144 resultados para Signal de transduction
Resumo:
Two-dimensional magnetic recording (2-D TDMR) is an emerging technology that aims to achieve areal densities as high as 10 Tb/in(2) using sophisticated 2-D signal-processing algorithms. High areal densities are achieved by reducing the size of a bit to the order of the size of magnetic grains, resulting in severe 2-D intersymbol interference (ISI). Jitter noise due to irregular grain positions on the magnetic medium is more pronounced at these areal densities. Therefore, a viable read-channel architecture for TDMR requires 2-D signal-detection algorithms that can mitigate 2-D ISI and combat noise comprising jitter and electronic components. Partial response maximum likelihood (PRML) detection scheme allows controlled ISI as seen by the detector. With the controlled and reduced span of 2-D ISI, the PRML scheme overcomes practical difficulties such as Nyquist rate signaling required for full response 2-D equalization. As in the case of 1-D magnetic recording, jitter noise can be handled using a data-dependent noise-prediction (DDNP) filter bank within a 2-D signal-detection engine. The contributions of this paper are threefold: 1) we empirically study the jitter noise characteristics in TDMR as a function of grain density using a Voronoi-based granular media model; 2) we develop a 2-D DDNP algorithm to handle the media noise seen in TDMR; and 3) we also develop techniques to design 2-D separable and nonseparable targets for generalized partial response equalization for TDMR. This can be used along with a 2-D signal-detection algorithm. The DDNP algorithm is observed to give a 2.5 dB gain in SNR over uncoded data compared with the noise predictive maximum likelihood detection for the same choice of channel model parameters to achieve a channel bit density of 1.3 Tb/in(2) with media grain center-to-center distance of 10 nm. The DDNP algorithm is observed to give similar to 10% gain in areal density near 5 grains/bit. The proposed signal-processing framework can broadly scale to various TDMR realizations and areal density points.
Resumo:
We propose a multiple initialization based spectral peak tracking (MISPT) technique for heart rate monitoring from photoplethysmography (PPG) signal. MISPT is applied on the PPG signal after removing the motion artifact using an adaptive noise cancellation filter. MISPT yields several estimates of the heart rate trajectory from the spectrogram of the denoised PPG signal which are finally combined using a novel measure called trajectory strength. Multiple initializations help in correcting erroneous heart rate trajectories unlike the typical SPT which uses only single initialization. Experiments on the PPG data from 12 subjects recorded during intensive physical exercise show that the MISPT based heart rate monitoring indeed yields a better heart rate estimate compared to the SPT with single initialization. On the 12 datasets MISPT results in an average absolute error of 1.11 BPM which is lower than 1.28 BPM obtained by the state-of-the-art online heart rate monitoring algorithm.
Resumo:
Protein lysine acetylation is known to regulate multiple aspects of bacterial metabolism. However, its presence in mycobacterial signal transduction and virulence-associated proteins has not been studied. In this study, analysis of mycobacterial proteins from different cellular fractions indicated dynamic and widespread occurrence of lysine acetylation. Mycobacterium tuberculosis proteins regulating diverse physiological processes were then selected and expressed in the surrogate host Mycobacterium smegmatis. The purified proteins were analyzed for the presence of lysine acetylation, leading to the identification of 24 acetylated proteins. In addition, novel lysine succinylation and propionylation events were found to co-occur with acetylation on several proteins. Protein-tyrosine phosphatase B (PtpB), a secretory phosphatase that regulates phosphorylation of host proteins and plays a critical role in Mycobacterium infection, is modified by acetylation and succinylation at Lys-224. This residue is situated in a lid region that covers the enzyme's active site. Consequently, acetylation and succinylation negatively regulate the activity of PtpB.
Resumo:
Shallow-trench isolation drain extended pMOS (STI-DePMOS) devices show a distinct two-stage breakdown. The impact of p-well and deep-n-well doping profile on breakdown characteristics is investigated based on TCAD simulations. Design guidelines for p-well and deep-n-well doping profile are developed to shift the onset of the first-stage breakdown to a higher drain voltage and to avoid vertical punch-through leading to early breakdown. An optimal ratio between the OFF-state breakdown voltage and the ON-state resistance could be obtained. Furthermore, the impact of p-well/deep-n-well doping profile on the figure of merits of analog and digital performance is studied. This paper aids in the design of STI drain extended MOSFET devices for widest safe operating area and optimal mixed-signal performance in advanced system-on-chip input-output process technologies.
Resumo:
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.
Resumo:
Emerging data on cancer suggesting that target-based therapy is promising strategy in cancer treatment. PI3K-AKT pathway is extensively studied in many cancers; several inhibitors target this pathway in different levels. Recent finding on this pathway uncovered the therapeutic applications of PI3K-specific inhibitors; PI3K, AKT, and mTORC broad spectrum inhibitors. Noticeably, class I PI3K isoforms, p110 and p110 catalytic subunits have rational therapeutic application than other isoforms. Therefore, three classes of inhibitors: isoform-specific, dual-specific and broad spectrum were selected for molecular docking and dynamics. First, p110 structure was modelled; active site was analyzed. Then, molecular docking of each class of inhibitors were studied; the docked complexes were further used in 1.2ns molecular dynamics simulation to report the potency of each class of inhibitor. Remarkably, both the studies retained the similar kind of protein ligand interactions. GDC-0941, XL-147 (broad spectrum); TG100-115 (dual-specific); and AS-252424, PIK-294 (isoform-specific) were found to be potential inhibitors of p110 and p110, respectively. In addition to that pharmacokinetic properties are within recommended ranges. Finally, molecular phylogeny revealed that p110 and p110 are evolutionarily divergent; they probably need separate strategies for drug development.
Resumo:
This paper demonstrates light-load instability in a 100-kW open-loop induction motor drive on account of inverter deadtime. An improved small-signal model of an inverter-fed induction motor is proposed. This improved model is derived by linearizing the nonlinear dynamic equations of the motor, which include the inverter deadtime effect. Stability analysis is carried out on the 100-kW415-V three-phase induction motor considering no load. The analysis brings out the region of instability of this motor drive on the voltage versus frequency (V-f) plane. This region of light-load instability is found to expand with increase in inverter deadtime. Subharmonic oscillations of significant amplitude are observed in the steady-state simulated and measured current waveforms, at numerous operating points in the unstable region predicted, confirming the validity of the stability analysis. Furthermore, simulation and experimental results demonstrate that the proposed model is more accurate than an existing small-signal model in predicting the region of instability.
Resumo:
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.
Resumo:
Hydrogen peroxide (H2O2) is a key reactive oxygen species and a messenger in cellular signal transduction apart from playing a vital role in many biological processes in living organisms. In this article, we present phenyl boronic acid-functionalized quinone-cyanine (QCy-BA) in combination with AT-rich DNA (exogenous or endogenous cellular DNA), i.e., QCy-BA subset of DNA as a stimuli-responsive NIR fluorescence probe for measuring in vitro levels of H2O2. In response to cellular H2O2 stimulus, QCy-BA converts into QCy-DT, a one-donor-two-acceptor (D2A) system that exhibits switch-on NIR fluorescence upon binding to the DNA minor groove. Fluorescence studies on the combination probe QCy-BA subset of DNA showed strong NIR fluorescence selectively in the presence of H2O2. Furthermore, glucose oxidase (GOx) assay confirmed the high efficiency of the combination probe QCy-BA subset of DNA for probing H2O2 generated in situ through GOx-mediated glucose oxidation. Quantitative analysis through fluorescence plate reader, flow cytometry and live imaging approaches showed that QCy-BA is a promising probe to detect the normal as well as elevated levels of H2O2 produced by EGF/Nox pathways and post-genotoxic stress in both primary and senescent cells. Overall, QCy-BA, in combination with exogenous or cellular DNA, is a versatile probe to quantify and image H2O2 in normal and disease-associated cells.