Vector-Valued Entire Functions of Several Variables: Some Local Properties

The present paper is devoted to the properties of entire vector-valued functions of bounded L-index in join variables, where L:Cn→R+n is a positive continuous function. For vector-valued functions from this class we prove some propositions describing their local properties. In particular, these functions possess the property that maximum of norm for some partial derivative at a skeleton of polydisc does not exceed norm of the derivative at the center of polydisc multiplied by some constant. The converse proposition is also true if the described inequality is satisfied for derivative in each variable.

Multiscale Modelling and Characterization of Mechanical Properties in Heat-Resistant Alloys

Various heat-resistant alloys have been used in industry; however, the bridge between the bulk mechanical properties and the underlying micro- and nanoscopic local properties remains an issue [...]

Protein complexes detection based on node local properties and gene expression in PPI weighted networks

Background Identifying protein complexes from protein–protein interaction (PPI) networks is a crucial task, and many related algorithms have been developed. Most algorithms usually employ direct neighbors of nodes and ignore resource allocation and second-order neighbors. The effective use of such information is crucial to protein complex detection. Result Based on this observation, we propose a new way by combining node resource allocation and gene expression information to weight protein network (NRAGE-WPN), in which protein complexes are detected based on core-attachment and second-order neighbors. Conclusions Through comparison with eleven methods in Yeast and Human PPI network, the experimental results demonstrate that this algorithm not only performs better than other methods on 75% in terms of f-measure+, but also can achieve an ideal overall performance in terms of a composite score consisting of five performance measures. This identification method is simple and can accurately identify more complexes.

Automatic Text Summarization by Providing Coverage, Non-Redundancy, and Novelty Using Sentence Graph

The day-to-day growth of online information necessitates intensive research in automatic text summarization (ATS). The ATS software produces summary text by extracting important information from the original text. With the help of summaries, users can easily read and understand the documents of interest. Most of the approaches for ATS used only local properties of text. Moreover, the numerous properties make the sentence selection difficult and complicated. So this article uses a graph based summarization to utilize structural and global properties of text. It introduces maximal clique based sentence selection (MCBSS) algorithm to select important and non-redundant sentences that cover all concepts of the input text for summary. The MCBSS algorithm finds novel information using maximal cliques (MCs). The experimental results of recall oriented understudy for gisting evaluation (ROUGE) on Timeline dataset show that the proposed work outperforms the existing graph algorithms Bushy Path (BP), Aggregate Similarity (AS), and TextRank (TR).

Experimental evidence of non-classical brain functions

Exploring unknown quantum systems is an experimental challenge. Recent proposals exploring quantum gravity have suggested circumventing this problem by considering the unknown system as a mediator between two known systems. If such a mediation can locally generate entanglement in the known systems, then the mediator must be non-classical. The same approach may be applicable to other systems, in particular the brain, where speculations about quantum operations in consciousness and cognition have a long history. Translated to the brain, the mediator is then an unknown brain function. For the quantum systems, we could use proton spins of bulk water, which most likely interfere with the any brain function. Entanglement in these spins can be witnessed with multiple quantum coherence (MQC). We based our witness protocol on zero quantum coherence (ZQC) whereby potential signals from local properties were minimised. For short repetitive periods, we found ZQC signals in large parts of the brain, whereby the temporal appearance resembled heartbeat-evoked potentials (HEPs). Similar to HEPs, we also found that the ZQC signal depended on conscious awareness. Consciousness-related signals have, to our knowledge, not yet been reported in NMR. Remarkably, we could exclude local properties as contrast mechanism because (a) the ZQC signals had no correlates known in conventional MRI, and (b) the ZQC signals only appeared if the local properties of the magnetisation, which are complementary to non-local properties, were reduced. Our findings suggest that we may have witnessed entanglement mediated by consciousness-related brain functions. Those brain functions must then operate non-classically, which would mean that consciousness is non-classical.

High Sensitivity Electrical Properties Measurement of Graphene-based Composites using Interferometric Near-field Microwave Technique

High sensitivity electrical properties measurement of composite materials using an interferometric near-field microwave technique is proposed in this paper. A one-port calibration model is developed to relate the measured transmission coefficient to the local properties of the material. To represent the probe-composite sample interaction, an electrical model based on lumped elements is developed. As a demonstration, complex permittivity and conductivity of composite materials prepared with polyvinyl chloride (PVC) and different concentration of graphene are experimentally determined at 2.45 GHz. The obtained results show that the proposed technique is sensitive for the detection of small contrast of permittivity and conductivity in composite material. When graphene concentration increases from 1 to 30%, the conductivity increases from 0.0061 s/m to 0.056 s/m.

Post-selected double teleportation and the modelling of its related non-local properties

Quantum teleportation is a notable basement of quantum processing. It has been experimentally tested with outstanding growing success by introducing improvements and applied advances in the last two decades. Its quantum non-local properties have let to discover and introduce novel implementations based on it in quantum processing, cryptography, quantum resources generation among others. In the current work, we develop a scheme performing double teleportation on two different virtual receivers, while the sender is still able to post-select the final target of teleportation. This process can be then used to generate non-local resources in a coordinated way. Those resources can be transferred to one of the receivers in the form of the non-local resource desired. They are analysed in terms of their parametric behavior, and properties derived from the CHSH inequality.