Elastic Properties of the Non-Mixing Copper Donor Assisted Material in Friction Stir Welding of Aluminum Alloys Using Nanoindentation

Friction stir welding of high-strength materials such as steels is the impeded by the lack of the vast heat input needed to start the process. Contact friction is considered the most dominant source of heat generation for FSW steels which tends to cause severe wear conditions of the tool hear. To relieve the extreme wear conditions that occur on the tool heads because of FSW steels, we introduce the non-mixing Cu donor stir material to friction stir welding of aluminum alloys. The elastic properties of the Cu donor assisted friction stir welded aluminum alloys are measured using nanoindentation. The hardness and elastic modulus were measured for two regions, the base metal (BM) and the stir zone (SZ). The measurements were conducted for 20% and 60% Cu non-heat treated (NHT) and heat-treated (HT) samples. The nanomechanical properties were measured using nanoindentation with the continuous stiffness method (CSM) in depth control. The HT samples are softer than the NHT samples as expected. However, the 20% Cu NHT and HT samples depicted the same hardness at the SZ. Similar results were observed for the 60% Cu donor stir samples. It therefore concluded that the SZ is softer than the BM for the 20% and 60% Cu donor stir material as expected. The hardness of the weld at the SZ is similar to the hardness of the Al6061-T6 plate, suggesting that the Cu donor stir material did not impact the hardness properties of the Al6061-T6 plate due to the depletion of the Cu donor stir material during the welding process, an important result of the concept of the donor material. The elastic moduli of the Cu donor stir welded samples vary between 75 ~ 85 GPa at a depth of indentation of ~ 4600nm, which are different from the elastic moduli of Cu 110 (117.2 GPa) and similar to the elastic modulus of aluminum alloys (68.9 GPa), an important outcome

Structural and functional basis of transcriptional regulation by TetR family protein CprB from S. coelicolor A3(2)

Antibiotic production and resistance pathways in Streptomyces are dictated by the interplay of transcriptional regulatory proteins that trigger downstream responses via binding to small diffusible molecules. To decipher the mode of DNA binding and the associated allosteric mechanism in the subclass of transcription factors that are induced by gamma-butyrolactones, we present the crystal structure of CprB in complex with the consensus DNA element to a resolution of 3.25 angstrom. Binding of the DNA results in the restructuring of the dimeric interface of CprB, inducing a pendulum-like motion of the helix-turn-helix motif that inserts into the major groove. The crystal structure revealed that, CprB is bound to DNA as a dimer of dimers with the mode of binding being analogous to the broad spectrum multidrug transporter protein QacR from the antibiotic resistant strain Staphylococcus aureus. It was demonstrated that the CprB displays a cooperative mode of DNA binding, following a clamp and click model. Experiments performed on a subset of DNA sequences from Streptomyces coelicolor A3(2) suggest that CprB is most likely a pleiotropic regulator. Apart from serving as an autoregulator, it is potentially a part of a network of proteins that modulates the gamma-butyrolactone synthesis and antibiotic regulation pathways in S. coelicolor A3(2)

Structural and dynamics studies of the TetR family protein, CprB from Streptomyces coelicolor in complex with its biological operator sequence

In Streptomycetes, tetracycline repressor family of transcription regulators (TetR-FTRs) controls various biological processes including antibiotic biosynthesis, cellular morphology and innate resistance. Here, we focus on understanding the structural basis of transcription regulation by CprB, a member of TetR-FTRs from S. coelicolor. CprB is implicated as a receptor of gamma-butyrolactones, a class of quorum sensing molecules, responsible for initiating secondary metabolic pathways. In order to understand the molecular mechanism of DNA recognition, the X-ray structure of CprB in complex with its biological relevant operator sequence was solved to a resolution of 3.95 angstrom. Furthermore, to refine and compliment the results, atomistic molecular dynamics simulations were carried out using the X-ray structure as the template. The studies reveal that CprB binds to DNA as dimer of dimers with this mode of interaction results in minimal distortion in the DNA, enabling these proteins to recognize multiple sequences with varying affinity. Another crucial finding from our simulation results was that the positively charged N-terminal arm of CprB brings extra stability to the protein-DNA complex by interacting with the minor-groove of the DNA and anchoring itself to the phosphate backbone. Corroborating electrophoretic mobility shift assay and fluorescence anisotropy experiments showed that the mutant AN6-CprB exhibited about 7-8 fold reduced DNA binding. Comparison with other TetR-FTRs reveals that this strategy is also employed by over 25% of TetR-FTRs, where N-terminal anchoring mechanism is used to enhance selectivity for a particular DNA sequence. (C) 2017 Elsevier Inc. All rights reserved

Layered Security Architecture for Masquerade Attack Detection

Part 8: Probabilistic Attacks and Protection (Short Papers)International audienceMasquerade attack refers to an attack that uses a fake identity, to gain unauthorized access to personal computer information through legitimate access identification. Automatic discovery of masqueraders is sometimes undertaken by detecting significant departures from normal user behavior. If a user’s normal profile deviates from their original behavior, it could potentially signal an ongoing masquerade attack. In this paper we proposed a new framework to capture data in a comprehensive manner by collecting data in different layers across multiple applications. Our approach generates feature vectors which contain the output gained from analysis across multiple layers such as Window Data, Mouse Data, Keyboard Data, Command Line Data, File Access Data and Authentication Data. We evaluated our approach by several experiments with a significant number of participants. Our experimental results show better detection rates with acceptable false positives which none of the earlier approaches has achieved this level of accuracy so far