Search Results (257)

In this paper, a joint Matching Field Processing (MFP) Algorithm based on horizontal uniform circular array (UCA) is proposed for three-dimensional position of underwater wrecked targets. Firstly, a Marine search and rescue position model based on Minimum Variance Distortionless Response (MVDR) and matching field quadratic joint Algorithm was proposed. Secondly, an MVDR beamforming method based on pre-Kalman filtering is designed to refine the real-time DOA estimation of the desired signal and the interference source, and the sound source azimuth is determined for prepositioning. The antenna array weights are dynamically adjusted according to the filtered DOA information. Finally, the Adaptive Matching Field Algorithm (AMFP) used the DOA information to calculate the range and depth of the lost target, and obtained the range and depth estimates. Thus, the 3D position of the lost underwater target is jointly estimated. This method alleviates the angle ambiguity problem and does not require a computationally intensive 2D spectral search. The simulation results show that the proposed method can better realise underwater three-dimensional positioning under certain signal-to-noise ratio conditions. When there is no error in the sensor coordinates, the positioning error is smaller than that of the baseline method as the SNR increases. When the SNR is 0 dB, with the increase in the sensor coordinate error, the target location error increases but is smaller than the error amplitude of the benchmark Algorithm. The experimental results verify the robustness of the proposed framework in the hierarchical ocean environment, which provides a practical basis for the deployment of rapid response underwater positioning systems in maritime search and rescue scenarios. Full article

Total knee arthroplasty is an extensive orthopedic surgery for patients with severe cases of osteoarthritis. This surgery restores the range of motion in the knee joint and allows for pain-free movement. Advancements in medical techniques used in the surgical zone and implant technology, as well as the management of operations and administration for around two decades prior, have hugely improved surgical outcomes for patients. In this study, advancements in TKA were examined through exploring aspects such as robotic surgery, new implants and materials, minimally invasive surgery, and post-surgery rehabilitation. This paper entails a review of the peer-reviewed literature published between 2005 and 2025 in the PubMed and Google Scholar databases. For predictors, we incorporated clinical relevance together with methodological soundness and relation to review questions to select relevant research articles. We used the PRISMA flowchart to illustrate the article selection system in its entirety. Since robotic surgical and navigation systems have been implemented, surgical accuracy has improved, there is an increased possibility of ensuring alignment, and the use of cementless and 3D-printed implants has increased, offering durable long-term fixation features. The trend in the current literature is that minimally invasive knee surgery (MIS) techniques reduce permanent pain after surgery and length of hospital stays for patients, though the long-term impact still needs to be established. There is various evidence outlining that the enhanced recovery after surgery (ERAS) protocols show positive results in terms of functional recovery and patient satisfaction. The integration of these new advancements enhances TKA surgeries and translates them into ‘need of patient’ procedures, ensuring improved results and increases in patient satisfaction. The aim of this study was to perform a comprehensive analysis of the existing literature regarding TKA advancement studies to identify current gaps and problems. Full article

With the ongoing development of lightweight automobiles, research on new aluminum alloys and welding technology has gained significant attention. Friction stir welding (FSW) is a solid-state joining technique for welding aluminum alloys without melting. In this study, novel squeeze-cast Al-Si-Mg-Fe-Zn alloys with different Zn contents (0, 3.4, 6.5, and 8.3 wt%) were friction stir welded (FSWed) at a translational speed of 200 mm/min and a rotational speed of 800 rpm. These parameters were chosen based on the observations of visually sound welds, defect-free and fine-grained microstructures, homogeneous secondary phase distribution, and low roughness. Zn can affect the microstructure of Al-Si-Mg-Fe-Zn alloys, including the grain size and the content of secondary phases, leading to different mechanical and corrosion behavior. Adding different Zn contents with Mg forms the various amount of MgZn₂, which has a significant strengthening effect on the alloys. Softening observed in the weld zones of the alloys with 0, 3.4, and 6.5 wt% Zn is primarily attributed to the reduction in Kernel Average Misorientation (KAM) and a decrease in the Si phase and MgZn₂. Consequently, the mechanical strengths of the FSWed joints are lower as compared to the base material. Conversely, the FSWed alloy with 8.3 wt% Zn exhibited enhanced mechanical properties, with hardness of 116.3 HV_0.2, yield strength (YS) of 184.4 MPa, ultimate tensile strength (UTS) of 226.9 MP, percent elongation (EL%) of 1.78%, and a strength coefficient exceeding 100%, indicating that the joint retains the strength of the as-cast one, due to refined grains and more uniformly dispersed secondary phases. The highest corrosion resistance of the FSWed alloy with 6.5%Zn is due to the smallest grain size and KAM, without MgZn₂ and the highest percentage of {111} texture (24.8%). Full article

Respiratory diseases present significant global health challenges. Recent advances in respiratory sound analysis (RSA) have shown great potential for automated disease diagnosis and patient management. The International Conference on Biomedical and Health Informatics 2017 (ICBHI2017) database stands as one of the most authoritative open-access RSA datasets. This review systematically examines 135 technical publications utilizing the database, and a comprehensive and timely summary of RSA methodologies is offered for researchers and practitioners in this field. Specifically, this review covers signal processing techniques including data resampling, augmentation, normalization, and filtering; feature extraction approaches spanning time-domain, frequency-domain, joint time–frequency analysis, and deep feature representation from pre-trained models; and classification methods for adventitious sound (AS) categorization and pathological state (PS) recognition. Current achievements for AS and PS classification are summarized across studies using official and custom data splits. Despite promising technique advancements, several challenges remain unresolved. These include a severe class imbalance in the dataset, limited exploration of advanced data augmentation techniques and foundation models, a lack of model interpretability, and insufficient generalization studies across clinical settings. Future directions involve multi-modal data fusion, the development of standardized processing workflows, interpretable artificial intelligence, and integration with broader clinical data sources to enhance diagnostic performance and clinical applicability. Full article

Sound event localization and detection (SELD) is a fundamental task in spatial audio processing that involves identifying both the type and location of sound events in acoustic scenes. Current SELD models often struggle with low signal-to-noise ratios (SNRs) and high reverberation. This article addresses SELD by reformulating direction of arrival (DOA) estimation as a multi-class classification task, leveraging deep convolutional recurrent neural networks (CRNNs). We propose and evaluate two modified architectures: M-DOAnet, an optimized version of DOAnet for localization and tracking, and M-SELDnet, a modified version of SELDnet, which has been designed for joint SELD. Both modified models were rigorously evaluated on the STARSS23 dataset, which comprises 13-class, real-world indoor scenes totaling over 7 h of audio, using spectrograms and acoustic intensity maps from first-order Ambisonics (FOA) signals. M-DOAnet achieved exceptional localization (6.00° DOA error, 72.8% F1-score) and perfect tracking (100% MOTA with zero identity switches). It also demonstrated high computational efficiency, training in 4.5 h (164 s/epoch). In contrast, M-SELDnet delivered strong overall SELD performance (0.32 rad DOA error, 0.75 F1-score, 0.38 error rate, 0.20 SELD score), but with significantly higher resource demands, training in 45 h (1620 s/epoch). Our findings underscore a clear trade-off between model specialization and multifunctionality, providing practical insights for designing SELD systems in real-time and computationally constrained environments. Full article

Cardiovascular diseases remain one of the leading causes of mortality worldwide, highlighting the importance of effective monitoring and early diagnosis. While electrocardiography (ECG) is the standard technique for evaluating the heart’s electrical activity and detecting rhythm and conduction abnormalities, it alone is insufficient for identifying certain conditions, such as valvular disorders. Phonocardiography (PCG) allows the recording and analysis of heart sounds and improves the diagnostic accuracy when combined with ECG. In this study, ECG and PCG signals were simultaneously acquired from a resting adult subject using a compact system comprising an analog front-end (model AD8232, manufactured by Analog Devices, Wilmington, MA, USA) for ECG acquisition and a digital stethoscope built around a condenser electret microphone (model HM-9250, manufactured by HMYL, Anqing, China). Both the ECG electrodes and the microphone were positioned on the chest to ensure the spatial alignment of the signals. An adaptive segmentation algorithm was developed to segment PCG and ECG signals based on their morphological and temporal features. This algorithm identifies the onset and peaks of S1 and S2 heart sounds in the PCG and the Q, R, and S waves in the ECG, enabling the extraction of the systolic time intervals such as EMAT, PEP, LVET, and LVST parameters proven useful in the diagnosis and monitoring of cardiovascular diseases. Based on the segmented signals, the measured averages (EMAT = 74.35 ms, PEP = 89.00 ms, LVET = 244.39 ms, LVST = 258.60 ms) were consistent with the reference standards, demonstrating the reliability of the developed method. The proposed algorithm was validated on synchronized ECG and PCG signals from multiple subjects in an open-source dataset (BSSLAB Localized ECG Data). The systolic intervals extracted using the proposed method closely matched the literature values, confirming the robustness across different recording conditions; in detail, the mean Q–S1 interval was 40.45 ms (≈45 ms reference value, mean difference: −4.85 ms, LoA: −3.42 ms and −6.09 ms) and the R–S1 interval was 14.09 ms (≈15 ms reference value, mean difference: −1.2 ms, LoA: −0.55 ms and −1.85 ms). In conclusion, the results demonstrate the potential of the joint ECG and PCG analysis to improve the long-term monitoring of cardiovascular diseases. Full article

Background/Objectives: Temporomandibular joint disorders (TMDs) affect the temporomandibular joint and associated structures of the stomatognathic system. Joint Vibration Analysis (JVA) is a non-invasive method used to assess TMJ dysfunction through vibration frequencies. This study aimed to explore how age and gender influence TMJ vibration characteristics, hypothesizing that these factors may affect diagnostic accuracy in TMJ evaluations. Methods: This cross-sectional study includes 251 participants (143 females and 108 males) aged 10 to 30 years. TMJ evaluation used JVA to assess range of motion, integral values, and frequency distributions over and under 300 Hz. Participants with a history of TMJ disorders or significant maxillofacial trauma were excluded. Statistical analysis was conducted using employing Kolmogorov–Smirnov tests for data distribution, Kruskal–Wallis test for group comparisons, and Pearson correlation test for variable relationships. Results: Significant gender differences in range of motion (ROM) were observed, with males exhibiting higher values (p = 0.005). Age notably influenced vibration frequencies, particularly in total integral values (TIL and TIR) and frequency distributions around 300 Hz, suggesting links to degenerative changes. Females showed more pronounced age-related effects on vibration parameters. However, gender did not greatly affect vibration characteristics across all frequency bands, indicating that other factors also impact TMJ function. Conclusions: Age and gender significantly influence TMJ vibrations and the interpretation of JVA in clinical settings. Personalized approaches considering these demographic factors may enhance the accuracy of TMJ dysfunction diagnoses. Full article

Background and Objectives: This study aimed to evaluate the effects of hard, soft, and semi-soft splints on TMJ vibrations in bruxers with JVA and to compare them with data obtained from asymptomatic individuals. Materials and Methods: A total of 64 individuals were divided into four subgroups: control (n = 15); and hard (n = 17), soft (n = 16), and semi-soft (n = 16) splints. Electrovibratography records from all individuals included in the study before and after the 3-month splint treatment were obtained with the Biopak^® System. Joint vibration analysis was used to evaluate TMJ sounds. Data normality was examined with the Kolmogorov–Smirnov and Levene tests. The significance of the differences was investigated by One-Way ANOVA and by the Kruskal–Wallis test. Conover’s multiple comparison test was used in post hoc tests. (ClinicalTrials.gov identifier: NCT06893744, on 24 March 2025, titled; Effects of Different Occlusal Splints). Results: After 3 months of treatment, for I < 300 Hz right opening, the control group was statistically lower than both semi-soft (p < 0.001) and hard (p < 0.001) splint groups. The difference between semi-soft and hard splints in post-treatment I < 300 Hz right opening is not statistically significant. After 3 months of treatment compared with the beginning, the increases in left-opening Ti (p = 0.004), I < 300 Hz (p = 0.004), and PA (p = 0.007) values in the soft splint group were statistically significant. Conclusions: All three kinds of splints improved clinical symptoms and complaints of bruxers. For joint vibrations in bruxers, hard and semi-soft splints are more beneficial than soft splints. Full article

The rapid urbanization of the world has brought significant environmental, social, and economic challenges to human society. To build a sustainable county, there are many limiting factors, such as the environment, financial resources, and population. Based on this, the purpose of this study is to investigate how countries can empower their development through a sustainable design path for parks with the participation of all. The core of public participation in co-construction lies in the interactive relationship between the government, society, citizens, and many other groups. That is, “co-construction, co-governance, and sharing” is the basic content of the new pattern of social governance from the perspective of the park city; at its core is joint participation, division of labor, and cooperation. Using qualitative research methods, Kaiyuan, a county in Yunnan Province, was selected as a case study, focusing on the Phoenix Ecological Park and Happiness Lawn; citizens and managers were interviewed to explore paths for sustainable design in the counties. The contribution of this study is a research model of sustainable design for county parks with the participation of all the people. The study found that public participation should consider multiple co-constructions and formulate a sound sustainable design path from three dimensions: counties, managers, and citizens. Combined with the local characteristics of counties, the government has called on enterprises, organizations, and citizens to participate together in improving the quality of life and happiness of county residents. The results can be further verified in other counties. Full article

While open-set recognition algorithms have been extensively explored in computer vision, their application to environmental sound analysis remains understudied. To address this gap, this study investigates how to effectively recognize unknown sound categories in real-world environments by proposing a novel Kernel Density Estimation-based Generative Adversarial Network (KDE-GAN) for data augmentation combined with Attractor–Reciprocal Point Learning for open-set classification. Specifically, our approach addresses three key challenges: (1) How to generate boundary-aware synthetic samples for robust open-set training: A closed-set classifier’s pre-logit layer outputs are fed into the KDE-GAN, which synthesizes samples mapped to the logit layer using the classifier’s original weights. Kernel Density Estimation then enforces Density Loss and Offset Loss to ensure these samples align with class boundaries. (2) How to optimize feature space organization: The closed-set classifier is constrained by an Attractor–Reciprocal Point joint loss, maintaining intra-class compactness while pushing unknown samples toward low-density regions. (3) How to evaluate performance in highly open scenarios: We validate the method using UrbanSound8K, AudioEventDataset, and TUT Acoustic Scenes 2017 as closed sets, with ESC-50 categories as open-set samples, achieving AUROC/OSCR scores of 0.9251/0.8743, 0.7921/0.7135, and 0.8209/0.6262, respectively. The findings demonstrate the potential of this framework to enhance environmental sound monitoring systems, particularly in applications requiring adaptability to unseen acoustic events (e.g., urban noise surveillance or wildlife monitoring). Full article

(1) Background: A sedentary lifestyle may aggravate temporomandibular disorder (TMD) symptoms, increasing pain sensitivity and functional limitations. Physical exercise is recommended for pain management and improving quality of life. Comparing CrossFit^® athletes to sedentary individuals allows for examining whether regular high-intensity exercise impacts pain sensitivity and functional limitations associated with TMD. This cross-sectional study assessed the signs and symptoms of TMD in CrossFit^® athletes compared to sedentary individuals. (2) Methods: Participants (n = 121) were divided into four groups: sedentary with TMD (n = 39), sedentary without TMD (n = 37), CrossFit^® athletes with TMD (n = 23), and CrossFit^® athletes without TMD (n = 22). TMD signs and symptoms were evaluated using the Research Diagnostic Criteria for TMD (RDC/TMD) axis I, including mandibular movement patterns, range of motion, joint sounds, muscle pain, and jaw dysfunctions. Statistical analyses included chi-square and Dunn’s post hoc tests, ANOVA, and Kruskal–Wallis tests. Correlation and regression analyses were performed to examine associations between CrossFit^® practice and TMD (p ≤ 0.05). (3) Results: Myofascial pain was the most common diagnosis. All athlete groups exhibited greater mandibular movement amplitudes (unassisted opening without pain, p < 0.001, and protrusion, p = 0.039) and less pain (p < 0.001) than sedentary individuals. Pain reports and palpation-induced pain in muscles and joints were significantly associated with a sedentary lifestyle and TMD (p < 0.001). Joint and muscle pain were more prevalent (frequent) among sedentary participants, regardless of TMD diagnosis. Linear regression analysis showed that sedentary individuals without TMD had significantly reduced unassisted mouth opening amplitudes compared to athletes without TMD (p < 0.05). (4) Conclusions: Pain in the masseter, temporalis, posterior digastric, and medial pterygoid muscles was the most common symptom in sedentary individuals with TMD. They experience higher frequency and intensity of pain, as well as greater limitations in mouth movement. Athletes showed higher frequency of joint noises. Full article

This study explores the friction stir welding (FSW) of thin aluminum sheets, focusing on alloys 1050 and 5754. FSW, a solid-state joining technique, offers advantages like minimal deformation and high joint strength, but optimizing welding parameters is crucial for sound welds. In order to investigate the optimum welding parameters, the Taguchi method was employed, in which key parameters such as rotational and welding speed were optimized to enhance tensile strength and weld quality. The tensile testing of the welded specimens revealed that the optimal combination—1000 RPM rotational speed and 250 mm/min welding speed—produced the highest tensile strength and weld quality. The results highlight the importance of parameter optimization in ensuring strong, stable welds, with rotational speed having the most significant influence. Additionally, excessive rotational speeds were found to weaken welds due to excessive heat input, while a slower welding speed contributed to greater weld stability. Full article

This paper presents a comprehensive methodology to enable the optimization of an automotive electric axle to reduce noise emissions and improve load distribution. The proposed method consists of the application of two sequential optimization procedures. The first one focuses on the gears’ macro-geometry, based on an objective function that combines the contact ratio, power loss, and center distance. The second one optimizes the micro-geometry of the teeth to reduce the sound pressure generated by tooth impacts. Mechanical stress limits are considered as a constraint in the optimization process. Shafts, joints, and the electric motor are analyzed, taking into account their deformation that influences the dynamics of the entire system. The results of the proposed procedure are verified through experimental measurements and the comparison can be considered successful. Full article

Background: Knee osteoarthritis (OA) impairs functional mobility, including sit-to-stand and stand-to-sit movements. Thigh muscles stabilize the knee during these transitions, and variations in seat height and foot positioning may affect muscle activation. Assessing thigh muscle activity during these tasks may provide strategies to enhance function and guide targeted rehabilitation for individuals with knee OA. Objective: The aim of this study was to examine the EMG activity of the vastus medialis oblique (VMO), rectus femoris (RF), and biceps femoris (BF) muscles of arthritic knees during sit-to-stand and stand-to-sit movements when using varying seat heights and feet positions. Methods: The EMG activity was recorded from the three thigh muscles in the arthritic side during sit-to-stand and stand-to-sit movements under six different seating conditions from eight patients (three females; mean age: 64.6 ± 11.0 years). A three-way ANOVA was used to examine the effects of seat height, foot positioning, and movement type on muscle activation. Results: The results demonstrated significant interactions between muscle activation, movement type, and seating conditions (p = 0.022). The EMG activity of VMO and RF increased significantly during sit-to-stand movements from lower seat heights compared to knee-height seats (p < 0.05). RF activation was also significantly elevated during stand-to-sit transitions at low seat heights (p = 0.023). Additionally, sit-to-stand transitions with symmetrical foot placement elicited significantly greater VMO activation compared to BF activation (p < 0.05). While BF activation remained relatively low across most conditions, it was highest when the arthritic knee was positioned behind the sound foot during both movements. Conclusions: Seat height and foot positioning significantly impact thigh muscle activation in individuals with knee OA during sit-to-stand and stand-to-sit transitions. Lower seat heights require greater VMO and RF activation, indicating increased mechanical demands. Additionally, placing the arthritic knee behind the sound foot enhances BF activation, suggesting a potential strategy for targeted hamstring engagement. These findings provide directions for quadriceps and hamstring strengthening, alongside strategic seating adjustments to optimize functional mobility and reduce joint stress in individuals with knee OA. Full article

Sound speed profiles (SSPs) must be detected simultaneously to perform a multibeam depth survey. Accurate real-time sound speed profile (SSP) acquisition remains a critical challenge in deep-sea multibeam bathymetry due to the limitations regarding direct measurements under harsh operational conditions. To address the issue, we propose a joint inversion framework integrating World Ocean Atlas 2023 (WOA23) temperature–salinity model data, historical in situ SSPs, and surface sound speed measurements. By constructing a high-resolution regional sound speed field through WOA23 and historical SSP fusion, this method effectively mitigates spatiotemporal heterogeneity and seasonal variability. The artificial lemming algorithm (ALA) is introduced to optimize the inversion of empirical orthogonal function (EOF) coefficients, enhancing global search efficiency while avoiding local optimization. An experimental validation in the northwest Pacific Ocean demonstrated that the proposed method has a better performance than that of conventional substitution, interpolation, and WOA23-only approaches. The results indicate that the mean absolute error (MAE), root mean square error (RMSE), and maximum error (ME) of SSP reconstruction are reduced by 41.5%, 46.0%, and 49.4%, respectively. When the reconstructed SSPs are applied to multibeam bathymetric correction, depth errors are further reduced to 0.193 m (MAE), 0.213 m (RMSE), and 0.394 m (ME), effectively suppressing the “smiley face” distortion caused by sound speed gradient anomalies. The dynamic selection of the first six EOF modes balances computational efficiency and reconstruction fidelity. This study provides a robust solution for real-time SSP estimation in data-scarce deep-sea environments, particularly for underwater autonomous vehicles. This method effectively mitigates the seabed distortion caused by missing real-time SSPs, significantly enhancing the accuracy and efficiency of deep-sea multibeam surveys. Full article