Metal-Matrix Embedded Phononic Crystals

Metal-matrix embedded phononic crystals (MMEPCs) can be applied for noise and vibration reduction. Metal-matrix embedded phononic crystals (MMEPCs) consisting of double-sided stubs (single “hard” stubs/composite stubs) were introduced. The introduced MMEPCs are deposited on a two-dimensional locally resonant phononic crystal plate that consists of an array of rubber fillers embedded in a steel plate. The lower frequency complete bandgap will be produced in the MMEPCs with composite stubs by decoupling the spring-mass system of the resonator by means of the rubber filler. Then, the out-of-plane bandgap and the in-plane bandgap can be adjusted into the same lowest frequency range by the composite stubs. The broad complete bandgap will be produced in the metal-matrix embedded phononic crystals with single “hard” stubs by producing new kinds of resonance modes (in-plane and out-of-plane analogous-rigid modes) by introducing the single “hard” stubs, and then the out-of-plane bandgap and the in-plane bandgap can be broadened into the same frequency range by the single “hard” stubs. The proposed MMEPCs can be used for noise and vibration reduction

YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation

Weakly-supervised learning (WSL) has been proposed to alleviate the conflict between data annotation cost and model performance through employing sparsely-grained (i.e., point-, box-, scribble-wise) supervision and has shown promising performance, particularly in the image segmentation field. However, it is still a very challenging problem due to the limited supervision, especially when only a small number of labeled samples are available. Additionally, almost all existing WSL segmentation methods are designed for star-convex structures which are very different from curvilinear structures such as vessels and nerves. In this paper, we propose a novel sparsely annotated segmentation framework for curvilinear structures, named YoloCurvSeg, based on image synthesis. A background generator delivers image backgrounds that closely match real distributions through inpainting dilated skeletons. The extracted backgrounds are then combined with randomly emulated curves generated by a Space Colonization Algorithm-based foreground generator and through a multilayer patch-wise contrastive learning synthesizer. In this way, a synthetic dataset with both images and curve segmentation labels is obtained, at the cost of only one or a few noisy skeleton annotations. Finally, a segmenter is trained with the generated dataset and possibly an unlabeled dataset. The proposed YoloCurvSeg is evaluated on four publicly available datasets (OCTA500, CORN, DRIVE and CHASEDB1) and the results show that YoloCurvSeg outperforms state-of-the-art WSL segmentation methods by large margins. With only one noisy skeleton annotation (respectively 0.14%, 0.03%, 1.40%, and 0.65% of the full annotation), YoloCurvSeg achieves more than 97% of the fully-supervised performance on each dataset. Code and datasets will be released at https://github.com/llmir/YoloCurvSeg.Comment: 11 pages, 10 figures, submitted to IEEE Transactions on Medical Imaging (TMI

Does air pollution exposure affect semen quality? Evidence from a systematic review and meta-analysis of 93,996 Chinese men

BackgroundAir pollution may impair male fertility, but it remains controversial whether air pollution affects semen quality until now.ObjectivesWe undertake a meta-analysis to explore potential impacts of six pollutants exposure during the entire window (0–90 days prior to ejaculation) and critical windows (0–9, 10–14, and 70–90 days prior to ejaculation) on semen quality.MethodsSeven databases were retrieved for original studies on the effects of six pollutants exposure for 90 days prior to ejaculation on semen quality. The search process does not limit the language and search date. We only included original studies that reported regression coefficients (β) with 95% confidence intervals (CIs). The β and 95% CIs were pooled using the DerSimonian-Laird random effect models.ResultsPM2.5 exposure was related with decreased total sperm number (10–14 lag days) and total motility (10–14, 70–90, and 0–90 lag days). PM10 exposure was related with reduced total sperm number (70–90 and 0–90 lag days) and total motility (0–90 lag days). NO2 exposure was related with reduced total sperm number (70–90 and 0–90 lag days). SO2 exposure was related with declined total motility (0–9, 10–14, 0–90 lag days) and total sperm number (0–90 lag days).ConclusionAir pollution affects semen quality making it necessary to limit exposure to air pollution for Chinese men. When implementing protective measures, it is necessary to consider the key period of sperm development

Influence of radiation on Hemarthria compressa's genetic variations

Using the material of Hemarthria compressa (L.F.) R.Br. cv. YA’AN, we carried out this research to study the influence of radiation on the genetic variation of plants. Genetic difference was analyzed with expressed sequence tag-simple sequence repeat (EST-SSR) molecular marker through the comparison of 60Co-γ radiation on H. compressa seed stems and original variety. By using 20 primer pairs, 176 polymerase chain reaction (PCR)-amplifications with clear and consistent bands were obtained. The results showed that 155 of 176 bands were polymorphic, which indicating an 88.07% polymorphism rate, and each pair of primers had 8.8 amplified bands on average; the amplitude of polymorphism information content was 0.4709–0.6952 with an average value 0.6081. The genetic similarity coefficient of H. compressa and its mutants ranged from 0.4318 to 0.8239 with an average of 0.6671. As a consequence, existence of genetic differences between the mutants and the basic material was proved.We gratefully acknowledge financial support from the Modern Agro-industry Technology Research System (CARS-34) and the Sichuan Province Breeding Research grant (2016NZ0098-11).Peer reviewe

Experimental investigations on ice accretion process and anti-/de-icing technology for aero-engine icing mitigation

Aero-engine icing is widely recognized as a significant hazard to aviation safety in cold weather. During flights, upon the impingement of small, super-cooled, airborne water droplets in clouds, ice accretion would occur on the exposed surfaces of aero-engines, such as inlet lips, spinners, fan rotor blades, and inlet guide vanes. Ice formation on such components can significantly degrade the performance of aero-engines. The ice accretion over the fan blades and spinner surface can also result in an imbalance rotation of the rotor to cause serious mechanical vibrations. Furthermore, the ice shedding from these surfaces may cause damages to the fan rotor and components behind the fan, even be sucked into the core engine resulting in a severe stall, surge, or flameout. By using the Icing Research Tunnel of Iowa State University (i.e., ISU-IRT), a series of experimental studies were conducted to investigate the dynamic ice accretion process on the surface of an aero-engine spinner-fan model and to explore the feasibility of different anti-/de-icing technologies. At first, the dynamic ice accretion process on three different kinds of aero-engine spinners (i.e., conical, coniptical and elliptical) was examined. The trajectories and impingement characteristics of super-cooled water droplets were characterized by using a digital Particle Image Velocimetry (PIV) system. An infrared (IR) thermal imaging system was also used to quantify the unsteady heat transfer process over the surface of the aero-engine spinner models under different icing conditions. The transient ice accretion process over the rotating fan blades of an aero-engine fan model and the effects of ice accretion on the aerodynamic performance of the fan unit model were investigated. An explorative study was also conducted to use a bio-inspired super-hydrophobic coating for aero-engine icing mitigation. Finally, the anti-/de-icing performance of a hot-air circulating system for an engine inlet guide vane (IGV) was also evaluated under different icing conditions. The findings derived from the present study will provide a better understanding about aero-engine icing phenomena, which will lead to more effective and robust anti-/de-icing strategies to ensure safer and more efficient operation of an aero-engine in cold weather.</p

A study on feature selection for trend prediction of stock trading price

Conference Name:2013 5th International Conference on Computational and Information Sciences, ICCIS 2013. Conference Address: Shiyan, Hubei, China. Time:June 21, 2013 - June 23, 2013.The movement of price is influenced by many factors or features in stock market. It is a challenging work how to select these features and provide the relation between them and the movement of price. This paper applies two recursive feature elimination (RFE) methods SVM-RFE and RF-RFE to feature selection in the trend prediction of stock price, where SVM-RFE and RF-RFE are based on the famous support vector machine (SVM) and random forest (RF) techniques, respectively. Both the stability and classification performance for the subset of features selected are investigated. The experimental results on nine shares from Shanghai Stock Exchange in China show that both SVM and RF are effective for the trend prediction, and SVM performs better than RF. In addition, SVM seems to be unaffected by the correlation and redundant features and it turns better for the most shares when more features are used for modeling. Therefore, a suggestion for RFE in the trend prediction of stock price is that it may be unnecessary for SVM while it is needed for RF. ? 2013 IEEE

A Method to Improve the Response of a Speed Loop by Using a Reduced-Order Extended Kalman Filter

In servo systems, encoders are usually used to measure the position and speed signals of electric machines. But in a low speed range, the traditional M/T method has a larger time delay, which will cause an increase of the speed loop order and degradation of the speed loop performance. A method employed to reduce the delay of speed feedback by using a reduced-order Extended Kalman Filter (EKF) is introduced in this paper. The speed of the permanent magnet synchronous motor is estimated by the reduced-order EKF in a low speed range, which reduces the delay of speed feedback and extends the cutoff frequency of the speed loop to improve the dynamic performance of the servo system. In order to solve the issues that the traditional full-order EKF is sensitive to the inertia of the system and computationally complex, a composite load torque observer (CLTO) is proposed in this paper. The load torque and the friction torque are simultaneously observed by the CLTO. Additionally, the CLTO is used to reduce the order of the EKF, which reduces the sensitivity of EKF on inertia to enhance the robustness of the algorithm and simplifies the computational complexity. The feasibility and effectivity of the above method are verified by simulations and experiments