682 research outputs found
Posterior Wall Isolation Improves Outcomes for Persistent AF With Rapid Posterior Wall Activity: A CAPLA Substudy
No full textAbstract not availableLouise Segan, David Chieng, Sandeep Prabhu, Andrew Hunt, Troy Watts, Brian Klys, Aleksandr Voskoboinik, Hariharan Sugumar, Liang-Han Ling, Geoff Lee, Joseph Morton, Rajeev K. Pathak, Deep Chandh Raja, Laurence Sterns, Matthew Ginks, Prashanthan Sanders, Jonathan M. Kalman, Peter M. Kistle
Proceedings of ASME Turbo Expo 2013: Power for Land, Sea and Air, Volume 1A: Combustion, Fuels and Emissions
No full textShahrokh Etemad (with Sandeep Alavandi and Benjamin Baird) is a contributing author, Fuel Flexible Rich Catalytic Lean Burn System for Low Btu Fuels
Who Thinks Who Knows Who? Socio-cognitive Analysis of Email Networks
No full textInterpersonal interaction plays an important role in organizational dynamics, and understanding these interaction networks is a key issue for any organization, since these can be tapped to facilitate various organizational processes. However, the approaches of collecting data about them using surveys/interviews are fraught with problems of scalability, logistics and reporting biases, especially since such surveys may be perceived to be intrusive. Widespread use of computer networks for organizational communication provides a unique opportunity to overcome these difficulties and automatically map the organizational networks with a high degree of detail and accuracy. This paper describes an effective and scalable approach for modeling organizational networks by tapping into an organization's email communication. The approach models communication between actors as non-stationary Bernoulli trials and Bayesian inference is used for estimating model parameters over time. This approach is useful for socio-cognitive analysis (who knows who knows who) of organizational communication networks. Using this approach, novel measures for analysis of (i) closeness between actors' perceptions about such organizational networks (agreement), (ii) divergence of an actor's perceptions about organizational network from reality (misperception) are explained. Using the Enron email data, we show that these techniques provide sociologists with a new tool to understand organizational networks.Pathak, Nishith; Mane, Sandeep; Srivastava, Jaideep. (2006). Who Thinks Who Knows Who? Socio-cognitive Analysis of Email Networks. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215708
Acute Ethanol Administration Rapidly Increases Phosphorylation of Conventional Protein Kinase C in Specific Mammalian Brain Regions in Vivo
Get PDFBackground
Protein kinase C (PKC) is a family of isoenzymes that regulate a variety of functions in the central nervous system including neurotransmitter release, ion channel activity, and cell differentiation. Growing evidence suggests that specific isoforms of PKC influence a variety of behavioral, biochemical, and physiological effects of ethanol in mammals. The purpose of this study was to determine whether acute ethanol exposure alters phosphorylation of conventional PKC isoforms at a threonine 674 (p-cPKC) site in the hydrophobic domain of the kinase, which is required for its catalytic activity.
Methods
Male rats were administered a dose range of ethanol (0, 0.5, 1, or 2 g/kg, intragastric) and brain tissue was removed 10 minutes later for evaluation of changes in p-cPKC expression using immunohistochemistry and Western blot methods.
Results
Immunohistochemical data show that the highest dose of ethanol (2 g/kg) rapidly increases p-cPKC immunoreactivity specifically in the nucleus accumbens (core and shell), lateral septum, and hippocampus (CA3 and dentate gyrus). Western blot analysis further showed that ethanol (2 g/kg) increased p-cPKC expression in the P2 membrane fraction of tissue from the nucleus accumbens and hippocampus. Although p-cPKC was expressed in numerous other brain regions, including the caudate nucleus, amygdala, and cortex, no changes were observed in response to acute ethanol. Total PKC? immunoreactivity was surveyed throughout the brain and showed no change following acute ethanol injection
Structural and optical properties of methylammonium lead iodide across the tetragonal to cubic phase transition: Implications for perovskite solar cells
No full textWe report temperature resolved UV-vis absorption and spectral photocurrent response measurements of MAPbI(3) thin films and solar cells, together with ab initio simulations, to investigate the changes in material properties occurring across the tetragonal to cubic phase transition. We find that the MAPbI3 band-gap does not abruptly change when exceeding the tetragonal to cubic transition temperature, but it rather monotonically blue-shifts following the same temperature evolution observed within the tetragonal phase. Car-Parrinello molecular dynamics simulations demonstrate that the high temperature phase corresponds on average to the expected symmetric cubic structure assigned from XRD measurements, but that the system strongly deviates from such a structure in the sub-picosecond time scale. Thus, on the time scale of electronic transitions, the material seldom experiences a cubic environment, rather an increasingly distorted tetragonal one. This result explains the absence of dramatic changes in the optical of MAPbI3 across the explored temperature range of 270-420 K, which could have important consequences for the practical uptake of perovskite solar cells
Characterizing collagen mimetic peptides for orthogonal self-assembly
No full textA computational design of collagen mimetic peptides (CMPs) that self-assemble orthogonally (mutually exclusively), in the presence of other pre-existing collagen trimer mixtures, in vitro, has been proposed. The orthogonality in self-assembly was brought about by orthogonal patterning of ionic salt bridges and residues, along the collagen trimers’ axial length. Through the aid of circular dichroism spectroscopy alone, a novel experimental protocol was set-up to rapidly assess the level of cross-talk that may arise in such designed ‘heterogeneous monomer to trimer folding’ mixture environments. It is shown that the designed collagen mimetic peptides are stable and hetero-specific within their composite 3 chain peptide ecosystem. We experimentally demonstrate the extent to which loss in specificity could possibly occur, upon moving to a higher order ‘more than 3 monomers in solution’ peptide ensemble. Although the desired level of multi-state orthogonality was not achieved in the current design, the experimental results obtained were used to estimate the stability and specificity barrier threshold that one might run into, if one were to instead design orthogonal systems where-in specificity is incorporated during the computational design stage itself a priori. A Pareto frontier plot indicating the specificity versus stability trade-off is plotted. We conclude that a bottom-up design approach, incorporating design of specificity during the sequence design stage, would be a better way forward for achieving self-assembling orthogonality. In contrast to the complex chaperone assisted protein folding systems existing in nature, our method is a simplistic first step towards the complementary approach of modular synthetic collagen molecule design.Ph.D.Includes bibliographical referencesby Sandeep Vishwanath Belur
Resin and steel-reinforced resin used as injection materials in bolted connections
No full textInjection bolts are bolts in which the cavity produced by the clearance between the bolt and the wall of the hole is completely filled up with a two-component resin. Filling of the clearance is carried out through a small hole in the head of the bolt. After injection and complete curing, the connection is slip resistant. Recently the injection material, typically an epoxy resin, was modified at TU Delft by adding steel shots (spherical particles) to mitigate the effects of resin compliance in the shear connection of reusable composite (steel-concrete) structures. Experimental compressive material tests on unconfined/confined resin and steel-reinforced resin are evaluated in this chapter. The uniaxial model which combines damage mechanics and the Ramberg-Osgood relationship is proposed to describe the uniaxial compressive behavior of resin and steel-reinforced resin. First-order numerical homogenization is employed as a high-fidelity model, where a combined nonlinear isotropic/kinematic cyclic hardening model is employed to define the steel plasticity, the linear Drucker-Prager plastic criterion was used to simulate resin damage, and the cohesive surfaces reflecting the relationship between traction and displacement at the interface. The linear Drucker-Prager plastic model is used as a low-fidelity model.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Steel & Composite Structure
Anomaly-Based DNN Model for Intrusion Detection in IoT and Model Explanation: Explainable Artificial Intelligence
No full textIoT has gained immense popularity recently with advancements in technologies and big data. IoT network is dynamically increasing with the addition of devices, and the big data is generated within the network, making the network vulnerable to attacks. Thus, network security is essential, and an intrusion detection system is needed. In this paper, we proposed a deep learning-based model for detecting intrusions or attacks in IoT networks. We constructed a DNN model, applied a filter method for feature reduction, and tuned the model with different parameters. We also compared the performance of DNN with other machine learning techniques in terms of accuracy, and the proposed DNN model with weight decay of 0.0001 and dropout rate of 0.01 achieved an accuracy of 0.993, and the reduced loss on the NSL-KDD dataset having five classes. DL models are a black box and hard to understand, so we explained the model predictions using LIME.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit
Book Review - Dharmaraj K. Veer and Shivaji Sontakke, Advancement and Challenges for College Libraries in IT Era (New Delhi: Studera Press, 2018)
No full textThe edited book under review is divided into seven different sections examining the imperatives, process and status of development of library and information technology, especially the use of the e-Resources, library automation software, to make library an open source digital repository. Besides, the contributing authors have analyzed the role of library management and librarian during visit of The National Assessment and Accreditation Council (NAAC)
Ground State Studies Of Strongly Correlated 2D Systems
Get PDFThe quest for obtaining higher Tc superconductivity led to the discovery of cuprates about 20 years ago. Since then, they continue to puzzle the scientific community with their bizarre properties like non-BCS superconductivity, pseudo gap, Fermi arcs, linear T resistivity etc.
Since these materials show unusually high Tc, a novel mechanism is at play and strong correlations are believed to play an important role. The theme of this thesis work is to study physics of such strongly correlated systems in two dimensions at T = 0 along with development of new theoretical tools necessary for the study.
The focus of the thesis is on the ground state studies of strongly correlated models like t-J and Hubbard models using variational Monte Carlo (VMC) and renormalized mean field theory (RMFT). The general method is to propose a variational wave function, motivated by the physics ideas, to be a candidate ground state of the system. Methods to efficiently evaluate the ground state energy and minimizing it with respect to the variational parameters are developed in this work. Antiferromagnetism-superconductivity competition and electron-hole asymmetry in the extended t-J model is investigated. The main result of this work is that increasing the magnitude of the next neighbor hopping (t') on hole doped side strengthen superconductivity while it stabilizes antiferromagnetism on the electron doped side. It is also shown that it is possible to characterize the T = 0 phase diagram with just one parameter called as Fermi Surface Convexity Parameter (FSCP). Next, the possibility of phase separation in the t-J model on a
square lattice is investigated using local RMFT technique. It is found that for certain doping, the system phase separates into regions with antiferromagnetic and superconducting orders. Next, the role played by crystalline anisotropy of orthorhombic YBCO cuprates on their properties is examined using anisotropic
tx-ty-J model and this ground state study suggests that the anisotropies seen in their properties are plausible solely due to the crystalline anisotropy. A new general method to study strongly correlated systems with singlet ground states is developed and tested in this thesis work. The last part of the thesis explores the possibility of high Tc superconductivity in graphene which is a intermediate coupling resonating valence bond (RVB) system. It is found that undoped graphene is not a superconductor, consistent with the experiments. On doping, the ground state of graphene is found to be a superconductor with “d+id” symmetry whose strength shows a dome as a function of doping which is reminiscent of RVB physics
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