Semiconductor-like Sensitivity in Metallic Ultrathin Gold Nanowire-Based Sensors

Due to the ease of modification of electronic structure upon analyte adsorption, semiconductors have been the preferred materials as chemical sensors. At reduced dimension, however, the sensitivity of semiconductor-based sensors deteriorates significantly due to passivation, and often by increased band gap caused by quantum confinement. Using first-principles density functional theory combined with Boltzmann transport calculations, we demonstrate semiconductor-like sensitivity toward chemical species in ultrathin gold nanowires (AuNWs). The sensing mechanism is governed by the modification of the electronic structure of the AuNW as well as scattering of the charge carriers by analyte adsorption. Most importantly, the sensitivity exhibits a linear relationship with the electron affinities of the respective analytes. Based on this relationship, we propose an empirical parameter, which can predict an analyte-specific sensitivity of a AuNW, rendering them as effective sensors for a wide range of chemical an alytes.

Halogen Bonds in Crystal Engineering: Like Hydrogen Bonds yet Different

CONSPECTUS: The halogen bond is an attractive interaction in which an electrophilic halogen atom approaches a negatively polarized species. Short halogen atom contacts in crystals have been known for around 50 years. Such contacts are found in two varieties: type I, which is symmetrical, and type II, which is bent. Both are influenced by geometric and chemical considerations. Our research group has been using halogen atom interactions as design elements in crystal engineering, for nearly 30 years. These interactions include halogen center dot center dot center dot halogen interactions (X center dot center dot center dot X) and halogen center dot center dot center dot heteroatom interactions (X center dot center dot center dot B). Many X center dot center dot center dot X and almost all X center dot center dot center dot B contacts can be classified as halogen bonds. In this Account, we illustrate examples of crystal engineering where one can build up from previous knowledge with a focus that is provided by the modern definition of the halogen bond. We also comment on the similarities and differences between halogen bonds and hydrogen bonds. These interactions are similar because the protagonist atoms halogen and hydrogen are both electrophilic in nature. The interactions are distinctive because the size of a halogen atom is of consequence when compared with the atomic sizes of, for example, C, N, and O, unlike that of a hydrogen atom. Conclusions may be drawn pertaining to the nature of X center dot center dot center dot X interactions from the Cambridge Structural Database (CSD). There is a clear geometric and chemical distinction between type I and type II, with only type II being halogen bonds. Cl/Br isostructurality is explained based on a geometric model. In parallel, experimental studies on 3,4-dichlorophenol and its congeners shed light on the nature of halogen center dot center dot center dot halogen interactions and reveal the chemical difference between Cl and Br. Variable temperature studies also show differences between type I and type II contacts. In terms of crystal design, halogen bonds offer a unique opportunity in the strength, atom size and interaction gradation; this may be used in the design of ternary cocrystals. Structural modularity in which an entire crystal structure is defined as a combination of modules is rationalized on the basis of the intermediate strength of a halogen bond. The specific directionality of the halogen bond makes it a good tool to achieve orthogonality in molecular crystals. Mechanical properties can be tuned systematically by varying these orthogonally oriented halogen center dot center dot center dot halogen interactions. In a further development, halogen bonds are shown to play a systematic role in organization of LSAMs (long range synthon aufbau module), which are bigger structural units containing multiple synthons. With a formal definition in place, this may be the right time to look at differences between halogen bonds and hydrogen bonds and exploit them in more subtle ways in crystal engineering.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

A shortest path tree based algorithm for relay placement in a wireless sensor network and its performance analysis

In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given potential locations, while meeting a quality of service (QoS) objective specified as a hop count bound for paths from the sources to the BS. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard. For this problem, we propose a polynomial time approximation algorithm based on iteratively constructing shortest path trees and heuristically pruning away the relay nodes used until the hop count bound is violated. Results show that the algorithm performs efficiently in various randomly generated network scenarios; in over 90% of the tested scenarios, it gave solutions that were either optimal or were worse than optimal by just one relay. We then use random graph techniques to obtain, under a certain stochastic setting, an upper bound on the average case approximation ratio of a class of algorithms (including the proposed algorithm) for this problem as a function of the number of source nodes, and the hop count bound. To the best of our knowledge, the average case analysis is the first of its kind in the relay placement literature. Since the design is based on a light traffic model, we also provide simulation results (using models for the IEEE 802.15.4 physical layer and medium access control) to assess the traffic levels up to which the QoS objectives continue to be met. (C) 2014 Elsevier B.V. All rights reserved.

Modified Adomian Decomposition Method for Van der Pol equations

In the paper, the well known Adomian Decomposition Method (ADM) is modified to solve the parabolic equations. The present method is quite different than the numerical method. The results are compared with the existing exact or analytical method. The already known existing Adomian Decomposition Method is modified to improve the accuracy and convergence. Thus, the modified method is named as Modified Adomian Decomposition Method (MADM). The Modified Adomian Decomposition Method results are found to converge very quickly and are more accurate compared to ADM and numerical methods. MADM is quite efficient and is practically well suited for use in these problems. Several examples are given to check the reliability of the present method. Modified Adomian Decomposition Method is a non-numerical method which can be adapted for solving parabolic equations. In the current paper, the principle of the decomposition method is described, and its advantages are shown in the form of parabolic equations. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Survey of vector-like fermion extensions of the Standard Model and their phenomenological implications

With the renewed interest in vector-like fermion extensions of the Standard Model, we present here a study of multiple vector-like theories and their phenomenological implications. Our focus is mostly on minimal flavor conserving theories that couple the vector-like fermions to the SM gauge fields and mix only weakly with SM fermions so as to avoid flavor problems. We present calculations for precision electroweak and vector-like state decays, which are needed to investigate compatibility with currently known data. We investigate the impact of vector-like fermions on Higgs boson production and decay, including loop contributions, in a wide variety of vector-like extensions and their parameter spaces.

The WNT Signaling Pathway Contributes to Dectin-1-Dependent Inhibition of Toll-Like Receptor-Induced Inflammatory Signature

Macrophages regulate cell fate decisions during microbial challenges by carefully titrating signaling events activated by innate receptors such as dectin-1 or Toll-like receptors (TLRs). Here, we demonstrate that dectin-1 activation robustly dampens TLR-induced proinflammatory signature in macrophages. Dectin-1 induced the stabilization of beta-catenin via spleen tyrosine kinase (Syk)-reactive oxygen species (ROS) signals, contributing to the expression of WNT5A. Subsequently, WNT5A-responsive protein inhibitors of activated STAT (PIAS-1) and suppressor of cytokine signaling 1 (SOCS-1) mediate the downregulation of IRAK-1, IRAK-4, and MyD88, resulting in decreased expression of interleukin 12 (IL-12), IL-1 beta, and tumor necrosis factor alpha (TNF-alpha). In vivo activation of dectin-1 with pathogenic fungi or ligand resulted in an increased bacterial burden of Mycobacteria, Klebsiella, Staphylococcus, or Escherichia, with a concomitant decrease in TLR-triggered proinflammatory cytokines. All together, our study establishes a new role for dectin-1-responsive inhibitory mechanisms employed by virulent fungi to limit the proinflammatory environment of the host.

Wind speed prediction using spatio-temporal covariance

High wind poses a number of hazards in different areas such as structural safety, aviation, and wind energy-where low wind speed is also a concern, pollutant transport, to name a few. Therefore, usage of a good prediction tool for wind speed is necessary in these areas. Like many other natural processes, behavior of wind is also associated with considerable uncertainties stemming from different sources. Therefore, to develop a reliable prediction tool for wind speed, these uncertainties should be taken into account. In this work, we propose a probabilistic framework for prediction of wind speed from measured spatio-temporal data. The framework is based on decompositions of spatio-temporal covariance and simulation using these decompositions. A novel simulation method based on a tensor decomposition is used here in this context. The proposed framework is composed of a set of four modules, and the modules have flexibility to accommodate further modifications. This framework is applied on measured data on wind speed in Ireland. Both short-and long-term predictions are addressed.

Electronically nonadiabatic decomposition mechanisms of clusters of zinc and dimethylnitramine

Electronically nonadiabatic decomposition mechanisms of dimethylnitramine (DMNA) in presence of zinc metal clusters are explored. Complete active space self-consistent field (CASSCF) calculation is employed for DMNA-Zn and ONIOM (Our own N-layered integrated molecular orbital and molecular mechanics) methodology is coupled with CASSCF methodology for DMNA-Zn-10 cluster. Present computational results show that DMNA-Zn clusters undergo electronically nonadiabatic reactions, rendering nitro-nitrite isomerization followed by NO elimination. The overall reactions are also found to be highly exothermic in nature. This is the first report on electronically nonadiabatic decomposition pathways of DMNA-Zn-n neutral clusters. (C) 2014 Elsevier B.V. All rights reserved.

And yet it shrinks: A novel method for correcting bias in forest tree growth estimates caused by water-induced fluctuations

Accuracy in tree woody growth estimates is important to global carbon budget estimation and climate-change science. Tree growth in permanent sampling plots (PSPs) is commonly estimated by measuring stem diameter changes, but this method is susceptible to bias resulting from water-induced reversible stem shrinkage. In the absence of bias correction, temporal variability in growth is likely to be overestimated and incorrectly attributed to fluctuations in resource availability, especially in forests with high seasonal and inter-annual variability in water. We propose and test a novel approach for estimating and correcting this bias at the community level. In a 50-ha PSP from a seasonally dry tropical forest in southern India, where tape measurements have been taken every four years from 1988 to 2012, for nine trees we estimated bias due to reversible stem shrinkage as the difference between woody growth measured using tree rings and that estimated from tape. We tested if the bias estimated from these trees could be used as a proxy to correct bias in tape-based growth estimates at the PSP scale. We observed significant shrinkage-related bias in the growth estimates of the nine trees in some censuses. This bias was strongly linearly related to tape-based growth estimates at the level of the PSP, and could be used as a proxy. After bias was corrected, the temporal variance in growth rates of the PSP decreased, while the effect of exceptionally dry or wet periods was retained, indicating that at least a part of the temporal variability arose from reversible shrinkage-related bias. We also suggest that the efficacy of the bias correction could be improved by measuring the proxy on trees that belong to different size classes and census timing, but not necessarily to different species. Our approach allows for reanalysis - and possible reinterpretation of temporal trends in tree growth, above ground biomass change, or carbon fluxes in forests, and their relationships with resource availability in the context of climate change. (C) 2014 Elsevier B.V. All rights reserved.

Simple chemical aqueous synthesis of dahlia nanoflower consisting of finger-like ZnO nanorods and observation of stable ultraviolet photoluminescence emission

In this work, we have reported the synthesis of dahlia flower-like ZnO nanostructures consisting of human finger-like nanorods by the hydrothermal method at 120 degrees C and without using any capping agent. Optical properties of the samples, including UV-vis absorption and photoluminescence (PL) emission characteristics are determined by dispersing the samples in water as well as in ethanol media. The quenching of PL emission intensity along-with the red shifting of the PL emission peak are observed when the samples are dispersed in water in comparison to those obtained after dispersing the samples in ethanol. It has been found that PL emission characteristic, particularly the spectral nature of PL emission, of the samples remains almost unaltered (except some improvement in UV PL emission) even after thermally annealing it for 2 h at the temperature of 300 degrees C. Also the synthesized powder samples, kept in a plastic container, showed a very stable PL emission even after 15 months of synthesis. Therefore, the synthesized samples might be useful for their applications in future optoelectronics devices. (C) 2014 Elsevier Ltd. All rights reserved.

Composition dependent non-ideality in aqueous binary mixtures as a signature of avoided spinodal decomposition

We explore the potential energy landscape of structure breaking binary mixtures (SBBM) where two constituents dislike each other, yet remain macroscopically homogeneous at intermediate to high temperatures. Interestingly, we find that the origin of strong composition dependent non-ideal behaviour lies in its phase separated inherent structure. The inherent structure (IS) of SBBM exhibits bi-continuous phase as is usually formed during spinodal decomposition. We draw analogy of this correlation between non-ideality and phase separation in IS to explain observation of non-ideality in real aqueous mixtures of small amphiphilic solutes, containing both hydrophilic and hydrophobic groups. Although we have not been able to obtain IS of these liquids, we find that even at room temperature these liquids sustain formation of fluctuating, transient bi-continuous phase, with limited lifetime (tau less than or similar to 20 ps). While in the model (A, B) binary mixture, the non-ideal composition dependence can be considered as a fluctuation from a phase separated state, a similar scenario is expected to be responsible for the unusually strong non-ideality in these aqueous binary mixtures.

Excited electronic state decomposition mechanisms of clusters of dimethylnitramine and aluminum

In this report, electronically non-adiabatic decomposition pathways of clusters of dimethylnitramine and aluminum (DMNA-Al and DMNA-Al-2) are discussed in comparison to isolated dimethylnitramine (DMNA). Electronically excited state processes of DMNA-Al and DMNA-Al-2 are explored using the complete active space self-consistent field (CASSCF) and the restricted active space self-consistent field (RASSCF) theories, respectively. Similar to the nitro-nitrite isomerization reaction pathway of DMNA, DMNA-Al-n clusters also exhibit isomerization pathway. However, it involves several other steps, such as, first Al-O bond dissociation, then N-N bond dissociation followed by isomerization and finally NO elimination. Furthermore, DMNA-Al-n clusters exhibit overall exothermic decomposition reaction pathway and isolated DMNA shows overall endothermic reaction channel.

Efficient QR Decomposition Using Low Complexity Column-wise Givens Rotation (CGR)

QR decomposition (QRD) is a widely used Numerical Linear Algebra (NLA) kernel with applications ranging from SONAR beamforming to wireless MIMO receivers. In this paper, we propose a novel Givens Rotation (GR) based QRD (GR QRD) where we reduce the computational complexity of GR and exploit higher degree of parallelism. This low complexity Column-wise GR (CGR) can annihilate multiple elements of a column of a matrix simultaneously. The algorithm is first realized on a Two-Dimensional (2 D) systolic array and then implemented on REDEFINE which is a Coarse Grained run-time Reconfigurable Architecture (CGRA). We benchmark the proposed implementation against state-of-the-art implementations to report better throughput, convergence and scalability.

NrichD database: sequence databases enriched with computationally designed protein-like sequences aid in remote homology detection

NrichD ( ext-link-type=''uri'' xlink:href=''http://proline.biochem.iisc.ernet.in/NRICHD/'' xlink:type=''simple''>http://proline.biochem.iisc.ernet.in/NRICHD/)< /named-content> is a database of computationally designed protein-like sequences, augmented into natural sequence databases that can perform hops in protein sequence space to assist in the detection of remote relationships. Establishing protein relationships in the absence of structural evidence or natural `intermediately related sequences' is a challenging task. Recently, we have demonstrated that the computational design of artificial intermediary sequences/linkers is an effective approach to fill naturally occurring voids in protein sequence space. Through a large-scale assessment we have demonstrated that such sequences can be plugged into commonly employed search databases to improve the performance of routinely used sequence search methods in detecting remote relationships. Since it is anticipated that such data sets will be employed to establish protein relationships, two databases that have already captured these relationships at the structural and functional domain level, namely, the SCOP database and the Pfam database, have been `enriched' with these artificial intermediary sequences. NrichD database currently contains 3 611 010 artificial sequences that have been generated between 27 882 pairs of families from 374 SCOP folds. The data sets are freely available for download. Additional features include the design of artificial sequences between any two protein families of interest to the user.