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Target classification and recognition have always been complex problems in underwater acoustic signal processing because of noise interference and feature instability. In this paper, a robust feature extraction method based on multi-task learning is proposed, which provides an effective solution. Firstly, an MLP-based network model suitable for underwater acoustic signal processing is proposed to optimize feature extraction. Then, multi-task learning is deployed on the model in hard parameter-sharing so that the model can extract anti-noise interference features and embed prior feature extraction knowledge. In the model training stage, the simultaneous training method enables the model to improve the robustness and representation of classification features with the knowledge of different tasks. Furthermore, the optimized classification features are sent to the classification network to complete target recognition. The proposed method is evaluated by the dataset collected in the real environment. The results show that the proposed method effectively improves recognition accuracy and maintains high performance under different noise levels, which is better than popular methods. [ABSTRACT FROM AUTHOR]

ABSTRACTIn this paper, the discussion trend on Underwater Radiated Noise (URN) from Ships being discussed at the International Maritime Organization (IMO) meeting was shared. In some countries, such as Canada and United States, marine mammals such as whales are severely affected by URN from Ships and Offshore plant facilities. In relation to the regulation of URN, internationally agreed regulations such as greenhouse gas reduction from Ships have not been developed, but awareness of seriousness of the URN is gradually increasing. Accordingly, international policy trends and technology trends for URN from Shipping, which are being dealt with in the IMO meeting, were reviewed. The technology for the URN is divided into measurement and reduction, and the reduction of propeller cavitation is being dealt with as a major technical element. Currently, the actual regulation to reduce the URN from ships is the “restriction on the speed of a ship” implemented at the individual national level. In order to develop coherent international rules and regulations, methods for measuring URN and technologies for URN reduction should be continuously developed.

The protection of marine habitats from human-generated underwater noise is an emerging challenge. Baseline information on sound levels, however, is poorly available, especially in the Mediterranean Sea. To bridge this knowledge gap, the SOUNDSCAPE project ran a basin-scale, cross-national, long-term underwater monitoring in the Northern Adriatic Sea. A network of nine monitoring stations, characterized by different natural conditions and anthropogenic pressures, ensured acoustic data collection from March 2020 to June 2021, including the full lockdown period related to the COVID-19 pandemic. Calibrated stationary recorders featured with an omnidirectional Neptune Sonar D60 Hydrophone recorded continuously 24 h a day (48 kHz sampling rate, 16 bit resolution). Data were analysed to Sound Pressure Levels (SPLs) with a specially developed and validated processing app. Here, we release the dataset composed of 20 and 60 seconds averaged SPLs (one-third octave, base 10) output files and a Python script to postprocess them. This dataset represents a benchmark for scientists and policymakers addressing the risk of noise impacts on marine fauna in the Mediterranean Sea and worldwide. [ABSTRACT FROM AUTHOR]

The extraordinary circumstances of the COVID-19 pandemic led to measures to mitigate the spread of the disease, with lockdowns and mobility restrictions at national and international levels. These measures led to sudden and sometimes dramatic reductions in human activity, including significant reductions in ship traffic in the maritime sector. We report on a reduction of deep-ocean acoustic noise in three ocean basins in 2020, based on data acquired by hydroacoustic stations in the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty. The noise levels measured in 2020 are compared with predicted levels obtained from modelling data from previous years using Gaussian Process regression. Comparison of the predictions with measured data for 2020 shows reductions of between 1 and 3 dB in the frequency range from 10 to 100 Hz for all but one of the stations. [ABSTRACT FROM AUTHOR]

Icing phenomenon that occurs universally in nature and industry gets a great impact on human life. Over the past decades, extensive efforts have been made for a wide range of anti‐icing/deicing surfaces, but the preparation of anti‐icing/deicing interfaces that combine stability, rapid self‐healing and excellent anti‐icing/deicing performance remains a challenge. In this study, a photothermal solid slippery surface with excellent comprehensive performance is prepared by integrating cellulose acetate film, carbon nanotubes with paraffin wax (CCP). Apart from the excellent anti‐icing and deicing properties at −17 ± 1.0 °C under 1 sun illumination, the surface can further achieve deicing at temperatures as low as −22 ± 1.0 °C under infrared light. The fabricated surface also exhibits great stability when placed in harsh conditions such as underwater or ultra‐low temperature environments for over 30 days. Even when suffering from physical damage, the prepared surface can rapidly self‐repair under 1 sun illumination or near‐infrared (NIR) illumination within 16.0 ± 1.5 s. Due to the rapid and repeatable self‐healing performance, the lubricating properties of the interface material do not deteriorate even after 50 repeated abrasing‐repairing cycles. The photothermal solid slippery surface possesses wide‐ranging applications and commercial value at high latitude and altitude regions. [ABSTRACT FROM AUTHOR]

Simple Summary: We describe for the first time the underwater sounds of the Mediterranean monk seal; the study was carried out during the 2021 pupping season in an important reproductive area of the species in Greece. We defined 18 different call types included in three main categories: harmonic, noisy and pulsative calls. We also described the soundscape of the study area to highlight the anthropogenic disturbance this endangered marine mammal faces in its natural environment. The Mediterranean monk seal Monachus monachus is one of the most endangered pinnipeds in the world, and is classified as "Endangered" by the International Union for the Conservation of Nature. Any additional knowledge about the species is invaluable to its effective conservation. In the present study, we deployed an autonomous underwater recorder in an important reproductive area of the Mediterranean monk seal in Greece to describe its underwater vocal repertoire. Over the 330 h of continuous recordings, 9231 vocalizations were labelled as potentially produced by Mediterranean monk seals, and 1694 good quality calls were analyzed. We defined 18 call types divided into three main call categories: harmonic, noisy, and pulsative calls. We also described the soundscape in which this endangered species lives and found that human activities around the two main pupping caves had a strong impact on the sonic environment of these seals: the noise level produced by boat traffic was high, and occurred on an hourly (25 to 50 min/hour) and daily basis (10.8 to 16.9 h/day). Such high levels of noise might not only impair the communication of the species, but also impact its survival, as chronic noise can induce physiological stress. [ABSTRACT FROM AUTHOR]

A procedure is proposed to assess the impact of various relationships found in the literature and is used to convert acoustic target strengths (TS) to fishes' total length (TL) with respect to the compatibility of fish length data obtained from vertical hydroacoustics and gillnets. The study used one set of data collected with a 120 kHz echosounder across the mesotrophic, dimictic Lake Dejguny. Four general multi-species TS–TL relationships were tested for the maximum dorsoventral characteristic: (1) a relationship developed using mainly West Atlantic marine and brackish water fish for various frequencies, (2) a relationship developed using fish from the Salmonidae, Percidae, and Cyprinidae families at 120 kHz, as well as the relationship shown by two generalized equations for representatives of (3) the Cyprinidae family (200 kHz) and (4) the Percidae family (200 kHz). In addition, two other equations were developed for (5) perch (Perca fluviatilis) and (6) roach (Rutilus rutilus). The procedure for selecting the most appropriate TS–TL ratio began by determining the TS threshold that would eliminate small fish that were ineffectively caught with gillnets. Depending on the TS–TL relation, the threshold ranged from −48.5 dB to −45.5 dB, and the corresponding TL was in the range of 62.3–93.0 mm. Then, using linear regression, the relationship between the percentage of caught fish organized in length classes (TL), whose boundaries were determined using the tested TS–TL relationships, and the share of fish recorded acoustically in the corresponding TS classes (with a 1.5 dB interval) was examined. The fit of the regression model to the data (percentage) was assessed using the coefficient of determination r2, the mean absolute error (MAE), the Nash–Sutcliffe model efficiency coefficient (NSE), and root mean square error (RMSE). For the data from Lake Dejguny, the most similar distribution of fish echo proportions and the corresponding distribution of total length (TL) for fish larger than 62 mm were obtained using the TS–TL relation developed using fish from the Salmonidae, Percidae, and Cyprinidae families (2), and for fish larger than 74 mm, the relation was developed for the family Pericidae (4). No evidence was found to unambiguously verify the meanings of different sound frequencies (120 and 200 kHz) for which the TS–TL relationships used in the analysis were derived. The proposed procedure can be used to select the optimal regression equation. [ABSTRACT FROM AUTHOR]

Metamaterials have offered unprecedented potentials for wave manipulations. However, their applications in underwater acoustic wave control have remained largely unexplored. This is because of the limited material choices and the lack of reliable fabrication techniques for the complicated structures. Herein, a metamaterial with microlattice structures as the building blocks is proposed for underwater operations. By designing the building blocks of the metamaterial and assembling them in a layered fashion, anisotropy is embedded in the structure, which results along different effective sound speeds in orthogonal directions. The designed metamaterial is fabricated by metal additive manufacturing using aluminum and steel. Experiments are performed using a resonator tube to evaluate its performance in water. An anisotropy ratio of around 2 is achieved, which is in good agreement with numerical simulations. The proposed metamaterial provides an effective means for underwater sound control with reduced fabrication difficulties and increased service life. [ABSTRACT FROM AUTHOR]

Underwater acoustic is one of the hot-topic and complex research areas for advanced signal processing. In this research, our main motivation is to recommend a high accurate underwater sound classification method using a special graph-based feature generator. The most valuable features have been selected using ReliefF iterative neighborhood component analysis (RFINCA) selector. In the classification phase, Decision Tree (DT), k nearest neighbor (kNN), Linear Discriminant (LD), Naïve Bayes (NB), and support vector machine (SVM) classifiers have been used with 10-fold cross-validation. To calculate the performance of the TQWT and antiprism graph pattern-based feature generation and RFINCA selector-based sound classification method, two underwater acoustic datasets have been collected. According to tests, the best accurate classifier is SVM. SVM attained 90.33% and 96.91% accuracies for the collected depth and direction datasets respectively. The calculated results denoted the success of the presented antiprism graph pattern-based method for underwater acoustic classification. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to solve the problem that strong noise interference seriously affects the direction of arrival (DOA) estimation in complex underwater acoustic environment. In this paper, a combined noise reduction algorithm and micro-electro-mechanical system (MEMS) vector hydrophone DOA estimation algorithm based on singular value decomposition (SVD), variational mode decomposition (VMD) and wavelet threshold denoising (WTD) is proposed. Design/methodology/approach: Firstly, the parameters of VMD are determined by SVD, and the VMD method can decompose the signal into multiple intrinsic mode functions (IMFs). Secondly, the effective IMF component is determined according to the correlation coefficient criterion and the IMF less than the threshold is processed by WTD. Then, reconstruction is carried out to achieve the purpose of denoising and calibration baseline drift. Finally, DOA estimation is achieved by the combined directional algorithm of preprocessed signal. Findings: Simulation and field experiments results show that the algorithm has good noise reduction and baseline drift correction effects for nonstationary underwater signals, and high-precision azimuth estimation is realized. Originality/value: This research provides the basis for MEMS hydrophone detection and positioning and has great engineering significance in underwater detection system. [ABSTRACT FROM AUTHOR]

Due to the negative correlation between pressure resistance and waterborne sound insulation, low-impedance soundproof materials can hardly work in deep water. Here, we propose a new mechanism to circumvent this problem by employing a sandwich panel with designed dynamics quasi-zero-stiffness (QZS) truss cores. The latticed cores are made of programable curved beams, whose shape is carefully designed to meet the demand of both high-pressure resistance and dynamics QZS. An analytical model is developed to evaluate sound transmission of such panel. It is shown that the low-frequency sound insulation performance of the customized panel increases with the hydrostatic pressure and reaches its maximum when the QZS state is triggered. The effective pressure range of the proposed sandwich panel can be further programed by stacking QZS beam lattices of different static load plateaus. The proposed design strategy stems solely from the structural geometry of the curved beams and is therefore materials-insensitive. The linear/inverse relationships between static loading feature and characteristic mechanical properties/geometrical parameters, and the stacking arrangement of lattice bring out the programability of the panel's bearing capacity. The design strategy, together with the established database, provides a feasible approach for underwater sound insulation of equipment subjected to elevated pressures. [ABSTRACT FROM AUTHOR]

The changes in underwater sound levels as commercial vessels navigate through shipping lanes in the inland waters around the Gulf of Georgia and San Juan Islands were assessed. These in-situ measures build on previous, more experimental evaluations. Recordings from three acoustic moorings at Boundary Pass, Turn Point and Haro Strait, southern Vancouver Island, British Columbia, were used to compare sound field measures at vessels' closest point of approach before, during, and following a turn. Vessel types assessed included tankers, bulkers, vehicle carriers, containerships, and passenger vessels. A multi-variate linear regression confirmed the relationship between vessel speed and sound levels, showing that the course of the vessel was also influential. The slowest transit speeds, yet highest broadband (10 Hz to 100 kHz) and vessel noise levels were recorded as they manoeuvred at Turn Point. Vessel-derived sound emissions in the mid-to high-frequencies were also considerable. [ABSTRACT FROM AUTHOR]

Increasing the number of closely packed air bubbles immersed in water changes the frequency of the Minnaert resonance. The collective interactions between bubbles in a small ensemble are primarily in the same phase, causing them to radiate a spherically symmetric field that peaks at a frequency lower than the Minnaert resonance for a single bubble. In contrast, large periodic arrays include bubbles that are further apart than half of the wavelength such that collective resonances have bubbles oscillating in opposite phases, ultimately creating a fundamental resonance at a frequency higher than the single-bubble Minnaert resonance. This work investigates the transition in resonance behavior using a modal analysis of a mass-spring system and a boundary element method. The computational complexity of the full-wave solver is significantly reduced to a linear dependence on the number of bubbles in a rectangular array. The simulated acoustic fields confirm the initial downshift in resonance frequency and the strong influence of collective resonances when the array has hundreds of bubbles covering more than half of the wavelength. These results are essential in understanding the low-frequency resonance characteristics of bubble ensembles, which have important applications in diverse fields such as underwater acoustics, quantum physics, and metamaterial design. [ABSTRACT FROM AUTHOR]

Acoustic scattering and resonances of gas bubbles are computed using a time-domain simulation based on numerical solutions of the conservation laws. The time histories of scattered pressure and fluid velocity, outside and inside the bubble, are obtained simultaneously from an immersed-boundary method allowing for the investigation of exterior and interior fields for non-spherical geometries. The acoustic resonances of the bubble are investigated for various bubble sizes, shapes, and inner gas parameters and compared in limiting cases to the partial wave scattering solutions for spherical bubbles. The dynamics of the gas motion and its associated contribution to resonance response has received little attention in previous analytical and numerical formulations. In this study, the acoustic propagation and motion inside the interior gas is investigated with respect to the monopole resonance with the combined time-domain simulation and immersed-boundary method. For the non-spherical prolate and oblate shapes, the scattering and resonance behaviors are compared with the approximate analytical results based on the shape factor method. The simulation method can be extended to less-understood shapes relevant to underwater and physical acoustics, such as "pancake-shaped" or "cigar-shaped" bubbles, as well as to spatial and time-dependent forcing. [ABSTRACT FROM AUTHOR]

A coupled-mode model is a classic approach for solving range-dependent sound propagations and is often used to provide benchmark solutions in comparison with other numerical models because of its high accuracy. Existing coupled-mode programs have disadvantages such as high computational cost, weak adaptability to complex ocean environments, and numerical instability. In this paper, a new algorithm that uses an improved range normalization of a "stair-step" and global matrix approach to address range dependence in ocean environments is designed. This algorithm uses the Chebyshev–Tau spectral method to solve the eigenpairs in the range-independent segments. The Chebyshev–Tau spectral method can converge rapidly, and the rate of convergence depends on the smoothness of the sound speed and density profiles. The main steps of the algorithm are parallelized, so parallel computing technologies are also applied for further acceleration. Based on this algorithm, an efficient program is implemented, and numerical simulations verify that this algorithm is reliable, accurate, and capable. Compared with the existing coupled-mode programs, the newly developed program is more stable and efficient with comparable accuracy and can simulate waveguides in more complex and realistic ocean environments. [ABSTRACT FROM AUTHOR]

Normal mode models are commonly used to simulate sound propagation problems in horizontally stratified oceanic environments. Although several normal mode models have been developed, the fundamental techniques for accurately and efficiently solving the modal equation are still under development. Since the standard three-point central finite difference scheme (SFD) for the modal equation has a relatively large numerical error, at least twenty sampling grid points per wavelength should be set in the depth direction. Herein, a novel finite difference scheme (NFD) is developed to further improve the accuracy of the mode solution, and the resulting linear system still has a tridiagonal structure similar to that of the SFD. To compare the performance of the NFD to that of the SFD, the NFD has been implemented in the open-source normal mode model KrakenC, and three acoustic propagation cases have been carried out, including the plane-wave reflection, the Pekeris waveguide, and the Munk waveguide. Test results show that the NFD presented in this paper is more accurate than the SFD, and can be used to reduce the number of grid points needed in the depth direction for solving the modal equation in normal mode models. [ABSTRACT FROM AUTHOR]

This work is devoted to increasing the computational efficiency of numerical methods for the one-way Helmholtz Equation (higher-order parabolic equation) in a heterogeneous underwater environment. The finite-difference rational Padé approximation of the propagation operator is considered, whose artificial computational parameters are the grid cell sizes and reference sound speed. The relationship between the parameters of the propagation medium and the artificial computational parameters is established. An optimized method for automatic determination of the artificial computational parameters is proposed. The optimization method makes it possible to account for any propagation angle and arbitrary variations in refractive index. The numerical simulation results confirm the adequacy and efficiency of the proposed approach. Automating the selection process of the computational parameters makes it possible to eliminate human errors and avoid excessive consumption of computational resources. [ABSTRACT FROM AUTHOR]

Due to the absorption and scattering of underwater light, underwater images often have some phenomena such as colorcast, low contrast, and blurred details. Therefore, an underwater image enhancement method based on entropy weight fusion is proposed. First, white balance processing can effectively correct the blue (green) color appearance of the image. Then the white‐balanced images are converted from RGB space to LAB space, and L channel is processed with improved adaptive gamma correction, and then converted back to RGB space. CLAHE and bilateral filtering are performed in RGB space. The RGB space is converted to HSV space, the V channel is processed by single‐scale retinex algorithm combined with guided filtering, stretching the R channel with s‐cosine curve,and then converted back to RGB space. Finally, the three results are fused by entropy weight to obtain the final enhanced image. Experimental results show that the proposed algorithm can improve the contrast and clarity of underwater images, and effectively remove colorcast. [ABSTRACT FROM AUTHOR]

In the field of underwater acoustic recognition, machine learning methods rely on a large number of datasets to achieve high accuracy, while the actual collected signal samples are often very scarce, which has a great impact on the recognition performance. This paper presents a recognition method of an underwater acoustic target by the data augmentation technique and the residual convolutional neural network (CNN) model, which is used to expand training samples to improve recognition performance. As a representative model in residual CNN, the ResNet18 model is used for recognition. The whole process mainly includes mel-frequency cepstral coefficient (MFCC) feature extraction, data augmentation processing, and ResNet18 model recognition. On the base of the traditional data augmentation, this study used the deep convolutional generative adversarial network (DCGAN) model to realize the expansion of underwater acoustic samples and compared the recognition performance of support vector machine (SVM), common CNN, VGG19, and ResNet18. The recognition results of the MFCC, constant Q transform (CQT), and low-frequency analyzer and recorder (LOFAR) spectrum were also analyzed and compared. Experimental results showed that the recognition accuracy of the MFCC feature was better than that of other features at the same method, and using the data augmentation method could obviously improve the recognition performance. Moreover, the recognition performance of ResNet18 using data enhancement technology was better than that of other models, which was due to the combination of the data expansion advantage of data augmentation technology and the deep feature extracting ability of the residual CNN model. In addition, although this method was used for ship recognition in this paper, it is not limited to this. This method is also applicable to other target voice recognition, such as natural sound and underwater voice biometrics. [ABSTRACT FROM AUTHOR]

Sound is a physical stimulus that has the potential to affect various growth parameters of microorganisms. However, the effects of audible sound on microbes reported in the literature are inconsistent. Most published studies involve transmitting sound from external speakers through air toward liquid cultures of the microorganisms. However, the density differential between air and liquid culture could greatly alter the sound characteristics to which the microorganisms are exposed. In this study we apply white noise sound in a highly controlled experimental system that we previously established for transmitting sound underwater directly into liquid cultures to examine the effects of two key sound parameters, frequency and intensity, on the fermentation performance of a commercial Saccharomyces cerevisiae ale yeast growing in a maltose minimal medium. We performed these experiments in an anechoic chamber to minimise extraneous sound, and find little consistent effect of either sound frequency or intensity on the growth rate, maltose consumption, or ethanol production of this yeast strain. These results, while in contrast to those reported in most published studies, are consistent with our previous study showing that direct underwater exposure to white noise sound has little impact on S. cerevisiae volatile production and sugar utilization in beer medium. Thus, our results suggest the possibility that reported microorganism responses to sound may be an artefact associated with applying sound to cultures externally via transmission through air. [ABSTRACT FROM AUTHOR]

Climate shifts are particularly conspicuous in the Arctic. Satellite and terrestrial observations show significant increases in the melting and breakup of Arctic tidewater glaciers and their influence on sea level rise. Increasing melt rates are creating an urgency to better understand the link between atmospheric and oceanic conditions and glacier frontal ablation through iceberg calving and melting. Elucidating this link requires a combination of short and long-time scale measurements of terminus activity. Recent work has demonstrated the potential of using underwater sound to quantify the time and scale of calving events to yield integrated estimates of ice mass loss (Glowacki and Deane, 2020). Here, we present estimates of subaerial calving flux using underwater sound recorded at Hansbreen, Svalbard in September 2013 combined with an algorithm for the automatic detection of calving events. The method is compared with ice calving volumes estimated from geodetic measurements of the movement of the glacier terminus and an analysis of satellite images. The total volume of above-water calving during the 26 days of acoustical observation is estimated to be 1.7 ± 0.7 × 107 m3, whereas the subaerial calving flux estimated by traditional methods is 7 ± 2 × 106 m3. The results suggest that passive cryoacoustics is a viable technique for long-term monitoring of mass loss from marine-terminating glaciers. [ABSTRACT FROM AUTHOR]

Cation–π interactions are considered to be among the most important strong noncovalent interactions in aqueous solutions and as regulators of various biological phenomena, including biological adhesion, signal transduction, and liquid–liquid phase separation (LLPS). Despite their significant roles, cation–π interactions in aqueous environments are not systematically and experimentally understood. Here, we directly experimentally examined cation–π interactions between cationic and aromatic moieties common to biological systems using a surface forces apparatus (SFA) augmented by computational methods. Specifically, we chose cationic and aromatic moieties with different levels of hydration and observed how the molecular hydration of these moieties affects the formation and strengths of cation–π bonds. To date, the charge densities of the interacting moieties are primarily considered to modulate the interaction strength; however, it is experimentally and computationally revealed that the hydration strengths (or hydrophobic properties) of the interacting moieties are more important for controlling in underwater interactions. [ABSTRACT FROM AUTHOR]

Anthropogenic noise from navigation is a major contributor to the disturbance of the acoustic soundscape in underwater environments containing noise-sensitive life forms. While previous studies mostly developed protocols for the empirical determination of noise source levels associated with the world's commercial fleet, this work explores the radiated noise emitted by small recreational vessels that thrive in many coastal waters, such as in the St. Lawrence Estuary beluga population's summer habitat. Hydrophone-based measurements in the Saguenay River (QC, Canada) were carried out during the summers of 2021 and 2022. Shore-based observations identified 45 isolated transits of small, motorized vessels and were able to track their displacement during their passage near the hydrophone. Received noise levels at the hydrophone typically fell below the hearing audiogram of the endangered St. Lawrence Estuary beluga. Monopole source levels at low frequencies (0.1–≲2 kHz) held on average twice the acoustic power compared to their mid-frequency (≳2–30 kHz) counterparts. The speed over ground of recreational vessel showed a positive correlation with the back-propagated monopole source levels. Estimations of the mid-frequency noise levels based on low-frequency measurements should be used moderately. [ABSTRACT FROM AUTHOR]

We proposed an acoustic metamaterial with deep subwavelength thickness for low-frequency underwater sound absorption. The proposed hybrid metamaterial has a perforated facesheet, a fluid-filled square honeycomb core with inside rubber coating, and a fixed backsheet. A theoretical model is established to predict the sound absorption performance of this perforated honeycomb hybrid metamaterial based on the sound absorption theory of the micro-perforated panel and electro-acoustic analogy. The theoretical model agrees well with our finite element simulation. Results suggest that perfect sound absorption (99.9%) of the metamaterial occurs at 375 Hz, at which the thickness of the metamaterial is only 1/80 of the underwater sound wavelength. According to the simulation, most of the sound energy is consumed by the rubber coating. It can be analyzed that the rubber coating replaces the fluid in the square honeycomb resonant cavity improving the acoustic capacitance and acoustic resistance and triggering a quasi-Helmholtz resonance. This acoustic metamaterial also exhibits a broadband underwater sound absorption performance by parallel design with different perforations, which has a promising potential in engineering applications. [ABSTRACT FROM AUTHOR]

In the field of aviation anti-submarine warfare, magnetic detection systems often result in a large number of false alarms due to the inability to effectively distinguish between a local geomagnetic anomaly in the background field and a target magnetic anomaly. To address this problem, this paper proposes a matching detection method for the magnetic anomaly of underwater targets. This method is based on the measured data of the magnetic anomaly in the sea area, and the geomagnetic reference map of the area is generated by interpolation of the Kriging method; then, the background field signal extracted from the geomagnetic reference map and the real-time signal acquired by detection are matched by the similarity metric algorithm; finally, the target detection is realized by using the feature fusion-isolation forest algorithm. Compared with the conventional detection methods, such as time–frequency analysis, the detection rate is improved by nearly 15% and the false alarm rate is reduced by about 40%, indicating that matching detection can effectively filter out the magnetic anomaly in the background field, reduce the false alarm, and improve the detection rate in the real geomagnetic environment, which has certain application value. [ABSTRACT FROM AUTHOR]

We assessed the effectiveness of herding techniques on adult Silver Carp Hypophthalmichthys molitrix in a tributary to the Missouri River. Sites (600 m) were contained using block nets and treated with one of five herding techniques: (1) a method commonly used by commercial fishers in the United States (commercial technique), (2) pulsed‐DC electrofishing (electric technique), (3) broadband sound administered with underwater speakers (sound technique), (4) both sound and electric in combination (combination technique), and (5) solely the boat, with no added stimulus (control). Treatments were administered at sites with repeated 20‐min runs (3×) in a slow, bank‐to‐bank pattern downstream through a 4.5‐m opening between the block net and shoreline. Herding effectiveness was quantified by run category (cumulative for the second and third runs) using adaptive resolution imaging sonar. Mean herding effectiveness of the combination technique was three to four times greater than that of the other techniques regardless of the number of runs included. The effectiveness of the combination technique was significantly greater than the sound technique and control with inclusion of the second run and the commercial technique with inclusion of the third run. All herding techniques, excluding the combination technique, were statistically similar to the control. Inclusion of the second run was advantageous for all techniques, as herding effectiveness increased 54–103%, whereas inclusion of the third run was less beneficial (9–17% increase). Repeated runs allowed fish additional time to vacate the sample reach, but behavioral responses (i.e., acclimation or sensitization) were likely technique dependent. This study describes which techniques are most effective for herding Silver Carp and provides insight for improving mass removal efforts. [ABSTRACT FROM AUTHOR]

Noise produced by human activities has increased in the oceans over the last decades. Whereas most studies have focused on the impact of anthropogenic noise on marine mammals and fishes, those focusing on marine invertebrates are rarer and more recent, especially when considering peri-metamorphic benthic stages, highly sensitive to anthropogenic perturbations. A careful review of the literature reveals a simplistic characterization of the acoustics within the containers used to quantify larval and juvenile responses to noise, thus weakening the conclusions of such works. To address this problem, we developed the Larvosonic system, a laboratory tank equipped with acoustic assets to assess the impacts of noise on young stages of marine invertebrates. We first provide a careful analysis of the tank sound field using different sound types, and we assess the effects of expanded polystyrene units on the sounds emitted by a professional audio system in order to dampen reverberation and resonance. Then, we apply this acoustic calibration to the effects of both pile driving and drilling noises on postlarvae of the scallop bivalve Pecten maximus. Acoustic recordings highlight that diffuser and bass trap components constitute effective underwater sound absorbents, reducing the reflection of the whole frequency bandwidth. Scallop experiments reveal that both type and level of the tested noise influenced postlarval growth, with interactive effects between trophic environment and noise level/spectra. The Larvosonic system thus constitutes an efficient tool for bioacoustics research on bentho-planktonic invertebrate species. [ABSTRACT FROM AUTHOR]

Due to light absorption and scattering underwater images suffer from low contrast, color distortion, blurred details, and uneven illumination, which affect underwater vision tasks and research. Therefore, underwater image enhancement is of great significance in vision applications. In contrast to existing methods for specific underwater environments or reliance on paired datasets, this study proposes an underwater multiscene generative adversarial network (UMGAN) to enhance underwater images. The network implements unpaired image-to-image translation between the underwater turbid domain and the underwater clear domain. It has a great enhancement impact on several underwater image types. Feedback mechanisms and a noise reduction network are designed to optimize the generator and address the issue of noise and artifacts in GAN-produced images. Furthermore, a global–local discriminator is employed to improve the overall image while adaptively modifying the local region image effect. It resolves the issue of over- and underenhancement in local regions. The reliance on paired training data is eliminated through a cycle consistency network structure. UMGAN performs satisfactorily on various types of data when compared quantitatively and qualitatively to other state-of-the-art algorithms. It has strong robustness and can be applied to various enhancement tasks in different scenes. [ABSTRACT FROM AUTHOR]

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Ocean Acoustic Waveguide Remote Sensing (OAWRS) enables fish population density distributions to be instantaneously quantified and continuously monitored over wide areas. Returns from seafloor geology can also be received as background or clutter by OAWRS when insufficient fish populations are present in any region. Given the large spatial regions that fish inhabit and roam over, it is important to develop automatic methods for determining whether fish are present at any pixel in an OAWRS image so that their population distributions, migrations and behaviour can be efficiently analyzed and monitored in large data sets. Here, a statistically optimal automated approach for distinguishing fish from seafloor geology in OAWRS imagery is demonstrated with Neyman–Pearson hypothesis testing which provides the highest true-positive classification rate for a given false-positive rate. Multispectral OAWRS images of large herring shoals during spawning migration to Georges Bank are analyzed. Automated Neyman-Pearson hypothesis testing is shown to accurately distinguish fish from seafloor geology through their differing spectral responses at any space and time pixel in OAWRS imagery. These spectral differences are most dramatic in the vicinity of swimbladder resonances of the fish probed by OAWRS. When such significantly different spectral dependencies exist between fish and geologic scattering, the approach presented provides an instantaneous, reliable and statistically optimal means of automatically distinguishing fish from seafloor geology at any spatial pixel in wide-area OAWRS images. Employing Kullback–Leibler divergence or the relative entropy in bits from Information Theory is shown to also enable automatic discrimination of fish from seafloor by their distinct statistical scattering properties across sensing frequency, but without the statistical optimal properties of the Neyman–Pearson approach. [ABSTRACT FROM AUTHOR]

The presence of internal waves (IWs) in the ocean alters the isotropic properties of sound speed profiles (SSPs) in the water column. Changes in the SSPs affect underwater acoustics since most of the energy is dissipated into the seabed due to the downward refraction of sound waves. In consequence, variations in the SSP must be considered when modeling acoustic propagation in the ocean. Empirical orthogonal functions (EOFs) are regularly employed to model and represent SSPs using a linear combination of basis functions that capture the sound speed variability. A different approach is to use dictionary learning to obtain a learned dictionary (LD) that generates a nonorthogonal set of basis functions (atoms) that generate a better sparse representation. In this paper, the performance of EOFs and LDs are evaluated for sparse representation of SSPs affected by the passing of IWs. In addition, an LD-based supervised framework is presented for SSP classification and is compared with classical learning models. The algorithms presented in this work are trained and tested on data collected from the Shallow Water Experiment 2006. Results show that LDs yield lower reconstruction error than EOFs when using the same number of bases. In addition, overcomplete LDs are demonstrated to be a robust method to classify SSPs during low, medium, and high IW activity, reporting accuracy that is comparable to and sometimes higher than that of standard supervised classification methods. [ABSTRACT FROM AUTHOR]

Elevated levels of anthropogenic noise, especially those observed through boating activity, can negatively impact fish species, but it remains unclear which species are most affected and which behavioural metrics are best used in assessing fish responses to underwater noise. The effects of boat sounds on freshwater species are of particular interest because freshwater environments are less studied than the marine realm despite comparably high levels of biodiversity.In the current study, we examine the behavioural responses to boat noise in two freshwater species that differ in their hypothesised response to sound inputs: the spottail shiner (Notropis hudsonius), a species with known hearing specialisations, and the bluegill sunfish (Lepomis macrochirus), a species with more generalised hearing capabilities. Fish were presented with boat noise in a laboratory setting, and their swimming, escape and foraging behaviours were assessed to examine differential responses in relation to hypothesised hearing abilities.Both species showed a decrease in general swimming behaviours but an increase in erratic movements in response to boat noise, indicative of stress responses for both species. Despite the similarities in response based on swimming behaviours however, only spottail shiners exhibited true escape responses to the onset of the noise stimulus, suggesting a more extreme reaction in the species with a more refined hearing ability.Taken together, these results show that freshwater fish can respond to increased levels of anthropogenic noise, but that the severity of the response may differ based on auditory structures and therefore presumed hearing ability. The differences seen between behavioural metrics used (swimming vs. escape responses) also demonstrate how care must be taken in choosing a metric when developing exposure guidelines for underwater sound exposures, as different metrics could lead to differential impact assessments. [ABSTRACT FROM AUTHOR]

Seagrasses play an important role in coastal ecosystems and serve as important marine carbon stores. Acoustic monitoring techniques exploit the sensitivity of underwater sound to bubbles, which are produced as a byproduct of photosynthesis and present within the seagrass tissue. To make accurate assessments of seagrass biomass and productivity, a model is needed to describe acoustic propagation through the seagrass meadow that includes the effects of gas contained within the seagrass leaves. For this purpose, a new seagrass leaf model is described for Thalassia testudinum that consists of a comparatively rigid epidermis that composes the outer shell of the leaf and comparatively compliant aerenchyma that surrounds the gas channels on the interior of the leaf. With the bulk modulus and density of the seagrass tissue determined by previous work, this study focused on characterizing the shear moduli of the epidermis and aerenchyma. These properties were determined through a combination of dynamic mechanical analysis and acoustic resonator measurements coupled with microscopic imagery and finite element modeling. The shear moduli varied as a function of length along the leaves with values of 100 and 1.8 MPa at the basal end and 900 and 3.7 MPa at the apical end for the epidermis and aerenchyma, respectively. [ABSTRACT FROM AUTHOR]

The underwater sound absorption technique in low-frequency and broadband has far-reaching prospects since it is essential for noise reduction of deep-sea operation requirements and evading advanced underwater target detection. Here, we propose an underwater sound-absorbing composite lattice with low-frequency and ultra-broadband characteristics. The composite lattice is constructed by regular spatially stacking cells with different sizes of metallic core spheres. All the core spheres are coated with silicon rubbers, and cells are embedded in the rubber matrix. In the composite lattice stereostructure, the lattice cells convert incident longitudinal waves into transverse waves through multiple local resonance coupling and multiple scattering. The energy is localized and dissipated in the composite lattice. We analyze the relationship among the corresponding absorption spectrums, the displacement clouds, and the resonance modes of lattice cells. Then, we construct a composite lattice and realize low-frequency broadband absorption from 693 to 1106 Hz with absorptance above 0.8. Further, our investigation demonstrates that the absorption bandwidth can be extended to ultra-broadband from 1077 to 10 000 Hz, where the thickness of the composite lattice is λ / 17.05. The proposed composite lattice provides a practical approach to designing ultrathin low-frequency and ultra-broadband acoustic absorption coating for underwater noise suppression. [ABSTRACT FROM AUTHOR]

Methodological and technical possibilities of monitoring temperature fields along a 1000-km track in the Sea of Japan using acoustic thermometry are presented. The proposed tomographic method for monitoring the dynamics and structure of waters is based on emission and reception of complex phase-shift keyed signals on a diagnosed path with determination of the propagation time along various ray trajectories with further measurement of the speed of sound and temperature. The physical prerequisites for practical use of thermometric studies at large distances are based on the acoustic "mudslide" effect: the phenomenon of the transition of acoustic energy from the bottom shelf area to an underwater sound signal of the deep ocean. A high-precision system of acoustic thermometry on the basis of tomographic schemes with mobile and stationary hydroacoustic emitters and receiving systems is proposed and tested with the example of the Sea of Japan. [ABSTRACT FROM AUTHOR]

Bottom formations known as pockmarks basically arise due to extensive gas emission. Active pockmarks are characterized by exceptionally high gas saturation and substantially reduced sound speed. The latter circumstance leads to strong attenuation of sound waves contacting with a pockmark. In the present paper, we study low-frequency sound propagation in a 10-km long waveguide crossing a giant pockmark. A new method of acoustic waveguide scanning based on measurement of the wavefield propagator is represented. This method allows one to explore attenuation anomalies associated with the presence of the gas-saturated bottom region. In particular, one can find out which beams fall into a pockmark area and therefore experience strong losses. Identifying such beams, as well as beams which avoid pockmark-assisted losses, one can estimate probable locations of the pockmark segment in the waveguide, provided information about the background medium is sufficient. [ABSTRACT FROM AUTHOR]

The methodological and technical possibilities of monitoring temperature fields in the Sea of Japan by acoustic thermometry methods are presented. The proposed tomographic method for monitoring the dynamics and structure of water is based on the transmission and reception of complex phase-shift keyed acoustic signals on a diagnosed track with the determination of the travel time along various ray trajectories, followed by the sound speed (temperature) determination. The physical prerequisites for the practical implementation of thermometric studies at large distances are based on the acoustic "mudslide" effect—the phenomenon of the acoustic energy "injection" from the near-bottom shelf area to the underwater sound channel of the deep ocean. Based on the Sea of Japan example, an acoustic thermometry system based on tomographic schemes with mobile and stationary hydroacoustic sources for promising work in the field of oceanic climatology is proposed. For numerical calculations of the signal propagation channels' impulse responses between sources and receivers, a specialized database of oceanological information was formed for the northwestern part of the Sea of Japan. The database includes all available data from organizations in Russia, Japan, North Korea, the Republic of Korea, and the United States (23,247 stations completed from 1925 to 2017). In the example of the Sea of Japan, a high-precision acoustic thermometry system based on tomographic schemes with developed mobile and stationary hydroacoustic transmitting and receiving systems was proposed and experimentally tested. [ABSTRACT FROM AUTHOR]

Long-range propagation of sound pulses in the deep ocean is considered. A new method for the estimation of the pulse angular spectrum is presented. The method is based on the Husimi transform of a wave field and can be realized with a short vertical array of nondirectional hydrophones. As a result, one obtains a diagram of the arrival pattern in the time–angle plane. The method is applied to a model of the underwater sound channel in the Sea of Japan. Special attention is paid to sound scattering on a cold synoptic eddy along the waveguide. It is shown that the synoptic eddy leads to a splitting of the individual ray's arrivals into clusters with close angles and times. The random sound-speed perturbation induced by internal waves blurs these clusters into a fuzzy background and simultaneously broaden the angular spectrum of pulses. Nevertheless, it is found that the latter effect is relatively weak for short vertical arrays. In particular, it is shown that increasing the array length from 10 to 30 m results in the separation of the arrivals with opposite angles. [ABSTRACT FROM AUTHOR]

Automated target recognition is an important task in the littoral warfare domain, as distinguishing mundane objects from mines can be a matter of life and death. This is initial work towards the application of convolutional autoencoding to the littoral sonar space, with goals of disentangling the reflection noise prevalent in underwater acoustics and allowing recognition of the shape and material of targets. The autoencoders were trained on magnitude Fourier transforms of the TREX13 dataset. Clusters in the encoding space representing the known variable of measurement distance between the target and the sensor were found. An encoding vector space of around 16 dimensions appeared sufficient, and the space was shown to generalize well to unseen data. [ABSTRACT FROM AUTHOR]

Underwater sound speed plays a vital role in maritime safety. Based on the acousto-optic self-interference effect, we proposed a new method to measure underwater sound speed utilizing Raman–Nath diffraction, generated by the acousto-optic effect between an optical frequency comb and pulsed chirp signal. When the pulsed chirp travels between the measurement and reference arm in the experimental setup that we constructed, the same signal resulting from acousto-optic self-interference is produced. The time gap between the two identical signals represents the time interval. Thus, we can determine the time-of-flight using cross-correlation. The optical path difference between the two arms is double the flight distance of ultrasonic waves and can easily be obtained using femtosecond laser interferometry. The time gap and the distance can be used to measure sound speed. The experimental results show that the chirp signal improves the signal-to-noise ratio and expands the applicable time-of-flight algorithm. The waveform pulse width after cross-correlation is 1.5 μs, compared with 40 μs before. The time-of-flight uncertainty can achieve 1.03 ns compared to 8.6 ns before. Uncertainty of sound velocity can achieve 0.026 m/s. [ABSTRACT FROM AUTHOR]

Inspired by recent theoretical demonstrations of nonlocal waterborne acoustic metasurfaces (WAMs), herein experimental evidence of a WAM with highly nonlocal features for high‐efficient waterborne sound control is proposed. An easy‐to‐implement nonlocal metasurface with enhanced long‐range interaction is designed and the effects of fluid–solid interaction (FSI) are considered. Results show that the nonlocal WAMs are observed to manipulate underwater sound with enhanced efficiency, as high as 97% was experimentally achieved, compared with a maximum efficiency of 71% of the conventional local devices. Besides, the robustness against frequency fluctuations and coarse discretization of the nonlocal WAMs are observed. The proposed device is potentially applicable for underwater signal communication and high‐resolution ultrasonic imaging. [ABSTRACT FROM AUTHOR]

The protection of maritime communication routes, ships and coastal installations involves the use of hydroacoustic equipment (sonars) to detect underwater equipment (means) that may operate in the aquatic environment. This paper examines the influence of seafloor topography and structure on sound propagation and sonar detection probability. [ABSTRACT FROM AUTHOR]

Topological insulators provide a new route to design acoustic metamaterials, which can exhibit novel propagation properties. However, most of the current topological acoustic metamaterials are characterized by a passive response and operated at fixed frequency ranges, and there are few reports on the effect of temperature of water on acoustic topological insulators. Therefore, in this paper, we design the temperature-controlled tunable underwater acoustic topological insulators. The topological acoustic system is composed of a triangular array of triangular steel columns embedded in water. We calculate the Dirac point frequencies and bulk band structures at different temperatures. The results show that the topological nontrivial bandgap frequency range is very sensitive to the temperature of water. We also use some numerical examples to demonstrate the robustness and defect-immune properties of the topological phononic crystals, and the topological properties can be switched by controlling the temperature of water. Our study shows that the change in the temperature can behave as an acoustic switch, which may have applications in the underwater sound waveguide as well as underwater communications. [ABSTRACT FROM AUTHOR]

This article is an obituary for Professor Andrzej Stepnowski, a renowned expert in underwater acoustics. Born in 1940 in Biała Podlaska, he studied at Gdansk University of Technology and conducted hydroacoustics research. His work led to the development of a computer-based system for fish stock estimation. Professor Stepnowski held various positions at the university and was a visiting professor at universities around the world. He also contributed to scientific societies and received several awards for his work. [Extracted from the article]