bluuebunny/crossref_metadata_2025 huggingface dataset:
Focused ultrasound and microbubble induced changes in the phenotype of breast cancer cell lines
Authors: Khan Dure S. , Rubino Rachel E. , Nicol Christopher J. , Alkins Ryan
Published: July 2024

Up to 10%–15% of patients with breast cancer (BC), particularly those with triple negative (TNBC) and HER2 positive subtypes, develop brain metastases. Despite aggressive treatment, the median survival for patients is 15 months. Treatment of brain metastases is challenging due to the blood–brain barrier (BBB) that limits the passage of molecules commonly used to treat primary BC into the brain parenchyma. Focused Ultrasound (FUS) and Microbubble (MB) are a non-invasive, image-guided therapeutic modality that can create a reversible, safe, and transient opening of the BBB. While this burgeoning area of research has progressed to clinical trials, the direct effects of FUS + MBs in the absence of therapeutic agents on tumor cells are poorly characterized. Therefore, this study aims to identify the FUS+MB induced changes in migration, invasion, and proliferation of representative brain-derived (BD) BC cell lines, namely, BD-MDA-MB-231 and BD-SKBR3 post-sonication in comparison to untreated cells. Results from these experiments will help guide future in-vivo studies evaluating the impact of FUS+MB on brain metastases to better understand its therapeutic implications and applications for patients.
Wearable ultrasound technology
Authors: Xu Sheng
Published: July 2024

The use of wearable electronic devices that can acquire vital signs from the human body noninvasively and continuously is a significant trend for healthcare. The combination of materials design and advanced microfabrication techniques enables the integration of various components and devices onto a wearable platform, resulting in functional systems with minimal limitations on the human body. Physiological signals from deep tissues are particularly valuable as they have a stronger and faster correlation with the internal events within the body compared to signals obtained from the surface of the skin. In this presentation, I will demonstrate a soft ultrasonic technology that can noninvasively and continuously acquire dynamic information about deep tissues and central organs. I will also showcase examples of this technology's use in recording blood pressure and flow waveforms in central vessels, monitoring cardiac chamber activities, and measuring core body temperatures. The soft ultrasonic technology presented represents a platform with vast potential for applications in consumer electronics, defense medicine, and clinical practices.
Improving photoacoustic imaging through the skull using deep learning: a numerical study
Authors: Olmstead Matthew J. , Wang Yu-tong , Tian Zixuan , Park Hyungjoo , Han Aiguo , Jing Yun
Published: July 2024

Photoacoustic computed tomography (PACT) has recently emerged as an attractive imaging modality for functional brain imaging due to its rich optical absorption contrast, high spatial and temporal resolutions, and relatively deep penetration. However, a major hurdle in using PACT for the human brain is distortion of the signal due to the skull, which negatively affects the quality of the images. In this project, we aimed to improve transcranial PACT using a U-Net architecture that can minimize distortion from the skull. This numerical study utilized a large collection of blood vessel images obtained from an online database and a computed tomography (CT) scan of an ex vivo human skull. The synthetic photoacoustic radiofrequency data were generated using the open-source wave solver k-Wave. Comparing the images generated by deep learning with the ground truth images, we achieved an average structural similarity index of 0.874 and an average peak signal-to-noise ratio of 17.92 dB.
Room influence on the acoustical footprint of a violin
Authors: Quiros Anna , Rogers Chris
Published: July 2024

Every violin has a unique acoustical footprint characterized by its sound transfer function (TF), and this study measures the influence of a room’s acoustical properties on that footprint. Using an omnidirectional microphone (centered, perpendicular, 20 cm from the bridge) and a force measurement hammer, we collect data across six rooms (having 0.5 to 2 s average reverberation times). After vibrationally isolating the violin and muting its strings, we tap the bridge’s upper left corner ten times and record 0.3 s audio files of each tap (48 kHz sampling rate). We estimate the TF by normalizing the sound pressure level data by the tap force measurement in frequency space. Analysis of TFs reveal variations due to violin angle. Between 250 and 1.5 k Hz, (frequency range containing the violin's characteristic A0, B1+, B1−, and transition hill modes), the average standard deviation within a 10-tap set on one day is 1 dB, and 2 dB across multiple days. Higher frequencies have more variation. Observations are not clearly tied to room size or reverberation time. The data suggest repeatable measurements of the characteristic violin modes in different acoustical environments are possible, though additional research across multiple days is necessary to confirm reproducibility.
Generating Corcos-coherent signal series using phase perturbation
Authors: Swift S. Hales , El-Kady Ihab F.
Published: July 2024

A method for producing signals with coherence that decays exponentially as a function of the product of frequency and distance in the manner described by Corcos is proposed. This type of coherence constraint is used for simulating loads resulting from turbulent propagation or pressure signals resulting from wind noise. The present method is executed by stochastically perturbing the phase of the signal as a Gaussian random variable scaled by a simple function of frequency, distance, and a velocity-like decay parameter. While the present focus of this work is on producing signals that exhibit Corcos-type coherence decay, other varieties of coherence relationships including those associated with a diffuse field can also be produced with this approach. [SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.]
An overview of aeroacoustics-related analyses for the Artemis-I mission
Authors: Kellison Makayle S. , Gee Kent L. , Coyle Whitney L. , Mathews Logan T. , Anderson Mark C. , Hart Grant W.
Published: July 2024

To improve noise scaling laws for rockets and heated, supersonic jets, this paper discusses jet aeroacoustics-related scalings for the Space Launch System (SLS). Data from four measurement stations at the Artemis-I launch, located 1.4–1.8 km from the launchpad, are used in the analysis. First, SLS maximum overall sound pressure levels are compared against other rocket noise measurements at the same scaled distance using effective nozzle diameter. Second, Strouhal number frequency-scaling is used to compare the one-third-octave sound pressure and power level spectra with other jets and rockets. Third, the Oertel convective Mach number is used to interpret a maximum directivity angle of 60°–70°. Finally, SLS’s acoustic efficiency is evaluated relative to that of other rockets.
Using empirical data to validate the role of computational fluid dynamics in various stages of aero-acoustic simulations
Authors: Okhovatian Sogand , Koukounian Viken
Published: July 2024

The purpose of utilizing higher level of understanding techniques is to improve the overall outcome of any process. As a full-service provider of complex engineering solutions to environmental noise problems, there is a need to house specialized knowledge to design and deliver bespoke solutions that are compatible with various constraints that implicate numerous subjects (acoustics, aerodynamics, structural, materials/chemical compatibility). The physics associated with seemingly simple products, such as an industrial acoustic silencer, is often complex. More specifically, its study should be described as aero-vibro-acoustical—whereby (1) airflow causes vibrations in the structure of the silencer, (2) the vibrations generate airborne and structureborne noise, and (3) components of the silencer (i.e., baffles) attenuate noise propagating through the duct. Motivated to expand our understanding of our products’ performances, we are using Siemens software to circumvent exhaustive laboratory testing that is cost-prohibitive, and which is, generally, limited to common geometries and parameters. A systematic approach is necessary to validate correlations between simulated results with empirical data. This is accomplished by, first, correlating the aerodynamic performance of products using computational fluid dynamics (CFD) to predict pressure drop values and the distribution of forces on the structure, to then leverage additional solvers to assess the vibro-acoustical stage of the analysis.
Effect of shooting glasses on earmuff attenuation measured with an acoustic test fixture for gunfire impulses
Authors: Flamme Gregory , Murphy William J. , Tasko Stephen M. , Finan Donald S. , Meinke Deanna K. , Deiters Kristy K. , Lankford James E. , Stewart Michael
Published: July 2024

The EPA requirement for hearing protector labels is based on the decrepit ANSI S3.19-1974 standard, which prohibits the use of eyewear during the REAT testing that leads to the NRR on the product label. Firearm users are recommended to wear protective eyewear while shooting. In this presentation, we review past work regarding the effects of eyewear on earmuff performance and present results from five samples of one product that includes both eyewear and an earmuff. Impulses ranging between 139 and 178 dB peak SPL were used. Impulse Insertion Loss was less than 10 dB below 400 Hz for earmuffs alone and negligible for the earmuff and glasses condition and attenuation in the high frequencies was reduced by approximately 15 to 25 dB. Impulse peak insertion loss values per ANSI S12.42 were reduced from 21 to 39 dB for the earmuff alone to 15 to 22 dB when eye protection was added. Hearing conservation programs need to account for the deleterious effect of protective eyewear on earmuffs, and additional studies with broad combinations of earmuffs and eyewear are needed to establish the range over which eyewear can be expected to compromise earmuff attenuation.
Measuring hearing protector attenuation of impulse noise on acoustic test fixtures using maximum A-weighted energy reduction
Authors: Tasko Stephen M. , Murphy William J. , Flamme Gregory , Deiters Kristy K. , Meinke Deanna K. , Finan Donald S. , Lankford James E. , Stewart Michael
Published: July 2024

Hearing protection devices (HPDs) and firearm suppressors can help mitigate risk of hearing loss from small caliber firearms. ANSI S12.42 is the standard for measuring HPD impulse peak insertion loss (IPIL). No consensus standard exists for measuring firearm suppressor noise reduction, though the industry is working toward a standard using maximum accumulated A-weighted energy. A common attenuation metric for different impulse noise reduction technologies would inform the individual and combined impact of these technologies. The maximum A-weighted energy reduction for several HPDs was assessed using firearm impulses from two rifles (0.300 Winchester Magnum and 5.56x45) with two ATFs and five field microphones positioned on opposite sides of the gun at four locations (field levels between 180- and 140-dB pSPL). No adjustments were made to account for tissue/bone conduction. Maximum A-weighted energy reduction values for single protection ranged between 17 dB (earmuff with safety glasses) and 43 dB (preformed earplug). Similar to IPIL, maximum A-weighted energy reduction increased with increased impulse levels. Advantages, disadvantages, and technical issues associated with the procedure will be discussed.
Enhancing voice biometric security: Evaluating neural network and human capabilities in detecting cloned voices
Authors: Czyzewski Andrzej
Published: July 2024

This study assesses speaker verification efficacy in detecting cloned voices, particularly in safety-critical applications such as healthcare documentation and banking biometrics. It compares deeply trained neural networks like the Deep Speaker with human listeners in recognizing these cloned voices, underlining the severe implications of voice cloning in these sectors. Cloned voices in healthcare could endanger patient safety by altering medical records, causing inaccurate diagnoses and treatments. In banking, they threaten biometric security, increasing the risk of financial fraud and identity theft. The research reveals the neural network's superiority over human detection in pinpointing cloned voices, underscoring the urgent need for sophisticated AI-based security. The study stresses the importance of developing robust defenses against voice cloning attacks, which can have critical consequences in healthcare and fintech. This research is crucial for enhancing security in areas reliant on voice authentication, safeguarding confidential data, and preserving the integrity of vital services. The Polish National Center for Research and Development (NCBR) initially supported the project “BIOPUAP” (POIR.01.01.01-0092/19), which focused on digital banking. Subsequently, the project “ADMEDVOICE” (INFOSTRATEG4/0003/2022), also supported by the NCBR, conducted further research into voice cloning in the healthcare sector.
Atmospheric effects on the propagation of sonic booms utilizing ray tracing methods
Authors: Bouza Jonathan , Riegel Kimberly A.
Published: July 2024

The aviation industry’s push towards a return of supersonic flight has some hurdles in the United States due to the regulation restricting overland supersonic use of civil aircraft without prior authorization. This regulation was put in place in response to the public's concerns over property damage from the boom front as well as the audible nuisance complaints in the path of the boom carpet. The physical behavior of the boom is understood well enough that NASA is in the testing stage of the X-59 QueSST to test the feasibility of overland flight. The boom characteristics are affected by the temperature, direction, and wind speed of the atmosphere as the signature propagates through the atmosphere. Our research plan is to implement atmospheric profiles from NCAR CFSv2 into a ray tracing Python code in order to model the behavior of the boom front in urban areas through different atmospheres. Several atmospheric conditions will be modeled and the resulting signatures around large structures will be compared.
Explosive yield determination using infrasonic signal power estimates and propagation corrections from numerical modelling
Authors: Green David N. , Waxler Roger M.
Published: July 2024

Infrasonic signal power estimated from stratospheric returns can be related to near-field acoustic power generated by an explosion. This requires propagation losses to be corrected for; one method for estimating such losses is to undertake numerical acoustic propagation modelling using state-of-the-art atmospheric specifications. Earlier work, focused on a small set of signals from well characterised explosive trials, identified that an incoherent modal sum was a promising method for calculating the source-to-receiver transmission loss. We extend the initial studies by applying this method to a wider set of explosively generated signals and include both tropospheric and stratospheric returns in the analysis. The larger dataset allows a preliminary assessment to be made of the uncertainties associated with yield determination using infrasonic power estimates.
Acknowledging the Social Bases of Speech Intelligibility: A Key to Improving Equity in Psychological and Physiological Acoustics
Authors: Munson Benjamin
Published: July 2024

A major endeavor in psychological and physiological (P&P) acoustics is understanding the causes and consequences of hearing loss. One of the most common complaints of individuals with hearing loss is difficulty perceiving speech. Hence, many studies in P&P compare psychophysical or physiological measures of auditory perception with performance on speech perception tasks like sentence intelligibility. Sentence intelligibility tasks often use read speech samples produced by a small number of demographically unspecified talkers, with only limited exceptions (i.e., McCloy, Wright, & Souza, 2015; Wright & Souza, 2012). This talk reviews findings from the author’s and others’ research groups showing that sentence intelligibility varies as a function of talkers’ social identities, including a talker’s actual or perceived racial identity (Babel and Russell, 2015; McGowan, 2015; Tripp, Lyons, and Munson, 2022). These findings reinforce recent calls for P&P to revise the intelligibility measures used to characterize the consequences of hearing loss (i.e., Beechey, 2022a, 2022b). In particular, this talk argues for a collective research program developing entirely new speech intelligibility measures that reflect diverse ways of speaking, and the diverse functions of spoken language. [Work funded by NIH grant R21 DC018070.]
Unexpected results from structural acoustic optimizations
Authors: McDaniel James G.
Published: July 2024

Optimization algorithms for improving the sound and/or vibration characteristics of something, such as a consumer product, have become ubiquitous. However, using them may occasionally give unexpected and undesirable results. The story of the Herdsman from Aesop’s Fables ends with the following relevant moral: “Be careful what you wish for; your wish may be granted.” While optimization tools effectively minimize an objective function subject to constraints, they may do so in unexpected and undesirable ways. Optimizing with respect to one physical phenomenon may damage other physical phenomena. This presentation reviews optimization problems related to the steady-state response of a vibrating system due to a sinusoidal excitation. To reduce global vibration, the system parameters are varied to maximize the power absorbed by damping elements. The wish is granted. The optimization process maximizes power absorbed by increasing the power that enters the system from the excitation. The result is an unexpected increase in global vibration. This result, as well as similar results and remedies from the controls community, are discussed. [Work supported by ONR under Grant N00014-22-1-2785.]
Modeling of construction vibration impacts in transit project applications
Authors: Tam Nicholas
Published: July 2024

This presentation explores some of the challenges related to predicting the vibration impact from construction activities associated with new mass transit infrastructure. Pre-construction assessment methods are examined and compared against as-measured construction vibration monitoring data. Practical considerations and limitations of construction vibration monitoring are also discussed, citing examples, and insight from the ongoing projects, especially in the Greater Toronto Area.
Relationships and statistics between various vibration metrics, derived from a large set of measured train pass-bys
Authors: Jurdic Vincent , Digerness Joseph
Published: July 2024

The impacts of groundborne vibration (GBV) and sound (GBS) induced by railway infrastructure are assessed across the world through different metrics. Many national and international standards can be found for assessing GBV, based either on acceleration (UK, Spain, etc.) or velocity metrics (Germany, USA, etc.). Various frequency and/or time-weightings can be used, and different quantities (running RMS or highest levels) are also considered. Direct comparison between the various assessment criteria and measured metrics is, therefore, difficult. Although no international standard defines GBS criteria, many guidelines suggest such a criterion through a relationship between GBS levels and vibration velocity levels on room surfaces. Different quantities are often used, even for neighboring projects: London’s Crossrail (now Elizabeth Line) and Northern Line extension impact assessments both used maximum vibration velocity levels but with different time weighting (slow and fast, respectively). Arup has amassed a large dataset of vibration measurements through its involvement in many railway schemes over the years. For each of the thousands of train pass-bys, measured at different distances, infrastructure types, operation, and ground conditions, the most common European and North American GBS and GBV metrics are derived and compared to each other to develop statistical relationships and associated uncertainties.
Integration of semantic and coarticulation cues during spoken language comprehension in adults
Authors: Li Scarlet Wan Yee , McDonald Margarethe , Zamuner Tania
Published: July 2024

Recent work examining cue integration across levels of linguistic representation has found that listeners can dynamically integrate some of the lower-level and higher-level cues during spoken language comprehension. However, it is still not well understood how the mechanism of cue integration works. This study investigated how adults (n = 52) process preceding higher-level semantic cues and later low-level coarticulation cues during spoken language comprehension using an eye-tracking paradigm. Participants were tested on sentences that contained a prime (semantically related or semantically unrelated to the target) and a target which had varying coarticulation cues (matching versus mismatching splicing cues). Participants were presented with two pictures (target and competitor) on a screen. Analyses looked at the proportion of looking to the target during the prime and target time windows. Results demonstrate that adults flexibly use both the preceding semantic cues and later coarticulatory cues once they are available. Our findings also indicate that adults flexibly weighed both the preceding higher-level and later lower-level cues, such that the processing of low-level coarticulatory cue varied depending on the semantic context. We have added an unstudied level of cue (semantic context) to the set of cues that our cognitive system can integrate during language comprehension.
Perception and recognition of English /s/ and /ʃ/ with varying acoustic-auditory contrast
Authors: Babel Molly , Lo Roger Y. , Vaughn Charlotte , McAuliffe Michael
Published: July 2024

Seminal work (Newman et al., JASA, 2001) found that listeners’ responses to talkers with more variable fricative productions were slower, though listeners’ ability to categorize the varied fricatives was robust. The current study selects North American English-speaking talkers with /s/ and / ʃ/ productions that varying in the magnitude of the acoustic-auditory contrast. With selected speech samples, listeners were asked to categorize (1) the isolated fricative (C- only), (2) the fricative-vowel sequence (CV), or (3) to complete a speeded-shadowing task where listeners were auditorily presented with the full words and asked to identify the words by repeating them as quickly and accurately as possible. Data were analyzed with Bayesian methods. The fricatives from talkers with greater contrast were identified more accurately and more quickly, with a greater effect size for the C-only condition and /s/ productions. This suggests listeners leverage information from the formant transitions to differentiate these fricatives. The speeded-shadowing results indicate the participants are faster at identifying the words with less acoustic-auditory contrast. This is the opposite of the expected pattern. Coupling C-only, CV, and word-level responses paints a more accurate picture of how talker differences in auditory- acoustic contrast affect categorization and intelligibility.
Performance bounds for source localization using tetrahedral microphones
Authors: Todd Steven J. , Brown Daniel C. , Roan Michael
Published: July 2024

The Cramér-Rao Bound (CRB) quantifies the minimum variance on a given unbiased estimation parameter. It can be used to derive a lower bound on source localization error for arrays, of which there are several probabilistic models in the literature. However, existing work only considers source localization using arrays of omnidirectional sensors. This presentation describes a model of the CRB as a minimum variance estimation of localization using multiple tetrahedral microphones which have cardioid microphones. Tetrahedral microphones are commonly used to record soundfields for virtual audio reproduction. The proposed method uses the cross spectral density of signals in order to calculate the CRB. This allows for more signal parameters to be included in the model. The model of the CRB was validated with an experiment in an anechoic room with a single sound source. Experimental results show the CRB forms a lower bound at low signal-to-noise ratios.
Potential of K-means clustering for preliminary labeling of acoustic data samples
Authors: Bacon Emily C. , Neilsen Tracianne B. , Leary Paul , Gemba Kay L. , Smith Kevin B.
Published: July 2024

Labeling data for use in supervised learning algorithms can be a long and arduous process, especially for large datasets. This work explores if an unsupervised k-means clustering algorithm can act as a tool to efficiently obtain preliminary labels for large acoustic datasets. This approach is tested on vector sensor data from Monterey Accelerated Research System (MARS). To determine the optimal number of clusters in the k-means algorithm, the silhouette method is used. The clustering of different types of input data will be compared. Specifically, time average spectra from the pressure sensor, the acoustic particle velocity, and intensity will be considered. In addition, the results of clustering data from different times of day and months over a two-year period will be compared. Results of the clustering will be presented along with an assessment of the potential for using a k-means clustering as a preliminary labeling tool for large acoustic sets. [Undergraduate research funded by the College of Physical and Mathematical Sciences as Brigham Young University.]
Using a sequence deep learning model to increase the acoustic context of a killer whale detector
Authors: Frazao Fabio , Kirsebom Oliver S. , Houweling April , Wladichuk Jennifer , Kanes Jasper , Joy Ruth , Dowd Mike
Published: July 2024

Although Killer whales (Orcinus orca) produce many stereotypical vocalizations, their sounds can be difficult to identify in isolation. Experts often rely on acoustic context to accurately identify these animals acoustically. Automated detectors and classifiers, on the other hand, frequently rely on short clips that capture individual vocalizations, not leveraging information regarding previous sounds. We developed deep learning models that used 1-minute inputs containing from 0 to 50 calls, with the average clip having 18. We tested three artificial neural network architectures that used recurrent layers to take the sequence of acoustic events into account. As a baseline, we used a convolutional neural network that only took 3-s clips at a time, without considering sequences of events. Here, we present preliminary evaluations on a dataset containing 360 min with Southern Resident killer whale activity in the Salish Sea, and an equal amount of data without killer whale sounds. The best model used a combination of temporal convolutional layers and gated recurrent units to achieve a recall of 0.95 at the maximum precision of 0.98. The models will be applied to near real-time monitoring efforts and will be open-sourced in the future.
Online machine learning-based channel estimation for underwater acoustic communications
Authors: Zhang Yonglin , Tai Yupeng , Wang Diya , Wang Haibin , Wang Jun , Wu Lixin , Meriaudeau Fabrice
Published: July 2024

In recent years, machine learning-assisted underwater acoustic (UWA) communication technology has been proved its promising performance in simulations and ideal training and testing environments. However, given the unique characteristics of real-world UWA communication, offline training-based methods face two major challenges: (1) The severe temporal and spatial variations result in a significant gap between offline training and actual deployment conditions. (2) The availability of high-quality labeled samples is extremely limited, making it difficult to construct an appropriate offline training sample set. To address this, we propose two online learning methods for UWA channel estimation and apply them to an OFDM communication system. The first method employs an unsupervised learning approach, where pilot signals are split and input-output pairs for model construction are formed. Thus, the received real-time data can be applied for the online training directly. The second method adjusts the loss function during the machine learning training phase to embed the learned channel within it. It allows online-sampled data to be trained sequentially by leveraging prior knowledge of transmitted information as the actual learning target. Based on the experimental results of measured underwater acoustic channels, it is demonstrated that the proposed online learning methods can approximate the near-optimal solution.
Application of attention-based transformer for ship-of-opportunity spectrogram prediction
Authors: Dobbs Corey E. , Neilsen Tracianne B. , Knobles David P. , Hodgkiss William
Published: July 2024

Passive sonar is a useful tool for underwater acoustics that can be used to detect ships or other sound sources in the ocean. The input signals into the sonar system in turn can also be used to make inferences about the ocean environment. In recent work, ship noise has been used to infer seabed information from 15–20 minute spectrograms, with CPA in the center of the time window. Waiting for 15–20 minutes to record the full time window slows down real-time inference efforts. In this work, our goal is to complete ship-of-opportunity (SOO) spectrograms given the first few minutes. Our approach is to use a self-supervised attention-based transformer, which has been found to be effective for machine learning problems, particularly for natural language processing. The transformer is trained on simulated SOO spectrograms and tested on spectrograms from the Seabed Characterization Experiment in 2017 in the New England Mud Patch. The resulting predicted spectrograms contain the key features of the measured spectrograms over the full time window. If successful, this work may allow for real-time applications of ship detections and seabed inferencing methods. [Work supported by the Office of Naval Research, Grant N00014-22-12402.]
Theoretical model for correlation analysis of wideband signal received by two vertical arrays and retrieval of modal dispersion curves in shallow water
Authors: Yarina Marina , Katsnelson Boris , Godin Oleg A.
Published: July 2024

Goal of this work is to carry out theoretical modeling extraction of characteristics of layered bottom (sound speeds c ;2 in layer, c in water, c ;b in half-space and layer’s thickness h using construction of correlation function (matrix) of wideband synthetic sound signal radiated by the moving source and imitating shipping noise. This work's motivation was experiment carried out by authors in shallow water. Combination of two vertical line arrays acts as a diffraction grating with 2N hydrophones that uses interference pattern in vertical and horizontal directions and gives more information than one-dimensional array or single receiver. Our waveguide model constitutes water layer above low-speed thin layer (c ;2 ≪ c, h is about a few meters) and half space (c ;b  > c). In this waveguide there are two sorts of modes: in dependence on frequency and thickness of sediment’s layer– modes with vertical dependence distributed in water layer and modes trapped in the near bottom layer. It is shown that correlation function constructed in coordinates (phase speed, frequency) allows us to retrieve dispersion curves and to estimate critical frequencies—determining creation of trapped modes, which in turn give parameters of layered bottom. [Work was supported by ISF, Grant No. 946/20.]
Trans-dimensional joint inversion of modal amplitude and arrival- time data for geoacoustic properties in layered muddy sediments
Authors: Jiang Yong-Min , Dosso Stan , Bonnel Julien
Published: July 2024

Long-range sound fields in a shallow-water waveguide can be expressed as a summation of several dispersive propagating modes. Modal arrival times as a function of frequency, extracted via warping time-frequency analysis, have been used by many researchers to estimate sound speeds and densities for layered models of the seabed sediments. This paper explores joint inversion of modal amplitude spectra together with arrival times to also estimate sediment-layer attenuations. To consider the common case in underwater-acoustic applications where the source amplitude spectrum is unknown, we include this spectrum as unknown parameters in the inversion, formulated implicitly within the likelihood function. Trans-dimensional Bayesian inversion is applied to estimate marginal probability profiles of the geoacoustic properties, providing quantitative uncertainties. The data considered here were collected on the New England Mud Patch during the 2017 Seabed Characterization Experiment. [Work supported by the Office of Naval Research.]
Model-based deep learning for ultrasound beamforming
Authors: Stevens Tristan S. , Luijten Ben , Sloun Ruud J.
Published: July 2024

Recently, the ultrasound signal processing pipeline has shifted from hardware-based solutions to the digital domain, enabling more intricate reconstruction techniques. We highlight several beamforming methods from a statistical inference perspective, connecting deep learning techniques to established signal processing models grounded in fundamental principles. The ultrasound acquisition process can be modeled as a linear combination of scatterers x (i.e. tissue reflectivity) which amounts to the received channel data y, captured by a forward model y = Hx + n, with the measurement matrix H. Solving this system relies heavily on priors to yield a unique and anatomically feasible solution. A naive linear estimator for x is H T y, also known as the delay-and-sum beamformer, which crudely disregards all off-axis scattering as zero-mean white noise. Based on the structured-noise assumption for off-axis scattering in the minimum variance beamformer, ABLE implements fast statistical inference of the optimal linear beamformer through deep learning. In addition, we can infuse prior knowledge on the distribution of x resulting in the neural maximum-a-posteriori beamformer. All aforementioned methods assume no dependency between individual pixels. Ultimately, the use of generative models allows us to extend the methods with more informative spatial priors.
Teaching the next generation of engineers and scientists to write: Taking responsibility and overcoming challenges
Authors: Alley Michael
Published: July 2024

In educating engineering and science students as authors, four challenges exist today that did not exist thirty years ago. First, the decreasing attention over the past three decades on teaching grammar to students has left us with many students unable to analyze writing at the sentence level. Second, the increased focus by writing teachers on the writing process to the exclusion of the product has given many students the impression that properly finishing a paper is not important. No doubt, developing a process to write is important, but so is the final product. Third, many engineering and science instructors mistakenly assume that the responsibility of teaching students to write resides solely with English departments. To develop as authors in their disciplines, engineering and science students also need thoughtful feedback from experts in the field, particularly with regard to the precision of technical terms and the proper emphasis of details. Fourth, the emergence of artificial intelligence has led many students to assume that they need not learn anymore how to write. This paper presents three undertaught writing skills that engineering and science instructors should emphasize to the next generation of engineers and scientists for them to achieve excellence in their documents.
Best practices for publishing in the Journal of the Acoustical Society of America
Authors: Lynch James , Bury Elizabeth A.
Published: July 2024

Scientists, engineers, and practitioners all have good reasons to publish in technical journals such as The Journal of the Acoustical Society of America (JASA), and so need to understand the procedures and best practices involved in doing so. While JASA has a technical focus in acoustics, it is also similar to other journals in many aspects of its writing and procedural requirements. We will address both the “business communication” and technical content aspects of journal writing. We will also stress some of the standard rules and protocols of journal writing, such as (1) polite and professional communications; (2) following specific journal requirements; (3) quoting and citing appropriately; (4) responding to comments from editors and reviewers; (5) complying with ethical standards and journal policies, etc. Useful references will be supplied to help with particular topics.
A learned born series for highly scattering media
Authors: Stanziola Antonio , Arridge Simon , Cox Ben , Treeby Bradley
Published: July 2024

The Helmholtz equation with heterogeneous material properties is essential in various fields requiring single-frequency wave simulations, including optics, seismology, acoustics, and electromagnetics. Traditional methods for solving this equation, such as the Born Series, face limitations in converging for high-contrast scattering potentials. To address this challenge, we introduce a novel method called the Learned Born Series (LBS). The LBS is derived from the convergent Born Series but employs components that are learned through training. It demonstrates significantly improved accuracy compared to the conventional convergent Born Series, especially in scenarios with high-contrast scatterers, while maintaining similar computational complexity. The LBS can rapidly generate reasonably accurate predictions of the global pressure field with only a few iterations, and the errors decrease as more iterations are learned. We show its effectiveness through experiments on simulated datasets. The LBS offers promising prospects for accelerating simulations in scenarios with strong sound speed contrasts, potentially revolutionizing applications in transcranial treatment planning and full waveform inversion.
Coupled models for designing and predicting performance of active sonar systems
Authors: Blanford Thomas E. , Johnson Shawn , Philtron Jason , Brown Daniel C.
Published: July 2024

Active sonar systems used to survey and image the seafloor typically transmit a pulse on a projector, receive echoes on an array of hydrophones, and condition and digitize the signals using on-board electronics. The quality of the data produced by these sensors is a function of the transducers, the electronics, and the environment. Simultaneous modeling of all these factors is necessary for accurate prediction of the system performance. Data products from these systems are often uncalibrated because absolute calibration is not required for their applications. However, modeling active sonar systems in their natural units within each domain provides clear benefits such as allowing system limitations to be accurately identified early during the design phase and easing validation of system performance in comparison with experimental data. This presentation will discuss the use of coupled multi-domain models in the design of two active sonar systems: the Sediment Volume Search Sonar and a multibeam echosounder architecture based on sigma-delta conversion. By coupling electro-mechanical transducer models and electrical hardware models with the Point-based Sonar Signal Model (PoSSM), it was possible to identify critical design parameters and sensitivities in the design of these sensors.
Multidomain modeling of acoustical transducers and arrays using electrical network theory
Authors: Brown David A.
Published: July 2024

Modeling of piezoceramic acoustic transducers involves the transformation of energy in the electrical, mechanical, acoustical radiation domains. By using generalized coordinates and Lagrangian mechanics, in which principle of least action is applied in each domain, the electrical, piezoelectric, mechanical and sound radiation problems can be solved separately and then combined in a multi-contour equivalent electro-mechanical circuit with each mechanical vibrational resonant modes representing separate degrees of freedom in the coupled electrical circuit. This energy approach involves the calculation of the potential and kinetic energies of each practical mode of vibration, which can be determined analytically, experimentally, or by finite-element-analysis. This is an alternative to the use of Newtonian mechanics which requires an accurate description of the real boundary conditions in the device and is common in many FEA modeling approaches. The availability of software (e.g., Matlab, Python, LTSpice, etc.) to model electrical circuits (networks in the case of multi-resonant devices) makes for a powerful and efficient modeling approach. The historical emergence of this approach stems from adapting the Rayleigh-Ritz method for mechanical and electrical domains with the advent of piezoelectric and magnetostrictive bodies. Several example of piezoceramic transducers are presented.
Measuring the behavior of the acoustic standing wave exiting a flue organ pipe: Is the decay sinusoidal or exponential?
Authors: Schefter Lauren K. , Coyle Whitney L. , Cannaday Ashley E. , Rokni Eric
Published: July 2024

Correctly predicting the playing frequencies of a musical instrument is dependent on the length of the resonator with the addition of an end correction. There are multiple theories describing this end correction, perhaps the simplest being that the end correction of a pipe is a physical extension of the sinusoidal pressure standing wave inside the pipe. However, recent optical imaging of the flow in a flue organ pipe found an unexpected exponential decay of pressure just outside of the pipe. This work looks to validate those findings acoustically. A flue organ pipe was played at the 1st, 5th, and 7th harmonics and the pressure just inside and immediately outside the end of the pipe played was measured using a zero-degree PU Match Microflown sound intensity probe. These measurements were fit to both exponential and sinusoidal curves and compared to the optical images. While an exponential trend is in fact apparent in some cases, the goodness-of-fit appears to be dependent on which harmonic is sounding. Future work includes exploration of a potential transitional region, assessing the impact of altered pipe geometry (both cross-sectional shape and size), and investigating potential sensor interference by using other measurement equipment.
The reduction of noise and vibration of composite panels in aircraft through multi-dimensional particle swarm optimization
Authors: Veenstra Noah , Rocha Joana
Published: July 2024

The reduction of noise and vibrations on aircraft poses a unique challenge. This paper explores the use of multi-dimensional Particle Swarm Optimization (PSO) to reduce vibrations and transmitted noise in composite fuselage panels excited by turbulent boundary layer flow. Turbulent boundary layer Power Spectral Density (PSD) data is used to simulate the excitation of simply supported aircraft panels. A comparison is made between isotropic aluminum 2024-T3 panels and optimized composite panels of varying composition for the assessment of success in noise transmission reduction as well as structural function. The algorithm for PSO is implemented in Python and iterates through composites with varying thickness, ply makeup, ply orientation, and materials. Python allows for complex algorithms to be easily interfaced with Finite Element Analysis (FEA) programs. In the current study, ANSYS is used to determine the spectral response of the panels subject to turbulent flow using the superposition of the modes of vibration. During the optimization process, optimization parameters are updated in each iteration based on the success of reducing the spectral response of the panel without compromising its structural integrity or increasing its weight beyond a reasonable threshold.
Soundscape augmentation for people with dementia requires accounting for disease-induced changes in auditory ccene analysis
Authors: Talebzadeh Arezoo , Botteldooren Dick , Devos Paul
Published: July 2024

Recently, there has been an increased interest in adapting the sonic environment to support people with cognitive difficulties, such as dementia. Research shows that incorporating “pleasant” sounds into the environment positively impacts behaviour and reduces psychological symptoms of dementia. Introducing sound into the acoustic environment creates an enhanced auditory experience, an augmented soundscape, resulting in an improved interpretation of the environment. People with dementia experience changes in their perception, which includes misperceptions, misidentifications, hallucinations, delusions, and time-shifting. Sound augmentation can support a better understanding of the environment and help in navigation time during the day. Dementia is a broad name for a degenerative disease; different types of dementia result in different syndromes and diverse auditory scene analyses. Some key auditory symptoms of different variants of the disease are auditory hallucinations, auditory disorientation, increased sound sensitivity, auditory agnosia (difficulty processing auditory input), agnosia for environmental sounds, amusia (tonal deafness) and Musicophilia. These different syndromes of auditory perception need more understanding when designing a soundscape augmentation for people with dementia. This talk aims to discuss different auditory symptoms of dementia based on a literature review and introduce ways to design an augmented soundscape to foster individual auditory needs.
Inverse design of three-dimensional architected elastic metamaterials using graph neural networks
Authors: Wang Yu-tong , Oudich Mourad , Maurizi Marco , Zheng Xiaoyu , Jing Yun
Published: July 2024

Architected metamaterials exhibit novel mechanical properties shaped by the spatial arrangement of periodic structures, rather than their constituent materials. Truss lattices, a notable subtype, are recognized for their high strength-to-weight ratio; thus, they hold significant potential for applications in robotics, aerospace engineering, and other fields. Despite recent advances in deep learning (DL) have revolutionized traditional design, researchers have mainly focused on the inverse design of quasi-static properties, leaving a gap in addressing dynamic behavior or simultaneous considerations for both aspects. To overcome this gap, we develop a novel inverse design framework to generate truss metamaterials with tailored quasi-static (stress-strain curve) and dynamic (transmission curve) properties. Our data-driven framework, based on graph neural networks, integrates a forward model into an inverse model, trained using deep reinforcement learning. . To demonstrate the model performance, finite element method simulations, uniaxial compression tests, and vibration tests are conducted to verify the properties of the optimized structures. The successful realization of user-desired properties in both quasi-static and dynamic domain can potentially accelerate the inverse design of novel materials towards applications such as lightweight and high-strength vibration isolators.