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Background: Listening difficulties may frequently occur in school settings, but so far there were no tools to identify them for both hearing and hearing-impaired Italian students. This study performed cross-cultural adaptation and validation of the Listening Inventory for Education-Revised for Italian students (LIFE-R-ITA). Methods: The study procedure followed the stages suggested by the Guidelines for the Process of Cross-cultural Adaptation of Self-Report Measures. For the content validation, six cochlear implanted students (8–18 years old) pre-tested the initial version. Whenever any situation did not occur in Italy, the item was adapted to more typical listening situations in Italy. The final version of LIFE-R-ITA was administered to a sample of 223 hearing students from different school settings and educational degrees in order to collect normative data. Results: For the LIFE-R-ITA, hearing students showed an average score of 72.26% (SD = 11.93), reflecting some listening difficulties. The subscales (LIFE total, LIFE class, and LIFE social) indicated good internal consistency. All items were shown to be relevant. Most challenging situations happened when listening in large rooms, especially when other students made noise. LIFE social scores were significantly worse than those of LIFE class (p < 0.001). Conclusions: The present study provides cross-cultural adaptation and validation for the LIFE-R-ITA along with the normative data useful to interpret the results of students with hearing loss. The LIFE-R-ITA may support teachers and clinicians in assessing students’ self-perception of listening at school. Such understanding may help students overcome their listening difficulties, by planning and selecting the most effective strategies among classroom interventions.

To study mechanisms of jet atomization, a novel method of experimentation utilizing the resonation of diaphragms made from thin steel plates has been previously developed. In the experiments, a diaphragm covered by a film of water emitted acoustic sounds, and jet atomization from the water film was observed. Experiments using diaphragms composed of different materials and fast Fourier transformation analysis of the acoustic sound revealed that jet atomization occurred under limited surface conditions of the diaphragm and a specific range of frequency. In this article, the dynamics of a resonating body composed of the diaphragm and water film were analyzed using the finite element method with a combination of theoretical analyses of surface waves of water, such as the well-known Lang’s equation. The present FEA results, from harmonic response analyses with consideration of viscous damping effect due to interaction between the diaphragm and water film, precisely confirmed the results of FFT analysis previously obtained by the experiment. Specifically, the peak frequency of the frequency response agreed well with the FFT results, and the shift of the peak frequency and attenuation due to the interaction in the analyses corresponded with the difference in surface conditions between the hydrophilic and hydrophobic materials of the diaphragm in the experiments. Our interpretation of the mechanism of jet atomization is expanded by the present numerical results.

The activation of the musculature of the larynx of six professional trumpeters during performance was analysed using audio, electroglottography (EGG), oxygen saturation, and heart rate signals. Two university trumpet teachers listened to the audio recordings, to evaluate the participants’ laryngeal effort during performance. Statistical analysis was performed to explore if there were any correlations between parameters extracted from the EGG data and the responses to the audio stimuli by the listeners. Two hundred and fifty (250) laryngeal articulations were identified where laryngeal raising and effort was observed during trumpet performance. It was not possible to find any correlation between the EGG data and the auditory evaluation results, but both listeners could clearly hear the laryngeal effort.

(1) Background: Australian Aboriginal English (AAE) is a variety known to differ in various ways from the mainstream, but to date very little phonetic analysis has been carried out. This study is a description of L1 Aboriginal English in southern Australia, aiming to comprehensively describe the acoustics of vowels, focusing in particular on vowels known to be undergoing change in Mainstream Australian English. Previous work has focused on static measures of F1/F2, and here we expand on this by adding duration analyses, as well as dynamic F1/F2 measures. (2) Methods: This paper uses acoustic-phonetic analyses to describe the vowels produced by speakers of Aboriginal Australian English from two communities in southern Australia (Mildura and Warrnambool). The focus is vowels undergoing change in the mainstream variety–the short vowels in KIT, DRESS, TRAP, STRUT, LOT, and the long vowel GOOSE; focusing on duration, and static and dynamic F1/F2. As part of this description, we analyse the data using the sociophonetic variables gender, region, and age, and also compare the Aboriginal Australian English vowels to those of Mainstream Australian English. (3) Results: On the whole, for duration, few sociophonetic differences were observed. For static F1/F2, we saw that L1 Aboriginal English vowel spaces tend to be similar to Mainstream Australian English but can be analysed as more conservative (having undergone less change) as has also been observed for L2 Aboriginal English, in particular for KIT, DRESS, and TRAP. The Aboriginal English speakers had a less peripheral vowel space than Mainstream Australian English speakers. Dynamic analyses also highlighted dialectal differences between Aboriginal and Mainstream Australian English speakers, with greater F1/F2 movement in the trajectories of vowels overall for AAE speakers, which was more evident for some vowels (TRAP, STRUT, LOT, and GOOSE). Regional differences in vowel quality between the two locations were minimal, and more evident in the dynamic analyses. (4) Conclusions: This paper further highlights how Aboriginal Australian English is uniquely different from Mainstream Australian English with respect to certain vowel differences, and it also highlights some ways in which the varieties align. The differences, i.e., a more compressed vowel space, and greater F1/F2 movement in the trajectories of short vowels for AAE speakers, are specific ways that Aboriginal Australian English and Mainstream Australian English accents are different in these communities in the southern Australian state of Victoria.

The architectural configuration of the space plays a crucial role in the acoustics of neonatal intensive care units (NICUs). The design of the environment, the materials used in construction, and the organisation of noise sources within the room significantly influence the noise levels present in these critical areas. For this research, the noise levels found in two hospitals, with different architectural configurations and sizes but similar construction materials, have been analysed. Data were recorded at 1 s intervals over a period of more than 24 h. The data collected in these hospitals confirm the magnitude of the noise problem in NICUs, highlighting the urgent need to address it effectively to ensure an appropriate and safe environment for the recovery of neonates. Good architectural planning can help mitigate noise, while poor configuration can exacerbate acoustic problems, negatively affecting both patients and healthcare staff. It is crucial to involve architects, acoustic engineers, and healthcare staff in the design and renovation of NICUs to create spaces that not only meet medical needs but also consider the auditory well-being of neonates.

Emotions in animals may be expressed by arousal and understanding this often relies upon the monitoring of their behaviour. Under human care, animals’ arousal states may be linked to husbandry decisions, whereby animals may display arousal responses to scheduled events such as feeding and human interaction. Here, we investigate vocal correlates of arousal associated with public presentations of bottlenose dolphins (Tursiops spp.) in human care by comparing vocal production rates and characteristics between high and low arousal contexts. Elevated arousal during the day compared with overnight was characterised by increased signature and non-signature whistle production. High intensity broadband crack vocalisations were produced less than whistles during the day and did not correlate with increased arousal around presentation times. Three of ten dolphins increased signature whistle production before and/or after presentation sessions, indicating elevated arousal and variation in individual responses. Many individuals elevated minimum frequency and suppressed maximum frequency of signature whistles in a way that correlated with higher arousal contexts, indicating that these may therefore be good indicators of changes in arousal state. Overall, our study demonstrates that passive acoustic monitoring can provide a useful indication of arousal linked to husbandry decisions, and that individual variation in vocal responses, likely linked to personality, is important to consider.

Thousands of theatres were built during the Hellenistic period in Greece and overseas colonies. The main elements of the Hellenistic theatre are the following: the orchestra, where music and songs were performed to accompany the acting performance, and the koilon, where the audience sat. Hellenistic theatres were built without any ceiling, with an open-air configuration. This paper reports the acoustic characteristics of the Greek (Hellenistic) theatre located in Morgantina (Sicily, Italy) based on the technical data gathered in different listening positions selected across the sitting area (koilon). The theatre of Morgantina was built in the third century BC and renovated a few decades ago. Nowadays, it is the center of important social and cultural activities. The outcomes of the beamforming technique employed for the survey have been discussed in comparison with traditional acoustic parameters, such as ISO 3382. The scope of this article is to assess the usability of this theatre intended to be used for different types of artistic performances.

In this study, acoustic, sighting, trawl, and marine environmental surveys were used to determine the vertical distribution and density of giant jellyfish that have been observed in Korean waters over the past 3 years. From 2020 to 2022, annual surveys were conducted in May and July in the East China Sea and waters adjacent to South Korea. The acoustic data were processed by identifying and eliminating all signals considered as noise while excluding those suspected to be jellyfish signals. Subsequently, a single target detection method was employed. Giant jellyfish are distributed mostly in the middle and low layers. In May 2021, the average population density of giant jellyfish was recorded as 11.6 (ind./ha), which was the highest density. In July 2022, this value decreased to 1.7 (ind./ha), marking the lowest density. The sighting survey, which allows for the identification of jellyfish distributed in the surface layer, exhibited a difference of approximately 0.13 times compared to the acoustic survey conducted in the middle and low layers in 2020. In 2021 and 2022, this difference was approximately 0.11 times and 0.24 times, respectively. The average of this difference was 0.16 times or greater.

A solid phase of natural gas hydrates can form from dissolved gas in oil during cold water injection into shallow undersaturated oil reservoirs. This creates significant risks to oil production due to potential permeability reduction and flow assurance issues. Understanding the conditions under which gas hydrates form and their impact on reservoir properties is important for optimizing oil recovery processes and ensuring the safe and efficient operation of oil reservoirs subject to waterflooding. In this work, we present two fluid displacement experiments under temperature control using Bentheimer sandstone core samples. A large diameter core sample of 3 inches in diameter and 10 inches in length was instrumented with multiphysics sensors (i.e., ultrasonic, electrical conductivity, strain, and temperature) to detect the onset of hydrate formation during cooling/injection steps. A small diameter core sample of 1.5 inches in diameter and 12 inches in length was used in a coreflooding apparatus with high-precision pressure transducers to determine the effect of hydrate formation on rock permeability. The fluid phase transition to solid hydrate phase was detected during the displacement of live-oil with injected water. The experimental procedure consisted of cooling and injection steps. Gas hydrate formation was detected from ultrasonic measurements at 7 °C, while strain measurements registered changes at 4 °C after gas hydrate concentration increased further. Ultrasonic velocities indicated the pore-filling morphology of gas hydrates, resulting in a high hydrate saturation of theoretically up to 38% and a substantial risk of intrinsic permeability reduction in the reservoir rock due to pore blockage by hydrates.

Rupestrian churches are spaces obtained from excavation of soft rocks that are frequently found in many Mediterranean countries. In the present paper the church dedicated to Saints Andrew and Procopius, located close to the city of Monopoli in Apulia (Italy) is studied. On-site acoustical measures were made, obtaining a detailed description of the acoustics in the current state pointing out, thanks to a combination of analysis techniques, the presence of significant modal behavior in the low frequencies, causing reverberation time to be about 2 s, four times longer than in the other bands, as well as being strongly dependent on source and receiver position (with variations of about 1 s when source is moved outside the chancel). However, as the church is characterized by significant degradation of surfaces and large amounts of debris cover the floor, the original acoustic conditions can be expected to somewhat differ. Acoustical modelling can be very helpful in grasping the original conditions, but given the small dimensions of the space, conventional geometrical acoustic prediction methods cannot be applied to simulate the low-frequency behavior. Thus, the present paper proposes an application of finite-difference-time-domain (FDTD) computation to simulate the low-frequency behavior and analyze a possible reconstruction of the original state. Results showed that a very good agreement was obtained between predictions and measurements, both in terms of resonance frequencies and reverberation times that differed by less than 5%. Modal response strongly affected the acoustical conditions also in the hypothetical reconstruction of the original state, although the sound field proved to be more uniform than in the current state.

Organisms use multi-modal, scale-dependent, sensory information to decipher their surroundings. This can include, for example, recognizing the presence of con- or heterospecifics, including a predatory threat, the presence and abundance of prey, or navigational cues to travel between breeding or feeding areas. Here we advocate for the use of the concept of active space to understand the extent to which an individual might be sending and receiving habitat information, describing this as the active component of their niche space. We present the use of active space as a means to understand ecological interactions, giving focus to those species whose active space is acoustically defined, in particular, cetacean species. We show how the application of estimates of active space, and changes in extent, can help better understand the potential disturbance effects of changes in the soundscape, and be a useful metric to estimate possible adverse effects even when stress responses, or behavioral or calling modifications are not obvious.

This research evaluates the quality of the indoor environment and comfort of Palestinian public schools. The importance of this study is related to the pivotal role of indoor environmental quality (IEQ) on students’ health, well-being, and academic performance, especially in a region facing significant challenges such as limited financial resources and diverse climate conditions. Unlike traditional technical evaluations, this research uses a post-occupancy evaluation (POE) methodology. This research is based on a questionnaire about classes’ indoor environment and comfort parameters, including thermal comfort, lighting, acoustics, indoor air quality, and ergonomic environment. The research focuses on students’ overall well-being, considering factors often overlooked in traditional assessments. Key findings reveal significant challenges in thermal conditions due to inadequate heating, cooling, and ventilation systems and a lack of passive thermal design. High carbon dioxide levels in classrooms due to inadequate ventilation highlight a second critical challenge. Schools also suffered from noise pollution due to the absence of noise-absorbing materials. Students expressed their satisfaction with the lighting and indoor ergonomic comfort. This research resulted in recommendations to address classrooms’ IEQ challenges, focusing on strategies to improve thermal comfort, acoustics, and indoor air quality.

The vast array of interconnected microorganisms across Earth’s ecosystems and within holobionts has been called the “Internet of Microbes.” Bacteria and archaea are masters of energy and information collection, storage, transformation, and dissemination using both “wired” and wireless (at a distance) functions. Specific tools affecting microbial energy and information functions offer effective strategies for managing microbial populations within, between, and beyond holobionts. This narrative review focuses on microbial management using a subset of physical modifiers of microbes: sound and light (as well as related vibrations). These are examined as follows: (1) as tools for managing microbial populations, (2) as tools to support new technologies, (3) as tools for healing humans and other holobionts, and (4) as potential safety dangers for microbial populations and their holobionts. Given microbial sensitivity to sound, light, and vibrations, it is critical that we assign a higher priority to the effects of these physical factors on microbial populations and microbe-laden holobionts. We conclude that specific sound, light, and/or vibrational conditions are significant therapeutic tools that can help support useful microbial populations and help to address the ongoing challenges of holobiont disease. We also caution that inappropriate sound, light, and/or vibration exposure can represent significant hazards that require greater recognition.

Subsurface exploration of ice-covered planets and moons presents communications challenges because of the need to communicate through kilometers of ice. The objective of this task is to develop the capability to wirelessly communicate through kilometers of ice and thus complement the potentially failure-prone tethers deployed behind an ice-penetrating probe on Ocean Worlds. In this paper, the preliminary work on the development of wireless deep-ice communication is presented and discussed. The communication test and acoustic attenuation measurements in ice have been made by embedding acoustic transceivers in glacial ice at the Matanuska Glacier, Anchorage, Alaska. Field test results show that acoustic communication is viable through ice, demonstrating the transmission of data and image files in the 13–18 kHz band over 100 m. The results suggest that communication over many kilometers of ice thickness could be feasible by employing reduced transmitting frequencies around 1 kHz, though future work is needed to better constrain the likely acoustic attenuation properties through a refrozen borehole.

This study presents an innovative methodology to augment the accuracy of gravitational acceleration (g) measurements in free fall experiments. Employing smartphones and integrating mechanical switches, our approach utilizes a built-in microphone for precise time measurements during the initiation of free fall. A meticulously designed mechanical switch controls the release of a steel sphere, triggering the timer upon the initiation of descent. Our experimental outcomes showcase a commendable congruence between the calculated g value and the locally accepted reference value, pinpointing g at 9.8274 ± 0.01 m/s2. A salient feature of our method is the utilization of the smartphone’s onboard microphone sensor, offering superior convenience to conventional sensor-based methodologies that require additional equipment. Additionally, our study introduces the seamless integration of open-source software on smartphones, facilitating the direct display and analysis of sound parameters. This integration streamlines the experimental process, contributing to the ongoing endeavors aimed at enhancing accuracy in free fall experiments. Our findings underscore the potential of smartphones and mechanical switches as accessible and effective tools in advancing physics education and scientific investigations.

In this article, a dataset is described which combines wind turbine supervisory control and data acquisition (SCADA), meteorological and acoustical data and thus gives a detailed description of a wind farm and its atmospheric and acoustic environment. The data were collected during different seasons for several weeks at a time, such that a multitude of environmental and operational conditions are covered. In five measurement campaigns, in total three different locations with similar surroundings were captured. The raw data were enhanced with derived values such as atmospheric stability or direction of sound propagation. Data of one month including all time series measurements as well as monophonic audio recordings are now published. The dataset also contains three exemplary use cases along with documents that describe the data pre-processing.

This study is a survey of sound source localization and detection methods. The study provides a detailed classification of the methods used in the fields of science mentioned above. It classifies sound source localization systems based on criteria found in the literature. Moreover, an analysis of classic methods based on the propagation model and methods based on machine learning and deep learning techniques has been carried out. Attention has been paid to providing the most detailed information on the possibility of using physical phenomena, mathematical relationships, and artificial intelligence to determine sound source localization. Additionally, the article underscores the significance of these methods within both military and civil contexts. The study culminates with a discussion of forthcoming trends in the realms of acoustic detection and localization. The primary objective of this research is to serve as a valuable resource for selecting the most suitable approach within this domain.

Acoustic non-destructive testing is widely used to detect signs of damage. However, an experienced technician is typically responsible for interpreting the result, and often the evaluation varies depending on the technician’s opinion. The evaluation is especially challenging when the acoustic signal is analyzed in the near field as Fresnel range diffraction complicates the data. In this study, we propose a Convolutional Neural Network (CNN) algorithm to detect anomalies bearing in mind its future application to micro-scale specimens such as biomedical materials. Data are generated by emitting a continuous sound wave at a single frequency through a metal specimen with a sub-millimeter anomaly and collecting the transmitted signal at several lateral locations on the opposite side (the observation plane) of the specimen. The distance between the anomaly and the observation plane falls in the quasi Fresnel diffraction regime. The use of transmitted signals is essential to evaluate the phase shift due to the anomaly, which contains information about the substance in the anomaly. We have developed a seven-layered CNN to analyze the acoustic signal in the frequency domain. The CNN takes spectrograms representing the change in the amplitude and phase of the Fourier transform over the lateral position on the observation plane as input and classifies the anomaly into nine classes in association with the lateral location of the anomaly relative to the probing signal and the material of the anomaly. The CNN performed excellently demonstrating the validation accuracy as high as 99.9%. This result clearly demonstrates CNN’s ability to extract features in the input signal that are undetectable to humans.

In connection with subsonic jet noise production, especially regarding the hot jet from a micro turbojet engine, we encountered a lack of recent high-resolution data in the literature describing the flow field using experimental validation through optical diagnoses. The objective of this paper is to examine and compare the influence on shear layers of the exhaust plug nozzle of a micro turbojet engine with and without chevrons mounted, using a high-speed camera used in Schlieren-type optical system diagnosis. Three different operating regimes are examined for both the baseline configuration and the configuration with 16 triangular-shaped chevrons. In conjunction with the image captures, the sound pressure level was recorded with the help of a microphone placed perpendicular to the flow, 0.4 m from the exhaust of the nozzle which was further processed. In quantitative terms, we found that the OASPL decreases by more than 1% when the engine is operating at higher regimes. Moreover, we found that the average exhaust jet angle, which is a measure of the quality of the fluid mixing layer is increased by 5% with respect to the baseline nozzle. By using the “darkest pixel” technique in Schlieren imaging, we can verify experimentally, for all working regimes, the theory that asserts that subsonic jet noise is a consequence of fine-scale homogeneous turbulence. Additionally, the potential novelty lies in the specific observations related to consistent dispersion of fine-scale eddies and how the presence of chevrons amplifies this uniformity within the turbulent field.

Environmental noise pollution is a growing challenge worldwide, necessitating effective sound absorption strategies to improve acoustic environments. Materials that draw inspiration from nature’s structural design principles can provide enhanced functionalities. Wood exhibits an intricate multi-scale porous architecture that can dissipate acoustic energy. This study investigates a biomimetic sound-absorbing structure composed of hierarchical pores inspired by the vascular networks within wood cells. The perforated resonators induce complementary frequency responses and porous propagation effects for broadband attenuation. Samples were fabricated using 3D printing for systematic testing. The pore size, porosity, number of layers, and order of the layers were controlled as experimental variables. Acoustic impedance tube characterization demonstrated that optimizing these architectural parameters enables absorption coefficients approaching unity across a broad frequency range. The tuned multi-layer porous architectures outperformed single pore baselines, achieving up to a 25–35% increase in the average absorption. The bio-inspired coupled pore designs also exhibited a 95% broader working bandwidth. These enhancements result from the increased viscous losses and tailored impedance matching generated by the hierarchical porosity. This work elucidates structure–property guidelines for designing biomimetic acoustic metamaterials derived from the porous morphology of wood. The results show significant promise for leveraging such multi-scale cellular geometries in future materials and devices for noise control and dissipative engineering applications across diverse sectors.

The reduction of sonic boom levels is the main challenge but also the key factor to start a new era of supersonic commercial flights. Since 1970, a FAA regulation has banned supersonic flights overland for unacceptable sonic booms at the ground, and many research studies have been carried out from that date to understand sonic boom generation, propagation and effects, both on the environment and communities. Minimization techniques have also been developed with the attempt to reduce sonic boom annoyance to acceptable levels. In the last 20 years, the advances in both knowledge and technologies, and companies and institutions’ significant investments have again raised the interest in the development of new methods and tools for the design of low boom supersonic aircraft. The exploration of unconventional configurations and exotic solutions and systems seems to be needed to effectively reduce sonic boom and allow supersonic flight everywhere. This review provides a description of all aspects of the sonic boom phenomenon related to the design of the next generation of supersonic aircraft. In particular, a critical review of the prediction and minimization methods found in the literature, aimed at identifying their strengths, limitations and gaps, is made, along with a complete overview of disruptive unconventional aircraft configurations and exotic active/passive solutions to boom level reduction. The aim of the work is to give a clear statement of state-of-the-art sonic boom prediction methods and possible reduction solutions to be explored for the design of next low-boom supersonic aircraft.

With rising interest in marine renewable energy (MRE) associated with offshore wind, waves, and tidal flows, the effects of device placement on changes in animal behaviour require proper assessment to minimise environmental impacts and inform decision making. High-frequency multibeam echosounders, or imaging sonars, can be used to observe and record the underwater movement and behaviour of animals at a fine scale (tens of metres). However, robust target detection and tracking of closely spaced animals are required for assessing animal–device and predator–prey interactions. Dual-frequency multibeam echosounders combine longer detection ranges (low frequency) with greater detail (high frequency) while maintaining a wide field of view and a full water column range compared to acoustic or optical cameras. This study evaluates the performance of the Tritech Gemini 1200ik imaging sonar at 720 kHz (low frequency) and 1200 kHz (high frequency) for small target detection with increasing range and the ability of the two frequency modes to discriminate between two closely spaced targets using a 38.1 mm tungsten carbide acoustic calibration sphere under controlled conditions. The quality of target detection decreases for both modes with increasing range, with a 25 m limit of detection at high frequency and a low-frequency mode able to detect the target up to 30 m under test conditions in shallow water. We quantified the enhanced performance of the high-frequency mode in discriminating targets at short ranges and improved target detection and discrimination at high ranges in the low-frequency mode.

The complex mythological web of Miguel de Cervantes’s novella “El celoso extremeño” has been extensively explored by scholars. However, despite the fact that most conducting myths referenced in the novel revolve around themes of vigilance, clandestine gaze, and visual deceit, these topics have not been systematically addressed yet. This present essay intends to bridge this analytical gap by exploring the ways in which mythological parables in “El celoso extremeño” connect with contemporary scientific preoccupations regarding perception, optical illusions, the nature of images and sounds and the ways the human eye and ear perceive them.

Speech samples can provide valuable information regarding speaker characteristics, including their social backgrounds. Accent variations with speaker backgrounds reflect corresponding acoustic features of speech, and these acoustic variations can be analyzed to assist in tracking down criminals from speech samples available as forensic evidence. Speech accent identification has recently received significant consideration in the speech forensics research community. However, most works have utilized long-term temporal modelling of acoustic features for accent classification and disregarded the stationary acoustic characteristics of particular phoneme articulations. This paper analyzes short-term acoustic features extracted from a central time window of English vowel speech segments for accent discrimination. Various feature computation techniques have been compared for the accent classification task. It has been found that using spectral features as an input gives better performance than using cepstral features, with the lower filters contributing more significantly to the classification task. Moreover, detailed analysis has been presented for time window durations and frequency bin resolution to compute short-term spectral features concerning accent discrimination. Using longer time durations generally requires higher frequency resolution to optimize classification performance. These results are significant, as they show the benefits of using spectral features for speaker profiling despite the popularity of cepstral features for other speech-related tasks.

Macrophytes and seagrasses play a crucial role in a variety of functions in marine ecosystems and respond in a synchronized manner to a changing climate and the subsequent ecological status. The monitoring of seagrasses is one of the most important issues in the marine environment. One rapidly emerging monitoring technique is the use of acoustics, which has advantages compared to other remote sensing techniques. The acoustic method alone is ambiguous regarding the identities of backscatterers. Therefore, a computer program package was developed to identify and estimate the leaf biometrics (leaf length and biomass) of one of the most common seagrasses, Posidonia oceanica. Some problems in the acoustic data were resolved in order to obtain estimates related to problems with vegetation as well as fisheries and plankton acoustics. One of the problems was the “lost” bottom that occurred during the data collection and postprocessing due to the presence of acoustic noise, reverberation, interferences and intense scatterers, such as fish shoals. Another problem to be eliminated was the occurrence of near-bottom echoes belonging to submerged vegetation, such as seagrasses, followed by spurious echoes during the survey. The last one was the recognition of the seagrass to estimate the leaf length and biomass, the calibration of the sheaths/vertical rhizomes of the seagrass and the establishment of relationships between the acoustic units and biometrics. As a result, an autonomous package of code written in MATLAB was developed to perform all the processes, named “POSIBIOM”, an acronym for POSIdonia BIOMass. This study presents the algorithms, methodology, acoustic–biometric relationship and mapping of biometrics for the first time, and discusses the advantages and disadvantages of the package compared to the software dedicated to the bottom types, habitat and vegetation acoustics. Future studies are recommended to improve the package.

Acoustic metamaterials are materials artificially engineered to control sound waves, which is not possible with conventional materials. We have proposed a design of an acoustic metamaterial plate with inbuilt Helmholtz resonators. The plate is made of Polylactic acid (PLA) which is fabricated using an additive manufacturing technique. It consists of Helmholtz resonator-shaped cavities of different sizes. In this paper, we have analyzed the acoustic properties of the Helmholtz resonators-based metamaterial plate experimentally as well as numerically. The experimental results are in good agreement with the numerical results. These types of 3D-printed metamaterial plates can find their application where high sound transmission loss is required to create a quieter ambience. There is an additional advantage of being lightweight because of the Helmholtz resonator-shaped cavities built inside the plate. Thus, these types of metamaterial plates can find their application in the design sector requiring lighter materials with high sound transmission loss.

A new vibro-acoustic method is presented to analyze the sound radiation behavior of orthotropic panel-form sound radiators using strip-type exciters to exert line loads to the panels for sound radiation. The simple first-order shear deformation theory together with the Ritz method is used to formulate the proposed method that makes the vibro-acoustic analysis of elastically restrained stiffened orthotropic plates more computationally efficient than the methods formulated on the basis of the other shear deformation theories. An elastically restrained orthotropic plate consisting of two parallel strip-type exciters was tested to measure the experimental sound pressure level curve for validating the effectiveness and accuracy of the proposed method. The resonance characteristics (natural frequency and mode shape) detrimental to sound radiation are identified in the vibro-acoustic analysis of the orthotropic plate. For any orthotropic sound radiation plate, based on the detrimental mode shapes, a practical procedure is presented to design the line load locations on the plate to suppress the major sound pressure level dips for enhancing the smoothness of the plate sound pressure level curve. For illustration, the sound radiation enhancement of orthotropic plates with different fiber orientations for aspect ratios equal to 3, 2, and 1 subjected to one or two line loads is conducted using the proposed procedure. The results for the cases with two line loads perpendicular to the fiber direction and located at the nodal lines of the major detrimental mode shape may find applications in designing orthotropic panel-form speakers with relatively smooth sound pressure level curves.

Drug-loaded perfluorocarbon nanodroplets (NDs) can be activated non-invasively by focused ultrasound (FUS) and allow for precise drug-delivery. Anesthetic-loaded NDs and transcranial FUS have previously achieved targeted neuromodulation. To assess the clinical potential of anesthetic-loaded NDs, in depth physical characterization and investigation of storage strategies and triggered-activation is necessary. Pentobarbital-loaded decafluorobutane nanodroplets (PBNDs) with a Definity-derived lipid shell (237 nm; 4.08 × 109 particles/mL) were fabricated and assessed. Change in droplet stability, concentration, and drug-release efficacy were tested for PBNDs frozen at −80 °C over 4 weeks. PBND diameter and the polydispersity index of thawed droplets remained consistent up to 14 days frozen. Cryo-TEM images revealed NDs begin to lose circularity at 7 days, and by 14 days, perfluorocarbon dissolution and lipid fragmentation occurred. The level of acoustic response and drug release decreases through prolonged storage. PBNDs showed no hemolytic activity at clinically relevant concentrations and conditions. At increasing sonication pressures, liquid PBNDs vaporized into gas microbubbles, and acoustic activity at the second harmonic frequency (2 f0) peaked at lower pressures than the subharmonic frequency (1/2 f0). Definity-based PBNDs have been thoroughly characterized, cryo-TEM has been shown to be suitable to image the internal structure of volatile NDs, and PBNDs can be reliably stored at −80 °C for future use up to 7 days without significant degradation, loss of acoustic response, or reduction in ultrasound-triggered drug release.

Non-fed aquaculture is an important contributor to low environmental impact protein production. However, knowledge of spatiotemporal patterns of the fish community in non-fed fishery systems remains limited, despite their ecological importance for sustainable aquaculture and fisheries. To elucidate the status of the fisheries and their critical drivers in non-fed fishery systems, hydroacoustic surveys were conducted seasonally in Hongchaojiang Reservoir in two seasons (spring and autumn) of two consecutive years: 2018 and 2019. Results showed that the average fish density in Hongchaojiang Reservoir was 121.6 ind./1000 m3. Fish communities varied significantly between geographical locations and seasons. On the temporal scale, fish densities in October were higher than those in April. On the spatial scale, fish densities were higher in the upstream (S1 and S3) than those in the midstream (S2, S4, S5, S6), while the density of S7, S8 and S9 in the downstream was the lowest. Trophic level index, zooplankton, chlorophyll-a, and phytoplankton play vital roles in fish distributional patterns, while the target strength, which reflects fish body size, was highly associated with water temperature, dissolved oxygen, total organic carbon, and phytoplankton. These results suggest that the spatiotemporal distribution of the fish community in Hongchaojiang Reservoir was jointly influenced by biotic and abiotic variables of water bodies, and highlight the importance of water nutrient levels and food availability in shaping fish distribution in the non-fed aquaculture system. This study should improve our understanding of ecological patterns and dominant drivers in fish stocks and provide information for successful sustainable management in non-fed purification fisheries.

The purpose of this work is to increase the security of the perimeter of an area from unauthorized intrusions by creating an improved algorithm for classifying acoustic impacts recorded with a sensor system based on a phase-sensitive optical time reflectometer (phi-OTDR). The algorithm includes machine learning, so a dataset consisting of two classes was assembled. The dataset consists of two classes. The first class is the data of the steps, and the second class is other non-stepping influences (engine noise, a passing car, a passing cyclist, etc.). As an intrusion signal, a human walking signal is analyzed and recorded in frames of 5 s, which passed the threshold condition. Since, in most cases, the intruder moves on foot to overcome the perimeter, the analysis of the acoustic effects generated during the step will increase the efficiency of the perimeter detection tools. When walking quietly, step signals can be quite weak, and background signals can contain high energy and visually resemble the signals you are looking for. Therefore, an algorithm was created that processes space–time diagrams developed in real time, which are grayscale images. At the same time, during the processing of one image, two more images are calculated, which are the result of processing the denoised autoencoder and the created mathematical model of the adaptive correlation. Then, the three obtained images are fed to the input of the created three-channel neural network classifier, which includes convolutional layers for the automatic extraction of spatial features. The probability of correctly detecting steps is 98.3% and that of background actions is 97.93%.

Ultrasonic bat detectors are useful for research and monitoring purposes to assess occupancy and relative activity of bat communities. Environmental “clutter” such as tree boles and foliage can affect the recording quality and identification of bat echolocation calls collected using ultrasonic detectors. It can also affect the transmission of calls and recognition by bats when using acoustic lure devices to attract bats to mist-nets. Bat detectors are often placed in forests, yet automatic identification programs are trained on call libraries using echolocation passes recorded largely from open spaces. Research indicates that using clutter-recorded calls can increase classification accuracy for some bat species and decrease accuracy for others, but a detailed understanding of how clutter impacts the recording and identification of echolocation calls remains elusive. To clarify this, we experimentally investigated how two measures of clutter (i.e., total basal area and number of stems of simulated woody growth, as well as recording angle) affected the recording and classification of a synthesized echolocation signal under controlled conditions in an anechoic chamber. Recording angle (i.e., receiver position relative to emitter) significantly influenced the probability of correct classification and differed significantly for many of the call parameters measured. The probability of recording echo pulses was also a function of clutter but only for the detector angle at 0° from the emitter that could receive deflected pulses. Overall, the two clutter metrics were overshadowed by proximity and angle of the receiver to the sound source but some deviations from the synthesized call in terms of maximum, minimum, and mean frequency parameters were observed. Results from our work may aid efforts to better understand underlying environmental conditions that produce false-positive and -negative identifications for bat species of interest and how this could be used to adjust survey accuracy estimates. Our results also help pave the way for future research into the development of acoustic lure technology by exploring the effects of environmental clutter on ultrasound transmission.

Two significant spaces define the soundscape of worship in a church: chancel and nave. The chancel is a space with the primary function of a sound source, where the preachers and choir are often seated during church services. Church design and layout have changed throughout history based on the functional needs of its target congregation. Some modern churches have omitted the chancel to fit contemporary design aesthetics. The main aim of this study is to investigate the relationship between the chancel and the acoustics performance of a church. Four churches with varying geometries of circular, polygonal, and rectangular chancels were selected for this study. Two simulations of varying chancel characteristics of chancel availability and chancel geometry were conducted. The recorded speech intelligibility index (STI) and reverberation time (RT) results indicate that chancel availability and geometry significantly affect churches’ acoustic performance. The simulation of the chancel availability mainly affected speech intelligibility, where the models with chancels recorded a higher STI than the models without chancels. In terms of chancel geometry, the results of the STI of the circular chancels were more encouraging than the polygonal and rectangular chancels.

Polymers are increasingly being used in higher demanding applications due to their ability to tailor the properties of structures while allowing for a weight and cost reduction. Solvents play an important role in the manufacture of polymeric structures since they allow for a reduction in the polymer’s viscosity or assist with the dispersion of fillers into the polymer matrix. However, the incorrect removal of the solvent affects both the physical and chemical properties of polymeric materials. The presence of residual solvent can also negatively affect the curing kinetics and the final quality of polymers. Destructive testing is mainly performed to characterize the properties of these materials. However, this type of testing involves using lab-type equipment that cannot be taken in-field to perform in situ testing and requires a specific sample preparation. Here, a method is presented to non-destructively evaluate the curing process and final viscoelastic properties of polymeric materials using ultrasonics. In this study, changes in longitudinal sound speed were detected during the curing of an aerospace epoxy adhesive as a result of variations in polymer chemistry. To simulate the presence of residual solvent, samples containing different weight percentages of isopropyl alcohol were manufactured and tested using ultrasonics. Thermogravimetric analysis was used to show changes in the decomposition of the adhesive due to the presence of IPA within the polymer structure. Adding 2, 4, and 6 wt.% of IPA decreased the adhesive’s lap shear strength by 40, 58, and 71%, respectively. Ultrasonics were used to show how the solvent influenced the curing process and the final sound speed of the adhesive. Young’s modulus and Poisson’s ratio were determined using both the longitudinal and shear sound speeds of the adhesive. Using ultrasonics has the potential to non-invasively characterize the quality of polymers in both an in-field and manufacturing settings, ensuring their reliability during use in demanding applications.

This paper seeks to develop some conceptual elements that articulated the social construction of the soundscape of the urban spaces of the kingdom of Castile (15th–16th centuries). We focus our attention on the revision of the normative spheres that structured the subjective universe of the Castilian inhabitants, in order to notice and spot the different sound representations that intervened in the spatial and social configuration of the cities, their possible conflicts, and levels of acoustic tolerance. This proposal is part of the so-called “sensorial turn” in the Social Sciences, defined by David Howes as a cultural approach to the study of the senses as well as a sensorial approach to the study of culture. The research is carried out through the analysis of the sensory marks present in a documentary corpus made up of normative documents (municipal ordinances, books of agreement, chapter acts, diocesan synods, and royal dispositions) and judicial documents (General Archive of Simancas) combining methods of discourse analysis and the history of the senses. In the article, we argue and remark that the sound dimension operated as a device that acted in the shaping of the identity of places, since it contributed to define and delimit their use. This was reflected in the importance given by the authorities to the normative regulation of the community, which included a textual dimension in which the historical soundscape was imprinted, revealing the multiple social interactions that integrated it.

Many fields now perform non-destructive testing using acoustic signals for the detection of objects or features of interest. This detection requires the decision of an experienced technician, which varies from technician to technician. This evaluation becomes even more challenging as the object decreases in size. In this paper, we assess the use of both traditional signal-processing machine learning algorithms, Long Short-Term Memory (LSTM), as well as Convolutional Neural Network (CNN) architectures to approximate acoustic anomalies with an eye toward micro-scale applications such as application to biofilms. The probing signal is generated using a continuous sound wave emitted at controlled frequencies of 1 and 5 MHz through metallic specimens of varying heights each containing an anomaly in the form of a hole. Data are collected as the transmitted signal is sampled at several locations as the wave travels through the specimen. We have developed both a CNN and an LSTM architecture for frequency-domain feature detection and approximation. The CNN models, one for phase and one for amplitude data, take short-distance Fourier transforms (SDFTs) representing the change in the signal over multiple observation points as input. The LSTM model takes the change in phase or amplitude points at each lateral location as a comma-separated value (CSV) input. The models analyze the frequency and spatial changes experienced by each specimen and produce an estimation of the acoustic path length of the anomaly in radians. The models are evaluated using mean-square error and the R-square statistic. All models perform with a fairly high R-square score, the amplitude CNN and LSTM models achieving upwards of a 99% fit and the phase CNN achieving a 97% fit on average for the predicted values. With the performance of these models, we demonstrate that utilizing the transfer function phase and amplitude data to analyze acoustic diffraction patterns leads to the ability to extract, with great precision, features in the input signal that describe the nature of the anomaly.

Sacred constructions like churches are built both for holy and architectural purposes. They are influenced by the design fashions, city history and the government. When a church, or more generally a religious building, is constructed, it is rarely torn down. Instead, these kinds of edifices are refurbished, expanded and modified according to the architectural trend of a specific period. The indoor activities of the church have changed over time, especially after the Second Vatican Council. Thus, it can be interesting to study the past modifications of churches and their features and uses. The aim of this paper is to explore the influence of a building’s history on the architectural change over time and more specifically, the subsequent influence on the indoor acoustic field. Additionally, this study aims to show how a precise and scientific reconstruction of a church’s history, using ancient documents, can provide researchers with a valuable method of investigation. Furthermore, this study aims to analyze the indoor acoustics of these holy buildings over time and elucidate whether these were considered or not for the purposes of the contemporary sacred celebrations. Therefore, in this paper, the Dome of Conegliano (Italy) is the focus of the present study. Detailed historical research was performed by means of reviewing ancient documents to faithfully reconstruct the Dome’s history. Furthermore, acoustic measurements were executed to characterize its shape in our times. Using these results, the ancient configuration of the dome was reconstructed virtually and compared to the contemporary one. Interestingly, the results show that seven centuries of history did influence the church’s architecture and consequently its indoor acoustics. The source–receiver distance has been shown to be an influential parameter, determining that the church is acoustically more suitable for listening to music rather than voice. Clearly, the Dome of Conegliano’s indoor acoustics were not modified or improved over time to fulfill their potential use, but the internal shape was modified according to the architectural fashion and to fulfill other requests as well as the structural requirements of the owners.

This paper provides novel insights into the robustness of machine learning and signal-processing-based acoustic material classification for material transport in modern iron- and steelmaking. The proposed method is designed to deal with the specific harsh and challenging environmental conditions encountered in steel plants. Robust classification depends on the dataset and its contamination with noise. The present work investigates the application of noise detection together with classification algorithms and shows the impact on classification performance. Four contributions are addressed: (i) an evaluation of an outlier detection method for time series, which is based on the short-term enhanced root mean square value RMS (RMSe), (ii) a comparison of different artificial neural network (ANN) structures applied for acoustic classification of material classes, (iii) results on the test dataset splits and (iv) evaluation of the robustness of proposed convolutional neural network (CNN) architecture against environmental disturbances such as the adversarial dropping sound of contaminants. With the combination of preprocessing and CNN on a material transport process dataset, we show an improvement of the overall classification accuracy. It proves the significance of preprocessing a contaminated dataset and the applicability of CNN for real-world acoustic sensoring systems.

This article is devoted to the development of a classification method based on an artificial neural network architecture to solve the problem of recognizing the sources of acoustic influences recorded by a phase-sensitive OTDR. At the initial stage of signal processing, we propose the use of a band-pass filter to collect data sets with an increased signal-to-noise ratio. When solving the classification problem, we study three widely used convolutional neural network architectures: AlexNet, ResNet50, and DenseNet169. As a result of computational experiments, it is shown that the AlexNet and DenseNet169 architectures can obtain accuracies above 90%. In addition, we propose a novel CNN architecture based on AlexNet, which obtains the best results; in particular, its accuracy is above 98%. The advantages of the proposed model include low power consumption (400 mW) and high speed (0.032 s per net evaluation). In further studies, in order to increase the accuracy, reliability, and data invariance, the use of new algorithms for the filtering and extraction of acoustic signals recorded by a phase-sensitive reflectometer will be considered.

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.

Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable, and prompt method to screen for COVID-19 using easily acquirable physiological sounds. These systems have been demonstrated previously and have shown promise but lack robust analysis of their deployment in real-world settings when faced with diverse recording equipment, noise environments, and test subjects. The primary aim of this work is to begin to understand the impacts of these real-world deployment challenges on the system performance. Using Mel-Frequency Cepstral Coefficients (MFCC) and RelAtive SpecTrAl-Perceptual Linear Prediction (RASTA-PLP) features extracted from cough, speech, and breathing sounds in a crowdsourced dataset, we present a baseline classification system that obtains an average receiver operating characteristic area under the curve (AUC-ROC) of 0.77 when discriminating between COVID-19 and non-COVID subjects. The classifier performance is then evaluated on four additional datasets, resulting in performance variations between 0.64 and 0.87 AUC-ROC, depending on the sound type. By analyzing subsets of the available recordings, it is noted that the system performance degrades with certain recording devices, noise contamination, and with symptom status. Furthermore, performance degrades when a uniform classification threshold from the training data is subsequently used across all datasets. However, the system performance is robust to confounding factors, such as gender, age group, and the presence of other respiratory conditions. Finally, when analyzing multiple speech recordings from the same subjects, the system achieves promising performance with an AUC-ROC of 0.78, though the classification does appear to be impacted by natural speech variations. Overall, the proposed system, and by extension other acoustic-based diagnostic aids in the literature, could provide comparable accuracy to rapid antigen testing but significant deployment challenges need to be understood and addressed prior to clinical use.

Monitoring the status of Arctic marine ecosystems is aided by multi-sensor oceanographic moorings that autonomously collect data year-round. In the northeast Chukchi Sea, an ASL Environmental Sciences Acoustic Zooplankton Fish Profiler (AZFP) collected data from the upper 30 m of the water column every 10–20 s from 2014 to 2020. We here describe the processing of the AZFP’s 455 kHz acoustic backscatter return signal for the purpose of developing methods to assist in characterizing local sea ice conditions. By applying a self-organizing map (SOM) machine learning algorithm to 15-min ensembles of these data, we are able to accurately differentiate between the presence of open water and sea ice, and thereby characterize statistical properties surface wave height envelopes and ice draft. The ability to algorithmically identify small-scale features within the information-dense acoustic dataset enables efficient and rich characterizations of environmental conditions, such as frequency of sparse ice floes in otherwise open water and brief open-water leads amidst the ice pack. Corrections for instrument tilt, speed of sound, and water level allow us to resolve the sea surface reflection interface to within approximately 0.06 ± 0.09 m. By automating the acoustic data processing and alleviating labor- and time-intensive analyses, we extract additional information from the AZFP backscatter data, which is otherwise used for assessing fish and zooplankton densities and behaviors. Beyond applications to new datasets, the approach opens possibilities for the efficient extraction of new information from existing upward-looking sonar records that have been collected in recent decades.

Advancements in lean premixed combustion have increased the efficiency and reduced the amount of greenhouse gas emissions, but they have led to increased noise emissions due to higher turbulence and mixing fluctuations. This study used an external sensor (microphone) to validate the simulation of the combustion noise of a confined space. An experimental facility with a laboratory-scale furnace was used to carry out the measurement, and the simulation of the confined flame noise was conducted in OpenFOAM. The simulation utilized the Partially Stirred Reactor (PaSR) and a hybrid computational aeroacoustics (CAA) approach using the large eddy simulation (LES)/the Ffwocs Williams–Hawkings (FWH) method. Additionally, unsteady Reynolds-averaged Navier–Stokes (URANS)/the FWH method was tested for a comparison with the LES prediction. A sensor which was placed outside the enclosure for ease of access was then used to validate the results of the numerical model. The sensor data agreed with the LES/FWH results including the amplitude and frequency of the primary combustion peak and the overall sound pressure level (OASPL). This suggested that a sensor which was placed outside the enclosure could serve as a validation tool for the simulation of the confined flames despite the sound reflections from the walls.

Computational models of sufficient quality are indispensable to quantitatively assess aircraft noise reduction measures. Within this study, a multi-level simulation framework is established in order to predict the environmental noise of holding approach procedures by coupling simulation models from three different domains: flight performance calculation employing the base of aircraft data (BADA), jet engine performance using the software Gasturb and aircraft noise simulations based on the software sonAIR. Two different concepts of holding approach procedures are investigated, namely, the vertical holding stack and the linear hold point merge. The study is conducted considering generic air traffic scenarios at a single-runway airport. Thereby, the investigated air traffic is based on a statistical analysis of traffic data at existing airports and thus assumed to be representative. As the aircraft’s noise emission depends on both the aircraft and the engine performance, reliable results can be expected only if all individual challenges and interdependencies are accounted for simultaneously. Addressing this challenge is the main contribution of the presented work. The presented results show the plausibility of the proposed multi-level simulation framework, thus supporting its use to investigate the environmental noise impact of air traffic scenarios.

Specific features of the human body, such as fingerprint, iris, and face, are extensively used in biometric authentication. Conversely, the internal structure and material features of the body have not been explored extensively in biometrics. Bioacoustics technology is suitable for extracting information about the internal structure and biological and material characteristics of the human body. Herein, we report a biometric authentication method that enables multichannel bioacoustic signal acquisition with a systematic approach to study the effects of selectively distilled frequency features, increasing the number of sensing channels with respect to multiple fingers. The accuracy of identity recognition according to the number of sensing channels and the number of selectively chosen frequency features was evaluated using exhaustive combination searches and forward-feature selection. The technique was applied to test the accuracy of machine learning classification using 5,232 datasets from 54 subjects. By optimizing the scanning frequency and sensing channels, our method achieved an accuracy of 99.62%, which is comparable to existing biometric methods. Overall, the proposed biometric method not only provides an unbreakable, inviolable biometric but also can be applied anywhere in the body and can substantially broaden the use of biometrics by enabling continuous identity recognition on various body parts for biometric identity authentication.

Relative fundamental frequency (RFF) is an acoustic measure that characterizes changes in voice fundamental frequency during voicing transitions. Despite showing promise as an indicator of vocal disorder and laryngeal muscle tension, the clinical adoption of RFF remains challenging, partly due to a lack of research integration. As such, this review sought to provide summative information and highlight next steps for the clinical implementation of RFF. A systematic literature search was completed across 5 databases, yielding 37 articles that met inclusion criteria. Studies most often included adults with and without tension-based voice disorders (e.g., muscle tension dysphonia), though patient and control groups were directly compared in only 32% of studies. Only 11% of studies tracked therapeutic progress, making it difficult to understand how RFF can be used as a clinical outcome. Specifically, there is evidence to support within-person RFF tracking as a clinical outcome, but more research is needed to understand how RFF correlates to auditory-perceptual ratings (strain, effort, and overall severity of dysphonia) both before and after therapeutic interventions. Finally, a marked increase in the use of automated estimation methods was noted since 2016, yet there remains a critical need for a universally available algorithm to support widespread clinical adoption.

The paper presents the sound absorption coefficient of acoustic absorbers fabricated from natural durian husk fibers, which are currently still considered as agricultural wastes, especially in Malaysia. Samples were fabricated with different fiber densities and thicknesses and the sound absorption performance was measured using the impedance tube method. The results reveal that the durian husk fibers can have absorption coefficient of more than 0.5 above 1 kHz for a minimum thick sample of 20 mm and with minimum density of 160 kg/m3. The optimised macroscopic parameters for various densities were calculated using the inverse method employing the well-known Johnson-Champoux-Allard (JCA) model for porous material.

Wireless power transfer provides a most convenient solution to charge devices remotely and without contacts. R&D has advanced the capabilities, variety, and maturity of solutions greatly in recent years. This survey provides a comprehensive overview of the state of the art on different technological concepts, including electromagnetic coupled and uncoupled systems and acoustic technologies. Solutions to transfer mW to MW of power, over distances ranging from millimeters to kilometers, and exploiting wave concepts from kHz to THz, are covered. It is an attractive charging option for many existing applications and moreover opens new opportunities. Various technologies are proposed to provide wireless power to these devices. The main challenges reside in the efficiency and range of the transfer. We highlight innovation in beamforming and UV-assisted approaches. Of particular interest for designers is the discussion of implementation and operational aspects, standards, and safety relating to regulations. A high-level catalog of potential applications maps these to adequate technological options for wireless power transfer.

Driven by reproductive motives, male African elephants (Loxodonta africana) in musth often expand their home ranges to locate estrous females. This extended range, coupled with heightened aggression often observed in musth males, can be particularly problematic in regions where human-modified landscapes and elephant territories increasingly overlap. Several mitigation tools have been tested to resolve a wide range of human–elephant conflicts with varying degrees of success due to geographical disparities and habituation. We present findings on the potential application of estrous call playbacks in manipulating the behavior and movement of male elephants non-invasively, particularly mature musth adults and younger post-dispersal males, in Etosha National Park. Estrous vocalizations were presented across 26 experimental trials to mature musth adults (n = 5), mature non-musth adults (n = 6), and non-musth males belonging to younger, post-dispersal age classes (n = 8), with behavioral responses scored on a gradient scale from 0–1. Both mature musth adults and younger non-musth elephants were significantly more likely to respond with the highest intensity by approaching the acoustic source compared to mature non-musth adults that avoided the call. However, younger males tested in the presence of an older, higher-ranking male tended to react with a lower intensity than those tested alone. This result likely demonstrates the influence of social hierarchy and associations on male elephant behavior. We also observed a significant increase in physiological response, measured by defecation rate, across all male groups in response to the estrous call playbacks. Our findings suggest that using estrous calls as acoustic deterrents may effectively and non-invasively aid in reducing tension at the human–elephant interface, depending on the age, social context, and reproductive status of the male elephant.

The acoustic evaluation of indoor environments is common in the application of virtual acoustics. In addition, in the study of cultural heritage buildings, it is a useful tool, but it is not so common when describing the acoustic environment in intangible cultural heritage events and even in outdoor environments. In this paper, the acoustic environment of the Water Tribunal of the Plain of Valencia (Spain) is studied. It is analyzed from a soundscape perspective, characterizing the sound source and evaluating it within relation to the environment and evaluating its subjective response. With the research carried out, it has been obtained, on the one hand, a complete study of the acoustics of the environment of the Water Tribunal and, on the other, an enhancement of the Valencian tangible and intangible heritage.

Microrobots can operate in tiny areas that traditional bulk robots cannot reach. The combination of acoustic actuation with microrobots extensively expands the application areas of microrobots due to their desirable miniaturization, flexibility, and biocompatibility features. Herein, an overview of the research and development of acoustics-actuated microrobots is provided. We first introduce the currently established manufacturing methods (3D printing and photolithography). Then, according to their different working principles, we divide acoustics-actuated microrobots into three categories including bubble propulsion, sharp-edge propulsion, and in-situ microrotor. Next, we summarize their established applications from targeted drug delivery to microfluidics operation to microsurgery. Finally, we illustrate current challenges and future perspectives to guide research in this field. This work not only gives a comprehensive overview of the latest technology of acoustics-actuated microrobots, but also provides an in-depth understanding of acoustic actuation for inspiring the next generation of advanced robotic devices.