Gearbox fault diagnosis under different operating conditions based on time synchronous average and ensemble empirical mode decomposition

In this paper, a new method is proposed by combining ensemble empirical mode decomposition (EEMD) with order tracking techniques to analyse the vibration signals from a two stage helical gearbox. The method improves EEMD results in that it overcomes the potential deficiencies and achieves better order spectrum representation for fault diagnosis. Based on the analysis, a diagnostic feature is designed based on the order spectra of extracted IFMs for detection and separation of gearbox faults. Experimental results show this feature is sensitive to different fault severities and robust to the influences from operating conditions and remote sensor locations

Quantum criticality and nodal superconductivity in the FeAs-based superconductor KFe2As2

The in-plane resistivity $\rho$ and thermal conductivity $\kappa$ of FeAs-based superconductor KFe$_2$As$_2$ single crystal were measured down to 50 mK. We observe non-Fermi-liquid behavior $\rho(T) \sim T^{1.5}$ at $H_{c_2}$ = 5 T, and the development of a Fermi liquid state with $\rho(T) \sim T^2$ when further increasing field. This suggests a field-induced quantum critical point, occurring at the superconducting upper critical field $H_{c_2}$. In zero field there is a large residual linear term $\kappa_0/T$, and the field dependence of $\kappa_0/T$ mimics that in d-wave cuprate superconductors. This indicates that the superconducting gaps in KFe$_2$As$_2$ have nodes, likely d-wave symmetry. Such a nodal superconductivity is attributed to the antiferromagnetic spin fluctuations near the quantum critical point.Comment: 4 pages, 4 figures - replaces arXiv:0909.485

On Reducing the Effect of Covariate Factors in Gait Recognition: a Classifier Ensemble Method

Robust human gait recognition is challenging because of the presence of covariate factors such as carrying condition, clothing, walking surface, etc. In this paper, we model the effect of covariates as an unknown partial feature corruption problem. Since the locations of corruptions may differ for different query gaits, relevant features may become irrelevant when walking condition changes. In this case, it is difficult to train one fixed classifier that is robust to a large number of different covariates. To tackle this problem, we propose a classifier ensemble method based on the random subspace Method (RSM) and majority voting (MV). Its theoretical basis suggests it is insensitive to locations of corrupted features, and thus can generalize well to a large number of covariates. We also extend this method by proposing two strategies, i.e, local enhancing (LE) and hybrid decision-level fusion (HDF) to suppress the ratio of false votes to true votes (before MV). The performance of our approach is competitive against the most challenging covariates like clothing, walking surface, and elapsed time. We evaluate our method on the USF dataset and OU-ISIR-B dataset, and it has much higher performance than other state-of-the-art algorithms

A surface defect detection method of the magnesium alloy sheet based on deformable convolution neural network

In the rolling process of the magnesium alloy sheet, due to improper control parameters or inaccurate production equipment and other reasons, the surface of the magnesium alloy sheet is prone to appearance of edge crack, fold, inclusion, ripple, scratch and other defects. In order to improve the surface quality of the magnesium alloy sheet, a surface defect detection method based on deformable convolution neural network is proposed in the paper, which presents a higher detection accuracy than those traditional methods on the convolutional neural network (CNN), support vector machine (SVM) and Bayes. The experiment result shows the final detecting accuracy is greater than 95 %

Thickness-dependent spontaneous dewetting morphology of ultrathin Ag films

We show here that the morphological pathway of spontaneous dewetting of ultrathin Ag films on SiO2 under nanosecond laser melting is found to be film thickness dependent. For films with thickness h between 2 <= h <= 9.5 nm, the morphology during the intermediate stages of dewetting consisted of bicontinuous structures. For films 11.5 <= h <= 20 nm, the intermediate stages consisted of regularly-sized holes. Measurement of the characteristic length scales for different stages of dewetting as a function of film thickness showed a systematic increase, which is consistent with the spinodal dewetting instability over the entire thickness range investigated. This change in morphology with thickness is consistent with observations made previously for polymer films [A. Sharma et al, Phys. Rev. Lett., v81, pp3463 (1998); R. Seemann et al, J. Phys. Cond. Matt., v13, pp4925, (2001)]. Based on the behavior of free energy curvature that incorporates intermolecular forces, we have estimated the morphological transition thickness for the intermolecular forces for Ag on SiO2 . The theory predictions agree well with observations for Ag. These results show that it is possible to form a variety of complex Ag nanomorphologies in a consistent manner, which could be useful in optical applications of Ag surfaces, such as in surface enhanced Raman sensing.Comment: 20 pages, 5 figure

Ionitronic manipulation of current-induced domain wall motion in synthetic antiferromagnets

The current induced motion of domain walls forms the basis of several advanced spintronic technologies. The most efficient domain wall motion is found in synthetic antiferromagnetic (SAF) structures that are composed of an upper and a lower ferromagnetic layer coupled antiferromagnetically via a thin ruthenium layer. The antiferromagnetic coupling gives rise to a giant exchange torque with which current moves domain walls at maximum velocities when the magnetic moments of the two layers are matched. Here we show that the velocity of domain walls in SAF nanowires can be reversibly tuned by several hundred m/s in a non-volatile manner by ionic liquid gating. Ionic liquid gating results in reversible changes in oxidation of the upper magnetic layer in the SAF over a wide gate-voltage window. This changes the delicate balance in the magnetic properties of the SAF and, thereby, results in large changes in the exchange coupling torque and the current-induced domain wall velocity. Furthermore, we demonstrate an example of an ionitronic-based spintronic switch as a component of a potential logic technology towards energy-efficient, all electrical, memory-in-logic

Overexpression of N-terminal kinase like gene promotes tumorigenicity of hepatocellular carcinoma by regulating cell cycle progression and cell motility

Amplification and overexpression of CHD1L is one of the most frequent genetic alterations in hepatocellular carcinoma (HCC). Here we found that one of CHD1L downstream targets, NTKL, was frequently upregulated in HCC, which was significantly correlated with vascular invasion (P = 0.012) and poor prognosis (P = 0.050) of HCC. ChIP assay demonstrated the binding of CHD1L to the promoter region of NTKL. QRT-PCR study showed that the expression of NTKL positively correlated with CHD1L expression in both clinical samples and cell lines. Functional study found that NTKL had strong oncogenic roles, including increased cell growth, colony formation in soft agar, and tumor formation in nude mice. Further study found that NTKL could promote G1/S transition by decreasing P53 and increasing CyclinD1 expressions. NTKL overexpression could accelerate the mitotic exit and chromosome segregation, which led to the cytokinesis failure and subsequently induced apoptosis. NTKL also regulated cell motility by facilitating philopodia and lamellipodia formation through regulating F-actin reorganization and the phosphorylation of small GTPase Rac1/ cdc42. Using co-IP and mass spectrometry approach, we identified the large GTPase dynamin2 as an interacting protein of NTKL, which might be responsible for the phenotype alterations caused by NTKL overexpression, such as cytokinesis failure, increased cell motility and abnormal of cell division.published_or_final_versio