Influence limitation in multi-campaign social networks: A Shapley value based approach

We investigate the problem of influence limitation in the presence of competing campaigns in a social network. Given a negative campaign which starts propagating from a specified source and a positive/counter campaign that is initiated, after a certain time delay, to limit the the influence or spread of misinformation by the negative campaign, we are interested in finding the top k influential nodes at which the positive campaign may be triggered. This problem has numerous applications in situations such as limiting the propagation of rumor, arresting the spread of virus through inoculation, initiating a counter-campaign against malicious propaganda, etc. The influence function for the generic influence limitation problem is non-submodular. Restricted versions of the influence limitation problem, reported in the literature, assume submodularity of the influence function and do not capture the problem in a realistic setting. In this paper, we propose a novel computational approach for the influence limitation problem based on Shapley value, a solution concept in cooperative game theory. Our approach works equally effectively for both submodular and non-submodular influence functions. Experiments on standard real world social network datasets reveal that the proposed approach outperforms existing heuristics in the literature. As a non-trivial extension, we also address the problem of influence limitation in the presence of multiple competing campaigns.

A nested linear codes approach to distributed function computation over subspaces

In this paper, we consider a distributed function computation setting, where there are m distributed but correlated sources X1,...,Xm and a receiver interested in computing an s-dimensional subspace generated by [X1,...,Xm]Γ for some (m × s) matrix Γ of rank s. We construct a scheme based on nested linear codes and characterize the achievable rates obtained using the scheme. The proposed nested-linear-code approach performs at least as well as the Slepian-Wolf scheme in terms of sum-rate performance for all subspaces and source distributions. In addition, for a large class of distributions and subspaces, the scheme improves upon the Slepian-Wolf approach. The nested-linear-code scheme may be viewed as uniting under a common framework, both the Korner-Marton approach of using a common linear encoder as well as the Slepian-Wolf approach of employing different encoders at each source. Along the way, we prove an interesting and fundamental structural result on the nature of subspaces of an m-dimensional vector space V with respect to a normalized measure of entropy. Here, each element in V corresponds to a distinct linear combination of a set {Xi}im=1 of m random variables whose joint probability distribution function is given.

k.p based closed form energy band gap and transport electron effective mass model for 100] and 110] relaxed and strained Silicon nanowire

In this paper, we address a physics based closed form model for the energy band gap (E-g) and the transport electron effective mass in relaxed and strained 100] and 110] oriented rectangular Silicon Nanowire (SiNW). Our proposed analytical model along 100] and 110] directions are based on the k.p formalism of the conduction band energy dispersion relation through an appropriate rotation of the Hamiltonian of the electrons in the bulk crystal along 001] direction followed by the inclusion of a 4 x 4 Luttinger Hamiltonian for the description of the valance band structure. Using this, we demonstrate the variation in Eg and the transport electron effective mass as function of the cross-sectional dimensions in a relaxed 100] and 110] oriented SiNW. The behaviour of these two parameters in 100] oriented SiNW has further been studied with the inclusion of a uniaxial strain along the transport direction and a biaxial strain, which is assumed to be decomposed from a hydrostatic deformation along 001] with the former one. In addition, the energy band gap and the effective mass of a strained 110] oriented SiNW has also been formulated. Using this, we compare our analytical model with that of the extracted data using the nearest neighbour empirical tight binding sp(3)d(5)s* method based simulations and has been found to agree well over a wide range of device dimensions and applied strain. (C) 2012 Elsevier Ltd. All rights reserved.

Thermoelectric properties of chalcogenide based Cu2+xZnSn1-xSe4

Quaternary chalcogenide compounds Cu2+ xZnSn1-xSe4 (0 <= x <= 0.15) were prepared by solid state synthesis. Rietveld powder X-ray diffraction (XRD) refinements combined with Electron Probe Micro Analyses (EPMA, WDS-Wavelength Dispersive Spectroscopy) and Raman spectra of all samples confirmed the stannite structure (Cu2FeSnS4-type) as the main phase. In addition to the main phase, small amounts of secondary phases like ZnSe, CuSe and SnSe were observed. Transport properties of all samples were measured as a function of temperature in the range from 300 K to 720 K. The electrical resistivity of all samples decreases with an increase in Cu content except for Cu2.1ZnSn0.9Se4, most likely due to a higher content of the ZnSe. All samples showed positive Seebeck coefficients indicating that holes are the majority charge carriers. The thermal conductivity of doped samples was high compared to Cu2ZnSnSe4 and this may be due to the larger electronic contribution and the presence of the ZnSe phase in the doped samples. The maximum zT = 0.3 at 720 K occurs for Cu2.05ZnSn0.95Se4 for which a high-pressure torsion treatment resulted in an enhancement of zT by 30% at 625 K. Copyright 2013 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4794733]

A risk-estimation-based formulation for speech enhancement and its relation to Wiener filtering

The goal of speech enhancement algorithms is to provide an estimate of clean speech starting from noisy observations. The often-employed cost function is the mean square error (MSE). However, the MSE can never be computed in practice. Therefore, it becomes necessary to find practical alternatives to the MSE. In image denoising problems, the cost function (also referred to as risk) is often replaced by an unbiased estimator. Motivated by this approach, we reformulate the problem of speech enhancement from the perspective of risk minimization. Some recent contributions in risk estimation have employed Stein's unbiased risk estimator (SURE) together with a parametric denoising function, which is a linear expansion of threshold/bases (LET). We show that the first-order case of SURE-LET results in a Wiener-filter type solution if the denoising function is made frequency-dependent. We also provide enhancement results obtained with both techniques and characterize the improvement by means of local as well as global SNR calculations.

On the zeta function of a periodic-finite-type shift

Periodic-finite-type shifts (PFT's) are sofic shifts which forbid the appearance of finitely many pre-specified words in a periodic manner. The class of PFT's strictly includes the class of shifts of finite type (SFT's). The zeta function of a PET is a generating function for the number of periodic sequences in the shift. For a general sofic shift, there exists a formula, attributed to Manning and Bowen, which computes the zeta function of the shift from certain auxiliary graphs constructed from a presentation of the shift. In this paper, we derive an interesting alternative formula computable from certain ``word-based graphs'' constructed from the periodically-forbidden word description of the PET. The advantages of our formula over the Manning-Bowen formula are discussed.

Optimal design of timer-based, distributed selection with unknown number of nodes

The timer-based selection scheme is a popular, simple, and distributed scheme that is used to select the best node from a set of available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal timer mapping that maximizes the average success probability for the practical scenario in which the number of nodes in the system is unknown but only its probability distribution is known. We show that it has a special discrete structure, and present a recursive characterization to determine it. We benchmark its performance with ad hoc approaches proposed in the literature, and show that it delivers significant gains. New insights about the optimality of some ad hoc approaches are also developed.

Optical read-out scheme based on Grated Waveguide Cantilever cavity resonance for interrogation of cantilever sensor arrays

The design and analysis of an optical read-out scheme based on a grated waveguide (GWG) resonator for interrogating microcantilever sensor arrays is presented. The optical system consisting of a micro cantilever monolithically integrated in proximity to a grated waveguide (GWG), is realized in silicon optical bench platform. The mathematical analysis of the optical system is performed using a Fabry-Perot interferometer model with a lossy cavity formed between the cantilever and the GWG and an analytical expression is derived for the optical power transmission as a function of the cantilever deflection which corresponds to cavity width variation. The intensity transmission of the optical system for different cantilever deflections estimated using the analytical expression captures the essential features exhibited by a FDTD numerical model.

Single electron transfer-driven multi-dimensional signal read-out function of TCNQ as an ``off-the-shelf'' detector for cyanide

Herein we report the first applications of TCNQ as a rapid and highly sensitive off-the-shelf cyanide detector. As a proof-of-concept, we have applied a kinetically selective single-electron transfer (SET) from cyanide to deep-lying LUMO orbitals of TCNQ to generate a persistently stable radical anion (TCNQ(center dot-)), under ambient condition. In contrast to the known cyanide sensors that operate with limited signal outputs, TCNQ(center dot-) offers a unique multiple signaling platform. The signal readability is facilitated through multichannel absorption in the UV-vis-NIR region and scattering-based spectroscopic methods like Raman spectroscopy and hyper Rayleigh scattering techniques. Particularly notable is the application of the intense 840 nm NIR absorption band to detect cyanide. This can be useful for avoiding background interference in the UV-vis region predominant in biological samples. We also demonstrate the fabrication of a practical electronic device with TCNQ as a detector. The device generates multiorder enhancement in current with cyanide because of the formation of the conductive TCNQ(center dot-).

Shape-function-relationship (SFR) framework for semantic interoperability of product model

The problem of semantic interoperability arises while integrating applications in different task domains across the product life cycle. A new shape-function-relationship (SFR) framework is proposed as a taxonomy based on which an ontology is developed. Ontology based on the SFR framework, that captures explicit definition of terminology and knowledge relationships in terms of shape, function and relationship descriptors, offers an attractive approach for solving semantic interoperability issue. Since all instances of terms are based on single taxonomy with a formal classification, mapping of terms requires a simple check on the attributes used in the classification. As a preliminary study, the framework is used to develop ontology of terms used in the aero-engine domain and the ontology is used to resolve the semantic interoperability problem in the integration of design and maintenance. Since the framework allows a single term to have multiple classifications, handling context dependent usage of terms becomes possible. Automating the classification of terms and establishing the completeness of the classification scheme are being addressed presently.

The Lovasz θ function, SVMs and finding large dense subgraphs

The Lovasz θ function of a graph, is a fundamental tool in combinatorial optimization and approximation algorithms. Computing θ involves solving a SDP and is extremely expensive even for moderately sized graphs. In this paper we establish that the Lovasz θ function is equivalent to a kernel learning problem related to one class SVM. This interesting connection opens up many opportunities bridging graph theoretic algorithms and machine learning. We show that there exist graphs, which we call SVM−θ graphs, on which the Lovasz θ function can be approximated well by a one-class SVM. This leads to a novel use of SVM techniques to solve algorithmic problems in large graphs e.g. identifying a planted clique of size Θ(n√) in a random graph G(n,12). A classic approach for this problem involves computing the θ function, however it is not scalable due to SDP computation. We show that the random graph with a planted clique is an example of SVM−θ graph, and as a consequence a SVM based approach easily identifies the clique in large graphs and is competitive with the state-of-the-art. Further, we introduce the notion of a ''common orthogonal labeling'' which extends the notion of a ''orthogonal labelling of a single graph (used in defining the θ function) to multiple graphs. The problem of finding the optimal common orthogonal labelling is cast as a Multiple Kernel Learning problem and is used to identify a large common dense region in multiple graphs. The proposed algorithm achieves an order of magnitude scalability compared to the state of the art.

Graphene based E. coli sensor on flexible acetate sheet

A low cost, reagent free, Escherichia coli sensor is demonstrated with graphene, on transparent flexible acetate substrate. Graphene is grown on 100 mu m thick Cu foil, using CVD process and subsequently transferred on to a flexible acetate substrate. Gold electrodes are deposited on graphene to form a two terminal, interdigitated capacitor structure. Impedance spectroscopy (10 Hz to 100 kHz) is performed to characterize the change in impedance, as a function of E. coli concentration on graphene surface. The residual methyl groups on graphene, resulting from the transfer process, act as binding sites for E. coli. It has been observed that the resistance of graphene decreases with increasing E. coli concentration. This is due to the increased hole doping induced by negatively charged E. coli. A sensitivity of 60% is achieved for an E. coli concentration of 4.5 x 10(7) cfu/ml. An equivalent RC model is proposed to explain the sensing mechanism. (C) 2013 Elsevier B.V. All rights reserved.

Structural Insights into Saccharomyces cerevisiae Msh4-Msh5 Complex Function Using Homology Modeling

The Msh4-Msh5 protein complex in eukaryotes is involved in stabilizing Holliday junctions and its progenitors to facilitate crossing over during Meiosis I. These functions of the Msh4-Msh5 complex are essential for proper chromosomal segregation during the first meiotic division. The Msh4/5 proteins are homologous to the bacterial mismatch repair protein MutS and other MutS homologs (Msh2, Msh3, Msh6). Saccharomyces cerevisiae msh4/5 point mutants were identified recently that show two fold reduction in crossing over, compared to wild-type without affecting chromosome segregation. Three distinct classes of msh4/5 point mutations could be sorted based on their meiotic phenotypes. These include msh4/5 mutations that have a) crossover and viability defects similar to msh4/5 null mutants; b) intermediate defects in crossing over and viability and c) defects only in crossing over. The absence of a crystal structure for the Msh4-Msh5 complex has hindered an understanding of the structural aspects of Msh4-Msh5 function as well as molecular explanation for the meiotic defects observed in msh4/5 mutations. To address this problem, we generated a structural model of the S. cerevisiae Msh4-Msh5 complex using homology modeling. Further, structural analysis tailored with evolutionary information is used to predict sites with potentially critical roles in Msh4-Msh5 complex formation, DNA binding and to explain asymmetry within the Msh4-Msh5 complex. We also provide a structural rationale for the meiotic defects observed in the msh4/5 point mutations. The mutations are likely to affect stability of the Msh4/5 proteins and/or interactions with DNA. The Msh4-Msh5 model will facilitate the design and interpretation of new mutational data as well as structural studies of this important complex involved in meiotic chromosome segregation.

Platinum surface additive based nanostructured CuO films for ethanol sensing

In the present work, Platinum (Pt)/Copper (II) oxide (CuO) thin film based ethanol sensors were fabricated by sputtering of Pt in varying concentrations over pre-sputtered nanostructured CuO films. The responses of these sensors as a function of Pt concentrations were studied using operating temperature modulation (200-450 °C) and ethanol concentration modulation (100-2500 ppm). During these modulations, it was found that the sensing response was maximum at operating temperature near 400 °C for all the samples irrespective of the Pt concentration dispersed over them. Moreover, the sensing behavior improves for lower Pt concentration (Pt/CuO-60s) and deteriorates for higher Pt concentration (Pt/CuO-120s). In comparison with bare CuO sample, the sensitivity of Pt/CuO-60s increased up to 22% in the linear range and 33% for maximum ethanol concentration. Hence, the well dispersed optimum Pt additive concentration improves the overall sensing behavior including sensitivity, linear working range and response as well as recovery time.

mulPBA: an efficient multiple protein structure alignment method based on a structural alphabet

The increasing number of available protein structures requires efficient tools for multiple structure comparison. Indeed, multiple structural alignments are essential for the analysis of function, evolution and architecture of protein structures. For this purpose, we proposed a new web server called multiple Protein Block Alignment (mulPBA). This server implements a method based on a structural alphabet to describe the backbone conformation of a protein chain in terms of dihedral angles. This sequence-like' representation enables the use of powerful sequence alignment methods for primary structure comparison, followed by an iterative refinement of the structural superposition. This approach yields alignments superior to most of the rigid-body alignment methods and highly comparable with the flexible structure comparison approaches. We implement this method in a web server designed to do multiple structure superimpositions from a set of structures given by the user. Outputs are given as both sequence alignment and superposed 3D structures visualized directly by static images generated by PyMol or through a Jmol applet allowing dynamic interaction. Multiple global quality measures are given. Relatedness between structures is indicated by a distance dendogram. Superimposed structures in PDB format can be also downloaded, and the results are quickly obtained. mulPBA server can be accessed at www.dsimb.inserm.fr/dsimb_tools/mulpba/.