Mid-infrared Outbursts in Nearby Galaxies (MIRONG). II. Optical Spectroscopic Follow-up

Infrared echo has proven to be an effective means to discover transient accretion events of supermassive black holes (SMBHs), such as tidal disruption events (TDEs) and changing-look active galactic nuclei (AGNs), in dusty circumnuclear environments. To explore the dusty populations of SMBH transient events, we have constructed a large sample of mid-infrared outbursts in nearby galaxies (MIRONG) and performed multiwavelength observations. Here we present the results of multiepoch spectroscopic follow-up observations of a subsample of 54 objects spanning a timescale of 4 yr. Emission-line variability was detected in 22 of them with either emergence or enhancement of broad Balmer emission lines in comparison with pre-outburst spectra. Coronal lines, He ii λ4686, and Bowen line N iii λ4640 appeared in the spectra of nine, seven, and two sources, respectively. These results suggest that MIRONG is a mixed bag of different transient sources. We have tentatively classified them into different subclass according to their spectral evolution and light curves. Two sources have been in a steady high broad Hα flux up to the latest observation and might be turn-on AGNs. Broad lines faded out in the remaining sources, indicating a transient ionizing source ignited by TDE or sporadic gas accretion. Thirty-one sources do not show noticeable spectral change with respect to their pre-outburst spectra. They have a statistically redder MIR color and lower MIR luminosity of the outbursts, which are consistent with heavily obscured events.

Unified and non-ideal switch model for analysis of switching circuits

Purpose This paper aims to propose a new unified and non-ideal switch model for analysis of switching circuits. Design/methodology/approach The model has a single unified structure that includes all possible states (on, off) of the switches. The analysis with the proposed switch model requires only one topology and uses the single system equation regardless of states of switches. Moreover, to improve accuracy, the model contains the on-state resistance and capacitive effect of switches. The system equations and the states of switches are updated by control variables, used in the model. Findings There are no restrictions on circuit topology and switch connections. Switches can be internally and externally controlled. The non-ideal nature of the model allows the switch to be modeled more realistically and eliminates the drawbacks of the ideal switch concept. After modeling with the proposed switch model, a linear circuit is obtained. Two examples related to switching circuits are included into the study. The results confirm the accuracy of the model. Originality/value This paper contributes a different switch model for analysis of switching converters to the literature. The main advantage of the model is that it has a unified and non-ideal property. With the proposed switch model, the transient events, like voltage spikes and high-frequency noises, caused by inductor and capacitor elements at switching instants can be observed properly.

Automatic Detection of Slow Slip Events Using the PICCA: Application to Chilean GNSS Data

The detection of transient events related to slow earthquakes in GNSS positional time series is key to understanding seismogenic processes in subduction zones. Here, we present a novel Principal and Independent Components Correlation Analysis (PICCA) method that allows for the temporal and spatial detection of transient signals. The PICCA is based on an optimal combination of the principal (PCA) and independent component analysis (ICA) of positional time series of a GNSS network. We assume that the transient signal is mostly contained in one of the principal or independent components. To detect the transient, we applied a method where correlations between sliding windows of each PCA/ICA component and each time series are calculated, obtaining the stations affected by the slow slip event and the onset time from the resulting correlation peaks. We first tested and calibrated the method using synthetic signals from slow earthquakes of different magnitudes and durations and modelled their effect in the network of GNSS stations in Chile. Then, we analyzed three transient events related to slow earthquakes recorded in Chile, in the areas of Iquique, Copiapó, and Valparaíso. For synthetic data, a 150 days event was detected using the PCA-based method, while a 3 days event was detected using the ICA-based method. For the real data, a long-term transient was detected by PCA, while a 16 days transient was detected by ICA. It is concluded that simultaneous use of both signal separation methods (PICCA) is more effective when searching for transient events. The PCA method is more useful for long-term events, while the ICA method is better suited to recognize events of short duration. PICCA is a promising tool to detect transients of different characteristics in GNSS time series, which will be used in a next stage to generate a catalog of SSEs in Chile.

High Impedance Amplifiers for Non-Contact Bio-Potential Sensing

<p>This research develops a non-contact bio-potential sensor which can quickly respond to input transient events, is insensitive to mechanical disturbances, and operates with a bandwidth from 0.04Hz – 20kHz, with input voltage noise spectral density of 200nV / √Hz at 1kHz. Initial investigations focused on the development of an active biasing scheme to control the sensors input impedance in response to input transient events. This scheme was found to significantly reduce the settling time of the sensor; however the input impedance was degraded, and the device was sensitive to distance fluctuations. Further research was undertaken, and a circuit developed to preserve fast settling times, whilst decreasing the sensitivity to distance fluctuations. A novel amplifier biasing network was developed using a pair of junction field effect transistors (JFETs), which actively compensates for DC and low frequency interference, whilst maintaining high impedance at signal frequencies. This biasing network significantly reduces the settling time, allowing bio-potentials to be measured quickly after sensor application, and speeding up recovery when the sensor is in saturation. Further work focused on reducing the sensitivity to mechanical disturbances even further. A positive feedback path with low phase error was introduced to reduce the effective input capacitance of the sensor. Tuning of the positive feedback loop gain was achieved with coarse and fine control potentiometers, allowing very precise gains to be achieved. The sensor was found to be insensitive to distance fluctuations of up to 0.5mm at 1Hz, and up to 2mm at 5kHz. As a complement to the non-contact sensor, an amplifier to measure differential bio-potentials was developed. This differential amplifier achieved a CMRR of greater than 100dB up to 10kHz. Precise fixed gains of 20±0:02dB, 40±0:01dB, 60±0:03dB, and 80±0:3dB were achieved, with input voltage noise density of 15nV / √Hz at 1kHz.</p>

High Impedance Amplifiers for Non-Contact Bio-Potential Sensing

<p>This research develops a non-contact bio-potential sensor which can quickly respond to input transient events, is insensitive to mechanical disturbances, and operates with a bandwidth from 0.04Hz – 20kHz, with input voltage noise spectral density of 200nV / √Hz at 1kHz. Initial investigations focused on the development of an active biasing scheme to control the sensors input impedance in response to input transient events. This scheme was found to significantly reduce the settling time of the sensor; however the input impedance was degraded, and the device was sensitive to distance fluctuations. Further research was undertaken, and a circuit developed to preserve fast settling times, whilst decreasing the sensitivity to distance fluctuations. A novel amplifier biasing network was developed using a pair of junction field effect transistors (JFETs), which actively compensates for DC and low frequency interference, whilst maintaining high impedance at signal frequencies. This biasing network significantly reduces the settling time, allowing bio-potentials to be measured quickly after sensor application, and speeding up recovery when the sensor is in saturation. Further work focused on reducing the sensitivity to mechanical disturbances even further. A positive feedback path with low phase error was introduced to reduce the effective input capacitance of the sensor. Tuning of the positive feedback loop gain was achieved with coarse and fine control potentiometers, allowing very precise gains to be achieved. The sensor was found to be insensitive to distance fluctuations of up to 0.5mm at 1Hz, and up to 2mm at 5kHz. As a complement to the non-contact sensor, an amplifier to measure differential bio-potentials was developed. This differential amplifier achieved a CMRR of greater than 100dB up to 10kHz. Precise fixed gains of 20±0:02dB, 40±0:01dB, 60±0:03dB, and 80±0:3dB were achieved, with input voltage noise density of 15nV / √Hz at 1kHz.</p>

A New Clustering Approach for Automatic Oscillographic Records Segmentation

The analysis of waveforms related to transient events is an important task in power system maintenance. Currently, electric power systems are monitored by several event recorders called phasor measurement units (PMUs) which generate a large amount of data. The number of records is so high that it makes human analysis infeasible. An alternative way of solving this problem is to group events in similar classes so that it is no longer necessary to analyze all the events, but only the most representative of each class. Several automatic clustering algorithms have been proposed in the literature. Most of these algorithms use validation indexes to rank the partitioning quality and, consequently, find the optimal number of clusters. However, this issue remains open, as each index has its own performance highly dependent on the data spatial distribution. The main contribution of this paper is the development of a methodology that optimizes the results of any clustering algorithm, regardless of data spatial distribution. The proposal is to evaluate the internal correlation of each cluster to proceed or not in a new partitioning round. In summary, the traditional validation indexes will continue to be used in the cluster’s partition process, but it is the internal correlation measure of each one that will define the stopping splitting criteria. This approach was tested in a real waveforms database using the K-means algorithm with the Silhouette and also the Davies–Bouldin validation indexes. The results were compared with a specific methodology for that database and were shown to be totally consistent.

Binaural Background Noise Enhances Neuromagnetic Responses from Auditory Cortex

The presence of binaural low-level background noise has been shown to enhance the transient evoked N1 response at about 100 ms after sound onset. This increase in N1 amplitude is thought to reflect noise-mediated efferent feedback facilitation from the auditory cortex to lower auditory centers. To test this hypothesis, we recorded auditory-evoked fields using magnetoencephalography while participants were presented with binaural harmonic complex tones embedded in binaural or monaural background noise at signal-to-noise ratios of 25 dB (low noise) or 5 dB (higher noise). Half of the stimuli contained a gap in the middle of the sound. The source activities were measured in bilateral auditory cortices. The onset and gap N1 response increased with low binaural noise, but high binaural and low monaural noise did not affect the N1 amplitudes. P1 and P2 onset and gap responses were consistently attenuated by background noise, and noise level and binaural/monaural presentation showed distinct effects. Moreover, the evoked gamma synchronization was also reduced by background noise, and it showed a lateralized reduction for monaural noise. The effects of noise on the N1 amplitude follow a bell-shaped characteristic that could reflect an optimal representation of acoustic information for transient events embedded in noise.

GALAXY-TARGETED ROBOTIC TELESCOPE FOLLOW-UP OF GRAVITATIONAL WAVE EVENTS

Robotic telescopes and networks are well equipped to respond rapidly to transient events. However, the era of multi-messenger astronomy presents new challenges in the search for electromagnetic counterparts to gravitational wave events. Specifically, these sources can be distant, faint, poorly localised, and quickly decaying. Effciently searching for counterparts requires coverage of large localisation regions and/or targeted observations. This paper presents a galaxy retrieval and ranking algorithm for targeted observations, and a public web interface to retrieve ranked galaxy lists following a gravitational wave event. The website is publicly available at https://gwtool.watchertelescope.ie/.