Robust local and nonlocal transport in the topological Kondo insulator SmB6 in the presence of a high magnetic field

SmB6 has been predicted to be a Kondo topological insulator with topologically protected conducting surface states. We have studied quantitatively the electrical transport through surface states in high-quality single crystals of SmB6. We observe a large nonlocal surface signal at temperatures lower than the bulk Kondo gap scale. Measurements and finite-element simulations allow us to distinguish unambiguously between the contributions from different transport channels. In contrast to general expectations, the electrical transport properties of the surface channels were found to be insensitive to high magnetic fields. We propose possible scenarios that might explain this unexpected finding. Local and nonlocal magnetoresistance measurements allowed us to identify possible signatures of helical spin states and strong interband scattering at the surface.

Combinatorial selection of molecular conformations and supramolecular synthons in quercetin cocrystal landscapes: a route to ternary solids

The crystallization of 28 binary and ternary cocrystals of quercetin with dibasic coformers is analyzed in terms of a combinatorial selection from a solution of preferred molecular conformations and supramolecular synthons. The crystal structures are characterized by distinctive O-H center dot center dot center dot N and O-H center dot center dot center dot O based synthons and are classified as nonporous, porous and helical. Variability in molecular conformation and synthon structure led to an increase in the energetic and structural space around the crystallization event. This space is the crystal structure landscape of the compound and is explored by fine-tuning the experimental conditions of crystallization. In the landscape context, we develop a strategy for the isolation of ternary cocrystals with the use of auxiliary template molecules to reduce the molecular and supramolecular `confusion' that is inherent in a molecule like quercetin. The absence of concomitant polymorphism in this study highlights the selectivity in conformation and synthon choice from the virtual combinatorial library in solution.

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Multi-dimensional Goodness-of-Fit Tests for Spectrum Sensing Based on Stochastic Distances

In this paper, we study two multi-dimensional Goodness-of-Fit tests for spectrum sensing in cognitive radios. The multi-dimensional scenario refers to multiple CR nodes, each with multiple antennas, that record multiple observations from multiple primary users for spectrum sensing. These tests, viz., the Interpoint Distance (ID) based test and the h, f distance based tests are constructed based on the properties of stochastic distances. The ID test is studied in detail for a single CR node case, and a possible extension to handle multiple nodes is discussed. On the other hand, the h, f test is applicable in a multi-node setup. A robustness feature of the KL distance based test is discussed, which has connections with Middleton's class A model. Through Monte-Carlo simulations, the proposed tests are shown to outperform the existing techniques such as the eigenvalue ratio based test, John's test, and the sphericity test, in several scenarios.

Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method

Three-dimensional (3-D) full-wave electromagnetic simulation using method of moments (MoM) under the framework of fast solver algorithms like fast multipole method (FMM) is often bottlenecked by the speed of convergence of the Krylov-subspace-based iterative process. This is primarily because the electric field integral equation (EFIE) matrix, even with cutting-edge preconditioning techniques, often exhibits bad spectral properties arising from frequency or geometry-based ill-conditioning, which render iterative solvers slow to converge or stagnate occasionally. In this communication, a novel technique to expedite the convergence of MoMmatrix solution at a specific frequency is proposed, by extracting and applying Eigen-vectors from a previously solved neighboring frequency in an augmented generalized minimum residual (AGMRES) iterative framework. This technique can be applied in unison with any preconditioner. Numerical results demonstrate up to 40% speed-up in convergence using the proposed Eigen-AGMRES method.

Dissecting pi-helices: sequence, structure and function

A new procedure for the identification of regular secondary structures using a C-alpha trace has identified 659 pi-helices in 3582 protein chains, solved at high resolution. Taking advantage of this significantly expanded database of pi-helices, we have analysed the functional and structural roles of helices and determined the position-wise amino acid propensity within and around them. These helices range from 5 to 18 residues in length with the average twist and rise being 85.2 +/- 7.2 and 1.28 +/- 0.31 angstrom, respectively. A total of 546 (similar to 83%) out of 659 pi-helices occur in conjunction with alpha-helices, with 101 pi-helices being interspersed between two alpha-helices. The majority of interspersed pi-helices were found to be conserved across a large number of structures within a protein family and produce a significant bend in the overall helical segment as well as local distortions in the neighbouring a-helices. The presence of a pi-helical fragment leads to appropriate orientation of the constituent residues, so as to facilitate favourable interactions and also help in proper folding of the protein chain. In addition to intra helical 6 -> 1 N H center dot center dot center dot O hydrogen bonds, pi-helices are also stabilized by several other non-bonded interactions. pi-Helices show distinct positional residue preferences, which are different from those of a-helices.

Effect of methylene group insertions on the structural rigidity of Aib containing helices

Nonprotein amino acids are being extensively used in the design of synthetic peptides to create new structure mimics. In this study we report the effect of methylene group insertions in a heptapeptide Boc-Ala(1)-Leu(2)-Aib(3)-Xxx(4)-Ala(5)-Leu(6)-Aib(7)-OMe which nicely folds into a mixed 3(10)-/-helical structure when Xxx= Ala. Analogs of this peptide have been made and studied by replacing central Xxx(4) residue with Glycine (-residue), -Alanine (-la), -aminobutyric acid (Gaba), and epsilon-aminocaproic acid (epsilon-Aca). NMR and circular dichroism were used to study the solution structure of these peptides. Crystals of the peptides containing alanine, -la, and Gaba reveal that increasing the number of central methylene (-CH2-) groups introduces local perturbations even as the helical structure is retained. (c) 2015 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 104: 720-732, 2015.

Crystal structure of a tripeptide containing aminocyclododecane carboxylic acid: a supramolecular twisted parallel -sheet in crystals

The crystal structure of a tripeptide Boc-Leu-Val-Ac(12)c-OMe (1) is determined, which incorporates a bulky 1-aminocyclododecane-1-carboxylic acid (Ac(12)c) side chain. The peptide adopts a semi-extended backbone conformation for Leu and Val residues, while the backbone torsion angles of the C-,C--dialkylated residue Ac(12)c are in the helical region of the Ramachandran map. The molecular packing of 1 revealed a unique supramolecular twisted parallel -sheet coiling into a helical architecture in crystals, with the bulky hydrophobic Ac(12)c side chains projecting outward the helical column. This arrangement resembles the packing of peptide helices in crystal structures. Although short oligopeptides often assemble as parallel or anti-parallel -sheet in crystals, twisted or helical -sheet formation has been observed in a few examples of dipeptide crystal structures. Peptide 1 presents the first example of a tripeptide showing twisted -sheet assembly in crystals. Copyright (c) 2016 European Peptide Society and John Wiley & Sons, Ltd.

Crystal structure of a tripeptide containing aminocyclododecane carboxylic acid: a supramolecular twisted parallel -sheet in crystals

The crystal structure of a tripeptide Boc-Leu-Val-Ac(12)c-OMe (1) is determined, which incorporates a bulky 1-aminocyclododecane-1-carboxylic acid (Ac(12)c) side chain. The peptide adopts a semi-extended backbone conformation for Leu and Val residues, while the backbone torsion angles of the C-,C--dialkylated residue Ac(12)c are in the helical region of the Ramachandran map. The molecular packing of 1 revealed a unique supramolecular twisted parallel -sheet coiling into a helical architecture in crystals, with the bulky hydrophobic Ac(12)c side chains projecting outward the helical column. This arrangement resembles the packing of peptide helices in crystal structures. Although short oligopeptides often assemble as parallel or anti-parallel -sheet in crystals, twisted or helical -sheet formation has been observed in a few examples of dipeptide crystal structures. Peptide 1 presents the first example of a tripeptide showing twisted -sheet assembly in crystals. Copyright (c) 2016 European Peptide Society and John Wiley & Sons, Ltd.

The legacy of G. N. Ramachandran and the development of structural biology in India

G. N. Ramachandran is among the founding fathers of structural molecular biology. He made pioneering contributions in computational biology, modelling and what we now call bioinformatics. The triple helical coiled coil structure of collagen proposed by him forms the basis of much of collagen research at the molecular level. The Ramachandran map remains the simplest descriptor and tool for validation of protein structures. He has left his imprint on almost all aspects of biomolecular conformation. His contributions in the area of theoretical crystallography have been outstanding. His legacy has provided inspiration for the further development of structural biology in India. After a pause, computational biology and bioinformatics are in a resurgent phase. One of the two schools established by Ramachandran pioneered the development of macromolecular crystallography, which has now grown into an important component of modern biological research in India. Macromolecular NMR studies in the country are presently gathering momentum. Structural biology in India is now poised to again approach heights of the kind that Ramachandran conquered more than a generation ago.

On the Capacity and Performance of Generalized Spatial Modulation

Generalized spatial modulation (GSM) uses N antenna elements but fewer radio frequency (RF) chains (R) at the transmitter. In GSM, apart from conveying information bits through R modulation symbols, information bits are also conveyed through the indices of the R active transmit antennas. In this letter, we derive lower and upper bounds on the the capacity of a (N, M, R)-GSM MIMO system, where M is the number of receive antennas. Further, we propose a computationally efficient GSM encoding method and a message passing-based low-complexity detection algorithm suited for large-scale GSM-MIMO systems.