Sequence-Structure Similarity: Do Sequentially Identical Peptide Fragments have Similar Three-Dimensional Structures?

The rapidly growing structure databases enhance the probability of finding identical sequences sharing structural similarity. Structure prediction methods are being used extensively to abridge the gap between known protein sequences and the solved structures which is essential to understand its specific biochemical and cellular functions. In this work, we plan to study the ambiguity between sequence-structure relationships and examine if sequentially identical peptide fragments adopt similar three-dimensional structures. Fragments of varying lengths (five to ten residues) were used to observe the behavior of sequence and its three-dimensional structures. The STAMP program was used to superpose the three-dimensional structures and the two parameters (Sequence Structure Similarity Score (Sc) and Root Mean Square Deviation value) were employed to classify them into three categories: similar, intermediate and dissimilar structures. Furthermore, the same approach was carried out on all the three-dimensional protein structures solved in the two organisms, Mycobacterium tuberculosis and Plasmodium falciparum to validate our results.

Making STMs Cache Friendly with Compiler Transformations

Software transactional memory (STM) is a promising programming paradigm for shared memory multithreaded programs. In order for STMs to be adopted widely for performance critical software, understanding and improving the cache performance of applications running on STM becomes increasingly crucial, as the performance gap between processor and memory continues to grow. In this paper, we present the most detailed experimental evaluation to date, of the cache behavior of STM applications and quantify the impact of the different STM factors on the cache misses experienced by the applications. We find that STMs are not cache friendly, with the data cache stall cycles contributing to more than 50% of the execution cycles in a majority of the benchmarks. We find that on an average, misses occurring inside the STM account for 62% of total data cache miss latency cycles experienced by the applications and the cache performance is impacted adversely due to certain inherent characteristics of the STM itself. The above observations motivate us to propose a set of specific compiler transformations targeted at making the STMs cache friendly. We find that STM's fine grained and application unaware locking is a major contributor to its poor cache behavior. Hence we propose selective Lock Data co-location (LDC) and Redundant Lock Access Removal (RLAR) to address the lock access misses. We find that even transactions that are completely disjoint access parallel, suffer from costly coherence misses caused by the centralized global time stamp updates and hence we propose the Selective Per-Partition Time Stamp (SPTS) transformation to address this. We show that our transformations are effective in improving the cache behavior of STM applications by reducing the data cache miss latency by 20.15% to 37.14% and improving execution time by 18.32% to 33.12% in five of the 8 STAMP applications.

Control of switching surges due to energization of 765kV UHV transmission line

Reduction of switching surge over voltages allows an economic design of UHV transmission system with reduced insulation. The various means of switching surge over voltage control with pre-insertion resistors/closing resistors, shunt re-actors and controlled switching are illustrated. The switching surge over voltages during the energization of series compensated line are compared with uncompensated line. An Electromagnetic transients program has been developed for studying the effect of various means of control of switching transients during 765kV UHV transmission line energization. This paper presents the studies carried out on switching surges control in 765kV UHV transmission line energization.

Reconciling transactional conflicts with compiler's help

Software transactional memory(STM) is a promising programming paradigm for shared memory multithreaded programs. While STM offers the promise of being less error-prone and more programmer friendly compared to traditional lock-based synchronization, it also needs to be competitive in performance in order for it to be adopted in mainstream software. A major source of performance overheads in STM is transactional aborts. Conflict resolution and aborting a transaction typically happens at the transaction level which has the advantage that it is automatic and application agnostic. However it has a substantial disadvantage in that STM declares the entire transaction as conflicting and hence aborts it and re-executes it fully, instead of partially re-executing only those part(s) of the transaction, which have been affected due to the conflict. This "Re-execute Everything" approach has a significant adverse impact on STM performance. In order to mitigate the abort overheads, we propose a compiler aided Selective Reconciliation STM (SR-STM) scheme, wherein certain transactional conflicts can be reconciled by performing partial re-execution of the transaction. Ours is a selective hybrid approach which uses compiler analysis to identify those data accesses which are legal and profitable candidates for reconciliation and applies partial re-execution only to these candidates selectively while other conflicting data accesses are handled by the default STM approach of abort and full re-execution. We describe the compiler analysis and code transformations required for supporting selective reconciliation. We find that SR-STM is effective in reducing the transactional abort overheads by improving the performance for a set of five STAMP benchmarks by 12.58% on an average and up to 22.34%.

Influence of binder solvent on carbon-layer structure in electrical-double-layer capacitors

Porous activated-carbons with a large surface-area have been the most common materials for electrical-double-layer capacitors (EDLCs). These carbons having a wide pore distribution ranges from micropores to macropores in conjunction with a random pore connection that facilitates the high specific-capacitance values. Pore distribution plays a central role in controlling the capacitance value of EDLCs, since electrolyte distribution inside the active material mainly depends on the pore distribution. This has a direct influence on the distribution of resistance and capacitance values within the electrode. As a result, preparation of electrodes remains a vital issue in realising high-performance EDLCs. Generally, carbon materials along with some binders are dispersed into a solvent and coated onto the current collectors. This study examines the role of binder solvents used for the carbon-ink preparation on the microstructure of the electrodes and the consequent performance of the EDLCs. It is observed that the physical properties of the binder solvent namely its dielectric constant, viscosity and boiling point have important role in determining the pore-size distribution as well as the microstructure of electrodes which influence their specific capacitance values.

Measurement Based Impromptu Deployment of a Multi-Hop Wireless Relay Network

We study the problem of optimal sequential (''as-you-go'') deployment of wireless relay nodes, as a person walks along a line of random length (with a known distribution). The objective is to create an impromptu multihop wireless network for connecting a packet source to be placed at the end of the line with a sink node located at the starting point, to operate in the light traffic regime. In walking from the sink towards the source, at every step, measurements yield the transmit powers required to establish links to one or more previously placed nodes. Based on these measurements, at every step, a decision is made to place a relay node, the overall system objective being to minimize a linear combination of the expected sum power (or the expected maximum power) required to deliver a packet from the source to the sink node and the expected number of relay nodes deployed. For each of these two objectives, two different relay selection strategies are considered: (i) each relay communicates with the sink via its immediate previous relay, (ii) the communication path can skip some of the deployed relays. With appropriate modeling assumptions, we formulate each of these problems as a Markov decision process (MDP). We provide the optimal policy structures for all these cases, and provide illustrations of the policies and their performance, via numerical results, for some typical parameters.

Large-MIMO Receiver based on Linear Regression of MMSE Residual

Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs quite well: at a bit error rate (BER) of 10(-3), the SNR gain over MMSE receiver is about 7 dB for a 16 x 16 system; for a 64 x 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.

Organic solar cell by using vertically aligned nanostructured ZnO nanorods

A low temperature solution approach was employed to grow zinc oxide (ZnO) nanorods with various aspect ratios. Various sizes (diameter-10-25nm) of the nanorods were grown by changing the concentrations of the growth solution. The length (50nm-500nm) of nanorods was controlled using growth times. These one-dimensional (1D) nanostructures with direct paths for a charge transport with high surface area for light harvesting, are promising candidates for organic photovoltaics (OPV). The structural and optical properties of the prepared ZnO nanorods have been studied using SEM, XRD and UV-Vis absorption spectroscopy. Using as-grown ZnO inverted OPV was fabricated. ZnO nanorods were subjected to various doses of UV-ozone irradiation which led to improvement in transmission and hence enhanced device performance.

Solar driven Adsorption Desalination system

Desalination is one of the most traditional processes to generate potable water. With the rise in demand for potable water and paucity of fresh water resources, this process has gained special importance. Conventional thermal desalination processes involves evaporative methods such as multi-stage flash and solar distils, which are found to be energy intensive, whereas reverse osmosis based systems have high operating and maintenance costs. The present work describes the Adsorption Desalination (AD) system, which is an emerging process of thermal desalination cum refrigeration capable of utilizing low grade heat easily obtainable from even non-concentrating type solar collectors. The system employs a combination of flash evaporation and thermal compression to generate cooling and desalinated water. The current study analyses the system dynamics of a 4-bed single stage silica-gel plus water based AD system. A lumped model is developed using conservation of energy and mass coupled with the kinetics of adsorption/desorption process. The constitutive equations for the system components viz. evaporator, adsorber and condenser, are solved and the performance of the system is evaluated for a single stage AD system at various condenser temperatures and cycle times to determine optimum operating conditions required for desalination and cooling. (C) 2013 P. Dutta. Published by Elsevier Ltd.

NESTED SPARSE BAYESIAN LEARNING FOR BLOCK-SPARSE SIGNALS WITH INTRA-BLOCK CORRELATION

In this work, we address the recovery of block sparse vectors with intra-block correlation, i.e., the recovery of vectors in which the correlated nonzero entries are constrained to lie in a few clusters, from noisy underdetermined linear measurements. Among Bayesian sparse recovery techniques, the cluster Sparse Bayesian Learning (SBL) is an efficient tool for block-sparse vector recovery, with intra-block correlation. However, this technique uses a heuristic method to estimate the intra-block correlation. In this paper, we propose the Nested SBL (NSBL) algorithm, which we derive using a novel Bayesian formulation that facilitates the use of the monotonically convergent nested Expectation Maximization (EM) and a Kalman filtering based learning framework. Unlike the cluster-SBL algorithm, this formulation leads to closed-form EMupdates for estimating the correlation coefficient. We demonstrate the efficacy of the proposed NSBL algorithm using Monte Carlo simulations.

3-D GPU Based Real Time Diffuse Optical Tomographic System

3-Dimensional Diffuse Optical Tomographic (3-D DOT) image reconstruction algorithm is computationally complex and requires excessive matrix computations and thus hampers reconstruction in real time. In this paper, we present near real time 3D DOT image reconstruction that is based on Broyden approach for updating Jacobian matrix. The Broyden method simplifies the algorithm by avoiding re-computation of the Jacobian matrix in each iteration. We have developed CPU and heterogeneous CPU/GPU code for 3D DOT image reconstruction in C and MatLab programming platform. We have used Compute Unified Device Architecture (CUDA) programming framework and CUDA linear algebra library (CULA) to utilize the massively parallel computational power of GPUs (NVIDIA Tesla K20c). The computation time achieved for C program based implementation for a CPU/GPU system for 3 planes measurement and FEM mesh size of 19172 tetrahedral elements is 806 milliseconds for an iteration.

ESD Behavior of Metallic Carbon Nanotubes

ESD behavior of metallic carbon nanotubes (CNTs) is explored. Unique TLP I-V characteristics and failure mechanism of carbon shells are discussed. ESD failure in CNTs is attributed to shell burning. It was found that CNT interconnect changes resistance in steps of fundamental quantum resistance (h/2e(2)) after individual shell burning.

Alternative Formulation of the Discrete Linear Quadratic Regulator (DLQR)

In this paper, an alternative apriori and aposteriori formulation has been derived for the discrete linear quadratic regulator (DLQR) in a manner analogous to that used in the discrete Kalman filter. It has been shown that the formulation seamlessly fits into the available formulation of the DLQR and the equivalent terms in the existing formulation and the proposed formulation have been identified. Thereafter, the significance of this alternative formulation has been interpreted in terms of the sensitivity of the controller performances to any changes in the states or to changes in the control inputs. The implications of this alternative formulation to adaptive controller tuning have also been discussed.

Studies on 12 V substrate-integrated lead-carbon hybrid ultracapacitors

A cost-effective 12 V substrate-integrated lead-carbon hybrid ultracapacitor is developed and performance tested. These hybrid ultracapacitors employ flexible-graphite sheets as negative plate current-collectors that are coated amperometrically with a thin layer of conducting polymer, namely poly-aniline to provide good adhesivity to activated-carbon layer. The positive plate of the hybrid ultracapacitors comprise conventional lead-sheet that is converted electrochemically into a substrate-integrated lead-dioxide electrode. 12 V substrate-integrated lead-carbon hybrid ultracapacitors both in absorbent-glass-mat and polymeric silica-gel electrolyte configurations are fabricated and characterized. It is possible to realize 12 V configurations with capacitance values of similar to 200 F and similar to 300 F, energy densities of similar to 1.9 Wh kg(-1) and similar to 2.5 Wh kg(-1) and power densities of similar to 2 kW kg(-1) and similar to 0.8 kW kg(-1), respectively, having faradaic-efficiency values of similar to 90 % with cycle-life in excess of 100,000 cycles. The effective cost of the mentioned hybrid ultracapacitors is estimated to be about similar to 4 US$/Wh as compared to similar to 20 US$/Wh for commercially available ultracapacitors.

Study of Wrist Pulse Signals Using a Bi-Modal Gaussian Model

Wrist pulse signals contain important information about the health of a person and hence diagnosis based on pulse signals has assumed great importance. In this paper we demonstrate the efficacy of a two term Gaussian model to extract information from pulse signals. Results have been obtained by conducting experiments on several subjects to record wrist pulse signals for the cases of before exercise and after exercise. Parameters have been extracted from the recorded signals using the model and a paired t-test is performed, which shows that the parameters are significantly different between the two groups. Further, a recursive cluster elimination based support vector machine is used to perform classification between the groups. An average classification accuracy of 99.46% is obtained, along with top classifiers. It is thus shown that the parameters of the Gaussian model show changes across groups and hence the model is effective in distinguishing the changes taking place due to the two different recording conditions. The study has potential applications in healthcare.