Multichannel-Emissive V-Shaped Boryl-BODIPY Dyads: Synthesis, Structure, and Remarkably Diverse Response toward Fluoride

Three new V-shaped boryl-BODIPY dyads (1-3) were synthesized and structurally characterized. Compounds 1-3 are structurally close molecular siblings differing only in the number of methyl substituents on the BODIPY moiety that were found to play a major role in determining their photophysical behavior. The dyads show rare forms of multiple-channel emission characteristics arising from different extents of electronic energy transfer (EET) processes between the two covalently linked fluorescent chromophores (borane and BODIPY units). Insights into the origin and nature of their emission behavior were gained from comparison with closely related model molecular systems and related photophysical investigations. Because of the presence of the Lewis acidic triarylborane moiety, the dyads function as highly selective and sensitive fluoride sensors with vastly different response behaviors. When fluoride binds to the tricoordinate borane center, dyad 1 shows gradual quenching of its BODIPY-dominated emission due to the ceasing of the (borane to BODIPY) EET process. Dyad 2 shows a ratiometric fluorescence response for fluoride ions. Dyad 3 forms fluoride-induced nanoaggregates that result in fast and effective quenching of its fluorescence intensity just for similar to 0.3 ppm of analyte (i.e., 0.1 equiv 0.26 ppm of fluoride). The small structural alterations in these three structurally close dyads (1 - 3) result in exceptionally versatile and unique photophysical behaviors and remarkably diverse responses toward a single analyte, i.e., fluoride ion.

Colorimetric anion sensor based on receptor having indole- and thiourea-binding sites

A new colorimetric sensor L containing nitro-substituted indole and bisthiocarbonohydrazone units for selective fluoride and acetate ions is designed and synthesized. The receptor L shows well-defined color change in the visible region of the spectrum with an absorption band at similar to 515 nm and 506 nm, respectively, for the F- and CH3COO- ions in an acetonitrile solution. Job's plots indicated the formation of 1 : 1 (L with CH3COO-) and 1 : 2 (L with F-) complexes. The interaction of L with the F- ion undergoes a deprotonation process and release of HX2](-), whereas with the CH3COO- ion, it forms a stable LH2(...)X](-) complex. The relative affinities of the anions with L are rationalized using computational studies.

Design and synthesis of new low band gap organic semiconductors for photovoltaic applications

Donor-acceptor (D-A) conjugated polymers have attracted a good deal of attention in recent years. In D-A systems, the introduction of electron withdrawing groups reduces E-g by lowering the LUMO levels whereas, the introduction of electron donating groups reduces E-g by raising the HOMO levels. Also, conjugated polymers with desired HOMO and LUMO energy levels could be obtained by the proper selection of donor and acceptor units. Because of this reason, D-A conjugated polymers are emerging as promising materials particularly for polymer light emitting diodes (PLEDs) and polymer solar cells (PSCs). We report the design and synthesis of four new narrow band gap donor-acceptor (D-A) conjugated polymers, PTCNN, PTCNF, PTCNV and PTCNO, containing electron donating 3,4-didodecyloxythiophene and electron accepting cyanovinylene units. The effects of further addition of electron donating and electron withdrawing groups to the repeating unit of a D-A conjugated polymer (PTCNN) on its optical and electrochemical properties are discussed. The studies revealed that the nature of D and A units as well as the extent of alternate D-A structure influences the optical and the electrochemical properties of the polymers. All the polymers are thermally stable up to a temperature of 300 degrees C under nitrogen atmosphere. The electrochemical studies revealed that the polymers possess low-lying HOMO energy levels and low-lying LUMO energy levels. In the UV-Vis absorption study, the polymer films displayed broad absorption in the wavelength region of 400-700 nm. The polymers exhibited low optical band gaps in the range 1.70 - 1.77 eV.

An Advanced Gate Driver for Insulated Gate Bipolar Transistors to Eliminate Dead-time Induced Distortions in Inverter Output

Dead-time is introduced between the gating signals to the top and bottom switches in a voltage source inverter (VSI) leg, to prevent shoot through fault due to the finite turn-off times of IGBTs. The dead-time results in a delay when the incoming device is an IGBT, resulting in error voltage pulses in the inverter output voltage. This paper presents the design, fabrication and testing of an advanced gate driver, which eliminates dead-time and consequent output distortion. Here, the gating pulses are generated such that the incoming IGBT transition is not delayed and shoot-through is also prevented. The various logic units of the driver card and fault tolerance of the driver are verified through extensive tests on different topologies such as chopper, half-bridge and full-bridge inverter, and also at different conditions of load. Experimental results demonstrate the improvement in the load current waveform quality with the proposed circuit, on account of elimination of dead-time.

Effect of Chalcogens on Electronic and Photophysical Properties of Vinylene-Based Diketopyrrolopyrrole Copolymers

Three vinylene linked diketopyrrolopyrrole based donor acceptor (D-A) copolymers have been synthesized with phenyl, thienyl, and selenyl units as donors. Optical and electronic properties were investigated with UV-vis absorption spectroscopy, cyclic voltammetry, near edge X-ray absorption spectroscopy, organic field effect transistor (OFET) measurements, and density functional theory (DFT) calculations. Optical and electrochemical band gaps decrease in the order phenyl, thienyl, and selenyl. Only phenyl-based polymers are nonplanar, but the main contributor to the larger band gap is electronic, not structural effects. Thienyl and selenyl polymers exhibit ambipolar charge transport but with higher hole than electron mobility. Experimental and theoretical results predict the selenyl system to have the best transport properties, but OFET measurements prove the thienyl system to be superior with p-channel mobility as high as 0.1 cm(2) V-1 s(-1).

Spectral Clustering with Jensen-type kernels and their multi-point extensions

Motivated by multi-distribution divergences, which originate in information theory, we propose a notion of `multipoint' kernels, and study their applications. We study a class of kernels based on Jensen type divergences and show that these can be extended to measure similarity among multiple points. We study tensor flattening methods and develop a multi-point (kernel) spectral clustering (MSC) method. We further emphasize on a special case of the proposed kernels, which is a multi-point extension of the linear (dot-product) kernel and show the existence of cubic time tensor flattening algorithm in this case. Finally, we illustrate the usefulness of our contributions using standard data sets and image segmentation tasks.

A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

Triarylborane conjugated dicyanovinyl chromophores: intriguing optical properties and colorimetric anion discrimination

Three new triarylborane conjugated dicyanovinyl chromophores (Mes(2)B-pi-donor-DCV); donor: N-methyldiphenylamine (1) and triphenylamine (2 and 3 with two BMes(2) substitutions]) of type A-D-A (acceptor-donor- acceptor) are reported. Compounds 1-3 exhibit intense charge transfer (CT) absorption bands in the visible region. These absorption peaks are combination CT bands of the amine donor to both the BMes(2) and DCV units. This inference was supported by theoretical studies. Compound 1 shows weak fluorescence compared to 2 and 3. The discrimination of fluoride and cyanide ions is essential in the case of triarylborane (TAB) based anion sensors as a similar response is given towards both the anions. Anion binding studies of 1, 2 and 3 showed that fluoride ions bind selectively to the boron centre and block the corresponding CT transition (donor to BMes(2)) leaving the other CT transition to be red shifted. On the other hand, cyanide ions bind with both the receptor sites and stop both the CT transition processes and hence a different colorimetric response was noted. The binding of F-/CN- induces colour changes in the visible region of the electronic spectra of 2 and 3, which allows for the naked-eye detection of F- and CN- ions. The anion binding mechanisms are established using NMR titration experiments.

Speaker verification based on the fusion of speech acoustics and inverted articulatory signals

We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.

Length scales in glass-forming liquids and related systems: a review

The central problem in the study of glass-forming liquids and other glassy systems is the understanding of the complex structural relaxation and rapid growth of relaxation times seen on approaching the glass transition. A central conceptual question is whether one can identify one or more growing length scale(s) associated with this behavior. Given the diversity of molecular glass-formers and a vast body of experimental, computational and theoretical work addressing glassy behavior, a number of ideas and observations pertaining to growing length scales have been presented over the past few decades, but there is as yet no consensus view on this question. In this review, we will summarize the salient results and the state of our understanding of length scales associated with dynamical slow down. After a review of slow dynamics and the glass transition, pertinent theories of the glass transition will be summarized and a survey of ideas relating to length scales in glassy systems will be presented. A number of studies have focused on the emergence of preferred packing arrangements and discussed their role in glassy dynamics. More recently, a central object of attention has been the study of spatially correlated, heterogeneous dynamics and the associated length scale, studied in computer simulations and theoretical analysis such as inhomogeneous mode coupling theory. A number of static length scales have been proposed and studied recently, such as the mosaic length scale discussed in the random first-order transition theory and the related point-to-set correlation length. We will discuss these, elaborating on key results, along with a critical appraisal of the state of the art. Finally we will discuss length scales in driven soft matter, granular fluids and amorphous solids, and give a brief description of length scales in aging systems. Possible relations of these length scales with those in glass-forming liquids will be discussed.

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.

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(sigma(2)) operations per pixel, where sigma is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary sigma (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the so-called Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.