Investigating the quark flavor dependence of the chiral magnetic effect with a multiphase transport model

Because the properties of the QCD phase transition and the chiral magnetic effect (CME) depend on the number of quark flavors ($N_{f}$) and quark mass, relativistic heavy-ion collisions provide a natural environment to investigate the flavor features if quark deconfinement occurs. We introduce an initial two-flavor or three-flavor dipole charge separation into a multiphase transport (AMPT) model to investigate the flavor dependence of the CME. By taking advantage of the recent ALICE data of charge azimuthal correlations with identified hadrons, we attempt to disentangle two-flavor and three-flavor CME scenarios in Pb+Pb collisions at 2.76 TeV. We find that the experimental data show a certain potential to distinguish the two scenarios, therefore we further suggest to collect more data to clarify the possible flavor dependence in future experiments.Comment: 12 pages, 4 figures; final published versio

Electronic band gaps and transport in aperiodic graphene superlattices of Thue-Morse sequence

We have studied the electronic properties in aperiodic graphene superlattices of Thue-Morse sequence. Although the structure is aperiodic, an unusual Dirac point (DP) does exist and its location is exactly at the position of the zero-averaged wave number (zero-$\bar{k})$. Furthermore, the zero-$\bar{k}$ gap associated with the DP is robust against the lattice constants and the incident angles, and multi-DPs can appear under the suitable conditions. A resultant controllability of electron transport in Thue-Morse sequence is predicted, which may facilitate the development of many graphene-based electronics.Comment: Accepted for publication in Applied Physics Letters; 4 pagese, 5 figure

APQL: A process-model query language

As business process management technology matures, organisations acquire more and more business process models. The management of the resulting collections of process models poses real challenges. One of these challenges concerns model retrieval where support should be provided for the formulation and efficient execution of business process model queries. As queries based on only structural information cannot deal with all querying requirements in practice, there should be support for queries that require knowledge of process model semantics. In this paper we formally define a process model query language that is based on semantic relationships between tasks in process models and is independent of any particular process modelling notation

Privacy Preserving Utility Mining: A Survey

In big data era, the collected data usually contains rich information and hidden knowledge. Utility-oriented pattern mining and analytics have shown a powerful ability to explore these ubiquitous data, which may be collected from various fields and applications, such as market basket analysis, retail, click-stream analysis, medical analysis, and bioinformatics. However, analysis of these data with sensitive private information raises privacy concerns. To achieve better trade-off between utility maximizing and privacy preserving, Privacy-Preserving Utility Mining (PPUM) has become a critical issue in recent years. In this paper, we provide a comprehensive overview of PPUM. We first present the background of utility mining, privacy-preserving data mining and PPUM, then introduce the related preliminaries and problem formulation of PPUM, as well as some key evaluation criteria for PPUM. In particular, we present and discuss the current state-of-the-art PPUM algorithms, as well as their advantages and deficiencies in detail. Finally, we highlight and discuss some technical challenges and open directions for future research on PPUM.Comment: 2018 IEEE International Conference on Big Data, 10 page

Distinct patterns of temporal and directional connectivity among intrinsic networks in the human brain

To determine the spatiotemporal relationships among intrinsic networks of the human brain, we recruited seven neurosurgical patients (four males and three females) who were implanted with intracranial depth electrodes. We first identified canonical resting-state networks at the individual subject level using an iterative matching procedure on each subject's resting-state fMRI data. We then introduced single electrical pulses to fMRI pre-identified nodes of the default network (DN), frontoparietal network (FPN), and salience network (SN) while recording evoked responses in other recording sites within the same networks. We found bidirectional signal flow across the three networks, albeit with distinct patterns of evoked responses within different time windows. We used a data-driven clustering approach to show that stimulation of the FPN and SN evoked a rapid (&lt;70 ms) response that was predominantly higher within the SN sites, whereas stimulation of the DN led to sustained responses in later time windows (85–200 ms). Stimulations in the medial temporal lobe components of the DN evoked relatively late effects (&gt;130 ms) in other nodes of the DN, as well as FPN and SN. Our results provide temporal information about the patterns of signal flow between intrinsic networks that provide insights into the spatiotemporal dynamics that are likely to constrain the architecture of the brain networks supporting human cognition and behavior.SIGNIFICANCE STATEMENTDespite great progress in the functional neuroimaging of the human brain, we still do not know the precise set of rules that define the patterns of temporal organization between large-scale networks of the brain. In this study, we stimulated and then recorded electrical evoked potentials within and between three large-scale networks of the brain, the default network (DN), frontoparietal network (FPN), and salience network (SN), in seven subjects undergoing invasive neurosurgery. Using a data-driven clustering approach, we observed distinct temporal and directional patterns between the three networks, with FPN and SN activity predominant in early windows and DN stimulation affecting the network in later windows. These results provide important temporal information about the interactions between brain networks supporting human cognition and behavior.</jats:p

Observation of Majorana fermions with spin selective Andreev reflection in the vortex of topological superconductor

Majorana fermion (MF) whose antiparticle is itself has been predicted in condensed matter systems. Signatures of the MFs have been reported as zero energy modes in various systems. More definitive evidences are highly desired to verify the existence of the MF. Very recently, theory has predicted MFs to induce spin selective Andreev reflection (SSAR), a novel magnetic property which can be used to detect the MFs. Here we report the first observation of the SSAR from MFs inside vortices in Bi2Te3/NbSe2 hetero-structure, in which topological superconductivity was previously established. By using spin-polarized scanning tunneling microscopy/spectroscopy (STM/STS), we show that the zero-bias peak of the tunneling differential conductance at the vortex center is substantially higher when the tip polarization and the external magnetic field are parallel than anti-parallel to each other. Such strong spin dependence of the tunneling is absent away from the vortex center, or in a conventional superconductor. The observed spin dependent tunneling effect is a direct evidence for the SSAR from MFs, fully consistent with theoretical analyses. Our work provides definitive evidences of MFs and will stimulate the MFs research on their novel physical properties, hence a step towards their statistics and application in quantum computing.Comment: 4 figures 15 page