21,533 research outputs found

    Ferrimagnetism in the organic polymeric Hubbard model: Quantum Monte Carlo simulation

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    The ground-state properties of organic polymers are studied by means of the quantum Monte Carlo simulation. The polymer doped by transition-metal impurities at every other radical site of the chain is described by the quasi-one-dimensional polymeric Hubbard chain. The topological structure of the chain possesses a flat-band structure of the energy band. The spin-spin correlation function and the static magnetic susceptibility are investigated in the case of half filling. Our analysis shows that the on-site Coulomb repulsions in the chain and/or in the radical lead to the coexistence of ferromagnetic and antiferromagnetic order, i.e., the ferrimagnetic order. The on-site Coulomb repulsion (U d) of electrons at the radicals plays a more significant role in stabilizing the ferromagnetic order than that (U) on the chain does, while U has a stronger impact on the antiferromagnetic order. © 1999 The American Physical Society.published_or_final_versio

    Berry phase and its induced charge and spin currents in a ring of a double-exchange system

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    A ring of double-exchange system is investigated to explore the Berry phase acquired by the interplay of localized and conduction electrons. The competition between the double-exchange ferromagnetism and the superexchange antiferromagnetic coupling from the localized electrons leads to a phase transition from a ferromagnetic state to a spin spiral state. The spin spiral state acquires a nonzero Berry phase along the ring, and induces both charge and spin currents simultaneously. It is predicted that both the Aharonov-Bohm effect and Aharonov-Cashier effect will be exhibited spontaneously in the system. © 1999 The American Physical Society.published_or_final_versio

    Jet Trimming

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    Initial state radiation, multiple interactions, and event pileup can contaminate jets and degrade event reconstruction. Here we introduce a procedure, jet trimming, designed to mitigate these sources of contamination in jets initiated by light partons. This procedure is complimentary to existing methods developed for boosted heavy particles. We find that jet trimming can achieve significant improvements in event reconstruction, especially at high energy/luminosity hadron colliders like the LHC.Comment: 20 pages, 11 figures, 3 tables - Minor changes to text/figure

    Keyword-Based Delegable Proofs of Storage

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    Cloud users (clients) with limited storage capacity at their end can outsource bulk data to the cloud storage server. A client can later access her data by downloading the required data files. However, a large fraction of the data files the client outsources to the server is often archival in nature that the client uses for backup purposes and accesses less frequently. An untrusted server can thus delete some of these archival data files in order to save some space (and allocate the same to other clients) without being detected by the client (data owner). Proofs of storage enable the client to audit her data files uploaded to the server in order to ensure the integrity of those files. In this work, we introduce one type of (selective) proofs of storage that we call keyword-based delegable proofs of storage, where the client wants to audit all her data files containing a specific keyword (e.g., "important"). Moreover, it satisfies the notion of public verifiability where the client can delegate the auditing task to a third-party auditor who audits the set of files corresponding to the keyword on behalf of the client. We formally define the security of a keyword-based delegable proof-of-storage protocol. We construct such a protocol based on an existing proof-of-storage scheme and analyze the security of our protocol. We argue that the techniques we use can be applied atop any existing publicly verifiable proof-of-storage scheme for static data. Finally, we discuss the efficiency of our construction.Comment: A preliminary version of this work has been published in International Conference on Information Security Practice and Experience (ISPEC 2018

    Efficient mining of frequent item sets on large uncertain databases

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    The data handled in emerging applications like location-based services, sensor monitoring systems, and data integration, are often inexact in nature. In this paper, we study the important problem of extracting frequent item sets from a large uncertain database, interpreted under the Possible World Semantics (PWS). This issue is technically challenging, since an uncertain database contains an exponential number of possible worlds. By observing that the mining process can be modeled as a Poisson binomial distribution, we develop an approximate algorithm, which can efficiently and accurately discover frequent item sets in a large uncertain database. We also study the important issue of maintaining the mining result for a database that is evolving (e.g., by inserting a tuple). Specifically, we propose incremental mining algorithms, which enable Probabilistic Frequent Item set (PFI) results to be refreshed. This reduces the need of re-executing the whole mining algorithm on the new database, which is often more expensive and unnecessary. We examine how an existing algorithm that extracts exact item sets, as well as our approximate algorithm, can support incremental mining. All our approaches support both tuple and attribute uncertainty, which are two common uncertain database models. We also perform extensive evaluation on real and synthetic data sets to validate our approaches. © 1989-2012 IEEE.published_or_final_versio

    Epidemiological characteristics of Pandemic Influenza A (H1N1-2009) in Zhanjiang, China

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    Background: A novel influenza A virus strain (H1N1-2009) spread first in Mexico and the United Stated in late April 2009, leading to the first influenza pandemic of the 21st century. The objective of this study was to determine the epidemiological and virological characteristics of the pandemic influenza A (H1N1-2009) in Zhanjiang, China. Methods: The case and outbreak reports of influenza-like illness (ILI) were collected from the Chinese information system of disease control and prevention and the influenza surveillance system of Zhanjiang city. Real-time RT-PCR was conducted, and epidemic and virological characteristics of the virus were analyzed using descriptive epidemiological methods and Chi-square trend tests. Results: A total of 276 reported cases were confirmed from July 16, 2009 to June 30, 2010. The attack rate of outbreak was from 1.1% to 6.0%. The disease peak occurred in December 2009, after which the outbreak subsided gradually. The last case was confirmed in April 2010. Conclusion: The main population struck by the H1N1-2009 virus was young adults, youths and children. The outbreaks most frequently occurred in schools, and most cases were acquired locally
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