Isospin dependence of projectile-like fragment production at intermediate energies

The cross sections of fragments produced in 140 $A$ MeV $^{40,48}$Ca + $^9$Be and $^{58,64}$Ni + $^9$Be reactions are calculated by the statistical abration-ablation(SAA) model and compared to the experimental results measured at the National Superconducting Cyclotron Laboratory (NSCL) at Michigan State University. The fragment isotopic and isotonic cross section distributions of $^{40}$Ca and $^{48}$Ca, $^{58}$Ni and $^{64}$Ni, $^{40}$Ca and $^{58}$Ni, and $^{48}$Ca and $^{64}$Ni are compared and the isospin dependence of the projectile fragmentation is studied. It is found that the isospin dependence decreases and disappears in the central collisions. The shapes of the fragment isotopic and isotonic cross section distributions are found to be very similar for symmetric projectile nuclei. The shapes of the fragment isotopic and isotonic distributions of different asymmetric projectiles produced in peripheral reactions are found very similar. The similarity of the distributions are related to the similar proton and neutron density distributions inside the nucleus in framework of the SAA model.Comment: 7 pages, 4 figures; to be published in Phys Rev

Animalization of Industrial Structure Transformation on Economic Growth in Liaoning’s Province

Industrial structure and economic growth are independent. Based on the new statistical figures of Liaoning, this paper analyzes the contribution of industrial structure to economic growth of Liaoning Province with econometrics method. Then put forward some suggestions.Key words: Industrial structure; Theory of grey system; Economic growt

Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples

There is a growing interest in developing unlearnable examples (UEs) against visual privacy leaks on the Internet. UEs are training samples added with invisible but unlearnable noise, which have been found can prevent unauthorized training of machine learning models. UEs typically are generated via a bilevel optimization framework with a surrogate model to remove (minimize) errors from the original samples, and then applied to protect the data against unknown target models. However, existing UE generation methods all rely on an ideal assumption called label-consistency, where the hackers and protectors are assumed to hold the same label for a given sample. In this work, we propose and promote a more practical label-agnostic setting, where the hackers may exploit the protected data quite differently from the protectors. E.g., a m-class unlearnable dataset held by the protector may be exploited by the hacker as a n-class dataset. Existing UE generation methods are rendered ineffective in this challenging setting. To tackle this challenge, we present a novel technique called Unlearnable Clusters (UCs) to generate label-agnostic unlearnable examples with cluster-wise perturbations. Furthermore, we propose to leverage VisionandLanguage Pre-trained Models (VLPMs) like CLIP as the surrogate model to improve the transferability of the crafted UCs to diverse domains. We empirically verify the effectiveness of our proposed approach under a variety of settings with different datasets, target models, and even commercial platforms Microsoft Azure and Baidu PaddlePaddle. Code is available at \url{https://github.com/jiamingzhang94/Unlearnable-Clusters}.Comment: CVPR202

Biodynamic features Syuantszy Chzhuanti 720°.

Presents the internal parameters and image Syuantszy Chzhuanti 720 ° is shown that in the implementation of the element Syuantszy Chzhuanti 720 °, the center of gravity shifts to 2.94 pm, 1.71 m. and 1.22 m. on the X, Y and Z; rate varies according to X - with 4,22 m/s to 0, Y - to 2,42 m/s to 0, and Z - from 3.68 m/s to 3.86 m/s. Run-time item 1.4 seconds: the first turnover - 0.41 sec., The second turnover-0, 33 sec. At the end of the takeoff run strike force left and right foot of 1147.2 N and 1005 N. Pressing the second, third, fourth, fifth finger and part of the metatarsal of right foot maximum intensity of pressure - 146.1 N; when pressing the first finger and part of the metatarsal maximum intensity of pressure - 280.8 N. The dependence of convergence or remove body parts with a vertical axis of the torque to increase or decrease its speed

Machine learning method for 12^{12}C event classification and reconstruction in the active target time-projection chamber

Active target time projection chambers are important tools in low energy radioactive ion beams or gamma rays related researches. In this work, we present the application of machine learning methods to the analysis of data obtained from an active target time projection chamber. Specifically, we investigate the effectiveness of Visual Geometry Group (VGG) and the Residual neural Network (ResNet) models for event classification and reconstruction in decays from the excited $2^+_2$ state in $^{12}$C Hoyle rotation band. The results show that machine learning methods are effective in identifying $^{12}$C events from the background noise, with ResNet-34 achieving an impressive precision of 0.99 on simulation data, and the best performing event reconstruction model ResNet-18 providing an energy resolution of $\sigma_E<77$ keV and an angular reconstruction deviation of $\sigma_{\theta}<0.1$ rad. The promising results suggest that the ResNet model trained on Monte Carlo samples could be used for future classifying and predicting experimental data in active target time projection chambers related experiments.Comment: 9 pages, 10 figures, 9 table

Detection of limited-energy α particles using CR-39 in laser-induced p −11B reaction

Due to the harsh radiation environment produced by strong laser plasma, most of the detectors based on semiconductors cannot perform well. So, it is important to develop new detecting techniques with higher detection thresholds and highly charged particle resolution for investigating nuclear fusion reactions in laser-plasma environments. The Columbia Resin No. 39 (CR-39) detector is mainly sensitive to ions and insensitive to the backgrounds, such as electrons and photons. The detector has been widely used to detect charged particles in laser-plasma environments. In this work, we used a potassium–ethanol–water (PEW) etching solution to reduce the proton sensitivity of CR-39, by raising the detection threshold for the research of laser-induced 11B(p, α)2α reaction. We calibrated the 3–5 MeV α particles in an etching condition of 60°C PEW-25 solution (17% KOH + 25%C2H5OH + 58%H2O) and compared them with the manufacturer’s recommended etching conditions of 6.25 N NaOH aqueous solution at 98°C in our laser-induced nuclear reaction experiment. The results indicate, with the PEW-25 solution, that CR-39 is more suitable to distinguish α tracks from the proton background in our experiment. We also present a method to estimate the minimum detection range of α energy on specific etching conditions in our experiment

Two-Particle Angular Correlations in pp and p -Pb Collisions at Energies Available at the CERN Large Hadron Collider From a Multiphase Transport Model

We apply a multi-phase transport (AMPT) model to study two-particle angular correlations in $pp$ collisions at $\sqrt{s}= 7$ TeV. Besides being able to describe the angular correlation functions of meson-meson pairs, a large improvement for the angular correlations of baryon-baryon and antibaryon-antibaryon is achieved. We further find that the AMPT model with new quark coalescence provides an even better description on the anti-correlation feature of baryon-baryon correlations observed in the experiments. We also extend the study to p-Pb collisions at $\sqrt{s}= 5.02$ TeV and obtained similar results. These results help us better understand the particle production mechanism in $pp$ and p-Pb collisions at LHC energies.Comment: 12 pages, 9 figures, submit for publicatio