Search Results (14)

At present, researchers in the field of pipeline inspection focus on pipe wall defects while neglecting pipeline defects in special situations such as welds. This poses a threat to the safe operation of projects. In this paper, a multi-node fusion and modal projection algorithm of steel pipes based on guided wave technology is proposed. Through an ANSYS numerical simulation, research is conducted to achieve the identification, localization, and quantification of axial cracks on the surface of straight pipelines and internal cracks in circumferential welds. The propagation characteristics and vibration law of ultrasonic guided waves are theoretically solved by the semi-analytical finite element method in the pipeline. The model section is discretized in one-dimensional polar coordinates to obtain the dispersion curve of the steel pipe. The T(0,1) mode, which is modulated by the Hanning window, is selected to simulate the axial crack of the pipeline and the L(0,2) mode to simulate the crack in the weld, and the correctness of the dispersion curve is verified. The results show that the T(0,1) and L(0,2) modes are successfully excited, and they are sensitive to axial and circumferential cracks. The time–frequency diagram of wavelet transform and the time domain diagram of the crack signal of Hilbert transform are used to identify the echo signal. The first wave packet peak point and group velocity are used to locate the crack. The pure signal of the crack is extracted from the simulation data, and the variation law between the reflection coefficient and the circumferential and radial dimensions of the defect is calculated to evaluate the size of the defect. This provides a new and feasible method for steel pipe defect detection. Full article

Lake ice thickness (LIT) is one of the key climate variables in the lake ice domain, but there are currently large uncertainties in the retrieval of LIT. We present and validate a new LIT retrieval method that utilizes ICESat-2 data to assist CryoSat-2 echo peak selection, aiming to improve the accuracy of LIT retrieval and enable data acquisition without on-site measurements. The method involves screening out similar ICESat-2 and CryoSat-2 tracks based on time and space constraints. It also involves dynamically adjusting the range constraint window of CryoSat-2 waveforms based on the high-precision lake ice surface ellipsoid height obtained from ICESat-2/ATL06 data. Within this range constraint window, the peak selection strategy is used to determine the scattering interfaces between snow-ice and ice-water. By utilizing the distance between the scattering horizons, the thickness of the lake ice can be determined. We performed the ice thickness retrieval experiment for Baker Lake in winter and verified it against the on-site measurement data. The results showed that the accuracy was about 0.143 m. At the same time, we performed the ice thickness retrieval experiment for Great Bear Lake (GBL), which does not have on-site measurement data, and compared it with the climate change trend of GBL. The results showed that the retrieval results were consistent with the climate change trend of GBL, confirming the validity of the proposed method. Full article

Radio-echo sounding (RES) is widely used for polar ice sheet detection due to its wide coverage and high efficiency. The multivariate variational mode decomposition (MVMD) algorithm for the processing of RES data is an improvement to the variational mode decomposition (VMD) algorithm. It processes data encompassing multiple channels. Determining the most effective component combination of the penalty parameter (α) and the number of intrinsic mode functions (IMFs) (K) is fundamental and affects the decomposition results. α and K in traditional MVMD are provided by subjective experience. We integrated the particle swarm optimization (PSO) algorithm to iteratively optimize these parameters—specifically, α and K—with high precision. This was then combined with the four quantitative parameters: energy entropy, signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and root-mean-square error (RMSE). The RES signal decomposition results were judged, and the most effective component combination for noise suppression was selected. We processed the airborne RES data from the East Antarctic ice sheet using the combined PSO–MVMD method. The results confirmed the quality of the proposed method in attenuating the RES signal noise, enhancing the weak signal of the ice base, and improving the SNR. This combined PSO–MVMD method may help to enhance weak signals in deeper parts of ice sheets and may be an effective tool for RES data interpretation. Full article

The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional echo-planar correlated spectroscopic imaging (5D EP-COSI) and diffusion-weighted imaging (DWI). Twenty-four different metabolite and lipid ratios with respect to diagonal fat peaks (1.4 ppm, 5.4 ppm) from 2D spectra, and water and fat peaks (4.7 ppm, 1.4 ppm) from one-dimensional non-water-suppressed (NWS) spectra were used as the features. Additionally, water fraction, fat fraction and water-to-fat ratios from NWS spectra and apparent diffusion coefficients (ADC) from DWI were included. The nine most important features were identified using recursive feature elimination, sequential forward selection and correlation analysis. XGBoost (AUC: 93.0%, Accuracy: 85.7%, F1-score: 88.9%, Precision: 88.2%, Sensitivity: 90.4%, Specificity: 84.6%) and GradientBoost (AUC: 94.3%, Accuracy: 89.3%, F1-score: 90.7%, Precision: 87.9%, Sensitivity: 94.2%, Specificity: 83.4%) were the best-performing models. Conventional biomarkers like choline, myo-Inositol, and glycine were statistically significant predictors. Key features contributing to the classification were ADC, 2D diagonal peaks at 0.9 ppm, 2.1 ppm, 3.5 ppm, and 5.4 ppm, cross peaks between 1.4 and 0.9 ppm, 4.3 and 4.1 ppm, 2.3 and 1.6 ppm, and the triglyceryl–fat cross peak. The results highlight the contribution of the 2D spectral peaks to the model, and they demonstrate the potential of 5D EP-COSI for early breast cancer detection. Full article

X-band dual-polarization phased array radar (XPAR-D) possesses high resolution and plays a significant role in detecting meso- and micro-scale convective systems. However, the precipitation attenuation it endures necessitates an effective correction method. This study selected radar data from XPAR-D at the peak of Maofeng Mountain in Guangzhou during 16–17 May 2020 from three precipitation stages after quality control. Attenuation coefficients were calculated for different precipitation types through scattering simulations of raindrop size distribution (RSD) data. Next, an attenuation correction algorithm (MZ_H-K_DP method) was proposed for the radar reflectivity factor (Z_H) according to different raindrop types and compared to the Z_H-K_DP method currently in use. The results indicate that the attenuation amount of XPAR-D echoes depends on the attenuation path and echo intensity. When the attenuation path is shorter and the echo intensity is weaker, the amount of attenuation and correction is smaller. Difficulties arise when there are noticeable deviations, which are challenging to resolve using attenuation correction methods. Longer attenuation paths and stronger echoes highlight the advantages of the MZ_H-K_DP method, while the Z_H-K_DP method tends to overcorrect the bias. The MZ_H-K_DP method outperforms the Z_H-K_DP method for different precipitation types. The superior correction capability of the MZ_H-K_DP method provides a significant advantage in improving the performance of XPAR-D for the detection of extreme weather. Full article

Background: The complete left bundle branch block (CLBBB) results in ventricular dyssynchrony and a reduction in systolic and diastolic efficiency. We noticed a distinct clockwise rotation of the left ventricle (LV) in patients with CLBBB (“longitudinal rotation”). Aim: The aim of this study was to quantify the “longitudinal rotation” of the LV in patients with CLBBB in comparison to patients with normal conduction or complete right bundle branch block (CRBBB). Methods: Sixty consecutive patients with normal QRS, CRBBB, or CLBBB were included. Stored raw data DICOM 2D apical-4 chambers view images cine clips were analyzed using EchoPac plugin version 203 (GE Vingmed Ultrasound AS, Horten, Norway). In EchoPac–Q-Analysis, 2D strain application was selected. Instead of apical view algorithms, the SAX-MV (short axis—mitral valve level) algorithm was selected for analysis. A closed loop endocardial contour was drawn to initiate the analysis. The “posterior” segment (representing the mitral valve) was excluded before finalizing the analysis. Longitudinal rotation direction, peak angle, and time-to-peak rotation were recorded. Results: All patients with CLBBB (n = 21) had clockwise longitudinal rotation with mean four chamber peak rotation angle of −3.9 ± 2.4°. This rotation is significantly larger than in patients with normal QRS (−1.4 ± 3°, p = 0.005) and CRBBB (0.1 ± 2.2°, p = 0.00001). Clockwise rotation was found to be correlated to QRS duration in patients with the non-RBBB pattern. The angle of rotation was not associated with a lower ejection fraction or the presence of regional wall abnormalities. Conclusions: Significant clockwise longitudinal rotation was found in CLBBB patients compared to normal QRS or CRBBB patients using speckle-tracking echocardiography. Full article

The single-beam bathymetric light detection and ranging (LiDAR) system 1 (SBLS-1), which is equipped with a 532-nm-band laser projector and two concentric-circle receivers for shallow- and deep-water echo signals, is a lightweight and convenient prototype instrument with low energy consumption. In this study, a novel LiDAR bathymetric method is utilized to achieve single-beam and dual-channel bathymetric characteristics, and an adaptive extraction method is proposed based on the cumulative standard deviation of the peak and trough, which is mainly used to extract the signal segment and eliminate system and random noise. To adapt the dual-channel bathymetric mechanism, an automatic channel-selection method was used at various water depths. A minimum half-wavelength Gaussian iterative decomposition is proposed to improve the detection accuracy of the surface- and bottom-water waveform components and ensure bathymetric accuracy and reliability. Based on a comparison between the experimental results and in situ data, it was found that the SBLS-1 obtained a bathymetric accuracy and RMSE of 0.27 m and 0.23 m at the Weifang and Qingdao test fields. This indicates that the SBLS-1 was bathymetrically capable of acquiring a reliable, high-efficiency waveform dataset. Hence, the novel LiDAR bathymetric method can effectively achieve high-accuracy near-shore bathymetry. Full article

Plasma sheath poses a serious challenge to inverse synthetic aperture radar (ISAR) imaging of hypersonic targets. This paper investigated the distribution characteristics of the electron density and velocity field in the plasma sheath surrounding the hypersonic target in various flight scenes. The incident depth and reflective surface of electromagnetic (EM) waves with X-band, Ku-band, and Ka-band can be determined based on the plasma frequency. We established the echo model coupled with the velocity field of the plasma sheath on the reflective surface and obtained one-dimensional range profiles and ISAR images of the hypersonic target in various flight scenes. The simulation results indicated that the non-uniform velocity field on the reflective surface induced displacement and diffusion in the one-dimensional range profile, resulting in ISAR image distortion. A changing flight scene and radar frequency can have an impact on imaging results. Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) were utilized to assess the impact of plasma sheath on ISAR images. This study revealed the defocus mechanism of the ISAR image caused by the velocity field of the plasma sheath and provided a theoretical reference for the selection of radar frequency for hypersonic targets in various flight scenes. Full article

We report on a self-adaptive waveform centroid algorithm that combines the selection of double-scale data and the intensity-weighted (DSIW) method for accurate LiDAR distance–intensity imaging. A time window is set to adaptively select the effective data. At the same time, the intensity-weighted method can reduce the influence of sharp noise on the calculation. The horizontal and vertical coordinates of the centroid point obtained by the proposed algorithm are utilized to record the distance and echo intensity information, respectively. The proposed algorithm was experimentally tested, achieving an average ranging error of less than 0.3 ns under the various noise conditions in the listed tests, thus exerting better precision compared to the digital constant fraction discriminator (DCFD) algorithm, peak (PK) algorithm, Gauss fitting (GF) algorithm, and traditional waveform centroid (TC) algorithm. Furthermore, the proposed algorithm is fairly robust, with remarkably successful ranging rates of above 97% in all tests in this paper. Furthermore, the laser echo intensity measured by the proposed algorithm was proved to be robust to noise and to work in accordance with the transmission characteristics of LiDAR. Finally, we provide a distance–intensity point cloud image calibrated by our algorithm. The empirical findings in this study provide a new understanding of using LiDAR to draw multi-dimensional point cloud images. Full article

Oncolytic viruses (OVs) are emerging as promising and potential anti-cancer therapeutic agents, not only able to kill cancer cells directly by selective intracellular viral replication, but also to promote an immune response against tumor. Unfortunately, the bioavailability under systemic administration of OVs is limited because of undesired inactivation caused by host immune system and neutralizing antibodies in the bloodstream. To address this issue, a novel hyaluronic acid based redox responsive nanohydrogel was developed in this study as delivery system for OVs, with the aim to protect the OVs following systemic administration. The nanohydrogel was formulated by water in oil (W/O) nanoemulsion method and cross-linked by disulfide bonds derived from the thiol groups of synthesized thiolated hyaluronic acid. One DNA OV Ad[I/PPT-E1A] and one RNA OV Rigvir^® ECHO-7 were encapsulated into the developed nanohydrogel, respectively, in view of their potential of immunovirotherapy to treat cancers. The nanohydrogels showed particle size of approximately 300–400 nm and negative zeta potential of around −13 mV by dynamic light scattering (DLS). A uniform spherical shape of the nanohydrogel was observed under the scanning electron microscope (SEM) and transmission electron microscope (TEM), especially, the successfully loading of OV into nanohydrogel was revealed by TEM. The crosslinking between the hyaluronic acid chains was confirmed by the appearance of new peak assigned to disulfide bond in Raman spectrum. Furthermore, the redox responsive ability of the nanohydrogel was determined by incubating the nanohydrogel into phosphate buffered saline (PBS) pH 7.4 with 10 μM or 10 mM glutathione at 37 °C which stimulate the normal physiological environment (extracellular) or reductive environment (intracellular or tumoral). The relative turbidity of the sample was real time monitored by DLS which indicated that the nanohydrogel could rapidly degrade within 10 h in the reductive environment due to the cleavage of disulfide bonds, while maintaining the stability in the normal physiological environment after 5 days. Additionally, in vitro cytotoxicity assays demonstrated a good oncolytic activity of OVs-loaded nanohydrogel against the specific cancer cell lines. Overall, the results indicated that the developed nanohydrogel is a delivery system appropriate for viral drugs, due to its hydrophilic and porous nature, and also thanks to its capacity to maintain the stability and activity of encapsulated viruses. Thus, nanohydrogel can be considered as a promising candidate carrier for systemic administration of oncolytic immunovirotherapy. Full article

Due to the influence of equipment instability and surveying environment, scattering echoes and other factors, it is sometimes difficult to obtain high-quality sub-bottom profile (SBP) images by traditional denoising methods. In this paper, a novel SBP image denoising method is developed for obtaining underlying clean images based on a non-local low-rank framework. Firstly, to take advantage of the inherent layering structures of the SBP image, a direction image is obtained and used as a guidance image. Secondly, the robust guidance weight for accurately selecting the similar patches is given. A novel denoising method combining the weight and a non-local low-rank filtering framework is proposed. Thirdly, after discussing the filtering parameter settings, the proposed method is tested in actual measurements of sub-bottom, both in deep water and shallow water. Experimental results validate the excellent performance of the proposed method. Finally, the proposed method is verified and compared with other methods quantificationally based on the synthetic images and has achieved the total average peak signal-to-noise ratio (PSNR) of 21.77 and structural similarity index (SSIM) of 0.573, which is far better than other methods. Full article

Low-field nuclear magnetic resonance (NMR) has been widely used in the petroleum industry for reservoir evaluation. Fluid properties and petrophysical parameters can be determined from NMR spectra, obtained from processing echo data measured from the NMR tool. The more accurate NMR spectra are, the higher the reliability of reservoir evaluation based on NMR logging is. The purpose of this paper is to obtain more precise T₁–T₂ spectra in heavy oil reservoirs, with focus on the T₁–T₂ data acquisition and inversion. To this end, four inversion algorithms were tested on synthetic T₁–T₂ data, their precision was evaluated and the optimal inversion algorithm was selected. Then, the sensitivity to various acquisition parameters (wait time and echo spacing) was evaluated with T₁–T₂ experiments using a disordered accumulation of glass beads with a diameter of 45 μm saturated with heavy oil and distilled water. Finally, the sensitivity to various inversion parameters (convergence tolerance, maximum number of iterations and regularization parameter) was evaluated using the optimal inversion algorithm. The results showed that the inverted T₁–T₂ spectra loss some relaxation information when the number of echo train is less than 7. The peak of the heavy oil signal gradually moves along the direction of increase in the T₂ and the intensity of the heavy oil signal gradually decreases with increasing echo spacing. The echo spacing should be as small as possible for T₁–T₂ measurements in heavy oil reservoirs on the premise that the NMR instrument operates normally. A convergence tolerance that is too large or a maximum number of iterations that is too small may result in exiting the iteration prematurely during the inversion. A convergence tolerance of 1 × 10⁻⁷ and a maximum number of iterations of 30,000 are recommended for the inversion of the T₁–T₂ spectra. An appropriate regularization parameter is an important factor for obtaining accurate T₁–T₂ spectra from the optimal inversion algorithm. Full article

In an airborne laser bathymetry system, the full-waveform echo signal is usually recorded by discrete sampling. The accuracy of signal recognition and the amount of effective information that can be extracted by conventional methods are limited. To improve the validity and reliability of airborne laser bathymetry data and to extract more information to better understand the water reflection characteristics, we select the effective portion of the original waveform for further research, suppress random noise, and decompose the selected portion progressively using the half-wavelength Gaussian function with the time sequence of the received echo signals. After parameter optimization, a reasonable and effective reflection component selection mechanism is established to obtain accurate parameters for the reflected components. The processing strategy proposed in this paper reduces the problems of unreasonable decomposition and the reflected pulse peak-position shift caused by echo waveform superposition and offers good precision for waveform decomposition and peak detection. In another experiment, the regional processing result shows an obvious improvement in the shallow water area, and the bottom point cloud is as accurate as the intelligent waveform digitizer (IWD), a subsystem of airborne laser terrain mapping (ALTM). These findings confirm that the proposed method has high potential for application. Full article

2-hydroxyglutarate (2-HG) has emerged as a biomarker of tumor cell isocitrate dehydrogenase mutations that may enable the differential diagnosis of patients with glioma. At 3 T, detection of 2-HG with magnetic resonance spectroscopy is challenging because of metabolite signal overlap and spectral pattern modulation by slice selection and chemical shift displacement. Using density matrix simulations and phantom experiments, an optimized semi-LASER scheme (echo time = 110 milliseconds) considerably improves localization of the 2-HG spin system compared with that of an existing point-resolved spectroscopy sequence. This results in a visible 2-HG peak in the in vivo spectra at 1.9 ppm in the majority of isocitrate dehydrogenase-mutated tumors. Detected concentrations of 2-HG were similar using both sequences, although the use of semi-LASER generated narrower confidence intervals. Signal overlap with glutamate and glutamine, as measured by pairwise fitting correlation, was reduced. Lactate was readily detectable across patients with glioma using the method presented here (mean Cramér–Rao lower bound: 10% ± 2%). Together with more robust 2-HG detection, long-echo time semi-LASER offers the potential to investigate tumor metabolism and stratify patients in vivo at 3 T. Full article