Magnetic fluctuations and superconducting properties of CaKFe4As4 studied by 75As NMR

We report $^{75}$As nuclear magnetic resonance (NMR) studies on a new iron-based superconductor CaKFe$_4$As$_4$ with $T_{\rm c}$ = 35 K. $^{75}$As NMR spectra show two distinct lines corresponding to the As(1) and As(2) sites close to the K and Ca layers, respectively, revealing that K and Ca layers are well ordered without site inversions. We found that nuclear quadrupole frequencies $\nu_{\rm Q}$ of the As(1) and As(2) sites show an opposite temperature ($T$) dependence. Nearly $T$ independent behavior of the Knight shifts $K$ are observed in the normal state, and a sudden decrease in $K$ in the superconducting (SC) state clearly evidences spin-singlet Cooper pairs. $^{75}$As spin-lattice relaxation rates 1/$T_1$ show a power law $T$ dependence with different exponents for the two As sites. The isotropic antiferromagnetic spin fluctuations characterized by the wavevector ${\bf q}$ = ($\pi$, 0) or (0, $\pi$) in the single-iron Brillouin zone notation are revealed by 1/$T_1T$ and $K$ measurements. Such magnetic fluctuations are necessary to explain the observed temperature dependence of the $^{75}$As quadrupole frequencies, as evidenced by our first-principles calculations. In the SC state, 1/$T_1$ shows a rapid decrease below $T_{\rm c}$ without a Hebel-Slichter peak and decreases exponentially at low $T$, consistent with an $s^{\pm}$ nodeless two-gap superconductor.Comment: 9 pages, 6 figures, accepted for publication in Phys.Rev.

W boson mass in the NP models with extra U(1)U(1) gauge group

The precise measurement of the W boson mass is closely related to the contributions of new physics (NP), which can significantly constrain the parameter space of NP models, particularly those with an additional $U(1)$ local gauge group. The inclusion of a new $Z'$ gauge boson and gauge couplings in these models can contribute to the oblique parameters $S$, $T$, $U$ and W boson mass at tree level. Taking into account the effects of kinetic mixing, we calculate and analyze the oblique parameters $S$, $T$, $U$ and W boson mass in such NP models in this study. It is found that the kinetic mixing effects can make significant contributions to the W boson mass, which can satisfy the recently measured W boson mass at CDF II or ATLAS by choosing appropriate values of gauge coupling constants and extra $U(1)$ group charges of leptons or scalar doublets. In addition, if the leptonic Yukawa couplings are invariant under the extra $U(1)$ local gauge group, these contributions can be eliminated by redefining the gauge boson fields through eliminating the neutral currents involving charged leptons, even with nonzero kinetic mixing effects.Comment: 11 pages, 2 figure

Enhancement of singly and multiply strangeness in p-Pb and Pb-Pb collisions at 158A GeV/c

The idea that the reduction of the strange quark suppression in string fragmentation leads to the enhancement of strange particle yield in nucleus-nucleus collisions is applied to study the singly and multiply strange particle production in p-Pb and Pb-Pb collisions at 158A GeV/c. In this mechanism the strange quark suppression factor is related to the effective string tension, which increases in turn with the increase of the energy, of the centrality and of the mass of colliding system. The WA97 observation that the strange particle enhancement increases with the increasing of centrality and of strange quark content in multiply strange particles in Pb-Pb collisions with respect to p-Pb collisions was accounted reasonably.Comment: 8 pages, 3 PostScript figures, in Latex form. submitted to PR

Distill Gold from Massive Ores: Efficient Dataset Distillation via Critical Samples Selection

Data-efficient learning has drawn significant attention, especially given the current trend of large multi-modal models, where dataset distillation can be an effective solution. However, the dataset distillation process itself is still very inefficient. In this work, we model the distillation problem with reference to information theory. Observing that severe data redundancy exists in dataset distillation, we argue to put more emphasis on the utility of the training samples. We propose a family of methods to exploit the most valuable samples, which is validated by our comprehensive analysis of the optimal data selection. The new strategy significantly reduces the training cost and extends a variety of existing distillation algorithms to larger and more diversified datasets, e.g. in some cases only 0.04% training data is sufficient for comparable distillation performance. Moreover, our strategy consistently enhances the performance, which may open up new analyses on the dynamics of distillation and networks. Our method is able to extend the distillation algorithms to much larger-scale datasets and more heterogeneous datasets, e.g. ImageNet-1K and Kinetics-400. Our code will be made publicly available

The two-loop contributions to muon MDM in U(1)XU(1)_X SSM

The MSSM is extended to the $U(1)_X$SSM, whose local gauge group is $SU(3)_C \times SU(2)_L \times U(1)_Y \times U(1)_X$. To obtain the $U(1)_X$SSM, we add the new superfields to the MSSM, namely: three Higgs singlets $\hat{\eta},~\hat{\bar{\eta}},~\hat{S}$ and right-handed neutrinos $\hat{\nu}_i$. It can give light neutrino tiny mass at the tree level through the seesaw mechanism. The study of the contribution of the two-loop diagrams to the MDM of muon under $U(1)_X$SSM provides the possibility for us to search for new physics. In the analytical calculation of the loop diagrams (one-loop and two-loop diagrams), the effective Lagrangian method is used to derive muon MDM. Here, the considered two-loop diagrams include Barr-Zee type diagrams and rainbow type two-loop diagrams, especially Z-Z rainbow two-loop diagram is taken into account. The obtained numerical results can reach $7.4\times10^{-10}$, which can remedy the deviation between SM prediction and experimental data to some extent.Comment: 19 pages, 8 figure

Fast Learning of Temporal Action Proposal via Dense Boundary Generator

Generating temporal action proposals remains a very challenging problem, where the main issue lies in predicting precise temporal proposal boundaries and reliable action confidence in long and untrimmed real-world videos. In this paper, we propose an efficient and unified framework to generate temporal action proposals named Dense Boundary Generator (DBG), which draws inspiration from boundary-sensitive methods and implements boundary classification and action completeness regression for densely distributed proposals. In particular, the DBG consists of two modules: Temporal boundary classification (TBC) and Action-aware completeness regression (ACR). The TBC aims to provide two temporal boundary confidence maps by low-level two-stream features, while the ACR is designed to generate an action completeness score map by high-level action-aware features. Moreover, we introduce a dual stream BaseNet (DSB) to encode RGB and optical flow information, which helps to capture discriminative boundary and actionness features. Extensive experiments on popular benchmarks ActivityNet-1.3 and THUMOS14 demonstrate the superiority of DBG over the state-of-the-art proposal generator (e.g., MGG and BMN). Our code will be made available upon publication.Comment: Accepted by AAAI 2020. Ranked No. 1 on ActivityNet Challenge 2019 on Temporal Action Proposals (http://activity-net.org/challenges/2019/evaluation.html

Physicochemical, morphological and cellular uptake properties of lutein nanodispersions prepared by using surfactants with different stabilizing mechanisms

In this study, we prepared a series of lutein nanodispersions via the solvent displacement method, by using surfactants with different stabilizing mechanisms. The surfactants used include Tween 80 (steric stabilization), sodium dodecyl sulfate (SDS; electrostatic stabilization), sodium caseinate (electrosteric stabilization) and SDS–Tween 80 (electrostatic–steric stabilization). We then characterized the resulting lutein nanodispersions in terms of their particle size, particle size distribution, zeta potential, lutein content, flow behavior, apparent viscosity, transmittance, color, morphological properties and their effects on cell viability and cellular uptake. The type of surfactant used significantly (p < 0.05) affected the physical properties of the nanodispersions, but the chemical properties (lutein content) remained unaffected. Transmission electron microscopy (TEM) images obtained from this study demonstrated that the solvent displacement method was capable of producing lutein nanodispersions containing spherical particles with sizes ranging from 66.20–125.25 nm, depending on the type of surfactant used. SDS and SDS–Tween 80 surfactants negatively affected the viability of the HT-29 cells used in this study. Thus, for the cellular uptake determination, only Tween 80 and sodium caseinate surfactants were used. The cellular uptake of the lutein nanodispersion stabilized by sodium caseinate was higher than that which was stabilized by Tween 80. All things considered, the type of surfactant with different stabilizing mechanisms did produce lutein nanodispersions with different characteristics. These findings would aid in future selection of surfactants in order to produce nanodispersions with desirable properties

Halophilic Actinomycetes in 1 Saharan Soils of Algeria: Isolation, Taxonomy and Antagonistic Properties

The diversity of a population of 52 halophilic actinomycetes was evaluated by a polyphasic approach, which showed the presence of Actinopolyspora, Nocardiopsis, Saccharomonospora, Streptomonospora and Saccharopolyspora genera. One strain was considered to be a new member of the last genus and several other strains seem to be new species. Furthermore, 50% of strains were active against a broad range of indicators and contained genes encoding polyketide synthetases and nonribosomal peptide synthetases