Joint Bilateral Filtering based Non-local Means Image Denoising

This paper proposes a denoising algorithm which performs non-local means bilateral filtering. As existing literature suggests, non-local means (NLM) is one of the widely used denoising techniques, but has a critical drawback of smoothing of edges. In order to improve this, we perform fast and efficient NLM using Approximate Nearest Neighbour Fields and improve the edge content in denoising by formulating a joint-bilateral filter. Using the proposed joint bilateral, we are able to denoise smooth regions using the NLM approach and efficient edge reconstruction is obtained from the bilateral filter. Furthermore, to avoid tedious parameter selection, we carry out a noise estimation before performing joint bilateral filtering. The proposed approach is observed to perform well on high noise images.

Entropy Constrained Exemplar-based Image Inpainting

Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L-2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques

Air microjet system for non-contact force application and the actuation of micro-structures

We demonstrate a non-contact technique to apply calibrated and localized forces in the micro-Newton to milli-Newton range using an air microjet. An electromagnetically actuated diaphragm controlled by a signal generator is used to generate the air microjet. With a nozzle diameter of 150 mu m, the microjet diameter was maintained to a maximum of 1 mm at a distance of 5 mm from the nozzle. The force generated by the microjet was measured using a commercial force sensor to determine the velocity profile of the jet. Axial flow velocities of up to 25 m s(-1) were obtained at distances as long as 6 mm. The microjet exerted a force up to 1 mu N on a poly dimethyl siloxane (PDMS) micropillar (50 mu m in diameter, 157 mu m in height) and 415 mu N on a PDMS membrane (3 mm in diameter, 28 mu m thick). We also demonstrate that from a distance of 6 mm our microjet can exert a peak pressure of 187 Pa with a total force of about 84 mu N on a flat surface with 8 V operating voltage. Out of the cleanroom fabrication and robust design make this system cost effective and durable.

Infiltration of Matrix-Non-producers Weakens the Salmonella Biofilm and Impairs Its Antimicrobial Tolerance and Pathogenicity

Bacterial biofilms display a collective lifestyle, wherein the cells secrete extracellular polymeric substances (EPS) that helps in adhesion, aggregation, stability, and to protect the bacteria from antimicrobials. We asked whether the BPS could act as a public good for the biofilm and observed that infiltration of cells that do not produce matrix components weakened the biofilm of Salmonella enterica serovar Typhimurium. PS production was costly for the producing cells, as indicated by a significant reduction in the fitness of wild type (WT) cells during competitive planktonic growth relative to the non-producers. Infiltration frequency of non-producers in the biofilm showed a concomitant decrease in overall productivity. It was apparent in the confocal images that the non producing cells benefit from the BPS produced by the Wild Type (WT) to stay in the biofilm. The biofilm containing non-producing cells were more significantly susceptible to sodium hypochlorite and ciprofloxacin treatment than the WT biofilm. Biofilm infiltrated with non-producers delayed the pathogenesis, as tested in a murine model. The cell types were spatially assorted, with non producers being edged out in the biofilm. However, cellulose was found to act as a barrier to keep the non-producers away from the WT microcolony. Our results show that the infiltration of non-cooperating cell types can substantially weaken the biofilm making it vulnerable to antibacterials and delay their pathogenesis. Cellulose, a component of BPS, was shown to play a pivotal role of acting as the main public good, and to edge-out the non-producers away from the cooperating microcolony.

Exact Phase Retrieval in Principal Shift-Invariant Spaces

We address the problem of phase retrieval from Fourier transform magnitude spectrum for continuous-time signals that lie in a shift-invariant space spanned by integer shifts of a generator kernel. The phase retrieval problem for such signals is formulated as one of reconstructing the combining coefficients in the shift-invariant basis expansion. We develop sufficient conditions on the coefficients and the bases to guarantee exact phase retrieval, by which we mean reconstruction up to a global phase factor. We present a new class of discrete-domain signals that are not necessarily minimum-phase, but allow for exact phase retrieval from their Fourier magnitude spectra. We also establish Hilbert transform relations between log-magnitude and phase spectra for this class of discrete signals. It turns out that the corresponding continuous-domain counterparts need not satisfy a Hilbert transform relation; notwithstanding, the continuous-domain signals can be reconstructed from their Fourier magnitude spectra. We validate the reconstruction guarantees through simulations for some important classes of signals such as bandlimited signals and piecewise-smooth signals. We also present an application of the proposed phase retrieval technique for artifact-free signal reconstruction in frequency-domain optical-coherence tomography (FDOCT).

Efficient coupled polynomial interpolation scheme for out-of-plane free vibration analysis of curved beams

The performance of two curved beam finite element models based on coupled polynomial displacement fields is investigated for out-of-plane vibration of arches. These two-noded beam models employ curvilinear strain definitions and have three degrees of freedom per node namely, out-of-plane translation (v), out-of-plane bending rotation (theta(z)) and torsion rotation (theta(s)). The coupled polynomial interpolation fields are derived independently for Timoshenko and Euler-Bernoulli beam elements using the force-moment equilibrium equations. Numerical performance of these elements for constrained and unconstrained arches is compared with the conventional curved beam models which are based on independent polynomial fields. The formulation is shown to be free from any spurious constraints in the limit of `flexureless torsion' and `torsionless flexure' and hence devoid of flexure and torsion locking. The resulting stiffness and consistent mass matrices generated from the coupled displacement models show excellent convergence of natural frequencies in locking regimes. The accuracy of the shear flexibility added to the elements is also demonstrated. The coupled polynomial models are shown to perform consistently over a wide range of flexure-to-shear (EI/GA) and flexure-to-torsion (EI/GJ) stiffness ratios and are inherently devoid of flexure, torsion and shear locking phenomena. (C) 2015 Elsevier B.V. All rights reserved.

Error exponent analysis of energy-based Bayesian decentralized spectrum sensing under fading

This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.

Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk

Complex systems inspired analysis suggests a hypothesis that financial meltdowns are abrupt critical transitions that occur when the system reaches a tipping point. Theoretical and empirical studies on climatic and ecological dynamical systems have shown that approach to tipping points is preceded by a generic phenomenon called critical slowing down, i.e. an increasingly slow response of the system to perturbations. Therefore, it has been suggested that critical slowing down may be used as an early warning signal of imminent critical transitions. Whether financial markets exhibit critical slowing down prior to meltdowns remains unclear. Here, our analysis reveals that three major US (Dow Jones Index, S&P 500 and NASDAQ) and two European markets (DAX and FTSE) did not exhibit critical slowing down prior to major financial crashes over the last century. However, all markets showed strong trends of rising variability, quantified by time series variance and spectral function at low frequencies, prior to crashes. These results suggest that financial crashes are not critical transitions that occur in the vicinity of a tipping point. Using a simple model, we argue that financial crashes are likely to be stochastic transitions which can occur even when the system is far away from the tipping point. Specifically, we show that a gradually increasing strength of stochastic perturbations may have caused to abrupt transitions in the financial markets. Broadly, our results highlight the importance of stochastically driven abrupt transitions in real world scenarios. Our study offers rising variability as a precursor of financial meltdowns albeit with a limitation that they may signal false alarms.

A glucose-centric perspective of hyperglycemia

Digestion of food in the intestines converts the compacted storage carbohydrates, starch and glycogen, to glucose. After each meal, a flux of glucose (>200 g) passes through the blood pool (4-6 g) in a short period of 2 h, keeping its concentration ideally in the range of 80-120 mg/100 mL. Tissue-specific glucose transporters (GLUTs) aid in the distribution of glucose to all tissues. The balance glucose after meeting the immediate energy needs is converted into glycogen and stored in liver (up to 100 g) and skeletal muscle (up to 300 g) for later use. High blood glucose gives the signal for increased release of insulin from pancreas. Insulin binds to insulin receptor on the plasma membrane and activates its autophosphorylation. This initiates the post-insulin-receptor signal cascade that accelerates synthesis of glycogen and triglyceride. Parallel control by phos-dephos and redox regulation of proteins exists for some of these steps. A major action of insulin is to inhibit gluconeogensis in the liver decreasing glucose output into blood. Cases with failed control of blood glucose have alarmingly increased since 1960 coinciding with changed life-styles and large scale food processing. Many of these turned out to be resistant to insulin, usually accompanied by dysfunctional glycogen storage. Glucose has an extended stay in blood at 8 mM and above and then indiscriminately adds on to surface protein-amino groups. Fructose in common sugar is 10-fold more active. This random glycation process interferes with the functions of many proteins (e.g., hemoglobin, eye lens proteins) and causes progressive damage to heart, kidneys, eyes and nerves. Some compounds are known to act as insulin mimics. Vanadium-peroxide complexes act at post-receptor level but are toxic. The fungus-derived 2,5-dihydroxybenzoquinone derivative is the first one known to act on the insulin receptor. The safe herbal products in use for centuries for glucose control have multiple active principles and targets. Some are effective in slowing formation of glucose in intestines by inhibiting alpha-glucosidases (e.g., salacia/saptarangi). Knowledge gained from French lilac on active guanidine group helped developing Metformin (1,1-dimethylbiguanide) one of the popular drugs in use. One strategy of keeping sugar content in diets in check is to use artificial sweeteners with no calories, no glucose or fructose and no effect on blood glucose (e.g., steviol, erythrytol). However, the three commonly used non-caloric artificial sweetener's, saccharin, sucralose and aspartame later developed glucose intolerance, the very condition they are expected to evade. Ideal way of keeping blood glucose under 6 mM and HbAlc, the glycation marker of hemoglobin, under 7% in blood is to correct the defects in signals that allow glucose flow into glycogen, still a difficult task with drugs and diets.

Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals

Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.

An out-of-plane linear motion measurement system based on optical beam deflection

Measurement of out-of-plane linear motion with high precision and bandwidth is indispensable for development of precision motion stages and for dynamic characterization of mechanical structures. This paper presents an optical beam deflection (OBD) based system for measurement of out-of-plane linear motion for fully reflective samples. The system also achieves nearly zero cross-sensitivity to angular motion, and a large working distance. The sensitivities to linear and angular motion are analytically obtained and employed to optimize the system design. The optimal shot-noise limited resolution is shown to be less than one angstrom over a bandwidth in excess of 1 kHz. Subsequently, the system is experimentally realized and the sensitivities to out-of-plane motions are calibrated using a novel strategy. The linear sensitivity is found to be in agreement with theory. The angular sensitivity is shown to be over 7.5-times smaller than that of conventional OBD. Finally, the measurement system is employed to measure the transient response of a piezo-positioner, and, with the aid of an open-loop controller, reduce the settling time by about 90%. It is also employed to operate the positioner in closed-loop and demonstrate significant minimization of hysteresis and positioning error.

Status of the 98-125 GeV Higgs bosons scenario with updated LHC-8 data

In the context of the minimal supersymmetric standard model (MSSM), we discuss the possibility of the lightest Higgs boson with mass M-h = 98 GeV to be consistent with the 2.3 sigma excess observed at the LEP in the decay mode e(+)e(-) -> Zh, with h -> b (b) over bar. In the same region of the MSSM parameter space, the heavier Higgs boson (H) with mass M-H similar to 125 GeV is required to be consistent with the latest data on Higgs coupling measurements at the end of the 7 + 8 TeV LHC run with 25 fb(-1) of data. While scanning the MSSM parameter space, we impose constraints coming from flavor physics, relic density of the cold dark matter as well as direct dark matter searches. We study the possibility of observing this light Higgs boson in vector boson fusion process and associated production with W/Z-boson at the high luminosity (3000 fb(-1)) run of the 14 TeV LHC. Our analysis shows that this scenario can hardly be ruled out even at the high luminosity run of the LHC. However, the precise measurement of the Higgs signal strength ratios can play a major role to distinguish this scenario from the canonical MSSM one.