8,389 research outputs found
Mean Field Approach for a Statistical Mechanical Model of Proteins
We study the thermodynamical properties of a topology-based model proposed by
Galzitskaya and Finkelstein for the description of protein folding. We devise
and test three different mean-field approaches for the model, that simplify the
treatment without spoiling the description. The validity of the model and its
mean-field approximations is checked by applying them to the -hairpin
fragment of the immunoglobulin-binding protein (GB1) and making a comparison
with available experimental data and simulation results. Our results indicate
that this model is a rather simple and reasonably good tool for interpreting
folding experimental data, provided the parameters of the model are carefully
chosen. The mean-field approaches substantially recover all the relevant exact
results and represent reliable alternatives to the Monte Carlo simulations.Comment: RevTeX-4, 11 pages, 6 eps-figures, To Appear on J.Chem.Phy
Know Your Enemy: Stealth Configuration-Information Gathering in SDN
Software Defined Networking (SDN) is a network architecture that aims at
providing high flexibility through the separation of the network logic from the
forwarding functions. The industry has already widely adopted SDN and
researchers thoroughly analyzed its vulnerabilities, proposing solutions to
improve its security. However, we believe important security aspects of SDN are
still left uninvestigated. In this paper, we raise the concern of the
possibility for an attacker to obtain knowledge about an SDN network. In
particular, we introduce a novel attack, named Know Your Enemy (KYE), by means
of which an attacker can gather vital information about the configuration of
the network. This information ranges from the configuration of security tools,
such as attack detection thresholds for network scanning, to general network
policies like QoS and network virtualization. Additionally, we show that an
attacker can perform a KYE attack in a stealthy fashion, i.e., without the risk
of being detected. We underline that the vulnerability exploited by the KYE
attack is proper of SDN and is not present in legacy networks. To address the
KYE attack, we also propose an active defense countermeasure based on network
flows obfuscation, which considerably increases the complexity for a successful
attack. Our solution offers provable security guarantees that can be tailored
to the needs of the specific network under consideratio
Superfluidity and Quantum Melting of para-Hydrogen clusters
Structural and superfluid properties of para-Hydrogen clusters of size up to
N=40 molecules, are studied at low temperature (0.5 K < T < 4 K) by Path
Integral Monte Carlo simulations. The superfluid fraction displays an
interesting, non-monotonic behavior for 22 < N < 30. We interpret this
dependence in terms of variations with N of the cluster structure.
Superfluidity is observed at low T in clusters of as many as 27 molecules; in
the temperature range considered here, quantum melting is observed in some
clusters, which freeze at high temperature
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