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A partial discharge (PD) detection system includes a PD sensor configured to sense a PD event of an electrical system and to generate a sensor signal in response to the PD event. An envelope generator is coupled to receive the sensor signal from the PD sensor. The envelope generator extracts an envelope signal from the sensor signal. A digitizer is configured to convert the envelope signal to a digital representation of the PD event.
Ultrafast nonlinear spectroscopy, which records transient wave-mixing signals in a medium, is a robust tool to access microscopic information using light sources in the radio-frequency and optical regimes. The extension of this technique towards the extreme ultraviolet (XUV) or even x-ray regimes holds the promise to uncover rich structural or dynamical information with even higher spatial or temporal resolution. In this report, we demonstrate noncollinear wave mixing between weak XUV attosecond pulses and a strong near-infrared (NIR) few-cycle laser pulse in gas phase atoms (one photon of XUV and two photons of NIR). In the noncollinear geometry the attosecond and either one or two NIR pulses interact with argon atoms. Nonlinear XUV signals are generated in a spatially resolved fashion as required by phase matching. Different transition pathways can be identified from these background-free nonlinear signals according to the specific phase-matching conditions. Time-resolved measurements of the spatially gated XUV signals reveal electronic coherences of Rydberg wave packets prepared by a single XUV photon or XUV-NIR two-photon excitation, depending on the applied pulse sequences. These measurements open possible applications of tabletop multidimensional spectroscopy to the research of dynamics associated with valence or core excitation with XUV photons.
A calibration assembly for a spectrometer is provided. The assembly includes a spectrometer having n detector elements, where each detector element is assigned a predetermined wavelength value. A first source emitting first radiation is used to calibrate the spectrometer. A device is placed in the path of the first radiation to split the first radiation into a first beam and a second beam. The assembly is configured so that one of the first and second beams travels a path-difference distance longer than the other of the first and second beams. An output signal is generated by the spectrometer when the first and second beams enter the spectrometer. The assembly includes a controller operable for processing the output signal and adapted to calculate correction factors for the respective predetermined wavelength values assigned to each detector element.
If the accidents happen in nuclear power plants (NPPs), the NPP operators identify the transients through observing the behaviors of the major parameters. However, the integrity of the instrumentation signals is not ensured under the accident circumstances and the major parameters essential in identifying the transients can rapidly change although the instruments generate accurate signals. Thus, to successfully control the accidents by taking necessary measures relatively faster, it is very important to provide the operators with the information that can identify the transients and accidents accurately. In this study, the transients of severe accidents in NPPs are identified and classified using artificial intelligence methodologies. Several transients are identified using support vector classification (SVC) and probabilistic neural network (PNN) as artificial intelligence methodologies. The used data for the transients are the simulation data using the modular accident analysis program (MAAP) code for the optimized power reactors (OPR1000s). The time-integrated values of chosen simulated sensor signals are used as the input variables for identifying the transients. As a result of this study, the proposed models identified the transients quite precisely. Therefore, the quite accurate identification of the transients indicates the excellence of these artificial intelligence methods and they will produce useful supporting information for the operators even under extreme transient circumstances in NPPs. (authors)
The possibility of detecting artificial signals transmitted by alien civilizations via collimated X-ray or gamma-ray beams is investigated. The prospect of using such beams for human communication within the solar system and beyond is also discussed. Detector responses were simulated for input signals and analyzed using relative entropy. For simplicity, all signals were assumed to use on-off keying (OOK) modulation. “Real” signals were generated by taking digital files and sequentially feeding their raw binary data to the detector simulator, the resulting normalized information content of the detector signals was plotted and compared to random noise signals. Since jpeg files contain compressed information, these served as a proxy for artificial alien signals. This showed that there is a clear difference in measured information content between natural and artificial signals, even with relatively poor time resolution in the detector causing the signals to be smeared (dead-time/rise-time intervals many times longer than the duration between signal pulses). It was found that so long as the signal lasts for at least several rise-time/dead-time intervals, the distinction between random and artificial signals is obvious. A space-telescope with high time resolution for searching for such signals is briefly described and its basic requirements are outlined.
Spectral analysis of human EEG generators in posterior cerebral regions
Propagation delay of a signal through a channel is measured by cyclically generating a first step-wave signal for transmission through the channel to a two-input logic element and a second step-wave signal with a controlled delay to the second input terminal of the logic element. The logic element determines which signal is present first at its input terminals and stores a binary signal indicative of that determination for control of the delay of the second signal which is advanced or retarded for the next cycle until both the propagation delayed first step-wave signal and the control delayed step-wave signal are coincident. The propagation delay of the channel is then determined by measuring the time between the first and second step-wave signals out of the controlled step-wave signal generator.
Resonant X-ray sum-frequency generation is calculated for excitations of the fluorine and oxygen core K-edge electrons in acetyl fluoride using real-time time-dependent density functional theory. The signal is generated by an extreme-ultraviolet followed by an Xray pulse with variable delay T. The X-ray pulse is tuned to different element-specific core excitations and used to probe the dynamics of a valence electronic wavepacket. A twodimensional signal is recorded as a function of the dispersed X-ray pulse frequency and the frequency conjugated to T, revealing the couplings between core and valence excited states. Molecular orbital decomposition of the signal shows which regions of the molecule contribute to the X-ray excitation.
A phase lock servo system is described for synchronizing the rotation of a slip ring assembly with the rotation of an air bearing table so that a minimum of torque will be imparted through cables extending from the slip ring assembly to the air bearing table as such is rotated. The system includes two servo loops. The first servo loop includes a rate gyroscope carried on the air bearing table which generates a signal through a summing junction to be compared with a signal coming from a tachometer coupled to the slip ring assembly. The corrective signal is applied to a torque motor for rotating the slip ring assembly. The second servo loop includes a pair of photo detector cells which generate pulses responsive to the rotation of the air bearing table and slip ring assembly which are fed through a phase detector, and a variable gain amplifier to the summing junction circuit to provide a fine adjustment for rotating the slip ring assembly.
The invention disclosed in this document is a brushless DC motor including a housing having an end cap secured thereto. The housing encloses a rotor, a stator and a rotationally displaceable commutation board having 5 sensors secured thereon and spaced around the periphery of the rotor. An external rotational force is applied to the commutation board for displacement of the sensors to various positions whereby varying feedback signals are generated by the positioning of the sensors relative to the rotating rotor. The commutation board is secured in a fixed position in response to feedback signals indicative of optimum sensor position being determined. The rotation of the commutation board and the securing of the sensors in the desired fixed position is accomplished without requiring the removal of the 5 end cap and with the DC motor operating.
A brushless DC motor including a housing having an end cap secured thereto. The housing encloses a rotor. a stator and a rotationally displaceable commutation board having sensors secured thereon and spaced around the periphery of the rotor. An external rotational force is applied to the commutation board for displacement of the sensors to various positions whereby varying feedback signals are generated by the positioning of the sensors relative to the rotating rotor. The commutation board is secured in a fixed position in response to feedback signals indicative of optimum sensor position being determined. The rotation of the commutation board and the securing of the sensors in the desired fixed position is accomplished without requiring the removal of the end cap and with the DC motor operating.
Smart traffic signals bring together transportation infrastructure and advance technologies to improve the mobility and efficiency of urban transportation network. Adaptive traffic signal control studies can be categorized into modeling-based approaches and learning-based approaches. In order to take advantages of these two systems, this study developed an offline-online combined Partial Observable Imitation Network for Traffic signal control (POINT). In the offline system, the traffic signal timing optimization problem was formulated as a Mixed Integer Nonlinear Programming (MINLP) given complete traffic information, i.e., second-by-second speeds and locations of all vehicles. Furthermore, the objective of MINLP is to minimize total travel delays considering individual vehicle trajectories under Connected Vehicle (CV) environment. The calculated optimal solutions under various traffic conditions were considered as the ”expert” decisions. In the online system, an imitation neural network model was developed to learn the ”expert” signal plans generated from offline system. Given partial observable traffic conditions in real time, e.g., the aggregate-level of traffic volume, the POINT model can compute the signal timing parameters in the online system. The numerical results demonstrated that the proposed method outperformed other state-of-the-art signal control method under high and unbalanced traffic demand levels in terms of reducing travel delays and queue length.
Significance Photosynthetic organisms evolved their light-harvesting antenna complexes to optimize energy transfer. It was recently shown that the redox environment can tune the mixing of electronic and vibrational states to steer energy through different pathways of a pigment–protein complex. Quantum beating signals in the spectra of pigment–protein complexes have been used to probe the excited-state dynamics within the complexes, but the microscopic dynamics that generate these signals and their role in promoting energy transfer are not fully understood. Here, we show that the redox environment that tunes energy transfer similarly tunes the quantum beating signals in the same complex. We find that the beats report on excited-state vibrations that maintain coherence through the vibronically enhanced energy transfer process.
Aircraft roll command signals are generated as a function of the Microwave Landing System based azimuth, groundtrack, groundspeed and azimuth rate or range distance input parameters. On initial approach, roll command signals are inhibited until a minimum roll command requirement is met. As the aircraft approaches the centerline of the runway, the system reverts to a linear track control.
Low-temperature ion-plasma treatment of metal workpieces may be monitored in terms of the electrical signals recorded in the circuit consisting of the plasma, the workpiece, the clamp, and ground. The electrical signals are analyzed by means of the Hurst statistic H, which provides a basic quantitative picture of the formation and modification of the signal structure in the course of machining. Experiments show that the best results (a surface layer of maximum hardness) are obtained when machining is accompanied by the generation of signals for which the Hurst statistic indicates antipersistent behavior.
Dynamic Newtonian gravitational force gradient fields generator to calibrate response of dynamic gravitational gradient sensor
Signal arrival-time estimation plays a critical role in a variety of downstream seismic analyses, including location estimation and source characterization. Any arrival-time errors propagate through subsequent data-processing results. In this article, we detail a general framework for refining estimated seismic signal arrival times along with full estimation of their associated uncertainty. Using the standard short-term average/long-term average threshold algorithm to identify a search window, we demonstrate how to refine the pick estimate through two different approaches. In both cases, new waveform realizations are generated through bootstrap algorithms to produce full a posteriori estimates of uncertainty of onset arrival time of the seismic signal. The onset arrival uncertainty estimates provide additional data-derived information from the signal and have the potential to influence seismic analysis along several fronts.
Polychlorinated biphenyls (PCBs) are classic persistent organic pollutants (POPs). Many studies have found a positive association between the progression of hepatocellular carcinoma (HCC) and PCBs exposure. However, the influence of PCBs on epithelial-mesenchymal transition (EMT) of HCC remains to be unclear. In this study, we explored the effect of PCB126 on EMT in HCC cells and its underlying mechanisms. The data showed that PCB126, exposing both Bel-7402 and SMMC-7721 cells for 48 h, promoted EMT that was demonstrated by E-cadherin repression, up-regulation of N-cadherin and vimentin, and morphological alteration. We found that signal transducer and activator of transcription 3 (STAT3)/Snail1 signaling was activated after PCB126 exposure, and the addition of STAT3 inhibitor WP1066 blocked PCB126-induced down-regulation of E-cadherin as well as up-regulation of N-cadherin and vimentin. Moreover, PCB126 exposure increased pyruvate kinase M2 (PKM2) expression and its nuclear translocation, whereas treatment with PKM2 shRNA suppressed the activation of STAT3/Snail1 signaling and the alternation of EMT-related molecules (E-cadherin, N-cadherin and vimentin). Furthermore, this study indicated estrogen receptor (ER) and aryl hydrocarbon receptor (AhR) were involved in PCB126-induced effects on PKM2, STAT3/Snail1 signaling and EMT by according treatment using ER inhibitor ICI and AhR shRNA. Notably, PCB126-increased reactive oxygen species (ROS) production via AhR is associated with activation of PKM2/STAT3/Snail1 cascades and contributes to EMT. Taken together, these results indicated that PCB126 promotes EMT process of HCC cells via PKM2/STAT3/Snail1 signaling which is mediated by ER and AhR. - Highlights: • PCB126 promotes epithelial-mesenchymal transition of HCC cells. • PCB126 regulates EMT through the activation of STAT3/Snail1 signaling. • PKM2 is responsible for PCB126-induced activation of STAT3/Snail1 signaling. • AhR-induced ROS generation regulates PKM2/STAT3/Snail1 signaling. • PCB126-induced EMT is mediated by ER and AhR.