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Image reconstruction for positron emission tomography (PET) is challenging because of the ill-conditioned tomographic problem and low counting statistics. Kernel methods address this challenge by using kernel representation to incorporate image prior information in the forward model of iterative PET image reconstruction. Existing kernel methods construct the kernels commonly using an empirical process, which may lead to unsatisfactory performance. In this paper, we describe the equivalence between the kernel representation and a trainable neural network model. A deep kernel method is then proposed by exploiting a deep neural network to enable automated learning of an improved kernel model and is directly applicable to single subjects in dynamic PET. The training process utilizes available image prior data to form a set of robust kernels in an optimized way rather than empirically. The results from computer simulations and a real patient dataset demonstrate that the proposed deep kernel method can outperform the existing kernel method and neural network method for dynamic PET image reconstruction.

In this paper, we study a tumor growth model with nutrients. The model presents dynamic patch solutions due to the incompressibility of the tumor cells. We show that when the nutrients do not diffuse and the cells do not die, the tumor density exhibits regularizing dynamics thanks to an unexpected comparison principle. Using the comparison principle, we provide quantitative L 1 L^1 -contraction estimates and establish the C 1 , α C^{1,\alpha } -boundary regularity of the tumor patch. Furthermore, whenever the initial nutrient n 0 n_0 either lies entirely above or entirely below the critical value n 0 = 1 n_0=1 , we are able to give a complete characterization of the long-time behavior of the system. When n 0 n_0 is constant, we can even describe the dynamics of the full system in terms of some simpler nutrient-free and parameter-free model problems. These results are in sharp contrast to the observed behavior of the models either with nutrient diffusion or with death rate in tumor cells.

We consider an inverse problem arising in nonlinear ultrasound imaging. The propagation of ultrasound waves is modeled by a quasilinear wave equation. We make measurements at the boundary of the medium encoded in the Dirichlet-to-Neumann map, and we show that these measurements determine the nonlinearity., 36 pages. arXiv admin note: substantial text overlap with arXiv:2104.08386

In density functional theory (DFT) based total energy studies, the van der Waals (vdW) and zero-point vibrational energy (ZPVE) correction terms are included to obtain energy differences between polymorphs. We propose and compute a new correction term to the total energy, due to electron-phonon interactions (EPI). We rely on Allen's general formalism, which goes beyond the Quasi-Harmonic Approximation (QHA), to include the free energy contributions due to quasiparticle interactions. We show that, for semiconductors and insulators, the EPI contributions to the free energies of electrons and phonons are the corresponding zero-point energy contributions. Using an approximate version of Allen's formalism in combination with the Allen-Heine theory for EPI corrections, we calculate the zero-point EPI corrections to the total energy for cubic and hexagonal polytypes of Carbon, Silicon and Silicon Carbide. The EPI corrections alter the energy differences between polytypes. In SiC polytypes, the EPI correction term is more sensitive to crystal structure than the vdW and ZPVE terms and is thus essential in determining their energy differences. It clearly establishes that the cubic SiC-3C is metastable and hexagonal SiC-4H is the stable polytype. Our results are consistent with the experimental results of Kleykamp. Our study enables the inclusion of EPI corrections as a separate term in the free energy expression. This opens the way to go beyond the QHA by including the contribution of EPI on all thermodynamic properties., Comment: 30 pages and 2 figures

Answering a question due to Min, we prove that a finite graph of roses admits a regluing such that the resulting graph of roses has hyperbolic fundamental group., 25pgs, no figs

As a magnet utilized for a rotating gantry in heavy particle radiotherapy, a superconducting magnet with active shielding has been proposed to reduce the magnet weight. The magnet is composed of a dipole coil and an active shielding coil wound with NbTi wires. In this study, an electromagnetic-structural analysis of the magnet with active shielding was conducted using an FEM model. The results of the analysis indicate that the coil deformation, due to an electromagnetic force, slightly affects the field quality but negligible for the operation. The design concept of superconducting magnets with active shielding is valid in terms of magnetic field and the support structure for a rotating gantry. In addition, based on the previous study, the weight of the superconducting magnet with active shielding was revaluated. As a result, the superconducting magnet with active shielding can be one-third lighter than a superconducting magnet surrounded with an iron yoke, in terms of the magnet weight per unit length.

The use of carbon ions in particle therapy can enhance the treatment quality, introducing higher biological effectiveness compared to photons and protons. Rotating gantries are nowadays used to deliver particle beams from different directions to obtain precise conformal dose mapping at the tumor location. The mechanical stability requirements during the rotation usually require heavy structures. Superconducting magnets can be used to reduce the size and weight of the machine, but complex cryogenics systems are needed to maintain superconductivity during the gantry rotation. The seek for novel gantry configurations for carbon ions is one of the greatest challenges that need to be tackled to widen the accessibility of hadron therapy to a larger number of patients. The concept of GaToroid, a steady-state toroidal gantry implemented with superconducting magnets, can be used to deliver the beam from different directions without the rotation of neither the structure nor the patient. In this work, we present the magnetic design of two GaToroid solutions for Carbon ions, conceived to operate with Nb-Ti cables in the range of 6-7 Tesla. The first solution was designed with 20 pairs of coils, to maximize the flexibility of the treatment, and with an internal diameter of 3.5 meters, to allow a complete couch rotation on the plane. The second option, based on a more conservative design with an internal diameter of 2.3 meters and eight couples of coils, aims to be a compromise between the complexity and cost of the machine, and the flexibility of the treatments. For both configurations, the coil geometry and current distribution were optimized to maximize the carbon ion momentum acceptance for complete coverage of the treatment range without variation of the toroidal magnetic field. The studies here presented can be considered as the first milestone toward the design of toroidal gantries for heavy ions.

The optoelectronic application of gold nanoparticles is majorly influenced by certain unique features they exhibit, like surface plasmon resonance, ready functionalization and ease of conjugation with bio-analytes etc. Production of gold nanoparticles through laser ablation is the simplest method with the advantage of obtaining high purity particles. In this work, the saturation and reverse saturation behaviour during ultrafast absorption in laser ablated gold nanoparticles is studied using the Z-scan technique. The Z-scan experiment is conducted using 800 nm, 84 MHz and 120 fs intense laser pulses at different excitation intensities from 6.23 GW/cm2 to 23.37 GW/cm2. The open aperture Z-scan measurements show distinct positive region till an excitation of 17 GW/cm2 after which there is a clear cross-over into negative trend. The strength of this negative wing increases with the excitation intensity, which is featured by the nonlinear absorption due to the two-photon and three-photon absorption contributions with their respective coefficients in the range of 10-3. The optical limiting nature of these gold nanoparticles is demonstrated. An understanding of these nonlinear optical properties provides better insight in their application towards biomedical diagnostics and optical switching and limiting.

Quantum process tomography is a critical capability for building quantum computers, enabling quantum networks, and understanding quantum sensors. Like quantum state tomography, the process tomography of an arbitrary quantum channel requires a number of measurements that scale exponentially in the number of quantum bits affected. However, the recent field of shadow tomography, applied to quantum states, has demonstrated the ability to extract key information about a state with only polynomially many measurements. In this work, we apply the concepts of shadow state tomography to the challenge of characterizing quantum processes. We make use of the Choi isomorphism to directly apply rigorous bounds from shadow state tomography to shadow process tomography, and we find additional bounds on the number of measurements that are unique to process tomography. Our results, which include algorithms for implementing shadow process tomography enable new techniques including evaluation of channel concatenation and the application of channels to shadows of quantum states. This provides a dramatic improvement for understanding large-scale quantum systems., Comment: 12 pages, 5 figures; Added citation to similar work; Errors corrected. Previous statements of main result first missed and then miscalculated an exponential cost in system size; Version accepted for publication

Magnetic resonance imaging (MRI) is increasingly used by the orbital surgeon to aid in the diagnosis, surgical planning, and monitoring of orbital disease. MRI provides superior soft tissue detail compared with computed tomography or ultrasound, and advancing techniques enhance its ability to highlight abnormal orbital pathology. Diffusion-weighted imaging is a specialized technique that uses water molecule diffusion patterns in tissue to generate contrast signals and can help distinguish malignant from benign lesions. Steady-state free precession sequences such as Constructive Interference in Steady-State (CISS) and Fast Imaging Employing Steady-state Acquisition (FIESTA) generate highly detailed, 3-dimensional reconstructed images and are particularly useful in distinguishing structures adjacent to cerebral spinal fluid. Magnetic resonance angiography can be used to characterize vascular lesions within the orbit. New developments in magnetic field strength as well as the use of orbital surface coils achieve increasingly improved imaging resolution.

Accurate electroencephalogram (EEG) pattern decoding for specific mental tasks is one of the key steps for the development of brain-computer interface (BCI), which is quite challenging due to the considerably low signal-to-noise ratio of EEG collected at the brain scalp. Machine learning provides a promising technique to optimize EEG patterns toward better decoding accuracy. However, existing algorithms do not effectively explore the underlying data structure capturing the true EEG sample distribution and, hence, can only yield a suboptimal decoding accuracy. To uncover the intrinsic distribution structure of EEG data, we propose a clustering-based multitask feature learning algorithm for improved EEG pattern decoding. Specifically, we perform affinity propagation-based clustering to explore the subclasses (i.e., clusters) in each of the original classes and then assign each subclass a unique label based on a one-versus-all encoding strategy. With the encoded label matrix, we devise a novel multitask learning algorithm by exploiting the subclass relationship to jointly optimize the EEG pattern features from the uncovered subclasses. We then train a linear support vector machine with the optimized features for EEG pattern decoding. Extensive experimental studies are conducted on three EEG data sets to validate the effectiveness of our algorithm in comparison with other state-of-the-art approaches. The improved experimental results demonstrate the outstanding superiority of our algorithm, suggesting its prominent performance for EEG pattern decoding in BCI applications.

To ensure the effectiveness of the inductive power transfer (IPT) systems for high power applications, the multiple coils are being used. But the cross-couplings among the same side coils reduce the efficiency of the system. Thus, the decoupling coils are commonly used to mitigate the same side couplings in multiple transmitters and receivers system. The decoupling coils are either used outside of the main coils or concentric with the main coils. In both cases, these decoupling coils do not take part in the power transmission and have some adverse effects on the system performance. In this paper, a new IPT system with dual transmitters and dual receivers with integrated decoupling coils is introduced. Besides mitigating the mutual inductances of the same side coils, the proposed decoupling coils are also taking part in power transmission. In addition, the proposed coils also have good misalignment performance. A three-dimensional finite element analysis (FEA) tool ANSYS MAXWELL is used to investigate the proposed magnetic coupler. A scaled-down experimental setup is used to verify the feasibility of the proposed structure. The maximum dc-dc efficiency of this system is 93.14 % while delivering 700 W to the load with a 200 mm air gap.

The effect of electrode orientation in an electrohydrodynamic (EHD) gas pump inside a square channel is experimentally examined for its effective use in thermal management. The two-stage gas pump w...

Context Prostate-specific membrane antigen (PSMA) positron emission tomography/magnetic resonance imaging (PET/MRI) is a novel imaging technique with several potential applications in the prostate cancer (PCa) setting. Objective To perform a systematic review of the current evidence regarding the diagnostic performance of PSMA PET/MRI in patients with primary and recurrent PCa. Evidence acquisition A comprehensive bibliographic search on the MEDLINE and Cochrane Library databases was performed in October 2020. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Studies were deemed eligible if they assessed patients with primary or recurrent PCa (P) undergoing PSMA PET/MRI (I) with or without comparison with other imaging techniques (C) in order to evaluate its diagnostic performance (O). Retrospective and prospective primary clinical studies were included. Results of previous meta-analyses were reported. Evidence synthesis A total of 23 original articles and three meta-analyses were included. Limited evidence on PSMA PET/MRI is available, especially in the setting of partial gland ablation. PET/MRI can be an effective imaging modality for detecting primary PCa, showing higher accuracy than multiparametric MRI alone. It provides accurate local staging of primary PCa; however, there are contradictory results in this context when its performance is compared with other imaging techniques. PET/MRI also shows high performance for restaging and detecting tumor recurrence, even at low prostate-specific antigen levels. Conclusions PSMA PET/MRI could represent a valuable tool in the management of patients with primary and recurrent PCa. No specific recommendations can be provided. Patient summary Encouraging data regarding the benefits of prostate-specific membrane antigen positron emission tomography/magnetic resonance imaging in patients with prostate cancer are emerging from the literature.

An electrohydrodynamic (EHD) gas pump inside a square channel is experimentally evaluated for its effectiveness in flow delivery. The gas pump with three sets of electrode assemblies (separately wi...

Accuracy of stopping power ratio calculation and experimental validation of proton range with dual-layer computed tomography

Respiratory motion is one of the main sources of motion artifacts in positron emission tomography (PET) imaging. The emission image and patient motion can be estimated simultaneously from respiratory gated data through a joint estimation framework. However, conventional motion estimation methods based on registration of a pair of images are sensitive to noise. The goal of this study is to develop a robust joint estimation method that incorporates a deep learning (DL)-based image registration approach for motion estimation. We propose a joint estimation framework by incorporating a learned image registration network into a regularized PET image reconstruction. The joint estimation was formulated as a constrained optimization problem with moving gated images related to a fixed image via the deep neural network. The constrained optimization problem is solved by the alternating direction method of multipliers (ADMM) algorithm. The effectiveness of the algorithm was demonstrated using simulated and real data. We compared the proposed DL-ADMM joint estimation algorithm with a monotonic iterative joint estimation. Motion compensated reconstructions using pre-calculated deformation fields by DL-based (DL-MC recon) and iterative (iterative-MC recon) image registration were also included for comparison. Our simulation study shows that the proposed DL-ADMM joint estimation method reduces bias compared to the ungated image without increasing noise and outperforms the competing methods. In the real data study, our proposed method also generated higher lesion contrast and sharper liver boundaries compared to the ungated image and had lower noise than the reference gated image.

Positron emission tomography (PET) imaging is used to track biochemical processes in the human body. PET image quality is limited by noise and several methods have been implemented to improve the quality. Kernel-based image reconstruction is among the methods implemented to increase PET image quality and commonly uses a Gaussian kernel to include spatial correlations from image priors into the forward projection model of PET. Unfortunately, the Gaussian kernel tends to smooth details in the reconstructed image. To reduce noise without losing contrast details, a different kernel is needed. Wavelet kernels can be more efficient than the Gaussian kernel in reducing noise while keeping contrast details 1 by better separating signal from noise and thus it does not over smooth peak values in the final reconstructed images. In this work, we evaluate a wavelet kernel for kernel-based PET image reconstruction. For this goal, a wavelet kernel approach has been tested using simulated brain data, physical phantom data and patient data. Reconstruction results are presented and discussed in detail comparing the wavelet kernel method with the Gaussian kernel method. Our results suggest that a wavelet kernel performs better in contrast recovery for phantoms and also results in higher signal-to-noise ratio (SNR) for real patient data.

The effect of contact pressure on the performance of electrolyte supported planar solid oxide fuel cells (SOFCs) are experimentally investigated in this study by varying the pressure applied on the push rod. For this purpose, cells with 1 cm2, 9 cm2, 16 cm2, 81 cm2 and 150 cm2 active areas are manufactured and tested under different external compression pressures. Maximum power densities of 0.486 W/cm2, 0.308 W/cm2 and 0.231 W/cm2 are obtained from the cells with an active area of 1 cm2, 9 cm2 and 16 cm2, respectively, under the same contact pressure. When the impedance results are considered, it is seen that under the same compression pressure, the cell resistance increases nonlinearly with the cell size. However, when the pressure is adjusted according to the active area, a similar power density of approximately 0.4 W/cm2 is obtained from these three cells. Moreover, very similar performances are measured from all cells when a portion of cells with 1 cm2 active is cut and tested under the same contact pressure of 0.2 MPa. The overall results indicate that the external load should be adjusted according to the cell size, but there is no linear relationship between the active area and the applied external pressure.

Mathematical modeling of a cancer treatment and drug delivery at the macroscale requires evaluating the leakage of solute flux into the targeted tumor or healthy tissue. This study provides a 2D model for the blood and nanoparticle transport in a single vessel surrounded by a tumor. In the vessel, the blood flow is described by Navier-Stokes equations which are coupled to advection–diffusion equation and energy equation for the fluid and nanoparticle transport. Impacts of the Brownian motion and thermophores parameters together with a thermal radiation are examined. Constant vascular fluid velocity across the vessel walls are assumed, and two phase nanofluid model is considered to represent the nanoparticle concentration. The solution methodology is depending on the finite volume method and features of the blood velocity, temperature and nanoparticle concentration are presented graphically. The major outcomes reveal that the blood temperature within the vessel is enhanced as the nanoparticle extravasation coefficient is increasing, while the concentration of the nanoparticles around the tumor is reduced.

The clinical use of microwave tomography (MT) requires addressing the significant mismatch between simulated environment, which is used in the forward solver, and real-life system. To alleviate this mismatch, a calibrated tomography, which uses two homogeneous calibration phantoms and a modified distorted Born iterative method (DBIM), is presented. The two phantoms are used to derive a linear model that matches the forward solver to real-life measurements. Moreover, experimental observations indicate that signal quality at different frequencies varies between different antennas due to inevitably inconsistent manufacturing tolerance and variances in radio-frequency chains. An optimum frequency, at which the simulated and measured signals of the antenna present maximum similarity when irradiating the calibrated phantoms, is thus calculated for each antenna. A frequency-division DBIM (FD-DBIM), in which different antennas in the array transmit their corresponding optimum frequencies, is subsequently developed. A clinical brain scanner is then used to assess performance of the algorithm in lab and healthy volunteers' tests. The linear calibration model is first used to calibrate the measured data. After that FD-DBIM is used to solve the problem and map the dielectric properties of the imaged domain. The simulated and experimental results confirm validity of the presented approach and its superiority to other tomographic method.

A new method of dose calculation algorithm, called GPU-accelerated Monte Carlo and collapsed cone Convolution (GMCC) was developed to improve the calculation speed of BNCT treatment planning system. The GPU-accelerated Monte Carlo routine in GMCC is used to simulate the neutron transport over whole energy range and the Collapsed Cone Convolution method is to calculate the gamma dose. Other dose components due to alpha particles and protons, are calculated using the calculated neutron flux and reaction data. The mathematical principle and the algorithm architecture are introduced. The accuracy and performance of the GMCC were verified by comparing with the FLUKA results. A water phantom and a head CT voxel model were simulated. The neutron flux and the absorbed dose obtained by the GMCC were consistent well with the FLUKA results. In the case of head CT voxel model, the mean absolute percentage error for the neutron flux and the absorbed dose were 3.98% and 3.91%, respectively. The calculation speed of the absorbed dose by the GMCC was 56 times faster than the FLUKA code. It was verified that the GMCC could be a good candidate tool instead of the Monte Carlo method in the BNCT dose calculations.

Aiming at the problem that the Ultra-Wide-Band (UWB) positioning accuracy is reduced in the Non-Line-of-Sight (NLOS) environment, a UWB positioning accuracy evaluation mechanism is introduced. This paper analyzes the geometric distribution of UWB equipment theoretically to evaluate the positioning accuracy of the UWB system. Furthermore, it optimizes the geometric distribution of UWB and optimizes the UWB positioning algorithm model to improve the positioning accuracy. A set of UWB positioning accuracy estimation process is proposed. Through theoretical analysis and simulation, a model of the influence of the geometric distribution of base stations on the UWB positioning precision is established. The obtained model provides a reference for setting and adjusting the measurement noise in the Kalman filter for UWB/Inertial Navigation System (INS) integration positioning, which improves the combined positioning accuracy.

The present study addresses the fluid transport behaviour of the flow of gold (Au)-copper (Cu)/biomagnetic blood hybrid nanofluid in an inclined irregular stenosis artery as a consequence of varying viscosity and Lorentz force. The nonlinear flow equations are transformed into dimensionless form by using nonsimilar variables. The finite-difference technique (FTCS) is involved in computing the nonlinear transport dimensionless equations. The significant parameters like angle parameter, the Hartmann number, changing viscosity, constant heat source, the Reynolds number, and nanoparticle volume fraction on the flow field are exhibited through figures. Present results disclose that the Lorentz force strongly lessens the hybrid nanofluid velocity. Elevating the Grashof number values enhances the rate of blood flow. Growing values of the angle parameter cause to reduce the resistance impedance on the wall. Hybrid nanoparticles have a superior wall shear stress than copper nanoparticles. The heat transfer rate is amplifying at the axial direction with the growing values of nanoparticles concentration. The applied Lorentz force significantly reduces the hybrid and unitary nanofluid flow rate in the axial direction. The hybrid nanoparticles expose a supreme rate of heat transfer than the copper nanoparticles in a blood base fluid. Compared to hybrid and copper nanofluid, the blood base fluid has a lower temperature.

Time-dependent nonlinear lateral vibrations of plates composed of a hyperelastic matrix and uniformly/nonuniformly distributed hyperelastic reinforcing inclusions are studied. Since the material constants of a hyperelastic must be extracted from the whole slope-varying stress-strain curve rather than a single slope, choosing power/exponential distributions for the material constants or using Voigt’s rule of mixtures is quite wrong. The neo-Hookean and Mooney–Rivlin constitutive models are adopted, and their results are compared. Another hint is incorporating the incompressibility condition. The governing equations of motion are derived by using Hamilton’s principle, a new energy-equivalence-based micromechanical model that can be employed for reinforcing phases with nonlinear constitutive laws, and von Kármán assumptions in the left Cauchy–Green deformation tensor, and solved by incorporation of an updating finite-element and Newmark’s techniques. Not only the displacement but typical stress results are also reported here. Results show that the neo-Hookean model overestimates the rigidity in comparison to the Mooney–Rivlin model, and unlike the elastic plates, the effect of the stiffer phase is more remarkable in the uniform distribution in comparison to the nonuniform distribution of the stiffening materials because the magnitudes of the tensile stresses of the hyperelastic plate are much larger than that of the bending stresses.

Rapid development in robotics and bionics make it possible for robotic leg prostheses to help amputees while impose challenges on duplicating the motion characteristics of amputees' healthy leg. One critical problem in prosthetic control is joint angle drift problem, that is, a repetitive motion trajectory in task space cannot guarantee that the generated motion trajectories in joint space are also repetitive. In order to solve the problem, we propose neural-dynamics optimization for robotic leg prostheses to generate the repetitive joint trajectories in real-time. Our proposed method duplicates the self-selected walking speed of the amputees' healthy leg. The online motion generation is formulated as a constrained quadratic programming (QP) optimization problem whose objective function adopts the kinetic energy and joint displacement performance criterion. The varying parameter convergent differential neural network is developed as a real-time QP solver which can globally converge to the optimal solution of the constrained QP problem. Then, a repetitive learning controller is designed for robotic leg prostheses to reduce the tracking errors while following the repetitive motion. Through the physical experiments on the developed two-degree-of-freedom robotic leg prosthesis worn on an amputee, the neural-dynamics optimization is substantiated to be a remedy of online motion generation, and the effectiveness of repetitive learning control for reducing the prosthetic tacking errors is verified.

Quantitative magnetic resonance imaging is one of the few available methods for noninvasive diagnosis of degenerative changes in articular cartilage. The clinical use of the imaging data is limited by the lack of a clear association between structural changes at the molecular level and the measured magnetic relaxation times. In anisotropic, collagen-containing tissues, such as articular cartilage, the orientation dependency of nuclear magnetic relaxation can obscure the content of the images. Conversely, if the molecular origin of the phenomenon would be better understood, it would provide opportunities for diagnostics as well as treatment planning of degenerative changes in these tissues. We study the magnitude and orientation dependence of the nuclear magnetic relaxation due to dipole–dipole coupling of water protons in anisotropic, collagenous structures. The water–collagen interactions are modeled with molecular dynamics simulations of a small collagen-like peptide dissolved in water. We find that in the vicinity of the collagen-like peptide, the dipolar relaxation of water hydrogen nuclei is anisotropic, which can result in orientation-dependent relaxation times if the water remains close to the peptide. However, the orientation-dependency of the relaxation is different from the commonly observed magic-angle phenomenon in articular cartilage MRI.

In this paper, the mechanisms of mass transfer in the In/CdTe system under nanosecond pulsed laser irradiation, which are due to nonstationarity, nonequilibrium, physical and geometric nonlinearity, high speed and simultaneity of various physical processes; in particular, it is a change in the physical state of a solid body, the generation of elastic and shock waves, significant temperature and stress gradients, defect formation, diffusion, and others. The dominant mechanisms and regularities of indium mass transfer in CdTe under nanosecond laser irradiation of the In-CdTe structure have been established.

In proton therapy, a highly conformal proton dose can be delivered to the tumor by means of the steep distal dose penumbra at the end of the beam range. The proton beam range, however, is highly sensitive to range uncertainty, which makes accurately locating the proton range in the patient difficult. In-vivo range verification is a method to manage range uncertainty, one of the promising techniques being prompt gamma imaging (PGI). In earlier studies, we proposed gamma electron vertex imaging (GEVI), and constructed a proof-of-principle system. The system successfully demonstrated the GEVI imaging principle for therapeutic proton pencil beams without scanning, but showed some limitations under clinical conditions, particularly for pencil beam scanning proton therapy. In the present study, we upgraded the GEVI system in several aspects and tested the performance improvements such as for range-shift verification in the context of line scanning proton treatment. Specifically, the system showed better performance in obtaining accurate prompt gamma (PG) distributions in the clinical environment. Furthermore, high shift-detection sensitivity and accuracy were shown under various range-shift conditions using line scanning proton beams.

Proton therapy for cancer treatment has a precise dose deposition capability owing to the nature of the interactions of heavy charge particles with matter resulting in a Bragg Peak. Uncertainties in the proton range can limit the scope of proton therapy. Academia Sinica PET employs a modular design for In-beam detection using SiPMs and crystals read out by STiC asic for range verification. In this work we report the depth distribution of the positron emitters from a PMMA sample irradiated with 130 MeV protons at the Chang Gung Memorial Hospital measured using a compact 32-channel setup. The timing capabilities of this system are assessed and presented. The depth dependence of the positron activity measured using coincidences agrees well with the Geant4 simulated distributions. Using a multi-exponential fit function we estimate and compare the relative amounts of different positron emitting isotopes with the relative cross sections. The application of this method can be useful to estimate the anatomical changes between different treatment sessions. The modular design of the AS-PET currently under development at Academia Sinica is presented and the simulated images of the reconstructed positron activity for the palm sized modules are used to assess the range verification capability.

The automatic brain tumor segmentation in MRI (Magnetic Resonance Images) is becoming a challenging task in the field of medicine, since the brain tumor occurs in different shapes, intensities and sizes. This paper proposes an efficient automatic brain tumor segmentation using Greedy Snake Model and Fuzzy C-Means optimization. This method initially identifies the approximate Region Of Interest (ROI), by removing the non-tumor part by two level morphological reconstruction such as dilation and erosion. A mask is formed by thresholding the reconstructed image and is eroded to improve the accuracy of segmentation in Greedy Snake algorithm. Using the mask boundary as initial contour of the snake, the greedy snake model estimates the new boundaries of tumor. These boundaries are accurate in regions where there is sharp edge and are less accurate where there are ramp edges. The inaccurate boundaries are further optimized by using Fuzzy C-Means algorithm to obtain the accurate segmentation output. The region that has large perimeter is finally chosen, to eliminate the in- accurate segmented regions. The experimental verification were done on T1-weighted contrast-enhanced image data set, using the metrics such as dice score, specificity, sensitivity and Hausdorff distance. The proposed method outperforms when compared with the traditional brain tumor segmentation methods in MRI images.

For interpretation of electroencephalography (EEG) and magnetoencephalography (MEG) data, multiple solutions of the respective forward problems are needed. In this paper, we assess performance of the mixed-hybrid finite element method (MHFEM) applied to EEG and MEG modeling. The method provides an approximate potential and induced currents and results in a system with a positive semi-definite matrix. The system thus can be solved with a variety of standard methods (e.g. the preconditioned conjugate gradient method). The induced currents satisfy discrete charge conservation law making the method conservative. We studied its performance on unstructured tetrahedral grids for a layered spherical head model as well as a realistic head model. We also compared its accuracy versus the conventional nodal finite element method (P1 FEM). To avoid modeling singular sources, we completed our computations with a subtraction approach; the derived expression for the MEG response different from earlier published and involves integration of finite quantities only. We conclude that although the MHFEM is more computationally demanding than the P1 FEM, its use is justified for EEG and MEG modeling on low-resolution head models where P1 FEM loses accuracy.

In photoacoustic tomography (PAT), conventional image reconstruction methods are generally based on the assumption of an ideal point-like ultrasonic detector. This assumption is appropriate when the receiving surface of the detector is sufficiently small and/or the distance between the imaged object and the detector is large enough. However, it does not hold in endoscopic applications of PAT. In this study, we propose a model-based image reconstruction method for endoscopic photoacoustic tomography (EPAT), considering the effect of detector responses on image quality. We construct a forward model to physically describe the imaging process of EPAT, including the generation of the initial pressure due to optical absorption and thermoelastic expansion, the propagation of photoacoustic waves in tissues, and the acoustic measurement. The model outputs the theoretical sampling voltage signal, which is the response of the ultrasonic detector to the acoustic pressure reaching its receiving surface. The images representing the distribution map of the optical absorption energy density on cross-sections of the imaged luminal structures are reconstructed from the sampling voltage signals output by the detector through iterative inversion of the forward model. Compared with the conventional approaches based on back-projection and other imaging models, our method improved the quality and spatial resolution of the resulting images.

Diffusion MRI (dMRI) is a valuable imaging technique to study the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various acquisition strategies have been developed to achieve high resolutions, but they require long scan times. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* and the greater field non-uniformities will degrade image quality. In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral, over a range of resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6-1.8 mm. In-vivo scans were acquired using the three readout trajectories. Field probes were used to measure dynamic magnetic fields up to the 3rd order of spherical harmonics. Using a static field map and the measured trajectories image artifacts were corrected, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps. In-vivo scans were acquired to calculate the SNR. EPI trajectories had the highest specificity, effective resolution, and image sharpening effect, but also had substantially lower SNR. Spirals had significantly higher SNR, but lower specificity. Line plots of the in-vivo scans in phase and frequency encode directions showed ~0.2 units difference in FA values between the different trajectories. The difference between the effective and nominal resolution is greater for spirals than for EPI. However, the higher SNR of spiral trajectories at UHFs allows us to achieve higher effective resolutions compared to EPI and PF-EPI trajectories.

We study the Loschmidt echo in the quenched two-dimensional $p$-wave topological superconductor. We find that if this superconductor is quenched out of the critical point separating its topological and non-topological phases into either of the two gapful phases, its Loschmidt echo features singularities occurring periodically in time where the second derivative of the Loschmidt echo over time diverges logarithmically. Conversely, we give arguments towards $s$-wave superconductors not having singularities in their Loschmidt echo regardless of the quench. We also demonstrate that the conventional mean field theory calculates classical echo instead of its quantum counterpart, and show how it should be modified to capture the full quantum Loschmidt echo.

At the stage of design research of armored bodies of lightly armored vehicles it is extremely important to determine the range of their natural frequencies and natural forms of oscillation. For this purpose, the finite element method is usually used. It is necessary to substantiate the parameters of the finite element model, which provide an acceptable level of accuracy of numerical modeling of dynamic properties of this type of structures. For this purpose, data from parallel numerical and experimental studies of the mock-up of the armored hull of the armored personnel carrier are used. The mock-up of the upper projection of the armored hull is made in the appropriate scale. The material is sheet steel. This mock-up is subjected to dynamic excitation on a vibrating table. Resonant excitation frequencies are recorded, as well as the natural vibration forms. Shock-pulse excitation of the armored hull’s mock-up was also performed. The response to this excitation is recorded using accelerometers. Then, the spectrum of natural vibration frequencies is determined from these oscillograms. In parallel, numerical modeling of natural frequencies and natural vibration forms of the armored hull’s mock-up is carried out. After that, the results of numerical and experimental studies are compared. By varying the parameters of the finite element model, a satisfactory correspondence between the results of numerical calculations and experimental measurements is achieved. In particular, the following are determined: the acceptable type of used finite elements; the number of finite elements required to satisfy the accuracy of numerical modeling of the dynamic properties of similar structures; zones of the recommended thickening-rarefaction of a grid of finite elements, etc. According to the research results, the parameters of finite-element models have been established, which can be used to study the dynamic processes and properties of full-scale armored hulls of lightly armored vehicles. Keywords: lightly armored vehicle, mock-up, natural frequency, spectrum of natural vibration frequencies, На этапе проектных исследований бронекорпусов легкобронированных машин крайне важно определение спектра их собственных частот колебаний и собственных форм колебаний. С этой целью обычно применяется метод конечных элементов. При этом необходимо обосновывать параметры конечно-элементной модели, обеспечивающие приемлемый уровень точности численного моделирования динамических свойств такого типа конструкций. Для этой цели привлекаются данные параллельно осуществляемых численных и экспериментальных исследований макета бронекорпуса бронетранспортера. Сам макет верхней проекции бронекорпуса сделан в соответствующем масштабе. Материал – листовая сталь. Этот макет подвержен динамическому возбуждению на вибростенде. Фиксируются резонансные частоты возбуждения и собственные формы колебаний. Также осуществлено ударно-импульсное возбуждение макета бронекорпуса. Отклик на это возбуждение фиксируется с помощью акселерометров. В дальнейшем из этих осциллограмм определяется спектр собственных частот колебаний. Параллельно осуществляется численное моделирование собственных частот колебаний и форм колебаний макета бронекорпуса. В дальнейшем результаты численных и экспериментальных исследований сравниваются. Путем варьирования параметров конечно-элементной модели достигается удовлетворительное соответствие результатов численных расчетов и экспериментальных измерений. В частности, определяются: приемлемый тип применяемых конечных элементов; количество конечных элементов, необходимое для удовлетворения точности численного моделирования динамических свойств конструкций подобного типа; зоны рекомендуемого сгущения-разрежения сетки оконченных элементов и т.п. По результатам исследований установлены параметры конечно-элементных моделей, которые могут быть применены для исследования динамических процессов и свойств натурных бронекорпусов легкобронированных машин. Ключевые слова: легкобронированная машина, макет, собственная частота колебаний, спектр собственных частот колебаний, На етапі проєктних досліджень бронекорпусів легкоброньованих машин вкрай важливим є визначення спектру їх власних частот коливань та власних форм коливань. Із цією метою зазвичай застосовується метод скінченних елементів. При цьому необхідно обґрунтовувати параметри скінченно-елементної моделі, які забезпечують прийнятний рівень точності чисельного моделювання динамічних властивостей такого типу конструкцій. Із цією метою залучаються дані паралельно здійснюваних чисельних та експериментальних досліджень макету бронекорпусу бронетранспортера. Сам макет верхньої проекції бронекорпусу виготовлено у відповідному масштабі. Матеріал – листова сталь. Цей макет піддано динамічному збудженню на вібростенді. Фіксуються резонансні частоти збудження, а також власні форми коливань. Також здійснено ударно-імпульсне збудження макета бронекорпуса. Відгук на це збудження фіксується за допомогою акселерометрів. Надалі із цих осцилограм визначається спектр власних частот коливань. Паралельно здійснюється чисельне моделювання власних частот коливань і власних форм коливань макету бронекорпусу. Надалі результати чисельних і експериментальних досліджень порівнюються. Шляхом варіювання параметрів скінченно-елементної моделі досягається задовільна відповідність результатів чисельних розрахунків та експериментальних вимірювань. Зокрема, визначаються: прийнятний тип скінченних елементів, що застосовуються; кількість скінченних елементів, необхідна для задоволення точності чисельного моделювання динамічних властивостей конструкцій подібного типу; зони рекомендованого згущення-розрідження сітки скінченних елементів тощо. За результатами досліджень установлені параметри скінченно-елементних моделей, які можуть бути застосовані для дослідження динамічних процесів і властивостей натурних бронекорпусів легкоброньованих машин. Ключові слова: легкоброньована машина, макет, власна частота коливань, спектр власних частот коливань

Simple Summary Healthy tissue tolerance to radiation is one of the main limitations in radiotherapy treatment. To broaden the therapeutic index, innovative approaches using non-conventional spatial and temporal beam structure are currently being investigated. Among them, proton minibeam radiation therapy is a promising solution that has already shown a remarkable increase in healthy tissue tolerance in various preclinical models. The purpose of this study is to propose potential strategies to further optimize proton minibeam spatial modulation with the use of magnetic fields. By generating a converging minibeam pattern with dipole magnetic fields, we show that spatial modulation can be improved at shallow depth for the same dose distribution at the tumor location. This indicates that proton minibeam radiation therapy could be efficiently combined with magnetic fields to further increase healthy tissue tolerance. Abstract Proton MiniBeam Radiation Therapy (pMBRT) is a novel strategy that combines the benefits of minibeam radiation therapy with the more precise ballistics of protons to further optimize the dose distribution and reduce radiation side effects. The aim of this study is to investigate possible strategies to couple pMBRT with dipole magnetic fields to generate a converging minibeam pattern and increase the center-to-center distance between minibeams. Magnetic field optimization was performed so as to obtain the same transverse dose profile at the Bragg peak position as in a reference configuration with no magnetic field. Monte Carlo simulations reproducing realistic pencil beam scanning settings were used to compute the dose in a water phantom. We analyzed different minibeam generation techniques, such as the use of a static multislit collimator or a dynamic aperture, and different magnetic field positions, i.e., before or within the water phantom. The best results were obtained using a dynamic aperture coupled with a magnetic field within the water phantom. For a center-to-center distance increase from 4 mm to 6 mm, we obtained an increase of peak-to-valley dose ratio and decrease of valley dose above 50%. The results indicate that magnetic fields can be effectively used to improve the spatial modulation at shallow depth for enhanced healthy tissue sparing.

In this paper, the variation of axial velocity of blood plasma with arterial radius has been studied in the laminar flow of blood plasma through a non-deformed artery. Since blood plasma is a Newtonian fluid, the Hagen-Poiseuille flow was used to study this variation. The Hagen-Poiseuille model was obtained by transforming the Navier- Stokes equations from rectangular coordinates system to cylindrical coordinates system and then making some approximations to the transformed equations. Furthermore, the axial velocity of blood plasma was plotted against the radius of a sampled artery, results and conclusions were made between the relationships.

Arrhythmias are potentially fatal disruptions to the normal heart rhythm, but their underlying dynamics is still poorly understood. Theoretical modeling is an important tool to fill this gap. Typical studies often employ detailed multidimensional conductance-based models. We describe the cardiac muscle with a three-dimensional map-based membrane potential model in lattices. Although maps retain the biophysical behavior of cells and generate computationally efficient tissue models, few studies have used them to understand cardiac dynamics. Our study captures healthy and pathological behaviors with fewer parameters and simpler equations than conductance models. We successfully generalize results obtained previously with reaction-diffusion systems, showing how chaotic properties result in reentry, a pathological propagation of stimuli that evolves to arrhythmias with complex spatiotemporal features. The bifurcation diagram of the single cell is very similar to that obtained in a detailed conductance-based model. We find torsade de pointes, a clinical manifestation of some types of tachycardia in the electrocardiogram, using a generic sampling of the whole network during spiral waves. We also find a novel type of dynamical pattern, with wavefronts composed of synchronized cardiac plateaus and bursts. Our study provides the first in-depth look at the use of map-based models to simulate complex cardiac dynamics., 15 pages, 9 figures. Eur. Phys. J. Spec. Top. (2022)

The risk of cardiovascular diseases is determined by the deposition of plaque in the coronary arteries. The areas of plaque deposition are also controlled by the flow dynamics and, for this, the topology of the arterial bifurcations has shown to be crucial. We present a detailed analysis of different topologies at the bifurcation based on numerical simulations of a mathematical model. Different diameters of the involved vessels as well as angle between them are analyzed. Unexpectedly, the curvature of the walls connecting the vessels is observed to play an important role.

The necessity of application of rigid type acoustic screens in hydroacoustic stations with deep-water antennas of variable depth is substantiated. By the method of coupled fi elds in multiconnected regions for antennas formed from cylindrical piezoceramicradiators with rigid screens in the form of open rings of fi nite thickness, analytical expressions for calculations of acoustic fi elds of such radiators are obtained. In the solution of the problem “pass-through” radiation shielded transducer included interactions: electrical, mechanical and acoustic fi elds in the conversion of energy; acoustic fi elds of the shell and screen during energy generation; processes of energy conversion and formation. Quantitative results of calculations of acoustic fi elds on the received expression are resulted.

Carbon nanotubes orientation has a significant impact on the performance of carbon nanotubes/epoxy resin (CNTs/EP) composite materials. The ultrasonic velocity is sensitive to the degree of carbon nanotubes orientation. However, the time-of-flight (TOF) is difficulty to accurately measured due to ultrasonic echo aliasing and waveform distortion occurred in the thin CNTs/EP composite material. Therefore, the ultrasonic characterization method of carbon nanotubes orientation based on the sparse representation is studied in this paper. Two groups of CNTs/EP specimens are taken as research objects. Firstly, the dictionary is constructed by Gabor function，and the matching degree between dictionary and ultrasonic echo signals is researched. Then, the matching pursuit (MP) algorithm is used to solve the problem of dictionary redundancy and obtain the best matching atom; the signal reconstruction is completed and ultrasonic TOF of carbon nanotubes is extracted more accurately. Finally, a carbon nanotubes orientation prediction model based on the sparse representation is established. The result shows that the Gabor dictionary has good similarity with ultrasonic echo signals and the root mean square relative error is 0.0147. The degree of carbon nanotubes orientation and ultrasonic velocity have positive correlation. The carbon nanotubes orientation prediction model relative error is 5.58%. This paper has provided an effective method to characterize the degree of carbon nanotubes orientation.

International audience; Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic Monte Carlo simulations of an existing pCT scanner prototype, which we describe in detail.

Tensile testing of steel specimens under 'soft' and 'hard' loading conditions with simultaneous measurement of the self-magnetic field of the specimens using the metal magnetic memory (MMM) method is performed. By comparing the obtained tensile diagrams with magnetograms of the self-magnetic field variation, the relationship between the magnetic and mechanical characteristics at different stages of loading is determined. It is found that the self-magnetic field variation magnetograms of the specimens closely correspond to the true tensile diagrams. The ratios between the magnetic and mechanical characteristics, obtained during tensile testing of the specimens, allow for the determination of the limiting state of the metal at the time of crack formation using the measured magnetic parameters in stress concentration zones when performing practical diagnostics of equipment.

Sensor layout of biomagnetic measurement systems is measured using a multiple coil array that generates a magnetic signal. However, the results of the sensor array measurement included the error of the coil array because the coil array was not calibrated. In this paper, we proposed a calibration method to obtain the effective geometry and uncertainty of the coil array. The calibration was performed based on the X-ray CT measurements and numerical analysis of the position and shape of the coils. The differences between the designed and calibrated coil array geometries were 0.6 mm, 0.7°, and 0.3 mm with respect to the center position, orientation of the normal vector, and radius of the coils, respectively. The uncertainty of the calibration was 0.3 mm and 1.70 in terms of the dimension and orientation, respectively. We measured the sensor array layout of a magnetoencephalography (MEG) system using a calibrated coil array geometry. The source localization accuracy of the MEG system was improved compared with that of the sensor array layout obtained using the designed coil array geometry. We revealed the necessity of calibrating the coil array, regardless of the precision of the fabrication.

In order to have highly flexible secondary beamlines collimation is crucial. Collimators are blocks of material placed along the beamline that let the main beam pass within the collimator aperture limits, while most of the particles beyond it interact in the material and gets absorbed or loses enough energy to be deflected away from the beam core by the magnets placed downstream. Some particles can interact at the edge of the collimators and be accepted within the main beam, creating background for the experiments downstream. The thickness of the layer contributing to this potential background is called Skin Depth. It depends on the material of the collimator, on the beam momentum as well as the acceptance of the beamline in terms of momentum band and divergence. This article presents the first studies with GEANT4 and FLUKA based simulations on the effects of such interactions at the CERN secondary beamlines.

A Piecewise Sub-Optimal Threshold (PSOT) is proposed to select the Most Significant Samples (MSS) of the Channel Impulse Response (CIR) for channel estimation of ultrasonic through-metal (UTM) communication. We analyze the correlation of echoes in the UTM channel, i.e., the periodicity and the exponential decay of echoes. The summation of mean-square error (MSE) is partitioned by using the periodicity of the echoes so that each partitioned MSE contains only one echo. The PSOT is derived by setting the first derivative of the partitioned MSE to zero. Channel tap energies, namely the received energies of ultrasonic waves, are required to calculate the PSOT, which can be estimated by using the exponential decay of echoes. After selecting MSSs by PSOT, we propose a further selection approach to get rid of possible noise samples in the MSS by using the correlation of echoes. Simulation results show that the proposed method is robust. Specifically, the performance of the proposed method does not depend on ultrasonic velocity, is unaffected by the estimated number of the echoes at a low signal-to-noise ratio (SNR), and can be applied to UTM channels with different metal thicknesses. The simulation also shows that the proposed method has a lower MSE than other methods, especially at low SNR.

In this paper, the effects of hot isostatic pressing (HIP) temperature on the crystal structure, optical, dielectric and magnetic properties of GdMnO3 ceramics were studied. All samples form a single-phase structure without structural transformation, while HIP temperature induces the changes in lattice parameters. HIP causes the change in Mn ions valence state, oxygen vacancy concentration, Raman vibration modes and microscopic morphology of GdMnO3. Vacancy concentration of the samples prepared by HIP at 800 °C increases compared with that of the samples without HIP, then remains unchanged when the HIP temperature is from 800 to 900 °C, and finally decreases with the further increase of HIP temperature. Appropriate HIP temperature can increase the dielectric constant and decrease the dielectric loss. The transition temperature of paramagnetism to antiferromagnetism and magnetization can be significantly affected by HIP temperature. Magnetic transition temperature and magnetization are closely related to Mn2+ ions concentration and cation vacancy concentration, respectively.

We consider bifurcations from the homogeneous solution of a circular or square hyperelastic sheet that is subjected to equibiaxial stretching under either force- or displacement-controlled edge conditions. We derive the condition for axisymmetric necking and show, for the class of strain-energy functions considered, that the critical stretch for necking is greater than the critical stretch for the Treloar-Kearsley (TK) instability and less than the critical stretch for the limiting-point instability. An amplitude equation for the bifurcated necking solution is derived through a weakly nonlinear analysis and is used to show that necking initiation is generally sub-critical. Abaqus simulations are conducted to verify the bifurcation conditions and the expectation that the TK instability should occur first under force control, but when the edge displacement is controlled the TK instability is suppressed, and it is the necking instability that will be observed. It is also demonstrated that axisymmetric necking follows a growth/propagation process typical of all such localization problems., 27 pages, 10 figures. This paper was accepted by Mathematics and Mechanics of Solids on 11 December 2021

All available thermodynamic data and phase diagram data in the Al2O3–ZrO2, CaO–Al2O3–ZrO2, and Al2O3–SiO2–ZrO2 systems at 1 bar total pressure were critically evaluated and assessed simultaneously to obtain a set of the optimized Gibbs energies of all phases in the systems. Due to the lack of reliable data on the mutual solubility of Al2O3 and ZrO2, key phase diagram experiments in the Al2O3–ZrO2 binary system were carried out by using a classical phase equilibrium and quenching technique followed by the EPMA phase analysis. Based on the optimized Gibbs energies, the reliable experimental phase diagram and thermodynamic property data of the Al2O3–ZrO2, CaO–Al2O3–ZrO2, and Al2O3–SiO2–ZrO2 systems are well reproduced, and unknown phase diagram and thermodynamic properties are predicted.