Notes

Fragmentation behavior of EDTA things under different initial situations.
Currently, blindness cannot be cured and patients' living quality can be compromised severely. Ultrasonic (US) neuromodulation is a promising technology for the development of noninvasive cortical visual prosthesis. We investigated the feasibility of transcranial focused ultrasound (tFUS) for noninvasive stimulation of the visual cortex (VC) to develop improved visual prosthesis. tFUS was used to successfully evoke neural activities in the VC of both normal and retinal degenerate (RD) blind rats. Our results showed that blind rats showed more robust responses to ultrasound stimulation when compared with normal rats. ( , two-sample t-test). Three different types of ultrasound waveforms were used in the three experimental groups. Different types of cortical activities were observed when different US waveforms were used. In all rats, when stimulated with continuous ultrasound waves, only short-duration responses were observed at "US on and off" time points. In comparison, pulsed waves (PWs) evoked longer low-frequency responses. Testing different parameters of PWs showed that a pulse repetition frequency higher than 100 Hz is required to obtain the low-frequency responses. Based on the observed cortical activities, we inferred that acoustic radiation force (ARF) is the predominant physical mechanism of ultrasound neuromodulation.Recent works highlighted the significant potential of lung ultrasound (LUS) imaging in the management of subjects affected by COVID-19. In general, the development of objective, fast, and accurate automatic methods for LUS data evaluation is still at an early stage. This is particularly true for COVID-19 diagnostic. In this article, we propose an automatic and unsupervised method for the detection and localization of the pleural line in LUS data based on the hidden Markov model and Viterbi Algorithm. The pleural line localization step is followed by a supervised classification procedure based on the support vector machine (SVM). The classifier evaluates the healthiness level of a patient and, if present, the severity of the pathology, i.e., the score value for each image of a given LUS acquisition. The experiments performed on a variety of LUS data acquired in Italian hospitals with both linear and convex probes highlight the effectiveness of the proposed method. The average overall accuracy in detecting the pleura is 84% and 94% for convex and linear probes, respectively. The accuracy of the SVM classification in correctly evaluating the severity of COVID-19 related pleural line alterations is about 88% and 94% for convex and linear probes, respectively. The results as well as the visualization of the detected pleural line and the predicted score chart, provide a significant support to medical staff for further evaluating the patient condition.The mechanical properties of soft tissues can be quantitatively characterized through the estimation of shear wave velocity (SWV) using various motion estimation methods, such as the commonly used block matching (BM) methods. However, such methods suffer from slow computational speed and many tunable parameters. In order to solve these problems, Butterworth filter-based clutter filter wave imaging (BW-CFWI) is recently proposed to detect the mechanical wave propagation by highlighting the tissue velocity induced by mechanical wave, without using any motion estimation methods. In this study, in order to improve the SWV estimation performance of the clutter filter wave imaging (CFWI) method, we propose singular value decomposition (SVD)-based clutter filter for CFWI (SVD-CFWI) and further accelerate it using a randomized SVD (rSVD)-based clutter filter (rSVD-CFWI). Homogeneous phantoms with different Young's moduli are used to investigate the influences of the cutoff order of singular value and iteration time oFWI than with BW-CFWI and NCC-BM. Besides, RSVD-CFWI has lower computational complexity than SVD-CFWI and NCC-BM and has lower memory space requirement than SVD-CFWI. The computational speed of rSVD-CFWI is comparable to that of BW-CFWI and over 10 times higher than that of SVD-CFWI. Therefore, RSVD-CFWI is demonstrated to be a competitive tool for fast shear wave imaging.We present an air-coupled ultrasonic imaging system based on a 40-kHz 8×8 phased-array for 3-D real-time localization of multiple objects in the far-field. By attaching a waveguide to the array, the effective interelement spacing is reduced to half wavelength. This enables grating lobe-free transmit and receive beamforming with a uniform rectangular array of efficient low-cost transducers. The system further includes custom transceiver electronics, an field programmable gate array (FPGA) system-on-chip and a PC for GPU accelerated frequency domain signal processing, consisting of matched filtering, conventional beamforming, and envelope extraction using Nvidia Compute Unified Device Architecture (CUDA) and OpenGL for visualization. The uniform rectangular layout allows utilizing multiple transmit and receive methods, known from medical imaging applications. selleck compound Thus, the system is dynamically adaptable to maximize the frame rate or detection range. One implemented method demonstrates the real-time capability by transmitting a hemispherical pulse (HP) with a single transducer to irradiate the surroundings simultaneously, whereas all transducers are used for echo reception. The imaging properties, such as axial and lateral resolution, field of view and range of view, are characterized in an anechoic chamber. The object localization is validated for a horizontal and vertical field of view of ±80° and a range of view of 0.5-3 m with 29 frames/s. Using the same system, a comparison between the HP method and the dynamic transmit beamforming method, which transmits multiple sequential beamformed pulses for long-range localization, is provided.Most reconstruction algorithms for photoacoustic imaging assume that the pressure field is measured by the ultrasound sensors placed on a detection surface. However, such sensors do not measure pressure exactly due to their nonuniform directional and frequency responses, and resolution limitations. This is the case for piezoelectric sensors that are commonly employed for photoacoustic imaging. In this article, using the method of matched asymptotic expansions and the basic constitutive relations for piezoelectricity, we propose a simple mathematical model for piezoelectric transducers. The approach simultaneously models how the pressure waves induce the piezoelectric measurements and how the presence of the sensors affects the pressure waves. Using this model, we analyze whether the data gathered by the piezoelectric sensors lead to the mathematical solvability of the photoacoustic imaging problem. We conclude that this imaging problem is well posed in certain normed spaces and under a geometric assumption. We also propose an iterative reconstruction algorithm that incorporates the model for piezoelectric measurements. A numerical implementation of the reconstruction algorithm is presented.Endoscopic ultrasound (EUS), an interventional imaging technology, utilizes a circular array to delineate the cross-sectional morphology of internal organs through the gastrointestinal (GI) track. However, the performance of conventional EUS transducers has scope for improvement because of the ordinary piezoelectric parameters of Pb(Zr, Ti) [Formula see text] (PZT) bulk ceramic as well as its inferior mechanical flexibility which can cause material cracks during the circular shaping process. To achieve both prominent imaging capabilities and high device reliability, a 128-element 6.8-MHz circular array transducer is developed using a Pb(Mg [Formula see text]Nb [Formula see text]) [Formula see text]-PbTiO3 (PMN-PT) 1-3 composite with a coefficient of high electromechanical coupling ( [Formula see text]) and good mechanical flexibility. The characterization results exhibit a large average bandwidth of 58%, a high average sensitivity of 100 mVpp, and a crosstalk of less than -37 dB near the center frequency. Imaging performance of the PMN-PT composite-based array transducer is evaluated by a wire phantom, an anechoic cyst phantom, and an ex-vivo swine intestine. This work demonstrates the superior performance of the crucial ultrasonic device based on an advanced PMN-PT composite material and may lead to the development of next-generation biomedical ultrasonic devices for clinical diagnosis and treatment.The multiview total focusing method (TFM) enables a region of interest within a specimen to be imaged using different ray paths and wave-mode combinations. For defects larger than the ultrasonic wavelength, different portions of the same defect may manifest in a number of views. For a crack, the tip diffraction response may be evident in certain views and the specular reflection in others. Accurate characterization of large defects requires the information in multiple views to be combined. In this work, three data fusion methodologies are presented a simple sum over all views, a sum weighted according to the inverse of the noise in each view, and a matched filter approach. Four large defects are examined; one stress corrosion crack (SCC), two weld cracks, and a pair of slagline defects in a weld. The matched filter (matched to a small circular void) provided significant improvement over the best individual view. The data fusion process incorporates artifact removal, where nondefect artifact signals within each image view are identified and masked, using a single defect-free data set for training. The matched filter was able to accurately visualize the full 3-D extent of the four defects, allowing characterization via the decibel drop method. When compared to X-ray computed tomography and micrograph data in the case of the SCC, the matched filter fusion provided excellent agreement. Its performance was also superior to any individual view while providing a single fused image that is easier for an operator to interpret than a set of multiview images.We consider a model of a nanocomposite based on noninteracting spherical single-domain ferroelectric nanoparticles (NPs) of various sizes embedded in a dielectric matrix. The size distribution function of these NPs is selected as a part of the truncated Gaussian distribution from minimum to maximum radius. For such nanocomposites, we calculate the dependences of the reversible part of the electric polarization, the electrocaloric (EC) temperature change, and the dielectric permittivity on the external electric field, which have the characteristic form of hysteresis loops. We then analyze the change in the shape of the hysteresis loops relative to the particle size distribution parameters. We demonstrate that the remanent polarization, coercive field, dielectric permittivity maximums, and maximums and minimums of the EC temperature change depend most strongly on the most probable radius, moderately on the dispersion, and have the weakest dependence on the maximum radius of the NP. We calculate and analyze the dependences of pyroelectric figures of merit on the average radius of the NPs in the composite. The dependences confirm the presence of a phase transition induced by the size of the NPs, which is characterized by the presence of a maxima near the critical average radius of the particles, the value of which increases with an increasing dispersion of the distribution function.
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