Multi-copy and stochastic transformation of multipartite pure states

Characterizing the transformation and classification of multipartite entangled states is a basic problem in quantum information. We study the problem under two most common environments, local operations and classical communications (LOCC), stochastic LOCC and two more general environments, multi-copy LOCC (MCLOCC) and multi-copy SLOCC (MCSLOCC). We show that two transformable multipartite states under LOCC or SLOCC are also transformable under MCLOCC and MCSLOCC. What's more, these two environments are equivalent in the sense that two transformable states under MCLOCC are also transformable under MCSLOCC, and vice versa. Based on these environments we classify the multipartite pure states into a few inequivalent sets and orbits, between which we build the partial order to decide their transformation. In particular, we investigate the structure of SLOCC-equivalent states in terms of tensor rank, which is known as the generalized Schmidt rank. Given the tensor rank, we show that GHZ states can be used to generate all states with a smaller or equivalent tensor rank under SLOCC, and all reduced separable states with a cardinality smaller or equivalent than the tensor rank under LOCC. Using these concepts, we extended the concept of "maximally entangled state" in the multi-partite system.Comment: 8 pages, 1 figure, revised version according to colleagues' comment

Suppression of steady-state, but not stimulus-induced NF-kappaB activity inhibits alphavirus-induced apoptosis.

Recent studies have established cell type- specific, proapoptotic, or antiapoptotic functions for the transcription factor NF-kappaB. In each of these studies, inhibitors of NF-kappaB activity have been present before the apoptotic stimulus, and so the role of stimulus- induced NF-kappaB activation in enhancing or inhibiting survival could not be directly assessed. Sindbis virus, an alphavirus, induces NF-kappaB activation and apoptosis in cultured cell lines. To address whether Sindbis virus- induced NF-kappaB activation is required for apoptosis, we used a chimeric Sindbis virus that expresses a superrepressor of NF-kappaB activity. Complete suppression of virus-induced NF-kappaB activity neither prevents nor potentiates Sindbis virus-induced apoptosis. In contrast, inhibition of NF-kappaB activity before infection inhibits Sindbis virus-induced apoptosis. Our results demonstrate that suppression of steady-state, but not stimulus-induced NF-kappaB activity, regulates expression of gene products required for Sindbis virus-induced death. Furthermore, we show that in the same cell line, NF-kappaB can be proapoptotic or antiapoptotic depending on the death stimulus. We propose that the role of NF-kappaB in regulating apoptosis is determined by the death stimulus and by the timing of modulating NF-kappaB activity relative to the death stimulus

A quantitative comparison of in-line coating thickness distributions obtained from a pharmaceutical tablet mixing process using discrete element method and terahertz pulsed imaging

The application of terahertz pulsed imaging (TPI) in the in-line configuration to monitor the coating thickness distribution of pharmaceutical tablets has the potential to improve the performance and quality of the spray coating process. In this study, an in-line TPI method is used to measure coating thickness distributions on pre-coated tablets during mixing in a rotating pan, and compared with results obtained numerically using the discrete element method (DEM) combined with a ray-tracing technique. The hit rates (i.e. the number of successful coating thickness measurements per minute) obtained from both terahertz in-line experiments and the DEM/ray-tracing simulations are in good agreement, and both increase with the number of baffles in the mixing pan. We demonstrate that the coating thickness variability as determined from the ray-traced data and the terahertz in-line measurements represents mainly the intra-tablet variability due to relatively uniform mean coating thickness across tablets. The mean coating thickness of the ray-traced data from the numerical simulations agrees well with the mean coating thickness as determined by the off-line TPI measurements. The mean coating thickness of in-line TPI measurements is slightly higher than that of off-line measurements. This discrepancy can be corrected based on the cap-to-band surface area ratio of the tablet and the cap-to-band sampling ratio obtained from ray-tracing simulations: the corrected mean coating thickness of the in-line TPI measurements shows a better agreement with that of off-line measurements

SECaps: A Sequence Enhanced Capsule Model for Charge Prediction

Automatic charge prediction aims to predict appropriate final charges according to the fact descriptions for a given criminal case. Automatic charge prediction plays a critical role in assisting judges and lawyers to improve the efficiency of legal decisions, and thus has received much attention. Nevertheless, most existing works on automatic charge prediction perform adequately on high-frequency charges but are not yet capable of predicting few-shot charges with limited cases. In this paper, we propose a Sequence Enhanced Capsule model, dubbed as SECaps model, to relieve this problem. Specifically, following the work of capsule networks, we propose the seq-caps layer, which considers sequence information and spatial information of legal texts simultaneously. Then we design a attention residual unit, which provides auxiliary information for charge prediction. In addition, our SECaps model introduces focal loss, which relieves the problem of imbalanced charges. Comparing the state-of-the-art methods, our SECaps model obtains 4.5% and 6.4% absolutely considerable improvements under Macro F1 in Criminal-S and Criminal-L respectively. The experimental results consistently demonstrate the superiorities and competitiveness of our proposed model.Comment: 13 pages, 3figures, 5 table

OMARS: The Framework of an Online Multi-Dimensional Association Rules Mining System

Recently, the integration of data warehouses and data mining has been recognized as the primary platform for facilitating knowledge discovery. Effective data mining from data warehouses, however, needs exploratory data analysis. The users often need to investigate the warehousing data from various perspectives and analyze them at different levels of abstraction. To this end, comprehensive information processing and data analysis have to be systematically constructed surrounding data warehouses, and an on-line mining environment should be provided. In this paper, we propose a system framework to facilitate on-line association rules mining, called OMARS, which is based on the idea of integrating OLAP service and our proposed OLAM cubes and auxiliary cubes. According to the concept of OLAM cubes, we define the OLAM lattice framework that exploit arbitrary hierarchies of dimensions to model all possible OLAM data cubes

Hepatic fibrogenesis requires sympathetic neurotransmitters

Background and aims: Hepatic stellate cells (HSC) are activated by liver injury to become proliferative fibrogenic myofibroblasts. This process may be regulated by the sympathetic nervous system (SNS) but the mechanisms involved are unclear. Methods: We studied cultured HSC and intact mice with liver injury to test the hypothesis that HSC respond to and produce SNS neurotransmitters to promote fibrogenesis. Results: HSC expressed adrenoceptors, catecholamine biosynthetic enzymes, released norepinephrine (NE), and were growth inhibited by α- and β-adrenoceptor antagonists. HSC from dopamine β-hydroxylase deficient (Dbh(−/−)) mice, which cannot make NE, grew poorly in culture and were rescued by NE. Inhibitor studies demonstrated that this effect was mediated via G protein coupled adrenoceptors, mitogen activated kinases, and phosphatidylinositol 3-kinase. Injury related fibrogenic responses were inhibited in Dbh(−/−) mice, as evidenced by reduced hepatic accumulation of α-smooth muscle actin(+ve) HSC and decreased induction of transforming growth factor β1 (TGF-β1) and collagen. Treatment with isoprenaline rescued HSC activation. HSC were also reduced in leptin deficient ob/ob mice which have reduced NE levels and are resistant to hepatic fibrosis. Treating ob/ob mice with NE induced HSC proliferation, upregulated hepatic TGF-β1 and collagen, and increased liver fibrosis. Conclusions: HSC are hepatic neuroglia that produce and respond to SNS neurotransmitters to promote hepatic fibrosis

Statistical methods for imaging genetic data

More and more large-scale imaging genetic studies are being widely conducted to collect a rich set of imaging, genetic, and clinical data in order to detect susceptibility genes for complexly inherited diseases including common mental disorders (e.g., schizophrenia) and neurodegenerative disorders, among many others. However, the development of statistical and computational methods for the joint analysis of complex imaging phenotypes, genetic data, and clinical data has fallen seriously behind the technological advances. The aim this work is to develop three statistical approaches called Projection Regression Method (PRM) and functional mixed effects model (FMEM) for the joint analysis of high-dimensional imaging data with a set of genetic markers. In PRM, it generalizes a statistical method based on the principal component of heritability for association analysis in genetic studies of complex multivariate phenotypes. The key components of the PRM include an estimation procedure for extracting several principal directions of multivariate phenotypes relating to covariates and a test procedure based on wild-bootstrap method for testing for the association between the weighted multivariate phenotype and explanatory variables. Simulation studies and an imaging genetic dataset are used to examine the finite sample performance of the PRM. In FMEM, to accommodate the correlation structure of the marker set, we model the genetic effects as population-shared random effects with a common variance component (VC), whereas to accommodate spatial feature in imaging data, we spatially model varying associations between imaging measures in a three-dimensional (3D) volume (or 2D surface) with a set of covariates and the genetic random effects. We develop a two-stage estimation procedure to spatially and adaptively estimate the varying coefficient functions, while preserving its edges among different piecewise-smooth regions. To test hypothesis of interest, we provide two test statistics with well-controlled type I error and better power comparing to traditional voxel-based approach. Simulation studies and a real data analysis of the Alzheimer's Disease Neuroimage Initiative (ADNI) show that FMEM significantly outperforms voxel-based approaches in terms of identification of activation regions.Doctor of Philosoph

An intra-vehicular wireless sensor network based on Android mobile devices and bluetooth low energy

This chapter presents the development and test of an intra-vehicular wireless sensor network (IVWSN), based on Bluetooth Low Energy (BLE), designed to present to the driver, in real-time, information collected from multiple sensors distributed inside of the car, using a human-machine interface (HMI) implemented on an Android smartphone. The architecture of the implemented BLE network is composed by the smartphone, which has the role of central station, and two BLE modules (peripheral stations) based on the CC2540 system-on-chip (SoC), which collect relevant sensor information from the battery system and the traction system of a plug-in electric car. Results based on an experimental performance evaluation of the wireless network show that the network is able to satisfy the application requirements, as long as the network parameters are properly configured taking into account the peculiarities of the BLE data transfer modes and the observed limitations of the BLE platform used in the implementation of the IVWSN.This work is supported by FCT with the reference project UID/EEA/04436/2013, COMPETE 2020 with the code POCI-01-0145-FEDER-006941