Modulation Noise Research Articles

Comparative Analysis of 16-QAM and 64-QAM Modulation in Additive White Gaussian Noise and Rayleigh Fading Channels

This reseach simulates and analyzes paramaters bit error rate (BER) of 16-QAM and 64-QAM modulation on Additive White Gaussian Noise and Rayleigh Fading channels. This research aims to determine 5G modulation with the level of data quality after the transmission process is carried out. The modulation simulation results obtained will be compared with the theoretical bit error rate (BER). The simulation results obtained from the two channel scenarios used are 16-QAM modulation reaching BER 10-4, AWGN channel only requires 15 dB Eb/N0 and for Rayleigh Fading channel it requires 38 dB Eb/N0. The BER theoretical results obtained for the 16-QAM modulation of the AWGN channel have a difference of 3 dB with the simulation results, while for the Rayleigh Fading channel it is 5 dB. Then, the simulation results of 64-QAM modulation AWGN channel to achieve BER 10-4 requires Eb/N0 of 24.6 dB, Rayleigh Fading of 47 dB. The theoretical results of BER obtained for the 64-QAM modulation of the AWGN channel have a difference of 1 dB with the simulation results, while for the Rayleigh Fading channel it is 0.5 dB. In this study, between 16-QAM and 64-QAM 5G modulation is more suitable to use 16-QAM modulation because it requires less power to achieve the desired BER 10-4.

The use of non-steady state noise interferences to counteract passive eavesdropping devices

The use of noise interference has become a common practice for information security. Recently appeared publications showing a potential possibility to use the noise radio frequency interference for information skimming by passive radio eavesdropping device. In particular, the vulnerability of the premises protected from eavesdropping devices is increased, if the radio frequency noising is switched on when confidential negotiations are being conducted. The use of radio noise waves energy for eavesdropping makes such devices invisible to nonlinear locators for listening devices if they activated only by noise signals. The paper shows that the use of non-steady state noise allows counteracting the unauthorized pickup of information. The analysis of non-steady state radio frequency noise effectiveness was carried out using the correlation receiver model. The correlation receiver has the highest sensitivity, and it works more efficiently with noise-like signals. It is shown that for counteracting the information pickup, it is necessary to use a noise, amplitude modulated by a random signal, whose spectrum coincides with a spectrum of a potential informational signal. Imposition a more powerful modulation noise to a weak informational signal makes impossible the information transfer. It is shown on the example of changing the power of a monochromatic signal while “beetle” transmits using steady-state and non-steady state noises, that due to the signal energy parametric redistribution over the non-steady-state noise modulation spectrum, the power of monochromatic signal is reduced by more than 10 dB compared to the transmission of the same signal using a steady-state noise. It can be concluded that the use of non-steady state noise signals for radio frequency suppression makes impossible their use for passive eavesdropping devices operation.

Image quality and radiologists\u2019 subjective acceptance using model-based iterative and deep learning reconstructions as adjuncts to ultrahigh-resolution CT in low-dose contrast-enhanced abdominopelvic CT: phantom and clinical pilot studies

PurposeIn contrast-enhanced abdominopelvic CT (CE-APCT) for oncologic follow-up, ultrahigh-resolution CT (UHRCT) may improve depiction of fine lesions and low-dose scans are desirable for minimizing the potential adverse effects by ionizing radiation. We compared image quality and radiologists’ acceptance of model-based iterative (MBIR) and deep learning (DLR) reconstructions of low-dose CE-APCT by UHRCT.MethodsUsing our high-resolution (matrix size: 1024) and low-dose (tube voltage 100 kV; noise index: 20–40 HU) protocol, we scanned phantoms to compare the modulation transfer function and noise power spectrum between MBIR and DLR and assessed findings in 36 consecutive patients who underwent CE-APCT (noise index: 35 HU; mean CTDIvol: 4.2 ± 1.6 mGy) by UHRCT. We used paired t-test to compare objective noise and contrast-to-noise ratio (CNR) and Wilcoxon signed-rank test to compare radiologists’ subjective acceptance regarding noise, image texture and appearance, and diagnostic confidence between MBIR and DLR using our routine protocol (matrix size: 512; tube voltage: 120 kV; noise index: 15 HU) for reference.ResultsPhantom studies demonstrated higher spatial resolution and lower low-frequency noise by DLR than MBIR at equal doses. Clinical studies indicated significantly worse objective noise, CNR, and subjective noise by DLR than MBIR, but other subjective characteristics were better (P < 0.001 for all). Compared with the routine protocol, subjective noise was similar or better by DLR, and other subjective characteristics were similar or worse by MBIR.ConclusionImage quality, except regarding noise characteristics, and acceptance by radiologists were better by DLR than MBIR in low-dose CE-APCT by UHRCT.Graphical abstract

A Hollow-Core Photonic-Crystal Fiber-Optic Gyroscope Based on a Parallel Double-Ring Resonator.

A novel system structure of resonant fiber optical gyroscope using a parallel double hollow-core photonic crystal fiber ring resonator is proposed, which employs the double closed loop and reciprocal modulation–demodulation technique to solve the problem of the length mismatch between rings. This structure can suppress the residual amplitude modulation noise and laser frequency noise, essentially eliminating the influence of the Rayleigh backscattering noise and dramatically reduce the Kerr-effect-induced drift by three orders of magnitude. Thanks to its excellent noise suppression effect, the sensitivity of this novel system can approach the shot-noise-limited theoretical value of 8.94 × 10−7 rad/s assuming the length of the fiber ring resonator is 10 m.

Digital in-service relative time delay estimation for SDM self-homodyne coherent systems.

For space division multiplexing self-homodyne coherent systems, we propose a novel digital in-service relative time delay (RTD) estimation method without any additional optoelectronic device. Taking advantage of the frequency-domain periodicity of the colored frequency modulation noise, we manage to find the peak with location reflecting the RTD in its autocorrelation function (ACF). The peak to average ratio is further enhanced by leveraging a low-pass differential finite impulse response filter for robust identification. By simulations, the method is validated to be feasible for various linewidths, formats (16QAM, 32QAM and 64QAM), and links up to 80 km. Particularly, it is proved to be inherently compatible with large-linewidth low-cost lasers for the 10-km link. Also, for a low-complexity implementation, we discuss the way to reduce the number of points used to calculate the ACF while maintaining the same dynamic range. Furthermore, we demonstrate a 50-GBaud 16-QAM experiment to investigate its performances. With received optical power varying from -11 dBm to -17 dBm, 216 points are sufficient to provide an estimation accuracy of standard deviation (STD) less than 0.089 ns for the RTD range of [2.6, 491.0 ns]. The STD can be lowered to 0.036 ns by adopting 218 points. Especially, at -11-dBm ROP, the highest performance has been achieved with an accuracy smaller than the symbol period (0.018-ns STD) and a RTD range of [1.5, 491.0 ns].

Double-pass consistency for amplitude- and frequency-modulation detection in normal-hearing listeners.

Amplitude modulation (AM) and frequency modulation (FM) provide crucial auditory information. If FM is encoded as AM, it should be possible to give a unified account of AM and FM perception both in terms of response consistency and performance. These two aspects of behavior were estimated for normal-hearing participants using a constant-stimuli, forced-choice detection task repeated twice with the same stimuli (double pass). Sinusoidal AM or FM with rates of 2 or 20 Hz were applied to a 500-Hz pure-tone carrier and presented at detection threshold. All stimuli were masked by a modulation noise. Percent agreement of responses across passes and percent-correct detection for the two passes were used to estimate consistency and performance, respectively. These data were simulated using a model implementing peripheral processes, a central modulation filterbank, an additive internal noise, and a template-matching device. Different levels of internal noise were required to reproduce AM and FM data, but a single level could account for the 2- and 20-Hz AM data. As for FM, two levels of internal noise were needed to account for detection at slow and fast rates. Finally, the level of internal noise yielding best predictions increased with the level of the modulation-noise masker. Overall, these results suggest that different sources of internal variability are involved for AM and FM detection at low audio frequencies.

Deep residual learning-based cognitive model for detection and classification of transmitted signal patterns in 5G smart city networks

Primary user (PU) signal detection or classification is a critical component of cognitive radio (CR) related wireless communication applications. In CR, the PU detection methods are mostly based on statistical models, and their detection performance heavily relies on the accuracy of assumed models. In this paper, we design a novel detector, dubbed as PU-Net, that dynamically learns the PU activity patterns in a cognitive 5G smart city, where a network of unmanned aerial vehicles (UAVs) is deployed as flying base stations to serve the Internet-of-Things (IoT) users. Unlike the traditional schemes, the PU-Net is free from signal-noise model assumptions and is leveraged through deep residual learning integrated with atrous spatial pyramid pooling (ASPP) to sense the PU's transmitted signal patterns in the network. The PU-Net detects and classifies the active and idle PU states by exploiting the multilevel spatial-temporal features in the signal and noise frames. The proposed model is trained using locally synthesized Rayleigh channel-impaired data with large variability of modulated signals and different noise floor regimes. Additionally, the PU-Net model is blind-tested and evaluated on real-world over-the-air signals and with variable-length frames and varying channel effects at secondary users (SUs). With extensive experiments, it is shown that PU-Net outperforms other benchmark detectors, obtaining an accuracy of 0.9974, with 0.9978 recall and 0.9970 precision in detecting and classifying the PU transmitted signal patterns. Correspondingly, the proposed PU-Net can be adopted for IoT/UAV-assisted communication systems in optimizing spectrum efficiency and resolving the coexistence issues in 5G and beyond networks.

Enhancing the Efficacy of Noise Modulation for SBS Suppression in High Power, Narrow Linewidth Fiber Lasers by the Incorporation of Sinusoidal Modulation

Power scaling of continuous-wave, narrow-linewidth fiber lasers are limited by the onset of stimulated Brillouin scattering (SBS) which manifests at threshold as potentially damaging, peak power, backward propagating pulses. While several SBS mitigation techniques exist, optical linewidth broadening through external phase modulation using white noise is predominantly used for its simplicity. But the broadened line-shape is non-ideal and has a slow roll-off resulting in increased SBS seeding from reflections and hence limited power scaling. With better line-shape control, higher output powers can be achieved. In this work, we propose a simple and effective technique to improve the SBS suppression of these high power, narrow linewidth, noise broadened systems, by the addition of a sinusoidal modulation in cascade. The dual modulation results in an improved line-shape with a relatively flat topped-center and fast roll-off when compared to pure noise modulation at similar root-mean-square (RMS) linewidths. Using a multi-stage fully polarization maintaining, kW-class amplifier, we demonstrate >2.3X enhancement in SBS limited output power when compared to the pure noise modulated case at ∼7.3 GHz and >1.029 kW output power at ∼10.4 GHz RMS linewidth.

Amplitude modulation of background noise varies listeners’ spectral weights for sentence recognition

The band importance function that captures how the spectral weight varies across frequencies was estimated for sentence recognition in noises with steady-state or fluctuating temporal envelopes from ten young, normal-hearing adult listeners. The test sentences were from either the IEEE or AzBio corpus. The background noise was a 12-talker babble, either unmodulated or amplitude-modulated using an 8-Hz sinusoidal modulator. In the co-located condition, the noise was presented from the same loudspeaker as the target sentence in front of the listener (0°). In the spatially separated condition, the noise was presented simultaneously from two loudspeakers on either side of the target speaker (±90°). The co-located condition was replicated in a separated test session, at least one week from the first session, which demonstrated the reliability of the estimated band importance functions. With the introduction of amplitude modulation, an increase of spectral weight in the 2-kHz frequency band and a decrease of weight in the 250-Hz band was observed, which was consistent for the two test materials and for the two spatial placements of the noise. Compared to amplitude modulation, spatial separation between the target and noise had a less influence on the band importance function.

Prediction of speech recognition in background noise and competing speech from suprathreshold auditory and cognitive measures

Previous studies have struggled to identify measures beyond the audiogram to reliably predict speech-in-noise scores. This may owe to: (i) different mechanisms mediate performance depending on materials and task; and (ii) effects are not reproducible. Here, 38 listeners with normal/near-normal audiograms completed batteries of temporal auditory and cognitive tests, and speech recognition (“Theo-Victor-Michael” test) in speech-shaped noise (SSN), speech-envelope modulated noise (envSSN), one (1T) and two (2T) competing talkers. A two-stage Bayesian modeling approach was employed. In Stage 1, speech scores were corrected for target-word frequency/neighborhood density, psychometric function parameters were extracted from temporal tests, and cognitive measures were reduced to three composite variables. Stage 2 then applied Gaussian process models to predict speech scores from temporal and cognitive measures. Leave-one-out cross-validation and model stacking determined the best combination of predictive models. Performance in SSN/envSSN was best predicted by temporal envelope measures (forward masking, gap duration discrimination), while performance in 1T was best predicted by cognitive measures (executive function, processing speed). Temporal fine structure measures (frequency-modulation, interaural-phase-difference detection) predicted the number of 1T distractor responses. All models failed on 2T. These results show that prediction of speech-in-noise scores from suprathreshold “process” measures is highly task dependent.

Effects of word frequency and phonological neighborhood density on speech recognition in background noise and competing speech

Clinical speech-in-noise tests typically use materials without contextual constraint or balanced for linguistic properties like word/phoneme frequency. However, real-world linguistic context effects can be substantial and vary by listener and scenario. Here, 38 participants completed the Theo-Victor-Michael (TVM) speech test in four types of background: speech shaped noise (SSN), speech-envelope modulated noise (envSSN), one competing talker (1T), and two competing talkers (2T) (Helfer and Freyman, 2009). The TVM is a matrix test using keywords from a corpus of one- and two- syllable nouns that vary considerably in word frequency (FREQ) and phonological neighborhood density (DENS). Bayesian logistic regression was used to estimate the effects of FREQ/DENS on TVM performance. A multinomial model was used for 1T/2T to assess reporting of target and distractor keywords. Overall, percent-correct recognition increased with increasing keyword FREQ and decreased with increasing keyword DENS. Effects were larger in SSN/envSSN than 1T/2T. Statistically significant but small effects of FREQ/DENS were observed on distractor responses in 1T/2T. Adjusting performance for FREQ/DENS substantially shifted the distribution of scores but only for SSN/envSSN. Performance in 1T/2T may be dominated by non-linguistic factors, and/or less sensitive to FREQ/DENS due to higher difficulty or linguistic competition from the background talkers. [Work supported by VA RR&D Service.]

An Algorithm for Implementing a Modulator Whose Output is Spur-Free After Nonlinear Distortion

When the accumulated zero-mean output of a digital modulator encounters a nonlinear function, nonlinearity-induced spurs can arise in the spectrum of the resulting signal. These spurs occur with both periodic and aperiodic modulator outputs, and can appear in applications such as frequency synthesis at frequencies where filtering approaches are ineffective. The mechanism at the root of these spurs is the nonlinear transformation of the cyclostationary modulator-induced phase noise. An algorithm is presented which determines modulator parameters that guarantee a spur-free spectrum after the application of a memoryless nonlinearity to the accumulated modulator noise. The algorithm takes as its input a sampled representation of the in-loop nonlinearity function, and determines a matrix of probabilities to be applied by the modulator. The algorithm can handle arbitrary nonlinear functions and relies on straightforward, synthesizable operations. Simulations demonstrate the ability of the algorithm to program a modulator such that spur-free operation is obtained for an illustrative selection of nonlinearities.

Towards biologically constrained attractor models of schizophrenia.

Alterations in neuromodulation or synaptic transmission in biophysical attractor network models, as proposed by the dominant dopaminergic and glutamatergic theories of schizophrenia, successfully mimic working memory (WM) deficits in people with schizophrenia (PSZ). Yet, multiple, often opposing alterations in memory circuits can lead to the same behavioral patterns in these network models. Here, we critically revise the computational and experimental literature that links NMDAR hypofunction to WM precision loss in PSZ. We show in network simulations that currently available experimental evidence cannot set apart competing biophysical accounts. Critical points to resolve are the effects of increases vs. decreases in E/I ratio (e.g. through NMDAR blockade) on firing rate tuning and shared noise modulations and possible concomitant deficits in short-term plasticity. We argue that these concerted experimental and computational efforts will lead to a better understanding of the neurobiology underlying cognitive deficits in PSZ.

Sparsely Distributed, Pre-synaptic Kv3 K+ Channels Control Spontaneous Firing and Cross-Unit Synchrony via the Regulation of Synaptic Noise in an Auditory Brainstem Circuit.

Spontaneous subthreshold activity in the central nervous system is fundamental to information processing and transmission, as it amplifies and optimizes sub-threshold signals, thereby improving action potential initiation and maintaining reliable firing. This form of spontaneous activity, which is frequently considered noise, is particularly important at auditory synapses where acoustic information is encoded by rapid and temporally precise firing rates. In contrast, when present in excess, this form of noise becomes detrimental to acoustic information as it contributes to the generation and maintenance of auditory disorders such as tinnitus. The most prominent contribution to subthreshold noise is spontaneous synaptic transmission (synaptic noise). Although numerous studies have examined the role of synaptic noise on single cell excitability, little is known about its pre-synaptic modulation owing in part to the difficulties of combining noise modulation with monitoring synaptic release. Here we study synaptic noise in the auditory brainstem dorsal cochlear nucleus (DCN) of mice and show that pharmacological potentiation of Kv3 K+ currents reduces the level of synaptic bombardment onto DCN principal fusiform cells. Using a transgenic mouse line (SyG37) expressing SyGCaMP2-mCherry, a calcium sensor that targets pre-synaptic terminals, we show that positive Kv3 K+ current modulation decreases calcium influx in a fifth of pre-synaptic boutons. Furthermore, while maintaining rapid and precise spike timing, positive Kv3 K+ current modulation increases the synchronization of local circuit neurons by reducing spontaneous activity. In conclusion, our study identifies a unique pre-synaptic mechanism which reduces synaptic noise at auditory synapses and contributes to the coherent activation of neurons in a local auditory brainstem circuit. This form of modulation highlights a new therapeutic target, namely the pre-synaptic bouton, for ameliorating the effects of hearing disorders which are dependent on aberrant spontaneous activity within the central auditory system.

Longitudinal auditory pathophysiology following mild blast-induced trauma.

Blast-induced hearing difficulties affect thousands of veterans and civilians. The long-term impact of even a mild blast exposure on the central auditory system is hypothesized to contribute to lasting behavioral complaints associated with mild blast traumatic brain injury (bTBI). Although recovery from mild blast has been studied separately over brief or long time windows, few, if any, studies have investigated recovery longitudinally over short-term and longer-term (months) time windows. Specifically, many peripheral measures of auditory function either recover or exhibit subclinical deficits, masking deficits in processing complex, real-world stimuli that may recover differently. Thus, examining the acute time course and pattern of neurophysiological impairment using appropriate stimuli is critical to better understanding and intervening in bTBI-induced auditory system impairments. Here, we compared auditory brainstem response, middle-latency auditory-evoked potentials, and envelope following responses. Stimuli were clicks, tone pips, amplitude-modulated tones in quiet and in noise, and speech-like stimuli (iterated rippled noise pitch contours) in adult male rats subjected to mild blast and sham exposure over the course of 2 mo. We found that blast animals demonstrated drastic threshold increases and auditory transmission deficits immediately after blast exposure, followed by substantial recovery during the window of 7-14 days postblast, although with some deficits remaining even after 2 mo. Challenging conditions and speech-like stimuli can better elucidate mild bTBI-induced auditory deficit during this period. Our results suggest multiphasic recovery and therefore potentially different time windows for treatment, and deficits can be best observed using a small battery of sound stimuli.NEW & NOTEWORTHY Few studies on blast-induced hearing deficits go beyond simple sounds and sparsely track postexposure. Therefore, the recovery arc for potential therapies and real-world listening is poorly understood. Evidence suggested multiple recovery phases over 2 mo postexposure. Hearing thresholds largely recovered within 14 days and partially explained recovery. However, midlatency responses, responses to amplitude modulation in noise, and speech-like pitch sweeps exhibited extended changes, implying persistent central auditory deficits and the importance of subclinical threshold shifts.

Evaluation of a Laser Altimeter using the Pseudo-Random Noise Modulation Technique for Apophis Mission

Apophis is a near-Earth object with a diameter of approximately 340 m, which will come closer to the Earth than a geostationary orbit in 2029, offering a unique opportunity for characterizing the object during the upcoming encounter. Therefore, Korea Astronomy and Space Science Institute has a plan to propose a space mission to explore the Apophis asteroid using scientific instruments such as a laser altimeter. In this study, we evaluate the performance metrics of a laser altimeter using a pseudorandom noise modulation technique for the Apophis mission, in terms of detection probability and ranging accuracy. The closed-form expression of detection probability is provided using the cross correlation between the received pulse trains and pseudo-random binary sequence. And the new ranging accuracy model using Gaussian error propagation is also derived by considering the sampling rate. The operation range is significantly limited by thermal noise rather than background noise, owing to not only the low power laser but also the avalanche photodiode in the analog mode operation. However, it is demonstrated from the numerical simulation that the laser altimeter can achieve the ranging performance required for a proximity operation mode, which employs commercially available components onboard CubeSat-scale satellites for optical communications.

Glimpsing keywords across sentences in noise: A microstructural analysis of acoustic, lexical, and listener factors.

This study investigated how acoustic and lexical word-level factors and listener-level factors of auditory thresholds and cognitive-linguistic processing contribute to the microstructure of sentence recognition in unmodulated and speech-modulated noise. The modulation depth of the modulated masker was changed by expanding and compressing the temporal envelope to control glimpsing opportunities. Younger adults with normal hearing (YNH) and older adults with normal and impaired hearing were tested. A second group of YNH was tested under acoustically identical conditions to the hearing-impaired group, who received spectral shaping. For all of the groups, speech recognition declined and masking release increased for later keywords in the sentence, which is consistent with the word position decreases in the signal-to-noise ratio. The acoustic glimpse proportion and lexical word frequency of individual keywords predicted recognition under different noise conditions. For the older adults, better auditory thresholds and better working memory abilities facilitated sentence recognition. Vocabulary knowledge contributed more to sentence recognition for younger than for older adults. These results demonstrate that acoustic and lexical factors contribute to the recognition of individual words within a sentence, but relative contributions vary based on the noise modulation characteristics. Taken together, acoustic, lexical, and listener factors contribute to how individuals recognize keywords during sentences.

DNA repair amplifies transcriptional noise

Systems Biology The potential role of “noise,” or stochastic variations in rates of gene expression, remains to be elucidated. Desai et al. used screens to identify a compound, 5′-iodo-2′-deoxyuridine (IdU), that increased gene expression noise in mouse embryonic stem cells in culture without changing the overall rate of transcription of most genes. They propose a model by which the thymidine analog IdU promotes binding of the base excision repair protein AP endonuclease to DNA, thereby inducing helical distortion of DNA and modulating transcriptional bursting. Such modulation of noise enhanced reprogramming of the embryonic stem cells. Thus, variation in gene expression noise could influence developmental or disease processes. Science , abc6506, this issue p. [eabc6506][1] [1]: /lookup/doi/10.1126/science.abc6506

Quantitative control of noise in mammalian gene expression by dynamic histone regulation.

Fluctuation ('noise') in gene expression is critical for mammalian cellular processes. Numerous mechanisms contribute to its origins, yet the mechanisms behind large fluctuations that are induced by single transcriptional activators remain elusive. Here, we probed putative mechanisms by studying the dynamic regulation of transcriptional activator binding, histone regulator inhibitors, chromatin accessibility, and levels of mRNAs and proteins in single cells. Using a light-induced expression system, we showed that the transcriptional activator could form an interplay with dual functional co-activator/histone acetyltransferases CBP/p300. This interplay resulted in substantial heterogeneity in H3K27ac, chromatin accessibility, and transcription. Simultaneous attenuation of CBP/p300 and HDAC4/5 reduced heterogeneity in the expression of endogenous genes, suggesting that this mechanism is universal. We further found that the noise was reduced by pulse-wide modulation of transcriptional activator binding possibly as a result of alternating the epigenetic states. Our findings suggest a mechanism for the modulation of noise in synthetic and endogenous gene expression systems.

Characterizing microRNA-mediated modulation of gene expression noise and its effect on synthetic gene circuits.

MicroRNAs (miRNAs) have been shown to modulate gene expression noise, but less is known about how miRNAs with different properties may regulate noise differently. Here, we investigate the role of competing RNAs and the composition of miRNA response elements (MREs) in modulating noise. We find that weak competing RNAs could introduce lower noise than strong competing RNAs. In comparison with a single MRE, both repetitive and composite MREs can reduce the noise at low expression, but repetitive MREs can elevate the noise remarkably at high expression. We further observed the behavior of a synthetic cell-type classifier with miRNAs as inputs and find that miRNAs and MREs that could introduce higher noise tend to enhance cell state transition. These results provide a systematic and quantitative understanding of the function of miRNAs in controlling gene expression noise and the utilization of miRNAs to modulate the behavior of synthetic gene circuits.