EuSn2As2 with layered rhombohedral crystal structure is proposed to be a candidate of intrinsic antiferromagnetic (AFM) topological insulator. Here, we have investigated systematic magnetoresistance (MR) and magnetization measurements on the high qua
lity EuSn2As2 single crystal with the magnetic field both parallel and perpendicular to (00l) plane. Both the kink of magnetic susceptibility and longitudinal resistivity reveal that EuSn2An2 undergoes an AFM transition at TN = 21 K. At T = 2 K, the magnetization exhibits two successive plateaus of ~ 5.6 {mu}B/Eu and ~ 6.6 {mu}B/Eu at the corresponding critical magnetic fields. Combined with the negative longitudinal MR and abnormal Hall resistance, we demonstrate that EuSn2An2 undergoes complicated magnetic transitions from an AFM state to a canted ferromagnetic (FM) state at Hc and then to a polarized FM state at Hs as the magnetic field increase.
The paper is concerned with elongating the shortest curvature-bounded path between two oriented points to an expected length. The elongation of curvature-bounded paths to an expected length is fundamentally important to plan missions for nonholonomic
-constrained vehicles in many practical applications, such as coordinating multiple nonholonomic-constrained vehicles to reach a destination simultaneously or performing a mission with a strict time window. In the paper, the explicit conditions for the existence of curvature-bounded paths joining two oriented points with an expected length are established by applying the properties of the reachability set of curvature-bounded paths. These existence conditions are numerically verifiable, allowing readily checking the existence of curvature-bounded paths between two prescribed oriented points with a desired length. In addition, once the existence conditions are met, elongation strategies are provided in the paper to get curvature-bounded paths with expected lengths. Finally, some examples of minimum-time path planning for multiple fixed-wing aerial vehicles to cooperatively achieve a triangle-shaped flight formation are presented, illustrating and verifying the developments of the paper.
Federated Learning (FL) is a newly emerged decentralized machine learning (ML) framework that combines on-device local training with server-based model synchronization to train a centralized ML model over distributed nodes. In this paper, we propose
an asynchronous FL framework with periodic aggregation to eliminate the straggler issue in FL systems. For the proposed model, we investigate several device scheduling and update aggregation policies and compare their performances when the devices have heterogeneous computation capabilities and training data distributions. From the simulation results, we conclude that the scheduling and aggregation design for asynchronous FL can be rather different from the synchronous case. For example, a norm-based significance-aware scheduling policy might not be efficient in an asynchronous FL setting, and an appropriate age-aware weighting design for the model aggregation can greatly improve the learning performance of such systems.
Competing risks data are common in medical studies, and the sub-distribution hazard (SDH) ratio is considered an appropriate measure. However, because the limitations of hazard itself are not easy to interpret clinically and because the SDH ratio is
valid only under the proportional SDH assumption, this article introduced an alternative index under competing risks, named restricted mean time lost (RMTL). Several test procedures were also constructed based on RMTL. First, we introduced the definition and estimation of RMTL based on Aalen-Johansen cumulative incidence functions. Then, we considered several combined tests based on the SDH and the RMTL difference (RMTLd). The statistical properties of the methods are evaluated using simulations and are applied to two examples. The type I errors of combined tests are close to the nominal level. All combined tests show acceptable power in all situations. In conclusion, RMTL can meaningfully summarize treatment effects for clinical decision making, and three combined tests have robust power under various conditions, which can be considered for statistical inference in real data analysis.
Many recent works have proposed methods to train classifiers with local robustness properties, which can provably eliminate classes of evasion attacks for most inputs, but not all inputs. Since data distribution shift is very common in security appli
cations, e.g., often observed for malware detection, local robustness cannot guarantee that the property holds for unseen inputs at the time of deploying the classifier. Therefore, it is more desirable to enforce global robustness properties that hold for all inputs, which is strictly stronger than local robustness. In this paper, we present a framework and tools for training classifiers that satisfy global robustness properties. We define new notions of global robustness that are more suitable for security classifiers. We design a novel booster-fixer training framework to enforce global robustness properties. We structure our classifier as an ensemble of logic rules and design a new verifier to verify the properties. In our training algorithm, the booster increases the classifiers capacity, and the fixer enforces verified global robustness properties following counterexample guided inductive synthesis. We show that we can train classifiers to satisfy different global robustness properties for three security datasets, and even multiple properties at the same time, with modest impact on the classifiers performance. For example, we train a Twitter spam account classifier to satisfy five global robustness properties, with 5.4% decrease in true positive rate, and 0.1% increase in false positive rate, compared to a baseline XGBoost model that doesnt satisfy any property.
Ferroelectric materials are spontaneous symmetry breaking systems characterized by ordered electric polarizations. Similar to its ferromagnetic counterpart, a ferroelectric domain wall can be regarded as a soft interface separating two different ferr
oelectric domains. Here we show that two bound state excitations of electric polarization (polar wave), or the vibration and breathing modes, can be hosted and propagate within the ferroelectric domain wall. Specially, the vibration polar wave has zero frequency gap, thus is constricted deeply inside ferroelectric domain wall, and can propagate even in the presence of local pinnings. The ferroelectric domain wall waveguide as demonstrated here, offers new paradigm in developing ferroelectric information processing units.
We report the transport properties of kagome superconductor CsV3Sb5 single crystals at magnetic field up to 32 T. The Shubnikov de Haas (SdH) oscillations emerge at low temperature and four frequencies of $F_{alpha}=$ 27 T, F_beta = 73 T, F_epsilon =
727 T, and F_eta = 786 T with relative small cyclotron masses are observed. For F_beta and F_epsilon, the Berry phases are close to pi, providing a clear evidence of nontrivial topological band structures of CsV3Sb5. Furthermore, combined with the angular dependence of SdH oscillations and theoretical calculations based on the undistorted structure, we have demonstrated that the Fermi surface related to F_beta is quasi-two-dimensional and can be assigned to the Dirac cone along the Gamma-K direction of Brillouin zone (BZ). The F_epsilon could be related to the Fermi surface centering at the H point of BZ. The absence of F_alpha and F_eta in theoretical calculations suggests that charge density wave transition could have an important influence on the shapes of Fermi surfaces, especially near the M and L points of BZ. These results will shed light on the nature of correlated topological physics in kagome material CsV3Sb5.
Quasi-two-dimensional kagome metals AV3Sb5 (A = K, Rb, and Cs) have attracted much recent interest due to exotic quantum phenomena such as unconventional superconductivity, topological charge order and giant anomalous Hall effect. Here we report pres
sure-induced reemergent superconductivity in CsV3Sb5 by electrical transport measurements under high pressures up to 47.9 GPa. We show that the superconducting critical temperature Tc is first enhanced by pressure and reaches its first maximum ~ 8.9 K at 0.8 GPa, then the Tc is suppressed by pressure and cannot be detected above 7.5 GPa, forming a dome-shaped superconducting phase diagram. Remarkably, upon further compression above 16.5 GPa, a new superconducting state arises, of which Tc is enhanced by pressure to a second maximum ~ 5.0 K and the reemergent superconductivity keeps robust up to 47.9 GPa. Combined with high-pressure synchrotron x-ray diffraction measurements that demonstrate the stability of the pristine hexagonal phase up to 43.1 GPa, we suggest that the reemergence of superconductivity in the V-based superconductor could be attributed to a pressure-induced Lifshitz transition.
Channel reciprocity greatly facilitates downlink precoding in time-division duplexing (TDD) multiple-input multiple-output (MIMO) communications without the need for channel state information (CSI) feedback. Recently, reconfigurable intelligent surfa
ces (RISs) emerge as a promising technology to enhance the performance of future wireless networks. However, since the artificial electromagnetic characteristics of RISs do not strictly follow the normal laws of nature, it brings up a question: does the channel reciprocity hold in RIS-assisted TDD wireless networks? After briefly reviewing the reciprocity theorem, in this article, we show that there still exists channel reciprocity for RIS-assisted wireless networks satisfying certain conditions. We also experimentally demonstrate the reciprocity at the sub-6 GHz and the millimeter-wave frequency bands by using two fabricated RISs. Furthermore, we introduce several RIS-assisted approaches to realizing nonreciprocal channels. Finally, potential opportunities brought by reciprocal/nonreciprocal RISs and future research directions are outlined.
With the popularity of online access in virtual reality (VR) devices, it will become important to investigate exclusive and interactive CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) designs for VR devices. In th
is paper, we first present four traditional two-dimensional (2D) CAPTCHAs (i.e., text-based, image-rotated, image-puzzled, and image-selected CAPTCHAs) in VR. Then, based on the three-dimensional (3D) interaction characteristics of VR devices, we propose two vrCAPTCHA design prototypes (i.e., task-driven and bodily motion-based CAPTCHAs). We conducted a user study with six participants for exploring the feasibility of our two vrCAPTCHAs and traditional CAPTCHAs in VR. We believe that our two vrCAPTCHAs can be an inspiration for the further design of CAPTCHAs in VR.
