Noise constrains heterospecific eavesdropping more than conspecific reception of alarm calls.

Many vertebrates eavesdrop on alarm calls of other species, as well as responding to their own species' calls, but eavesdropping on heterospecific alarm calls might be harder than conspecific reception when environmental conditions make perception or recognition of calls difficult. This could occur because individuals lack hearing specializations for heterospecific calls, have less familiarity with them, or require more details of call structure to identify calls they have learned to recognize. We used a field playback experiment to provide a direct test of whether noise, as an environmental perceptual challenge, reduces response to heterospecific compared to conspecific alarm calls. We broadcast superb fairy-wren (Malurus cyaneus) and white-browed scrubwren (Sericornis frontalis) flee alarm calls to each species with or without simultaneous broadcast of ambient noise. Using two species allows isolation of the challenge of heterospecific eavesdropping independently of any effect of call structure on acoustic masking. As predicted, birds were less likely to flee to heterospecific than conspecific alarm calls during noise. We conclude that eavesdropping was harder in noise, which means that noise could disrupt information on danger in natural eavesdropping webs and so compromise survival. This is particularly significant in a world with increasing anthropogenic noise.

Moho Imaging with Fiber Borehole Strainmeters Based on Ambient Noise Autocorrelation.

Moho tomography is important for studying the deep Earth structure and geodynamics, and fiber borehole strainmeters are broadband, low-noise, and attractive tools for seismic observation. Recently, many studies have shown that fiber optic seismic sensors can be used for subsurface structure imaging based on ambient noise cross-correlation, similar to conventional geophones. However, this array-dependent cross-correlation method is not suitable for fiber borehole strainmeters. Here, we developed a Moho imaging scheme for the characteristics of fiber borehole strainmeters based on ambient noise autocorrelation. S-wave reflection signals were extracted from the ambient noise through a series of processing steps, including phase autocorrelation (PAC), phase-weighted stacking (PWS), etc. Subsequently, the time-to-depth conversion crustal thickness beneath the station was calculated. We applied our scheme to continuous four-component recordings from four fiber borehole strainmeters in Lu'an, Anhui Province, China. The obtained Moho depth was consistent with the previous research results. Our work shows that this method is suitable for Moho imaging with fiber borehole strainmeters without relying on the number of stations.

The origin of secondary microseism Love waves.

The interaction of ocean surface waves produces pressure fluctuations at the seafloor capable of generating seismic waves in the solid Earth. The accepted mechanism satisfactorily explains secondary microseisms of the Rayleigh type, but it does not justify the presence of transversely polarized Love waves, nevertheless widely observed. An explanation for two-thirds of the worldwide ambient wave field has been wanting for over a century. Using numerical simulations of global-scale seismic wave propagation at unprecedented high frequency, here we explain the origin of secondary microseism Love waves. A small fraction of those is generated by boundary force-splitting at bathymetric inclines, but the majority is generated by the interaction of the seismic wave field with three-dimensional heterogeneity within the Earth. We present evidence for an ergodic model that explains observed seismic wave partitioning, a requirement for full-wave field ambient-noise tomography to account for realistic source distributions.

Statistical study on shallow water soundscape variability of Eastern Arabian Sea using noise level metrics.

Underwater soundscape that spans a broad frequency band shows variability consistent with contributing noise sources and ocean environment. However, increased anthropogenic activities result in noise proliferation which can harm natural marine habitat. Continuous monitoring of background sound is useful to assess such spatio-temporal variability of soundscape. Standard noise level metrics, for instance, mean (µ), 90th percentiles (90P), standard deviation (σ), and kurtosis (ß), are constructed from noise field measured from three coastal stations in Eastern Arabian Sea. These metrics are found to be suitable to describe the soundscape variability with respect to season, frequency, and depth. Mean and 90P are used to compare the seasonal variations while kurtosis metrics are exercised to check the impulsive nature of composite signal. Histogram representation and probability density function (PDF) were utilized to analyze the spectral variation in soundscape with respect to season. Analysis was carried out at 500-ms temporal window in two spectral bands corresponding to traffic and wind noise fields. Seasonal analysis shows that in summer, mean noise level decreases as hydrophone depth increases, while in winter, deeper depths have higher mean value with the presence of seasonal surface duct. This implication of sound speed profile on noise field has also been confirmed using appropriate noise model.

Development and Testing of a 5G Multichannel Intelligent Seismograph Based on Raspberry Pi.

A seismograph was designed based on Raspberry Pi. Although comprising 8 channels, the seismograph can be expanded to 16, 24, or 32 channels by using a USB interfacing with a microcontroller. In addition, by clustering more than one Raspberry Pi, the number of possible channels can be extended beyond 32. In this study, we also explored the computational intelligence of Raspberry Pi for running real-time systems and multithreaded algorithms to process raw seismic data. Also integrated into the seismograph is a Huawei MH5000-31 5G module, which provided high-speed internet real-time operations. Other hardware peripherals included a 24 bit ADS1251 analog-to-digital converter (ADC) and a STM32F407 microcontroller. Real-time data were acquired in the field for ambient noise tomography. An analysis tool called spatial autocorrelation (SPAC) was used to analyze the data, followed by inversion, which revealed the subsurface velocity of the site location. The proposed seismograph is prospective for small, medium, or commercial data acquisition. In accordance with the processing power and stability of Raspberry Pi, which were confirmed in this study, the proposed seismograph is also recommended as a template for developing high-performance computing applications, such as artificial intelligence (AI) in seismology and other related disciplines.

Simulation Study of Different OPM-MEG Measurement Components.

Magnetoencephalography (MEG) is a neuroimaging technique that measures the magnetic fields of the brain outside of the head. In the past, the most suitable magnetometer for MEG was the superconducting quantum interference device (SQUID), but in recent years, a new type has also been used, the optically pumped magnetometer (OPM). OPMs can be configured to measure multiple directions of magnetic field simultaneously. This work explored whether combining multiple directions of the magnetic field lowers the source localization error of brain sources under various conditions of noise. We simulated dipolar-like sources for multiple configurations of both SQUID- and OPM-MEG systems. To test the performance of a given layout, we calculated the average signal-to-noise ratio and the root mean square of the simulated magnetic field; furthermore, we evaluated the performance of the dipole fit. The results showed that the field direction normal to the scalp yields a higher signal-to-noise ratio and that ambient noise has a much lower impact on its localization error; therefore, this is the optimal choice for source localization when only one direction of magnetic field can be measured. For a low number of OPMs, combining multiple field directions greatly improves the source localization results. Lastly, we showed that MEG sensors that can be placed closer to the brain are more suitable for localizing deeper sources.

The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks.

Recent technological advances have reduced the complexity and cost of developing sensor networks for remote environmental monitoring. However, the challenges of acquiring, transmitting, storing, and processing remote environmental data remain significant. The transmission of large volumes of sensor data to a centralized location (i.e., the cloud) burdens network resources, introduces latency and jitter, and can ultimately impact user experience. Edge computing has emerged as a paradigm in which substantial storage and computing resources are located at the "edge" of the network. In this paper, we present an edge storage and computing framework leveraging commercially available components organized in a tiered architecture and arranged in a hub-and-spoke topology. The framework includes a popular distributed database to support the acquisition, transmission, storage, and processing of Internet-of-Things-based sensor network data in a field setting. We present details regarding the architecture, distributed database, embedded systems, and topology used to implement an edge-based solution. Lastly, a real-world case study (i.e., seismic) is presented that leverages the edge storage and computing framework to acquire, transmit, store, and process millions of samples of data per hour.

Impact of COVID-19 lockdown on ambient noise levels in seven metropolitan cities of India.

The paper analyzed the impact of lockdown on the ambient noise levels in the seventy sites in the seven major cities of India and ascertained the noise scenario in lockdown period, and on the Janta Curfew day in comparison to the pre-lock down period and year 2019 annual average values. It was observed that the majority of the noise monitoring sites exhibited a decrement in ambient day and night equivalent noise levels on the national Janta Curfew day and Lockdown period as compared with the normal working days attributed to the restricted social, economical, industrial, urbanization activity and reduced human mobility. A mixed pattern was observed at a few sites, wherein the ambient day and night equivalent noise levels during Janta curfew day and Lockdown period had been reported to be higher than that on the normal working days. The study depicts the noise scenario during the lockdown and pre-lockdown period for seventy sites in India and shall be instrumental in analyzing the consequences and implications of imposing lockdowns in future on the environmental noise pollution in Indian cities.

Acoustic crypsis in southern right whale mother-calf pairs: infrequent, low-output calls to avoid predation?

Southern right whales (Eubalaena australis) invest substantial amounts of energy in their calves, while facing the risk of having them predated upon by eavesdropping killer whales (Orcinus orca). We tested the hypothesis that southern right whale mother-calf pairs employ acoustic crypsis to reduce acoustic detectability by such predators. Specifically, we deployed multi-sensor DTAGs on nine lactating whales for a total of 62.9 h in a Western Australian breeding ground, and used a SoundTrap to estimate the concomitant acoustic background noise. Vocalisations were recorded at low rates of <10 calls h-1 (1 call per dive) and at low received levels between 123±8 and 134±10 dB re. 1 µPa RMS depending on call type. We conclude that such acoustic crypsis in southern right whales and other baleen whales decreases the risk of alerting potential predators and hence jeopardizing a substantial energetic investment by the mother.

Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks.

A wireless seismic network can be effectively used as a tool for subsurface monitoring and imaging. By recording and analyzing ambient noise, a seismic network can image underground infrastructures and provide velocity variation information of the subsurface that can help to detect anomalies. By studying the variation in the noise cross-correlation function of the noise, it is possible to determine the subsurface seismic velocity and image underground infrastructures. Ambient noise imaging can be done in a decentralized fashion using Distributed Spatial Auto-Correlation (dSPAC). In dSPAC over sensor networks, the cross-correlation is the most intensive communication process since nodes need to communicate their data with neighbor nodes. In this paper, a new communication-reduced method for cross-correlation is presented to meet bandwidth and cost of communication constraints in networks while ambient noise imaging is performed using dSPAC method. By applying the proposed communication-reduced method, we show that energy and computational cost of the nodes is also preserved.

Embodied Emotion Recognition Based on Life-Logging.

Embodied emotion is associated with interaction among a person's physiological responses, behavioral patterns, and environmental factors. However, most methods for determining embodied emotion has been considered on only fragmentary independent variables and not their inter-connectivity. This study suggests a method for determining the embodied emotion considering interactions among three factors: the physiological response, behavioral patterns, and an environmental factor based on life-logging. The physiological response was analyzed as heart rate variability (HRV) variables. The behavioral pattern was calculated from features of Global Positioning System (GPS) locations that indicate spatiotemporal property. The environmental factor was analyzed as the ambient noise, which is an external stimulus. These data were mapped with the emotion of that time. The emotion was evaluated on a seven-point scale for arousal level and valence level according to Russell's model of emotion. These data were collected from 79 participants in daily life for two weeks. Their relationships among data were analyzed by the multiple regression analysis, after pre-processing the respective data. As a result, significant differences between the arousal level and valence level of emotion were observed based on their relations. The contributions of this study can be summarized as follows: (1) The emotion was recognized in real-life for a more practical application; (2) distinguishing the interactions that determine the levels of arousal and positive emotion by analyzing relationships of individuals' life-log data. Through this, it was verified that emotion can be changed according to the interaction among the three factors, which was overlooked in previous emotion recognition.

Geophonino-W: A Wireless Multichannel Seismic Noise Recorder System for Array Measurements.

The characterization of soil is essential for the evaluation of seismic hazard, because soil properties strongly influence the damage caused by earthquakes. Methods based on seismic noise are the most commonly used in soil characterization. Concretely, methods based on seismic noise array measurements allow for the estimation of Rayleigh wave dispersion curves and, subsequently, shear-wave velocity profiles. The equipment required for the application of this technique is usually very expensive, which could be a significant economic challenge for small research groups. In this work, we have developed a wireless multichannel seismic noise recorder system (Geophonino-W), which is suitable for array measurements. Each station includes a microcontroller board (Arduino), a conditioning circuit, an Xbee module, an SD card, and a GPS module. Several laboratory tests were carried out in order to study the performance of the Geophonino-W: A frequency response test (impulse response and noise); synchronization test; and battery duration test. Comparisons of Geophonino-W with the commercial systems and field measurements were also carried out. The estimated dispersion curves obtained using the proposed system were compared with the ones obtained using other commercial equipment, demonstrating the effectiveness of Geophonino-W for seismic noise array measurements. Geophonino-W is an economic open-source and hardware system that is available to any small research group or university.

An Integrated Energy-Efficient Wireless Sensor Node for the Microtremor Survey Method.

The microtremor survey method (MSM) has the potential to be an important geophysical method for identifying the strata velocity structure and detecting the buried fault structures. However, the existing microtremor exploration equipment has been unable to satisfy the requirements of the MSM, which suffers from low data accuracy, long measurement time, and blind acquisition. In this study, we combined a 2 Hz moving coil geophone with advanced acquisition systems to develop a new integrated energy-efficient wireless sensor node for microtremor exploration. A high-precision AD chip and noise matching technology are used to develop a low-noise design for the sensor node. Dynamic frequency selection technology (DFS) and dynamic power management technology (DPM) are used to design an energy-efficient mode. The data quality monitoring system solves the closed technical flaws between the acquisition systems and the control center via 4G wireless monitoring technologies. According to the results of a series of in situ tests and field measurements, the noise level of the system was 0.7 µV@500 Hz with 0 dB attenuation and 220 mW power consumption of the system in the autonomous data acquisition mode. Therefore, it provides substantial support for the effective data acquisition over long measurement durations in microtremor exploration processes. The applicability of the system is evaluated using field data, according to which the integrated energy-efficient wireless sensor node is convenient and effective for MSM.

Acoustic communication in marine shallow waters: testing the acoustic adaptive hypothesis in sand gobies.

Acoustic communication is an important part of social behaviour of fish species that live or breed in shallow noisy waters. Previous studies have shown that some fish species exploit a quiet window in the background noise for communication. However, it remains to be examined whether hearing abilities and sound production of fish are adapted to marine habitats presenting high hydrodynamism. Here, we investigated whether the communication system of the painted (Pomatoschistus pictus) and the marbled (Pomatoschistus marmoratus) gobies is adapted to enhance sound transmission and reception in Atlantic shallow water environments. We recorded and measured the sound pressure levels of social vocalisations of both species, as well as snapshots of ambient noise of habitats characterised by different hydrodynamics. Hearing thresholds (in terms of both sound pressure and particle acceleration) and responses to conspecific signals were determined using the auditory evoked potential recording technique. We found that the peak frequency range (100-300 Hz) of acoustic signals matched the best hearing sensitivity in both species and appeared well adapted for short-range communication in Atlantic habitats. Sandy/rocky exposed beaches presented a quiet window, observable even during the breaking of moderate waves, coincident with the main sound frequencies and best hearing sensitivities of both species. Our data demonstrate that the hearing abilities of these gobies are well suited to detect conspecific sounds within typical interacting distances (a few body lengths) in Atlantic shallow waters. These findings lend support to the acoustic adaptive hypothesis, under the sensory drive framework, proposing that signals and perception systems coevolve to be effective within local environment constraints.

Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones.

Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near the bottom in deep ocean direct-arrival zones.

A Noise Removal Method for Uniform Circular Arrays in Complex Underwater Noise Environments with Low SNR.

Generally, many beamforming methods are derived under the assumption of white noise. In practice, the actual underwater ambient noise is complex. As a result, the noise removal capacity of the beamforming method may be deteriorated considerably. Furthermore, in underwater environment with extremely low signal-to-noise ratio (SNR), the performances of the beamforming method may be deteriorated. To tackle these problems, a noise removal method for uniform circular array (UCA) is proposed to remove the received noise and improve the SNR in complex noise environments with low SNR. First, the symmetrical noise sources are defined and the spatial correlation of the symmetrical noise sources is calculated. Then, based on the preceding results, the noise covariance matrix is decomposed into symmetrical and asymmetrical components. Analysis indicates that the symmetrical component only affect the real part of the noise covariance matrix. Consequently, the delay-and-sum (DAS) beamforming is performed by using the imaginary part of the covariance matrix to remove the symmetrical component. However, the noise removal method causes two problems. First, the proposed method produces a false target. Second, the proposed method would seriously suppress the signal when it is located in some directions. To solve the first problem, two methods to reconstruct the signal covariance matrix are presented: based on the estimation of signal variance and based on the constrained optimization algorithm. To solve the second problem, we can design the array configuration and select the suitable working frequency. Theoretical analysis and experimental results are included to demonstrate that the proposed methods are particularly effective in complex noise environments with low SNR. The proposed method can be extended to any array.

Magnetoelectric Transverse Gradient Sensor with High Detection Sensitivity and Low Gradient Noise.

We report, theoretically and experimentally, the realization of a high detection performance in a novel magnetoelectric (ME) transverse gradient sensor based on the large ME effect and the magnetic field gradient (MFG) technique in a pair of magnetically-biased, electrically-shielded, and mechanically-enclosed ME composites having a transverse orientation and an axial separation. The output voltage of the gradient sensor is directly obtained from the transverse MFG-induced difference in ME voltage between the two ME composites and is calibrated against transverse MFGs to give a high detection sensitivity of 0.4-30.6 V/(T/m), a strong common-mode magnetic field noise rejection rate of <-14.5 dB, a small input-output nonlinearity of <10 ppm, and a low gradient noise of 0.16-620 nT/m/ Hz in a broad frequency range of 1 Hz-170 kHz under a small baseline of 35 mm. An analysis of experimental gradient noise spectra obtained in a magnetically-unshielded laboratory environment reveals the domination of the pink (1/f) noise, dielectric loss noise, and power-frequency noise below 3 kHz, in addition to the circuit noise above 3 kHz, in the gradient sensor. The high detection performance, together with the added merit of passive and direct ME conversion by the large ME effect in the ME composites, makes the gradient sensor suitable for the passive, direct, and broadband detection of transverse MFGs.

Effect of noise on comfort in open-plan offices: application of an assessment questionnaire.

Open-plan offices account for 60% of French office workspaces. The noise levels recorded in this type of environment are much lower than those encountered in industrial workplaces. Nevertheless, surveys show that noise is considered by employees as the main source of discomfort. A first questionnaire dedicated to noise discomfort was produced in 2013 and tested on a panel made up of 217 people working in 7 French companies. Today, it also makes it possible to address the issues of fatigue related to ambient sound, but above all, the survey aims to study the differences in how ambient noise is perceived depending on the type of open-plan office. On the basis of that new version, a second survey has been conducted in 23 open-plan offices, making it possible to collect the responses from 617 employees. Most of the results of the first survey have been confirmed, with an increase in the significance of the statistical analyses. Moreover, French Standard NF S 31-199, which is currently being drafted, establishes a typology of open-plan office spaces according to the types of work done in them. Based on this typology, it appears that when dealing with the impact on noise on workers, a distinction has to be made between the types of open plan offices. Practitioner Summary: Surveys conducted in open-plan offices show that noise is considered by employees as the main source of discomfort even if the noise recorded in this type of environment is not hazardous. This work presents the result of a large survey dedicated to noise discomfort conducted in 23 open-plan offices.

Potential Uses of Anthropogenic Noise as a Source of Information in Animal Sensory and Communication Systems.

Although current research on the impact of anthropogenic noise has focused on the detrimental effects, there is a range of ways by which animals could benefit from increased noise levels. Here we discuss two potential uses of anthropogenic noise. First, local variations in the ambient-noise field could be used to perceive objects and navigate within an environment. Second, introduced sound cues could be used as a signal for prey detection or orientation and navigation. Although the disadvantages of noise pollution will likely outweigh any positive effects, it is important to acknowledge that such changes may benefit some species.

Effects of Previous Acoustic Experience on Behavioral Responses to Experimental Sound Stimuli and Implications for Research.

Ambient noise differs considerably between habitats. Increased ambient noise can affect the physiology and behavior in a variety of taxa. Previous acoustic experience can modify behavior and potentially affect research conclusions in natural and laboratory environments. Acoustic conditions should thus be accounted for, especially in experiments involving experimental sound stimuli. Methods sections should contain acoustic specifications, and a consensus should be achieved over which measurements to include for comparability between researchers. Further investigation of how previous and repeated exposure to sound affects behavior and research conclusions is needed to improve our knowledge of acoustic long-term effects in animal welfare and conservation.