59 resultados para Lactate minimum
Resumo:
A Finite Feedback Scheme (FFS) for a quasi-static MIMO block fading channel with finite N-ary delay-free noise-free feedback consists of N Space-Time Block Codes (STBCs) at the transmitter, one corresponding to each possible value of feedback, and a function at the receiver that generates N-ary feedback. A number of FFSs are available in the literature that provably attain full-diversity. However, there is no known full-diversity criterion that universally applies to all FFSs. In this paper a universal necessary condition for any FFS to achieve full-diversity is given, and based on this criterion the notion of Feedback-Transmission duration optimal (FT-optimal) FFSs is introduced, which are schemes that use minimum amount of feedback N for the given transmission duration T, and minimum T for the given N to achieve full-diversity. When there is no feedback (N = 1) an FT-optimal scheme consists of a single STBC, and the proposed condition reduces to the well known necessary and sufficient condition for an STBC to achieve full-diversity. Also, a sufficient criterion for full-diversity is given for FFSs in which the component STBC yielding the largest minimum Euclidean distance is chosen, using which full-rate (N-t complex symbols per channel use) full-diversity FT-optimal schemes are constructed for all N-t > 1. These are the first full-rate full-diversity FFSs reported in the literature for T < N-t. Simulation results show that the new schemes have the best error performance among all known FFSs.
Resumo:
The authors consider the channel estimation problem in the context of a linear equaliser designed for a frequency selective channel, which relies on the minimum bit-error-ratio (MBER) optimisation framework. Previous literature has shown that the MBER-based signal detection may outperform its minimum-mean-square-error (MMSE) counterpart in the bit-error-ratio performance sense. In this study, they develop a framework for channel estimation by first discretising the parameter space and then posing it as a detection problem. Explicitly, the MBER cost function (CF) is derived and its performance studied, when transmitting binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals. It is demonstrated that the MBER based CF aided scheme is capable of outperforming existing MMSE, least square-based solutions.
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Phase-locked loops (PLLs) are necessary in grid connected systems to obtain information about the frequency, amplitude and phase of the grid voltage. In stationary reference frame control, the unit vectors of PLLs are used for reference generation. It is important that the PLL performance is not affected significantly when grid voltage undergoes amplitude and frequency variations. In this paper, a novel design for the popular single-phase PLL topology, namely the second-order generalized integrator (SOGI) based PLL is proposed which achieves minimum settling time during grid voltage amplitude and frequency variations. The proposed design achieves a settling time of less than 27.7 ms. This design also ensures that the unit vectors generated by this PLL have a steady state THD of less than 1% during frequency variations of the grid voltage. The design of the SOGI-PLL based on the theoretical analysis is validated by experimental results.
Resumo:
Advanced bus-clamping switching sequences, which employ an active vector twice in a subcycle, are used to reduce line current distortion and switching loss in a space vector modulated voltage source converter. This study evaluates minimum switching loss pulse width modulation (MSLPWM), which is a combination of such sequences, for static reactive power compensator (STATCOM) application. It is shown that MSLPWM results in a significant reduction in device loss over conventional space vector pulse width modulation. Experimental verification is presented at different power levels of up to 150 kVA.
Resumo:
Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.
Resumo:
Lactate dehydrogenase (LDH) of the malaria parasite, Plasmodium vivax (Pv), serves as a drug target and immunodiagnostic marker. The LDH cDNA generated from total RNA of a clinical isolate of the parasite was cloned into pRSETA plasmid. Recombinant his-tagged PvLDH was over-expressed in E. coli Rosetta2DE3pLysS and purified using Ni2+-NTA resin giving a yield of 25-30 mg/litre bacterial culture. The recombinant protein was enzymatically active and its catalytic efficiency for pyruvate was 5.4 x 10(8) min(-1) M-1, 14.5 fold higher than a low yield preparation reported earlier to obtain PvLDH crystal structure. The enzyme activity was inhibited by gossypol and sodium oxamate. The recombinant PvLDH was reactive in lateral flow immunochromatographic assays detecting pan- and vivax-specific LDH. The soluble recombinant PvLDH purified using heterologous expression system can facilitate the generation of vivax LDH-specific monoclonals and the screening of chemical compound libraries for PvLDH inhibitors.
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We address the problem of designing an optimal pointwise shrinkage estimator in the transform domain, based on the minimum probability of error (MPE) criterion. We assume an additive model for the noise corrupting the clean signal. The proposed formulation is general in the sense that it can handle various noise distributions. We consider various noise distributions (Gaussian, Student's-t, and Laplacian) and compare the denoising performance of the estimator obtained with the mean-squared error (MSE)-based estimators. The MSE optimization is carried out using an unbiased estimator of the MSE, namely Stein's Unbiased Risk Estimate (SURE). Experimental results show that the MPE estimator outperforms the SURE estimator in terms of SNR of the denoised output, for low (0 -10 dB) and medium values (10 - 20 dB) of the input SNR.
Resumo:
In a complete bipartite graph with vertex sets of cardinalities n and n', assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as n -> infinity, with n' = n/alpha] for any fixed alpha > 1, the minimum weight of many-to-one matchings converges to a constant (depending on alpha). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.
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Small covers were introduced by Davis and Januszkiewicz in 1991. We introduce the notion of equilibrium triangulations for small covers. We study equilibrium and vertex minimal 4-equivariant triangulations of 2-dimensional small covers. We discuss vertex minimal equilibrium triangulations of RP3#RP3, S-1 x RP2 and a nontrivial S-1 bundle over RP2. We construct some nice equilibrium triangulations of the real projective space RPn with 2(n) + n 1 vertices. The main tool is the theory of small covers.
Resumo:
Minimizing energy consumption is of utmost importance in an energy starved system with relaxed performance requirements. This brief presents a digital energy sensing method that requires neither a constant voltage reference nor a time reference. An energy minimizing loop uses this to find the minimum energy point and sets the supply voltage between 0.2 and 0.5 V. Energy savings up to 1275% over existing minimum energy tracking techniques in the literature is achieved.
Resumo:
We consider carrier frequency offset (CFO) estimation in the context of multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems over noisy frequency-selective wireless channels with both single- and multiuser scenarios. We conceived a new approach for parameter estimation by discretizing the continuous-valued CFO parameter into a discrete set of bins and then invoked detection theory, analogous to the minimum-bit-error-ratio optimization framework for detecting the finite-alphabet received signal. Using this radical approach, we propose a novel CFO estimation method and study its performance using both analytical results and Monte Carlo simulations. We obtain expressions for the variance of the CFO estimation error and the resultant BER degradation with the single- user scenario. Our simulations demonstrate that the overall BER performance of a MIMO-OFDM system using the proposed method is substantially improved for all the modulation schemes considered, albeit this is achieved at increased complexity.
Resumo:
Gas discharge plasmas used for thinfilm deposition by plasma-enhanced chemical vapor deposition (PECVD) must be devoid of contaminants, like dust or active species which disturb the intended chemical reaction. In atmospheric pressure plasma systems employing an inert gas, the main source of such contamination is the residual air inside the system. To enable the construction of an atmospheric pressure plasma (APP) system with minimal contamination, we have carried out fluid dynamic simulation of the APP chamber into which an inert gas is injected at different mass flow rates. On the basis of the simulation results, we have designed and built a simple, scaled APP system, which is capable of holding a 100 mm substrate wafer, so that the presence of air (contamination) in the APP chamber is minimized with as low a flow rate of argon as possible. This is examined systematically by examining optical emission from the plasma as a function of inert gas flow rate. It is found that optical emission from the plasma shows the presence of atmospheric air, if the inlet argon flow rate is lowered below 300 sccm. That there is minimal contamination of the APP reactor built here, was verified by conducting an atmospheric pressure PECVD process under acetylene flow, combined with argon flow at 100 sccm and 500 sccm. The deposition of a polymer coating is confirmed by infrared spectroscopy. X-ray photoelectron spectroscopy shows that the polymer coating contains only 5% of oxygen, which is comparable to the oxygen content in polymer deposits obtained in low-pressure PECVD systems. (C) 2015 AIP Publishing LLC.
Resumo:
Key points The physiological metabolite, lactate and the two-pore domain leak potassium channel, TREK1 are known neuroprotectants against cerebral ischaemia. However, it is not known whether lactate interacts with TREK1 channel to provide neuroprotection. In this study we show that lactate increases TREK1 channel activity and hyperpolarizes CA1 stratum radiatum astrocytes in hippocampal slices. Lactate increases open probability and decreases longer close time of the human (h)TREK1 channel in a concentration dependent manner. Lactate interacts with histidine 328 (H328) in the carboxy terminal domain of hTREK1 channel to decrease its dwell time in the longer closed state. This interaction was dependent on the charge on H328. Lactate-insensitive mutant H328A hTREK1 showed pH sensitivity similar to wild-type hTREK1, indicating that the effect of lactate on hTREK1 is independent of pH change. AbstractA rise in lactate concentration and the leak potassium channel TREK1 have been independently associated with cerebral ischaemia. Recent literature suggests lactate to be neuroprotective and TREK1 knockout mice show an increased sensitivity to brain and spinal cord ischaemia; however, the connecting link between the two is missing. Therefore we hypothesized that lactate might interact with TREK1 channels. In the present study, we show that lactate at ischaemic concentrations (15-30mm) at pH7.4 increases TREK1 current in CA1 stratum radiatum astrocytes and causes membrane hyperpolarization. We confirm the intracellular action of lactate on TREK1 in hippocampal slices using monocarboxylate transporter blockers and at single channel level in cell-free inside-out membrane patches. The intracellular effect of lactate on TREK1 is specific since other monocarboxylates such as pyruvate and acetate at pH7.4 failed to increase TREK1 current. Deletion and point mutation experiments suggest that lactate decreases the longer close dwell time incrementally with increase in lactate concentration by interacting with the histidine residue at position 328 (H328) in the carboxy terminal domain of the TREK1 channel. The interaction of lactate with H328 is dependent on the charge on the histidine residue since isosteric mutation of H328 to glutamine did not show an increase in TREK1 channel activity with lactate. This is the first demonstration of a direct effect of lactate on ion channel activity. The action of lactate on the TREK1 channel signifies a separate neuroprotective mechanism in ischaemia since it was found to be independent of the effect of acidic pH on channel activity. Key points The physiological metabolite, lactate and the two-pore domain leak potassium channel, TREK1 are known neuroprotectants against cerebral ischaemia. However, it is not known whether lactate interacts with TREK1 channel to provide neuroprotection. In this study we show that lactate increases TREK1 channel activity and hyperpolarizes CA1 stratum radiatum astrocytes in hippocampal slices. Lactate increases open probability and decreases longer close time of the human (h)TREK1 channel in a concentration dependent manner. Lactate interacts with histidine 328 (H328) in the carboxy terminal domain of hTREK1 channel to decrease its dwell time in the longer closed state. This interaction was dependent on the charge on H328. Lactate-insensitive mutant H328A hTREK1 showed pH sensitivity similar to wild-type hTREK1, indicating that the effect of lactate on hTREK1 is independent of pH change.
Resumo:
In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.