Miracle-dz/UniFAR-FTUs huggingface dataset:
Positive-energy D-bar method for acoustic tomography: a computational study

A new computational method for reconstructing a potential from the Dirichlet-to-Neumann (DN) map at positive energy is developed. The method is based on D-bar techniques and it works in absence of exceptional points—in particular, if the potential is small enough compared to the energy. Numerical tests reveal exceptional points for perturbed, radial potentials. Reconstructions for several potentials are computed using simulated DN maps with and without added noise. The new reconstruction method is shown to work well for energy values between 10−5 and 5, smaller values giving better results.
Precision of the PET activity range during irradiation with 10C, 11C, and 12C beams

Objective. Beams of stable ions have been a well-established tool for radiotherapy for many decades. In the case of ion beam therapy with stable 12C ions, the positron emitters 10,11C are produced via projectile and target fragmentation, and their decays enable visualization of the beam via positron emission tomography (PET). However, the PET activity peak matches the Bragg peak only roughly and PET counting statistics is low. These issues can be mitigated by using a short-lived positron emitter as a therapeutic beam. Approach. An experiment studying the precision of the measurement of ranges of positron-emitting carbon isotopes by means of PET has been performed at the FRS fragment-separator facility of GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany. The PET scanner used in the experiment is a dual-panel version of a Siemens Biograph mCT PET scanner. Main results. High-quality in-beam PET images and activity distributions have been measured from the in-flight produced positron emitting isotopes 11C and 10C implanted into homogeneous PMMA phantoms. Taking advantage of the high statistics obtained in this experiment, we investigated the time evolution of the uncertainty of the range determined by means of PET during the course of irradiation, and show that the uncertainty improves with the inverse square root of the number of PET counts. The uncertainty is thus fully determined by the PET counting statistics. During the delivery of 1.6 × 107 ions in 4 spills for a total duration of 19.2 s, the PET activity range uncertainty for 10C, 11C and 12C is 0.04 mm, 0.7 mm and 1.3 mm, respectively. The gain in precision related to the PET counting statistics is thus much larger when going from 11C to 10C than when going from 12C to 11C. The much better precision for 10C is due to its much shorter half-life, which, contrary to the case of 11C, also enables to include the in-spill data in the image formation. Significance. Our results can be used to estimate the contribution from PET counting statistics to the precision of range determination in a particular carbon therapy situation, taking into account the irradiation scenario, the required dose and the PET scanner characteristics.
Effective Maxwell’s equations in general periodic microstructures

ABSTRACT We study the time harmonic Maxwell equations in a meta-material consisting of perfect conductors and void space. The meta-material is assumed to be periodic with period ; we study the behaviour of solutions in the limit and derive an effective system. In geometries with a non-trivial topology, the limit system implies that certain components of the effective fields vanish. We identify the corresponding effective system and can predict, from topological properties of the meta-material, whether or not it permits the propagation of waves.
The partial $C^0$-estimate along the continuity method

We prove that the partial $C^0$-estimate holds for metrics along Aubin's continuity method for finding Kahler-Einstein metrics, confirming a special case of a conjecture due to Tian. We use the method developed in recent work of Chen-Donaldson-Sun on the analogous problem for conical Kahler-Einstein metrics.
Incremental Weighted Ensemble for Data Streams With Concept Drift

As a popular strategy to tackle concept drift, chunk-based ensemble method adapts a new concept by adjusting the weights of historical classifiers. However, most previous approaches normally evaluate the historical classifier based on an entire chunk newly arrived, which may cause delayed adaptation. To address the issue, two novel ensemble models, named incremental weighted ensemble (IWE) and incremental weighted ensemble for multi-classification (IWE-M), are proposed. At each time step, all base classifiers are incrementally updated on a newly arrived instance. Following that, the instance is collected into a cache array. Once a data chunk is formed, a new base classifier is created. More specially, a forgetting mechanism based on variable-size window is designed to adjust the weight of each base classifier in IWE in terms of its classification accuracy on the latest instances in an online manner. IWE-M, an extension of IWE, aims to solve multiclass problems with local concept drifts. In IWE-M, the weight of a base classifier is expanded to a weight vector. In this way, this ensemble model can retain specific historical information about nondrift regions from a local drift. Experimental results show that the proposed ensemble frameworks outperform six competitive approaches on accuracy and G-mean.
Transient error growth and local predictability: a study in the Lorenz system

Lorenz's three-variable convective model is used as a prototypical chaotic system in order to develop concepts related to finite time local predictability. Local predictability measures can be represented by global measures only if the instability properties of the attractor are homogeneous in phase space. More precisely, there are two sources of variability of predictability in chaotic attractors. The first depends on the direction of the initial error vector, and its dependence is limited to an initial transient period. If the attractor has homogeneous predictability properties, this is the only source of variability of error growth rate and, after the transient has elapsed, all initial perturbations grow at the same rate, given by the first (global) Lyapunov exponent. The second is related to the local instability properties in phase space. If the predictability properties of the attractor are not homogeneous, this additional source of variability affects both the transient and post-transient phases of error growth. After the transient phase all initial perturbations of a particular initial condition grow at the same rate, given in this case by the first local Lyapunov exponent. We consider various currently used indexes to quantify finite time local predictability. The probability distributions of the different indexes are examined during and after the transient phase. By comparing their statistics it is possible to discriminate the relative importance of the two sources of variability of predictability and to determine the most appropriate measure of predictability for a given forecast time. It is found that a necessary premise for choosing a relevant local predictability index for a specific system is the study of the characteristics of its transient. The consequences for the problem of forecasting forecast skill in operational models are discussed. DOI: 10.1034/j.1600-0870.1995. 00006.x
Some implications of a small bag radius

We consider the possibility that the bag radius of the nucleon is of the order of the proton Compton wavelength. We explore this possibility for the cloudy-bag-model Hamiltonian when the interaction between the intrinsic isobar source and the pion field is turned off. Because of the large pion-nucleon coupling for a small bag radius, we apply the strong-coupling approximation to this model. Unlike other models of the nucleon with a small bag radius, our approach emphasizes the quantum-mechanical behavior of the infinitely many degrees of freedom of the pion field in the dressed nucleon wave function. Considerable attention is given to the approximate analytic solution of the strong-coupling part of the cloudy-bag-model Hamiltonian, which is a collective Hamiltonian involving nine coupled quantum-mechanical oscillators. An important feature of the model is the existence of collective excitations of the dressed nucleon which are rotational and vibrational excitations in spin and isospin space. The lowest-lying collective state is a spin and isospin rotational excitation which is identified with the . delta. , while the N( is a vibrational excitation. The approximate analytic expressions for the low-lying baryon wave functions facilitate the actual calculation of some static properties of the baryons such as masses, magnetic moments, more » charge radii, etc. We find for a bag radius R = 0.32 fm that the average number of pions in the dressed nucleon state is roughly 6. Furthermore, the overall agreement between the model and experiment is roughly 30%; however, the charge radius of the proton is too small. Some speculative ideas for improving the model are discussed. « less
Stochastic instability and turbulent transport. Characteristic scales, increments, and diffusion coefficients

Stochastic instability and its associated turbulent diffusion models are reviewed, with particular attention given to the problem of obtaining estimates and scaling laws that characterize correlation effects and increments. Specific models considered include the quasilinear Kazantsev approximation, stochasticity in a system of convective cells, the Kadomtsev–Pogutse scaling, percolation models, and the Rochester–Rosenbluth balance. The primary goal is to highlight the importance of determining the functional dependence of the stochastic instability increments and transport coefficients on turbulent pulsation amplitudes and other key parameters (characteristic pulsation frequencies, drift velocities, spectral energy flow, etc.) describing the systems under discussion.
Experimental Study of the Behavior of Confined Variable Density Jets in a Time Varying Crossflow

An experimental work and a physical analysis dedicated to the study of a low density jet subjected to a time varying crossflow with high acceleration/deceleration levels are presented in this paper. Relevant nondimensional numbers are derived and show that unsteady effects associated with the presence of the jet in the acceleration field have noticeable consequences on the flapping of the jet. The Schlieren technique is applied in the test section of a square duct to obtain time resolved images of the jet. Analysis of the results is focused on the influence of the unsteady effects on the global dynamic behaviour of the jet in the near field. The interaction between the jet and the crossflow is analysed in three contrasted situations corresponding to different values of the jet outlet velocity U0. We predict and observe an increase of the jet deflection during the acceleration phase and a competition between drag and acceleration during the deceleration. This competition is particularly clear for the two lowest ejection velocities of the jet and we have shown that the jet is initially deflected upstream the nozzle. The influence of exit jet injection angle is finally considered. We show that upstream or downstream injections induce a very strong modification of the mixing process of the jet fluid with the pulsed crossflow.
Solving the OSCAR and SLOPE Models Using a Semismooth Newton-Based Augmented Lagrangian Method

The octagonal shrinkage and clustering algorithm for regression (OSCAR), equipped with the $\ell_1$-norm and a pair-wise $\ell_{\infty}$-norm regularizer, is a useful tool for feature selection and grouping in high-dimensional data analysis. The computational challenge posed by OSCAR, for high dimensional and/or large sample size data, has not yet been well resolved due to the non-smoothness and inseparability of the regularizer involved. In this paper, we successfully resolve this numerical challenge by proposing a sparse semismooth Newton-based augmented Lagrangian method to solve the more general SLOPE (the sorted L-one penalized estimation) model. By appropriately exploiting the inherent sparse and low-rank property of the generalized Jacobian of the semismooth Newton system in the augmented Lagrangian subproblem, we show how the computational complexity can be substantially reduced. Our algorithm presents a notable advantage in the high-dimensional statistical regression settings. Numerical experiments are conducted on real data sets, and the results demonstrate that our algorithm is far superior, in both speed and robustness, than the existing state-of-the-art algorithms based on first-order iterative schemes, including the widely used accelerated proximal gradient (APG) method and the alternating direction method of multipliers (ADMM).
Analysis of Computational Algorithms for Linear Multistep Methods

Linear multistep methods (LMMs) constitute a class of time-stepping methods for the solution of initial value ODEs; the most well-known methods of this class are the Adams methods (AMs) and the backward differentiation formulae (BDFs). For the fixed stepsize LMMs there exists an extensive error and stability analysis; in practical computations, however, one always uses a variable stepsize. It is well known that the varying stepsize affects the error and stability properties of the LMMs; the analysis of variable stepsize LMMs is generally much more complicated than for the fixed stepsize methods. Due to this, many of the computational algorithms in LMM codes are based on results from analyses for fixed stepsize LMMs or onestep methods, and the purpose pf these algorithms is partly to supply operating conditions that resemble as much as possible the properties of the fixed stepsize methods. In this monograph we investigate different variable stepsize AMs and BDFs, with regard to method representation, solution of nonlinear equations, error estimation, and stepsize control. The methods are thoroughly derived and presented under a uniform taxonomy. In the error analysis the approach is to avoid premature Taylor approximations and crude norm bounds to be able to reveal some general properties of error propagation and error estimates for the different variable stepsize AMs and BDFs. The stepsize control is viewed from a control theoretical standpoint, where we, opposed to the conventional analysis, also take the errors' dependence on past stepsizes into account. The results show that the assumptions, on which the conventional strategies rely, are not always fulfilled and, furthermore, that they can yield some undesirable secondary effects. We show that the predictors may have a severe impact on the behaviour of both method and error estimation properties. This will not only affect the choice of methods and predictors, but also several stages of the computational algorithms. (Less)
Magnetotransport through a quantum wire side coupled to a quantum dot

We study the spin-dependent zero-bias conductance through a quantum wire with a single ballistic channel side coupled to a quantum dot as a function of gate voltage ${V}_{g}$, magnetic field $B$, and temperature $T$. The system is modeled with the Anderson model, solved using an interpolative approximation for moderate values of the Coulomb repulsion $U$, and within the slave-boson mean field for infinite $U$ and $T=0$. Tuning ${V}_{g}$, for large enough $B$ and small enough $T$, the system is a very efficient spin filter.
On the Design of Control Invariant Regions for Feedback Linearized Car-Like Vehicles

This letter proposes a novel procedure to design a control invariant region for feedback-linearized car-like vehicles subject to linear and steering velocity constraints. To this end, first, it is formally proved that the state-dependent input constraints acting on the feedback-linearized car model admit a worst-case circular inner approximation. Then, it is shown that such a characterization can be used to analytically design a tracking controller with an associated invariant region capable of ensuring constraints fulfillment. Finally, simulation results show the effectiveness of the proposed solution and its potential to enable the design, via control invariance, of a new class of constrained and model predictive solutions for input-constrained feedback-linearized car-like vehicles.
Classes of generalized ∗-modules

We study the class, STAR , of all ∗-modules by means of the classes, Sλ, of all ∗λ-modules, λ> 0 being a cardinal. Since STAR, equals the intersection of the decreasing chain Sλ, λ > 0, our approach ‘from above’ complements the usual approach ‘from below’ consisting in the study of quasi-progenerators and tilting modules. We present relations between categorical properties of ∗-;modules and those of ∗-modules. Answering a question of Menini, we use the solution of the Artin's problem to show that the chain Sλ,λ > No, is strictly decreasing in general.
Stochastic ontogenetic growth model

An ontogenetic growth model (OGM) for a thermodynamically closed system is generalized to satisfy both the first and second law of thermodynamics. The hypothesized stochastic ontogenetic growth model (SOGM) is shown to entail the interspecies allometry relation by explicitly averaging the basal metabolic rate and the total body mass over the steady-state probability density for the total body mass (TBM). This is the first derivation of the interspecies metabolic allometric relation from a dynamical model and the asymptotic steady-state distribution of the TBM is fit to data and shown to be inverse power law.
P-SUMMING MULTIPLICATION OPERATORS, DYADIC HARDY SPACES AND ATOMIC DECOMPOSITION

For u2 H p , 0 < p 2, with Haar expansion u = P xIhI we construc- tively determine the Pietsch measure of the 2-summing multiplication operator Mu : ' 1 ! H p ; ('I)7! X 'IxIhI: Our method yields a constructive proof of Pisier's decomposition of u2 H p juj =jxj 1 jyj and kxk 10 kyk H2 CkukHp; where X0 is Pisier's extrapolation lattice associated to H p and H 2 . Our construc- tion of the Pietsch measure for the multiplication operatorMu involves the Haar coecients of u and its atomic decomposition.
Alfvén solitons in a dense ultrarelativistic electron–positron pulsar plasma

The nonlinear propagation of Alfven waves in a hot electron-positron plasma of a pulsar magnetosphere is investigated. Spiky intense Alfven solitons are found to exist at ultrarelativistic (T Mc2) temperatures. Landau damping and three dimensional modulation perturbations of these solitons are discussed.
Plasma Effect on Radiofrequency Communications for Lifting Reentry Vehicles

The present work investigates plasma effects around two lifting hypersonic vehicles and their implications on the radiofrequency communication blackout performances during the Earth atmospheric reentry phase. In particular, the Intermediate Experimental Vehicle developed by the European Space Agency and a slender, high lift-over-drag space plane, investigated during previous studies, have been taken into account. Chemical nonequilibrium analyses have been carried out by means of a numerical code, updated with a customized chemical model comprised of several reacting species and different reaction mechanisms. Different flight conditions, including the most critical for communications, have been considered for both vehicles. The main outcomes of the study show that, for very similar freestream conditions, the slender space plane exhibits better communication capabilities when compared with the Intermediate Experimental Vehicle. Particularly, the results suggest that the Intermediate Experimental Vehicle wou.
MDou: Accelerating DouDiZhu Self-Play Learning Using Monte-Carlo Method With Minimum Split Pruning and a Single Q-Network

Artificial intelligence (AI) has demonstrated outstanding performance in some perfect- and imperfect-information games, such as Go, Atari, and Texas Hold'em. Even though AI is successful in these games with small action spaces, it does not play well in large-scale multiplayer, imperfect-information games like DouDiZhu. DouZero, a DouDizhu AI system, has recently been proposed and beaten all the existing DouDizhu AI programs. This article introduces minimum split pruning (MSP) and a single Q-network to accelerate the training of DouZero, called MDou. Our experiments show that MDou improved through self-play using limited computational ability (only a 4-core CPU and 1 GPU) and less learning time (30 days), while achieving comparable performance to DouZero.
A New Bound on Quantum Wielandt Inequality

A new bound on quantum version of Wielandt inequality for positive (not necessarily completely positive) maps has been established. Also bounds for entanglement breaking and PPT channels are put forward which are better bound than the previous bounds known. We prove that a primitive positive map <inline-formula> <tex-math notation="LaTeX">$\mathcal {E}$ </tex-math></inline-formula> acting on <inline-formula> <tex-math notation="LaTeX">$\mathcal {M}_{d}$ </tex-math></inline-formula> that satisfies the Schwarz inequality becomes strictly positive after at most <inline-formula> <tex-math notation="LaTeX">$2(d-1)^{2}$ </tex-math></inline-formula> iterations. This is to say that after <inline-formula> <tex-math notation="LaTeX">$2(d-1)^{2}$ </tex-math></inline-formula> iterations, such a map sends every positive semidefinite matrix to a positive definite one. This finding does not depend on the number of Kraus operators as the map may not admit any Kraus decomposition. The motivation of this work is to provide an answer to a question raised by Sanz-García-Wolf and Cirac in their work on quantum Wielandt bound.
Structure-Function Guided Extraction and Scale-Up of Pea Protein Isolate Production

The lack of adequate guidance and control of the extraction conditions as well as the gap between bench- and industrial-scale production, contributes to the poor functionality of commercial pea protein isolate (cPPI). Therefore, pea protein extraction conditions were evaluated and scaled up to maximize protein purity and yield, while maintaining structural integrity, following mild alkaline solubilization with isoelectric precipitation and salt solubilization coupled with membrane filtration. Both extraction methods resulted in high protein yield (>64%) and purity (>87%). Structure-function characterization illustrated the preserved structural integrity of PPI samples and their superior solubility, gelation, and emulsification properties compared to cPPI. Results confirmed, for the first time, that double solubilization at mild pH (7.5) can replace single solubilization at high alkalinity and achieve a similar yield while preserving structural integrity. Additionally, this study demonstrated, the scalability of the benchtop salt extraction coupled with ultrafiltration/diafiltration. Scaling up the production eliminated some structural and functional differences between the salt-extracted PPI and pH-extracted PPI. Scaling-up under mild and controlled conditions resulted in partial denaturation and a low degree of polymerization, coupled with the superior functionality of the produced isolates compared to cPPI. Results of this work can be used as a benchmark to guide the industrial production of functional pea protein ingredients.