be utilized to improve the accuracy of adaptive filters. However, when initial weight errors are large, the hyperbolic cosine-based adaptive filter (HCAF) may be unstable. In this paper, a novel normalization based on the logarithmic hyperbolic cosine function is proposed to achieve the stabilization for the case of large initial weight errors, which generates a logarithmic HCAF (LHCAF). Actually, the cost function of LHCAF is the logarithmic hyperbolic cosine function that is robust to large errors and smooth to small errors. The transient and steady-state analyses of LHCAF in terms of the mean-square deviation (MSD) are performed for a stationary white input with an even probability density function in a stationary zero-mean white noise. The convergence and stability of LHCAF can be therefore guaranteed as long as the filtering parameters satisfy certain conditions. The theoretical results based on the MSD are supported by the simulations. In addition, a variable scaling factor and step-size LHCAF (VSS-LHCAF) is proposed to improve the filtering accuracy of LHCAF further. The proposed LHCAF and VSS-LHCAF are superior to HCAF and other robust adaptive filters in terms of filtering accuracy and stability.

The multikernel adaptive filters based on the minimum mean square error (MMSE) criterion have been proposed to improve the performance of the kernel least mean square (KLMS), efficiently. However, these multikernel methods suffer from large computational burden as well as instability in impulsive noises. To address these issues, a novel multikernel method is proposed by replacing the trace operation of a matrix with the inner product of two vectors, thus leading to higher computational efficiency, significantly. Based on the maximum correntropy criterion, the multikernel maximum correntropy (MKMC) algorithm is therefore proposed. To further reduce the complexity, an online vector quantization strategy is presented for MKMC to generate the quantized MKMC (QMKMC) algorithm. Monte Carlo simulations on different nonlinear examples validate the superiorities of the proposed two algorithms.

The kernel conjugate gradient (KCG) algorithms have been proposed to improve the convergence rate and the filtering accuracy of kernel adaptive filters (KAFs) efficiently. However, sparsification is necessary in the KCG algorithms to curb the growth of network structure for online applications. To this end, a novel online kernel conjugate gradient algorithm under the mean square error criterion is proposed to approximate the kernel matrix in KAFs by combining k-means sampling into the Nystrom method in a fixed-dimensional feature space, namely a Nystrom kernel conjugate gradient algorithm based on k-means sampling (NysKCG-KM). The approximation accuracy of the kernel matrix as well as the filtering performance of NysKCG-KM are therefore guaranteed by k-means sampling. The proposed NysKCG-KM with no requirement of sparsification can achieve dramatically better filtering accuracy than the kernel least mean square with sparsification, and approach the filtering accuracy of the kernel recursive least squares with sparsification. Monte Carlo simulations using both the synthetic and real-world data validate the superiorities of the proposed NysKCG-KM.

Significance Afferent and efferent nerve fibers cannot be distinguished based on the axonal diameter or the presence of the Remark bundle. The compaction of the myelin sheath involves 2 steps: 1) The distance between the 2 layers of cell membranes in the double-bilayer decreases; 2) the adjacent double-bilayers close to form MDL. The expression of MBP is positively correlated with the formation of the MDL. Anchoring of the myelin sheath by lipophilin particles might be required for the formation of a compacted myelin sheath. The abnormalities in nerve fiber structure observed in autologous nerve grafts do not appear to be related to either MBP or lipophilin, so further research is needed to determine their causes., Observing the structure and regeneration of the myelin sheath in peripheral nerves following injury and during repair would help in understanding the pathogenesis and treatment of neurological diseases caused by an abnormal myelin sheath. In the present study, transmission electron microscopy, immunofluorescence staining, and transcriptome analyses were used to investigate the structure and regeneration of the myelin sheath after end-to-end anastomosis, autologous nerve transplantation, and nerve tube transplantation in a rat model of sciatic nerve injury, with normal optic nerve, oculomotor nerve, sciatic nerve, and Schwann cells used as controls. The results suggested that the double-bilayer was the structural unit that constituted the myelin sheath. The major feature during regeneration was the compaction of the myelin sheath, wherein the distance between the 2 layers of cell membrane in the double-bilayer became shorter and the adjacent double-bilayers tightly closed together and formed the major dense line. The expression level of myelin basic protein was positively correlated with the formation of the major dense line, and the compacted myelin sheath could not be formed without the anchoring of the lipophilin particles to the myelin sheath.

The process of microbial spray-drying has inherent defects such as short time, complexity, and non-visualization of particle trajectory. However, there has been a lack of effective methods for real-time sampling, rehydration, and non-destructive storage of dried particles, as well as mathematical modeling of the drying process of yeast particles based on sampling and measurement data. Therefore, firstly, a real-time sampling system was developed which completed real-time sampling, rehydration, and non-destructive storage of spray-dried particles, and realized the real reproduction of the changes of yeast particles in the process of spray drying. The laws that the motion trajectory of microbial particles during spray drying are divided into the first cycle region and the reflux cycle region were concluded, and the partition mechanism was explored. Then, based on the sampling data and the law of heat and mass transfer, a mathematical model of porous media was established to predict the variation of moisture content and rehydration survival rate of dried microbial particles with drying time. Finally, the mathematical model was tested by a microbial spray drying experiment, and the maximum errors between the predicted value and the test value of moisture content and rehydration survival rate were Xmax1=0.027(d.b) and Qvmax1=1.06%, respectively, both were less than 5% which proved the correctness of the mathematical model of porous media and laid a foundation for the study of the damage mechanism of microbial spray drying.

This paper addresses the stability issues of the least mean absolute third (LMAT) algorithm using the normalization based on the third order in the estimation error. A novel robust normalized least mean absolute third (RNLMAT) algorithm is therefore proposed to be stable for all statistics of the input, noise, and initial weights. For further improving the filtering performance of RNLMAT in different noises and initial conditions, the variable step-size RNLMAT (VSSRNLMAT) and the switching RNLMAT (SWRNLMAT) algorithms are proposed using the statistics of the estimation error and a switching method, respectively. The filtering performance of RNLMAT is improved by VSSRNLMAT and SWRNLMAT at the expense of affordable computational cost. RNLMAT with less computational complexity than other normalized adaptive filtering algorithms, can provide better filtering accuracy and robustness against impulsive noises. The steady-state performance of RNLMAT and SWRNLMAT in terms of the excess mean-square error is performed for theoretical analysis. Simulations conducted in system identification under different noise environments confirm the theoretical results and the superiorities of the proposed algorithms from the aspects of filtering accuracy and robustness against large outliers.

This article first introduces the research background and working principle of the TX phase alignment function of the Virtex-7 series FPGA. Then, according to the application requirements of the PCIe protocol, a design scheme for 12-channel bonding based on the GTH IP core is proposed. This solution solves the traditional High-speed serial transceivers only support up to eight channel bonding problems. The simulation results and board-level verification results of the solution show that the solution can stably achieve 12-channel bonding, and at the same time, the link bandwidth can be expanded to 1.5 times.

This article first discusses the DDR3 system calibration principle of the Virtex-7 series FPGA, analyzes the reliability of the DDR3 controller under different temperature and voltage conditions, and then proposes a solution to improve the reliability of the DDR3 controller. Simulation verification and on-board debugging test results show that this solution can effectively improve the reliability of the DDR3 system in FPGA devices under different temperature and voltage changes.

This paper first introduces the influence of process parameter fluctuation on FPGA interconnect timing. Then, according to the characteristics of FPGA architecture and the implementation method, the reason of FPGA chip yield reduction caused by interconnect timing difference is analyzed. Finally, this paper proposes a technical scheme of embedded EFUSE timing calibration, and introduces the calibration circuit. Chip test results show that the scheme can effectively control interconnect timing deviation and improve FPGA chip yield when process fluctuation is serious.

This article first introduces two implementation methods of Virtex-7 series FPGA reconfiguration, and then combines two implementation methods according to their characteristics, proposes an online upgrade solution based on FPGA reconfiguration. Finally, according to the scheme design, simulation results show that the online upgrade scheme can ensure that the FPGA chip will not cause functional failure after the online upgrade.

This article first introduces the implementation of FPGA dynamic partial reconfiguration, combined with the space radiation environment’s demand for FPGA configuration refresh, and analyzes the advantages and disadvantages of different refresh control systems. According to the understanding of the FPGA bitstream structure, this paper proposes a Self-Refresh bitstream design scheme based on FPGA dynamic partial reconfiguration and designs the corresponding bitstream. The simulation results show that the bitstream design scheme is easy to implement in FPGA and significantly reduces the refresh time.

Adaptive filters based on the maximum correntropy criterion (MCC) exhibit good robustness against impulsive interferences. The commonly used kernel function employed in MCC is Gaussian although it may not be the best option in all cases. To this end, a generalization of the Gaussian kernel, called the q-Gaussian kernel, combined with the MCC is developed using the gradient, however leading a slow convergence rate. To overcome this defect of slow convergence rate, this paper presents a novel q-Gaussian maximum correntropy criterion with conjugate gradient (QMCC-CG) algorithm. The proposed QMCC-CG algorithm accelerates the convergence and improves filtering accuracy compared to the conventional MCC algorithms in impulsive noises. Monte Carlo simulated results on system identification validate the superior performance of QMCC-CG.

The traditional kernel adaptive filter (KAF) based on the minimum mean square error (MMSE) criterion suffers from poor filtering accuracy and slow convergence rate in Gaussian noises. To this end, the recursive KAF based on the least squares (LS) criterion can improve filtering accuracy and convergence rate in Gaussian noises with the increase of computational and storage burdens. However, both quadratic similarity measures based filters may suffer instability in non-Gaussian noises. To address these issues, a robust kernel conjugate gradient least mean p-power (KCGLMP) algorithm based on the mean p- power error (MPE) criterion is therefore proposed by combining the conjugate gradient optimization method with kernel trick. The proposed KCGLMP algorithm improves filtering accuracy and computational efficiency, simultaneously. Simulation results confirm the superiorities of the proposed KCGLMP algorithm over other conventional KAFs in non-Gaussian noises.

As a nonlinear measure similarity developed in a kernel space, the generalized correntropic loss (GC-Loss) has been successfully used for signal processing and machine learning in non-Gaussian situations thanks to its ability of extracting high-order statistical properties of data. However, a highly non-convex performance surface in GC-Loss leads to poor optimization performance. To address this issue, we propose a new similarity measure developed in the kernel space by combining a generalized Gaussian distributed kernel function into the Cauchy loss. By minimizing the proposed loss function and using the kernel method, a novel kernel recursive generalized Cauchy kernel loss (KRGCKL) algorithm in the reproducing kernel Hilbert space (RKHS) is proposed. Simulations on different examples under non-Gaussian noises show the superiorities of KRGCKL over other representative algorithms in terms of filtering accuracy and robustness to large outliers.