Power Transformer Voiceprint Operation State Monitoring Considering Sample Unbalance

The voiceprint characteristics of transformers are closely related to the operating conditions, but there is currently a lack of effective research on the voiceprint characteristics of transformers during operation. First of all, this article collects three operating conditions of load, light load, and no load on the basis of the transformer voiceprint signal acquisition platform. Secondly, in view of the characteristics of the transformer’s voiceprint, the 50Hz frequency multiplier component amplitude is extracted to form a feature vector, which solves the problem of low utilization rate of common feature extraction information. Finally, in view of the problem of transformer voiceprint failure and sample imbalance caused by fewer abnormal samples, a pattern recognition based on the RUSBoost algorithm is proposed. The algorithm has good recognition accuracy and applicability for transformer voiceprint samples with imbalance problems. The research results provide effective support for the monitoring and identification of the mechanical condition of transformers with sample unbalanced voiceprints, and the analysis of the operating conditions can effectively eliminate the errors that may be caused by their own different operating conditions.

Filtering Properties of Hodgkin-Huxley Neuron to Different Time-Scale Signals

Neuron can be excited and inhibited by filtered signals. The filtering properties of neural networks have a huge impact on memory, learning, and disease. In this paper, the filtering properties of Hodgkin-Huxley neuron to different time-scale signals are investigated. It is found that the neuronal filtering property depends on the locking relationship between the signal's frequency band and the natural frequency of neuron. The natural firing frequency is a combination of the fundamental component and the various level harmonic components. The response of neuron to the filtered signal is related to the amplitude of the harmonic components. Neuron responds better to the low-frequency signals than the high-frequency signals because of the reduction in the harmonic component amplitude. The filtering ability of neuron can be modulated by the excitation level, and is stronger around the excitation threshold. Our results might provide novel insights into the filtering properties of neural networks and guide the construction of artificial neural networks.

Inhibitory control elicited by physical activity and inactivity stimuli: an EEG study

The theory of effort minimization in physical activity (TEMPA) argues that individuals have an automatic attraction toward effort minimization. To engage in a physically active behavior, this automatic attraction needs to be overridden by controlled processes. However, direct evidence showing that inhibitory control is required to avoid effort minimization is lacking. Here, we used go/no-go tasks and electroencephalography (EEG) to assess the neural correlates of inhibitory control associated with visual stimuli depicting physical inactivity, physical activity, or that were neutral in 50 healthy young adults. The N2 event-related potential (ERP) component amplitude was used as a physiological index of inhibitory control. Results showed significant two-way interactions between the type of trials (i.e., go vs. no-go trials) and the type of stimuli on N2, revealing a significantly more pronounced no-go effect (i.e., higher N2 in no-go relative to go trials) for neutral and physical inactivity stimuli compared with physical activity stimuli. Simple tests further revealed that N2 amplitude was more negative in no-go than go trials for neutral stimuli (b=-.91 µV, 95%CI=-1.42 to -.40 µV, p<.001) and for stimuli depicting physical inactivity (b=-.58 µV, 95%CI=-1.08 to -.08 µV, p=.025). By contrast, we found no evidence of significant differences in N2 amplitude between no-go and go trials for stimuli depicting physical activity (b=.20 µV, 95%CI=-1.08 to –.08 µV, p=.445). These findings provide evidence that inhibiting responses to physical inactivity stimuli requires significantly higher inhibitory control than inhibiting responses to physical activity stimuli. The study pre-registration form can be found at https://doi.org/10.17605/OSF.IO/RKYHB.

Comparing Methods and Defining Practical Requirements for Extracting Harmonic Tidal Components from Groundwater Level Measurements

The groundwater pressure response to the ubiquitous Earth and atmospheric tides provides a largely untapped opportunity to passively characterize and quantify subsurface hydro-geomechanical properties. However, this requires reliable extraction of closely spaced harmonic components with relatively subtle amplitudes but well-known tidal periods from noisy measurements. The minimum requirements for the suitability of existing groundwater records for analysis are unknown. This work systematically tests and compares the ability of two common signal processing methods, the discrete Fourier transform (DFT) and harmonic least squares (HALS), to extract harmonic component properties. First, realistic conditions are simulated by analyzing a large number of synthetic data sets with variable sampling frequencies, record durations, sensor resolutions, noise levels and data gaps. Second, a model of two real-world data sets with different characteristics is validated. The results reveal that HALS outperforms the DFT in all aspects, including the ability to handle data gaps. While there is a clear trade-off between sampling frequency and record duration, sampling rates should not be less than six samples per day and records should not be shorter than 20 days when simultaneously extracting tidal constituents. The accuracy of detection is degraded by increasing noise levels and decreasing sensor resolution. However, a resolution of the same magnitude as the expected component amplitude is sufficient in the absence of excessive noise. The results provide a practical framework to determine the suitability of existing groundwater level records and can optimize future groundwater monitoring strategies to improve passive characterization using tidal signatures.

Sigmoidal NMFD: Convolutional NMF with Saturating Activations for Drum Mixture Decomposition

In many types of music, percussion plays an essential role to establish the rhythm and the groove of the music. Algorithms that can decompose the percussive signal into its constituent components would therefore be very useful, as they would enable many analytical and creative applications. This paper describes a method for the unsupervised decomposition of percussive recordings, building on the non-negative matrix factor deconvolution (NMFD) algorithm. Given a percussive music recording, NMFD discovers a dictionary of time-varying spectral templates and corresponding activation functions, representing its constituent sounds and their positions in the mix. We observe, however, that the activation functions discovered using NMFD do not show the expected impulse-like behavior for percussive instruments. We therefore enforce this behavior by specifying that the activations should take on binary values: either an instrument is hit, or it is not. To this end, we rewrite the activations as the output of a sigmoidal function, multiplied with a per-component amplitude factor. We furthermore define a regularization term that biases the decomposition to solutions with saturated activations, leading to the desired binary behavior. We evaluate several optimization strategies and techniques that are designed to avoid poor local minima. We show that incentivizing the activations to be binary indeed leads to the desired impulse-like behavior, and that the resulting components are better separated, leading to more interpretable decompositions.

Stop! Graphic Health Warnings Enhance Inhibitory Control in Adolescents: An ERP Study

Introduction The majority of smokers begin consumption in adolescence and the earlier initiation of cigarette smoking is associated with a greater likelihood of cigarette dependence. Graphic health warnings (GHW) are one of the most used strategies to communicate the consequences of cigarette smoking, but little is known about their ability to increase inhibitory control and thus prevent consumption. The objective of the present study was to evaluate the effects of different sizes of GHWs on inhibitory control in adolescents. We hypothesized that GHWs promote inhibitory control, and increasing GHW size, enhance inhibitory control. Methods Fifty-nine participants completed a Go/No-Go task during electroencephalographic recording. The No-Go stimuli were pictures of cigarette packs without GHWs, and cigarette packs with GHWs that covered 30% or 60% of the front (main side) of the pack. The event-related potential N200 component and behavioral measures in the Go/No-Go task were analyzed. Results Separate mixed-model ANOVAs were used for N200 component (amplitude and latency) and for behavioral data. The GHWs increased the amplitude of the N200 potential, especially GHWs that covered 60% of the front of the pack. The behavioral data showed that GHWs that covered 60% of the front of the pack generated higher a percentage of accuracy in No-Go trials (i.e., fewer commission errors). Conclusions These results suggest that GHWs increase inhibitory control in adolescents, especially when the GHWs cover 60% of the front of the cigarette pack.

Intensity and time series of extreme solar-terrestrial storm in 1946 March

ABSTRACT Major solar eruptions occasionally cause magnetic superstorms on the Earth. Despite their serious consequences, the low frequency of their occurrence provides us with only limited cases through modern instrumental observations, and the intensities of historical storms before the coverage of the Dst index have been only sporadically estimated. Herein, we examine a solar-terrestrial storm that occurred in 1946 March and quantitatively evaluate its parameters. During the ascending phase of Solar Cycle 18, two moderate sunspot groups caused a major flare. The H α flaring area was recorded to be ≥600–1200 millionths of solar hemisphere, suggesting that this was an M- or X-class flare in soft X-ray intensity. Upon this eruption, a rapid interplanetary coronal mass ejection (ICME) with an average speed of ≈1590 km s−1 was launched. Based on measurements in four known mid-latitude and relatively complete magnetograms, the arrival of this extreme ICME caused a magnetic superstorm, which caused an initial phase with the H-component amplitude of ≥80 nT, followed by a main phase whose intensity was reconstructed as ≤−512 nT using most negative Dst* estimates. Meanwhile, the equatorial boundary of the auroral oval extended down to ≤41${^{\circ}_{.}}$8 in invariant latitude and formed a corona aurora in Watheroo, Australia. Interestingly, during this magnetic superstorm, larger magnetic disturbances were recorded at dusk and near the dip equator on the dayside. Its cause may be associated with a strong westward equatorial electrojet and field-aligned current, in addition to the contribution from the storm-time ring current.

Dissociating activation and integration of discourse referents: evidence from ERPs and oscillations

A key challenge in understanding stories and conversations is the comprehension of ‘anaphora’, words that refer back to previously mentioned words or concepts (‘antecedents’). In psycholinguistic theories, anaphor comprehension involves the initial activation of the antecedent and its subsequent integration into the unfolding representation of the narrated event. A recent proposal suggests that these processes draw upon the brain’s recognition memory and language networks, respectively, and may be dissociable in patterns of neural oscillatory synchronization (Nieuwland & Martin, 2017). We addressed this proposal in an electroencephalogram (EEG) study with pre-registered data acquisition and analyses, using event-related potentials (ERPs) and neural oscillations. Dutch participants read two-sentence mini stories containing proper names, which were repeated or new (ease of activation) and coherent or incoherent with the preceding discourse (ease of integration). Repeated names elicited lower N400 and Late Positive Component amplitude than new names, and also an increase in theta-band (4-7 Hz) synchronization, which was largest around 240-450 ms after name onset. Discourse-coherent proper names elicited an increase in gamma-band (60-80 Hz) synchronization compared to discourse-incoherent names. This effect was largest around 690-1000 ms after name onset and was localized to the left frontal cortex. We argue that the initial activation and subsequent discourse-level integration of referents can be dissociated with event-related EEG activity, and are associated with respectively theta- and gamma-band activity. These findings further establish the link between memory and language through neural oscillations.

Effects of Repeated Concussions and Sex on Early Processing of Emotional Facial Expressions as Revealed by Electrophysiology

Objectives: Concussions affect the processing of emotional stimuli. This study aimed to investigate how sex interacts with concussion effects on early event-related brain potentials (ERP) measures (P1, N1) of emotional facial expressions (EFE) processing in asymptomatic, multi-concussion athletes during an EFE identification task. Methods: Forty control athletes (20 females and 20 males) and 43 multi-concussed athletes (22 females and 21 males), recruited more than 3 months after their last concussion, were tested. Participants completed the Beck Depression Inventory II, the Beck Anxiety Inventory, the Post-Concussion Symptom Scale, and an Emotional Facial Expression Identification Task. Pictures of male and female faces expressing neutral, angry, and happy emotions were randomly presented and the emotion depicted had to be identified as fast as possible during EEG acquisition. Results: Relative to controls, concussed athletes of both sex exhibited a significant suppression of P1 amplitude recorded from the dominant right hemisphere while performing the emotional face expression identification task. The present study also highlighted a sex-specific suppression of the N1 component amplitude after concussion which affected male athletes. Conclusions: These findings suggest that repeated concussions alter the typical pattern of right-hemisphere response dominance to EFE in early stages of EFE processing and that the neurophysiological mechanisms underlying the processing of emotional stimuli are distinctively affected across sex. (JINS, 2018, 24, 1–11)

Levetiracetam and Rufinamide are effective at supressing spike and wave seizure activity in an in vitro model of absence epilepsy

Spike-and-wave discharges (SpW) are seen in absence-type epilepsies. They are heterogeneous in terms of their clinical burden and their electrographic signature, which is used to classify different types of absence seizures; typical absence, in which SpW frequency is 3-4Hz and atypical absence, which shows a slower 1-2Hz frequency. Treatment of SpW varies dependent upon the syndrome, but both Valproic Acid (VPA) and Ethosuximide (ESM) are shown to be effective in controlling typical absence seizures. Other anti-epileptic’s (AED’s), Levetiracetam (LEV) and Rufinamide (RUF), have shown promise in treating absence epilepsies and their associated syndromes. Here we examine the efficacy of these AED’s on an in vitro model of SpW.Both LEV and RUF show an effective reduction in both the number of SpW events and the spike component amplitude; VPA shows no effect, whilst ESM enhances the spike amplitude. Phenytoin exacerbates the SpW activity, increasing both the number of SpW, amplitude of the SpW and the number of spikes within each event. These data suggest that both LEV and RUF could be effective in the treatment of absence-type epilepsies. They also suggest this model could be an effective tool to test other AED’s aimed at treating atypical absence syndromes.