Search Results (38)

The development of an intelligent ultrasonic aspirator controlled by a fiber-optic neoplasm sensor that detects 5-aminolevulinic acid-derived porphyrin fluorescence presents a significant advancement in glioma surgery. By leveraging the fluorescence phenomenon associated with 5-aminolevulinic acid in malignant neoplasms, this device integrates an excitation laser and a high-sensitivity photodiode into the tip of an ultrasonic aspirator handpiece. This setup allows for real-time tumor fluorescence detection, which in turn modulates the aspirator’s power based on fluorescence intensity. Preliminary testing demonstrated high sensitivity, with the device capable of differentiating between weak, strong, and no fluorescence. The sensor sensitivity was comparable to human visual perception, enabling effective tumor differentiation. Tumors with strong fluorescence were effectively crushed, while the aspirator ceased operation in non-fluorescent areas, enabling precise tissue resection. Furthermore, the device functioned efficiently in bright surgical environments and was designed to maintain a clean sensor tip through constant saline irrigation. The system was successfully applied in a surgical case of recurrent glioblastoma, selectively removing tumor tissue while preserving surrounding brain tissue. This innovative approach shows promise for safer, more efficient glioma surgeries and may pave the way for sensor-based robotic surgical systems integrated with navigation technologies. Full article

This paper presents an intelligent navigation wearable device for visually impaired individuals. The system aims to improve their independent travel capabilities and reduce the negative emotional impacts associated with visible disability indicators in travel tools. It employs an RGB-D camera and an inertial measurement unit (IMU) sensor to facilitate real-time obstacle detection and recognition via advanced point cloud processing and YOLO-based target recognition techniques. An integrated intelligent interaction module identifies the core obstacle from the detected obstacles and translates this information into multidimensional auxiliary guidance. Users receive haptic feedback to navigate obstacles, indicating directional turns and distances, while auditory prompts convey the identity and distance of obstacles, enhancing spatial awareness. The intuitive vibrational guidance significantly enhances safety during obstacle avoidance, and the voice instructions promote a better understanding of the surrounding environment. The device adopts an arm-mounted design, departing from the traditional cane structure that reinforces disability labeling and social stigma. This lightweight mechanical design prioritizes user comfort and mobility, making it more user-friendly than traditional stick-type aids. Experimental results demonstrate that this system outperforms traditional white canes and ultrasonic devices in reducing collision rates, particularly for mid-air obstacles, thereby significantly improving safety in dynamic environments. Furthermore, the system’s ability to vocalize obstacle identities and distances in advance enhances spatial perception and interaction with the environment. By eliminating the cane structure, this innovative wearable design effectively minimizes social stigma, empowering visually impaired individuals to travel independently with increased confidence, ultimately contributing to an improved quality of life. Full article

Due to accelerated urbanization, modern urban residents are facing increasing life pressures. Many citizens are experiencing situational aversion in daily commuting, and the deterioration in the traffic environment has led to psychological distress of varying degrees among urban dwellers. Cyclists, who account for about 7% of urban commuters, lack a sense of belonging in the urban space and experience significant deficiencies in the corresponding urban infrastructure, which causes more people to face significant barriers to choosing cycling as a mode of transportation. To address the aforementioned issues, this study proposes a bionic intelligent interaction helmet (BIIH) designed and validated based on the principles of bionics, which has undergone morphological design and structural validation. Constructed around the STM32-embedded development board, the BIIH is an integrated smart cycling helmet engineered to perceive environmental conditions and enable both human–machine interactions and environment–machine interactions. The system incorporates an array of sophisticated electronic components, including temperature and humidity sensors; ultrasonic sensors; ambient light sensors; voice recognition modules; cooling fans; LED indicators; and OLED displays. Additionally, the device is equipped with a mobile power supply, enhancing its portability and ensuring operational efficacy under dynamic conditions. Compared with conventional helmets designed for analogous purposes, the BIIH offers four distinct advantages. Firstly, it enhances the wearer’s environmental perception, thereby improving safety during operation. Secondly, it incorporates a real-time interaction function that optimizes the cycling experience while mitigating psychological stress. Thirdly, validated through bionic design principles, the BIIH exhibits increased specific stiffness, enhancing its structural integrity. Finally, the device’s integrated power and storage capabilities render it portable, autonomous, and adaptable, facilitating iterative improvements and fostering self-sustained development. Collectively, these features establish the BIIH as a methodological and technical foundation for exploring novel research scenarios and prospective applications. Full article

In pursuing functional foods that promote health, nanoliposomal carriers have been used to enhance the stability and functionality of dairy products such as yogurt, promising therapeutic benefits. This study aimed to evaluate the impact of fucoxanthin-loaded nanoliposomes in yogurt on its antioxidant, physicochemical, and rheological properties under cold storage (21 days). Fucoxanthin-loaded nanoliposomes were prepared using the ultrasonic film dispersion technique and added at concentrations of 0%, 5%, and 10% in the yogurt (Y-C, Y-FXN-5, Y-FXN-10). Homogeneous and uniform nanoliposomes (98.28 nm) were obtained, preserving their integrity and functionality and ensuring the prolonged release and bioavailability of fucoxanthin. Y-FXN-10 maintained the highest antioxidant activity according to the DPPH (52.96%), ABTS (97.97%), and FRAP (3.16 mmol ET/g) methods. This formulation exhibited enhanced erythroprotective potential, inhibiting hemolysis, photohemolysis, and heat-induced hemolysis. However, viscosity and firmness decreased, affecting the texture and appearance. Sensory properties such as the color, flavor, aftertaste, texture, and overall acceptance improved with the 10% fucoxanthin-enriched yogurt formulation. These results suggest that nanoliposomes are suitable for carrying fucoxanthin. Their incorporation into food matrices is critical to developing functional foods. Regulatory approvals and consumer perceptions regarding nanotechnology-based products must be addressed, emphasizing their safety and health benefits. Full article

We propose a new method for constructing a virtual sound source (VSS) based on the direct-to-reverberant ratio (DRR) of room impulse responses (RIRs), using multiple pairs of parametric-array loudspeakers (PALs) and conventional loudspeakers (hereafter referred to simply as loudspeakers). In this paper, we focus on the differences in the DRRs of the RIRs generated by PALs and loudspeakers. The DRR of an RIR is recognized as a key cue for distance perception. A PAL can achieve super-directivity using an array of ultrasonic transducers. Its RIR exhibits a high DRR, characterized by a large-amplitude direct wave and low-amplitude reverberations. Consequently, a PAL makes the VSS appear to be closer to the listener. In contrast, a loudspeaker causes the VSS to be perceived as farther away because the sound it emits has a low DRR. The proposed method leverages the differences in the DRRs of the RIRs between PALs and loudspeakers. It controls the perceived distance of the VSS by reproducing the desired DRR at the listener’s position through a weighted combination of the RIRs emitted from PALs and loudspeakers into the air. Additionally, the proposed method adjusts the direction of the VSS using vector-based amplitude panning (VBAP). Finally, we have confirmed the effectiveness of the proposed method through evaluation experiments. Full article

Acoustic vibrations may induce different changes in plants that perceive them, and plants themselves can also emit acoustic signals. The aim of this review was to cover the past ten years of plant acoustic research and its shortcomings, with a focus on the reflecting, sensing, and emission of ultrasound by plants. Ultrasonication may alter plant growth and development, and an increasing number of studies are being carried out to investigate its effects on both in vitro plant culture and greenhouse or field plant production, as well as on the biochemical and molecular functions of plants. In this paper, we summarized the progress in the use of ultrasound in horticulture and agriculture for enhancing plant growth and development, either in vitro or in vivo, improving yield and crop quality and increasing stress tolerance, as well as for special methodological applications, like sonication-assisted Agrobacterium-mediated transformation. Some research gaps, such as the lack of a precise mechanism for plant ultrasound emission, the possible participation of some reactive radicals in ultrasound signaling, the effect of ultrasound on the epigenome, the role of ultrasound in plant-to-plant communication, and whether there is a specific, sound perceiving organ, etc., were also presented. In addition, a predictive vision is described of how ultrasonication of plants and ultrasound detection emitted by plants can be used in the future to develop green and sustainable agricultural and horticultural technologies. Furthermore, based on our current knowledge, a proposal is presented to combine them with machine learning and artificial intelligence for developing novel production technologies. Full article

Promoting alternative modes of transportation such as cycling represents a valuable strategy to minimize environmental impacts, as confirmed in the main targets set out by the European Commission. In this regard, in cities throughout the world, there has been a significant increase in the construction of bicycle paths in recent years, requiring effective maintenance strategies to preserve their service levels. The continuous monitoring of road networks is required to ensure the timely scheduling of optimal maintenance activities. This involves regular inspections of the road surface, but there are currently no automated systems for monitoring cycle paths. In this study, an integrated monitoring and assessment system for cycle paths was developed exploiting Raspberry Pi technologies. In more detail, a low-cost Inertial Measurement Unit (IMU), a Global Positioning System (GPS) module, a magnetic Hall Effect sensor, a camera module, and an ultrasonic distance sensor were connected to a Raspberry Pi 4 Model B. The novel system was mounted on a e-bike as a test vehicle to monitor the road conditions of various sections of cycle paths in Rome, characterized by different pavement types and decay levels as detected using the whole-body vibration $a_{wz}$ index (ISO 2631 standard). Repeated testing confirmed the system’s reliability by assigning the same vibration comfort class in 74% of the cases and an adjacent one in 26%, with an average difference of 0.25 m/s², underscoring its stability and reproducibility. Data post-processing was also focused on integrating user comfort perception with image data, and it revealed anomaly detections represented by numerical acceleration spikes. Additionally, data positioning was successfully implemented. Finally, $a_{wz}$ measurements with GPS coordinates and images were incorporated into a Geographic Information System (GIS) to develop a database that supports the efficient and comprehensive management of surface conditions. The proposed system can be considered as a valuable tool to assess the pavement conditions of cycle paths in order to implement preventive maintenance strategies within budget constraints. Full article

Lithium-ion batteries (LIBs) are widely used in the fields of consumer electronics, new energy vehicles, and grid energy storage due to their high energy density and long cycle life. However, how to effectively evaluate the State of Charge (SOC), State of Health (SOH), and overcharging behavior of batteries has become a key issue in improving battery safety and lifespan. Acoustic sensing technology, as an advanced non-destructive monitoring method, achieves real-time monitoring of the internal state of batteries and accurate evaluation of key parameters through ultrasonic testing technology and acoustic emission technology. This article systematically reviews the research progress of acoustic sensing technology in SOC, SOH, and overcharge behavior evaluation of LIBs, analyzes its working principle and application advantages, and explores future optimization directions and industrialization prospects. Acoustic sensing technology provides important support for building efficient and safe battery management systems. Full article

Due to their compact sizes, low power consumption levels, and convenient integration capabilities, piezoelectric micromachined ultrasonic transducers (PMUTs) have gained significant attention for enabling environmental sensing functionalities. However, the frequency inconsistency of the PMUT arrays often leads to directional errors with the ultrasonic beams. Herein, we propose a reconfigurable PMUT array based on a Sc_0.2Al_0.8N piezoelectric thin film for in-air ranging. Each element of the reconfigurable PMUT array possesses the ability to be independently replaced, enabling matching of the required frequency characteristics, which enhances the reusability of the device. The experimental results show that the frequency uniformity of the 2 × 2 PMUT array reaches 0.38% and the half-power beam width (θ_−3dB) of the array measured at 20 cm is 60°. At a resonance of 69.7 kHz, the sound pressure output reaches 7.4 Pa (sound pressure level of 108.2 dB) at 19 mm, with a reception sensitivity of approximately 11.6 mV/Pa. Ultimately, the maximum sensing distance of the array is 7.9 m, and it extends to 14.1 m with a horn, with a signal-to-noise ratio (SNR) of 19.5 dB. This research significantly expands the ranging capability of PMUTs and showcases their great potential in environmental perception applications. Full article

Objectives: This randomized clinical trial evaluated the microbiological efficacy and the ergonomic impact of three prototypes of a device to reduce aerosol dispersion during dental procedures. Methods: Sixty patients undergoing dental care using high-speed turbines and/or ultrasonic tips were randomly assigned to 4 groups (n = 15): CG: control group, with standard personal protective equipment (PPE); G1: PPE + acrylic device (AD) with aspiration; G2: PPE + AD without aspiration; and G3: PPE + polyvinyl chloride device. The device prototypes consisted of a rigid translucent acrylic structure (G1 and G2), or a rigid PVC tube structure surrounded by layers of translucent flexible PVC films (G3), adjusted to the dental chair, involving the patient’s head, neck and chest. The main outcome was the microbiological analysis (mean Δ of CFU at 10 different sites), and the secondary outcome was the ergonomic evaluation (questionnaire to dentists and patients). Results: The final sample comprised 59 participants (mean age 38.6 ± 11.4 years, 55.2% male). The overall mean time for dental procedures was 32.4 ± 16.9 min, with no differences between groups (p = 0.348). Microbiological analyses showed that the use of the device significantly reduced contamination in the light reflector (01.46 ± 4.43 ΔCFU in G2 vs. 19.25 ± 36.50 ΔCFU in CG; p = 0.028), apron (09.11 ± 12.05 ΔCFU in G3 vs. 21.14 ± 43.41 ΔCFU in GC; p = 0.044), and face shield (08.80 ± 32.70 ΔCFU in G1 vs. 56.78 ± 76.64 ΔCFU in the GC; p = 0.017). The device was well accepted by patients and increased the dentists‘ perception of safety and protection (p < 0.001), but significantly decreased ergonomics related to the clinical view, space, agility and access to the patient, and ease of performing procedures (p < 0.001). Conclusions: The tested device can be an additional tool for infection prevention and control in dentistry, not only during the COVID-19 pandemic, but also for the control of future infectious diseases and epidemics. Full article

The predictive brain hypothesis suggests that perception can be interpreted as the process of minimizing the error between predicted perception tokens generated via an internal world model and actual sensory input tokens. When implementing working examples of this hypothesis in the context of in-air sonar, significant difficulties arise due to the sparse nature of the reflection model that governs ultrasonic sensing. Despite these challenges, creating consistent world models using sonar data is crucial for implementing predictive processing of ultrasound data in robotics. In an effort to enable robust robot behavior using ultrasound as the sole exteroceptive sensor modality, this paper introduces EchoPT (Echo-Predicting Pretrained Transformer), a pretrained transformer architecture designed to predict 2D sonar images from previous sensory data and robot ego-motion information. We detail the transformer architecture that drives EchoPT and compare the performance of our model to several state-of-the-art techniques. In addition to presenting and evaluating our EchoPT model, we demonstrate the effectiveness of this predictive perception approach in two robotic tasks. Full article

Urban traffic congestion has become an increasingly serious problem, and the transportation industry is gradually becoming a high-energy-consuming industry. Intelligent Transportation System (ITSs) that integrate technologies such as electronic sensing, data transmission, and intelligent control have emerged as a new approach to fundamentally solving transportation problems. As one of the cores of intelligent transportation systems, multi-vehicle formation technology has the advantage of promoting vehicle information interaction, improving vehicle mobility, and enhancing traffic conditions. Due to the high cost and risk of conducting multi-vehicle formation experiments using real vehicles, experimenting with intelligent vehicles has become a viable option. Based on the leader–follower formation strategy, this study designed an intelligent vehicle formation system using the Arduino platform. It utilizes infrared sensors, ultrasonic sensors, and photoelectric encoders to perceive information about the vehicle fleet and the road. Information is aggregated to the master vehicle through ZigBee communication modules. The controller of the master vehicle applies a PID algorithm, combined with a differential steering model, to solve the speed instructions for each vehicle in the fleet. Motion control instructions are then transmitted to each slave vehicle through ZigBee communication modules, enabling the automatic adjustment of the fleet’s traveling speed and spacing. Additionally, a Bluetooth app has been designed for users to monitor and control the movement status of the fleet dynamically in real time. Experimental verification has shown that this research effectively improves intelligent fleets’ capabilities in environmental perception, intelligent decision-making, collaborative control, and motion execution. It also enhances road traffic efficiency and safety, providing new ideas and methods for the development of autonomous driving technology. Full article

The appearance of dried fruit clearly influences the consumer’s perception of the quality of the product but is a subtle and nuanced characteristic that is difficult to quantitatively measure, especially online. This paper describes a method that combines several simple strategies to assess a suitable surrogate for the elusive quality using imaging, combined with multivariate statistics and machine learning. With such a convenient tool, this study also shows how one can vary the pretreatments and drying conditions to optimize the resultant product quality. Specifically, an image batch processing method was developed to extract color (hue, saturation, and value) and morphological (area, perimeter, and compactness) features. The accuracy of this method was verified using data from a case study experiment on the pretreatment of hot-air-dried kiwifruit slices. Based on the extracted image features, partial least squares and random forest models were developed to satisfactorily predict the moisture ratio (MR) during drying process. The MR of kiwifruit slices during drying could be accurately predicted from changes in appearance without using any weighing device. This study also explored determining the optimal drying strategy based on appearance quality using principal component analysis. Optimal drying was achieved at 60 °C with 4 mm thick slices under ultrasonic pretreatment. For the 70 °C, 6 mm sample groups, citric acid showed decent performance. Full article

Aiming to solve the partial discharge problem caused by defects in composite insulators, most existing live detection methods are limited by the subjectivity of human judgment, the difficulty of effective quantification, and the use of a single detection method. Therefore, a composite insulator defect diagnosis model based on acoustic–electric feature fusion and a multi-scale perception multi-input of stacked auto-encoder (MMSAE) network is proposed in this paper. Initially, during the withstanding voltage experiment, the electromagnetic wave spectrometer and ultrasonic detector were used to collect and process the data of six types of composite insulator samples with artificial defects. The electromagnetic wave spectrum, ultrasonic power spectral density, and n-S map were then obtained. Then, the network architecture of MMSAE was built by integrating a stacked auto-encoder and multi-scale perception module; the feature extraction and fusion methods of the electromagnetic wave spectrum and ultrasonic signal were investigated. The proposed method was used to diagnose test samples, and the diagnostic results were compared to those obtained using a single input source and the artificial neural network (ANN) method. The results demonstrate that the detection accuracy of acoustic–electric feature fusion is greater than that of a single feature; the accuracy of the proposed method is 99.17%, which is significantly higher than the accuracy of the conventional ANN method. Finally, composite insulator defect diagnosis software based on PYQT5 and Keras was developed. Ten 500 kV aging composite insulators were used to validate the effectiveness of the proposed method and design software. Full article

Photocatalytic activity of HB₂Nb₃O₁₀ perovskite nanosheets (B = Ca, Sr) has been systematically investigated in the reactions of hydrogen production, depending on the method of the photocatalyst preparation: using the pristine nanosheets in the parent suspension without reassembly, filtered nanosheets as well as nanosheets restacked by hydrochloric acid. Photocatalytic measurements were organized in such a way as to control a wide range of parameters, including the hydrogen generation rate, quantum efficiency of the reaction, potential dark activity of the sample as well as stability and pH of the reaction suspension. Exfoliation of the niobates into nanosheets allowed obtaining efficient photocatalysts surpassing the initial bulk materials in the activity up to 55 times and providing apparent quantum efficiency up to 20.8% after surface decoration with a Pt cocatalyst. Among the reassembled samples, greater hydrogen evolution activity was exhibited by simply filtered nanosheets that, unlike the HCl-restacked ones, were found to possess much lower specific surface area in a dry state but contain a perceptible amount of tetrabutylammonium cations on the surface. The activity difference, potentially, is associated with the fact that the filtered nanosheets undergo ultrasonic disaggregation before photocatalytic tests much easier than their HCl-restacked counterparts and, thanks to this, have greater active surface in the reaction suspension. In addition, the enhanced activity of the filtered nanosheets may be due to the presence of tetrabutylammonium as an organic modifier on their surface, which is consistent with the high photocatalytic performance of organically modified layered perovskites considered in our previous reports. Full article