Decoupling anomaly discrimination and representation learning: self-supervised learning for anomaly detection on attributed graph

Anomaly detection on attributed graphs is a crucial topic for its practical application. Existing methods suffer from semantic mixture and imbalance issue because they mainly focus on anomaly discrimination, ignoring representation learning. It conflicts with the assortativity assumption that anomalous nodes commonly connect with normal nodes directly. Additionally, there are far fewer anomalous nodes than normal nodes, indicating a long-tailed data distribution. To address these challenges, a unique algorithm,Decoupled Self-supervised Learning forAnomalyDetection (DSLAD), is proposed in this paper. DSLAD is a self-supervised method with anomaly discrimination and representation learning decoupled for anomaly detection. DSLAD employs bilinear pooling and masked autoencoder as the anomaly discriminators. By decoupling anomaly discrimination and representation learning, a balanced feature space is constructed, in which nodes are more semantically discriminative, as well as imbalance issue can be resolved. Experiments conducted on various six benchmark datasets reveal the effectiveness of DSLAD

Realization of exceptional points along a synthetic orbital angular momentum dimension

Exceptional points (EPs), at which more than one eigenvalue and eigenvector coalesce, are unique spectral features of Non-Hermiticity (NH) systems. They exist widely in open systems with complex energy spectra. We experimentally demonstrate the appearance of paired EPs in a periodical driven degenerate optical cavity along the synthetic orbital angular momentum (OAM) dimension with a tunable parameter. The complex-energy band structures and the key features of EPs, i.e. their Fermi arcs, parity-time symmetry breaking transition, energy swapping, and half-integer band windings are directly observed by detecting the cavity's transmission spectrum. Our results advance the fundamental understanding of NH physics and demonstrate the flexibility of using the photonic synthetic dimensions to implement NH systems

An In Vivo Mouse Model of Long-Term Potentiation at Synapses between Primary Afferent C-Fibers and Spinal Dorsal Horn Neurons: Essential Role of Ephb1 Receptor

Abstract Background Long-term potentiation (LTP), a much studied cellular model of synaptic plasticity, has not been demonstrated at synapses between primary afferent C-fibers and spinal dorsal horn (DH) neurons in mice in vivo. EphrinB-EphB receptor signaling plays important roles in synaptic connection and plasticity in the nervous system, but its role in spinal synaptic plasticity remains unclear. Results This study characterizes properties of LTP at synapses of C-fibers onto neurons in the superficial DH following high-frequency stimulation (HFS) of a peripheral nerve at an intensity that activates C-fibers and examines associated activation of Ca2+/calmodulin-activated protein kinase II (p-CaMKII), extracellular signal-regulated kinase (p-ERK) and the cyclic AMP response element binding protein (p-CREB) and expression of c-Fos, and it investigates further roles for the EphB1 receptor in LTP. HFS induced LTP within 5 min and lasts for 3–8 h during the period of recording and resulted in upregulation of p-CaMKII, p-ERK and p-CREB protein levels in the spinal cord and expression of c-Fos in DH. Intrathecal pretreatment of MK-801 or EphB2-Fc prevented LTP and significantly reduced upregulation of p-CaMKII, p-ERK, p-CREB and c-Fos. Further, targeted mutation of EphB1 receptor prevented induction of LTP and associated increases in phosphorylation of CaMKII, ERK, and CREB. Conclusion This study provides an in vivo mouse model of LTP at synapses of C-fibers onto the superficial DH neurons that will be valuable for studying the DH neuron excitability and their synaptic plasticity and hyperalgesia. It further takes advantage of examining functional implications of a specific gene targeted mice and demonstrates that the EphB1 receptor is essential for development of LTP.</p

Filtering one-way Einstein-Podolsky-Rosen steering

Einstein-Podolsky-Rosen (EPR) steering, a fundamental concept of quantum nonlocality, describes one observer's capability to remotely affect another distant observer's state by local measurements. Unlike quantum entanglement and Bell nonlocality, both associated with the symmetric quantum correlation, EPR steering depicts the unique asymmetric property of quantum nonlocality. With the local filter operation in which some system components are discarded, quantum nonlocality can be distilled to enhance the nonlocal correlation, and even the hidden nonlocality can be activated. However, asymmetric quantum nonlocality in the filter operation still lacks a well-rounded investigation, especially considering the discarded parts where quantum nonlocal correlations may still exist with probabilities. Here, in both theory and experiment, we investigate the effect of the local filter on EPR steering. We observe all configurations of EPR steering simultaneously and other intriguing evolution of asymmetric quantum nonlocality, such as reversing the direction of one-way EPR steering. This work provides a complementary perspective to understand the asymmetric quantum nonlocality and demonstrates a practical toolbox for manipulating asymmetric quantum systems with significant potential applications in quantum information tasks.Comment: 11pages, 7figure