Search Results (32)

Background: Intracranial aneurysm (IA) rupture is a life-threatening cerebrovascular event with a mortality rate of up to 40%, affecting approximately 500,000 people globally each year. Although environmental pollutants such as 2,2′,4,4′-tetrabromodiphenyl ether (PBDE-47) have been implicated in the pathogenesis of IA, the causal relationship and underlying mechanisms remain unclear. This study aims to systematically explore the potential causal role of PBDE-47 in the development of IA by integrating multi-omics approaches. Methods: We utilized the UK Biobank Drug Proteomics Project (UKB-PPP) genome-wide association study (GWAS) data, including 2940 plasma proteins and 1400 metabolites, along with IA genetic data from 456,348 individuals, to perform a two-sample Mendelian randomization (MR) analysis. Instrumental variables were selected based on genome-wide significance (p < 5 × 10⁻⁸) or suggestive thresholds (p < 5 × 10⁻⁵). Analytical methods included inverse variance weighting (IVW), MR-Egger, weighted median, MR-PRESSO, and Steiger filtering for sensitivity analysis. Molecular docking and 100-nanosecond molecular dynamics simulations were used to evaluate interactions between PBDE-47 and proteins. Mediation analysis assessed the roles of plasma metabolites and miRNAs, and SMR-HEIDI tests were used to verify causal relationships. Results: MR analysis identified 93 plasma proteins potentially causally associated with IA, including 53 protective factors and 40 risk factors. By integrating PBDE-47 targets, IA-related genes, and metabolite-related genes, we identified 15 hub genes. Molecular docking revealed potential binding between PBDE-47 and F2R (binding energy: −5.516 kcal/mol), and SMR-HEIDI testing supported F2R as a potential causal risk factor for IA. Molecular dynamics simulations indicated the stability of the complex structure. Mediation analysis suggested that F2R may influence IA risk through eight plasma metabolites, and miR-130b-3p may indirectly promote IA development by upregulating F2R. Conclusions: Our findings suggest that exposure to PBDE-47 may have a potential causal relationship with IA risk, potentially mediated through the “PBDE–47–F2R–metabolite–miRNA” regulatory axis. These results provide preliminary evidence for early diagnostic biomarkers and targeted interventions for IA. The multi-omics analytical framework established in this study offers new insights into environmental determinants of neurovascular diseases, although further validation is needed to address potential limitations. Full article

This study proposes a novel framework to enhance inner race fault features in servo motor bearings by acquiring rotary encoder-derived instantaneous angular speed (IAS) signals, which are obtained from a servo motor encoder without requiring additional external sensors. However, such signals are often obscured by strong periodic interferences from motor pole-pair and shaft rotation order components. To address this issue, three key improvements are introduced within the cyclic blind deconvolution (CYCBD) framework: (1) a comb-notch filtering strategy based on rotation domain synchronous averaging (RDA) to suppress dominant periodic interferences; (2) an adaptive fault order estimation method using the autocorrelation of the squared envelope spectrum (SES) for robust localization of the true fault modulation order; and (3) an improved envelope harmonic product (IEHP), based on the geometric mean of harmonics, which optimizes the deconvolution filter length. These combined enhancements enable the proposed improved CYCBD (ICYCBD) method to accurately extract weak fault-induced cyclic impulses under complex interference conditions. Experimental validation on a test rig demonstrates the effectiveness of the approach in enhancing and extracting the fault-related features associated with the inner race defect. Full article

Drought is an extremely terrifying environmental calamity, causing declining agricultural production, escalating food prices, water scarcity, soil erosion, increased wildfire risks, and changes in ecosystem. Drought data is noisy and poses challenges to accurate forecasts due to it being nonstationary and non-linear. This research aims to construct a contemporary and novel approach termed as TVFEMD-GPR, crossbreeding time varying filter-based empirical mode decomposition (TVFEMD) and gaussian process regression (GPR), to model multi-scaler standardized precipitation index (SPI) to forecast droughts. At first, the statistically significant lags at (t − 1) were computed via partial auto-correlation function (PACF). In the second step, the TVFEMD splits the (t − 1) lag into several factors named as intrinsic mode functions (IMFs) and residual components. The third step is the final step, where the GPR model took the IMFs and residual as input predictors to forecast one-month SPI (SPI1), three-months SPI (SPI3), six-months SPI (SPI6), and twelve-months SPI1 (SPI12) for Mackay and Springfield stations in Australia. To benchmark the new TVFEMD-GPR model, the long short-term memory (LSTM), boosted regression tree (BRT), and cascaded forward neural network (CFNN) were also developed to assess their accuracy in drought forecasting. Moreover, the TVFEMD was integrated to create TVFEMD-LSTM, TVFEMD-BRT, and TVFEMD-CFNN models to forecast multi-scaler SPI where the TVFEMD-GPR surpassed all comparable models in both stations. The outcomes proved that the TVFEMD-GPR outperformed comparable models by acquiring ENS = 0.5054, IA = 0.8082, U95% = 1.8943 (SPI1), ENS = 0.6564, IA = 0.8893, U95% = 1.5745(SPI3), ENS = 0.8237, IA = 0.9502, U95% = 1.1123 (SPI6), and ENS = 0.9285, IA = 0.9813, U95% = 0.7228 (SPI12) for Mackay Station. For Station 2 (Springfield), the TVFEMD-GPR obtained these metrics as ENS = 0.5192, IA = 0.8182, U95% = 1.9100 (SPI1), ENS = 0.6716, IA = 0.8953, U95% = 1.5163 (SPI3), ENS = 0.8289, IA = 0.9534, U95% = 1.1296 (SPI6), and ENS = 0.9311, IA = 0.9829, and U95% = 0.7695 (SPI12). The research exhibits the practicality of the TVFEMD-GPR model to anticipate drought events, minimize their impacts, and implement timely mitigation strategies. Moreover, the TVFEMD-GPR can assist in early warning systems, better water management, and reducing economic losses. Full article

To solve the low efficiency of traditional sheet metal measurement, this paper proposes a digital inspection method for sheet metal parts based on 3D point clouds. The 3D point cloud data of sheet metal parts are collected using a 3D laser scanner, and the topological relationship is established by using a K-dimensional tree (KD tree). The pass-through filtering method is adopted to denoise the point cloud data. To preserve the fine features of the parts, an improved voxel grid method is proposed for the downsampling of the point cloud data. Feature points are extracted via the intrinsic shape signatures (ISS) algorithm and described using the fast point feature histograms (FPFH) algorithm. After rough registration with the sample consensus initial alignment (SAC-IA) algorithm, an initial position is provided for fine registration. The improved iterative closest point (ICP) algorithm, used for fine registration, can enhance the registration accuracy and efficiency. The greedy projection triangulation algorithm optimized by moving least squares (MLS) smoothing ensures surface smoothness and geometric accuracy. The reconstructed 3D model is projected onto a 2D plane, and the actual dimensions of the parts are calculated based on the pixel values of the sheet metal parts and the conversion scale. Experimental results show that the measurement error of this inspection system for three sheet metal workpieces ranges from 0.1416 mm to 0.2684 mm, meeting the accuracy requirement of ±0.3 mm. This method provides a reliable digital inspection solution for sheet metal parts. Full article

To overcome incomplete point cloud data obtained from laser scanners scanning complex surfaces, multi-viewpoint cloud data needs to be aligned for use. A hybrid improved SAC-IA with a KD-ICP algorithm is proposed for local point cloud alignment optimization. The scanned point cloud data is preprocessed with statistical filtering, as well as uniform down-sampling. The sampling consistency initial alignment (SAC-IA) algorithm is improved by introducing a dissimilarity vector for point cloud initial alignment. In addition, the iterative closest point (ICP) algorithm is improved by incorporating bidirectional KD-tree to form the KD-ICP algorithm for fine point cloud alignment. Finally, the algorithms are compared in terms of runtime and alignment accuracy. The implementation of the algorithms is based on the Visual Studio 2013 software configurating point cloud library environment for testing experiments and practical experiments. The overall alignment method can be 40%~50% faster in terms of running speed. The improved SAC-IA algorithm provides better transformed poses, combined with the KD-ICP algorithm to select the corresponding nearest neighbor pairs, which improves the accuracy, as well as the applicability of the alignment. Full article

Traditional iterative closest point (ICP) registration algorithms are sensitive to initial positions and easily fall into the trap of locally optimal solutions. To address this problem, a point cloud registration algorithm is put forward in this study based on adaptive neighborhood eigenvalue loading ratios. In the algorithm, the resolution of the point cloud is first calculated and used as an adaptive basis to determine the raster widths and radii of spherical neighborhoods in the raster filtering; then, the adaptive raster filtering is implemented to the point cloud for denoising, while the eigenvalue loading ratios of point neighborhoods are calculated to extract and match the contour feature points; subsequently, sample consensus initial alignment (SAC-IA) is used to carry out coarse registration; and finally, a fine registration is delivered with KD-tree-accelerated ICP. The experimental results of this study demonstrate that the feature points extracted with this method are highly representative while consuming only 35.6% of the time consumed by other feature point extraction algorithms. Additionally, in noisy and low-overlap scenarios, the registration error of this method can be controlled at a level of 0.1 mm, with the registration speed improved by 56% on average over that of other algorithms. Taken together, the method in this study cannot only ensure strong robustness in registration but can also deliver high registration accuracy and efficiency. Full article

Analog front-end (AFE) circuits play an important role in the acquisition of physiological signals with low-level amplitudes (from tens of μV to tens of mV) and broadband low-frequency ranges (from sub-Hz to several hundred Hz). Possessing a high input impedance, an instrumentation amplifier (IA) accurately amplifies signals with low amplitude and low frequency, making it suitable for AFE circuits. This work demonstrates a capacitively coupled IA whose feedback resistance is realized by the proposed hybrid resistor, consisting of a switched-capacitor low-pass filter, a switched-capacitor resistor, and a continuous-time low-pass filter. The capacitively coupled IA achieves tera-ohm (TΩ) resistance and is insensitive to process, voltage, and temperature (PVT) variations. The simulation results show that the proposed IA illustrates a high-pass corner of 73.9 mHz, and the change of its high-pass corner with temperature is 0.05 mHz/°C. With the variation in the PVT corners, the difference between the maximum and minimum values of the high-pass corner of the proposed capacitively coupled IA is only 0.06 Hz. The design was implemented in a 130 nm standard CMOS process. The AFE with the proposed capacitively coupled IA achieves a 53.9 dB signal-to-noise and distortion ratio (SNDR) and 69.5 dB total harmonic distortion (THD). Full article

Due to the intense noise interference in hydraulic systems, it is extremely difficult to detect component faults through vibration signals. Diagnostic performance is also constrained by highly time-varying and non-stationary operating conditions. This study proposes to use instantaneous angular speed (IAS) signals that are both operational and state parameters as sources of information. Firstly, the instantaneous angular speed fluctuation (IASF) of a piston pump is analyzed theoretically, and it is concluded that its fluctuating components contain the health status information of the components. The IASF can then be obtained by subtracting the speed trend term from IAS signals obtained via a magneto-electric speed sensor. A synchro-extraction of the normal S transform (SNST) is proposed to process it via line-pass filtering. Finally, the filtered and reconstructed IASF signal is utilized to draw a two-dimensional polar coordinate map online. A non-stationary-condition test is carried out on the test platform to monitor the morphological characteristics of the valve plate under normal, slight, and severe wear conditions. The polar plot shows significant increases in speed fluctuations and oscillation times within a range from 180° to 270°. The relevant research results reflect that the IAS signal can provide a new method for monitoring the operating status of and conducting fault diagnoses for hydraulic equipment. Full article

This paper proposes a stereo-vision-based method that detects and registers the positions and postures of muti-type, randomly placed miniature circuit breaker (MCB) components within scene point clouds acquired by a 3D stereo camera. The method is designed to be utilized in the flexible assembly of MCBs to improve the precision of gripping small-sized and complex-structured components. The proposed method contains the following stages: First, the 3D computer-aided design (CAD) models of the components are converted to surface point cloud models by voxel down-sampling to form matching templates. Second, the scene point cloud is filtered, clustered, and segmented to obtain candidate-matching regions. Third, point cloud features are extracted by Intrinsic Shape Signatures (ISSs) from the templates and the candidate-matching regions and described by Fast Point Feature Histogram (FPFH). We apply Sample Consensus Initial Alignment (SAC-IA) to the extracted features to obtain a rough matching. Fourth, fine registration is performed by employing Iterative Closest Points (ICPs) with a K-dimensional Tree (KD-tree) between the templates and the roughly matched targets. Meanwhile, Random Sample Consensus (RANSAC), which effectively solves the local optimal problem in the classic ICP algorithm, is employed to remove the incorrectly matching point pairs for further precision improvement. The experimental results show that the proposed method achieves spatial positioning errors smaller than 0.2 mm and postural estimation errors smaller than 0.5°. The precision and efficiency meet the requirements of the robotic flexible assembly for MCBs. Full article

It is critical for the safety monitoring of highway bridges that beam bridge damage can be identified from the dynamic response of passing vehicles. Numerical simulations of passing vehicles were conducted utilizing the vehicle–bridge coupling vibration theory and the indirect measurement method. Fast Fourier transform was performed on the time history response of vehicle acceleration, and the driving frequency component response and its instantaneous amplitude square value (IAS value) were obtained by band-pass filtering and Hilbert transform processing. The identified IAS value detected the damage location of the bridge. The identification method of IAS value is used to analyze the applicability of a simply supported beam bridge, a continuous beam bridge, and an irregular skew beam bridge. The effects of vehicle speed, vehicle damping, bridge damping, and a social vehicle on damage identification are discussed. The results show that the effect of damage location is better when the vehicle speed is less than 4 m/s. In the presence of social vehicles, the excitation on the bridge increases, and the damage location can still be accurately determined by the IAS method. Vehicle damping and bridge damping have little effect on the results of damage identification. In structural health monitoring for bridges, this paper can provide a theoretical reference for the application of IAS motion sensing to identify the damage location indirectly. Full article

In environment sound classification, log Mel band energies (MBEs) are considered as the most successful and commonly used features for classification. The underlying algorithm, fast Fourier transform (FFT), is valid under certain restrictions. In this study, we address these limitations of Fourier transform and propose a new method to extract log Mel band energies using amplitude modulation and frequency modulation. We present a comparative study between traditionally used log Mel band energy features extracted by Fourier transform and log Mel band energy features extracted by our new approach. This approach is based on extracting log Mel band energies from estimation of instantaneous frequency (IF) and instantaneous amplitude (IA), which are used to construct a spectrogram. The estimation of IA and IF is made by associating empirical mode decomposition (EMD) with the Teager–Kaiser energy operator (TKEO) and the discrete energy separation algorithm. Later, Mel filter bank is applied to the estimated spectrogram to generate EMD-TKEO-based MBEs, or simply, EMD-MBEs. In addition, we employ the EMD method to remove signal trends from the original signal and generate another type of MBE, called S-MBEs, using FFT and a Mel filter bank. Four different datasets were utilised and convolutional neural networks (CNN) were trained using features extracted from Fourier transform-based MBEs (FFT-MBEs), EMD-MBEs, and S-MBEs. In addition, CNNs were trained with an aggregation of all three feature extraction techniques and a combination of FFT-MBEs and EMD-MBEs. Individually, FFT-MBEs achieved higher accuracy compared to EMD-MBEs and S-MBEs. In general, the system trained with the combination of all three features performed slightly better compared to the system trained with the three features separately. Full article

Contaminants of emerging concern (CEC) localize in the biome in variable combinations of complex mixtures that are often environmentally persistent, bioaccumulate and biomagnify, prompting a need for extensive monitoring. Many cosmetics include UV filters that are listed as CECs, such as benzophenone derivatives (oxybenzone, OXYB), cinnamates (2-ethylhexyl 4-methoxycinnamate, EMC) and camphor derivatives (4-methylbenzylidene-camphor, 4MBC). Furthermore, in numerous water sources, these UV filters have been detected together with Bisphenols (BPs), which are commonly used in plastics and can be physiologically detrimental. We utilized bioluminescent bacteria (Microtox assay) to monitor these CEC mixtures at environmentally relevant doses, and performed the first systematic study involving three sunscreen components (OXYB, 4MBC and EMC) and three BPs (BPA, BPS or BPF). Moreover, a breast cell line and cell viability assay were employed to determine the possible effect of these mixtures on human cells. Toxicity modeling, with concentration addition (CA) and independent action (IA) approaches, was performed, followed by data interpretation using Model Deviation Ratio (MDR) evaluation. The results show that UV filter sunscreen constituents and BPs interact at environmentally relevant concentrations. Of notable interest, mixtures containing any pair of three BPs (e.g., BPA + BPS, BPA + BPF and BPS + BPF), together with one sunscreen component (OXYB, 4MBC or EMC), showed strong synergy or overadditive effects. On the other hand, mixtures containing two UV filters (any pair of OXYB, 4MBC and EMC) and one BP (BPA, BPS or BPF) had a strong propensity towards concentration dependent underestimation. The three-component mixtures of UV filters (4MBC, EMC and OXYB) acted in an antagonistic manner toward each other, which was confirmed using a human cell line model. This study is one of the most comprehensive involving sunscreen constituents and BPs in complex mixtures, and provides new insights into potentially important interactions between these compounds. Full article

In order to improve industrial production efficiency, a hand–eye system based on 3D vision is proposed and the proposed system is applied to the assembly task of workpieces. First, a hand–eye calibration optimization algorithm based on data filtering is proposed in this paper. This method ensures the accuracy required for hand–eye calibration by filtering out part of the improper data. Furthermore, the improved U-net is adopted for image segmentation and SAC-IA coarse registration ICP fine registration method is adopted for point cloud registration. This method ensures that the 6D pose estimation of the object is more accurate. Through the hand–eye calibration method based on data filtering, the average error of hand–eye calibration is reduced by 0.42 mm to 0.08 mm. Compared with other models, the improved U-net proposed in this paper has higher accuracy for depth image segmentation, and the A_cc coefficient and D_ice coefficient achieve 0.961 and 0.876, respectively. The average translation error, average rotation error and average time-consuming of the object recognition and pose estimation methods proposed in this paper are 1.19 mm, 1.27°, and 7.5 s, respectively. The experimental results show that the proposed system in this paper can complete high-precision assembly tasks. Full article

Hospital wastewaters often carry multidrug-resistant bacteria and priority pathogens, such as methicillin-resistant Staphylococcus aureus (MRSA). Pathogens and antibiotic resistance genes present in wastewaters may reach the natural environment facilitating their spread. Thus, we aimed to isolate MRSA from wastewater of 3 hospitals located in the north of Portugal and to characterize the isolates regarding the antimicrobial resistance and genetic lineages. A total of 96 wastewater samples were collected over six months. The water was filtered, and the filtration membrane was immersed in BHI broth supplemented with 6.5% of NaCl and incubated. The inoculum was streaked in ORSAB agar plates for MRSA isolation. The isolates susceptibility testing was performed against 14 antimicrobial agents. The presence of resistance and virulence genes was accessed by PCR. Molecular typing was performed in all isolates. From the 96 samples, 28 (29.2%) were MRSA-positive. Most isolates had a multidrug-resistant profile and carried the mecA, blaZ, aac(6′)-Ie-aph(2″)-Ia, aph(3′)-IIIa, ermA, ermB, ermC, tetL, tetM, dfrA dfrG and cat_pC221 genes. Most of the isolates were ascribed to the immune evasion cluster (IEC) type B. The isolates belonged to ST22-IV, ST8-IV and ST105-II and spa-types t747, t1302, t19963, t6966, t020, t008 and tOur study shows that MRSA can be found over time in hospital wastewater. The wastewater treatment processes can reduce the MRSA load. The great majority of the isolates belonged to ST22 and spa-type t747 which suggests the fitness of these genetic lineages in hospital effluents. Full article

Power Hardware-in-the-Loop (PHiL) simulation is an emerging testing methodology of real hardware equipment within an emulated virtual environment. The closed loop interfacing between the Hardware under Test (HuT) and the Real Time Simulation (RTS) enables a realistic simulation but can also result in an unstable system. In addition to fundamentals in PHiL simulation and interfacing, this paper therefore provides a consistent and comprehensive study of PHiL stability. An analytic analysis is compared with a simulative approach and is supplemented by practical validations of the stability limits in PHiL simulation. Special focus is given on the differences between a switching and a linear amplifier as power interface (PI). Stability limits and the respective factors of influence (e.g., Feedback Current Filtering) are elaborated with a minimal example circuit with voltage-type Ideal Transformer Model (ITM) PHiL interface algorithm (IA). Finally, the findings are transferred to a real low-voltage grid PHiL application with residential load and photovoltaic system. Full article