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Rotating machines, such as pumps and compressors, are critical components in refineries and chemical plants used to transport fluids between processing units. Bearings are often the critical parts of rotating machinery, and their failure could result in economic loss and/or safety issues. Therefore, estimation of the remaining useful life (RUL) of a bearing plays an important role in reducing production losses and avoiding machine damage. Because bearing failure mechanisms tend to be complex and stochastic, data-driven RUL estimation approaches have found more applications. This work proposes a novel RUL estimation method based on systematic feature engineering and extreme learning machine (ELM). The PRONOSTIA dataset is used to demonstrate the effectiveness of the proposed method. 

We report the design and performance of a nonmagnetic drift stable optically pumped cesium magnetometer with a measured sensitivity of 35 fT at 200 s integration time and stability below 50 fT between 70 and 600 s. The sensor is based on the nonlinear magneto-optical rotation effect: in a Bell–Bloom configuration, a higher order polarization moment (alignment) of Cs atoms is created with a pump laser beam in an anti-relaxation coated Pyrex cell under vacuum, filled with Cs vapor at room temperature. The polarization plane of light passing through the cell is modulated due the precession of the atoms in an external magnetic field of 2.1 μT, used to optically determine the Larmor precession frequency. Operation is based on a sequence of optical pumping and observation of freely precessing spins at a repetition rate of 8 Hz. This free precession decay readout scheme separates optical pumping and probing and, thus, ensures a systematically highly clean measurement. Due to the residual offset of the sensor of <15 pT together with negligible crosstalk of adjacent sensors, this device is uniquely suitable for a variety of experiments in low-energy particle physics with extreme precision, here as a highly stable and systematically clean reference probe in search for time-reversal symmetry violating electric dipole moments. 

Electromigration (EM) analysis for complicated interconnects requires the solving of partial differential equations, which is expensive. In this paper, we propose a fast transient hydrostatic stress analysis for EM failure assessment for multi-segment interconnects using generative adversarial networks (GANs). Our work is inspired by the image synthesis and feature of generative deep neural networks. The stress evaluation of multi-segment interconnects, modeled by partial differential equations, can be viewed as time-varying 2D-images-to-image problem where the input is the multi-segment interconnects topology with current densities and the output is the EM stress distribution in those wire segments at the given aging time. We show that the conditional GAN can be exploited to attend the temporal dynamics for modeling the time-varying dynamic systems like stress evolution over time. The resulting algorithm, called {\it EM-GAN}, can quickly give accurate stress distribution of a general multi-segment wire tree for a given aging time, which is important for full-chip fast EM failure assessment. Our experimental results show that the EM-GAN shows 6.6\% averaged error compared to COMSOL simulation results with orders of magnitude speedup. It also delivers $8.3 \times$ speedup over state-of-the-art analytic based EM analysis solver. 

We report the phase-connected timing ephemeris, polarization pulse profiles, Faraday rotation measurements, and Rotating-Vector-Model (RVM) fitting results of 12 millisecond pulsars (MSPs) discovered with the Five-hundred-meter Aperture Spherical radio Telescope (FAST) in the Commensal Radio Astronomy FAST survey (CRAFTS). The timing campaigns were carried out with FAST and Arecibo over 3 yr. 11 of the 12 pulsars are in neutron star–white dwarf binary systems, with orbital periods between 2.4 and 100 d. 10 of them have spin periods, companion masses, and orbital eccentricities that are consistent with the theoretical expectations for MSP–Helium white dwarf (He WD) systems. The last binary pulsar (PSR J1912−0952) has a significantly smaller spin frequency and a smaller companion mass, the latter could be caused by a low orbital inclination for the system. Its orbital period of 29 d is well within the range of orbital periods where some MSP–He WD systems have shown anomalous eccentricities, however, the eccentricity of PSR J1912−0952 is typical of what one finds for the remaining MSP–He WD systems.