High order energy invariant fast algorithm for space two dimensional Klein-Gordon-Zakharov equations

High order explicit Lorentz invariant volume-preserving algorithms for relativistic dynamics of charged particles

Massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. We have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although this represents an optimal computation, due to the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. We develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. We also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.

In several papers of 2013–2016, Guglielmi and Protasov made a breakthrough in the problem of the joint spectral radius computation, developing the invariant polytope algorithm that for most matrix families finds the exact value of the joint spectral radius. This algorithm found many applications in problems of functional analysis, approximation theory, combinatorics, and so on. In this article, we propose a modification of the invariant polytope algorithm making it roughly 3 times faster (single threaded), suitable for higher dimensions, and parallelise it. The modified version works for most matrix families of dimensions up to 25, for non-negative matrices up to 3,000. In addition, we introduce a new, fast algorithm, called modified Gripenberg algorithm, for computing good lower bounds for the joint spectral radius. The corresponding examples and statistics of numerical results are provided. Several applications of our algorithms are presented. In particular, we find the exact values of the regularity exponents of Daubechies wavelets up to order 42 and the capacities of codes that avoid certain difference patterns.

The pencil beam dose calculation method is frequently used in modern radiation therapy treatment planning regardless of the fact that it is documented inaccurately for cases involving large density variations. The inaccuracies are larger for higher beam energies. As a result, low energy beams are conventionally used for lung treatments. The aim of this study was to analyze the advantages and disadvantages of dynamic IMRT treatment planning for high and low photon energy in order to assess if deviating from the conventional low energy approach could be favorable in some cases. Furthermore, the influence of motion on the dose distribution was investigated. Four non-small cell lung cancer cases were selected for this study. Inverse planning was conducted using Varian Eclipse. A total number of 31 dynamic IMRT plans, distributed amongst the four cases, were created ranging from PTV conformity weighted to normal tissue sparing weighted. All optimized treatment plans were calculated using three different calculation algorithms (PBC, AAA and MC). In order to study the influence of motion, two virtual lung phantoms were created. The idea was to mimic two different situations: one where the GTV is located centrally in the PTV and another where the GTV was close to the edge of the PTV. PBC is in poor agreement with MC and AAA for all cases and treatment plans. AAA overestimates the dose, compared to MC. This effect is more pronounced for 15 than 6 MV. AAA and MC both predict similar perturbations in dose distributions when moving the GTV to the edge of the PTV. PBC, however, predicts results contradicting those of AAA and MC. This study shows that PB-based dose calculation algorithms are clinically insufficient for patient geometries involving large density inhomogeneities. AAA is in much better agreement with MC, but even a small overestimation of the dose level by the algorithm might lead to a large part of the PTV being underdosed. It is advisable to use low energy as a default for tumor sites involving lungs. However, there might be situations where it is favorable to use high energy. In order to deviate from the recommended low energy convention, an accurate dose calculation algorithm (e.g. MC) should be consulted. The study underlines the inaccuracies introduced when calculating dose using a PB-based algorithm in geometries involving large density variations. PBC, in contrast to other algorithms (AAA and MC), predicts a decrease in dose when the density is increased.

We consider the general system of n first order linear ordinary differential equations y'(t)=A(t)y(t)+g(t), a<t< b, subject to "boundary" conditions, or rather linear constraints, of the form Σ^(N)_(ν=1) B_(ν)y(τ_ν)=β Here y(t), g(t) and II are n-vectors and A(t), Bx,..., BN are n × n matrices. The N distinct points {τ_ν} lie in [a,b] and we only require N ≧ 1. Thus as special cases initial value problems, N=1, are included as well as the general 2-point boundary value problem, N=2, with τ_1=a, τ_2=b. (More general linear constraints are also studied, see (5.1) and (5.17).)

Energy Minimization and the Satisfiability of Propositional Logic

In order to rapidly and non-destructively calculate image eigenvalue,by combining the Mallat algorithm, a new invariant wavelet moment algorithm with non-destructive sampling is presented.Feature extraction based on amplitude spectrum and wavelet moment invariants is also presented.The experimental results show that compared with the traditional cubic B-spline wavelet moments and Hu moment invariants,this algorithm can greatly accelerate the wavelet moment invariants calculation with few losses in performance.The new wavelet moment invariants algorithm based on amplitude spectrum is verified to be insensitive to noises compared with other wavelet moment invariants.

Emerging advanced technologies have seen a revolution of applications into medical field, in all its aspects and sides, this has helped healthcare practitioners and empowered them in achieving accurate diagnosis and treatment, specifically with the evolution of computer Aided Diagnosis systems which use image processing techniques, Computer vision,and deep learning applied on different medical images in order to diagnose the image, or sections of the image with particular diseases or illnesses. Medical images of multiples organs or parts of the body (Liver, brain, kidney, skin, etc...) can today be visualized thanks to the advanced medical imaging techniques that exists in the market (MRI, CT, etc…) these technologies uses high energy in order to acquire high quality images but high energy can harm human cells, this is why we us low energy and with this used we get slightly low quality medical images, and here technology intervenes where we can use preprocessing techniques in order to increase image resolution prior to perform diagnosis either by doctor or CAD system. We present in this paper a computer aided diagnosis system that provides an automated brain tissue segmentation applied on 3D MRI images with its four different modalities (T1, T1C, T2, T2 weighted) of BRatS 2020 challenge dataset, by implementing a U-Net like deep neural network which provides information about classification of brain tissue into healthy tissue, Edema, Enhancing tumour, Non enhancing tumour. The model achieved an accuracy of 99.01% and dice coefficient of 47.95% after 35 epochs of training.KeywordsSegmentationDeep learningBrain tumorsMedical image segmentationMedical image analysis

Animal models for insulin resistance and type 2 diabetes are required for the study of the mechanism of these phenomena and for a better understanding of diabetes complications in human populations. Type 2 diabetes is a syndrome that affects 5-10% of the adult population. Hyperinsulinaemia, hypertriglyceridaemia, decreased high-density lipoprotein (HDL) cholesterol levels, obesity and hypertension, all form a cluster of risk factors that increase the risk of coronary artery disease, and are known as insulin resistance syndrome or syndrome X. The gerbil, Psammomys obesus is characterized by primary insulin resistance and is a well-defined model for dietary induced type 2 diabetes. Weanling Psammomys and Albino rats were held individually for several weeks on high energy (HE) and low energy (LE) diets in order to determine the development of metabolic changes leading to diabetes. Feeding Psammomys on HE diet resulted in hyperglycaemia (303 +/- 40 mg/dl), hyperinsulinaemia (194 +/- 31 microU/ml) and a moderate elevation in body weight, obesity and plasma triglycerides. Albino rats on HE diet demonstrated an elevation in plasma insulin (30 +/- 4 microU/ml), hypertriglyceridaemia (170 +/- 11 mg/dl), an elevation in body weight and obesity, but maintained normoglycaemia (98 +/- 6 mg/dl). Psammomys represent a model that is similar to human populations, with primary insulin resistance expressed in young age, which leads to a high percentage of adult type 2 diabetes. Examples for such populations are the Pima Indians, Australian Aborigines and many other Third World populations. The results indicate that the metabolism of Psammomys is well adapted towards life in a low energy environment, where Psammomys takes advantage of its capacity for a constant accumulation of adipose tissue that will serve for maintenance and breeding in periods of scarcity. This metabolism known as 'thrifty metabolism', is compromised at a high nutrient intake.

When an atom or a molecule interacts with an intense laser field, a coherent high-order harmonic emission is observed at a frequency that is an integer multiple magnitude of the initial frequency of the incident laser field. The harmonic emission has the characteristic of high emission efficiency at relatively high orders, and it also has a wide expansion in the frequency domain. Thus, the high-order harmonic generation can be utilized to generate coherent EUV or soft X-ray light sources as well as ultrashort at to second laser pulses. It is promising that the attosecond laser pulse will be an important tool for detecting and controlling the electron dynamics in atom and molecule systems. The mechanisms of high-order harmonics especially the high energy part of the harmonic spectrum can be explained by the well-known three-step model. The three-step model assumes that the electron in the bound state firstly are ionized by the potential barrier formed by the laser electric field and the atomic potential, then the ionized electrons oscillate in the laser field, and finally the electron with high kinetic energy gained in the laser field has the possibility to return back to the parent ion and recombines with the ground state of the system with a high energy photon emitted. As for harmonics with low orders, especially those with single photon energy near the ionization threshold, the Coulomb potential of the atom has significant influences on them. However,the effect of the Coulomb potential of the atom are not included in the three-step model, so the mechanism of near-threshold harmonics (NTH) cannot be clearly interpreted with the three-step model alone. In this circumstance, the study of the mechanism of near-threshold harmonic emission attracted people's attention in general. One important application of NTH is that it can be utilized to generate optical comb with EUV frequencies. Theoretically, Xiong et al. studied the mechanism of below-threshold harmonic (BTH) emission and found that the mechanism of this part of harmonics include the effect of the quantum-path interference and the Coulomb potential. He et al. analyzed the emission of BTH in various laser intensity regions and found that the harmonic spectrum exhibits a periodic structure as a function of the harmonic frequency when the incident laser intensity is about 1013 W/cm2. Utilizing the quantum-path and time-frequency analyses of the harmonic emission, He et al. indicated that this periodic structure can be attributed to the interference effect between two specific quantum paths. Li et al. adopted the synchrosqueezing scheme to study the near-and below-threshold harmonic emission of Cs atoms in an intense mid-infrared laser field and they showed that the multiphoton and the multiple rescattering trajectories have an effect on the NTH and BTH generation processes. Shafir et al. found that the ionic potential plays an critical role in NTH emission. Under the interaction between the atom and the intense laser field, electron in the ground state not only can be ionized but also be pumped into excited state, and these excitation processes also affect the harmonic emission. We studied the harmonic emission process near the ionization threshold by solving the time-dependent Schrdinger equation of an atom interacting with a strong laser field. Utilizing the obtained wavefunction, we systematically studied the high-order harmonic emission with the variation of the incident laser intensity. Meanwhile, through solving the TDSE with the momentum-space method, the excited-state population is precisely calculated and achieved. We show that the ninth harmonic exhibits a periodic oscillation structure with the intensity of the incident laser field increasing, and we reveals that there is a synchronous variation between the harmonic intensity and the relatively high bound state population.Within a certain range of laser intensity, the increase of the total population of the excited states corresponds to the low efficiency of harmonic emission, and this competition relationship is quite clear. Therefore, when the wavelength of the driving laser pulse is fixed, we can optimize the driving laser intensity to achieve the near-threshold harmonic emission with high efficiency.

A new high order energy and enstrophy conserving Arakawa-like Jacobian differential operator

The difficulties in designing an effective load autopilot for missile arise from highly nonlinear and non-minimum phase plant characteristics from load command to missile load output. In this paper, the method of designing controller relied upon the notion of system immersion and manifold invariance. The construction of the stabilizing control laws resembles the procedure used in nonlinear regulator theory to derive the (invariant) output zeroing manifold and its friend. The method is well suited in situations where we know a stabilizing controller of a nominal reduced order mode, which we would like to robustify with respect to higher order dynamics. This method overcomes these difficulties and the designed autopilot improves system performances.

A fully affine invariant matching method for side scan sonar image is proposed in this paper. This method uses fully affine invariant features under nonlinear scale space built by nonlinear diffusion filter. We call the new Nonlinear Affine Inva-Riant feature NAIR feature, it makes full use of the advantage of affine invariant of ASIFT algorithm and feature distinctiveness in nonlinear scale space. It overcomes the problem of the failure of large view-changed side scan sonar image matching caused by the change of heading direction during sonar data acquisition and the anti-noise performance is enhanced through the nonlinear diffusion filter. The experimental results show that the proposed method has better anti-noise performance and higher accuracy compared with the state of art feature matching algorithms.

The success of the rechargeable Li-S cell is limited in part by the dissolution of lithium-polysulfide in the electrolyte. Remarkably, it is found that removal of the conventional membrane separator in a Li-S cell improves sulfur utilization and cycling performance, whether the sulfur is initially contained in the cathode or electrolyte. An optimized cell design yields discharge capacities as high as 980 mA h g-1 after 100 cycles.

This report describes work done in Fiscal Year 1977 by the Fusion Reactor Studies Group of LLL on the conceptual design of a 1000-MW(e) Tandem Mirror Reactor (TMR). The high Q (defined as the ratio of fusion power to injection power) predicted for the TMR (approximately 5) reduces the recirculating power to a nondominant problem and results in an attractive mirror fusion power plant. The fusion plasma of the TMR is contained in the 100-m-long central cell where the magnetic field strength is a modest 2 T. The blanket for neutron energy recovery and tritium breeding is cylindrical and, along with the solenoidal magnet, is divided into 3-m-long modules to facilitate maintenance. The central cell is fueled (but not heated) by the injection of low-energy neutral beams near its ends. Thus, the central cell is simple and of low technology. The end-cell plasmas must be of high density and high energy in order to plug and heat (via the electrons) the central-cell plasma. The present conceptual design uses 1.2-MeV neutral-beam injection for the end plugs and a cryogenic-aluminum, Yin-Yang magnet that produces an incremental field of about 1 T over a field of 16 T produced by a pair of Nb/sub 3/Sn superconducting solenoids. Important design problems remain in both the neutral-beam injector and in the end-plug magnet. Also remaining are important physics questions such as alpha-beam particle transport and end-plug stability. These questions are discussed at length in the report and suggestions for future work are given.