Low Noise Level Research Articles

Near-Ultrasonic Transfer Function and SNR of Differential MEMS Microphones Suitable for Photoacoustics

Can ordinary Micro-Electro-Mechanical-Systems (MEMS) microphones be used for near-ultrasonic applications? Manufacturers often provide little information about the signal-to-noise ratio (SNR) in the ultrasound (US) range and, if they do, the data are often determined in a manufacturer-specific manner and are generally not comparable. Here, four different air-based microphones from three different manufacturers are compared with respect to their transfer functions and noise floor. The deconvolution of an exponential sweep and a traditional calculation of the SNR are used. The equipment and methods used are specified, which makes it easy to repeat or expand the investigation. The SNR of MEMS microphones in the near US range is mainly affected by resonance effects. These can be matched for applications with low-level signals and background noise such that the highest possible SNR can be achieved. Two MEMS microphones from Knowles performed best for the frequency range from 20 to 70 kHz; above 70 kHz, an Infineon model delivered the best performance.

Degeneration of the Grover search algorithm with depolarization in the oracle-box wires

Grover’s search algorithm and similar techniques are widely used in quantum information science. Communication lines with the so-called oracle are one of inevitable vulnerabilities of quantum search. The impact of localized dephasing and amplitude damping on Grover’s algorithm had already been discussed in recent literature. In this paper, we study the influence of depolarization in the oracle-box wires on the search process. It is shown that even low level of noise is sufficient to degenerate Grover’s algorithm. Complementarity relations between the relative entropy of coherence and the success probability in the presence of depolarization are studied as well.

Vibratory installation of bucket foundations

This paper presents an analysis of vibratory installation of short, large-diameter bucket foundations. Vibratory installation has numerous conventional applications, e.g. bridge caisson foundations, as well as considerable promise for offshore wind farm development. Although ideally suited to cohesionless soil profiles, vibratory driving is also feasible in clays. Desirable features of vibratory driving include its feasibility for a broad range of soil profiles, low driving stresses, rapid installation time, and low noise levels. For installation in cohesionless soils, the model employs classical soil-structure interaction theory for shallow rigid foundations. The crux of the analysis is the determination of the cyclic strain at the soil-wall interface of the bucket to determine whether it reaches the threshold cyclic strain for porewater pressure generation and strength degradation, which permits advancement of the pile into the seabed. For installation in clays, the threshold cyclic strain is typically too high to be reached by pile cyclic excitation. Nevertheless, penetration is possible if the dead weight of the pile plus the vibro-driver inertial force can overcome soil resistance. The proposed model invokes rigid body dynamic equilibrium to simulate penetration in clays.

Grazing incidence fast atom diffraction in high-pressure conditions

Grazing Incidence Fast Atom Diffraction (GIFAD) is a recent technique for characterizing surface structures and real-time monitoring of thin film growth. Up to now, GIFAD has only been used in Ultra-High-Vacuum conditions, typically in the range of 10−10 to 10−8 mbar, and has therefore only been considered for high vacuum deposition methods like Molecular Beam Epitaxy or very low-pressure Chemical Vapor Deposition (CVD). At pressures exceeding 10−6 mbar, gas phase collisions along the atom beam trajectory not only reduce the mean free path but also degrade the beam coherence length and thus potentially suppress the diffraction signal. In addition, pressures lower than 10−5 mbar are required to maintain a low noise level on the scattered particle detector. In a new configuration, we demonstrate that GIFAD can operate at pressure as high as 10−2 mbar of argon with well-contrasted diffraction patterns. This opens wide avenues for the study of surface reactivity, thin film growth in Magnetron Sputtering Deposition, where electron diffraction is inevitably perturbed by the electromagnetic fields. This High-Pressure version of GIFAD could also be extended to Reactive Pulsed Laser Deposition and many CVD variants.

A likelihood-based particle imaging filter using prior information.

Particle imaging can increase precision in proton and ion therapy. Interactions with nuclei in the imaged object increase image noise and reduce image quality, especially for multinucleon ions that can fragment, such as helium. This work proposes a particle imaging filter, referred to as the Prior Filter, based on using prior information in the form of an estimated relative stopping power (RSP) map and the principles of electromagnetic interaction, to identify particles that have undergone nuclear interaction. The particles identified as having undergone nuclear interactions are then excluded from the image reconstruction, reducing the imagenoise. The Prior Filter uses Fermi-Eyges scattering and Tschalär straggling theories to determine the likelihood that a particle only interacts electromagnetically. A threshold is then set to reject those particles with a low likelihood. The filter was evaluated and compared with a filter that estimates this likelihood based on the measured distribution of energy and scattering angle within pixels, commonly implemented as the 3σ filter. Reconstructed radiographs from simulated data of a 20-cm water cylinder and an anthropomorphic chest phantom were generated with both protons and helium ions to assess the effect of the filters on noise reduction. The simulation also allowed assessment of secondary particle removal through the particle histories. Experimental data were acquired of the Catphan CTP 404 Sensitometry phantom using the U.S. proton CT (pCT) collaboration prototype scanner. The proton and helium images were filtered with both the prior filtering method and a state-of-the-art method including an implementation of the 3σ filter. For both cases, a dE-E telescope filter, designed for this type of detector, was alsoapplied. The proton radiographs showed a small reduction in noise (1mm of water-equivalent thickness [WET]) but a larger reduction in helium radiographs (up to 5-6mm of WET) due to better secondary filtering. The proton and helium CT images reflected this, with similar noise at the center of the phantom (0.02 RSP) for the proton images and an RSP noise of 0.03 for the proposed filter and 0.06 for the 3σ filter in the helium images. Images reconstructed from data with a dose reduction, up to a factor of 9, maintained a lower noise level using the Prior Filter over the state-of-the-art filteringmethod. The proposed filter results in images with equal or reduced noise compared to those that have undergone a filtering method typical of current particle imaging studies. This work also demonstrates that the proposed filter maintains better performance against the state of the art with up to a nine-fold dose reduction.

Photonic comb-rooted synthesis of ultra-stable terahertz frequencies

Stable terahertz sources are required to advance high-precision terahertz applications such as molecular spectroscopy, terahertz radars, and wireless communications. Here, we demonstrate a photonic scheme of terahertz synthesis devised to bring the well-established feat of optical frequency comb stabilization down to the terahertz region. The source comb is stabilized to an ultra-low expansion optical cavity offering a frequency instability of 10−15 at 1-s integration. By photomixing a pair of comb lines extracted coherently from the source comb, terahertz frequencies of 0.10–1.10 THz are generated with an extremely low level of phase noise of –70 dBc/Hz at 1-Hz offset. The frequency instability measured for 0.66 THz is 4.4 × 10−15 at 1-s integration, which reduces to 5.1×10−17 at 65-s integration. Such unprecedented performance is expected to drastically improve the signal-to-noise ratio of terahertz radars, the resolving power of terahertz molecular spectroscopy, and the transmission capacity of wireless communications.

Acceptability of amplitude modulated tonal wind farm noise for sleep: a laboratory study

This study investigated self-reported sleep acceptability of wind farm noise (WFN) containing low-frequency amplitude modulated tones during evening listening tests in an acoustics and sleep laboratory. A range of 29 WFN samples with and without low-frequency amplitude modulated tonal noise were synthesised and delivered via headphones to participants who were asked to adjust the sound pressure level to the highest level they felt was acceptable for sleep. Fifty-five participants were recruited from four groups; N = 8, living <10 km from a wind farm and reporting WFN related sleep disruption; N = 18, living <10 km from a wind farm and reporting no WFN sleep disruption; N = 15, reporting road traffic noise (RTN) related sleep disruption; and N = 14 control participants living in a quiet rural area. In general, participants had normal hearing and were aged between 18 and 80 years. The WFN disturbed group overall mean acceptable sound pressure level for sleep was 33.9 dBA, which was the lowest among groups and 10.7 dBA (95% confidence interval, 7.9–13.6) lower than for the control group. There were negligible differences in acceptable levels for sleep of low-frequency amplitude modulated tonal wind farm noise compared to the reference sample, which was the same stimulus without tonality or amplitude modulation. Only the participant group reporting RTN related sleep disruption preferred lower noise levels for the amplitude modulated tonal wind farm noise compared to the reference sample (mean −1.4 dBA, 95% confidence interval: −2.7–−0.1).

Comparison of deep learning-based denoising methods in cardiac SPECT

BackgroundMyocardial perfusion SPECT (MPS) images often suffer from artefacts caused by low-count statistics. Poor-quality images can lead to misinterpretations of perfusion defects. Deep learning (DL)-based methods have been proposed to overcome the noise artefacts. The aim of this study was to investigate the differences among several DL denoising models.MethodsConvolution neural network (CNN), residual neural network (RES), UNET and conditional generative adversarial neural network (cGAN) were generated and trained using ordered subsets expectation maximization (OSEM) reconstructed MPS studies acquired with full, half, three-eighths and quarter acquisition time. All DL methods were compared against each other and also against images without DL-based denoising. Comparisons were made using half and quarter time acquisition data. The methods were evaluated in terms of noise level (coefficient of variation of counts, CoV), structural similarity index measure (SSIM) in the myocardium of normal patients and receiver operating characteristic (ROC) analysis of realistic artificial perfusion defects inserted into normal MPS scans. Total perfusion deficit scores were used as observer rating for the presence of a perfusion defect.ResultsAll the DL denoising methods tested provided statistically significantly lower noise level than OSEM without DL-based denoising with the same acquisition time. CoV of the myocardium counts with the different DL noising methods was on average 7% (CNN), 8% (RES), 7% (UNET) and 14% (cGAN) lower than with OSEM. All DL methods also outperformed full time OSEM without DL-based denoising in terms of noise level with both half and quarter acquisition time, but this difference was not statistically significant. cGAN had the lowest CoV of the DL methods at all noise levels. Image quality and polar map uniformity of DL-denoised images were also better than reduced acquisition time OSEM’s. SSIM of the reduced acquisition time OSEM was overall higher than with the DL methods. The defect detection performance of full time OSEM measured as area under the ROC curve (AUC) was on average 0.97. Half time OSEM, CNN, RES and UNET provided equal or nearly equal AUC. However, with quarter time data CNN, RES and UNET had an average AUC of 0.93, which was lower than full time OSEM’s AUC, but equal to quarter acquisition time OSEM. cGAN did not achieve the defect detection performance of the other DL methods. Its average AUC with half time data was 0.94 and 0.91 with quarter time data.ConclusionsDL-based denoising effectively improved noise level with slightly lower perfusion defect detection performance than full time reconstruction. cGAN achieved the lowest noise level, but at the same time the poorest defect detection performance among the studied DL methods.

Lowering the vertical component seismic noise-floor in the normal-mode band by frequency-dependent air-pressure corrections

SUMMARY Contrary to popular belief in seismology, the vertical component seismic background level of Earth’s body in the normal-mode band is lower than current low-noise models would indicate. With a correction of atmospherically induced disturbances the low-noise level of the vertical component of the STS-1 at Black Forest Observatory (BFO) is reduced below the Peterson low noise model (NLNM). We demonstrate this with a moving window analysis (MWA) of 10 yr of data in the normal-mode band between 0.2 and 2 mHz. The 5th percentile low-noise level for the data initially is at the level of the NLNM. We lower this by 8 dB at the frequency of 0S2 (0.31 mHz) by partially correcting the seismometer recording in the time domain for disturbances caused by mass fluctuations in the atmosphere. The disturbances are estimated by the frequency dependent ‘improved Bouguer plate model’ (IBPM, defined by asymptotic admittance αDC and notch-frequency fn) from a recording of local air-pressure. In more than 90 per cent of the time windows of the MWA the signal level is lowered when using a priori set IBPM-parameters ($\alpha _{\text{DC}}= -3.5\, {\rm nm\, s}^{-2}\, {\rm hPa}^{-1}$, $f_{\text{n}}=2.25\, {\rm mHz}$). In 50 per cent of the time windows the background level at the frequency of 0S2 is reduced by at least 6 dB. With a priori set IBPM-parameters the level of the 1st percentile is lowered by up to 16 dB for windows of $1\, {\rm d}$ length and by 13 dB for windows of $7\, {\rm d}$ length. Overall, there is little additional benefit from optimizing the IBPM-parameters per time window. If optimized per time window, the parameters show a slight annual variation which apparently compensates for systematic deviations of the dynamics of the atmosphere from the simple considerations of the IBPM-model. By application of the correction procedure and with seismic sensors of sufficiently low self-noise, the range of observations for signals from Earth’s body can be extended to below current low-noise models at frequencies below 2 mHz.

Parallel Factorization to Implement Group Analysis in Brain Networks Estimation.

When dealing with complex functional brain networks, group analysis still represents an open issue. In this paper, we investigated the potential of an innovative approach based on PARAllel FActorization (PARAFAC) for the extraction of the grand average connectivity matrices from both simulated and real datasets. The PARAFAC approach was solved using three different numbers of rank-one tensors (PAR-FACT). Synthetic data were parametrized according to different levels of three parameters: network dimension (NODES), number of observations (SAMPLE-SIZE), and noise (SWAP-CON) in order to investigate the way they affect the grand average estimation. PARAFAC was then tested on a real connectivity dataset, derived from EEG data of 17 healthy subjects performing wrist extension with left and right hand separately. Findings on both synthetic and real data revealed the potential of the PARAFAC algorithm as a useful tool for grand average extraction. As expected, the best performances in terms of FPR, FNR, and AUC were achieved for great values of sample size and low noise level. A crucial role has been revealed for the PAR-FACT parameter, revealing that an increase in the number of rank-one tensors solving the PARAFAC problem leads to an increase in FPR values and, thus, to a worse grand average estimation.

Listening effort for sentence comprehension in noisy classroom: the mediating role of linguistic factors, inhibitory control and noise sensitivity

Children learn in noisy classrooms, where often the main masker is their own babble. Even when the acoustic conditions are favorable (i.e. low noise levels), differences in individual performance and listening effort in complex academic tasks are observed. Personal characteristics such as linguistic and cognitive skills, and sensitivity to noise have been reported as factors supporting students' performance. Moreover, the Framework for Understanding Effortful Listening (FUEL) postulates that the additional individual dimension of children's motivation should be considered when evaluating listening effort besides task-related cognitive demands. This study aims to explore the interplay of the above-mentioned individual factors for primary school children (N=120, grades 3 to 5) doing a sentence comprehension task in a two-talkers background noise. Data on both accuracy and response time, as well as self-ratings of effort and motivation were acquired. In addition, inhibitory control, linguistic competences and self-ratings of noise sensitivity were measured in quiet. Results first highlight how acoustic conditions and linguistic competencies influence child's motivation, and then show how the child's inhibitory control and noise sensitivity mediate behavioral and subjective effort. Thus, individual factors shall be taken into consideration when evaluating the effect of classroom acoustics on the performance in academic tasks.

Connecting Contemporary Trauma Care to Florence Nightingale's Visionary Work.

The impact of Florence Nightingale's visionary work continues to influence the delivery of nursing care in the contemporary emergency department (ED). Her foundational work in the Crimean War resulted in data-based recommendations for using the environment to promote healing and wellness among sick and wounded British soldiers. She advocated for attention to environmental details, including ventilation, air, warmth, drainage, cleanliness, natural light, and low noise levels. These important environmental concepts play a significant role in the nursing management of trauma patients in today's ED. This article features an application of Nightingale's environmental concepts to a trauma patient case exemplar and demonstrates the enduring impact of her work for trauma patients who receive care in the ED.

Optimal Electric Bus Scheduling with Multiple Vehicle Types Considering Bus Crowding Degree

Electric buses are environmentally friendly with the features of zero emissions and low noise levels. Therefore, it is an inevitable trend to replace traditional fuel buses with electric buses. In the urban transportation system, the most common electric bus scheduling mode is single-vehicle-type scheduling, where crowdedness in peak hours could impair the bus service level. In contrast, a high vacancy rate in off-peak hours might lead to a waste of resources. To balance efficiency and the bus service level, this paper built an electric bus scheduling model with multiple vehicle types distinguished by vehicle configurations, such as bus capacity, battery capacity, purchase cost, charging power, and electricity consumption rate. The optimization objective was to minimize the bus system costs, including bus depreciation costs, charging costs, and congestion time costs. Then, a genetic algorithm was designed to solve the model, and the model is verified by a case study of one bus line in Nanjing, China. Compared with the single-vehicle-type scheduling schemes, including large and small vehicle types, the experimental results showed that the proposed model can reduce total bus system costs by 3.52% and 6.85%, respectively. The research results can provide references for bus companies to formulate driving plans and configure vehicles.

Association between aircraft noise levels and deprivation

There is limited evidence on socioeconomic distribution of noise exposure. Noise data (Lden, Laeq24, Lnight, Levening, and Lday) were available for London Heathrow airport for 2014-18. These were linked with different measures of deprivation: the Carstairs deprivation index (UK Census-derived), fuel poverty rate and the avoidable death rate. Using Carstairs, mean noise levels were slightly higher in more deprived areas for most noise metrics, especially for Lnight (~2dB between least and most deprived Carstairs quintiles). However, Leve had slightly lower mean noise levels in the most deprived quintile (~0.5dB difference). A clear pattern of higher mean noise levels with deprivation was seen using avoidable death rates (~4dB difference between lowest and highest quintile for Lnight). Conversely, mean noise levels were slightly lower in more deprived quintiles of fuel poverty. Differences have been further quantified using a random-effects model, accounting for year. Heathrow airport is situated close to highly populated areas, some of which are very wealthy, so may not be representative of other airports. Results will be discussed with community groups near Heathrow prior to Internoise 2022. As air transport increases post-pandemic, information on noise exposures as well as views from community groups can inform future airport policies

Large area hybrid detectors based on Medipix3RX: commissioning and characterization at Sirius beamlines

Hybrid pixel detectors are inherently modular and typically operate at relative low noise levels, while providing high spatial resolution, easing the assembling of large area detectors. This report summarizes the procedures and results regarding the characterization studies performed on the Medipix3RX ASIC based detector, known as PIMEGA, which was developed and is deployed at Sirius synchrotron facility at the Brazilian Synchrotron Light Laboratory. They consist of modular constructions that reach up to 170 × 170 mm2 of active area, with 300 µm thick silicon sensors, and pixel size of 55 × 55 µm2. We investigated the spatial and energy resolutions, structural noise properties, and count-rate linearity up to large fluxes from the synchrotron beamlines. The Modulation Transfer Function presents a considerably slow decay rate as a function of the spatial frequency, reaching 30% at 10.5 lp/mm, for an operation with a threshold setting equivalent to half of the incident energy. We have also found that the energy resolutions of the two highest gain modes are around 15% for 17.5 keV incident photons. In particular, we have found that, for a noise-suppressing set of configurations, the detector presents a dead time of 460 ± 10 ns. Additionally, the pile-up effect leads to a 10% loss of linearity at input fluxes of 2.3 × 105 photons/pixel.s. These results open the possibility for operating these devices with in-depth knowledge of their performance, allowing various scientific experiments, such as X-ray diffraction, computed controlled tomography, and ptychography.

Measuring low noise level in dwellings

DS 490:2018 "Akustik - Lydklassifikation af boliger", translated to "Acoustics - Acoustic Classification of Dwellings" relates to many acoustical parameters, and two of them "Noise from ventilation" and "Reverberation times" are now being tested in real life in the Danish "Voluntary sustainability classification".(Called FBK) Danish building regulation state a sound level limit in dwellings from all kinds of technical systems at 30 dB(A), equal to the Acoustical class C, comparable with the limit in several countries. Research shows that 30 dB(A) does not ensure acoustic satisfying comfort for most people. The FBK have chosen to lower the noise limit to 25 dB(A), equal to acoustical class B. We need to improve the ventilation systems in order to reach such lower level of sound emission, and to be able to measure it implemented in dwellings. The paper describes some methods and in situ experience fighting background noise problems caused by activities around and in the dwelling, as well as in the measurement systems. Special analyses and editing of recordings based on listening and pragmatic judgements are relevant. The goal is: Measure and document low noise without a cost in time and money being a barrier for lower noise levels in dwellings.

Enhancing cosmic shear with the multiscale lensing probability density function

ABSTRACT We quantify the cosmological constraining power of the ‘lensing probability density function (PDF)’ – the one-point probability density of weak lensing convergence maps – by modelling this statistic numerically with an emulator trained on w cold dark matter cosmic shear simulations. After validating our methods on Gaussian and lognormal fields, we show that ‘multiscale’ PDFs – measured from maps with multiple levels of smoothing – offer considerable gains over two-point statistics, owing to their ability to extract non-Gaussian information: For a mock Stage-III survey, lensing PDFs yield 33 per cent tighter constraints on the clustering parameter $S_8=\sigma _8\sqrt{\Omega _{\rm m}/0.3}$ than the two-point shear correlation functions. For Stage-IV surveys, we achieve &amp;gt;90 per cent tighter constraints on S8, but also on the Hubble and dark energy equation-of-state parameters. Interestingly, we find improvements when combining these two probes only in our Stage-III set-up; in the Stage-IV scenario the lensing PDFs contain all information from the standard two-point statistics and more. This suggests that while these two probes are currently complementary, the lower noise levels of upcoming surveys will unleash the constraining power of the PDF.

An HIV stochastic model with cell-to-cell infection, B-cell immune response and distributed delay

In this study, a delayed HIV stochastic model with virus-to-cell infection, cell-to-cell transmission and B-cell immune response is proposed. We first transform the stochastic differential equation with distributed delay into a high-dimensional degenerate stochastic differential equation, and then theoretically analyze the dynamic behaviour of the degenerate model. The unique global solution of the model is given by rigorous analysis. By formulating suitable Lyapunov functions, the existence of the stationary Markov process is obtained if the stochastic B-cell-activated reproduction number is greater than one. We also use the law of large numbers theorem and the spectral radius analysis method to deduce that the virus can be cleared if the stochastic B-cell-inactivated reproduction number is less than one. Through uncertainty and sensitivity analysis, we obtain key parameters that determine the value of the stochastic B-cell-activated reproduction number. Numerically, we examine that low level noise can maintain the number of the virus and B-cell populations at a certain range, while high level noise is helpful for the elimination of the virus. Furthermore, the effect of the cell-to-cell infection on model behaviour, and the influence of the key parameters on the size of the stochastic B-cell-activated reproduction number are also investigated.

Counting statistics of single electron transport in bilayer graphene quantum dots

We measure telegraph noise of current fluctuations in an electrostatically defined quantum dot in bilayer graphene by real-time detection of single electron tunneling with a capacitively coupled neighboring quantum dot. Suppression of the second and third cumulant (related to shot noise) in a tunable graphene quantum dot is demonstrated experimentally. With this method we demonstrate the ability to measure very low current and noise levels. Furthermore, we use this method to investigate the first spin excited state, an essential prerequisite to measure spin relaxation.

Frequency comb-referenced cavity ring-down spectroscopy of natural water between 8041 and 8633 cm−1

The 1.25 µm atmospheric transparency window is of importance for a number of atmospheric applications. As a continuation of our previous works on the improvement of water vapor line parameters in the near infrared, the room temperature absorption spectrum of water vapor in natural isotopic abundance is recorded with unprecedented sensitivity between 8041 and 8633 cm−1, using comb-referenced cavity ring-down spectroscopy. The line positions and intensities of more than 5400 lines were retrieved. Their intensities range between 3.6 × 10−30 and 1.5 × 10−22 cm/molecule. The high sensitivity and low noise level of the recordings (αmin≈ 10−11 cm−1) allow for measuring more than 1600 new lines and determine their positions with an accuracy of about 10−4 cm−1 in the case of isolated features. The rovibrational assignments were performed using known experimental energy levels and calculated spectra based on variational calculations by Schwenke and Partridge. The final line list is assigned to more than 5400 transitions of the first six water isotopologues (H216O, H218O, H217O, HD16O, HD18O and HD17O). The measured line positions allow to determine the energy of 79 new levels of H216O, H218O, H217O, and HD16O, and to correct 139 previously reported term values. Although a good agreement is generally observed, the comparison to the HITRAN2020 spectroscopic database and to the W2020 transition frequencies reveals a number of discrepancies both for line positions and line intensities. The lack of traceability of some HITRAN line parameters and some biases in the derivation procedure of the W2020 energy levels are confirmed in the studied range. Validation tests of the theoretical values of the line intensities against measured values show both band-by-band variations of the deviations on the order of a few % and line-by-line fluctuations within a given band.