An 8-to-1 bit 1-MS/s SAR ADC With VGA and Integrated Data Compression for Neural Recording

Low power consumption per channel and data rate minimization are two key challenges which need to be addressed in future generations of neural recording systems (NRS). Power consumption can be reduced by avoiding unnecessary processing whereas data rate is greatly decreased by sending spike time-stamps along with spike features as opposed to raw digitized data. Dynamic range in NRS can vary with time due to change in electrode-neuron distance or background noise, which demands adaptability. An analog-to-digital converter (ADC) is one of the most important blocks in a NRS. This paper presents an 8-bit SAR ADC in 0.13-mu m CMOS technology along with input and reference buffer. A novel energy efficient digital-to-analog converter switching scheme is proposed, which consumes 37% less energy than the present state-of-the-art. The use of a ping-pong input sampling scheme is emphasized for multichannel input to alleviate the bandwidth requirement of the input buffer. To reduce the data rate, the A/D process is only enabled through the in-built background noise rejection logic to ensure that the noise is not processed. The ADC resolution can be adjusted from 8 to 1 bit in 1-bit step based on the input dynamic range. The ADC consumes 8.8 mu W from 1 V supply at 1 MS/s speed. It achieves effective number of bits of 7.7 bits and FoM of 42.3 fJ/conversion-step.

Image reconstruction enables high resolution imaging at large penetration depths in fluorescence microscopy

Imaging thick specimen at a large penetration depth is a challenge in biophysics and material science. Refractive index mismatch results in spherical aberration that is responsible for streaking artifacts, while Poissonian nature of photon emission and scattering introduces noise in the acquired three-dimensional image. To overcome these unwanted artifacts, we introduced a two-fold approach: first, point-spread function modeling with correction for spherical aberration and second, employing maximum-likelihood reconstruction technique to eliminate noise. Experimental results on fluorescent nano-beads and fluorescently coated yeast cells (encaged in Agarose gel) shows substantial minimization of artifacts. The noise is substantially suppressed, whereas the side-lobes (generated by streaking effect) drops by 48.6% as compared to raw data at a depth of 150 mu m. Proposed imaging technique can be integrated to sophisticated fluorescence imaging techniques for rendering high resolution beyond 150 mu m mark. (C) 2013 AIP Publishing LLC.

Remarkable Regioisomer Control in the Hydrogel Formation from a Two-Component Mixture of Pyridine-End Oligo(p-phenylenevinylene)s and N-Decanoyl-L-alanine

N-Decanoyl-L-alanine (DA) was mixed with either colorless 4,4-bipyridine (BP) or various derivatives such as chromogenic oligo(p-phenylenevinylene) (OPV) functionalized with isomeric pyridine termini in specific molar ratios. This mixtures form salt-type gels in a water/ethanol (2:1, v/v) mixture. The gelation properties of these two-component mixtures could be modulated by variation of the position of the N atom of the end pyridyl groups in OPVs. The presence of acid-base interactions in the self-assembly of these two-component systems leading to gelation was probed in detail by using stoichiometry-dependent UV/Vis and FTIR spectroscopy. Furthermore, temperature-dependent UV/Vis and fluorescence spectroscopy clearly demonstrated a J-type aggregation mode of these gelator molecules during the sol-to-gel transition process. Morphological features and the arrangement of the molecules in the gels were examined by using scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD) techniques. Calculation of the length of each molecular system by energy minimization in its extended conformation and comparison with the XRD patterns revealed that this class of gelator molecules adopts lamellar organizations. Rheological properties of these two-component systems provided clear evidence that the flow behavior could be modulated by varying the acid/amine ratio. Polarized optical microscopy (POM), differential scanning calorimetry (DSC), and XRD results revealed that the solid-phase behavior of such two-component mixtures (acid/base=2:1) varied significantly upon changing the proton-acceptor part from BP to OPV. Interestingly, the XRD pattern of these acid/base mixtures after annealing at their associated isotropic temperature was significantly different from that of their xerogels.

Joint Scheduling & Jamming for Data Secrecy in Wireless Networks

The broadcast nature of the wireless medium jeopardizes secure transmissions. Cryptographic measures fail to ensure security when eavesdroppers have superior computational capability; however, it can be assured from information theoretic security approaches. We use physical layer security to guarantee non-zero secrecy rate in single source, single destination multi-hop networks with eavesdroppers for two cases: when eavesdropper locations and channel gains are known and when their positions are unknown. We propose a two-phase solution which consists of finding activation sets and then obtaining transmit powers subject to SINR constraints for the case when eavesdropper locations are known. We introduce methods to find activation sets and compare their performance. Necessary but reasonable approximations are made in power minimization formulations for tractability reasons. For scenarios with no eavesdropper location information, we suggest vulnerability region (the area having zero secrecy rate) minimization over the network. Our results show that in the absence of location information average number of eavesdroppers who have access to data is reduced.

Ultrastructural and hormonal changes in rat cauda epididymal spermatozoa induced by Boswellia papyrifera and Boswellia carterii

Boswellia papyrifera and Boswellia carterii diffuses smoke polluting air that adversely affects indoor environment that certainly harm human health. Therefore, this study aims at ascertaining the effect of these plants on gonadal hormones and molecular changes in rat spermatozoa. The animals were exposed to 4 g/kg body weight of B. papyrifera and B. carterii daily for 120 days along with suitable controls. Significant decreases in FSH, LH and testosterone levels were evidenced, along with a reduction of protein, sialic acid, and carnitine levels. In sperm physiology, sperm count, motility, speed decrease, whereas sperm anomalies increase. TEM observation indicates morphological changes in plasma and acrosomal membranes, cytoplasmic droplet in the tail region, vacuolated, and disorganization of the mitochondrial sheath. These findings demonstrate that B. papyrifera and B. carterii smoke affects the process of sperm formation and maturation, which indicates the detrimental effects of these plants on the reproductive system. (c) 2014 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.d

Electronic band Structure and Photoemission Spectra of Graphene on Silicon Substrate

Synergizing graphene on silicon based nanostructures is pivotal in advancing nano-electronic device technology. A combination of molecular dynamics and density functional theory has been used to predict the electronic energy band structure and photo-emission spectrum for graphene-Si system with silicon as a substrate for graphene. The equilibrium geometry of the system after energy minimization is obtained from molecular dynamics simulations. For the stable geometry obtained, density functional theory calculations are employed to determine the energy band structure and dielectric constant of the system. Further the work function of the system which is a direct consequence of photoemission spectrum is calculated from the energy band structure using random phase approximations.

Riemann shock tube: 1D normal shocks in air, simulations and experiments

This paper presents numerical simulation of the evolution of one-dimensional normal shocks, their propagation, reflection and interaction in air using a single diaphragm Riemann shock tube and validate them using experimental results. Mathematical model is derived for one-dimensional compressible flow of viscous and conducting medium. Dimensionless form of the mathematical model is used to construct space-time finite element processes based on minimization of the space-time residual functional. The space-time local approximation functions for space-time p-version hierarchical finite elements are considered in higher order GRAPHICS] spaces that permit desired order of global differentiability of local approximations in space and time. The resulting algebraic systems from this approach yield unconditionally positive-definite coefficient matrices, hence ensure unique numerical solution. The evolution is computed for a space-time strip corresponding to a time increment Delta t and then time march to obtain the evolution up to any desired value of time. Numerical studies are designed using recently invented hand-driven shock tube (Reddy tube) parameters, high/low side density and pressure values, high- and low-pressure side shock tube lengths, so that numerically computed results can be compared with actual experimental measurements.

TIME VARYING LINEAR PREDICTION USING SPARSITY CONSTRAINTS

Time-varying linear prediction has been studied in the context of speech signals, in which the auto-regressive (AR) coefficients of the system function are modeled as a linear combination of a set of known bases. Traditionally, least squares minimization is used for the estimation of model parameters of the system. Motivated by the sparse nature of the excitation signal for voiced sounds, we explore the time-varying linear prediction modeling of speech signals using sparsity constraints. Parameter estimation is posed as a 0-norm minimization problem. The re-weighted 1-norm minimization technique is used to estimate the model parameters. We show that for sparsely excited time-varying systems, the formulation models the underlying system function better than the least squares error minimization approach. Evaluation with synthetic and real speech examples show that the estimated model parameters track the formant trajectories closer than the least squares approach.

Robust tracking with interest points: A sparse representation approach

Visual tracking is an important task in various computer vision applications including visual surveillance, human computer interaction, event detection, video indexing and retrieval. Recent state of the art sparse representation (SR) based trackers show better robustness than many of the other existing trackers. One of the issues with these SR trackers is low execution speed. The particle filter framework is one of the major aspects responsible for slow execution, and is common to most of the existing SR trackers. In this paper,(1) we propose a robust interest point based tracker in l(1) minimization framework that runs at real-time with performance comparable to the state of the art trackers. In the proposed tracker, the target dictionary is obtained from the patches around target interest points. Next, the interest points from the candidate window of the current frame are obtained. The correspondence between target and candidate points is obtained via solving the proposed l(1) minimization problem. In order to prune the noisy matches, a robust matching criterion is proposed, where only the reliable candidate points that mutually match with target and candidate dictionary elements are considered for tracking. The object is localized by measuring the displacement of these interest points. The reliable candidate patches are used for updating the target dictionary. The performance and accuracy of the proposed tracker is benchmarked with several complex video sequences. The tracker is found to be considerably fast as compared to the reported state of the art trackers. The proposed tracker is further evaluated for various local patch sizes, number of interest points and regularization parameters. The performance of the tracker for various challenges including illumination change, occlusion, and background clutter has been quantified with a benchmark dataset containing 50 videos. (C) 2014 Elsevier B.V. All rights reserved.

Morphological Evolution in Air-Stable Metallic Iron Nanostructures and Their Magnetic Study

Iron nanostructures with morphology ranging from discrete nanoparticles to nearly monodisperse hierarchical nanostructures have been successfully synthesized using solvated metal atom dispersion (SMAD) method. Such a morphological evolution was realized by tuning the molar ratio of ligand to metal. Surface energy minimization in confluence with strong magnetic interactions and ligand-based stabilization results in the formation of nanospheres of iron. The as-prepared amorphous iron nanostructures exhibit remarkably high coercivity in comparison to the discrete nanoparticles and bulk counterpart. Annealing the as-prepared amorphous Fe nanostructures under anaerobic conditions affords air-stable carbon-encapsulated Fe(0) and Fe3C nanostructures with retention of the morphology. The resulting nanostructures were thoroughly analyzed by powder X-ray diffraction (PXRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), and Raman spectroscopy. TGA brought out that Fe3C nanostructures are more robust toward oxidation than those of a-Fe. Finally, detailed magnetic studies were carried out by superconducting quantum interference device (SQUID) magnetometer and it was found that the magnetic properties remain conserved even upon exposure of the annealed samples to ambient conditions for months.

Boundary Tracking using a Hybrid Cyclic Pursuit Scheme

There has been a lot of work in the literature, related to the mapping of boundaries of regions, using multiple agents. Most of these are based on optimization techniques or rely on potential fields to drive the agents towards the boundary and then retain them there while they space out evenly along the perimeter or surface (in two-dimensional and three-dimensional cases, respectively). In this paper an algorithm to track the boundary of a region in space is provided based on the cyclic pursuit scheme. This enables the agents to constantly move along the perimeter in a cluster, thereby tracking a dynamically changing boundary. The trajectories of the agents provide a sketch of the boundary. The use of multiple agents may facilitate minimization of tracking error by providing accurate estimates of points on the boundary, besides providing redundancy. Simulation results are provided to highlight the performance of the proposed scheme.

Optimal Pulse Width Modulation of Voltage-Source Inverter fed Motor Drives with Relaxation of Quarter Wave Symmetry Condition

Optimal switching angles for minimization of total harmonic distortion of line current (I-THD) in a voltage source inverter are determined traditionally by imposing half-wave symmetry (HWS) and quarter-wave symmetry (QWS) conditions on the pulse width modulated waveform. This paper investigates optimal switching angles with QWS relaxed. Relaxing QWS expands the solution space and presents the possibility of improved solutions. The optimal solutions without QWS are shown here to outperform the optimal solutions with QWS over a range of modulation index (M) between 0.82 and 0.94 for a switching frequency to fundamental frequency ratio of 5. Theoretical and experimental results are presented on a 2.3kW induction motor drive.

A provably tight delay-driven concurrently congestion mitigating global routing algorithm

Routing is a very important step in VLSI physical design. A set of nets are routed under delay and resource constraints in multi-net global routing. In this paper a delay-driven congestion-aware global routing algorithm is developed, which is a heuristic based method to solve a multi-objective NP-hard optimization problem. The proposed delay-driven Steiner tree construction method is of O(n(2) log n) complexity, where n is the number of terminal points and it provides n-approximation solution of the critical time minimization problem for a certain class of grid graphs. The existing timing-driven method (Hu and Sapatnekar, 2002) has a complexity O(n(4)) and is implemented on nets with small number of sinks. Next we propose a FPTAS Gradient algorithm for minimizing the total overflow. This is a concurrent approach considering all the nets simultaneously contrary to the existing approaches of sequential rip-up and reroute. The algorithms are implemented on ISPD98 derived benchmarks and the drastic reduction of overflow is observed. (C) 2014 Elsevier Inc. All rights reserved.

CROSS-SECTIONAL ANALYSIS OF PRE-TWISTED THICK BEAMS USING VARIATIONAL ASYMPTOTIC METHOD

An asymptotically-exact methodology is presented for obtaining the cross-sectional stiffness matrix of a pre-twisted moderately-thick beam having rectangular cross sections and made of transversely isotropic materials. The anisotropic beam is modeled from 3-D elasticity, without any further assumptions. The beam is allowed to have large displacements and rotations, but small strain is assumed. The strain energy of the beam is computed making use of the constitutive law and the kinematical relations derived with the inclusion of geometrical nonlinearities and initial twist. Large displacements and rotations are allowed, but small strain is assumed. The Variational Asymptotic Method is used to minimize the energy functional, thereby reducing the cross section to a point on the reference line with appropriate properties, yielding a 1-D constitutive law. In this method as applied herein, the 2-D cross-sectional analysis is performed asymptotically by taking advantage of a material small parameter and two geometric small parameters. 3-D strain components are derived using kinematics and arranged as orders of the small parameters. Warping functions are obtained by the minimization of strain energy subject to certain set of constraints that renders the 1-D strain measures well-defined. Closed-form expressions are derived for the 3-D non-linear warping and stress fields. The model is capable of predicting interlaminar and transverse shear stresses accurately up to first order.

Investigations on Optimal Pulse-Width Modulation to Minimize Total Harmonic Distortion in the Line Current

PWM waveforms with positive voltage transition at the positive zero crossing of the fundamental voltage (type-A) are generally considered for PWM waveform with even number of switching angles per quarter whereas, waveforms with negative voltage transition at the positive zero crossing (type-B) are considered for odd number of switching angles per quarter. Optimal PWM, for minimization of total harmonic distortion of line to line (VWTHD), is generally solved with the aforementioned criteria. This paper establishes that a combination of both types of waveforms gives better performance than any individual type in terms of minimum VWTHD for complete range of modulation index (M). Optimal PWM for minimum VWTHD is solved for PWM waveforms with pulse numbers (P) of 5 and 7. Both type-A and type-B waveforms are found to be better in different ranges of M. The theoretical findings are confirmed through simulation and experimental results on a 3.7 kW squirrel cage induction motor in an open-loop V/f drive. Further, the optimal PWM is analysed from a space vector point of view.