Search Results (134)

To address the issue of voice leakage during the rapid deployment of meeting rooms, a piezoelectric flexible interference structure (PFIS) for active sound masking is developed in this paper. The PFIS uses rubber as the base, allowing it to bend or fold, offering good flexibility. The PFIS generates vibration through direct contact with the target object, without the need for adhesives or installation, fulfilling the need for rapid deployment. The experiment studied the driving of PFIS under three types of interference signals, analyzing the interference performance of PFIS by combining the vibration response of the surface of the table. The results show that the vibration response generated by PFIS on the surface of the table is significantly greater than when only a human voice is present. When a 3.5 kg weight is added to the surface of PFIS, its vibration performance increases by 5.6 times. Furthermore, increasing the voltage enhances the vibration interference effect of the PFIS across the entire frequency range; after adding weight, the vibration interference performance of the PFIS is significantly improved for frequencies above 2500 Hz. It has been verified that PFIS has strong vibration interference performance, effectively masking the vibrations of objects under human voice, providing a new technical solution for information security protection in sensitive areas. Full article

Acoustic Side-Channel Attacks (ASCAs) exploit the sound produced by keyboards and other devices to infer sensitive information without breaching software or network defenses. Recent advances in deep learning, large language models, and signal processing have greatly expanded the feasibility and accuracy of these attacks. To clarify the evolving threat landscape, this survey systematically reviews ASCA research published between January 2020 and February 2025. We categorize modern ASCA methods into three levels of text reconstruction—individual keystrokes, short text (words/phrases), and long-text regeneration— and analyze the signal processing, machine learning, and language-model decoding techniques that enable them. We also evaluate how environmental factors such as microphone placement, ambient noise, and keyboard design influence attack performance, and we examine the challenges of generalizing laboratory-trained models to real-world settings. This survey makes three primary contributions: (1) it provides the first structured taxonomy of ASCAs based on text generation granularity and decoding methodology; (2) it synthesizes cross-study evidence on environmental and hardware factors that fundamentally shape ASCA performance; and (3) it consolidates emerging countermeasures, including Generative Adversarial Network-based noise masking, cryptographic defenses, and environmental mitigation, while identifying open research gaps and future threats posed by voice-enabled IoT and prospective quantum side-channels. Together, these insights underscore the need for interdisciplinary, multi-layered defenses against rapidly advancing ASCA techniques. Full article

Background/Objectives: Enamel defects in molar-incisor hypomineralization (MIH) have a multifactorial etiology involving environmental, systemic, and genetic factors. These alterations represent an aesthetic and emotional challenge, especially in anterior teeth. Resin infiltration has emerged as a minimally invasive treatment for MIH opacities, though outcome predictability remains limited. This study aims to analyze the baseline characteristics of MIH enamel defects and identify specific patterns that may predict clinical outcomes. Methods: This was a single-arm, prospective, observational clinical study with a six-month follow-up, with a total of 101 MIH-affected teeth treated with Icon^® resin infiltration. Opacities were analyzed using CIELAB color parameters (Lab*), including luminance, lesion extent, affected tooth type, opacity location, and patient age. Treatment success was assessed using simple linear regression models with generalized estimating equations, which were based on different covariates. Clinical success was defined as the combined achievement of a significant reduction in ΔE, a decrease in L* indicating reduced opacity brightness, and a reduction in the relative surface area of the lesion at six months. Results: White opacities showed greater reduction after infiltration than yellow and brown ones (p < 0.029). Larger lesions exhibited greater improvement (p < 0.007). Canines and lateral incisors achieved better masking (p < 0.001), and incisal opacities had superior outcomes (p < 0.019). Additionally, younger patients experienced a greater reduction (p < 0.026). Conclusions: Resin infiltration enhances the esthetics of anterior teeth with MIH in pediatric patients. While no single predictive pattern was identified, white opacities achieved greater luminance reduction and better integration with sound enamel. Factors such as age, tooth type, opacity location, lesion extent, and color significantly influence treatment effectiveness and esthetic perception. Full article

Offshore wind farms (OWFs) represent an increasingly important renewable energy source, yet their environmental impacts, particularly underwater noise, require systematic study. Estimating the operational source level (SL) of a single turbine and predicting sound pressure levels (SPLs) at sensitive locations can be challenging. Here, we integrate a turbine SL prediction algorithm with open-source propagation models in a Jupyter Notebook (version 7.4.7) to streamline aggregated SPL estimation for OWFs. Species-specific audiograms and weighting functions are included to assess potential biological impacts. The tool is applied to four planned OWFs, two in the Canary region and two in the Belgian and German North Seas, under conservative assumptions. Results indicate that at 10 m/s wind speed, a single turbine’s SL reaches 143 dB re 1 µPa in the one-third octave band centered at 160 Hz. Sensitivity analyses indicate that variations in wind speed can cause the operational source level at 160 Hz to increase by up to approximately 2 dB re 1 µPa²/Hz from the nominal value used in this study, while differences in sediment type can lead to transmission loss variations ranging from 0 to on the order of 100 dB, depending on bathymetry and range. Maximum SPLs of 112 dB re 1 µPa are predicted within OWFs, decreasing to ~50 dB re 1 µPa at ~100 km. Within OWFs, Low-Frequency (LF) cetaceans and Phocid Carnivores in Water (PCW) would likely perceive the noise; National Marine Fisheries Service (NMFS) marine mammals’ auditory-injury thresholds are not exceeded, but behavioral-harassment thresholds may be crossed. Outside the farms, only LF audiograms are crossed. In high-traffic North Sea regions, OWF noise is largely masked, whereas in lower-noise areas, such as the Canary Islands, it can exceed ambient levels, highlighting the importance of site-specific assessments, accurate ambient noise monitoring and propagation modeling for ecological impact evaluation. Full article

Background/Objectives: Skin cancer is one of the most common diseases in the world, whose early and accurate detection can have a survival rate more than 90% while the chance of mortality is almost 80% in case of late diagnostics. Methods: A modified EfficientNet-B0 is developed based on mobile inverted bottleneck convolution with squeeze and excitation approach. The 3 × 3 convolutional layer is used to capture low-level visual features while the core features are extracted using a sequence of Mobile Inverted Bottleneck Convolution blocks having both 3 × 3 and 5 × 5 kernels. They not only balance fine-grained extraction with broader contextual representation but also increase the network’s learning capacity while maintaining computational cost. The proposed architecture hyperparameters and extracted feature vectors of standard benchmark datasets (HAM10000, ISIC 2019 and MSLD v2.0) of dermoscopic images are optimized with the quantum-behaved particle swarm optimization algorithm (QBPSO). The merit function is formulated by the training loss given in the form of standard classification cross-entropy with label smoothing, mean fitness value (mf^val), average accuracy (mAcc), mean computational time (mCT) and other standard performance indicators. Results: Comprehensive scenario-based simulations were performed using the proposed framework on a publicly available dataset and found an mAcc of 99.62% and 92.5%, mfval of 2.912 × 10⁻¹⁰ and 1.7921 × 10⁻⁸, mCT of 501.431 s and 752.421 s for HAM10000 and ISIC2019 datasets, respectively. The results are compared with state of the art, pre-trained existing models like EfficentNet-B4, RegNetY-320, ResNetXt-101, EfficentNetV2-M, VGG-16, Deep Lab V3 as well as reported techniques based on Mask RCCN, Deep Belief Net, Ensemble CNN, SCDNet and FixMatch-LS techniques having varying accuracies from 85% to 94.8%. The reliability of the proposed architecture and stability of QBPSO is examined through Monte Carlo simulation of 100 independent runs and their statistical soundings. Conclusions: The proposed framework reduces diagnostic errors and assists dermatologists in clinical decisions for an improved patient outcomes despite the challenges like data imbalance and interpretability. Full article

Monitoring the condition of belt conveyor idlers is critical for ensuring safe and efficient operation of industrial conveying systems. However, existing methods often suffer from limited scalability and delayed fault detection, particularly under variable environmental conditions. In this work, we propose MIRA, a transformer-based framework for monitoring idler roller anomalies, which detects and localizes faults using acoustic and vibration signals collected from low-cost sensors. MIRA employs a masked transformer-based autoencoder trained in an unsupervised manner to reconstruct normal patterns and detect deviations via reconstruction error. MIRA can also infer the fault location, enabling spatially aware anomaly detection without the need for labeled data. We validated the system on a custom-built conveyor belt testbed equipped with sensor units, each measuring sound and two-axis vibration signals. We evaluated MIRA on four types of idler faults across 14 roller locations and 6 belt speeds. The results show that MIRA achieves an anomaly detection accuracy of 98.70% and a fault localization accuracy of 96.09%, demonstrating its robustness and practical applicability in complex operational settings. Full article

Background/Objectives: Physical activity (PA) and energy intake (EI) are central targets of community initiatives to reduce the prevalence of childhood obesity. The general effects of PA and EI in influencing energy balance and body composition are clear. However, the independent impacts of PA and EI on the adiposity of children growing up amidst westernized lifestyles are inconclusive, as few studies have employed sufficiently robust methodology to provide solid independent associative data. Methods: We carried out a systematic review of the research addressing the independent associations of adiposity with each of PA and EI in free-living town or city-dwelling children and adolescents. Acceptable publications included objective measures of fat mass and PA, best standard practice EI assessments, and appropriate statistical modeling. Results: Of approximately 700 publications explored, only four satisfied all the pre-set methodological standards. All four studies involved predominantly White participants from westernized cities and had the same outcomes. Adiposity was strongly independently and negatively related to PA, but there was no evidence of any independent relationship between adiposity and EI. Potential misreporting was considered, especially under-reporting by participants with greater adiposity, butpost-hoc assessments were unable to find any evidence that this influenced the outcomes. Conclusions: In general, children with higher adiposity consumed no more food and beverage energy than their leaner counterparts, but they were less active. However, despite some support for the validity of the commonly used and validated EI assessments, their subjective nature raises the possibility that inaccuracy masked relationships. Additional well-designed research is needed, and notwithstanding the vital role that sound nutrition plays in the healthy development of our youth, the consistency of outcomes of the well-executed studies in this review suggests that campaigns targeting youth obesity would benefit from strategies focusing strongly on increasing PA. Full article

Zoos are increasingly hosting out-of-hours events such as ‘Music Nights’ to increase visitation, raising potential animal welfare concerns due to anthropogenic noise pollution. This study examined the physiological stress response, measured through faecal glucocorticoid metabolite (FGCM), of Bornean orangutans (Pongo pygmaeus; n = 6) at Twycross Zoo during four consecutive weekends of live music events. Faecal samples were collected over these weekends and compared with a comprehensive 24 h acoustic analysis of the enclosure. The acoustic data indicated that the environment was dominated by noise from the ventilation system, which masked the sound from the live music. Comparisons of acoustic metrics between Event and Non-Event periods showed that LAeq, LA10, and LA90 were significantly higher during event hours or open zoo periods. In contrast, daily means did not differ. Group-averaged FGCM concentrations were higher on Event days (mean ± SE: Event = 826 ± 99 ng/g; No Event = 701 ± 44 ng/g), but comparisons for each individual showed no significant differences (Batu: t = 0.577, p = 0.596; Maliku: t = 1.475, p = 0.212; Molly: t = 0.290, p = 0.786; Kibriah: t = 0.771, p = 0.506). In contrast, FGCM concentrations increased significantly with increasing acoustic levels (LAeq) across individuals, with Batu and Maliku generally showing higher FGCM levels in response to louder days. These findings suggest that the constant background noise may have caused partial habituation. At the same time, individual variation highlights the importance of assessing physiological responses at the individual level, as relying on group-level data may overlook adverse welfare effects on sensitive individuals. Full article

Alzheimer’s disease (AD) is the most prevalent form of dementia, and accessible biomarkers for early detection remain limited. This study introduces a biomimetic approach in which brain electrical activity is transformed into sound and vibration, emulating natural sensory encoding mechanisms. Resting-state EEG recordings from 36 AD patients and 29 healthy controls were averaged by group, directly sonified, and used to drive a membrane–laser system that projected dynamic vibrational patterns. This transformation mirrors how biological systems convert electrical signals into sensory representations, offering a novel bridge between neural dynamics and physical patterns. The resulting videos were processed through adaptive binarization, morphological filtering, and contour-based masking. Quantitative descriptors such as active area, spatial entropy, fractal dimension, and centroid dynamics were extracted, capturing group-specific differences. A Random Forest classifier trained on these features achieved an accuracy of 0.85 and an AUC of 0.93 in distinguishing AD from controls. These findings suggest that EEG sonification combined with vibrational projection provides not only a novel non-invasive biomarker candidate but also a biomimetic framework inspired by the brain’s own capacity to encode and represent complex signals. Full article

(1) Background: With the increasing incidence of cancer, the need for handling cytotoxic drugs has also grown. However, manipulating these drugs exposes healthcare professionals to significant risks, including occupational exposure to hazardous chemicals. Therefore, it is important to adopt protective measures, including personal protective equipment (PPE) and correct ergonomic practices, to ensure safe drug preparation and minimize health risks for the operators. However, while chemical exposure and PPE have been extensively addressed in the literature, the combined impact of ergonomic practices and protective measures remains insufficiently emphasized, representing a critical gap this review aims to address. Accordingly, the objective of this literature review was to analyze the ergonomic and individual protection practices during the handling of cytostatic drugs and all the implications that bad ergonomic practices and/or poor individual protection have on the operator’s health; (2) Methods: In order to perform this integrative review, a structured literature search was conducted using online databases (Web of Science^®, Google Scholar^®, and PubMed^®) from January 2005 to June 2025. (3) Results: A total of 19 articles were analyzed, with 17 focusing on PPE and 17 on ergonomics. The findings emphasize that PPE, such as gloves, masks, gowns, sleeves and safety glasses, plays a critical role in the safe handling of cytotoxic drugs, particularly when combined with other safety measures. Additionally, maintaining correct ergonomic posture is important in preventing musculoskeletal disorders; (4) Conclusions: This review emphasizes the significance of integrating appropriate PPE use with sound ergonomic procedures. Although PPE is still the secondary line of defense against occupational exposure, ergonomic issues must also be addressed to avoid chronic musculoskeletal problems. Continuous training, rigorous attention to safety procedures, and ergonomic enhancements should be prioritized by healthcare facilities as a key element of occupational safety programs to reduce the short-term and long-term health hazards for personnel handling dangerous drugs. Full article

A previous analysis of Antarctic acoustic data relevant to quantifying frazil contributions to sea ice accretion is reconsidered to address inconsistencies with river frazil results acquired with similar instrumentation but augmented to suppress instrument icing. It was found that sound attenuation by consequent icing limited credible Antarctic acoustic frazil measurements to afternoon and early evening periods, which are shown to encompass daily minimums in frazil production. This reality was masked by use of an unvalidated liquid oblate spheroidal frazil characterization model, which greatly overestimated frazil concentrations. Much lower frazil contents were derived for these periods using a robust 2-frequency characterization algorithm, which incorporated a validated, alternative theory of scattering by elastic solid spheres. Physical arguments based on these results and instrument depth data were strongly suggestive of maximal but, currently, unquantified frazil presences during unanalyzed heavily iced late evening and morning time periods. Full article

Electrification introduces additional NVH (noise, vibration and harshness) challenges during the development of powertrain mounting systems due to high-frequency excitations from the powertrain and the absence of masking effects from the combustion engine. In these frequency ranges, engine mounts can stiffen up to a factor of five due to continuum resonances, reducing their structure-borne sound isolation properties and negatively impacting the customer’s NVH perception. Common hardening factors used during elastomer mount development are therefore limited in terms of their applicable validation frequency range. This study presents a methodology for determining decoupled permissible stiffness ranges for a double-isolated mounting system up to 1500 Hz, based on solution space engineering. Instead of optimizing for a single best design, we seek to maximize solution boxes, resulting in robust stiffness ranges that ensure the fulfillment of the formulated system requirements. These ranges serve as NVH requirements at the component level, derived from the sound pressure level at the seat location. They provide tailored guidelines for mount development, such as geometric design or optimal resonance placement, while simultaneously offering maximum flexibility by spanning the solution space. The integration of machine learning approaches enables the application of large-scale finite-element models within the framework of solution space analysis by reducing the computational time by a factor of $7.19·{10}^3$. From a design process standpoint, this facilitates frontloading by accelerating the evaluation phase as suppliers can directly benchmark their mounting concepts against the permissible ranges and immediately verify compliance with the defined targets. Full article

As a perceptual representation of ecosystem structure and function, the soundscape has become an important indicator for evaluating ecological health and assessing the impacts of human disturbances. Understanding the spatiotemporal heterogeneity of soundscapes is essential for revealing ecological processes and human impacts in protected areas. This study investigates such heterogeneity in Zhangjiajie National Forest Park using deep learning approaches. To this end, we constructed a dataset comprising eight representative sound source categories by integrating field recordings with online audio (BBC Sound Effects Archive and Freesound), and trained a classification model to accurately identify biophony, geophony, and anthrophony, which enabled the subsequent analysis of spatiotemporal distribution patterns. Our results indicate that temporal variations in the soundscape are closely associated with circadian rhythms and tourist activities, while spatial patterns are strongly shaped by topography, vegetation, and human interference. Biophony is primarily concentrated in areas with minimal ecological disturbance, geophony is regulated by landforms and microclimatic conditions, and anthrophony tends to mask natural sound sources. Overall, the study highlights how deep learning-based soundscape classification can reveal the mechanisms by which natural and anthropogenic factors structure acoustic environments, offering methodological references and practical insights for ecological management and soundscape conservation. Full article

The Constrained Disorder Principle (CDP) characterizes systems by their inherent variability, which is regulated within dynamic boundaries to ensure optimal function and adaptability. In biological systems, this variability, or “noise”, is crucial for resilience and flexibility at various scales, ranging from genes and cells to more complex organ systems. Disruption of the boundaries that control this noise—whether through amplification or suppression—can lead to malfunctions and result in pathological conditions. White noise (WN), defined by equal intensity across all audible frequencies, is an exemplary clinical application of the CDP. It has been shown to stabilize disrupted processes and restore functional states by utilizing its stochastic properties within the auditory system. This paper explores WN-based therapies, specifically for the masking, habituation, and alleviation of tinnitus, a subjective perception of sound. It describes the potential to improve WN-based therapies’ effectiveness by applying the CDP and CDP-based second-generation artificial intelligence systems. Understanding the characteristics and limitations of these approaches is essential for their effective implementation across various fields. Full article

Background/Objectives: This study aimed to investigate the optimal sound presentation level for sound localization testing to assess the effect of hearing interventions in individuals with unilateral conductive hearing loss (UCHL). Methods: Nine participants with normal hearing were tested, and simulated two-stage UCHL was created using earmuffs and earplugs. We created two types of masking conditions: (1) only an earplug inserted, and (2) an earplug inserted with an earmuff worn. A sound localization test was performed for each condition. The sound presentation levels were 40, 45, 50, 55, 60, 65, and 70 dB SPL, and the results were evaluated using root mean square and d-values. Results: Both values showed little difference in masking Condition 2, regardless of the sound presentation level, whereas in masking Condition 1, the values were at their minimum at 55 dB SPL. In addition, comparing the differences between masking Conditions 1 and 2 for each sound presentation level, the greatest difference was observed at 55 dB SPL for both values. Conclusions: The optimal sound presentation level for sound localization testing to assess hearing intervention effects in UCHL was 55 dB. This result may be attributed to the effect of input from the non-masked ear, accounting for interaural attenuation; the effect was considered minimal at 55 dB SPL. Full article