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Background Hexavalent chromium (Cr (VI)) from environmental pollution shows severe toxicity towards human organs by causing oxidative damage. Apelin-13 may inhibit oxidative damage by blocking ROS accumulation and regulating multiple signals. Methods However, whether apelin-13 can attenuate Cr (VI)-induced toxicity has not been explored. Herein, the protective effect and molecular mechanism of apelin-13 against K2Cr2O7-induced cardiotoxicity in vitro and in vivo were evaluated. Results Apelin-13 significantly inhibited K2Cr2O7-induced H9c2 cytotoxicity and apoptosis, followed by the attenuated PARP cleavage and caspase activation. Further investigation revealed that apelin-13 co-treatment effectively suppressed K2Cr2O7-induced oxidative damage by inhibiting ROS accumulation. Moreover, apelin-13 co-treatment dramatically normalized MAPKs and PI3K/AKT pathways in K2Cr2O7-treated H9c2 cells. Importantly, apelin-13 administration in vivo effectively attenuated myocardial fibrosis, improved angiogenesis, and inhibited myocardial abnormal proliferation and apoptosis. Conclusions Ultimately, it alleviated K2Cr2O7-induced myocardial injury in rats.Taken together, our findings validated the strategy of the use of apelin-13 to effectively combat Cr (VI)-induced myocardial injury.

Full waveform inversion (FWI) is an extremely important velocity-model-building method. However, it involves a large amount of calculation, which hindsers its practical application. The multi-source technology can reduce the number of forward modeling shots during the inversion process, thereby improving the efficiency. However, it introduces cross-noise problems. In this paper, we propose a sparse constrained encoding multi-source FWI method based on K-SVD dictionary learning. The phase encoding technology is introduced to reduce crosstalk noise, whereas the K-SVD dictionary learning method is used to obtain the basis of the transformation according to the characteristics of the inversion results. The multi-scale inversion method is adopted to further enhance the stability of FWI. Finally, the synthetic subsag model and the Marmousi model are set to test the effectiveness of the newly proposed method. Analysis of the results suggest the following: (1) The new method can effectively reduce the computational complexity of FWI while ensuring inversion accuracy and stability; (2) The proposed method can be combined with the time-domain multi-scale FWI strategy flexibly to further avoid the local minimum and to improve the stability of inversion, which is of significant importance for the inversion of the complex model.

This study designs a method to improve the robustness of the micro air vehicle (MAV) yaw angle estimation for low-cost inertial navigation system/global positioning system (INS/GPS) integration by using a tri-axial magnetometer. Observability properties of the integration navigation system are first analysed, indicating that all attitude angles have great observability with the aid of the heading measurement by a magnetometer, while the observability of yaw angle is low in traditional INS/GPS. To improve the robustness of yaw angle estimation, the authors calibrate the tri-axial magnetometer according to the rotating ellipsoid model and establish a fault detection and isolation mechanism to adjust the weight of magnetic-measurement adaptively and dynamically in integration navigation. The simulation and experiment results show that the proposed method can calibrate the tri-axial magnetometer properly and screen out the abnormal magnetic measurement for the robustness of yaw angle estimation, suggesting that this technique is a viable candidate for MAV navigation and control applications in complex magnetic fields.

Air compressor is a main power equipment, and improving its reliability and security is important to enhance the competitiveness of pneumatic companies. This study proposes a real monitored data-based fault measure and early warning system for air compressor, which can guide field workers in economically and safely operating the air compressor by finding and dealing with faults ahead of time. A data-driven multivariate state estimation technique (MSET) is utilized to construct the non-parametric fault early warning model under normal operating condition, principal components analysis (PCA) and back propagation (BP) method are combined to construct the dynamic memory matrix and simplify the model. With the pre-built PCA-BP-MSET model, optimal values of the observed vectors are estimated and a deviation function is defined to calculated the deviation sequence between the estimated and observed vectors, where the qualitative-quantitative combined AHP method is adopted to determine the weights of the monitored variables. With the deviation sequence, the sliding window statistical method is applied to determine the fault early warming threshold, which can be used as a benchmark to measure and warn the fault of air compressor. The fault warning information of an air compressor is given out once the deviation degree of some observed vector exceeds the threshold, thereby realizing the function of fault measure and early warning in advance. In addition, an automatically updating method is proposed to ensure the accuracy of the PCA-BP-MSET model in case of the changes of running states. For verification, a real fault case of an air compressor has been chosen to verify the effectiveness of the proposed method. Result shows that the PCA-BP-MSET-based method can catch the fault developing process timely, which is appropriate for the faults prevention and rapid troubleshooting of air compressor.

In the traditional ground-penetrating radar image recognition methods, the recognition accuracy is not high, the recognition of complex targets is difficult, the recognition process is cumbersome, and the structural characteristics reflected by the measured data cannot be accurately judged. In this paper, a Faster R-CNN target detection algorithm in deep learning is applied to GPR image recognition. Firstly, based on the three-phase discrete random medium model, GPRmax software is used for forwarding simulation, and GPR images of different earth-rock dam disease types are obtained by changing the position, shape, and range of different disease types, and GPR image data sets are expanded using horizontal flipping, random erasing, scale transformation and adding random noise. Under the framework of TensorFlow, based on the Faster R-CNN target detection algorithm, the training and testing of the earth-rock dam disease target detection model are completed. The recognition performance on the test set is analyzed from three indexes of recall rate, precision rate and average precision rate, and evaluation indexes such as accuracy-recall rate curve. The results show that the average accuracy of the constructed target detection model for earth-rock dam disease recognition is over 90%. Among them, the recognition effect of concentrated leakage, scattered leaching, and cracks is the best. Finally, the effectiveness of the target detection model established in this paper is verified by the measured data of an abandoned slag slope.

The deformation prediction model is the key technical support of dam structure safety analysis. Given the shortcomings of the existing prediction models for settlement deformation of earth-rock dams in terms of accuracy and generalization, the adaptive network-based fuzzy inference system is introduced into the prediction model of earth-rock dam settlement deformation. The dynamic weight particle swarm optimization algorithm is used to optimize the parameters of the fitness value of the fuzzy layer in the adaptive network-based fuzzy inference system, the adaptive network-based fuzzy inference system that can find the optimal fitness value is formed, and the settlement deformation prediction model of earth-rock dam based on DPSO-ANFIS is established in this paper. The application of engineering examples can draw that the maximum deviation between the forecast output value of the settlement deformation prediction model based on DPSO-ANFIS and the measured value is 0.03mm, the root mean square error is 0.02mm, and the average absolute error is 0.01mm. The accuracy indexes are better than those of the settlement deformation prediction model of earth-rock dam based on PSO-ANFIS, ANFIS, and BP neural networks. For different measuring points and prediction interval length, the forecast output values of the settlement deformation prediction model of earth-rock dam based on DPSO-ANFIS is close to the measured values, the prediction trend conforms to the true value trend, the overall prediction performance is stable, and the accuracy value is within a reasonable range and better than other models. The application results of engineering examples show that the settlement deformation prediction model of earth-rock dam based on DPSO-ANFIS has high accuracy, good generalization, and reliable stability, and the comprehensive performance of engineering practice is better.

The local communication system of the metering automation system is mainly composed of concentrators, collectors, and smart meters. In addition to power metering, it also has functions such as power consumption information storage, user-side control, and power theft prevention. Attacks on smart meters and data concentrators may cause major power outages and losses. Taking CAN bus as an example, this paper proposes a communication protection scheme based on the national secret SM4-SM3 algorithm joint mechanism, which is applied to the local communication of the metering automation system. The software and hardware design of the scheme is carried out using the ZYNQ-7020 platform, and finally analyze and evaluate the results of experimental to verify the correctness of its function.

As an asymmetric encryption algorithm, RSA is currently known as the ripest and most widely used one. However, it is showed in many documents in recent years that RSA algorithm is lack of security, due to its weakness in defending side channel attacks, especially power analysis attacks. This paper proposes an RSA coprocessor resistant to power analysis attack, which adds pseudo operation and exponential randomization masking to defend SPA and DPA. Then, this paper improves the speed of RSA by using 256-base subtracted-free Montgomery multiplier combining with two-layer Karatsuba multiplier and CSA adder. This design is able to be implemented on both FPGA and ASIC. With a technology of 100 MHz clock frequency and SMIC 130 nm process, DC synthesis is implemented as well. The experiment result shows that our 1024-bit RSA design costs an area of 310 K gates and has a throughput of 110 Kbps.

The SM4 cryptographic algorithm is one of the standards of commercial cryptographic algorithm in China, which is used widely in the data encryption and other application scenarios for the advantages of less resources and fast speed. The attackers attack the first and last round of SM4 algorithm generally in the side channel attack. The number of the invalid random rounds before and after the SM4 cryptographic algorithm can make the side channel information collected by the attacker invalid in order to resist the side channel attack; At the same time, the multistage pipelining method is adopted to realize the SM4 cryptographic algorithm at the high speed, that is, four rounds of operations are realized every cycle, and one SM4 grouping operation is completed in eight cycles. The implementation results of the FPGA show that the clock frequency of SM4 cipher operation is up to 100MHz and the throughput rate under ECB mode is up to 1.6gbps, which has the advantages of high performance and anti-side channel attack.

This paper refers to a hardware implementation for executing modular multiplication in public-key cryptosystems using the Barrett reduction, which is a method of reducing a number modulo another number without the use of any division. Considering the flexibility of hardware, the modular multiplier we proposed is able to work over 3 prime fields \( {\text{GF}}\left( p \right) \), standardized by NIST for use in Elliptic Curve Cryptography (ECC), where the size of primes \( p \) are 256, 384, and 521 bits. We designed two methods to optimize the modular multiplier: Firstly, the circuit departed \( 257 \times 257 \) multiplier into two \( 257 \times 129 \) multipliers and an adder, three parts to optimize for clock frequency. Secondly, we proposed a parallel computing architecture to improve the utilization of multiplier and achieve high throughput. This modular multiplier runs at the clock rate of 300 MHz on 40 nm CMOS and performs a 256-bit modular multiplication in 3 cycles, while 384-bit modular multiplication costs 10 cycles and 521-bit modular multiplication costs 25 cycles. The architecture is very suitable for situations requiring high computing speed, such as online ECC signature verification.

Koji preparation is the key step in soy sauce brewing. In this study, 21 medicinal herbs were tested for their abilities in enhancing the protease activities of soy sauce koji. Among these herbs Rhodiola rosea was found to be the most efficient in increasing protease activities. Kinetic analyses revealed that R. rosea addition not only promoted microbe growth and increase the activities of neutral and acid proteases (by 29.8% and 13.4%, respectively) but also elevated α-diphenyl-β-picrylhydrazyl (DPPH) radical scavenging activity and total phenolics and flavonoids (by 9.5%, 47.1% and 14.1%, respectively); the formations of proteases and antioxidant properties depend largely on microbe growth; and the promotion effects of R. rosea addition were mainly displayed in later stage of fermentation. Using the R. rosea koji for soy sauce production resulted in 8.9%, 19.1%, 6.6%, 23% and 102% higher of total and amino-type nitrogen contents, protein utilization, total phenolics and flavonoids, respectively.

To understand the influence of aquatic vegetation on flow structures and sediment deposition, field experiments were conducted in a floodplain with water movement dominated by unidirectional current. Flow velocity, suspended sediment concentration, and sediment deposition were measured within and without vegetation at four sites covered by Phragmites communis (reed), Artemisia selengensis, Carex cinerascens, and a mix of them. Results show that the presence of vegetation reduced the time-averaged velocity and turbulent kinetic energy (TKE) and altered vertical distributions of the time-averaged velocity and TKE. For emergent conditions, both the time-averaged velocity and the TKE were uniformly distributed through the entire water column. Two layers were separated at the top of vegetation for submerged conditions. Within vegetation both the time-averaged velocity and TKE were decreased and uniformly distributed, similar to observations under emergent conditions. The discontinuity of drag force at the top of vegetation generated a region with rapidly increased velocity near the vegetation interface. TKE reached its maximum near the top of vegetation and decreased gradually toward both bed bottom and water surface. In present study, canopy with larger frontal area caused bigger reduction of time-averaged velocity and TKE within vegetation. By reducing the mean and turbulent velocities, the presence of vegetation decreased the depth-averaged suspended sediment concentration by 30–50% and increased the thickness of sediment deposited over one flood season by as high as 190% when compared with bare bed.

A combined wind tunnel and water flume experiment was performed to study the effect of an aquatic herbaceous plant patch on the turbulent structure and flow field of wind-induced currents. Eel grass was chosen as the test plant. The plants were settled in patch form. Three-dimensional instantaneous velocities were measured using an acoustic doppler velocimeter (ADV). The results indicate that in the non-eel grass patch flow, turbulent shear stress − u ′ w ′ ¯ has a local minimum near the flow reverse point, turbulent intensity has the tendency to decrease continually from surface to bottom, and the dominant turbulent event is sweeping. In the eel grass patch with wind-induced flow, reverse flow occurs more quickly than in the non-eel grass patch case, and the reverse point shifts downward. Turbulent shear stress − u ′ w ′ ¯ has two maxima below the canopy. Turbulent intensity u ′ 2 ¯ decreases generally from water surface to flume bed, but there are maxima below the canopy. The dominant turbulent event is the fourth quadrant event below the canopy, and the two relative contributions of the second and the fourth quadrant event have similar values above the canopy. The mean bias and RMS values at centre of the eel grass patch are almost as two times larger as that at other measuring lines in non-eel grass region. This indicates that not only the shear stress and turbulent intensity become larger, and the vertical variations of the shear stress and turbulent intensity are also larger due to the effect of vegetation. The differences in the effects of submerged herbaceous vegetation on open channel flow and wind-induced flow were discussed in relation to time averaged velocity, turbulent shear stress, turbulent intensity and coherent structure based on the present test data and previous data.

A flume experiment was conducted to investigate the effect of the aquatic herbaceous plant patch on the turbulent structure and flow field of shallow water. The eel grass that is widely distributed in the shallow lakes in China was chosen as the targeted plant. The plants were settled in patch form with three groups of densities and flow velocities. The three-dimensional instantaneous velocities were measured using an Audio Doppler Velocitimeter (ADV). The results indicate that the vertical velocity profile in the plant patch exhibits an S-shape from the canopy to the root of the eel grass . A secondary maximum in the vertical profile of velocity near the plant root is observed. The turbulent intensity increases from the water surface to the canopy, then decreases to the plant root; there is an inflection point around canopy, where the turbulent intensity deceases from the inner region to the side boundary of the patch. The vertical profiles of the eel grass resistance coefficient C P have different forms at different positions in the patch in general, but the forms of the C P profiles are similar along the boundary of the patch, and the forms of the C P profiles are similar in the inner part of the patch. In the patch area, the turbulent flow corresponds to the Quadrant 2 event (ejection event) above the canopy, the turbulent flow corresponds to the Quadrant 4 event (sweep event) below the canopy, but near the bed the Quadrant 1 event (outward interaction), the Quadrant 2 event and the Quadrant 4 event coexist. In the lateral boundary area of the patch the Quadrant 2 event and the Quadrant 3 event (inward interaction event) coexist due to presence of a strong shear layer.

The main purpose of this work was to develop and evaluate a self-emulsifying drug delivery system (SEDDS) of piperine to enhance its solubility and bioavailability. The formulation was optimized by solubility test and ternary phase diagrams. Then physiochemical properties and in vitro release of SEDDS were characterized. In vivo pharmacokinetics study and in situ single-pass intestinal perfusion were performed to investigate the effects of SEDDS on the bioavailability and intestinal absorption of piperine. The optimized formulation was composed of ethyl oleate, Tween 80 and Transcutol P (3:5.5:1.5, w/w), with the level of the piperine reached 2.5% (w/w). The in vitro dissolution rates of piperine SEDDS were significantly higher than the self-prepared capsules. In vivo pharmacokinetic study showed Cmax1, Cmax2 and area under the curve of piperine after oral administration of SEDDS in rats were 3.8-, 7.2- and 5.2-fold higher than the self-prepared capsules, respectively, and the relative bioavailability of SEDDS was 625.74%. The in situ intestinal absorption study revealed that the effective permeability and the effective absorption rate values of piperine for SEDDS were significantly improved comparing to solutions (p0.01). So SEDDS formulation could improve the oral bioavailability and intestinal absorption of piperine effectively.

This report describes the modification of crystallization plates by simply oxidizing the surface of the protein wells. The oxidized crystallization plates were tested in standard protein crystallization screening and reproducibility studies. The results showed that the protein wells of the treated plates were smoother and more optically transparent than those of the untreated plates, and more importantly, protein crystallization was significantly promoted after the oxidation treatment. Because there is no change to the routine screening protocol, this method is simple and easy to apply in protein crystallization.

A good ventilation system should reflect both safety reliable and economical reasonable. Safe and reliable mine ventilation system have high reliability and resilience during normal operation or in the disaster period. There is a close relationship between the reliability of mine ventilation network and the reliability of network branch. In order to make quantitative evaluation to the reliability of mine ventilation network. Based on the mine ventilation network equilibrium law, reliability theory is applied to the calculation of the branch of ventilation network, disjoint Boolean algebra is used to calculate the reliability of the network. This method has the advantages of simple operation, small calculation error etc.It will be helpful to the design, management and technological transformation of mine ventilation network.

Purpose: The aim of the present study is to separate the impedance change components of the blood vessels and ventricles in thorax from the mixed impedance signals detected on the chest surface. Methods: The mixed impedance signals on the chest surface are measured with a 15 electrode lead system. The thoracic impedance equations are established and solved iteratively with the algebraic reconstructed technique. Experiments were performed on 80 healthy, otherwise normal, adults. Results: Five impedance change components for the aorta (AO), blood vessel in left lung (PL), blood vessel in right lung (PR), left ventricle (LV), and right ventricle (RV) are separated from the mixed impedance signals. The experiments show that the main waveform of the ventricular components LV and RV is contrary to that of the vascular components AO, PL, and PR, and the negative peak point of the waveform graphs of LV and RV are in phase with the second cardiac sound (S2). The waveform graphs of various components correspond with the physiological activities of the heart and blood vessels in a cardiac cycle. The statistical results for 80 normal adults show that the amplitude of AO is the largest and that of PL and PR is the next, while that of LV and RV is the smallest. There are significant differences between them (P < 0.01). Conclusions: The mathematical model and the measurement method for the separation in the present paper are feasible.

We studied the growth of carbon nanotubes (CNTs) over a Co/Mo/Al2O3 catalyst by decomposing ethylene with or without the assistance of water. The optimal amount of water was determined to be 0.6% (φ) since excess water removed the amorphous carbon around the catalysts and also directly etched the CNTs at high temperature. Under this condition, the yield of CNTs can be increased from 3.7 g·g - 1 , based on the mass of catalyst, to 70 g·g - 1 within 1 h. The time-dependent online conversion of ethylene and the ratio of effective catalysts suggested that the effect of water is insignificant in the final growth period of the CNTs compared to that at the beginning. The correlation between the relative activity of the catalyst and the relative density of the CNT agglomerate suggests that the lack of growth volume inside the CNT agglomerate results in a gradual deactivation of the catalyst in the final CNT growth period. Raman characterization suggests that the degree of CNT defects increases with the bulk density of the CNT agglomerates since the mechanical resistance that is exposed on CNTs inside the agglomerate increases with reaction time. Thermal-gravimetric analysis indicates that the purity of CNTs ranges from 95.0% to 99.9% for a product with average purity of 99.2%. The non-uniform purity of the CNTs is due to the difference in mechanical resistance inside and outside the CNT agglomerate. The growth of CNTs outside the agglomerate is nearly free of mechanical resistance compared to that inside the agglomerate and, consequently, results in a high yield and high purity for the CNTs. These results suggest that it is necessary to control the agglomerate size and the structure, and to use a reactor with a large reactor volume for the growth of CNTs with low resistance and with high yield.

A novel polyimide composite with upper-use temperature of 420°C was prepared by autoclave process. The thermogravimetic analysis and rheological properties of uncured polyimide resin powders were analyzed. The influences of process parameters and post-treatment process on the properties of composites were also investigated. The morphologies of polyimide composites after shear fracture were observed by scanning electron microscope (SEM). The high-temperature resistance of composite was characterized by dynamic mechanical thermal analyzer (DMTA). Results showed that the imidization reaction mainly occurred in the temperature range of 100°C~220°C, and the largest weight loss rate appearing at 145°C indicated a drastic imidization reaction occurred. The melt viscosity of polyimide resin decreased with increasing the temperature between 220°C ∼305°C, and then increased with the increase of temperature due to the molecular crosslinking reactions. The fiber volume contents and void contents could be effectively ...

Selective catalytic reduction (SCR) is widely applied in coal-fired power plants. SCR process is a complex physical and chemical process with multi-input, strong coupling, nonlinear, and time delay characteristics. An effective model is the basis of conducting control and optimization. In this paper, influencing factors of catalytic reaction in SCR converter are analyzed and five measurable parameters are selected as the model input variables. NOx emission and NH 3 slip are separately taken as output variables. The LSSVM algorithm is employed to build the SCR models using real plant operation data from a 1000 MW coal-fired boiler. Simulation results have shown satisfied model accuracy and effectiveness are achieved.

Since traditional aviation bus gradually can not meet the requirements of modern military communication, migration of aviation bus towards high speed transmission is arousing wide concern for the purpose of salvaging the past investments on relevant systems. In this paper, a method for improving throughput and transmission rate of the aviation bus is purposed. The method combines OFDM modulation and aviation network, and exports a data highway using a broadband OFDM aviation interface over existing wires. Broadband OFDM interface over MIL-STD-1553 bus has been evaluated on FPGA board. It shows a considerable performance improvement and meets the requirements of avionic communication generally.

The demand for the clinical use of hepatocytes is increasing. The aim of this study was to develop a method for procurement of high qualitative pig hepatocytes and to evaluate the state of freshly isolated and cultured hepatocytes.The domestic extracorporeal circulating perfusion apparatus was used to isolate and harvest swine hepatocytes by the two-step perfusion method with EDTA and collagenase. The viability, function and morphology of the freshly isolated and cultured cells were evaluated and observed by the trypan blue exclusion test, biochemical measurements, phase contrast microscopy and transmission electron micrography (TEM).The total yield of isolated hepatocytes reached to 1.5(+/-0.4)X10(10) per liver with a viability of 92(+/-5)%, and the purity of hepatocytes reached to 98%. Immediately after isolation, phase-contrast microscope and TEM showed that undamaged hepatocytes appeared bright, translucent and spherical in shape, with a characteristic well-contrasted border. After 24 hours, the concentrations of alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), albumin (ALB), creatinine (Cr) and blood urea nitrogen (BUN) in the fluid of culture were declined significantly.This method of procuring swine hepatocytes could get high quality cells with active metabolic function.

Sodium laser beacon (SLB) excited by a macro-micro pulse laser with low power has the following advantages: the return photons without fluctuations and the high merit quantity, although the laser beam propagation and the size of SLB suffer form the atmospheric turbulence. In addition, the macro-pulse profile may influence the interaction of laser and sodium atoms. For the macro-pulse with a Gaussian profile, it is useful to enhance the merit quantity and the excitation probability of the SLB to increase the width of micropulse. In order to obtain more of the return photons in the SLB, while increasing the laser power, the fine beam quality, the appropriate launch diameter, and the spectral width of the laser etc. must be considered. Therefore, it is of practical significance for the SLB with fine characteristics to optimize the laser parameters, the launch diameter and launch pattern.

Symbolic partial mutual information is proposed in this paper, which is based on partial mutual information. This algorithm can be used to analyse the coupling between multivariate time series. We use this method to treat and analyse the sleeping multivariate bioelectricity signal (MBS) and wake one, it turns out that the coupling of wake MBS is obviously bigger than that of sleeping MBS. Finally hypothesis testing is done to prove that this method works and the average energy dissipation can be used as a parameter to detect nonequilibrium.