Asymptotics of the invariant measure in mean field models with jumps

We consider the asymptotics of the invariant measure for the process of spatial distribution of N coupled Markov chains in the limit of a large number of chains. Each chain reflects the stochastic evolution of one particle. The chains are coupled through the dependence of transition rates on the spatial distribution of particles in the various states. Our model is a caricature for medium access interactions in wireless local area networks. Our model is also applicable in the study of spread of epidemics in a network. The limiting process satisfies a deterministic ordinary differential equation called the McKean-Vlasov equation. When this differential equation has a unique globally asymptotically stable equilibrium, the spatial distribution converges weakly to this equilibrium. Using a control-theoretic approach, we examine the question of a large deviation from this equilibrium.

A Calcium-Dependent Plasticity Rule for HCN Channels Maintains Activity Homeostasis and Stable Synaptic Learning

Theoretical and computational frameworks for synaptic plasticity and learning have a long and cherished history, with few parallels within the well-established literature for plasticity of voltage-gated ion channels. In this study, we derive rules for plasticity in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and assess the synergy between synaptic and HCN channel plasticity in establishing stability during synaptic learning. To do this, we employ a conductance-based model for the hippocampal pyramidal neuron, and incorporate synaptic plasticity through the well-established Bienenstock-Cooper-Munro (BCM)-like rule for synaptic plasticity, wherein the direction and strength of the plasticity is dependent on the concentration of calcium influx. Under this framework, we derive a rule for HCN channel plasticity to establish homeostasis in synaptically-driven firing rate, and incorporate such plasticity into our model. In demonstrating that this rule for HCN channel plasticity helps maintain firing rate homeostasis after bidirectional synaptic plasticity, we observe a linear relationship between synaptic plasticity and HCN channel plasticity for maintaining firing rate homeostasis. Motivated by this linear relationship, we derive a calcium-dependent rule for HCN-channel plasticity, and demonstrate that firing rate homeostasis is maintained in the face of synaptic plasticity when moderate and high levels of cytosolic calcium influx induced depression and potentiation of the HCN-channel conductance, respectively. Additionally, we show that such synergy between synaptic and HCN-channel plasticity enhances the stability of synaptic learning through metaplasticity in the BCM-like synaptic plasticity profile. Finally, we demonstrate that the synergistic interaction between synaptic and HCN-channel plasticity preserves robustness of information transfer across the neuron under a rate-coding schema. Our results establish specific physiological roles for experimentally observed plasticity in HCN channels accompanying synaptic plasticity in hippocampal neurons, and uncover potential links between HCN-channel plasticity and calcium influx, dynamic gain control and stable synaptic learning.

On Selection of Search Space Dimension in Compressive Sampling Matching Pursuit

Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications.

Subspace Pursuit Embedded in Orthogonal Matching Pursuit

Orthogonal Matching Pursuit (OMP) is a popular greedy pursuit algorithm widely used for sparse signal recovery from an undersampled measurement system. However, one of the main shortcomings of OMP is its irreversible selection procedure of columns of measurement matrix. i.e., OMP does not allow removal of the columns wrongly estimated in any of the previous iterations. In this paper, we propose a modification in OMP, using the well known Subspace Pursuit (SP), to refine the subspace estimated by OMP at any iteration and hence boost the sparse signal recovery performance of OMP. Using simulations we show that the proposed scheme improves the performance of OMP in clean and noisy measurement cases.

Unique Type II Halogen center dot center dot center dot Halogen Interactions in Pentafluorophenyl-Appended 2,2 `-Bithiazoles

Herein, we report the design and synthesis of 2,2'-bithiazole derivatives with efficient intermolecular halogen interactions. The single crystal X-ray diffraction studies revealed unique type-II halogen interactions in these derivatives. The shortest type-II F center dot center dot center dot F interactions within the distance of 2.67 angstrom, at an angle of 89.1 degrees and 174.2 degrees, was observed for the first time. The Gaussian calculations were performed to further establish predominant F center dot center dot center dot F interactions.

X-ray photoelectron spectroscopy: a unique tool to determine the internal heterostructure of nanoparticles

We review the existing literature on the application of X-ray photoelectron spectroscopy in the study of nanocrystals. The unique ability of this technique to provide quantitative and reliable descriptions of highly complex internal structures of a variety of nanocrystals has been discussed in detail. We show that an accurate description of the nanocrystal internal structure is crucial and a prerequisite to understand many different properties, particularly optical properties, of such nanocrystal systems. We also discuss limitations and future outlook of this technique.

Revisiting borylanilines: unique solid-state structures and insight into photophysical properties

The structure and photophysical properties of two known borylanilines, 4-(dimesitylboryl)aniline (1) and 4-(dimesitylboryl)-3,5-dimethylaniline (2), have been investigated. 1 and 2 have similar donor and acceptor centers but differ in their molecular conformations. Compounds 1 and 2 have been structurally characterized, and they exhibit a rare form of intermolecular N-H - - -pi electrostatic interactions. The structure and photophysical properties of 1 and 2 are discussed in the context of computational results.

Authentication using finger Knuckle prints

Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like the finger knuckle print (FKP) of a person is unique and secure. Finger knuckle print is a novel biometric trait and is not explored much for real-time implementation. In this paper, three different algorithms have been proposed based on this trait. The first approach uses Radon transform for feature extraction. Two levels of security are provided here and are based on eigenvalues and the peak points of the Radon graph. In the second approach, Gabor wavelet transform is used for extracting the features. Again, two levels of security are provided based on magnitude values of Gabor wavelet and the peak points of Gabor wavelet graph. The third approach is intended to authenticate a person even if there is a damage in finger knuckle position due to injury. The FKP image is divided into modules and module-wise feature matching is done for authentication. Performance of these algorithms was found to be much better than very few existing works. Moreover, the algorithms are designed so as to implement in real-time system with minimal changes.

Crystal growth and nonlinear optical properties of sodium D-isoascorbate monohydrate

Optical quality single crystals of sodium D-isoascorbate monohydrate were grown by a slow cooling technique. The crystal possesses a bulky prismatic morphology. Thermal analyses indicate that the crystals are stable up to 125 degrees C. The optical transmission window ranges from 307 nm to 1450 nm. The principal refractive indices have been measured employing Brewster's angle method. The crystallographic and the principal dielectric axes coincide with each other such that a lies along Z, b along X and c along Y. The optic axis is oriented 58 degrees (at 532 nm) to the crystallographic a axis in the XZ plane and the crystal is negative biaxial. Type 1 and type 2 phase matching curves are generated and experimentally verified. No polarization dependence of the light absorption was observed confirming the validity of Kleinman's symmetry conjecture, leading to a single nonvanishing nonlinear tensor component. According to Hobden's classification the crystal belongs to class 3. The crystal also exhibits second order noncollinear conic sections. The single shot and multiple shot surface laser damage thresholds are determined to be 32.7 GW cm(-2) and 6.5 GW cm(-2) respectively for 1064 nm radiation.

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-).

Block Sparse Estimator for Grid Matching in Single Snapshot DoA Estimation

In this work, the grid mismatch problem for a single snapshot direction of arrival estimation problem is studied. We derive a Bayesian Cramer-Rao bound for the grid mismatch problem with the errors in variables model and propose a block sparse estimator for grid matching and sparse recovery.

Stable and Potent Analogues Derived from the Modification of the Dicarbonyl Moiety of Curcumin

Curcumin has shown promising therapeutic utilities for many diseases, including cancer; however, its clinical application is severely limited because of its poor stability under physiological conditions. Here we find that curcumin also loses its activity instantaneously in a reducing environment. Curcumin can exist in solution as a tautomeric mixture of keto and enol forms, and the enol form was found to be responsible for the rapid degradation of the compound. To increase the stability of curcumin, several analogues were synthesized in which the diketone moiety of curcumin was replaced by isoxazole (compound 2) and pyrazole (compound 3) groups. Isoxazole and pyrazole curcumins were found to be extremely stable at physiological pH, in addition to reducing atmosphere, and they can kill cancer cells under serum-depleted condition. Using molecular modeling, we found that both compounds 2 and 3 could dock to the same site of tubulin as the parent molecule, curcumin. Interestingly, compounds 2 and 3 also show better free radical scavenging activity than curcumin. Altogether, these results strongly suggest that compounds 2 and 3 could be good replacements for curcumin in future drug development.

Nucleation of a Stable Solid from Melt in the Presence of Multiple Metastable Intermediate Phases: Wetting, Ostwald's Step Rule, and Vanishing Polymorphs

In many systems, nucleation of a stable solid may occur in the presence of other (often more than one) metastable phases. These may be polymorphic solids or even liquid phases. Sometimes, the metastable phase might have a lower free energy minimum than the liquid but higher than the stable-solid-phase minimum and have characteristics in between the parent liquid and the globally stable solid phase. In such cases, nucleation of the solid phase from the melt may be facilitated by the metastable phase because the latter can ``wet'' the interface between the parent and the daughter phases, even though there may be no signature of the existence of metastable phase in the thermodynamic properties of the parent liquid and the stable solid phase. Straightforward application of classical nucleation theory (CNT) is flawed here as it overestimates the nucleation barrier because surface tension is overestimated (by neglecting the metastable phases of intermediate order) while the thermodynamic free energy gap between daughter and parent phases remains unchanged. In this work, we discuss a density functional theory (DFT)-based statistical mechanical approach to explore and quantify such facilitation. We construct a simple order-parameter-dependent free energy surface that we then use in DFT to calculate (i) the order parameter profile, (ii) the overall nucleation free energy barrier, and (iii) the surface tension between the parent liquid and the metastable solid and also parent liquid and stable solid phases. The theory indeed finds that the nucleation free energy barrier can decrease significantly in the presence of wetting. This approach can provide a microscopic explanation of the Ostwald step rule and the well-known phenomenon of ``disappearing polymorphs'' that depends on temperature and other thermodynamic conditions. Theory reveals a diverse scenario for phase transformation kinetics, some of which may be explored via modem nanoscopic synthetic methods.

Adaptive selection of search space in look ahead orthogonal matching pursuit

Compressive Sensing theory combines the signal sampling and compression for sparse signals resulting in reduction in sampling rate and computational complexity of the measurement system. In recent years, many recovery algorithms were proposed to reconstruct the signal efficiently. Look Ahead OMP (LAOMP) is a recently proposed method which uses a look ahead strategy and performs significantly better than other greedy methods. In this paper, we propose a modification to the LAOMP algorithm to choose the look ahead parameter L adaptively, thus reducing the complexity of the algorithm, without compromising on the performance. The performance of the algorithm is evaluated through Monte Carlo simulations.

Projection-based atom selection in orthogonal matching pursuit for compressive sensing

For compressive sensing, we endeavor to improve the atom selection strategy of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlying support set progressively through iterations, we use a least squares solution based atom selection method. From a set of promising atoms, the choice of an atom is performed through a new method that uses orthogonal projection along-with a standard matched filter. Through experimental evaluations, the effect of projection based atom selection strategy is shown to provide a significant improvement for the support set recovery performance, in turn, the compressive sensing recovery.