Multiple normalized solutions for quasi-linear Schr\"odinger equations

In this paper we prove the existence of two solutions having a prescribed $L^2$-norm for a quasi-linear Schr\"odinger equation. One of these solutions is a mountain pass solution relative to a constraint and the other one a minimum either local or global. To overcome the lack of differentiability of the associated functional, we rely on a perturbation method developed in [27]

Laboratory-Evolved Mutants of an Exogenous Global Regulator, IrrE from Deinococcus radiodurans, Enhance Stress Tolerances of Escherichia coli

The tolerance of cells toward different stresses is very important for industrial strains of microbes, but difficult to improve by the manipulation of single genes. Traditional methods for enhancing cellular tolerances are inefficient and time-consuming. Recently, approaches employing global transcriptional or translational engineering methods have been increasingly explored. We found that an exogenous global regulator, irrE from an extremely radiation-resistant bacterium, Deinococcus radiodurans, has the potential to act as a global regulator in Escherichia coli, and that laboratory-evolution might be applied to alter this regulator to elicit different phenotypes for E. coli.To extend the methodology for strain improvement and to obtain higher tolerances toward different stresses, we here describe an approach of engineering irrE gene in E. coli. An irrE library was constructed by randomly mutating the gene, and this library was then selected for tolerance to ethanol, butanol and acetate stresses. Several mutants showing significant tolerances were obtained and characterized. The tolerances of E. coli cells containing these mutants were enhanced 2 to 50-fold, based on cell growth tests using different concentrations of alcohols or acetate, and enhanced 10 to 100-fold based on ethanol or butanol shock experiments. Intracellular reactive oxygen species (ROS) assays showed that intracellular ROS levels were sharply reduced for cells containing the irrE mutants. Sequence analysis of the mutants revealed that the mutations distribute cross all three domains of the protein.To our knowledge, this is the first time that an exogenous global regulator has been artificially evolved to suit its new host. The successes suggest the possibility of improving tolerances of industrial strains by introducing and engineering exogenous global regulators, such as those from extremophiles. This new approach can be applied alone or in combination with other global methods, such as global transcriptional machinery engineering (gTME) for strain improvements

Self-Adaptive Fault Feature Extraction of Rolling Bearings Based on Enhancing Mode Characteristic of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise

Originally, a rolling bearing, as a key part in rotating machinery, is a cyclic symmetric structure. When a fault occurs, it disrupts the symmetry and influences the normal operation of the rolling bearing. To accurately identify faults of rolling bearing, a novel method is proposed, which is based enhancing the mode characteristics of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). It includes two parts: the first is the enhancing decomposition of CEEMDAN algorithm, and the second is the identified method of intrinsic information mode (IIM) of vibration signal. For the first part, the new mode functions (CIMFs) are obtained by combing the adjacent intrinsic mode functions (IMFs) and performing the corresponding Fast Fourier Transform (FFT) to strengthen difference feature among IMFs. Then, probability density function (PDF) is used to estimate FFT of each CIMF to obtain overall information of frequency component. Finally, the final intrinsic mode functions (FIMFs) are obtained by proposing identified method of adjacent PDF based on geometrical similarity (modified Hausdorff distance (MHD)). FIMFs indicate the minimum amount of mode information with physical meanings and avoid interference of spurious mode in original CEEMDAN decomposing. Subsequently, comprehensive evaluate index (Kurtosis and de-trended fluctuation analysis (DFA)) is proposed to identify IIM in FIMFs. Experiment results indicate that the proposed method demonstrates superior performance and can accurately extract characteristic frequencies of rolling bearing

Pre-Coated Fe–Ni Film to Promote Low-Pressure Carburizing of 14Cr14Co13Mo4 Steel

Case-hardening 14Cr14Co13Mo4 martensitic stainless steel needs to be carburized to improve surface performance. Low-pressure carburization has the benefit of having oxidation-free production and being ecofriendly. However, compared with the low-pressure carburization of the low-alloy steel, low-pressure carburization of the 14Cr14Co13Mo4 steel consumes more time and has a risk of network carbides. In order to promote carbon diffusion and avoid network carbide, Fe−Ni films with various thickness were electrodeposited on the 14Cr14Co13Mo4 steel prior to low-pressure carburization. The experimental results show that, under the same carburizing conditions, the surface carbon content decreases and the carburized layer increases with the increase of Fe−Ni film thickness. After the hardening heat treatment, the effective case depth (ECD) of the sample coated with 6.0 μm Fe−Ni film was increased by 29% compared to that of the uncoated sample. The morphology of carbides was a strip-shaped, discontinuous network distribution in the uncoated sample, while in the Fe−Ni coated samples, the carbides changed to a globular, uniformly dispersed distribution. The effect of Fe−Ni film on the low-pressure carburizing of steel is explained by the simulation of the carbon diffusion using DICTRA software. The Fe−Ni films reduce the steel surface carbon content in each boost stage of low-pressure carburizing and release carbon atoms in every diffusion stage. Through this adjustment mechanism, the steel surface carbon content can be reduced and carburized layer growth can be promoted

Fault Feature Extraction and Diagnosis of Rolling Bearings Based on Enhanced Complementary Empirical Mode Decomposition with Adaptive Noise and Statistical Time-Domain Features

In this paper, a novel method is proposed to enhance the accuracy of fault diagnosis for rolling bearings. First, an enhanced complementary empirical mode decomposition with adaptive noise (ECEEMDAN) method is proposed by determining two critical parameters, namely the amplitude of added white noise (AAWN) and the ensemble trails (ET). By introducing the concept of decomposition level, the optimal AAWN can be determined by judging the mutation of mutual information (MI) between adjacent intrinsic mode functions (IMFs). Furthermore, the ET is fixed at two to reduce the computational cost. This method can avoid disturbance of the spurious mode in the signal decomposition and increase computational speed. Enhanced CEEMDAN demonstrates a more significant improvement than that of the traditional CEEMDAN. Vibration signals can be decomposed into a set of IMFs using enhanced CEEMDAN. Some IMFs, which are named intrinsic information modes (IIMs), effectively reflect the vibration characteristic. The evaluated comprehensive factor (CF), which combines the shape, crest and impulse factors, as well as the kurtosis, skewness, and latitude factor, is developed to identify the IIM. CF can retain the advantage of a single factor and make up corresponding drawbacks. Experiment results, especially for the extraction of bearing fault under variable speed, illustrate the superiority of the proposed method for the fault diagnosis of rolling bearings over other methods