Air Pollution Control

The air we breathe is being polluted by activities such as vehicles; burning coal, oil, and other fossil fuels; and manufacturing chemicals. Air pollution can even come from smaller, everyday activities such as cooking, space heating, and degreasing and painting operations. These activities add gases and particles to the air we breathe. When these gases and particles accumulate in the air in high enough concentrations, they can harm us and our environment. The module on Air Pollution deals with the various sources of air pollution and the associated environmental and health impacts. It also discusses the appropriate measures to control/prevent the same.

Post combustion in cupola for pollution control

Carbon monoxide, a major pollutant from the cupola, is poisonous and flammable. It can vary from 12 to 25% in cupola emissions. Carbon monoxide content in cupola emissions can be reduced by the post-combustion air input at the appropriate level into the stack. Scientific support to this has been provided by simulation of the combustion process in the cupola. Location and the extent of input of air for post combustion into the stack have been determined.

Optimization of vibrating structures to reduce radiated noise

In this work, we propose an approach for reducing radiated noise from `light' fluid-loaded structures, such as, for example, vibrating structures in air. In this approach, we optimize the structure so as to minimize the dynamic compliance (defined as the input power) of the structure. We show that minimizing the dynamic compliance results in substantial reductions in the radiated sound power from the structure. The main advantage of this approach is that the redesign to minimize the dynamic compliance moves the natural frequencies of the structure away from the driving frequency thereby reducing the vibration levels of the structure, which in turn results in a reduction in the radiated sound power as an indirect benefit. Thus, the need for an acoustic and the associated sensitivity analysis is completely bypassed (although, in this work, we do carry out an acoustic analysis to demonstrate the reduction in sound power levels), making the strategy efficient compared to existing strategies in the literature which try to minimize some measure of noise directly. We show the effectiveness of the proposed approach by means of several examples involving both topology and stiffener optimization, for vibrating beam, plate and shell-type structures.

Experimental Investigation on the Effect of Advanced Bus-Clamping Pulsewidth Modulation on Motor Acoustic Noise

Voltage source inverters (VSIs) supply nonsinusoidal voltages to induction motor drives, leading to line current distortion and torque pulsation. Conventional space vector pulsewidth modulation (PWM) techniques are widely used in VSIs on the account of good waveform quality and high dc bus utilization. In a conventional space vector PWM technique, the switching sequence begins with one zero state and ends with the other zero state in a subcycle. Some novel switching sequences have been proposed, which employ only one zero state but apply one of the two active states twice in a subcycle. One pair of such special switching sequences has recently been shown to reduce the pulsating torque considerably. In this paper, the conventional and special switching sequences are compared experimentally in terms of acoustic noise. In the low-and medium-speed ranges, the special switching sequence is seen to reduce the amplitude of the tonal component of noise at the switching frequency considerably and is also found to result in spread spectrum.

Intrinsically disordered proteins and conformational noise Implications in cancer

Intrinsically disordered proteins, IDPs, are proteins that lack a rigid 3D structure under physiological conditions, at least in vitro. Despite the lack of structure, IDPs play important roles in biological processes and transition from disorder to order upon binding to their targets. With multiple conformational states and rapid conformational dynamics, they engage in myriad and often ``promiscuous'' interactions. These stochastic interactions between IDPs and their partners, defined here as conformational noise, is an inherent characteristic of IDP interactions. The collective effect of conformational noise is an ensemble of protein network configurations, from which the most suitable can be explored in response to perturbations, conferring protein networks with remarkable flexibility and resilience. Moreover, the ubiquitous presence of IDPs as transcriptional factors and, more generally, as hubs in protein networks, is indicative of their role in propagation of transcriptional (genetic) noise. As effectors of transcriptional and conformational noise, IDPs rewire protein networks and unmask latent interactions in response to perturbations. Thus, noise-driven activation of latent pathways could underlie state-switching events such as cellular transformation in cancer. To test this hypothesis, we created a model of a protein network with the topological characteristics of a cancer protein network and tested its response to a perturbation in presence of IDP hubs and conformational noise. Because numerous IDPs are found to be epigenetic modifiers and chromatin remodelers, we hypothesize that they could further channel noise into stable, heritable genotypic changes.

A low-noise low-power noise-adaptive neural amplifier in 0.13um CMOS technology

Chronic recording of neural signals is indispensable in designing efficient brain machine interfaces and in elucidating human neurophysiology. The advent of multichannel microelectrode arrays has driven the need for electronics to record neural signals from many neurons. The dynamic range of the system is limited by background system noise which varies over time. We propose a neural amplifier in UMC 130 nm, 2P8M CMOS technology. It can be biased adaptively from 200 nA to 2 uA, modulating input referred noise from 9.92 uV to 3.9 uV. We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. The amplifier can pass signal from 5 Hz to 7 kHz while rejecting input DC offsets at electrode-electrolyte interface. The bandwidth of the amplifier can be tuned by the pseudo-resistor for selectively recording low field potentials (LFP) or extra cellular action potentials (EAP). The amplifier achieves a mid-band voltage gain of 37 dB and minimizes the attenuation of the signal from neuron to the gate of the input transistor. It is used in fully differential configuration to reject noise of bias circuitry and to achieve high PSRR.

Parabolized stability equation models for predicting large-scale mixing noise of turbulent round jets

Parabolized stability equation (PSE) models are being deve loped to predict the evolu-tion of low-frequency, large-scale wavepacket structures and their radiated sound in high-speed turbulent round jets. Linear PSE wavepacket models were previously shown to be in reasonably good agreement with the amplitude envelope and phase measured using a microphone array placed just outside the jet shear layer. 1,2 Here we show they also in very good agreement with hot-wire measurements at the jet center line in the potential core,for a different set of experiments. 3 When used as a model source for acoustic analogy, the predicted far field noise radiation is in reasonably good agreement with microphone measurements for aft angles where contributions from large -scale structures dominate the acoustic field. Nonlinear PSE is then employed in order to determine the relative impor-tance of the mode interactions on the wavepackets. A series of nonlinear computations with randomized initial conditions are use in order to obtain bounds for the evolution of the modes in the natural turbulent jet flow. It was found that n onlinearity has a very limited impact on the evolution of the wavepackets for St≥0. 3. Finally, the nonlinear mechanism for the generation of a low-frequency mode as the difference-frequency mode 4,5 of two forced frequencies is investigated in the scope of the high Reynolds number jets considered in this paper.

Noise tolerance under risk minimization

In this paper, we explore noise-tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an unobservable training set that is noise free. The actual training set given to the learning algorithm is obtained from this ideal data set by corrupting the class label of each example. The probability that the class label of an example is corrupted is a function of the feature vector of the example. This would account for most kinds of noisy data one encounters in practice. We say that a learning method is noise tolerant if the classifiers learnt with noise-free data and with noisy data, both have the same classification accuracy on the noise-free data. In this paper, we analyze the noise-tolerance properties of risk minimization (under different loss functions). We show that risk minimization under 0-1 loss function has impressive noise-tolerance properties and that under squared error loss is tolerant only to uniform noise; risk minimization under other loss functions is not noise tolerant. We conclude this paper with some discussion on the implications of these theoretical results.

Suppression Of Barkhausen Noise Due To Exchange Biasing In Fe-FeMn Bilalayers

Exchange biased Fe(FM)-FeMn(AFM) bilayers were grown by pulsed laser ablation in UHV and probed by SQUID magnetometer and planar Hall effect measurements. A suppression of barkhausen avalanches was observed during the switching of the bilayer when compared to that of pure Fe, which is indicative of a change in the reversal mechanism.

Wide Voltage Input Receiver with Hysteresis Characteristic to Reduce Input Signal Noise Effect

In this paper, an input receiver with a hysteresis characteristic that can work at voltage levels between 0.9 V and 5 V is proposed. The input receiver can be used as a wide voltage range Schmitt trigger also. At the same time, reliable circuit operation is ensured. According to the research findings, this is the first time a wide voltage range Schmitt trigger is being reported. The proposed circuit is compared with previously reported input receivers, and it is shown that the circuit has better noise immunity. The proposed input receiver ends the need for a separate Schmitt trigger and input buffer. The frequency of operation is also higher than that of the previously reported receiver. The circuit is simulated using HSPICE at 035-mu m standard thin oxide technology. Monte Carlo analysis is conducted at different process conditions, showing that the proposed circuit works well for different process conditions at different voltage levels of operation. A noise impulse of (V-CC/2) magnitude is added to the input voltage to show that the receiver receives the correct logic level even in the presence of noise. Here, V-CC is the fixed voltage supply of 3.3 V.

High-resolution restoration of 3D structures from widefield images with extreme low signal-to-noise-ratio

Four-dimensional fluorescence microscopy-which records 3D image information as a function of time-provides an unbiased way of tracking dynamic behavior of subcellular components in living samples and capturing key events in complex macromolecular processes. Unfortunately, the combination of phototoxicity and photobleaching can severely limit the density or duration of sampling, thereby limiting the biological information that can be obtained. Although widefield microscopy provides a very light-efficient way of imaging, obtaining high-quality reconstructions requires deconvolution to remove optical aberrations. Unfortunately, most deconvolution methods perform very poorly at low signal-to-noise ratios, thereby requiring moderate photon doses to obtain acceptable resolution. We present a unique deconvolution method that combines an entropy-based regularization function with kernels that can exploit general spatial characteristics of the fluorescence image to push the required dose to extreme low levels, resulting in an enabling technology for high-resolution in vivo biological imaging.

Signal Detection in Generalized Gaussian Noise by Nonlinear Wavelet Denoising

In this paper, a nonlinear suboptimal detector whose performance in heavy-tailed noise is significantly better than that of the matched filter is proposed. The detector consists of a nonlinear wavelet denoising filter to enhance the signal-to-noise ratio, followed by a replica correlator. Performance of the detector is investigated through an asymptotic theoretical analysis as well as Monte Carlo simulations. The proposed detector offers the following advantages over the optimal (in the Neyman-Pearson sense) detector: it is easier to implement, and it is more robust with respect to error in modeling the probability distribution of noise.

Experimental Study on Substrate Noise Effects of a Pulsed Clocking Scheme on PLL Performance

In this brief, the substrate noise effects of a pulsed clocking scheme on the output spur level, the phase noise, and the peak-to-peak (Pk-Pk) deterministic period jitter of an integer-N charge-pump phase-locked loop (PLL) are demonstrated experimentally. The phenomenon of noise coupling to the PLL is also explained through experiments. The PLL output frequency is 500 MHz and it is implemented in the 0.13-mu m CMOS technology. Measurements show a reduction of 12.53 dB in the PLL output spur level at an offset of 5 MHz and a reduction of 107 ps in the Pk-Pk deterministic period jitter upon reducing the duty cycle of the signal injected into the substrate from 50% to 20%. The results of the analyses suggest that using a pulsed clocking scheme for digital systems in mixed-signal integration along with other isolation techniques helps reduce the substrate noise effects on sensitive analog/radio-frequency circuits.