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Background: Individuals living in rural areas had higher incidence rate for stroke than their urban counterparts in China. However, few studies investigated on the association between blood malondialdehyde (MDA), an end product of lipid oxidation caused by reactive oxygen species (ROS), and stroke risk in rural population. Aim: We aimed to investigate whether blood MDA level contributes to a higher stroke risk in a Chinese elderly population from rural areas. Methods: Data from 2011-2012 of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a national cohort of older adults in China were analyzed. Smooth curve and multivariable correction analysis were used to evaluate the association between blood MDA level and stroke risk in the elderly populations from rural and urban areas respectively. Results: The median age of all inluded participants (N=1598) was 84 years. The results of smooth curve model revealed a gradual upward trend on association of blood MDA levels with stroke risk in rural participants but not in urban participants. Similarly, the conditional logistic regression analysis suggested a significant association MDA levels with stroke risk in rural participants but not in urban participants after adjustments of related confounding factors (age, gender, current smoker, current drinker, current exercise, BMI and cardiovascular diseases (hypertension, heart disease, atrial fibrillation and diabetes) were made. Conclusion: Among the elderly population in China, elevated blood MDA levels were associated with increased stroke risk in rural participants but not in urban participants.

The temporal shape of laser pulses is one of the essential performances in the inertial confinement fusion (ICF) facility. Due to the complexity and instability of the laser propagation system, it is hard to predict the pulse shapes precisely by pure analytic methods based on the physical model [Frantz-Nodvik (F-N) equation]. Here, we present a data-driven model based on a convolutional neural network (CNN) for precise prediction. The neural network model introduces sixteen parameters neglected in the F-N equation based models to expand the representation dimension. The sensitivity analysis of the experimental results confirms that these parameters have different degrees of influence on the temporal output shapes and cannot be ignored. The network characterizes the whole physical process with commonality and specificity features to improve the description ability. The prediction accuracy evaluated by a root mean square of the proposed model is 7.93%, which is better compared to three optimized physical models. This study explores a nonanalytic methodology of combining prior physical knowledge with data-driven models to map the complex physical process by numerical models, which has strong representation capability and great potential to model other measurable processes in physical science.

Unbound granular materials (UGM) in permeable pavement will experience large numbers of infiltration during their service-life. The frequently changed moisture not only affects the cooling effect of permeable pavement, but also influences the mechanical behaviors of UGM. However, evidence is lacking to state the influence of infiltration on the behaviors of UGM, which is commonly in fully permeable pavement. Considering the influence of infiltration, this study conducted experimental tests to investigate the effect on the water-retaining and bearing capacity of UGM. With the water-retaining tests, the water-retaining rate in the whole structure and at different depths was analyzed under different infiltration numbers and duration. The results showed that the water-retaining rate increased with the extension of the infiltration duration. The infiltration duration had a significant influence on the water-retaining capacity of UGM, while the infiltration number had little. The difference in the water-retaining rate between the top and bottom layers was up to 2.56%. The water-retaining capacity of the integrated structure was hardly affected due to the dissimilarity of the water-retaining rate at different depths. With infiltrations, the fine aggregate in the upside structure migrated downward to the lower structure, resulting in a reduction in water-retaining rate in the upper structure and an increase at the bottom. In addition, the mechanical behaviors were evaluated by the traditional California Bearing Ratio (CBR) and repeated CBR tests under five infiltrations. The first and second infiltration had a significant influence on the CBR of UGM. With two infiltrations, the plastic strain increased by 57.8% via the repeated CBR tests. The resilient strain had an increase by 36.52% and the equivalent modulus decreased by 28.7% with the first infiltration. The first infiltration presented a critical influence on the bearing capacity of UGM and the effect decreased with the increase in the infiltration number. These findings will enrich the behaviors investigation of UGM and promote its application in the fully permeable pavement.

Icariside II (ICS II) has been reported to have protective effects against oxidative stress. However, whether ICS II protects cardiomyocytes from myocardial infarction (MI), and the associated underlying mechanisms, remain to be elucidated. Therefore, the current study investigated the effects of ICS II on hypoxia‑injured H9c2 cells, as well as the associated molecular mechanisms. A hypoxic injury model was established to emulate the effects of MI. The effects of ICS II on the proliferation of rat cardiomyocyte H9c2 cells were assessed with cell counting kit‑8 assays. The apoptotic status of the cells was assessed by flow cytometry, and the expression of apoptosis‑related proteins was analyzed by western blotting. A microRNA (miRNA/miR) microarray was used to quantify the differential expression of miRNAs after ICS II treatment, and the levels of miR‑7‑5p were further quantified by reverse transcription‑quantitative PCR. Whether ICS II affected hypoxia‑injured cells via miR‑7‑5p was subsequently examined, and the target of miR‑7‑5p was also investigated by bioinformatics analysis and luciferase reporter assays. The effects of ICS II on the PI3K/Akt pathway were then evaluated by western blot analysis. Hypoxia treatment decreased viability and the migration and invasion abilities of H9c2 cells, and also induced apoptosis. ICS II significantly increased viability and reduced hypoxia‑associated apoptosis. Moreover, ICS II treatment led to the upregulation of miR‑7‑5p, and the protective effects of ICS II were found to rely on miR‑7‑5p. Moreover, BTG anti‑proliferation factor (BTG2) was identified as a direct target of miR‑7‑5p, and overexpression of BTG2 inhibited the protective effects of miR‑7‑5p. Finally, ICS II treatment resulted in the activation of the PI3K/Akt signaling pathway, which is essential for the survival of H9c2 cells under hypoxic conditions. In summary, ICS II reduces hypoxic injury in H9c2 cells via the miR‑7‑5p/BTG2 axis and activation of the PI3K/Akt signaling pathway.

Fused silica optical elements are widely used in large high-power laser devices, and the subsurface defects of optical elements directly affect the laser damage threshold and imaging quality. These defects are distributed within a few to tens of microns from the surface and cannot be detected by conventional imaging methods. The characteristics of small size, low density and wide distribution range make it difficult to detect nondestructively, effectively and quickly with conventional methods. In order to solve the above problems, an experimental system was built based on the principles of photoluminescence and dark field scattering. Use the different characteristics of fluorescence image and scattering image to carry out the research of subsurface defect detection. First, preprocess the original image. Second, calculate the offset of adjacent images, perform background homogenization processing on the image, and stitch the sub-aperture images, and then segment the full-aperture image. Then, a more effective subsurface defect extraction algorithm is proposed. Finally, etch the sample with HF and observe it under a microscope. Experimental results show that this method can detect weak defects on the surface and sub-surface at the same time, and can effectively separate individual sub-surface defects. This method has the advantages of lossless, fast and high precision. Moreover, based on a large amount of data, analysis and summary of the causes of defects, distribution characteristics, etc.. This method can provide certain guidance for the evaluation of laser damage threshold and processing technology of optical components in high-power laser devices.

In this paper, an optical simulation system f-theta lens composed of three ordinary glass spherical lenses is optimized by using optical design software. The lens is made of quartz glass which is commonly used in infrared band. The total length of the lens is 139mm, forming area is 85mm × 85mm. It is compact, simple and low cost. Additionally, the focal spot is very small, and the moving aperture is in a large range of 10-40mm. The focusing performance is close to the diffraction limit, and the spot size of the image plane reaches the diffraction limit of 3μm. The relative linear distortion is less than 0.005%. Therefore, our design meets the requirements of high precision for optical devices.

In large high-power laser devices,the surface and subsurface defects of fused silica optical components directly affect the laser damage threshold and imaging quality. In this paper, fluorescence imaging technology is used to obtain images of defects in the subsurface layer of optical components that will absorb laser. Because the original image has the characteristics of sparse signal, weak intensity, low contrast, etc. In order to efficiently and reliably evaluate the surface and subsurface defects, this paper proposes a weak and small defect detection method based on local adaptive contrast enhancement and seed region growth. Firstly, the local adaptive contrast enhancement method is used to enhance the contrast of the original image. Secondly, the method of bilateral filtering is used to denoise. Thirdly, seed region growth method is used to segment the defective regions and perform morphological processing. Finally, defect detection is performed. The experiment uses different segmentation methods to detect images in different regions. The results show that this method can significantly enhance the contrast of the original fluorescence image, and detect pixel-level defects, and the detection rate is stable at about 95%. Meanwhile, the reasons, size distribution and other characteristics of the sub-surface defects of fused silica optical components are analyzed. This paper provides a nondestructive method of detecting weak and small defects in the subsurface layer of the optical element faster and higher accuracy.

In this study, we examined the effects of marination with five edible mushroom powders (3%, m/m) on the quality attributes and protein changes of pork longissimus dorsi compared to meat marinated with 0.2% papain and distilled water (control group). The results indicated that pork samples marinated with edible mushrooms displayed better water retention and lower shear force, especially in the 3% Hypsizygus marmoreus (HM) group (12.50 ± 0.73 N). Ultrastructural observation results showed that the Z-disk and M-line of the pork samples marinated with edible mushrooms were fractured and weakened. Furthermore, the degradation extent of desmin in the HM-marinated pork samples was obviously increased (43%) in comparison to the papain group (only 15%), which was further confirmed by the results of the myofibril fragmentation index. Overall, the pork samples marinated with 3% HM exhibited better quality traits among all groups and might be a potential strategy to improve tenderness.

To find a better conjugate direction, the optimization effect of six search (six-seeking) and three search method are analyzed. Because of the arbitrariness of the initial point, the first process of optimizing along the negative gradient direction is abandoned. The four search method is put forward. Each best or optimal point is the initial point of the next optimization. After three time of consecutive searches along the negative gradient directions, take the conjugate direction obtained from the second and the third optimization as the fourth search direction. That is, there are four search directions in each loop. The steps, valid mathematical proof, and program flow chart are given. A quadratic function with three variables and Rosenbrock function with two variables are used as the objective functions to verify the methods. Two examples prove the validity of the 4 search method to complex objective function. Therefore, the four search method is a better conjugate direction method.

A 1178 J near diffraction limited 527 nm laser is realized in a complete closed-loop adaptive optics (AO) controlled off-axis multi-pass amplification laser system. Generated from a fiber laser and amplified by the pre-amplifier and the main amplifier, a 1053 nm laser beam with the energy of 1900 J is obtained and converted into a 527 nm laser beam by a KDP crystal with 62% conversion efficiency, 1178 J and beam quality of 7.93 times the diffraction limit (DL). By using a complete closed-loop AO configuration, the static and dynamic wavefront distortions of the laser system are measured and compensated. After correction, the diameter of the circle enclosing 80% energy is improved remarkably from 7.93DL to 1.29DL. The focal spot is highly concentrated and the 1178 J, 527 nm near diffraction limited laser is achieved.

Due to the problems that some defects on the surface are very weak and the low contrast of the background, adaptive local contrast enhancement was adopted. Then multiscale gaussian side window filter was proposed to enhance the defect details. By looking for appropriate local maxima to locate the defect area for segmentation. The broken scratches were connected by the morphological method, then scratches and stains were classified by the geometric features parameters. By comparing and analyzing various methods of image detail enhancement and defect segmentation, the results show that the accuracy of the algorithm proposed in this paper is 91.3% in defect detection, faster than the traditional algorithms, and has higher detection efficiency and precision.

Laser beam dumps are necessary for laser systems designed to deliver high power or high energy to achieve effective control of stray light. However, the energy density of the stray light destroys the absorption glass of the beam dump with an increase in the output energy. To solve this problem, the initial laser-induced-damage threshold (LIDT) of a new optical absorption material was tested. A new type of laser beam dump was designed with this new optical material based on geometrical optics and light-field distribution analysis.

The long depth of field camera with wavefront coding is introduced in Design of Long Depth of Field Array Optical Components Defect Detection System [1]. It can obtain the whole object information at one time within 3-13 m of the depth of field. However, when binocular calibration is used in corner detection, the scalability and asymmetry of the point spread function will lead to images missing and redundancy. This article describes an improvement in the Hessian corner detector to solve this problem. Firstly, the local negative maximum with the largest change in curvature is extracted around the X corner, and the initial corner set is obtained according to their central symmetry. Then, by making use of the distance characteristics between corners of the checkerboard and constraining the angle characteristics of these corners, the false corners are filtered and the correct corner set is obtained. Finally, the corners set is sorted and the starting direction of the sorting is constrained. The corners extracted through this algorithm can be better applied to camera calibration and positioning. Experiments show that the proposed detector is better than OpenCV detector in the accuracy of positioning, calibration and measurement, and has certain robustness.

In high-power laser facilities, the application of a traditional wavefront control method is limited under the influence of a continuous phase plate (CPP). In order to obtain a satisfactory far-field intensity distribution at the target of the beamline with the CPP, a novel deformable mirror (DM) resolution-matching-based two-stage wavefront sensorless adaptive optics method is proposed and demonstrated. The principles of the DM resolution-matching method and two-stage wavefront sensorless adaptive optics method are introduced, respectively. Based on the numerical model, the matching relationship between the actuator space of the DM and the spatial period of the CPP is investigated. By using the resolution-matched DM, the feasibility of the two-stage wavefront sensorless adaptive optics method is numerically and experimentally verified. Both the numerical and the experimental results show that the presented DM resolution-matching-based two-stage wavefront sensorless adaptive optics method could achieve the target focal spot control under the influence of the CPP, and the profile and the intensity uniformity of the corrected focal spot are optimized close to the designed ideal focal spot.

Molecular dynamics simulations are performed to investigate the effects of hydrostatic and shock densification on the structural and mechanical properties of porous silica. In the 0–35 GPa pressure range, the equation of state reveals a unique plastic-elastic transition for this material, resulting in a continuous density increase followed by saturation. Structural modifications are reflected in the medium-range order only, as evidenced by the increase of inter-tetrahedral bond angles occurring through the pressure-induced rearrangement of Si O Si planes and associated bonds. Discontinuous evolution of the elastic moduli for densified porous silica is observed and associated with the change of ring statistics.

Monolithic large-aperture diffraction grating tiling is desired to increase the output capability of multi-kilojoule petawatt laser facilities. However, the wavefront errors of input pulse and gratings will degrade the focal spot quality and the compressibility of the output pulse. In this work, the effects of wavefront error of input pulse, deformation and wave aberration of the grating for the large-aperture tiled-grating compressor are investigated theoretically. A series of numerical simulations are presented to discuss the changing trends of focal spot energy caused by wavefront error of input pulse and obtain the error tolerance for specific goals. The influences of coating stress and the wave aberration of holographic exposure gratings on the diffraction wavefront are also discussed. Some advice is proposed for improving the performance of large-aperture tiled-grating. This work paves the way for the design of practical large-aperture tiled-grating compressor for ultrahigh intensity laser facilities in the future.

In this paper, a hierarchical kernel extreme learning machine (HK-ELM) is proposed to solve the problem that the size of laser-induced damage (LID) cannot be accurately measured under the condition of inhomogeneous total internal reflection illumination. The proposed method overcomes the limitations of the radiometric method, which depends on a single factor to measure the size of damage. After analyzing the light scattering characteristics of LID with the finite-difference time-domain method, we find that we should consider the influences of multiple factors when measuring the size of damage under the condition of uneven illumination. The experimental results show that HK-ELM can achieve ultra-resolution measurements, and the mean relative error of the measured size predicted by HK-ELM is within 5% on the testing samples. Compared with the traditional technology, the method proposed in this paper effectively improves the measurement accuracy.

Background Brain-Computer Interface (BCI) can bring great convenience to patients in the process of rehabilitation training and prosthetic control. However, how to extract effective features is a core issue in a BCI system. Methods We proposes the Multi-Feature Fusion Method based on Wavelength Optimal Spatial Filter and Multiscale Entropy for classifying the electroencephalogram signals (EEG) in four kinds of motor imagery tasks. The method can combine Wavelength features with Multiscale Entropy. Results Two groups of experiments were conducted. One for simple four types of motor imagery (MI) tasks and another for unilateral limb. Experiments show that our proposed method has better performance compared to other methods. (82.55% versus 73.08% average accuracy respectively). Conclusions The proposed method can effectively improve the accuracy of EEG classification in multiclass motor imagery and will be useful for neurorehabilitation through motor imagery for hemiplegic patients.