Ultrasound (US) is an effective intensified extraction technology for natural plant resources, but detailed microscale investigations into US-induced plant cell disintegration are lacking. This study explored the correlation between US-induced (P = 0–800 W, t = 0–40 min) cell disintegration degree and the extraction efficiency of intracellular components from purple sweet potato, also discussing extraction selectivity and visualizing the cell micro-disintegration process. Cell disintegration degree was estimated via electrical conductivity (cell permeabilization index, Zi) and fractal dimension analysis of damaged cells (cell wall disintegration index, Zd). Extraction efficiency was evaluated by using the extraction indexes of carbohydrate (Zc), protein (Zp), and total phenolic compound (ZTPC). Results indicated that US markedly enhanced cell permeabilization and intracellular components release. For example, at the highest intensity (800 W, 40 min), the enhancement in carbohydrate, protein and TPC contents were approximately 2 to 7 folds, compared to untreated sample (0 W, 40 min). Extraction efficiencies depended on the applied P and t, with the extractability order was carbohydrate > protein > TPC at each power. Different non-linear correlations between Zd with Zi, Zp, Zc, and ZTPC, reflecting the differences in the release behaviors of these water-soluble components after US treatment. Additionally, US favored carbohydrate extraction over protein, but stronger US intensity resulted in lower extraction selectivity. The visual microscale model showed that increasing P elevated cell surface acoustic pressure, cell stress and volume strain. Cell micro-disintegration process would initiate at the side and end faces, then gradually spread to the edges.
The diversity of architectural forms, together with the materials used, fundamentally determines how sound behaves in enclosed spaces. While previous research has predominantly focused on the acoustics of complex, historically or functionally specific buildings, it has given limited attention to the elementary volumetric forms that constitute the basis of architectural design. This study investigates the acoustic behavior of 20 generative geometries, ranging from basic primitives to long rooms, coupled spaces, and sequential volumes, that common architectural typologies. Room impulse responses are examined in a controlled setup through both ray-tracing simulations and the diffusion equation model (DEM). T30 values and relative sound pressure level (SPL) differences are systematically compared, and DEM is further employed to visualize time-dependent energy flow, revealing how form itself governs patterns of sound distribution. Material variations are introduced to assess the impact of inhomogeneous absorption, while a pilot field measurement in a corridor validates long-room acoustical predictions. By re-examining sound propagation in simplified forms, this research establishes the acoustic potential of architectural form as a primary design parameter, offering a framework that bridges methodological innovation with design practice in the early stages of acoustically informed architecture.
Numerical methods are widely used in the area of nonlinear problems including differential equations. There are various integral transformations to study the frequency formulations and nonlinear solutions, but there are many types of transformations that make it difficult to choose during use. Recently, Professor He proposed a general integral transformation, which is a generalization of the Laplace transform, Fourier transform, and other transformations existing in the literature. The unification can provide more opportunities for expanding research on physical phenomena and engineering problems. This new transformation coupled with the variational iteration method is highly effective for various nonlinear problems and offers a new window for wide applications. A new scheme of correction functional is obtained and a numerical example is taken to support the primary findings. The Lagrange multiplier is easily obtained and an algorithm is developed. Taking an oscillator with coordinate-dependent mass as an example to illustrate that the approximate solution is quickly obtained by the final algorithm. A high approximate nonlinear frequency and the solution are solved and the graphical representation is given. It will be a challenge and future trend for the nonlinear research.
Control engineering systems. Automatic machinery (General), Acoustics. Sound
Fresh-cut mushrooms are gaining popularity worldwide. However, their shelf life is limited because of enzymatic browning catalyzed by polyphenol oxidase (PPO), which leads to quality loss. The effects of different treatments (dual-frequency ultrasound (DFU), electrolytic water (EW), dual-frequency ultrasound combined with electrolytic water (DFU-EW)) on the molecular structure (Fourier infrared spectroscopy, X-ray diffraction, fluorescence spectroscopy, surface hydrophobicity, etc.), thermal properties, gene expression of PPO, and storage characteristics of mushrooms were investigated. The results showed that the DFU-EW decreased the relative contents of α-helix by 6.3 % and β-turns by 11.2 %, while increasing the contents of random coil and β-sheet by13.3 % and 4.7 %, respectively, compared to the control. The XRD analysis showed that the crystallinity of PPO was 7% higher than the control, while the fluorescence spectroscopy and surface hydrophobicity of PPO decreased from 921.7 (a.u) and 1154.5 to 393.5 (a.u) and 506.5, respectively. The DFU-EW treatment changed both the secondary and tertiary structures of PPO. The TGA analysis indicated that the thermal decomposition temperature decreased from the control 351.4 ℃ to 336.9 ℃. The gene expression level of AbPPO3 and AbPPO4 lowered. A 7-day storage period showed that DFU-EW inhibited the degree of browning, maintained the firmness of mushrooms, and stabilized the relative activity of PPO at 60% on average. Taken together, the DFU-EW treatment can effectively inactivate the PPO activity in fresh-cut mushrooms, thereby extending their shelf life, and this method provides a new insight to improve the quality of fresh-cut products.
Ultrasonic Liquid Phase Exfoliation (LPE) has gathered attention from both scientific and industrial communities for its accessibility and cost-effectiveness in producing graphene. However, this technique has faced challenges such as low yield and long production time. In this study, we developed a cyclic ultrasonication system to exfoliate expanded graphite (EG) by applying static pressure to a flow chamber to address these challenges. Using deionized water (DIW) as solvent and polyvinylpyrrolidone (PVP) as dispersion, we obtained graphene slurries with an average lateral size of 7 μm and averaged number of layers of 3.5 layers, after 40 min of ultrasonication. After centrifugation, the yield of single and bilayer graphene was approximately 16 %. The findings showed that regulating hydrostatic pressure can effectively affect the lateral size and number of layers of few-layer graphene. The proposed method is of good potential for scaled-up production of few-layer graphene.
Photoacoustic (PA) image reconstruction involves acoustic inversion that necessitates the specification of the speed of sound (SoS) within the medium of propagation. Due to the lack of information on the spatial distribution of the SoS within heterogeneous soft tissue, a homogeneous SoS distribution (such as 1540 m/s) is typically assumed in PA image reconstruction, similar to that of ultrasound (US) imaging. Failure to compensate for the SoS variations leads to aberration artefacts, deteriorating the image quality. Various methods have been proposed to address this issue, but they usually involve complex hardware and/or time-consuming algorithms, hindering clinical translation. In this work, we introduce a deep learning framework for SoS estimation and subsequent aberration correction in a dual-modal PA/US imaging system exploiting a clinical US probe. As the acquired PA and US images were inherently co-registered, the estimated SoS distribution from US channel data using a deep neural network was incorporated for accurate PA image reconstruction. The framework comprised an initial pre-training stage based on digital phantoms, which was further enhanced through transfer learning using physical phantom data and associated SoS maps obtained from measurements. This framework achieved a root mean square error of 10.2 m/s and 15.2 m/s for SoS estimation on digital and physical phantoms, respectively and structural similarity index measures of up to 0.88 for PA reconstructions compared to the conventional approach of 0.69. A maximum of 1.2 times improvement in the signal-to-noise ratio of PA images was further demonstrated with a human volunteer study. Our results show that the proposed framework could be valuable in various clinical and preclinical applications to enhance PA image reconstruction.
This study investigates the potential of fused deposition modeling (FDM) three-dimensional (3D) printing techniques for manufacturing catalytic static mixers during biodiesel synthesis. The printed catalytic mixing elements comprises acrylonitrile butadiene styrene (ABS) plastic with 15 wt% calcium oxide (CaO) as a solid catalyst. When the reactants flowed through the CaO/ABS mixing device, the blending and acceleration processes were both significantly impacted. Moreover, their characteristics, performance in biodiesel production, reusability, and economy were analyzed. The effects of methanol to oil (M:O) molar ratio, circulation time, and sonication time on methyl ester (ME) purity were also examined. The results showed that CaO crystals were distributed on the CaO/ABS mixer’s surface, which is crucial for catalytic purposes. During circulation process of ME from pretreated sludge palm oil (PSPO), catalytic static mixer (CSM) and CSM coupled with ultrasound (CSM/US) reactors were employed. The full ultrasonic power of CSM/US reactor of 16 × 400 W (total 6400 W) was operated at 20 kHz frequency. Moreover, the continuous and pulse ultrasonic modes of CSM/US reactor were compared to determine the ME purity and electricity consumption for ME production. For the CSM reactor, 12:1 M:O molar ratio and 8.5 h circulation time were recommended to realize 94.2 wt% ME purity. For the CSM/US reactor, 12:1 M:O molar ratio and 2.25 h circulation time were recommended to achieve 96.5 wt% ME purity. Under the pulsed mode operation, ME purity of 95.09 wt% was achieved, with a reduction in electricity consumption by approximately 37.6 % compared to continuous mode operation. Furthermore, the CaO/ABS catalytic static mixer was determined to be reusable for up to three cycles in both CSM and CSM/US reactors. Thus, CaO/ABS catalytic static mixers assure high purity ME production through FDM 3D printing technology with a CaO solid catalyst.
Natural resource depletion, negative environmental effects and the challenge to secure global food security led to the establishment of the Sustainable Development Goals (SDGs). In need to explore underutilized sustainable protein sources, this study aims at isolating protein from cowpea by ultrasound-assisted extraction (UAE), where the techno-functional characteristics of the protein isolates were studied at different sonication conditions i.e., 100 W and 200 W at processing times ranging from 5 to 20 min. The US at 200 W-10 min produced the optimal results for all properties. In this process combination, there was an increase in protein yield, solubility, water-holding capacity, foaming capacity and stability, emulsion activity and stability, zeta-potential, and in-vitro protein digestibility from 31.78% to 58.96%, 57.26% to 68.85%, 3.06 g/g to 3.68 g/g 70.64% to 83.74%, 30.76% to 60.01%, 47.48% to 64.26%, 56.59% to 87.71%, –32.9 mV to −44.2 mV and 88.27% to 89.99%, respectively and particle size dropped from 763 nm to 559 nm in comparison to control. The microstructure and secondary-structure alterations of proteins caused by sonication were validated by SEM images, SDS-PAGE, and FTIR analyses. Sonication leads to acoustic cavitation and penetrate the cell walls, improving extraction from the solid to liquid phase. After sonication, the hydrophobic protein groups were exposed and proteins were partially denatured which increased its functionality. The findings demonstrated that UAE of cowpea protein improved yield, modify characteristics to fit the needs of the food industry, and contribute to achieving SDGs 2, 3, 7, 12, and 13.
Considering the comprehensive effect of the internal non-inertial system of planetary gear transmission (PGT) and external non-inertial system of the body, combined with the modified Heywood formula and Hertz formula, a calculation model for the dynamic bending stress and contact dynamic stress of the PGT in a non-inertial system (NIS) is proposed. The stress non-inertial coefficients ( K NI ) describing the influence of the additional effects on the dynamic stress in the non-inertial system are defined. Additionally, the variation law of non-inertial coefficients under two typical non-inertial conditions of variable-speed horizontal flight and somersault motion was studied. The effect of gear installation and manufacturing errors on the non-inertial coefficients under two maneuvering conditions was analyzed. The results indicated that non-inertial coefficients increase with an increase in the maneuverability of the body, and the variable-speed horizontal flight and somersault motion have significant effects on the changing trend of non-inertial coefficients with the gear installation and manufacturing errors. Compared with the gear error, the effect of the NIS has a significant influence on the non-inertial coefficients.
Control engineering systems. Automatic machinery (General), Acoustics. Sound
The mulberry leaf protein extracted by ultrasound-assisted cellulase degradation (UACD) method was optimized with the protein dissolution amount (PDA) as the index. The Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy of extracted mulberry leaf protein were measured. The functional characteristics of protein extracted by the UACD method were evaluated. Results showed that the extraction condition was optimized and adjusted to the following parameters: pH value of 7.20, ultrasound temperature of 35.00 °C, enzyme dosage of 4.20% and ultrasound time of 10.00 min. Under these optimized conditions, the experimental verification value of PDA was 13.87 mg/mL, which was approaching to the predicted value of 13.54 mg/mL. The analysis results of FTIR showed that after extraction by the UACD method, the mulberry leaf protein with the vibrational peak of ester carbonyl (C = O) absorption peak (1734.66 cm−1) disappeared. The α-helix content of protein extracted by the UACD decreased by 8.13%, and the β-turn and random coil content of protein increased by 20.22% and 18.79%, respectively, compared to that of the blank. The microstructure of mulberry leaf protein showed that the UACD method could break the dense structure of protein raw materials, reduce the average size of proteins and increase the specific surface area and roughness of proteins. According to the results of functional characteristics, the mulberry leaf protein extracted by the UACD method presented the highest enzymolysis properties and solubility, which was beneficial for the application in the food industry. In conclusion, the UACD method was a very effective way to extract protein from mulberry leaf.
This work aims to predict the transfer function of a given modal content inside a circular duct with a bellmouth inlet in the presence of a mean flow. The transfer function is the relation in amplitude and phase between a given mode inside the duct and an observer located in the far-field. The numerical solution is obtained by finite element simulation in which the mean flow is input data. Verification is provided by comparison to the analytical solution of an unbaffled circular duct with uniform flow. Influence from various parameters such as the geometry and mean Mach number on the radiated pressure field is investigated. The analytical solution is a good approximation for finding the radiated principal lobe, and the inlet geometry is found to be more important than other parameters such as mean flow when static inlet configuration is studied.
Acoustics in engineering. Acoustical engineering, Acoustics. Sound
Jenno Joseph-Leenose-Helen, Nairah Noor, Mehvesh Mushtaq
et al.
In the present study, Himalayan cheese, kradi was coated with beeswax loaded with pine needle extract (PNE) to increase its shelf life and nutraceutical potential. PNE was extracted via ultrasonication and incorporated into beeswax at concentrations, 2:1, 1:1, and 2:3 (grams of beeswax to mL of PNE). The dispersion of PNE in the coatings was carried out using an ultrasonic probe at a frequency of 20 kHz for 15 min and at power rating of 500 W. The coatings were characterised using scanning electron microscopy, light microscopy, dynamic light scattering (DLS), fourier transmission infrared spectroscopy. DLS revealed a hydrodynamic diameter and zeta potential of 12.11 ± 0.41 µm and −19.32 ± 0.61 mV for coating loaded with highest concentration of PNE. The bioactivities of the coating including antioxidant, antidiabetic and antibacterial assays revealed significantly higher values with the increase in PNE concentration. Shelf life and sensory evaluation study including microbiological and sensory analysis revealed inhibition of mould growth and good score of texture and appearance with the increase in concentration of PNE. The study provides a future perspective for application of beeswax loaded PNE coatings in cheese industry.
M Sukri Hadi, Intan ZM Darus, Mat H Ab.Talib
et al.
This paper presents the development of an active vibration control for vibration suppression of the horizontal flexible plate structure using proportional–integral–derivative controller tuned by a conventional method via Ziegler–Nichols and an intelligent method known as particle swarm optimization algorithm. Initially, the experimental rig was designed and fabricated with all edges clamped at the horizontal position of the flexible plate. Data acquisition and instrumentation systems were designed and integrated into the experimental rig to collect input–output vibration data of the flexible plate. The vibration data obtained through experimental study was used to model the system using system identification technique based on auto-regressive with exogenous input structure. The plate system was modeled using particle swarm optimization algorithm and validated using mean squared error, one-step ahead prediction, and correlation tests. The stability of the model was assessed using pole zero diagram stability. The fitness function of particle swarm optimization algorithm is defined as the mean squared error between the measured and estimated output of the horizontal flexible plate system. Next, the developed model was used in the development of an active vibration control for vibration suppression on the horizontal flexible plate system using a proportional–integral–derivative controller. The proportional–integral–derivative gains are optimally determined using two different ways, the conventional method tuned by Ziegler–Nichols tuning rules and the intelligent method tuned by particle swarm optimization algorithm. The performances of developed controllers were assessed and validated. Proportional–integral–derivative-particle swarm optimization controller achieved the highest attenuation value for first mode of vibration by achieving 47.28 dB attenuation as compared to proportional–integral–derivative-Ziegler–Nichols controller which only achieved 34.21 dB attenuation.
Control engineering systems. Automatic machinery (General), Acoustics. Sound
Significance The sounds we encounter in everyday life (e.g. speech, voices, animal cries, wind, rain) are complex and various. How the human brain analyses their acoustics remains largely unknown. This research shows that mathematical modelling in combination with high spatial resolution functional magnetic resonance imaging enables reverse engineering of the human brain computations underlying real-life listening. Importantly, the research reveals that even general auditory processing mechanisms in the human brain are optimized for fine-grained analysis of the most behaviorally relevant sounds (i.e., speech, voices). Most likely, this observation reflects the evolutionary feat that, for humans, discriminating between speech sounds is more crucial than distinguishing, for example, between barking dogs. Ethological views of brain functioning suggest that sound representations and computations in the auditory neural system are optimized finely to process and discriminate behaviorally relevant acoustic features and sounds (e.g., spectrotemporal modulations in the songs of zebra finches). Here, we show that modeling of neural sound representations in terms of frequency-specific spectrotemporal modulations enables accurate and specific reconstruction of real-life sounds from high-resolution functional magnetic resonance imaging (fMRI) response patterns in the human auditory cortex. Region-based analyses indicated that response patterns in separate portions of the auditory cortex are informative of distinctive sets of spectrotemporal modulations. Most relevantly, results revealed that in early auditory regions, and progressively more in surrounding regions, temporal modulations in a range relevant for speech analysis (∼2–4 Hz) were reconstructed more faithfully than other temporal modulations. In early auditory regions, this effect was frequency-dependent and only present for lower frequencies (<∼2 kHz), whereas for higher frequencies, reconstruction accuracy was higher for faster temporal modulations. Further analyses suggested that auditory cortical processing optimized for the fine-grained discrimination of speech and vocal sounds underlies this enhanced reconstruction accuracy. In sum, the present study introduces an approach to embed models of neural sound representations in the analysis of fMRI response patterns. Furthermore, it reveals that, in the human brain, even general purpose and fundamental neural processing mechanisms are shaped by the physical features of real-world stimuli that are most relevant for behavior (i.e., speech, voice).
Seismic response of five-story frame structure supported by lead-rubber bearings isolation system is investigated subjected to near-fault ground motions. The main structure is modeled as a simple linear multi-degrees-of-freedom vibration system with lumped masses, excited by near-fault ground motions in the horizontal direction. The variation curves of peak top floor acceleration and peak bearing displacement of isolated building are plotted under different yield shear coefficient. The objective function selected for optimality is to maximize the seismic energy dissipated by the lead-rubber bearings. The main constraint conditions selected for optimality are the minimization of both peak bearing displacement and peak top floor acceleration. Optimum parameters of lead-rubber bearing isolation system are investigated and found that optimum yield shear coefficient of lead-rubber bearings is found to be in the range of 0.10–0.14 under near-fault ground motions. Optimum yield shear coefficient decreases with the increase of second isolation period. Optimum yield shear coefficient of lead-rubber bearings with higher yield displacement is larger than that of lead-rubber bearings with low yield displacement. Optimum ratio of pre-yield stiffness to post-yield stiffness of lead-rubber bearings is found to be in the range of 16–35. Optimum stiffness ratio increases proportionally with the decrease of yield displacement. Optimum stiffness ratio increases slightly with the increase of yield shear coefficient. Excluding the effect of pre-yield stiffness, the optimum second isolation period is recommended to be in the range of 4–6 s.
Control engineering systems. Automatic machinery (General), Acoustics. Sound
Rubber or elastomeric materials are widely used for shock absorbers having elastic and viscous properties such as high inherent damping, deflection capacity, and energy storage. The dynamic properties of these components are of primary concern in designing rubber absorbers to reduce the shock loading given as well as the structure-borne noise transmissibility. Besides, the dynamic response of the mechanical systems, at where the rubber shock absorbers are used, is directly associated with the properties of the shock absorbers. In order to determine these properties of the rubber, mathematical models are created in terms of hyperelasticity and viscoelasticity. The hyperelastic and viscoelastic material models represent the nonlinear elastic and strain rate dependencies of the overall rubber behavior, respectively. Hyperelastic material model captures the material’s nonlinear elasticity with no-time dependence whereas viscoelastic model describes the material response which contains an elastic and viscous part depending on time, frequency, and temperature. This paper presents the dynamic characterization of rubber shock absorbers, having different shore hardness values, in terms of hyperelastic and viscoelastic constitutive models. The parameters of the constitutive models are determined from the uniaxial tensile and relaxation tests. These parameters are used for the numerical model of the rubber components and the accuracy of the characterization is presented by means of a numerical case study.
Control engineering systems. Automatic machinery (General), Acoustics. Sound