Phase synchronization in brain networks derived from correlation between probabilities of recurrences in functional MRI data

It is increasingly being recognized that resting state brain connectivity derived from functional magnetic resonance imaging (fMRI) data is an important marker of brain function both in healthy and clinical populations. Though linear correlation has been extensively used to characterize brain connectivity, it is limited to detecting first order dependencies. In this study, we propose a framework where in phase synchronization (PS) between brain regions is characterized using a new metric ``correlation between probabilities of recurrence'' (CPR) and subsequent graph-theoretic analysis of the ensuing networks. We applied this method to resting state fMRI data obtained from human subjects with and without administration of propofol anesthetic. Our results showed decreased PS during anesthesia and a biologically more plausible community structure using CPR rather than linear correlation. We conclude that CPR provides an attractive nonparametric method for modeling interactions in brain networks as compared to standard correlation for obtaining physiologically meaningful insights about brain function.

A new approach for understanding ion transport in glasses; example of complex alkali diborate glasses containing lead, bismuth and tellurium oxides

Mechanism of ion transport in glasses continues to be incompletely understood. Several of the theoretical models in vogue fail to rationalize conductivity behaviour when d.c. and a.c. measurements are considered together. While they seem to involve the presence of at least two components in d.c. activation energy, experiments fail to reveal that feature. Further, only minor importance is given to the influence of structure of the glass on the ionic conductivity behaviour. In this paper, we have examined several general aspects of ion transport taking the example of ionically conducting glasses in pseudo binary, yNa(2)B(4)O(7)center dot(1-y) M (a) O (b) (with y = 0 center dot 25-0 center dot 79 and M (a) O (b) = PbO, TeO2 and Bi2O3) system of glasses which have also been recently characterized. Ion transport in them has been studied in detail. We have proposed that non-bridging oxygen (NBO) participation is crucial to the understanding of the observed conductivity behaviour. NBO-BO switching is projected as the first important step in ion transport and alkali ion jump is a subsequent event with a characteristically lower barrier which is, therefore, not observed in any study. All important observations in d.c. and a.c. transport in glasses are found consistent with this model.

Channel training signal design for reciprocal multiple antenna systems with beamforming

Fast and efficient channel estimation is key to achieving high data rate performance in mobile and vehicular communication systems, where the channel is fast time-varying. To this end, this work proposes and optimizes channel-dependent training schemes for reciprocal Multiple-Input Multiple-Output (MIMO) channels with beamforming (BF) at the transmitter and receiver. First, assuming that Channel State Information (CSI) is available at the receiver, a channel-dependent Reverse Channel Training (RCT) signal is proposed that enables efficient estimation of the BF vector at the transmitter with a minimum training duration of only one symbol. In contrast, conventional orthogonal training requires a minimum training duration equal to the number of receive antennas. A tight approximation to the capacity lower bound on the system is derived, which is used as a performance metric to optimize the parameters of the RCT. Next, assuming that CSI is available at the transmitter, a channel-dependent forward-link training signal is proposed and its power and duration are optimized with respect to an approximate capacity lower bound. Monte Carlo simulations illustrate the significant performance improvement offered by the proposed channel-dependent training schemes over the existing channel-agnostic orthogonal training schemes.

On Wilking's criterion for the Ricci flow

Wilking has recently shown that one can associate a Ricci flow invariant cone of curvature operators , which are nonnegative in a suitable sense, to every invariant subset . In this article we show that if is an invariant subset of such that is closed and denotes the cone of curvature operators which are positive in the appropriate sense then one of the two possibilities holds: (a) The connected sum of any two Riemannian manifolds with curvature operators in also admits a metric with curvature operator in (b) The normalized Ricci flow on any compact Riemannian manifold with curvature operator in converges to a metric of constant positive sectional curvature. We also point out that if is an arbitrary subset, then is contained in the cone of curvature operators with nonnegative isotropic curvature.

A study on pulsed laser deposited metallic spin valves

In the recent past conventional Spin Valve (SV) structures are gaining growing interest over Tunneling Magneto-resistance (TMR) because of its preference due to low RA product in hard disc read head sensor applications. Pulsed Laser Deposited (PLD) SV and Pseudo Spin Valve (PSV) samples are grown at room temperature with moderately high MR values using simple FM/NM/FM/AFM structure. Although PLD is not a popular technique to grow metallic SVs because of expected large intermixing of the interfaces, particulate formation, still by suitably adjusting the deposition parameters we could get exchange bias (EB) as well as 2-3% MR of these SVs in the Current In Plane (CIP) geometry. Exchange Bias, which sets in even without applying magnetic field during deposition observed by using SQUID magnetometry as well as by MR measurements. Angular variation of the MR reveals four-fold anisotropy of the hard layer (Co) which becomes two-fold in presence of an adjacent AFM layer.

Network properties of decoys and CASP predicted models: a comparison with native protein structures

Protein structure space is believed to consist of a finite set of discrete folds, unlike the protein sequence space which is astronomically large, indicating that proteins from the available sequence space are likely to adopt one of the many folds already observed. In spite of extensive sequence-structure correlation data, protein structure prediction still remains an open question with researchers having tried different approaches (experimental as well as computational). One of the challenges of protein structure prediction is to identify the native protein structures from a milieu of decoys/models. In this work, a rigorous investigation of Protein Structure Networks (PSNs) has been performed to detect native structures from decoys/ models. Ninety four parameters obtained from network studies have been optimally combined with Support Vector Machines (SVM) to derive a general metric to distinguish decoys/models from the native protein structures with an accuracy of 94.11%. Recently, for the first time in the literature we had shown that PSN has the capability to distinguish native proteins from decoys. A major difference between the present work and the previous study is to explore the transition profiles at different strengths of non-covalent interactions and SVM has indeed identified this as an important parameter. Additionally, the SVM trained algorithm is also applied to the recent CASP10 predicted models. The novelty of the network approach is that it is based on general network properties of native protein structures and that a given model can be assessed independent of any reference structure. Thus, the approach presented in this paper can be valuable in validating the predicted structures. A web-server has been developed for this purpose and is freely available at http://vishgraph.mbu.iisc.ernet.in/GraProStr/PSN-QA.html.

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.

Gibbs energy of formation of Ca7V4O17

Thermodynamic properties of Ca7V4O17 are measured for the first time using a solid-state electrochemical cell incorporating single crystal of CaF2 as the electrolyte over the temperature range from (900 to 1175) K. An equimolar mixture of CaO and CaF2 is used as the reference electrode and a mixture of Ca3V2O8, Ca7V4O17 and CaF2 as the measuring electrode. Both the electrodes are placed under flowing oxygen gas at ambient pressure. The standard Gibbs energy change for the reaction: 2Ca(3)V(2)O(8) + CaO -> Ca7V4O17; which is related to the chemical potential of CaO in the two-phase region (Ca3V2O8 + Ca7V4O17) of the pseudo-binary system CaO + V2O5, is obtained from the electromotive force of the cell as: Delta(r)G(o) +/- 127/(J . mol(-1)) = Delta mu(CaO) = -11453 + 8.273(T/K). The derived standard enthalpy of formation of Ca7V4O17 from elements in their normal standard states is ( 8208.97 +/- 8) kJ . mol (1) and its standard entropy is (560.05 +/- 7.5) J . K (1) . mol (1), both at T = 298.15 K. The results indicate that Ca7V4O17 decomposes into Ca3V2O8 and CaO at T = (1384 +/- 3) K.

Metal doped nanosized titania used for the photocatalytic degradation of rhodamine B dye under visible-light

Metal-doped anatase nanosized titania photocatalysts were successfully synthesized using a sal gel process. Different amounts of the dopants (0.2, 0.4, 0.6, 0.8 and 1.0%) of the metals (Ag, Ni, Co and Pd) were utilized. The UV-Vis spectra (solid state diffuse reflectance spectra) of the doped nanoparticles exhibited a red shift in the absorption edge as a result of metal doping. The metal-doped nanoparticles were investigated for their photocatalytic activity under visible-light irradiation using Rhodamine B (Rh B) as a control pollutant. The results obtained indicate that the metal-doped titania had the highest activity at 0.4% metal loading. The kinetic models revealed that the photodegradation of Rh B followed a pseudo first order reaction. From ion chromatography (IC) analysis the degradation by-products Rhodamine B fragments were found to be acetate, chloride, nitrite, carbonate and nitrate ions.

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

Solvent-templated supramolecular isomerism in 2D coordination polymer constructed by (Ni2CoII)-Co-II nodes and dicyanamido spacers: drastic change in magnetic behaviours

Two heterometallic coordination polymers (CPs) have been prepared using (NiL)-L-II](2)Co-II (where H2L = N,N'-bis(salicylidene)-1,3-propanediamine) as nodes and dicyanamido spacers by varying the solvent for synthesis. Structural characterizations revealed that methanol assisted the formation of a two-dimensional (4,4) connected rhombic grid network of (NiL)(2)Co(NCNCN)2](infinity) (1a) whereas relatively less polar acetonitrile afforded a different superstructure {(NiL)(2)Co(NCNCN)(2)]center dot CH3CN}(infinity) (1b) with a two-dimensional (4,4) connected square grid network. The presence of acetonitrile molecules in the structure of 1b seems to change the spatial orientation of the terminal metalloligands NiL] from pseudo-eclipsed in 1a to staggered-like in 1b around the central Co(II). These structural changes in the nodes together with the conformationally flexible dicyanamido spacers, which are cis coordinated to the Co(II) in both trinuclear units, led to the differences in the final 2D network. Variable-temperature magnetic susceptibility measurements revealed that this supramolecular isomerism led to a drastic transition from spin-frustrated antiferromagnetism for 1a to a dominant ferromagnetic behaviour for 1b. The geometrical differences in Ni2Co coordination clusters (CCs) which are scalene triangular in 1a but nearly linear in 1b, are held responsible for the changes of the magnetic properties. The DFT calculations of exchange interactions between metal centres provide a clear evidence of the role played by the fundamental geometrical factors on the nature and magnitude of the magnetic coupling in these pseudo-polymorphic CPs.

EFFECT OF OFF-STOICHIOMETRY AND TERNARY ADDITIONS ON PLANAR FAULT ENERGIES IN Ni3Al

First principles calculations were done to evaluate the lattice parameter, cohesive energy and stacking fault energies of ordered gamma' (Ll(2)) precipitates in superalloys as a function of composition. It was found that addition of Ti and Ta lead to an increase in lattice parameter and decrease in cohesive energy, while Ni antisites had the opposite effect. Ta and Ti addition to stoichiometric Ni3Al resulted in an initial increase in the energies of APB((111)), CSF(111), APB((001)) and SISF(111). However, at higher concentrations, the fault energies decreased. Addition of Ni antisites decreased the energy of all four faults monotonically. A model based on nearest neighbor bonding was used for Ni-3(Al, Ta), Ni-3(Al, Ti) and Ni-3(Al, Ni) pseudo-binary systems and extended to pseudo- ternary Ni-3(Al, Ta, Ni) and Ni-3(Al, Ti, Ni) systems. Recipes were developed for predicting lattice parameters, cohesive energies and fault energies in pseudo- ternary systems on the basis of coefficients derived from simpler pseudobinary systems. The model predictions were found to be in good agreement with first principles calculations for lattice parameters, cohesive energies, and energies of APB((111)) and CSF(111).

Hardness results for computing optimal locally Gabriel graphs

Delaunay and Gabriel graphs are widely studied geo-metric proximity structures. Motivated by applications in wireless routing, relaxed versions of these graphs known as Locally Delaunay Graphs (LDGs) and Lo-cally Gabriel Graphs (LGGs) have been proposed. We propose another generalization of LGGs called Gener-alized Locally Gabriel Graphs (GLGGs) in the context when certain edges are forbidden in the graph. Unlike a Gabriel Graph, there is no unique LGG or GLGG for a given point set because no edge is necessarily in-cluded or excluded. This property allows us to choose an LGG/GLGG that optimizes a parameter of interest in the graph. We show that computing an edge max-imum GLGG for a given problem instance is NP-hard and also APX-hard. We also show that computing an LGG on a given point set with dilation ≤k is NP-hard. Finally, we give an algorithm to verify whether a given geometric graph G= (V, E) is a valid LGG.

Maximizing transported data in a wireless sensor network: how much can the network transport before partition?

We consider a scenario where the communication nodes in a sensor network have limited energy, and the objective is to maximize the aggregate bits transported from sources to respective destinations before network partition due to node deaths. This performance metric is novel, and captures the useful information that a network can provide over its lifetime. The optimization problem that results from our approach is nonlinear; however, we show that it can be converted to a Multicommodity Flow (MCF) problem that yields the optimal value of the metric. Subsequently, we compare the performance of a practical routing strategy, based on Node Disjoint Paths (NDPs), with the ideal corresponding to the MCF formulation. Our results indicate that the performance of NDP-based routing is within 7.5% of the optimal.

A Multicast Authentication Protocol (MAP) for Dynamic Multicast Groups in Wireless Networks

In this paper, we have proposed a centralized multicast authentication protocol (MAP) for dynamic multicast groups in wireless networks. In our protocol, a multicast group is defined only at the time of the multicasting. The authentication server (AS) in the network generates a session key and authenticates it to each of the members of a multicast group using the computationally inexpensive least common multiple (LCM) method. In addition, a pseudo random function (PRF) is used to bind the secret keys of the network members with their identities. By doing this, the AS is relieved from storing per member secrets in its memory, making the scheme completely storage scalable. The protocol minimizes the load on the network members by shifting the computational tasks towards the AS node as far as possible. The protocol possesses a membership revocation mechanism and is protected against replay attack and brute force attack. Analytical and simulation results confirm the effectiveness of the proposed protocol.