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Monitoring the defects generated during metal additive manufacturing is crucial for maintaining high manufacturing quality and extending the applications of this technology to various industries. In this study, balling defect generation was studied through the experimental investigation of directed energy deposition (DED) of Inconel 718 alloy on stainless steel. The relationships of deposition size and balling defects with audible sound were analyzed. Microelectromechanical systems microphones were installed around the Inconel 718 deposition spot to collect audible sound signals. Moreover, a high-speed optical camera and a thermal camera were used to collect real-time optical and thermal images, respectively, during deposition. The results of this study indicate that the surface energy of the liquid metal in DED has a crucial effect on the geometry of the melt pool. The accumulation of melt material because of the surface energy causes a shift in the deposition position away from the front edge of previously deposited material and is the primary factor causing balling defects. Sound signal analysis confirmed strong correlations between the features of audible sound and the melt volume in single-point deposition experiments. The relationships between the features of audible sound and balling defects were also determined. The time and frequency features of collected audible sound signals can be used to identify the generation of balling defects in the DED of Inconel 718. [ABSTRACT FROM AUTHOR]

Most research on sonoluminescence and sonochemistry has been conducted at acoustic frequencies above ∼20 kHz. Consequently, mathematical models for the dynamics of acoustically-driven bubbles have hardly been examined in the audible frequency spectrum. Here, we develop a new hybrid modelling approach that combines the rigour of the advection–diffusion model whilst retaining the simplicity of a reduced-order boundary layer model to predict phase-change, mass and heat transfer in an inertially collapsing bubble excited by audible sound. Differences in these approaches are explored through a thorough validation against experimental data obtained from ultra-high speed videos of bubble dynamics at 17.8 kHz. Our results indicate that, while the boundary layer model agrees well with the advection–diffusion model at high driving frequencies, there are significant deviations at lower frequencies, where the boundary layer model overpredicts parameters such as bubble size and quantity of trapped vapour while underpredicting others such as temperature and pressure. These deviations at lower frequencies is caused by an inaccurate estimation of the boundary layer thickness originating from the time-scale competition between diffusion and fast bubble wall motion. Our work questions the suitability of existing reduced-order models developed for ultrasonic frequencies when applied to the audible range, reinforcing that further research in the audible range is needed.

• First systematic exploration of single bubble dynamics in the audible range. • Boundary layer model diverges from advection–diffusion equation at low frequencies. • Deviations caused by inaccurate estimation of boundary layer thickness. • Proposed hybrid model combines rigour of advection–diffusion equation with of reduced-order models. • Study reinforces need for further research within the audible range. Most research on sonoluminescence and sonochemistry has been conducted at acoustic frequencies above ∼ 20 kHz. Consequently, mathematical models for the dynamics of acoustically-driven bubbles have hardly been examined in the audible frequency spectrum. Here, we develop a new hybrid modelling approach that combines the rigour of the advection–diffusion model whilst retaining the simplicity of a reduced-order boundary layer model to predict phase-change, mass and heat transfer in an inertially collapsing bubble excited by audible sound. Differences in these approaches are explored through a thorough validation against experimental data obtained from ultra-high speed videos of bubble dynamics at 17.8 kHz. Our results indicate that, while the boundary layer model agrees well with the advection–diffusion model at high driving frequencies, there are significant deviations at lower frequencies, where the boundary layer model overpredicts parameters such as bubble size and quantity of trapped vapour while underpredicting others such as temperature and pressure. These deviations at lower frequencies is caused by an inaccurate estimation of the boundary layer thickness originating from the time-scale competition between diffusion and fast bubble wall motion. Our work questions the suitability of existing reduced-order models developed for ultrasonic frequencies when applied to the audible range, reinforcing that further research in the audible range is needed. [ABSTRACT FROM AUTHOR]

Abstract Background The emergence of antibiotic-resistant microorganisms has been largely associated with drug misuse, drug abuse, and indiscriminate disposal of drugs; however, the interactions between some environmental factors and antibiotic resistance by microorganisms have been understudied. In this study, the effects of sound and electromagnetic field on the growth and antibiotic susceptibility of selected microorganisms to antibiotics were investigated. Results Microorganisms used include Gluconobacter oxydans ATCC 19,357, Rhodobacter sphaeroides ATCC 17,023, Citrobacter freundii ATCC 33,128, Yersina pestis ATCC 11,953, Bacillus subtilis 6633, Acetobacter aceti ATCC 15,973, Escherichia coli ATCC 25,922, Pseudomonas aeuriginosa ATCC 9027, Streptococcus pyogenes ATCC 19,613, Klebsiella pneumonia ATCC 25,955, Staphylococcus aureus ATCC 25,923 and Serratia marcescens ATCC 14,766. The antibiotics used were: Ciprofloxacin 5 μg, Imipenem 10 μg, Ampicillin 10 μg, Ceftazidime 30 μg and Tetracycline 30 μg for Gram-negative bacteria while Pefloxacin 10 μg, Gentamycin 10 μg, Amplicillin + Cloxacillin 30 μg, Cefuroxime 20 μg, Amoxacillin 30 μg, Ceftriaxone 25 μg, Ciprofloxacin 10 μg, Streptomycin 30 μg, Co-trimoxazole 30 μg, and Erythromycin 10 μg for Gram-positive bacteria, respectively. Acoustic treatment had varying effects on the antibiotics susceptibility profile of all test bacterial culture. Before exposure, P. aeruginosa had the highest zone of inhibition of 34 ± 3.4 mm, while B. subtilis had least inhibition zone of 12 ± 2.8. After exposure to acoustic treatment at 5000 Hz/90 dB at 72 h, C. freundii had highest zone of inhibition of 32 ± 0.7 mm and the least zone of 11 ± 1.4 mm observed in P. aeruginosa. At 1125 Hz/80 dB after 72 h, R. sphaeroides had highest zone of 34 ± 0.7 mm while A. aceti had least zone of inhibition of 10 ± 0 mm. Effect of electromagnetic flux treatment of 15 min showed E. coli to be the most inhibited having a growth rate of 0.08 log cfu/mL, antibiotics testing showed G. oxydans to have the highest zone of inhibition of 28 ± 3.5 mm and least zone was observed in B. subtilis having a zone of 13 ± 2.8 mm. Conclusion This study showed that environmental factor such as sound and electromagnetic flux (EMF) could interfere with the physiology of bacteria including resistance/susceptibility to antibiotics. However, further investigation will be needed to understand full mechanisms of action of sound and electromagnetic field on bacteria.

In microlap welding, a real-time welding quality monitoring system is crucial to the identification of low strength joints caused by the unreliable contact between two layers of stainless metal sheets. In this study, a multispacing configured microphone array filter was designed and applied to a sound-based quality monitoring system for laser microlap welding, and the filter's performance was evaluated to improve the reliability of the developed monitoring system when collected sound signals are contaminated by the noises generated around a welding site. In the experimental setup, joint strength was modulated by controlling the clamping conditions of the fixture and changing the welding location. The results indicated that noises contaminated the signals obtained from single microphones and reduced classification rates by up to 25% when time domain features were adopted. Through the application of the proposed microphone array in the developed monitoring system, the classification rate of weld quality can be improved to a level resembling that observed when artificial noise is not applied to the system. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effect of sound wave exposure in different photoperiods on Synechococcus HS-9 cell density and lipid content using tubular photobioreactors (PBRs). In this study, nine PBRs were used: three PBRs were exposed to a sine wave of 279.9 Hz for three hours during the day (A), three PBRs were exposed to a sine wave of 279.9 Hz for three hours during the night (B), and three PBRs remained unexposed to any sound wave to serve as a control (K). All PBRs were studied for 18 days. The results showed that the highest average cell densities of Synechococcus HS-9 in PBR A, B, and K respectively were 8.883×105 cells/mL, 7.242×105 cells/mL, and 6.175×105 cells/mL. The highest lipid percentage, which was 17%, was observed in PBR A; the percentage in PBR B was 16%, and in PBR K, 7%. However, Synechococcus HS-9 in PBR B showed a higher growth rate compared to PBR A and PBR K. Sound waves could have increased cell activity and metabolism which led to the increase in cell densities and lipid percentages in Synechococcus HS-9. The photoperiodic differences might have resulted in a lower photosynthetic rate and cell metabolism, but the sound wave could have helped promote the growth of Synechococcus HS-9 despite the lower photosynthetic rate.

Background: The emergence of antibiotic-resistant microorganisms has been largely associated with drug misuse, drug abuse, and indiscriminate disposal of drugs; however, the interactions between some environmental factors and antibiotic resistance by microorganisms have been understudied. In this study, the effects of sound and electromagnetic field on the growth and antibiotic susceptibility of selected microorganisms to antibiotics were investigated. Results: Microorganisms used include Gluconobacter oxydans ATCC 19,357, Rhodobacter sphaeroides ATCC 17,023, Citrobacter freundii ATCC 33,128, Yersina pestis ATCC 11,953, Bacillus subtilis 6633, Acetobacter aceti ATCC 15,973, Escherichia coli ATCC 25,922, Pseudomonas aeuriginosa ATCC 9027, Streptococcus pyogenes ATCC 19,613, Klebsiella pneumonia ATCC 25,955, Staphylococcus aureus ATCC 25,923 and Serratia marcescens ATCC 14,766. The antibiotics used were: Ciprofloxacin 5 μg, Imipenem 10 μg, Ampicillin 10 μg, Ceftazidime 30 μg and Tetracycline 30 μg for Gram-negative bacteria while Pefloxacin 10 μg, Gentamycin 10 μg, Amplicillin + Cloxacillin 30 μg, Cefuroxime 20 μg, Amoxacillin 30 μg, Ceftriaxone 25 μg, Ciprofloxacin 10 μg, Streptomycin 30 μg, Co-trimoxazole 30 μg, and Erythromycin 10 μg for Gram-positive bacteria, respectively. Acoustic treatment had varying effects on the antibiotics susceptibility profile of all test bacterial culture. Before exposure, P. aeruginosa had the highest zone of inhibition of 34 ± 3.4 mm, while B. subtilis had least inhibition zone of 12 ± 2.8. After exposure to acoustic treatment at 5000 Hz/90 dB at 72 h, C. freundii had highest zone of inhibition of 32 ± 0.7 mm and the least zone of 11 ± 1.4 mm observed in P. aeruginosa. At 1125 Hz/80 dB after 72 h, R. sphaeroides had highest zone of 34 ± 0.7 mm while A. aceti had least zone of inhibition of 10 ± 0 mm. Effect of electromagnetic flux treatment of 15 min showed E. coli to be the most inhibited having a growth rate of 0.08 log cfu/mL, antibiotics testing showed G. oxydans to have the highest zone of inhibition of 28 ± 3.5 mm and least zone was observed in B. subtilis having a zone of 13 ± 2.8 mm. Conclusion: This study showed that environmental factor such as sound and electromagnetic flux (EMF) could interfere with the physiology of bacteria including resistance/susceptibility to antibiotics. However, further investigation will be needed to understand full mechanisms of action of sound and electromagnetic field on bacteria. [ABSTRACT FROM AUTHOR]

Electromagnetic interactions between conventional earphones and the electroencephalography (EEG) electrodes used for analyzing brain waves give rise to efficiency problems in neurophysiological studies of auditory perception. Currently used speakers and headphones are electromagnetic devices based on strong magnets. In spite of intensive use of such systems, there has been no effective way to eliminate the electromagnetic artifacts produced by such audio transmitting devices to date. The ability for transferring audible sounds without the use of electromagnetic devices that can affect the EEG signal would open up many innovative possibilities in Audio Technologies. Audible sound transfer over long distances is possible by the photoacoustic effect. In such studies, the modulated optical signal can be converted into an audible signal arising from the absorption of the light energy of relevant molecules. In this study, we propose an earphone based on the photoacoustic effect, and calculated the dB SPL (Sound Pressure Level) values for a spherical cell filled with olive pomace. By the use of the method of Diebold and Westervelt, we theoretically calculated the sound pressure levels for our cell and determined a 60 dB SPL at a sound frequency of 1000 Hz for our preliminary earphone design.

Objective: We aim to examine the existing literature on, and identify knowledge gaps in, the study of adverse animal and human audiovestibular effects from exposure to acoustic or electromagnetic waves that are outside of conventional human hearing.Design/Setting/Participants: A review was performed, which included searches of relevant MeSH terms using PubMed, Embase, and Scopus. Primary outcomes included documented auditory and/or vestibular signs or symptoms in animals or humans exposed to infrasound, ultrasound, radiofrequency, and magnetic resonance imaging. The references of these articles were then reviewed in order to identify primary sources and literature not captured by electronic search databases.Results: Infrasound and ultrasound acoustic waves have been described in the literature to result in audiovestibular symptomology following exposure. Technology emitting infrasound such as wind turbines and rocket engines have produced isolated reports of vestibular symptoms, including dizziness and nausea and auditory complaints, such as tinnitus following exposure. Occupational exposure to both low frequency and high frequency ultrasound has resulted in reports of wide-ranging audiovestibular symptoms, with less robust evidence of symptomology following modern-day exposure via new technology such as remote controls, automated door openers, and wireless phone chargers. Radiofrequency exposure has been linked to both auditory and vestibular dysfunction in animal models, with additional historical evidence of human audiovestibular disturbance following unquantifiable exposure. While several theories, such as the cavitation theory, have been postulated as a cause for symptomology, there is extremely limited knowledge of the pathophysiology behind the adverse effects that particular exposure frequencies, intensities, and durations have on animals and humans. This has created a knowledge gap in which much of our understanding is derived from retrospective examination of patients who develop symptoms after postulated exposures.Conclusion and Relevance: Evidence for adverse human audiovestibular symptomology following exposure to acoustic waves and electromagnetic energy outside the spectrum of human hearing is largely rooted in case series or small cohort studies. Further research on the pathogenesis of audiovestibular dysfunction following acoustic exposure to these frequencies is critical to understand reported symptoms.

Sound waves could improve the growth and increase yield. However, it could be a form of environmental stress. Therefore, the aim of this study was to investigate the effects of audible sound on the growth and endogenous hormones of strawberry plants (Fragaria_ananassa). Five endogenous hormones, namely Indole-3-acetic Acid (IAA), Gibberellin (GA), Abscisic Acid (ABA), Jasmonic acid (JA) and Zeatin Riboside (ZR) have been investigated. Plants were exposed to sound frequency of 0.1 - 1 kHz and sound pressure level (SPL) of 70 - 100 dB for 2 hours, 3 hours and 5 hours at different growth stages. Results revealed that plants had different responses to sound waves at different growth stages. Acoustic frequency could accelerate the blooming and the flowering rates in a short run. In contrast, exposing plants to sound for more than 3 hours per day for a long run more than 40 days could inhibit the growth. However, sound treatment could significantly accelerate the blooming and the flowering rates. The maximum concentration of ABA was in leaves of the treated plants for 90 days, each day for 5 hours. Whereas, mean of IAA levels in leaves of control plants was insignificantly higher than those of the treated plants for 5 hours and 2 hours after 90 days of sound treatment. Moreover, no significant difference was found in the concentration of JA in leaves between all treated plants and control plants after 75 and 90 days. In conclusion, audible sound could stimulate or inhibit the growth of strawberry plants. [ABSTRACT FROM AUTHOR]

Objective: We aim to examine the existing literature on, and identify knowledge gaps in, the study of adverse animal and human audiovestibular effects from exposure to acoustic or electromagnetic waves that are outside of conventional human hearing. Design/Setting/Participants: A review was performed, which included searches of relevant MeSH terms using PubMed, Embase, and Scopus. Primary outcomes included documented auditory and/or vestibular signs or symptoms in animals or humans exposed to infrasound, ultrasound, radiofrequency, and magnetic resonance imaging. The references of these articles were then reviewed in order to identify primary sources and literature not captured by electronic search databases. Results: Infrasound and ultrasound acoustic waves have been described in the literature to result in audiovestibular symptomology following exposure. Technology emitting infrasound such as wind turbines and rocket engines have produced isolated reports of vestibular symptoms, including dizziness and nausea and auditory complaints, such as tinnitus following exposure. Occupational exposure to both low frequency and high frequency ultrasound has resulted in reports of wide-ranging audiovestibular symptoms, with less robust evidence of symptomology following modern-day exposure via new technology such as remote controls, automated door openers, and wireless phone chargers. Radiofrequency exposure has been linked to both auditory and vestibular dysfunction in animal models, with additional historical evidence of human audiovestibular disturbance following unquantifiable exposure. While several theories, such as the cavitation theory, have been postulated as a cause for symptomology, there is extremely limited knowledge of the pathophysiology behind the adverse effects that particular exposure frequencies, intensities, and durations have on animals and humans. This has created a knowledge gap in which much of our understanding is derived from retrospective examination of patients who develop symptoms after postulated exposures. Conclusion and Relevance: Evidence for adverse human audiovestibular symptomology following exposure to acoustic waves and electromagnetic energy outside the spectrum of human hearing is largely rooted in case series or small cohort studies. Further research on the pathogenesis of audiovestibular dysfunction following acoustic exposure to these frequencies is critical to understand reported symptoms. [ABSTRACT FROM AUTHOR]

This study focused on correlation analysis between welding quality and sound-signal features collected during microlaser welding. The study provides promising features for developing a monitoring system that detects low joint strength caused by a gap between metal sheets after welding. To obtain sound signals for signal analysis and develop the monitoring system, experiments for laser microlap welding were conducted on a laser microwelding platform by installing a microelectromechanical system (MEMS) microphone away from the welding point, and an acoustic emission (AE) sensor on the fixture. The gap between two metal sheet layers was controlled using clamp force, a pressing bar, and the appropriate installation of a thin piece of paper between the metal sheets. After sound signals from the microphone were collected, the correlation between features of time-domain sound signals and of welding quality was analyzed by categorizing the referred signals into eight sections during welding. After appropriately generating the features after signal analysis and selecting the most promising features for low-joint-strength monitoring on the basis of scatter index J, a hidden Markov model (HMM)-based classifier was applied to evaluate the performance of the selected sound-signal features. Results revealed that three sound-signal features were closely related to joint-strength variation caused by the gap between two metal-sheet layers: (1) the root-mean-square (RMS) value of the first section of sound signals, (2) the standard deviation of the first section of sound signals, and (3) the standard deviation to the RMS ratio of the second section of sound signals. In system evaluation, a 100% classification rate was obtained for normal and low-bonding-strength monitoring when the HMM-based classifier was developed on the basis of the three selected features. [ABSTRACT FROM AUTHOR]

Today, the quality of welded seams is often examined off-line with either destructive or non-destructive testing. These test procedures are time-consuming and therefore costly. This is especially true if the welds are not welded accurately due to process anomalies. In manual welding, experienced welders are able to detect process anomalies by listening to the sound of the welding process. In this paper, an approach to transfer the “hearing” of an experienced welder into an automated testing process is presented. An acoustic measuring device for recording audible sound is installed for this purpose on a fully automated welding fixture. The processing of the sound information by means of machine learning methods enables in-line process control. Existing research results until now show that the arc is the main sound source. However, both the outflow of the shielding gas and the wire feed emit sound information. Other investigations describe welding irregularities by evaluating and assessing existing sound recordings. Descriptive analysis was performed to find a connection between certain sound patterns and welding irregularities. Recent contributions have used machine learning to identify the degree of welding penetration. The basic assumption of the presented investigations is that process anomalies are the cause of welding irregularities. The focus was on detecting deviating shielding gas flow rates based on audio recordings, processed by a convolutional neural network (CNN). After adjusting the hyperparameters of the CNN it was capable of distinguishing between different flow rates of shielding gas.

Physico-stimulant like audible sound is one of the new promising methods for enhancing microalgae growth rate. Here, microalgae Haematococcus pluvialis was cultivated with the addition of audible sound with titles “Blues for Elle” and “Far and Wide.” The objective of this research was to evaluate the effect of audible sound to the growth and productivity of microalgae. The experiment has been conducted by exposing the audible sound for 8 h in 22 days to microalgae cultivation. The result showed that microalgae H. pluvialis treated by the music “Blues for Elle” shows the highest growth rate (0.03 per day), and 58% higher than the one without audible sound. The average number of cells in stationary phase is 0.76 × 104 cells/mL culture and the productivity is 3.467 × 102 cells/mL/day. The pH of microalgae medium slightly decreases because of proton production during photosynthesis process. The kinetic rate constant (kapp) is 0.078 per day, reaction half-life (t1/2) is 8.89 days, and catalytic surface (Ksurf) is 1.66 × 10−5/day/cm2. In conclusion, this audible sound is very useful to stimulate microalgae growth rate, especially H. pluvialis.

Bubbles are important for carbonated beverage quality since smaller bubbles contribute to higher acceptability. Therefore, the effects and acceptability of the application of audible sound in carbonated water were studied using three brands and applying five frequencies for one minute each in ascending order. Six samples, two from each brand, were used for treatments: (i) control and (ii) sonication. Physicochemical measurements consisted of total dissolved solids (TDS), electric conductivity (EC), pH, bubble size, and bubble size distribution. A sensory session (N = 30) was conducted using the Bio-Sensory application to assess acceptability and emotions using self-reported and biometric responses. Statistical analysis included: ANOVA (ff = 0.05) and principal component analysis (PCA) for quantitative data and Cochran Q test with pairwise comparisons (p < 0.05) for self-reported emotion responses. Results showed that the sonication effect for the sample with higher TDS, EC, and pH (SPS) reduced bubble size by 46%, while in those with lowest TDS, EC, and pH (IceS) caused an increase of 158% compared to the control. For samples with intermediate values (NuS), there were non-significant differences (p > 0.05) compared to the control. Acceptability was higher for samples with sonication for the three brands. Emotional self-reported responses were more positive for samples with sonication, showing significant differences (p < 0.05) for emotions such as "happy" and "pleased" during both sound and visual assessments. From PCA, a positive relationship between bubble size and liking of bubbles was found as well as for the number of medium bubbles and happy facial expression. The audible sound generated by ubiquitous sound systems may potentially be used by the industry, applying it to the bottled product to modify bubble size and improve quality and acceptability of carbonated beverages. [ABSTRACT FROM AUTHOR]

This study focused on correlation analysis between welding quality and sound-signal features collected during microlaser welding. The study provides promising features for developing a monitoring system that detects low joint strength caused by a gap between metal sheets after welding. To obtain sound signals for signal analysis and develop the monitoring system, experiments for laser microlap welding were conducted on a laser microwelding platform by installing a microelectromechanical system (MEMS) microphone away from the welding point, and an acoustic emission (AE) sensor on the fixture. The gap between two metal sheet layers was controlled using clamp force, a pressing bar, and the appropriate installation of a thin piece of paper between the metal sheets. After sound signals from the microphone were collected, the correlation between features of time-domain sound signals and of welding quality was analyzed by categorizing the referred signals into eight sections during welding. After appropriately generating the features after signal analysis and selecting the most promising features for low-joint-strength monitoring on the basis of scatter index J, a hidden Markov model (HMM)-based classifier was applied to evaluate the performance of the selected sound-signal features. Results revealed that three sound-signal features were closely related to joint-strength variation caused by the gap between two metal-sheet layers: (1) the root-mean-square (RMS) value of the first section of sound signals, (2) the standard deviation of the first section of sound signals, and (3) the standard deviation to the RMS ratio of the second section of sound signals. In system evaluation, a 100% classification rate was obtained for normal and low-bonding-strength monitoring when the HMM-based classifier was developed on the basis of the three selected features.

Physico-stimulant like audible sound is one of the new promising methods for enhancing microalgae growth rate. Here, microalgae Haematococcus pluvialis was cultivated with the addition of audible sound with titles “Blues for Elle” and “Far and Wide.” The objective of this research was to evaluate the effect of audible sound to the growth and productivity of microalgae. The experiment has been conducted by exposing the audible sound for 8 h in 22 days to microalgae cultivation. The result showed that microalgae H. pluvialis treated by the music “Blues for Elle” shows the highest growth rate (0.03 per day), and 58% higher than the one without audible sound. The average number of cells in stationary phase is 0.76 × 104 cells/mL culture and the productivity is 3.467 × 102 cells/mL/day. The pH of microalgae medium slightly decreases because of proton production during photosynthesisprocess. The kinetic rate constant (kapp) is 0.078 per day, reaction half-life (t1/2) is 8.89 days, and catalytic surface (Ksurf) is 1.66 × 10−5/day/cm2. In conclusion, this audible sound is very useful to stimulate microalgae growth rate, especially H. pluvialis.

The use of ultrasounds has been implemented to increase yeast viability, de-foaming, and cavitation in foods and beverages. However, the application of low frequency audible sound to decrease bubble size and improve foamability has not been explored. In this study, three treatments using India Pale Ale beers were tested, which include (1) a control, (2) the application of audible sound during fermentation, and (3) the application of audible sound during natural carbonation. Five different audible frequencies (20 Hz, 30 Hz, 45 Hz, 55 Hz, and 75 Hz) were applied daily for one minute each (starting from the lowest frequency) during fermentation (11 days, treatment 2) and carbonation (22 days, treatment 3). Samples were measured in triplicates using the RoboBEER to assess color and foam-related parameters. A trained panel (n = 10) evaluated the intensity of sensory descriptors. Results showed that samples with sonication treatment had significant differences in the number of small bubbles, alcohol, and viscosity compared to the control. Furthermore, except for foam texture, foam height, and viscosity, there were non-significant differences in the intensity of any sensory descriptor, according to the rating from the trained sensory panel. The use of soundwaves is a potential treatment for brewing to improve beer quality by increasing the number of small bubbles and foamability without disrupting yeast or modifying the aroma and flavor profile. [ABSTRACT FROM AUTHOR]

Due to the demands of Computer-Integrated Manufacturing (CIM), the Tool Condition Monitoring (TCM) system, as a major component of CIM, is essential to improve the production quality, optimize the labor and maintenance costs, and minimize the manufacturing loses with the increase in productivity. To look for a reliable, efficient, and cost-effective solution, various monitoring systems employing different types of sensing techniques have been developed to detect the tool conditions as well as to monitor the abnormal cutting states. This paper explores the use of audible sound signals as sensing approach to detect the cutting tool wear and failure during end milling operation by using the Support Vector Machine (SVM) learning model as a decision-making algorithm. In this study, sound signals collected during the machining process are analyzed through frequency domain to extract signal features that correlate actual cutting phenomenon. The SVM method seeks to provide a linguistic model for tool wear estimation from the knowledge embedded in this machine learning approach. The performance evaluation results of the proposed algorithm have shown accurate predictions in detecting tool wear under various cutting conditions with rapid response rate, which provides the good solution for in-process TCM. In addition, the proposed monitoring system trained with sufficient signals collected from different positions has been proved to be position independent to monitor the tool wear conditions. [ABSTRACT FROM AUTHOR]

Bubbles are important for carbonated beverage quality since smaller bubbles contribute to higher acceptability. Therefore, the effects and acceptability of the application of audible sound in carbonated water were studied using three brands and applying five frequencies for one minute each in ascending order. Six samples, two from each brand, were used for treatments: (i) control and (ii) sonication. Physicochemical measurements consisted of total dissolved solids (TDS), electric conductivity (EC), pH, bubble size, and bubble size distribution. A sensory session (N = 30) was conducted using the Bio-Sensory application to assess acceptability and emotions using self-reported and biometric responses. Statistical analysis included: ANOVA (α = 0.05) and principal component analysis (PCA) for quantitative data and Cochran Q test with pairwise comparisons (p < 0.05) for self-reported emotion responses. Results showed that the sonication effect for the sample with higher TDS, EC, and pH (SPS) reduced bubble size by 46%, while in those with lowest TDS, EC, and pH (IceS) caused an increase of 158% compared to the control. For samples with intermediate values (NuS), there were non-significant differences (p > 0.05) compared to the control. Acceptability was higher for samples with sonication for the three brands. Emotional self-reported responses were more positive for samples with sonication, showing significant differences (p < 0.05) for emotions such as “happy” and “pleased” during both sound and visual assessments. From PCA, a positive relationship between bubble size and liking of bubbles was found as well as for the number of medium bubbles and happy facial expression. The audible sound generated by ubiquitous sound systems may potentially be used by the industry, applying it to the bottled product to modify bubble size and improve quality and acceptability of carbonated beverages.

Physico-stimulant like audible sound is one of the new promising methods for enhancing microalgae growth rate. Here, microalgae Haematococcus pluvialis was cultivated with the addition of audible sound with titles “Blues for Elle” and “Far and Wide.” The objective of this research was to evaluate the effect of audible sound to the growth and productivity of microalgae. The experiment has been conducted by exposing the audible sound for 8 h in 22 days to microalgae cultivation. The result showed that microalgae H. pluvialis treated by the music “Blues for Elle” shows the highest growth rate (0.03 per day), and 58% higher than the one without audible sound. The average number of cells in stationary phase is 0.76 × 10 4 cells/mL culture and the productivity is 3.467 × 10 2 cells/mL/day. The pH of microalgae medium slightly decreases because of proton production during photosynthesis process. The kinetic rate constant (k app ) is 0.078 per day, reaction half-life (t 1/2 ) is 8.89 days, and catalytic surface (K surf ) is 1.66 × 10 − 5 /day/cm 2 . In conclusion, this audible sound is very useful to stimulate microalgae growth rate, especially H. pluvialis . [ABSTRACT FROM AUTHOR]

The use of ultrasounds has been implemented to increase yeast viability, de-foaming, and cavitation in foods and beverages. However, the application of low frequency audible sound to decrease bubble size and improve foamability has not been explored. In this study, three treatments using India Pale Ale beers were tested, which include (1) a control, (2) the application of audible sound during fermentation, and (3) the application of audible sound during natural carbonation. Five different audible frequencies (20 Hz, 30 Hz, 45 Hz, 55 Hz, and 75 Hz) were applied daily for one minute each (starting from the lowest frequency) during fermentation (11 days, treatment 2) and carbonation (22 days, treatment 3). Samples were measured in triplicates using the RoboBEER to assess color and foam-related parameters. A trained panel (n = 10) evaluated the intensity of sensory descriptors. Results showed that samples with sonication treatment had significant differences in the number of small bubbles, alcohol, and viscosity compared to the control. Furthermore, except for foam texture, foam height, and viscosity, there were non-significant differences in the intensity of any sensory descriptor, according to the rating from the trained sensory panel. The use of soundwaves is a potential treatment for brewing to improve beer quality by increasing the number of small bubbles and foamability without disrupting yeast or modifying the aroma and flavor profile.

The paper presents the results of experimental gas metal arc welding. Namely, this welding process is commonly used in the automation and robotization of fusion welding, where adaptive regulation is indispensable. In addition to variable welding voltage and current, a distinctive characteristic of arc welding processes are also the pressure of audible sound phenomena which reflect the variable conditions in the arc to the highest extent. It follows that it is reasonable to monitor these phenomena and that the results can be used for the implementation of adaptive welding process control. [ABSTRACT FROM AUTHOR]

Abstract: Audible sound, one of the environmental factors, widely exists in natural world. However, the interaction between audible sound and biological materials is usually neglected in the field of biological research. Very little efforts have been put forth in studying the relation of organisms and audible sound. Here we investigated the response of Escherichia coli cells to the stimulation by audible sound under the normal condition and environmental stresses. The results showed that the audible sound treatment significantly increases the colony forming of E. coli under the normal growth condition. However, under osmotic stress induced by the sugar, audible sound stimulation may enhance the inhibitory effect of osmotic stress on E. coli growth. More interestingly, audible sound treatment seems to alleviate the inhibitory effect of salt stress on E. coli growth when the concentration of sodium chloride was increased to 30g/l, although the action of sound waves of audible frequency is likely to evoke an inhibition of the growth of E. coli in the medium containing 20g/l of sodium chloride. Some potential mechanisms may be involved in the responses of bacterial cells to audible sound stimulation. [Copyright &y& Elsevier]

Abstract: In this paper, audible sounds during keyhole and conduction laser welding were analyzed. The characteristic signals representing good welding quality was from 10 to 20kHz. The more the welded metal vaporizes, the higher the plasma temperature and the stronger the acoustic signals. Furthermore, keyhole shape also affected the acoustic signal intensities. Then time domain, frequency domain and wavelet analysis methods were used to analyze the acoustic signals. It was proved that frequency distributions are a better way to identify welding defects. The wavelet analysis results showed that the intensity of low frequency (<781Hz) components of the sound signals decreased dramatically when welding defects occurred. At the end, an artificial neural network (ANN) was constructed to diagnose welding faults. Features extracted from the acoustic signals were input into the ANN. After training, the ANN could be used to identify between normal and abnormal welds. [Copyright &y& Elsevier]

Today, the quality of welded seams is often examined off-line with either destructive or non-destructive testing. These test procedures are time-consuming and therefore costly. This is especially true if the welds are not welded accurately due to process anomalies. In manual welding, experienced welders are able to detect process anomalies by listening to the sound of the welding process. In this paper, an approach to transfer the "hearing" of an experienced welder into an automated testing process is presented. An acoustic measuring device for recording audible sound is installed for this purpose on a fully automated welding fixture. The processing of the sound information by means of machine learning methods enables in-line process control. Existing research results until now show that the arc is the main sound source. However, both the outflow of the shielding gas and the wire feed emit sound information. Other investigations describe welding irregularities by evaluating and assessing existing sound recordings. Descriptive analysis was performed to find a connection between certain sound patterns and welding irregularities. Recent contributions have used machine learning to identify the degree of welding penetration. The basic assumption of the presented investigations is that process anomalies are the cause of welding irregularities. The focus was on detecting deviating shielding gas flow rates based on audio recordings, processed by a convolutional neural network (CNN). After adjusting the hyperparameters of the CNN it was capable of distinguishing between different flow rates of shielding gas. [ABSTRACT FROM AUTHOR]

Pattern-recognition analysis of sound radiation was developed as a basis for monitoring the metal-cutting process. The sound-pressure signals radiated during cutting under fixed conditions were recorded using a sharp tool, a worn tool and a broken tool. A round bar of heat-treated AISI 4340 steel was machined in cylindrical turning, using a titanium-carbide-coated cutting tool. The spectral components in the 0-10 kHz range were used as features. Using resubstitution, signals coming from sharp and worn tools were easily distinguished, resulting in a 100% classification with just two features, being the average of the low (0-5 kHz) and high (5-10 kHz) frequency ranges. With tool breakage, two acceptable classifications were obtained using independent testing, the first with a performance of 100%, 75% and 100% for sharp, worn and breakage signals respectively, using nine features, and the second with 80%, 88% and 80%, using eight features. [ABSTRACT FROM AUTHOR]

Electromagnetic interactions between conventional earphones and the electroencephalography (EEG) electrodes used for analyzing brain waves give rise to efficiency problems in neurophysiological studies of auditory perception. Currently used speakers and headphones are electromagnetic devices based on strong magnets. In spite of intensive use of such systems, there has been no effective way to eliminate the electromagnetic artifacts produced by such audio transmitting devices to date. The ability for transferring audible sounds without the use of electromagnetic devices that can affect the EEG signal would open up many innovative possibilities in Audio Technologies. Audible sound transfer over long distances is possible by the photoacoustic effect. In such studies, the modulated optical signal can be converted into an audible signal arising from the absorption of the light energy of relevant molecules. In this study, we propose an earphone based on the photoacoustic effect, and calculated the dB SPL (Sound Pressure Level) values for a spherical cell filled with olive pomace. By the use of the method of Diebold and Westervelt, we theoretically calculated the sound pressure levels for our cell and determined a 60 dB SPL at a sound frequency of 1000 Hz for our preliminary earphone design., Competing Interests: The authors declare that there are no conflicts of interest., (© 2020 The Authors.)