Estimates on compressed neural networks regression

When the neural element number nn of neural networks is larger than the sample size mm, the overfitting problem arises since there are more parameters than actual data (more variable than constraints). In order to overcome the overfitting problem, we propose to reduce the number of neural elements by using compressed projection AA which does not need to satisfy the condition of Restricted Isometric Property (RIP). By applying probability inequalities and approximation properties of the feedforward neural networks (FNNs), we prove that solving the FNNs regression learning algorithm in the compressed domain instead of the original domain reduces the sample error at the price of an increased (but controlled) approximation error, where the covering number theory is used to estimate the excess error, and an upper bound of the excess error is given

Discrete Planning Unit Look-Ahead Velocity Control Strategy and Parallelization Research Based on GPU

During the machining of complicated curves and surfaces, the massive microsegments are generated. The microsegments are inputted into numerical control system (CNC) to process the velocity planning and high-velocity interpolation. This whole procedure is the core algorithm of CNC. During the procedure of velocity planning, the look-ahead iterative calculation is used for several specified future microsegments and the calculation quantity is very large. Additionally, the CNC is a typical hard real-time system. Every interpolation step must be finished in specified interpolation period, so the high calculating ability of CPU is needed. The concept of GPU is quite different from the traditional CPU. It has a very strong parallel computing ability. In this project, the GPU technology is introduced into CNC algorithm. The parallel structure model is constructed by CUDA, and a discrete planning unit look-ahead velocity control strategy is proposed. The GPU parallel computing mechanism of massive microsegments is discussed and, based on the research, a high-performance velocity planning algorithm is presented. This research result can highly raise the velocity planning and interpolation efficiency. This brand new solution can help improve the performance of CNC system dramatically. </jats:p

Study on the Nonsingular Problem of Fractional-Order Terminal Sliding Mode Control

An improved type of control strategy combining the fractional calculus with nonsingular terminal sliding mode control named non-singular fractional terminal sliding mode control (NFOTSM) is proposed for the nonlinear tire-road friction control system of vehicle in this paper. A fractional-order switching manifold is proposed, and the corresponding control law is formulated based on the Lyapunov stability theory to guarantee the sliding condition. The proposed controller ensures the finite time stability of the closed-loop system. Then, a terminal attractor is introduced to solve the singularity problem of fractional terminal sliding mode control (FOTSM). Finally, the performance of the NFOTSM is fully investigated compared with other related algorithms to find the effectiveness for the tire-road friction system. The results show that the NFOTSM has better performance than other related algorithms.</jats:p

Multiple measurements on the cosmic curvature using Gaussian process regression without calibration and a cosmological model

In this letter, we propose an improved cosmological model-independent method to measure cosmic curvature, combining the recent measurements of transverse and line-of-sight directions in the baryon acoustic oscillations (BAO) with cosmic chronometers (CC) datasets. Considering that the CC dataset is discrete and includes only 32 $H(z)$ measurements, we apply Gaussian process (GP) regression to fit the CC dataset and reconstruct them. Our methodology, which does not need the calibration or selection of any cosmological model, provide multiple measurements of spatial curvature ($\Omega_K$) at different redshifts (depending on the redshift coverage of BAO dataset). For combination of all BAO data, we find that the constraint result on cosmic curvature is $\Omega_K=-0.096^{+0.190}_{-0.195}$ with $1\sigma$ observational uncertainty. Although the measured $\Omega_K$ is in good agreement with zero cosmic curvature within 1$\sigma$ confidence level, our result revels the fact of a closed universe. More importantly, our results show that the obtained $\Omega_K$ measurements are almost unaffected by different priors of the Hubble constant. This could help solve the issue of the Hubble tension that may be caused by inconsistencies in the spatial curvature between the early and late universes.Comment: 12 pages, 2 figures, welcome to comment, submitted to Physics Letters

Infection of hepatitis B virus in extrahepatic endothelial tissues mediated by endothelial progenitor cells

BACKGROUND: Hepatitis B virus (HBV) replication has been reported to be involved in many extrahepatic viral disorders; however, the mechanism by which HBV is trans-infected into extrahepatic tissues such as HBV associated myocarditis remains largely unknown. RESULTS: In this study, we showed that human cord blood endothelial progenitor cells (EPCs), but not human umbilical vein endothelial cells (HUVECs) could be effectively infected by uptake of HBV in vitro. Exposure of EPCs with HBV resulted in HBV DNA and viral particles were detected in EPCs at day 3 after HBV challenge, which were peaked around day 7 and declined in 3 weeks. Consistently, HBV envelope surface and core antigens were first detected in EPCs at day 3 after virus challenge and were retained to be detectable for 3 weeks. In contrast, HBV covalently closed circular DNA was not detected in EPCs at any time after virus challenge. Intravenous transplantation of HBV-treated EPCs into myocardial infarction and acute renal ischemia mouse model resulted in incorporation of HBV into injured heart, lung, and renal capillary endothelial tissues. CONCLUSION: These results strongly support that EPCs serve as virus carrier mediating HBV trans-infection into the injured endothelial tissues. The findings might provide a novel mechanism for HBV-associated myocarditis and other HBV-related extrahepatic diseases as well

A Driver Modeling Based on the Preview-Follower Theory and the Jerky Dynamics

Based on the preview optimal simple artificial neural network driver model (POSANN), a new driver model, considering jerky dynamics and the tracing error between the real track and the planned path, is established. In this paper, the modeling for the driver-vehicle system is firstly described, and the relationship between weighting coefficients of driver model and system parameters is examined through test data. Secondly, the corresponding road test results are presented in order to verify the vehicle model and obtain the information on drive model and vehicle parameters. Finally, the simulations are carried out via CarSim. Simulation results indicate that the jerky dynamics need to be considered and the proposed new driver model can achieve a better path-following performance compared with the POSANN driver model

Study on the Removal of Heavy Metals From Wastewater by Ultra High Lime With Aluminum Precipitation Coupling Activated Carbon Adsorption in 300 MW Coal-Fired Units

ObjectivesThe wet flue gas desulphurization of coal-fired power plants generates a large amount of wastewater containing heavy metals, the removal of heavy metals from wastewater by coupling of limestone and sodium metaaluminate precipitation and activated carbon adsorption were studied.MethodsThe optimized feed ratio, temperature, and pH value for the precipitation method were obtained, and the experimental parameters for the type of adsorbent and adsorption layer height were optimized. Based on this, engineering tests were conducted on the 300 MW unit of Sanhe coal-fired power plant. Field experiments were conducted with an additional precipitator feeder and adsorption device, and effect was investigated.ResultsThe optimal feeding rate is 160 kg/h, the flow rate is 1 m3/h, and the adsorption height is 10 cm. Under the experimental conditions, the overall heavy metal removal efficiency is significantly improved. Compared with the heavy metal content in the original export of the power plant, the removal efficiency of lead, chromium, copper, and nickel from the export increase by 33.24%, 81.93%, 35.22%, and 57.52%, respectively, after installing a mixed precipitation and adsorption device.ConclusionsThe method of coupling of limestone and sodium metaaluminate precipitation and activated carbon adsorption can effectively promote the removal of heavy metals from desulfurization wastewater, providing guidance for the deep removal of heavy metals in the wastewater from coal-fired power plants

Analysis of anisotropy anomalies identification in apparent resistivity observation

Since 1966, China has been using apparent resistivity observation to forecast strong aftershocks of the Xingtai earthquake. Retrospective studies of subsequent strong earthquakes have shown that anomalies in apparent resistivity observation before earthquakes usually exhibit anisotropic characteristics. In addition to the anisotropic changes in apparent resistivity before earthquakes, factors such as subway operation near the observation area, metal pipeline networks, and changes in water levels have also been found to cause anisotropic changes. These factors are called environmental interference factors. Therefore, distinguishing between anisotropic changes before earthquakes and anisotropic changes caused by interference and eliminating the effects of interference is crucial for using apparent resistivity observations for forecasting. Taking the observation of Hefei seismic station in Anhui Province as an example, a model is constructed using the finite element method to try to establish a method for analyzing anisotropy in apparent resistivity before earthquakes, and the data from other provincial stations are used for verification. In the modeling process, the influence coefficient is a measure of the relationship between the variation in apparent resistivity and the changes in the medium of the measurement area. The following results are obtained by calculating the influence coefficient using the finite element method: the influence coefficient between the power supply electrode and the measuring electrode of the apparent resistivity observation is negative, and the rest are positive, and the distribution of the influence coefficient shows obvious symmetry, with the axis of symmetry being the line connecting the electrodes and its midline, and the absolute value of the influence coefficient is inversely proportional to the distance from the electrodes. In addition, according to the constructed finite element model, the amplitude of anisotropic changes caused by interference can be quantitatively calculated. Given that interference is ubiquitous in various regions of the world, this study can provide a reference for international earthquake forecasters to quantitatively remove environmental interference in anisotropy. Moreover, when building apparent resistivity stations in seismic areas for earthquake prediction, it is best to avoid areas with larger local influence coefficients to ensure that the anomalous data before the earthquake is true and reliable

Chronic Myeloid Leukemia Patients Sensitive and Resistant to Imatinib Treatment Show Different Metabolic Responses

The BCR-ABL tyrosine kinase inhibitor imatinib is highly effective for chronic myeloid leukemia (CML). However, some patients gradually develop resistance to imatinib, resulting in therapeutic failure. Metabonomic and genomic profiling of patients' responses to drug interventions can provide novel information about the in vivo metabolism of low-molecular-weight compounds and extend our insight into the mechanism of drug resistance. Based on a multi-platform of high-throughput metabonomics, SNP array analysis, karyotype and mutation, the metabolic phenotypes and genomic polymorphisms of CML patients and their diverse responses to imatinib were characterized. The untreated CML patients (UCML) showed different metabolic patterns from those of healthy controls, and the discriminatory metabolites suggested the perturbed metabolism of the urea cycle, tricarboxylic acid cycle, lipid metabolism, and amino acid turnover in UCML. After imatinib treatment, patients sensitive to imatinib (SCML) and patients resistant to imatinib (RCML) had similar metabolic phenotypes to those of healthy controls and UCML, respectively. SCML showed a significant metabolic response to imatinib, with marked restoration of the perturbed metabolism. Most of the metabolites characterizing CML were adjusted to normal levels, including the intermediates of the urea cycle and tricarboxylic acid cycle (TCA). In contrast, neither cytogenetic nor metabonomic analysis indicated any positive response to imatinib in RCML. We report for the first time the associated genetic and metabonomic responses of CML patients to imatinib and show that the perturbed in vivo metabolism of UCML is independent of imatinib treatment in resistant patients. Thus, metabonomics can potentially characterize patients' sensitivity or resistance to drug intervention