Extracting trust information from security system of a service

The issue of trust is a research problem in emerging open environments, such as ubiquitous networks. Such environments are highly dynamic and they contain diverse number of services and autonomous entities. Entities in open environments have different security needs from services. Trust computations related to the security systems of services necessitate information that meets needs of each entity. Obtaining such information is a challenging issue for entities. In this paper, we propose a model for extracting trust information from the security system of a service based on the needs of an entity. We formally represent security policies and security systems to extract trust information according to needs of an entity. The formal representation ensures an entity to extract trust information about a security property of a service and trust information about whole security system of the service. The proposed model is applied to Dental Clinic Patient Service as a case study with two scenarios. The scenarios are analyzed experimentally with simulations. The experimental evaluation shows that the proposed model provides trust information related to the security system of a service based on the needs of an entity and it is applicable in emerging open environments.     

Novel colloidal nanofiber electrolytes from PVA‐organoclay/poly(MA‐alt‐MVE), and their NaOH and Ag‐carrying polymer complexes

Novel multifunctional polymer nanofiber electrolytes with covalence crosslinked structures from various solution blends of reactive intercalated poly(vinyl alcohol)/octadecylamine montmorillonite (as a matrix polymer), poly(maleic anhydride‐alt‐methyl vinyl ether) (as a partner polymer) and their NaOH‐absorbing and Ag‐carrying polymer complexes were fabricated via electrospinning. Chemical, physical, morphological, and electrical properties of nanofiber structures were investigated by FTIR, XRD, SEM, and electrical analysis methods. Ag precursors in fiber composites significantly improved phase separation processing, fiber morphologies, diameter distributions, and electrical properties of the fibers. In situ generation of Ag nanoparticles and their distribution on nanofiber surfaces during fiber formation occurred via complex formation between silver cations and electronegative functional groups from both matrix and partner polymers as stabilizing/reducing agents. Electrical resistance and conductivity strongly depended on matrix/partner polymer ratios and absorption time of NaOH solution on nanofibers. Addition of NaOH changed the electrical properties of fiber structures from almost dielectric state to excellent conductivity form. The fabricated unique nanofiber electrolytes are promising candidates for applications in power and fuel cell nanotechnology, electrochemical, and bioengineering processes as reactive semiconductive platforms. POLYM. ENG. SCI., 56:204–213, 2016. © 2015 Society of Plastics Engineers     

Rapid Discovery of Aspartyl Protease Inhibitors Using an Anchoring Approach

Pharmacophore searches that include anchors, fragments contributing above average to receptor binding, combined with one-step syntheses are a powerful approach for the fast discovery of novel bioactive molecules. Here, we are presenting a pipeline for the rapid and efficient discovery of aspartyl protease inhibitors. First, we hypothesized that hydrazine could be a multi-valent warhead to interact with the active site Asp carboxylic acids. We incorporated the hydrazine anchor in a multicomponent reaction and created a large virtual library of hydrazine derivatives synthetically accessible in one-step. Next, we performed anchor-based pharmacophore screening of the libraries and resynthesized top-ranked compounds. The inhibitory potency of the molecules was finally assessed by an enzyme activity assay and the binding mode confirmed by several soaked crystal structures supporting the validity of the hypothesis and approach. The herein reported pipeline of tools will be of general value for the rapid generation of receptor binders beyond Asp proteases.     

Analysis of interaction between tunnels in soft ground by 3D numerical modeling

Tunnels are increasingly being excavated in soft ground conditions when services are required in urban environments, and it is now common to have tunnels crossing at various elevations. As the tunnel excavations are undertaken at different levels, there will be an interaction which can have a significant influence on stress distributions and consequently deformations within the tunnels and surface settlement. As multi-layer tunnelling is a three dimensional phenomenon in nature, 3D numerical solutions must be utilized for perpendicularly crossing tunnels at various levels. This paper reports the investigations into the changes in stress distribution, deformations and surface settlements which may be expected when the twin Tohid Tunnels pass beneath the Line 4 metro tunnel in Tehran.     

Investigating Neutronic Parameters of a Thorium Fusion Breeder with Recurrent Neural Networks

Artificial neural networks (ANNs) have recently been introduced to the nuclear engineering applications as a fast and flexible vehicle to modeling, simulation and optimization. In this paper, a new approach based on recurrent neural networks (RNNs) was presented for the neutronic parameters of a thorium fusion breeder. The results of the RNNs implemented for the tritium breeding ratio computation, energy multiplication factor and net ²³³U production in a thorium fusion breeder and the results available in the literature obtained by using Scale 4.3 were compared. The drawn conclusions confirmed that the proposed RNNs could provide an accurate computation of the tritium breeding ratio computation, the energy multiplication factor and the net ²³³U production of the thorium fusion breeder.     

Utilization of Heavy Metal Molten Salts in the ARIES-RS Fusion Reactor

ARIES-RS is one of the major magnetic fusion energy reactor designs that uses a blanket having vanadium alloy structure cooled by lithium [1, 2]. It is a deuterium–tritium (DT) fusion driven reactor, having a fusion power of 2170 MW [1, 2]. This study presents the neutronic analysis of the ARIES-RS fusion reactor using heavy metal molten salts in which Li₂BeF₄ as the main constituent was mixed with increased mole fractions of heavy metal salt (ThF₄ or UF₄) starting by 2 mol.% up to 12 mol.%. Neutron transport calculations were carried out with the help of the SCALE 4.3 system by solving the Boltzmann transport equation with the XSDRNPM code in 238 neutron groups and a S ₈–P ₃ approximation. According to the numerical results, tritium self-sufficiency was attained for the coolants, Flibe with 2% UF₄ or ThF₄ and 4% UF₄. In addition, higher energy multiplication values were found for the salt with UF₄ compared to that with ThF₄. Furthermore, significant amount of high quality nuclear fuel was produced to be used in external reactors.     

Two-Tier,Scalable and Highly Resilient Key Predistribution Scheme for Location-Aware Wireless Sensor Network Deployments

We propose a probabilistic key predistribution scheme for wireless sensor networks, where keying materials are distributed to sensor nodes for secure communication. We use a two-tier approach in which there are two types of nodes: regular nodes and agent nodes. Agent nodes are more capable than regular nodes. Our node deployment model is zone-based such that the nodes that may end up with closer positions on ground are grouped together. The keying material of nodes that belong to different zones is non-overlapping. However, it is still possible for nodes that belong to different zones to communicate with each other via agent nodes when needed. We give a comparative analysis of our scheme through simulations and show that our scheme provides good connectivity figures at reasonable communication cost by using minimal flooding in key distribution. Moreover, we show that our scheme is scalable such that no extra overhead in incurred in case of increased number of nodes and sensor field size. Most importantly, simulation results show that our scheme is highly resilient to node captures.     

Experimental evaluation of polycrystalline diamond tool geometries while drilling carbon fiber-reinforced plastics

Polycrystalline diamond (PCD) drills are commonly employed in carbon fiber-reinforced plastic (CFRP) drilling to satisfy hole quality conditions with an acceptable tool life and productivity. Despite their common use in industry, only a small number of studies have been reported on drilling CFRPs with PCD drills. In this study, drilling performances of three different PCD drill designs are investigated experimentally using thrust force, torque, and hole exit quality measurements. Results show that work material properties, drilling conditions, and drill design should all be considered together during the selection of process parameters, and the relationships among these factors are quite complex.