Tribological performances of fabric self-lubricating liner with different weft densities under severe working conditions

Several woven fabric self-lubricating liners with weft densities of 200-450 root/10cm in a spacing of 50 root/10cm have been prepared to investigate the tribological performances of the liner under severe working conditions, such as low velocity and heavy load (110, 179 and 248 MPa) and high velocity and light load (9, 18 and 27 m/min) by utilizing the self-lubricating liner performance assessment tester, and MMU-5G friction and wear tester respectively. The worn surface is characterized using confocal laser scanning microscopy. The tribological results show that the fabric self-lubricating liners with different weft densities share almost the same tribological property variation tendency. Fabric tightness affects the wear rate and the stability of wear resistance of liners under severe working conditions. The overall level of friction coefficient and the wear rate of liners with different weft densities are influenced by the cold flow degree of the polymer. In addition, proper weft density improves the tribological properties of liner and a preferred weft density for the liner under severe working conditions is found to be 300-350 root/10cm

Analysis of natural organic matter via fourier transform ion cyclotron resonance mass spectrometry: an overview of recent non‐petroleum applications

Among the different techniques for mass analysis, ultra‐high‐resolution Fourier transform ion cyclotron resonance (FTICR) is the method of choice for highly complex samples, as it offers unrivaled mass accuracy and resolving power, combined with a high degree of flexibility in hybrid instruments as well as for ion activation techniques. FTICR instruments are readily embraced by the biological and biomedical research communities and applied over a wide range of applications for the analysis of biomolecules such as carbohydrates, lipids, nucleic acids, and proteins. In the field of natural organic matter (NOM) analysis, petroleum‐related studies currently dominate FTICR‐MS applications. Recently, however, there is a growing interest in developing high‐performance MS methods for the characterization of NOM samples from natural aquatic and terrestrial environments. Here, we present an overview of FTICR‐MS techniques for complex, non‐petroleum NOM samples, including data analysis and novel tandem mass spectrometry (MS/MS) methods for structural classifications. © 2020 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd.Peer Reviewe

Glance and Focus Networks for Dynamic Visual Recognition

Spatial redundancy widely exists in visual recognition tasks, i.e., discriminative features in an image or video frame usually correspond to only a subset of pixels, while the remaining regions are irrelevant to the task at hand. Therefore, static models which process all the pixels with an equal amount of computation result in considerable redundancy in terms of time and space consumption. In this paper, we formulate the image recognition problem as a sequential coarse-to-fine feature learning process, mimicking the human visual system. Specifically, the proposed Glance and Focus Network (GFNet) first extracts a quick global representation of the input image at a low resolution scale, and then strategically attends to a series of salient (small) regions to learn finer features. The sequential process naturally facilitates adaptive inference at test time, as it can be terminated once the model is sufficiently confident about its prediction, avoiding further redundant computation. It is worth noting that the problem of locating discriminant regions in our model is formulated as a reinforcement learning task, thus requiring no additional manual annotations other than classification labels. GFNet is general and flexible as it is compatible with any off-the-shelf backbone models (such as MobileNets, EfficientNets and TSM), which can be conveniently deployed as the feature extractor. Extensive experiments on a variety of image classification and video recognition tasks and with various backbone models demonstrate the remarkable efficiency of our method. For example, it reduces the average latency of the highly efficient MobileNet-V3 on an iPhone XS Max by 1.3x without sacrificing accuracy. Code and pre-trained models are available at https://github.com/blackfeather-wang/GFNet-Pytorch.Comment: Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI). Journal version of arXiv:2010.05300 (NeurIPS 2020). The first two authors contributed equall

Pressure-tunable magnetic topological phases in magnetic topological insulator MnSb4Te7

Magnetic topological insulators, possessing both magnetic order and topological electronic structure, provides an excellent platform to research unusual physical properties. Here, we report a high-pressure study on the anomalous Hall effect of magnetic TI MnSb4Te7 through transports measurements combined with first-principle theoretical calculations. We discover that the ground state of MnSb4Te7 experiences a magnetic phase transition from the A-type antiferromagnetic state to ferromagnetic dominating state at 3.78 GPa, although its crystal sustains a rhombohedral phase under high pressures up to 8 GPa. The anomalous Hall conductance {\sigma}xyA keeps around 10 {\Omega}-1 cm-1, dominated by the intrinsic mechanism even after the magnetic phase transition. The results shed light on the intriguing magnetism in MnSb4Te7 and pave the way for further studies of the relationship between topology and magnetism in topological materials.Comment: 10 pages, 4 figure

Numerical Analysis of Isothermal Elastohydrodynamic Lubrication of Cylindrical Gears with Variable Hyperbolic Circular Arc and Tooth Trace

In this study on cylindrical gears with variable hyperbolic circular arc and tooth trace (VH-CATT), the tooth surface equation of the VH-CATT gear is obtained according to the theory of meshing and differential geometry. The data points of the tooth surface are obtained using MATLAB. Then, based on the data points, a model of a VH-CATT gear pair was built using UG. Considering the geometric features, contact form, relative velocity, entrainment velocity, load, etc., an isothermal elastohydrodynamic lubrication model of a VH-CATT gear pair is established. On the basis of the existing elastohydrodynamic lubrication (EHL) theory, an isothermal EHL numerical solution of a VH-CATT gear is obtained by utilizing the multigrid method. The distribution of dimensionless pressure and film thickness under the effect of various loads and at different speeds of a VH-CATT gear pair are discussed. The results show that both loading and speed have impact on oil film pressure and oil film thickness. The second pressure peaks and the minimum film thickness of the VH-CATT gear pair are greatly affected by the entrainment velocity and load. Based on the results of the study, we can provide a guide to creating a tribological design of VH-CATT gears and provide a theoretical basis and the application of value engineering in industrial applications of VH-CATT gear pairs under high speed and heavy load