Roles of heating and helicity in ultrafast all-optical magnetization switching in TbFeCo

Using the time-resolved magneto-optical Kerr effect method, helicity dependent all-optical magne- tization switching (HD-AOS) is observed in ferrimagnetic TbFeCo films. Our results reveal the individual roles of the thermal and nonthermal effects after a single circularly polarized laser pulse. The evolution of this ultrafast switching occurs over different time scales, and a defined magnetization reversal time of 460 fs is shown—the fastest ever observed. Micromagnetic simulations based on a single macro-spin model, taking into account both heating and the inverse Faraday effect, are performed which reproduce HDAOS demonstrating a linear path for magnetization reversal

A genome-wide association study of anorexia nervosa suggests a risk locus implicated in dysregulated leptin signaling

J. Kaprio, A. Palotie, A. Raevuori-Helkamaa ja S. Ripatti ovat työryhmän Eating Disorders Working Group of the Psychiatric Genomics Consortium jäseniä. Erratum in: Sci Rep. 2017 Aug 21;7(1):8379, doi: 10.1038/s41598-017-06409-3We conducted a genome-wide association study (GWAS) of anorexia nervosa (AN) using a stringently defined phenotype. Analysis of phenotypic variability led to the identification of a specific genetic risk factor that approached genome-wide significance (rs929626 in EBF1 (Early B-Cell Factor 1); P = 2.04 x 10(-7); OR = 0.7; 95% confidence interval (CI) = 0.61-0.8) with independent replication (P = 0.04), suggesting a variant-mediated dysregulation of leptin signaling may play a role in AN. Multiple SNPs in LD with the variant support the nominal association. This demonstrates that although the clinical and etiologic heterogeneity of AN is universally recognized, further careful sub-typing of cases may provide more precise genomic signals. In this study, through a refinement of the phenotype spectrum of AN, we present a replicable GWAS signal that is nominally associated with AN, highlighting a potentially important candidate locus for further investigation.Peer reviewe

Explore the potential of deep learning and hyperchaotic map in the meaningful visual image encryption scheme

Abstract In recent years, meaningful visual image encryption schemes that the plain image is compressed and encrypted and then hidden into the carrier image have received increasing attention. This paper proposes a new meaningful visual image encryption scheme, which consists of three stages: compression (compression network)—encryption (2D‐SLC hyperchaotic map)—hiding (matrix encoding). First, the advantages of deep learning are explored. It can compress the width, height, channel, and pixel values of the plain image simultaneously. Second, a new 2D‐SLC hyperchaotic map is designed to ensure security. It has a larger chaotic space and better randomness. Finally, to obtain a high‐quality cipher image, the secure secret image is hidden in the grey carrier image by matrix encoding. The scheme can compress and encrypt the grey or colour plain image and then hide it in a grey carrier image. In addition, the theoretical peak signal‐to‐noise ratio (PSNR) between the cipher image and the carrier image is improved from 40.9292 to 42.1785 dB. The total running time is only about 0.35, 0.87 and 3.1 s for a 256 × 256, 512 × 512 and 1024 × 1024 grey or colour plain image, respectively

Research on Vibration Behavior of the Plate-Like Joint Interfaces Based on Comprehensive Unit Stiffness Matrix

Abstract: The dynamic characteristics of joint interfaces have significant effect on both static and dynamic behaviors of the whole machine tool structures. Its dynamic model can be simplified as a group of equivalent spring-damping elements, that is, an ‘elastic interlayer ’ without mass. The unit area dynamic characteristic parameters are the key to analyze the dynamic properties of joint interfaces. However, when building the stiffness and damping matrices of the joint interfaces, the interaction between the ‘elastic interlayer ’ and the conjunctions are always ignored, which leads to errors arising. A test system for identifying the unit area dynamic characteristic parameters of different kinds of joint interfaces are represented based on Equivalent Single Degree Of Freedom (ESDOF) system theory. The unit area dynamic characteristic parameters can be applied under all kinds of conditions (including different materials, pre-tightening force, surface roughness, lubricating conditions, media, etc). Then a comprehensive unit stiffness matrix is derived from these parameters. The presented method is compared with the conventional method on analyzing the vibration behavior of an assembled beam structure. The comparison results show that the presented method is in excellent agreement on the actual conditions, which has an obvious advantage on accuracy. The presented method can be used as an effective way for precisely analyzing vibration behavior of complicated mechanical structures with plate-like joint interfaces. Copyright © 2014 IFSA Publishing, S. L

From Replay to Regeneration: Recovery of UDP Flood Network Attack Scenario Based on SDN

In recent years, various network attacks have emerged. These attacks are often recorded in the form of Pcap data, which contains many attack details and characteristics that cannot be analyzed through traditional methods alone. Therefore, restoring the network attack scenario through scene reconstruction to achieve data regeneration has become an important entry point for detecting and defending against network attacks. However, current network attack scenarios mainly reproduce the attacker’s attack steps by building a sequence collection of attack scenarios, constructing an attack behavior diagram, or simply replaying the captured network traffic. These methods still have shortcomings in terms of traffic regeneration. To address this limitation, this paper proposes an SDN-based network attack scenario recovery method. By parsing Pcap data and utilizing network topology reconstruction, probability, and packet sequence models, network traffic data can be regenerated. The experimental results show that the proposed method is closer to the real network, with a higher similarity between the reconstructed and actual attack scenarios. Additionally, this method allows for adjusting the intensity of the network attack and the generated topology nodes, which helps network defenders better understand the attackers’ posture and analyze and formulate corresponding security strategies