Multivariable Scaling for the Anomalous Hall Effect

We derive a general scaling relation for the anomalous Hall effect in ferromagnetic metals involving multiple competing scattering mechanisms, described by a quadratic hypersurface in the space spanned by the partial resistivities. We also present experimental findings, which show strong deviation from previously found scaling forms when different scattering mechanism compete in strength but can be nicely explained by our theory

DPAN: Dynamic Preference-based and Attribute-aware Network for Relevant Recommendations

In e-commerce platforms, the relevant recommendation is a unique scenario providing related items for a trigger item that users are interested in. However, users' preferences for the similarity and diversity of recommendation results are dynamic and vary under different conditions. Moreover, individual item-level diversity is too coarse-grained since all recommended items are related to the trigger item. Thus, the two main challenges are to learn fine-grained representations of similarity and diversity and capture users' dynamic preferences for them under different conditions. To address these challenges, we propose a novel method called the Dynamic Preference-based and Attribute-aware Network (DPAN) for predicting Click-Through Rate (CTR) in relevant recommendations. Specifically, based on Attribute-aware Activation Values Generation (AAVG), Bi-dimensional Compression-based Re-expression (BCR) is designed to obtain similarity and diversity representations of user interests and item information. Then Shallow and Deep Union-based Fusion (SDUF) is proposed to capture users' dynamic preferences for the diverse degree of recommendation results according to various conditions. DPAN has demonstrated its effectiveness through extensive offline experiments and online A/B testing, resulting in a significant 7.62% improvement in CTR. Currently, DPAN has been successfully deployed on our e-commerce platform serving the primary traffic for relevant recommendations. The code of DPAN has been made publicly available

Evidence of the side jump mechanism in the anomalous Hall effect in paramagnets

Persistent confusion has existed between the intrinsic (Berry curvature) and the side jump mechanisms of anomalous Hall effect (AHE) in ferromagnets. We provide unambiguous identification of the side jump mechanism, in addition to the skew scattering contribution in epitaxial paramagnetic Ni$_{34}$Cu$_{66}$ thin films, in which the intrinsic contribution is by definition excluded. Furthermore, the temperature dependence of the AHE further reveals that the side jump mechanism is dominated by the elastic scattering

A Meta-Analysis of the Relationship Between Corporate Social Responsibility and Consumer Response in the Chinese Context

Consumers’ attitudes toward corporate social responsibility (CSR) and their response levels can significantly affect a firm’s behaviors. Based on 61 research papers addressing CSR responses to consumers in China, this study conducted a meta-analysis on three variables: CSR type, CSR characteristics, and CSR publicity behavior, which impact the CSR relationship. The following conclusions are drawn: Corporate social responsibility (encompassing private and public moral dimensions) elicits a positive consumer response, with private moral behavior having a greater positive effect compared to public moral behavior. The four dimensions of CSR characteristics (CSR commitment, CSR level, CSR correlation, and CSR timing) all lead to positive consumer responses. Positive consumer responses also arise from CSR publicity behavior, including publicity initiative and publicity intensity. Additionally, product type, sample time, and sample source have significant moderating effects on these relationships

Protoplast transformation as a potential platform for exploring gene function in Verticillium dahliae

Position of siRNAs along the Vta2 gene of V. dahliae. The position of different siRNAs designed to target this gene is shown in this figure. Sequence underlined with different colors shows different siRNAs. (JPG 7797 kb

Can Electromagnetic Information Theory Improve Wireless Systems? A Channel Estimation Example

Electromagnetic information theory (EIT) is an emerging interdisciplinary subject that integrates classical Maxwell electromagnetics and Shannon information theory. The goal of EIT is to uncover the information transmission mechanisms from an electromagnetic (EM) perspective in wireless systems. Existing works on EIT are mainly focused on the analysis of degrees-of-freedom (DoF), system capacity, and characteristics of the electromagnetic channel. However, these works do not clarify how EIT can improve wireless communication systems. To answer this question, in this paper, we provide a novel demonstration of the application of EIT. By integrating EM knowledge into the classical MMSE channel estimator, we observe for the first time that EIT is capable of improving the channel estimation performace. Specifically, the EM knowledge is first encoded into a spatio-temporal correlation function (STCF), which we term as the EM kernel. This EM kernel plays the role of side information to the channel estimator. Since the EM kernel takes the form of Gaussian processes (GP), we propose the EIT-based Gaussian process regression (EIT-GPR) to derive the channel estimations. In addition, since the EM kernel allows parameter tuning, we propose EM kernel learning to fit the EM kernel to channel observations. Simulation results show that the application of EIT to the channel estimator enables it to outperform traditional isotropic MMSE algorithm, thus proving the practical values of EIT.Comment: Electromagnetic information theory (EIT) is an emerging interdisciplinary subject, aiming at providing a unified analytical framework for wireless systems as well as guiding practical system design. This paper answers the question: "How can we improve wireless communication systems via EIT"