Energy spectrum computed tomography multi-parameter imaging in preoperative assessment of vascular and neuroinvasive status in gastric cancer

BACKGROUND Vascular and nerve infiltration are important indicators for the progression and prognosis of gastric cancer(GC),but traditional imaging methods have some limitations in preoperative evaluation.In recent years,energy spectrum computed tomography(CT)multiparameter imaging technology has been gradually applied in clinical practice because of its advantages in tissue contrast and lesion detail display.AIM To explore and analyze the value of multiparameter energy spectrum CT imaging in the preoperative assessment of vascular invasion(LVI)and nerve invasion(PNI)in GC patients.METHODS Data from 62 patients with GC confirmed by pathology and accompanied by energy spectrum CT scanning at our hospital between September 2022 and September 2023,including 46 males and 16 females aged 36-71(57.5±9.1)years,were retrospectively collected.The patients were divided into a positive group(42 patients)and a negative group(20 patients)according to the presence of LVI/PNI.The CT values(CT40 keV,CT70 keV),iodine concentration(IC),and normalized IC(NIC)of lesions in the upper energy spectrum CT images of the arterial phase,venous phase,and delayed phase 40 and 70 keV were measured,and the slopes of the energy spectrum curves[K(40-70)]from 40 to 70 keV were calculated.Arterial Core Tip:To investigate the application value of multiparameter energy spectrum computed tomography(CT)imaging in the preoperative assessment of vascular and nerve infiltration in patients with gastric cancer(GC).The imaging data of GC patients were retrospectively analyzed to evaluate the accuracy and sensitivity of CT for identifying and quantifying vascular and nerve infiltration and for comparison with postoperative pathological results.The purpose of this study was to verify the clinical feasibility and potential advantages of multiparameter energy spectrum CT imaging in guiding preoperative diagnosis and treatment decision-making and to provide a new imaging basis for improving the diagnostic accuracy and prognosis of GC patients.

Optimal Spectrum Sensing in Energy Harvesting Cognitive Radio Systems

In this paper,we consider a cognitive radio system with energy harvesting,in which the secondary user operates in a saving-sensing-transmitting(SST) fashion.We investigate the tradeoff between energy harvesting,channel sensing and data transmission and focus on the optimal SST structure to maximize the SU's expected achievable throughput.We consider imperfect knowledge of energy harvesting rate,which cannot be exactly known and only its statistical information is available.By formulating the problem of expected achievable throughput optimization as a mixed-integer non-linear programming one,we derive the optimal saveratio and number of sensed channels with indepth analysis.Simulation results show that the optimal SST structure outperforms random one and performance gain can be enhanced by increasing the SU's energy harvesting rate.

A Study on Two-dimensional Spectrum Analysis System of Energy and Time

Proposed is a two-dimensional(2D)spectrum analysis system for acquiring the statistical information of radioactive particles on two dimensions,i.e.energy and time.Based on pulse width modulation readout circuit,such a system with 4-channels is designed,which converts the radiation signal into a rectangular pulse signal with pulse width modulated.The pulse width,occurrence time,and pulse count of the rectangular pulses are measured simultaneously with digital counters,so that the 2D spectra on energy and time of the radioactive particles can be obtained efficiently based on bi-parameter statistical analysis.A prototype of this 2D system is tested with gamma rays from 241Am isotopes,from which both the correlated 2D spectra and the independent spectra on energy and time are obtained.The energy spectra of four channels shows all characteristic peaks of 241Am gamma rays,among which the full-energy peak at 59.5keV exhibits energy resolution of about 5-6%,suggesting a good energy resolution and channel uniformity of the system.The regression of the time spectra of the characteristic peaks can give the time constants of each characteristic peak,revealing the time characteristics of the nuclear reactions in the radiative source.

Characteristics analysis of muzzle impulse noise based on wavelet energy spectrum

Because muzzle impulse noise could cause damage to or have an intluence on the operator, tiae ettecnve protecnve measures should be taken. Therefore, correct analysis of impulse noise characteristics is very significant. Considering the shortcomings of fast Fourier transform method （FFT） in analysis of muzzle impulse noise frequency characteristics, wavelet energy spectrum method is put forward. Based on specific experiment data, the frequency characteristics and spectral energy dis tribution can be obtained. The experiment results show that wavelet energy spectrum method is applicable in muzzle impulse noise characteristic analysis.

Freak wave simulation based on nonlinear model and the research on the time-frequency energy spectrum of simulation results

VOF （volume of fluid） method has been used to make the numerical simulation of freak wave come true. The comparisons between the numerical results and linear theoretical results corresponding to Eq.（5） have been carried out to show that the numerical results have a better exhibition of nonlinear characteristics. Wavelet analysis method has been adopted to investigate the time-frequency energy spectrum of simulation freak waves and the results reveal strong nonlinear interaction enables energy to be transferred to high harmonics during the progress of its formation. Varying water depth can enhance the nonlinear interaction, making much more energy be transferred to high harmonics and freak waves with higher asymmetry be generated.

An improved secondary electrons energy spectrum model and its application in multipactor discharge

Secondary electron emission(SEE)of metal and dielectric materials plays a key role in multipactor discharge,which is a bottle neck problem for high-power satelliate components.Measurements of both the secondary electron yield(SEY)and the secondary electron energy spectrum(SES)are performed on metal samples for an accurate description of the real SEE phenomenon.In order to simplify the fitting process and improve the simulation efficiency,an improved model is proposed for the description of secondary electrons(SE)emitted from the material surface,including true,elastic,and inelastic SE.Embedding the novel SES model into the electromagnetic particle-in-cell method,the electronic resonant multipactor in microwave components is simulated successfully and hence the discharge threshold is predicted.Simulation results of the SES variation in the improved model demonstrate that the multipactor threshold is strongly dependent on SES.In addition,the mutipactor simulation results agree quite well with the experiment for the practical microwave component,while the numerical model of SEY and SES fits well with the sample data taken from the microwave component.

Application of the wavelet packet and its energy spectrum to identify nugget splash during the aluminum alloys spot welding

Nugget splash during aluminum alloys spot welding has a detrimental effect on weld nugget integrity, strength and durability of the welded joints. This investigation is performed to identify nugget splash from voltage signals because these are easily accessible on-line. In the present work, we propose a novel method based on the wavelet packet transform and its energy spectrum for pattern recognition of splash signal. The result demonstrates that this novel method is more accuracy and a useful way of monitoring the spot welding quality.

The quantum Kirchhoff equation and quantum current and energy spectrum of a homogeneous mesoscopic dissipation transmission line

On the basis of quantization of charge, the loop equations of quantum circuits are investigated by using the Helsenberg motion equation for a mesoscopic dissipation transmission line. On the supposition that the system has a symmetry under translation in charge space, the quantum current and the quantum energy spectrum in the mesoscopic transmission llne are given by solving their eigenvalue equations. Results show that the quantum current and the quantum energy spectrum are not only related to the parameters of the transmission llne, but also dependent on the quantized character of the charge obviously.

Application of wavelet packet decomposition and its energy spectrum on the coal-rock interface identification

The theory and method of wavelet packet decomposition and its energy spectrum dealing with the coal rock Interface Identification are presented in the paper. The characteristic frequency band of the coal rock signal could be identified by wavelet packet decomposition and its energy spectrum conveniently, at the same time, quantification analysis were performed. The result demonstrates that this method is more advantageous and of practical value than traditional Fourier analysis method.

Experimental Study of Wave Energy Spectrum in Shallow Water

Wave energy spectrum in shallow water can be studied in wind wave channel in combination with irregular wave- maker. Fetch length is successfully extended and by 'Relay' method the corresponding spectrum pattern and the wind velocity scale are obtained.

A novel approach for feature extraction from a gamma‑ray energy spectrum based on image descriptor transferring for radionuclide identification

This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contained in the spectra,the vectors of the gamma-ray energy spectra from Euclidean space,which are fingerprints of the different types of radionuclides,were mapped to matrices in the Banach space.Subsequently,to make the spectra in matrix form easier to apply to image-based deep learning frameworks,the matrices of the gamma-ray energy spectra were mapped to images in the RGB color space.A deep convolutional neural network(DCNN)model was constructed and trained on the ImageNet dataset.The mapped gamma-ray energy spectrum images were applied as inputs to the DCNN model,and the corresponding outputs of the convolution layers and fully connected layers were transferred as descriptors of the images to construct a new classification model for radionuclide identification.The transferred image descriptors consist of global and local features,where the activation vectors of fully connected layers are global features,and activations from convolution layers are local features.A series of comparative experiments between the transferred image descriptors,peak information,features extracted by the histogram of the oriented gradients(HOG),and scale-invariant feature transform(SIFT)using both synthetic and measured data were applied to 11 classical classifiers.The results demonstrate that although the gamma-ray energy spectrum images are completely unfamiliar to the DCNN model and have not been used in the pre-training process,the transferred image descriptors achieved good classification results.The global features have strong semantic information,which achieves an average accuracy of 92.76%and 94.86%on the synthetic dataset and measured dataset,respectively.The results of the statistical comparison of features demonstrate that the proposed approach outperforms the peak-searching-based method,HOG,and SIFT on the synthetic and measured datasets.

Application of Wavelet Packet Energy Spectrum to Extract the Feature of the Pulse Signal

The wavelet packet is presented as a new kind of multiscale analysis technique followed by Wavelet analysis. The fundamental and realization arithmetic of the wavelet packet analysis method are described in this paper. A new application approach of the wavelet packed method to extract the feature of the pulse signal from energy distributing angle is expatiated. It is convenient for the microchip to process and judge by using the wavelet packet analysis method to make the pulse signals quantized and analyzed. Kinds of experiments are simulated in the lab, and the experiments prove that it is a convenient and accurate method to extract the feature of the pulse signal based on wavelet packed-energy spectrumanalysis.

Energy Spectrum of Two-Component Bose-Einstein Condensates in Optical Lattices

With the method of Green's function, we investigate the energy spectra of two-component ultracold bosonic atoms in optical lattices. We End that there are two energy bands for each component. The critical condition of the superfluid-Mott insulator phase transition is determined by the energy band structure. We also find that the nearest neighboring and on-site interactions fail to change the structure of energy bands, but shift the energy bands only. According to the conditions of the phase transitions, three stable superfluid and Mott insulating phases can be found by adjusting the experiment parameters. We also discuss the possibility of observing these new phases and their transitions in further experiments.

Transformation of Wave Energy Spectrum in Shallow Water

Combined with irregular wave-maker, the growing process of Wave Energy Spectrum in shallow water can be studied in wind wave channel on different water depth conditions, and its transformation characteristics and rules can be obtained.

A Cell Condition-Sensitive Frequency Segmentation Method Based on the Sub-Band Instantaneous Energy Spectrum of Aluminum Electrolysis Cell Voltage

Cell voltage is a widely used signal that can be measured online from an industrial aluminum electrolysis cell.A variety of parameters for the analysis and control of industrial cells are calculated using the cell voltage.In this paper,the frequency segmentation of cell voltage is used as the basis for designing filters to obtain these parameters.Based on the qualitative analysis of the cell voltage,the sub-band instantaneous energy spectrum(SIEP)is first proposed,which is then used to quantitatively represent the characteristics of the designated frequency bands of the cell voltage under various cell conditions.Ultimately,a cell condition-sensitive frequency segmentation method is given.The proposed frequency segmentation method divides the effective frequency band into the[0,0.001]Hz band of lowfrequency signals and the[0.001,0.050]Hz band of low-frequency noise,and subdivides the lowfrequency noise into the[0.001,0.010]Hz band of metal pad abnormal rolling and the[0.01,0.05]Hz band of sub-low-frequency noise.Compared with the instantaneous energy spectrum based on empirical mode decomposition,the SIEP more finely represents the law of energy change with time in any designated frequency band within the effective frequency band of the cell voltage.The proposed frequency segmentation method is more sensitive to cell condition changes and can obtain more elaborate details of online cell condition information,thus providing a more reliable and accurate online basis for cell condition monitoring and control decisions.

Effects of Spatial Noncommutativity on Energy Spectrum of a Trapped Bose-Einstein Condensate

In noncommutative space, we examine the problem of a noninteracting and harmonically trapped Bose- Einstein condensate, and derive a simple analytic expression for the effect of spatial noncommutatlvity on energy spectrum of the condensate, it indicates that the ground-state energy incorporating the spatial noncommutativity is reduced to a lower level, which depends upon the noncommutativity parameter 8. The gap between the noncommutative space and commutative one for the ground-state level of the condensate should be a signal of spatial noncommutativity.

Measurement of the Energy Spectrum of a 6 MV Linear Accelerator Using Compton Scattering Spectroscopy and Monte Carlo-Generated Corrections

Purpose: The energy spectrum of a linear accelerator used for dose calculations is determined during beam commissioning by iteratively adjusting the spectrum and comparing calculated and measured percent depth-dose curves. Direct measurement of the energy spectrum using pulse mode detectors is particularly challenging because of the high-energy, high fluence nature of these beams and limitations of the detector systems. This work implements a Compton scattering (CS) spectroscopy setup and presents detector corrections and spectral unfolding techniques to measure the spectrum of a 6 MV linear accelerator using a pulse mode detector. Methods: Spectral measurements were performed using a Varian Clinac 21EX linear accelerator and a high-purity germanium (HPGe) detector. To reduce fluence to the detector, a custom-built lead shield and a CS spectrometry setup were used. The detector was placed at CS angles of 46°, 89°, and 125°. At each of these locations, a detector response function was generated to account for photon interactions within the experimental geometry. Gold’s deconvolution algorithm was used to unfold the energy spectrum. The measured spectra were compared to simulated spectra, which were obtained using an experimentally benchmarked model of the Clinac 21EX in MCNP6. Results: Measurements were acquired and detector response corrections were calculated for all three CS angles. A comparison of spectra for all CS angles showed good agreement with one another. The spectra for all three angles were averaged and showed good agreement with the MCNP6 simulated spectrum, with all points above 400 keV falling within 4%, which was within the uncertainty of the measurement and statistical uncertainty. Conclusions: The measurement of the energy spectrum of a 6 MV linear accelerator using a pulse-mode detector is presented in this work. For accurate spectrum determination, great care must be taken to optimize the detector setup, determine proper corrections, and to unfold the spectrum.

Energy Spectrum, g Factors, Strain-Induced Level-Splittings and R-Line Thermal Shift of MgO:V^(2+)

Traditional ligand-field theory has to be improved by taking into account both pure electronic contribution and electron-phonon interaction one （including lattice-vibrational relaxation energy）. By means of improved ligand-field theory, the R line, t^322T1 and t^322T2 lines, t^22（^3T1）e^4T2, t^22（^3T1）e^4T1 and t2e^2（^4A2）4T1 bands, g factors of t^32 ^4A2 and t32E, four strain-induced level-splittings and R-line thermal shift of MgO：V^2＋ have been calculated. The results are in very good agreement with the experimental data. It is found that for MgO：V^2＋, the contributions due to electronphonon interaction （EPI） come from the first-order term; the contributions from the second-order and higher terms are insignificant. In thermal shift of R line of MgO：V^2＋, the temperature-dependent contribution due to EPI is dominant. The results obtained in this work may be used in theoretical calculations of other effects of EPI.

Improved Ligand-Field Calculation of Energy Spectrum and R-Line Thermal Shift of MgO：Cr^3＋

Traditional ligand-field theory has to be improved by taking into account both pure electronic contribution and electron-phonon interaction one （including lattice-vibrational relaxation energy）. By means of improved ligand-field theory, the R-line, t^3 2^2 T1 lines, t^2 2（^3 T1）e^4 T2, and t^2 2（^3T1）e^4T1 bands, ground-state g factor, four strain-induced level- splittings, and R-line thermal shift of MgO：Cr^3＋ have been calculated. The results are in very good agreement with the experimental data. It is found that for MgO：Cr^3＋, the contributions due to electron-phonon interaction （EPI） come from the first-order term. In thermal shift of R-line of MgO：Cr^3＋, the temperature-dependent contribution due to EPI is dominant.

Growth of deuterium clusters in a gas jet and ion energy spectrum of clusters in ultra-short laser field

Large deuterium clusters are generated using a cryogenic pulse valve with a cone nozzle （21 mm long, 4° open angle）. Rayleigh scattering experiment is carried out to obtain the scaling relation between scattering signal SR and backing pressure P0. A method using the Coulomb explosion model is proposed to verify that the clusters continue to grow after their leaving the nozzle. Our experiments suggest a tentatively optimized position for laser cluster interaction.