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This study proposes and experimentally validates an optimal integrated system to control the automotive continuously variable transmission (CVT) by Model Predictive Control (MPC) to achieve its expected transmission efficiency range. The control system framework consists of top and bottom layers. In the top layer, a driving intention recognition system is designed on the basis of fuzzy control strategy to determine the relationship between the driver intention and CVT target ratio at the corresponding time. In the bottom layer, a new slip state dynamic equation is obtained considering slip characteristics and its related constraints, and a clamping force bench is established. Innovatively, a joint controller based on model predictive control (MPC) is designed taking internal combustion engine torque and slip between the metal belt and pulley as optimization dual targets. A cycle is attained by solving the optimization target to achieve optimum engine torque and the input slip in real-time. Moreover, the new controller provides good robustness. Finally, performance is tested by actual CVT vehicles. Results show that compared with traditional control, the proposed control improves vehicle transmission efficiency by approximately 9.12%–9.35% with high accuracy.

The Ra EDM experiment uses a pair of high voltage electrodes to search for the atomic electric dipole moment of $^{225}$Ra. We use identical, plane-parallel electrodes with a primary high gradient surface of 200 mm$^2$ to generate reversible DC electric fields. Our statistical sensitivity is linearly proportional to the electric field strength in the electrode gap. We adapted surface decontamination and processing techniques from accelerator physics literature to chemical polish and clean a suite of newly fabricated large-grain niobium and grade-2 titanium electrodes. Three pairs of niobium electrodes and one pair of titanium electrodes were discharge-conditioned with a custom high voltage test station at electric field strengths as high as $+52.5$ kV/mm and $-51.5$ kV/mm over electrode gap sizes ranging from 0.4 mm to 2.5 mm. One pair of large-grain niobium electrodes was discharge-conditioned and validated to operate at $\pm 20$ kV/mm with steady-state leakage current $\leq 25$ pA ($1\sigma$) and a polarity-averaged $98 \pm 19$ discharges per hour. These electrodes were installed in the Ra EDM experimental apparatus, replacing a copper electrode pair, and were revalidated to $\pm 20$ kV/mm. The niobium electrodes perform at an electric field strength 3.1 times larger than the legacy copper electrodes and are ultimately limited by the maximum output of our 30 kV bipolar power supply., Comment: 16 pages, 11 figures

Cronobacter spp. are opportunistic pathogens that can cause serious diseases in neonates and infants via consumption of contaminated milk powder. To determine Cronobacter spp. contamination status, 632 samples, including 15 evaporated milk, 45 intermediate powder, 150 finished products, and 422 manufacturing environment samples, were collected from 3 goat milk powder factories in Shaanxi province, China, from July 2013 to April 2014. The recovered Cronobacter isolates were subtyped using pulsed-field gel electrophoresis to trace the potential dissemination routes during the whole production processing. Sixty-seven Cronobacter spp. isolates were recovered. The prevalence rates in manufacturing environment, intermediate powder, and finished products were 92.5, 6.0, and 1.5%, respectively. The predominant species were Cronobacter sakazakii (88.1%); no Cronobacter turicensis, Cronobacter condimenti, or Cronobacter dublinensis were detected. Sixty-seven Cronobacter isolates were grouped in 26 clusters by pulsed-field gel electrophoresis, and substantial genetic similarity was observed among isolates from different sampling sites in the same factory. Isolates in the main clusters were commonly recovered from intermediate powder, floor powder, and shoes. These data indicated that air, powder, and personnel movement were potential routes for Cronobacter dissemination, and manufacturing environment is the key control point for Cronobacter contamination.

A new despeckling algorithm for medical ultrasound images using multiscale weighting nonlinear diffusion is proposed in this paper. Firstly, the input image is decomposed by redundant Laplace transformation. Then, in the multiscale images, nonlinear diffusion is used. For nonlinear diffusion in each sub-image, an image gradient index is automatically determined by weighting the image gradient indexes of all the sub-images. To test the validity of the proposed algorithm, the typical methods of directly nonlinear diffusion and adaptive wavelet filter were used for comparison. The simulation and real ultrasound image results indicate that our approach can not only decrease speckle noise significantly but also preserve image details.

This paper investigates the point correspondence problem of two sets using scaled transform invariants. We proposed a method based on the idea of scaled invariant vector. A unit vector representation of invariants and scaling constant is introduced for affine transform. The method in principle applies to any dimension and any transformation with an computable invariant. The proposed method is shown to compute useful correspondence even with large number of outliers in noiseless case. We have also demonstrated improved performance comparing to most existing approaches for solving point pattern matching problem. The method is efficient and robust to noise up to a certain level.