Multivariate PLS Modeling of Apicomplexan FabD-Ligand Interaction Space for Mapping Target-Specific Chemical Space and Pharmacophore Fingerprints

Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.

Efficient Protocol for Authenticated Email Search

Executing authenticated computation on outsourced data is currently an area of major interest in cryptology. Large databases are being outsourced to untrusted servers without appreciable verification mechanisms. As adversarial server could produce erroneous output, clients should not trust the server's response blindly. Primitive set operations like union, set difference, intersection etc. can be invoked on outsourced data in different concrete settings and should be verifiable by the client. One such interesting adaptation is to authenticate email search result where the untrusted mail server has to provide a proof along with the search result. Recently Ohrimenko et al. proposed a scheme for authenticating email search. We suggest significant improvements over their proposal in terms of client computation and communication resources by properly recasting it in two-party settings. In contrast to Ohrimenko et al. we are able to make the number of bilinear pairing evaluation, the costliest operation in verification procedure, independent of the result set cardinality for union operation. We also provide an analytical comparison of our scheme with their proposal which is further corroborated through experiments.

Timing Calculations for a General N-Level Dodecagonal Space Vector Structure Using Only Reference Phase Voltages

Multilevel inverters with dodecagonal (12-sided polygon) voltage space vector (SV) structures have advantages like extension of linear modulation range, elimination of fifth and seventh harmonics in phase voltages and currents for the full modulation range including extreme 12-step operation, reduced device voltage ratings, lesser dv/dt stresses on devices and motor phase windings resulting in lower EMI/EMC problems, and lower switching frequency-making it more suitable for high-power drive applications. This paper proposes a simple method to obtain pulsewidth modulation (PWM) timings for a dodecagonal voltage SV structure using only sampled reference voltages. In addition to this, a carrier-based method for obtaining the PWM timings for a general N-level dodecagonal structure is proposed in this paper for the first time. The algorithm outputs the triangle information and the PWM timing values which can be set as the compare values for any carrier-based hardware PWM module to obtain SV PWM like switching sequences. The proposed method eliminates the need for angle estimation, computation of modulation indices, and iterative search algorithms that are typical in multilevel dodecagonal SV systems. The proposed PWM scheme was implemented on a five-level dodecagonal SV structure. Exhaustive simulation and experimental results for steady-state and transient conditions are presented to validate the proposed method.

Space-Vector-Based Hybrid PWM Technique to Reduce Peak-to-Peak Torque Ripple in Induction Motor Drives

Constant-volts-per-hertz induction motor drives and vector-controlled induction motor drives utilize pulsewidth modulation (PWM) to control the voltage applied on the motor. The method of PWM influences the pulsations in the torque developed by the motor. A space-vector-based approach to PWM facilitates special switching sequences involving the division of active state time. This paper proposes a space-vector-based hybrid PWM technique, which is a combination of the conventional and special switching sequences. The proposed hybrid PWM technique results in a lower peak-to-peak torque ripple than conventional space vector PWM(CSVPWM) at high speeds of an induction motor drive. Furthermore, the magnitude of the dominant torque harmonic due to the proposed hybrid PWM is significantly lower than that due to CSVPWM at high speeds of the drive. Experimental results from a 3.75-kW sensorless vector-controlled induction motor drive under various load conditions are presented to support analytical and simulation results.

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.