Search Results (7)

Peak detection is a fundamental task in spectral and time-series data analysis across diverse scientific and engineering disciplines, yet traditional approaches are highly sensitive to the choice of algorithm parameters, complicating reliable and consistent interpretation. Triggered by the requirement for the energy calibration for the 128 detectors of the PI3SO gamma ray scanner, we introduce a versatile methodology inspired by concepts from persistent homology, extending the traditional notion of persistence to a multi-parameter setting. Our approach systematically explores the space defined by multiple detection parameters and quantifies peak robustness through the hyper-volume in the parameter space where each peak is consistently identified. This volumetric multi-parameter persistence (VM-PP) measure enables robust peak ranking and significantly reduces the sensitivity of detection outcomes to individual parameter selection, demonstrating utility across simulated and experimental spectral datasets. Extensive validation reveals that this method reliably differentiates genuine peaks from noise-induced fluctuations under diverse noise conditions, proving effective in practical spectroscopic calibration scenarios. This framework, general by design, can be readily adapted to diverse signal-processing applications, enhancing interpretability and reliability in complex feature-detection tasks. Full article

The development of shale gas relies on hydraulic fracturing technology and requires the injection of a large amount of fracturing fluid. The well shut-off period after fracturing can promote water infiltration and suction. Optimizing the well shut-off time is crucial for enhancing the recovery rate. Among existing methods, the dimensionless time model is widely used, but it has limitations because it does not represent the length of on-site scale features. In this study, we focused on the shut-in time for a deep shale gas well (Lu-A) in Luzhou and a medium-deep shale gas well (Wei-B) in Weiyuan. By integrating the spontaneous seepage and aspiration experiments in the laboratory and the post-pressure backflow data (including mineralization degree, liquid volume recovery rate, etc.), a multi-scale well shutdown time prediction model considering the characteristic length was established. The experimental results show that the spontaneous resorption characteristic times of Lu-A and Wei-B are 3 h and 22 h, respectively. Based on the inversion of crack monitoring data, the key parameters such as the weighted average crack width (1.73/1.30 mm) and crack spacing (0.20/0.32 m) of Lu-A and Wei-B were obtained. Through the scale upgrade calculation of the feature length (0.10/0.16 m), the system determined that the optimal well shutdown times for the two wells were 14.5 days and 16.7 days, respectively. The optimization method based on a multi-parameter analysis of backflow fluid proposed in this study not only solves the limitations of the traditional dimensionless time model in characterizing the feature length but also provides a theoretical basis for the formulation of the well shutdown system and nozzle control strategy of shale gas wells. Full article

Magnetic resonance imaging (MRI) currently serves as the primary diagnostic method for glioma detection and monitoring. The integration of neurosurgery, radiation therapy, pathology, and radiology in a multi-disciplinary approach has significantly advanced its diagnosis and treatment. However, the prognosis remains unfavorable due to treatment resistance, inconsistent response rates, and high recurrence rates after surgery. These factors are closely associated with the complex molecular characteristics of the tumors, the internal heterogeneity, and the relevant external microenvironment. The complete removal of gliomas presents challenges due to their infiltrative growth pattern along the white matter fibers and perivascular space. Therefore, it is crucial to comprehensively understand the molecular features of gliomas and analyze the internal tumor heterogeneity in order to accurately characterize and quantify the tumor invasion range. The multi-parameter quantitative MRI technique provides an opportunity to investigate the microenvironment and aggressiveness of glioma tumors at the cellular, blood perfusion, and cerebrovascular response levels. Therefore, this review examines the current applications of advanced multi-parameter quantitative MRI in glioma research and explores the prospects for future development. Full article

Aiming at the space target detection application of a space-based terahertz (THz) radar, according to the imaging mechanism of broadband THz radars, a THz radar imaging simulation method based on improved path tracing is proposed. Firstly, the characterization method of THz scattering characteristics based on Kirchhoff’s approximation method is introduced. The multi-parameter THz bidirectional reflectance distribution function (THz-BRDF) models of aluminum (Al), white-painted Al, and polyimide film at 0.215 THz are fitted according to the theoretical data, with fitting errors below 4%. Then, the THz radar imaging simulation method based on improved path tracing is presented in detail. The simulation method utilizes path tracing to simulate parallelized THz radar echo signal data, considering multi-path energy scattering based on the THz-BRDF model. Finally, we conducted THz radar imaging simulation experiments. The influences in the imaging process of different fly-around motions are analyzed, and a comparison experiment is conducted with the fast-physical optics (FPO) method. The comparative results indicate that the proposed method exhibits richer and more realistic features compared with the FPO method. The simulation experiments results demonstrate that the proposed method can provide a data source for ground algorithm testing of THz radars, particularly in evaluating the target detection and recognition algorithm based on deep learning, providing strong support for the application of space-based THz radars in the future. Full article

The purpose of this study was to investigate the physiological recovery effects of olfactory, visual and olfactory–visual stimuli associated with garden plants. In a randomized controlled study design, ninety-five Chinese university students were randomly selected to be exposed to stimulus materials, namely the odor of Osmanthus fragrans and a corresponding panoramic image of a landscape featuring the plant. Physiological indexes were measured by the VISHEEW multiparameter biofeedback instrument and a NeuroSky EEG tester in a virtual simulation laboratory. The results showed the following: (1) In the olfactory stimulation group, from before to during exposure to the stimuli, the subjects’ diastolic blood pressure (DBP) (ΔDBP = 4.37 ± 1.69 mmHg, p < 0.05) and pulse pressure (PP) values increased (ΔPP = −4.56 ± 1.24 mmHg, p < 0.05), while their pulse (p) values decreased (ΔP = −2.34 ± 1.16 bmp, p < 0.05) significantly. When compared to the control group, only the amplitudes of α and β brainwaves increased significantly (Δα = 0.37 ± 2.09 µV, Δβ = 0.34 ± 1.01 µV, p < 0.05). (2) In the visual stimulation group, the amplitudes of skin conductance (SC) (ΔSC = 0.19 ± 0.01 µΩ, p < 0.05), α brainwaves (Δα = 6.2 ± 2.26 µV, p < 0.05) and β brainwaves (Δβ = 5.51 ± 1.7 µV, p < 0.05) all increased significantly relative to the control group. (3) In the olfactory–visual stimulus group, DBP (ΔDBP = 3.26 ± 0.45 mmHg, p < 0.05) values increased, and PP values decreased (ΔPP = −3.48 ± 0.33 bmp, p < 0.05) significantly from before to during exposure to the stimuli. The amplitudes of SC (ΔSC = 0.45 ± 0.34 µΩ, p < 0.05), α brainwaves (Δα = 2.28 ± 1.74 µV, p < 0.05) and β brainwaves (Δβ = 1.4 ± 0.52 µV, p < 0.05) all increased significantly relative to the control group. The results of this study show that the interaction of olfactory and visual stimuli associated with a garden plant odor landscape was able to relax and refresh the body to a certain extent, and this physiological health effect was greater with regards to the integrated response of the autonomic nervous system and central nervous system than the effect of only smelling or viewing the stimuli. In the planning and designing of plant smellscapes in garden green space, it should be ensured that plant odors and corresponding landscapes are present at the same time in order to ensure the best health effect. Full article

This paper deals with guided wave-based structural health monitoring of composite overwrapped pressure vessels adopted for space application. Indeed, they are well suited for this scope thanks to their improved performance compared with metallic tanks. However, they are characterized by a complex damage mechanics and suffer from impact induced damage, e.g., due to space debris. After reviewing the limited progress in this specific application, the paper thoroughly covers all the steps needed to design and verify guided wave structural health monitoring system, including methodology, digital modelling, reliability, and noise estimation for a correct decision-making process in a virtual environment. In particular, propagation characteristics of the fundamental anti-symmetric mode are derived experimentally on a real specimen to validate a variety of finite element models useful to investigate wave interaction with damage. Different signal processing techniques are demonstrated sensitive to defect and linearly dependent upon damage severity, showing promising reliability. Those features can be implemented in a probability-based diagnostic imaging in order to detect and localized impact induce damage. A multi-parameter approach is achieved by metrics fusion demonstrating increased capability in damage detection with promising implication in enhancing probability of detection. Full article

The task to develop a mechanism for predicting the hemodynamic parameters values based on non-invasive hydrocuff technology of a pulse wave signal fixation is described in this study. The advantages and disadvantages of existing methods of recording the ripple curve are noted in the published materials. This study proposes a new hydrocuff method for hemodynamic parameters and blood pressure values measuring. A block diagram of the device being developed is presented. Algorithms for processing the pulse wave contour are presented. A neural network applying necessity for the multiparametric feature space formation is substantiated. The pulse wave contours obtained using hydrocuff technology of oscillation formation for various age groups are presented. According to preliminary estimates, by the moment of the dicrotic surge formation, it is possible to judge the ratio of the heart and blood vessels work, which makes it possible to form an expanded feature space of significant parameters based on neural network classifiers. This study presents the characteristics accounted for creating a database for training a neural network. Full article