Surface chemical and adsorption studies using Thiobacillus ferrooxidans with reference to bacterial adhesion to sulfide minerals

Adhesion of Thiobacillus ferrooxidans to pyrite and chalcopyrite in relation to its importance in bioleaching and bioflotation has been studied. Electrokinetic studies as well as FT-IR spectra suggest that the surface chemistry of Thiobacillus ferrooxidans depends on bacterial growth conditions. Sulfur-,Pyrite- and chalcopyrite-grown Thiobacillus ferrooxidans were found to be relatively more hydrophobic. The altered surface chemistry of Thiobacillus ferrooxidans was due to secretion of newer and specific proteinaceous compounds. The adsorption density corresponds to a monolayer coverage in a horizontal orientation of the cells. The xanthate flotation of pyrite in presence of Thiobacillus ferrooxidans is strongly depressed where as the cells have insignificant effect on chalcopyrite flotation. This study demonstrate that: (a)Thiobacillus ferrooxidans cells can be used for selective flotation of chalcopyrite from pyrite and importantly at natural pH values. (b)Sulfur-grown cells exhibits higher leaching kinetics than ferrous ion-grown cells.

Recent Developments in the Chemistry and Biology of G-Quadruplexes with Reference to the DNA Groove Binders

DNA is the chemotherapeutic target for treating diseases of genetic origin. Besides well-known double-helical structures (A, B, Z, parallel stranded-DNA etc.), DNA is capable of forming several multi-stranded structures (triplex, tetraplex, i-motif etc.) which have unique biological significance. The G-rich 3'-ends of chromosomes, called telomeres, are synthesized by telomerase, a ribonucleoprotein, and over-expression of telomerase is associated with cancer. The activity of telomerase is suppressed if the G-rich region is folded into the four stranded structures, called G-quadruplexes (G4-DNAs) using small synthetic ligands. Thus design and synthesis of new G4-DNA ligands is an attractive strategy to combat cancer. G4-DNA forming sequences are also prevalent in other genomic regions of biological significance including promoter regions of several oncogenes. Effective gene regulation may be achieved by inducing a G4-DNA structure within the G-rich promoter sequences. To date, several G4-DNA stabilizing ligands are known. DNA groove binders interact with the duplex B-DNA through the grooves (major and minor groove) in a sequence-specific manner. Some of the groove binders are known to stabilize the G4-DNA. However, this is a relatively under explored field of research. In this review, we focus on the recent advances in the understanding of the G4-DNA structures, particularly made from the human telomeric DNA stretches. We summarize the results of various investigations of the interaction of various organic ligands with the G4-DNA while highlighting the importance of groove binder-G4-DNA interactions.

Performance and variability trade-off with gate-to-source/drain overlap length

The impact of gate-to-source/drain overlap length on performance and variability of 65 nm CMOS is presented. The device and circuit variability is investigated as a function of three significant process parameters, namely gate length, gate oxide thickness, and halo dose. The comparison is made with three different values of gate-to-source/drain overlap length namely 5 nm, 0 nm, and -5 nm and at two different leakage currents of 10 nA and 100 nA. The Worst-Case-Analysis approach is used to study the inverter delay fluctuations at the process corners. The drive current of the device for device robustness and stage delay of an inverter for circuit robustness are taken as performance metrics. The design trade-off between performance and variability is demonstrated both at the device level and circuit level. It is shown that larger overlap length leads to better performance, while smaller overlap length results in better variability. Performance trades with variability as overlap length is varied. An optimal value of overlap length of 0 nm is recommended at 65 nm gate length, for a reasonable combination of performance and variability.

Local demodulation of holograms using the Riesz transform with application to microscopy

We propose a Riesz transform approach to the demodulation of digital holograms. The Riesz transform is a higher-dimensional extension of the Hilbert transform and is steerable to a desired orientation. Accurate demodulation of the hologram requires a reliable methodology by which quadrature-phase functions (or simply, quadratures) can be constructed. The Riesz transform, by itself, does not yield quadratures. However, one can start with the Riesz transform and construct the so-called vortex operator by employing the notion of quasi-eigenfunctions, and this approach results in accurate quadratures. The key advantage of using the vortex operator is that it effectively handles nonplanar fringes (interference patterns) and has the ability to compensate for the local orientation. Therefore, this method results in aberration-free holographic imaging even in the case when the wavefronts are not planar. We calibrate the method by estimating the orientation from a reference hologram, measured with an empty field of view. Demodulation results on synthesized planar as well as nonplanar fringe patterns show that the accuracy of demodulation is high. We also perform validation on real experimental measurements of Caenorhabditis elegans acquired with a digital holographic microscope. (c) 2012 Optical Society of America

Active Sequential Hypothesis Testing with Application to a Visual Search Problem

We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.

Incentive Compatible Influence Maximization in Social Networks with Application to Viral Marketing

Information diffusion and influence maximization are important and extensively studied problems in social networks. Various models and algorithms have been proposed in the literature in the context of the influence maximization problem. A crucial assumption in all these studies is that the influence probabilities are known to the social planner. This assumption is unrealistic since the influence probabilities are usually private information of the individual agents and strategic agents may not reveal them truthfully. Moreover, the influence probabilities could vary significantly with the type of the information flowing in the network and the time at which the information is propagating in the network. In this paper, we use a mechanism design approach to elicit influence probabilities truthfully from the agents. Our main contribution is to design a scoring rule based mechanism in the context of the influencer-influencee model. In particular, we show the incentive compatibility of the mechanisms and propose a reverse weighted scoring rule based mechanism as an appropriate mechanism to use.

Gene expression in osteoblast cells treated with submicron to nanometer hydroxyapatite-mullite eluate particles

The present research focused on determining the effect of hydroxyapatite-20 wt% mullite (H20M) particle eluates on apoptosis and differentiation of human fetal osteoblast (hFOB) cells. The H20M particles (257 +/- 37 nm) were prepared, starting with the production of a nanocomposite using a unique route of spark plasma sintering, followed by a repeated grinding-cryo treatment and elution process. Tetrazolium based cytotoxicity assay results showed a time-and dose-dependent effect of H20M particle eluates on hFOB cytotoxicity. In particular, the results revealed statistically reduced cell viability after hFOB were exposed to the above 10% H20M (257 +/- 37 nm) eluates for 48 h. The apoptotic cell death triggered by H20M treatment was proven by the analysis of molecular markers of apoptosis, that is, the Bcl-2 family of genes. hFOB expression of Bcl-xL and Bcl-xS significantly increased 25.6- and 25.2-fold for 50% of H20M concentrations, respectively. The ratio of Bcl-xL/Bax (4.01) decreased 2-fold for hFOB exposed to 100% of H20M eluates than that for 10% H20M eluate (7.94) treated hFOB cells. On the other hand, the Bcl-xS/Bax ratio for the 10% H20M eluate was 4.15-fold, whereas for 100% H20M eluates, it was 11.55-fold. Specifically, the anti-apoptotic effect of the H20M particle eluates was corroborated by the up-regulation of bone cell differentiation marker genes such as, collagen type I, cbfa, and osteocalcin. In summary, the present work clearly demonstrated that H20M submicron to nanometer composite particle eluates have a minimal effect on hFOB apoptosis and can even up-regulate the expression of bone cell markers at the molecular level.

Quantum Phase Diagram of One-Dimensional Spin and Hubbard Models with Transitions to Bond Order Wave Phases

Similar quantum phase diagrams and transitions are found for three classes of one-dimensional models with equally spaced sites, singlet ground states (GS), inversion symmetry at sites and a bond order wave (BOW) phase in some sectors. The models are frustrated spin-1/2 chains with variable range exchange, half-filled Hubbard models with spin-independent interactions and modified Hubbard models with site energies for describing organic charge transfer salts. In some range of parameters, the models have a first order quantum transition at which the GS expectation value of the sublattice spin < S-A(2)> of odd or even-numbered sites is discontinuous. There is an intermediate BOW phase for other model parameters that lead to two continuous quantum transitions with continuous < S-A(2)>. Exact diagonalization of finite systems and symmetry arguments provide a unified picture of familiar 1D models that have appeared separately in widely different contexts.

Quantum Phase Diagram of One-Dimensional Spin and Hubbard Models with Transitions to Bond Order Wave Phases

Similar quantum phase diagrams and transitions are found for three classes of one-dimensional models with equally spaced sites, singlet ground states (GS), inversion symmetry at sites and a bond order wave (BOW) phase in some sectors. The models are frustrated spin-1/2 chains with variable range exchange, half-filled Hubbard models with spin-independent interactions and modified Hubbard models with site energies for describing organic charge transfer salts. In some range of parameters, the models have a first order quantum transition at which the GS expectation value of the sublattice spin < S-A(2)> of odd or even-numbered sites is discontinuous. There is an intermediate BOW phase for other model parameters that lead to two continuous quantum transitions with continuous < S-A(2)>. Exact diagonalization of finite systems and symmetry arguments provide a unified picture of familiar 1D models that have appeared separately in widely different contexts.

Glassy dielectric response in Tb2NiMnO6 double perovskite with similarities to a Griffiths phase

Results of frequency-dependent and temperature-dependent dielectric measurements performed on the double-perovskite Tb2NiMnO6 are presented. The real (epsilon(1)(f,T)) and imaginary (epsilon(2)(f,T)) parts of dielectric permittivity show three plateaus suggesting dielectric relaxation originating from the bulk, grain boundaries and the sample-electrode interfaces, respectively. The epsilon(1)(f,T) and epsilon(2)(f,T) are successfully simulated by a RC circuit model. The complex plane of impedance, Z'-Z `', is simulated using a series network with a resistor R and a constant phase element. Through the analysis of epsilon(f,T) using the modified Debye model, two different relaxation time regimes separated by a characteristic temperature, T*, are identified. The temperature variation of R and C corresponding to the bulk and the parameter alpha from modified Debye fit lend support to this hypothesis. Interestingly, the T* compares with the Griffiths temperature for this compound observed in magnetic measurements. Though these results cannot be interpreted as magnetoelectric coupling, the relationship between lattice and magnetism is markedly clear. We assume that the observed features have their origin in the polar nanoregions which originate from the inherent cationic defect structure of double perovskites. Copyright (C) EPLA, 2013

An approximation to the QoS aware throughput region of a tree network under IEEE 802.15.4 CSMA/CA with application to wireless sensor network design

In the context of wireless sensor networks, we are motivated by the design of a tree network spanning a set of source nodes that generate packets, a set of additional relay nodes that only forward packets from the sources, and a data sink. We assume that the paths from the sources to the sink have bounded hop count, that the nodes use the IEEE 802.15.4 CSMA/CA for medium access control, and that there are no hidden terminals. In this setting, starting with a set of simple fixed point equations, we derive explicit conditions on the packet generation rates at the sources, so that the tree network approximately provides certain quality of service (QoS) such as end-to-end delivery probability and mean delay. The structures of our conditions provide insight on the dependence of the network performance on the arrival rate vector, and the topological properties of the tree network. Our numerical experiments suggest that our approximations are able to capture a significant part of the QoS aware throughput region (of a tree network), that is adequate for many sensor network applications. Furthermore, for the special case of equal arrival rates, default backoff parameters, and for a range of values of target QoS, we show that among all path-length-bounded trees (spanning a given set of sources and the data sink) that meet the conditions derived in the paper, a shortest path tree achieves the maximum throughput. (C) 2015 Elsevier B.V. All rights reserved.

Biochemical Characterization of Nonamer Binding Domain of RAG1 Reveals its Thymine Preference with Respect to Length and Position

RAG complex consisting of RAG1 and RAG2 is a site-specific endonuclease responsible for the generation of antigen receptor diversity. It cleaves recombination signal sequence (RSS), comprising of conserved heptamer and nonamer. Nonamer binding domain (NBD) of RAG1 plays a central role in the recognition of RSS. To investigate the DNA binding properties of the domain, NBD of murine RAG1 was cloned, expressed and purified. Electrophoretic mobility shift assays showed that NBD binds with high affinity to nonamer in the context of 12/23 RSS or heteroduplex DNA. NBD binding was specific to thymines when single stranded DNA containing poly A, C, G or T were used. Biolayer interferometry studies showed that poly T binding to NBD was robust and comparable to that of 12RSS. More than 23 nt was essential for NBD binding at homothymidine stretches. On a double-stranded DNA, NBD could bind to A:T stretches, but not G:C or random sequences. Although NBD is indispensable for sequence specific activity of RAGs, external supplementation of purified nonamer binding domain to NBD deleted cRAG1/cRAG2 did not restore its activity, suggesting that the overall domain architecture of RAG1 is important. Therefore, we define the sequence requirements of NBD binding to DNA.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.