71 resultados para Simultaneous Diophantine approximations
Resumo:
We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.
Resumo:
A simple yet remarkable, electrochemically activated carbon paste electrode (EACPE) was prepared by successive potential cycling of carbon paste in a 0.1 M NaOH solution and was effectively used for the simultaneous determination of catecholamines such as dopamine (DA), epinephrine (E) and Norepinephrine (NE) in presence of uric acid (UA) and ascorbic acid (AA). Taking DA as the ideal catecholamine, the electrochemical behaviors of DA, UA and AA such as scan rate and pH variation was studied by cyclic voltammetry (CV) in phosphate buffer solution (PBS, pH 7.1). This electrochemical sensor exhibited strong electrocatalytic activity towards the oxidation of a mixture of catecholamines, UA and AA with apparent reduction of overpotentials. Crider optimum conditions, limit of detection (S/N = 3) of DA, E, NE, UA and AA was found to be 0.08, 0.08, 0.07, 0.1 and 6.0 mu M, respectively by differential pulse voltammetry (DPV). The analytical performance of this modified electrode as a biosensor was also demonstrated for the determination of DA, UA and AA in dopamine injection, human urine and vitamin C tablets, respectively, in presence of other interfering substances. (C) 2015 The Electrochemical Society. All-rights reserved.
Resumo:
A unique approach was adopted to drive the multiwall carbon nanotubes (MWNTs) to the interface of immiscible PVDF-ABS blends by wrapping the nanotubes with a mutually miscible homopolymer (PMMA). A tailor made interface with an improved stress transfer was achieved in the blends with PMMA wrapped MWNTs. This manifested in an impressive 108% increment in the tensile strength and 48% increment in the Young's modulus with 3 wt% PMMA wrapped MWNTs in striking contrast to the neat blends. As the PMMA wrapped MWNTs localized at the interface of PVDF-ABS blends, the electrical conductivity could be tuned with respect to only MWNTs, which were selectively localized in the PVDF phase, driven by thermodynamics. The electromagnetic shielding properties were assessed using a vector network analyser in a broad range of frequency, X-band (8-12 GHz) and Ku-band (12-18 GHz). Interestingly, enhanced EM shielding was achieved by this unique approach. The blends with only MWNTs shielded the EM waves mostly by reflection however, the blends with PMMA wrapped MWNTs (3 wt%) shielded mostly by absorption (62%). This study opens new avenues in designing materials, which show simultaneous improvement in mechanical, electrical conductivity and EM shielding properties.
Resumo:
In bacteria, alternate mechanisms are known to synthesize N-10-formyltetrahydrofolate (N10-formyl-THF) and formyl glycinamide ribotide (fGAR), which are important in purine biosynthesis. In one of the mechanisms, a direct transfer of one carbon unit from formate allows Fhs to convert tetrahydrofolate to N-10-formyl-THF, and PurT to convert glycinamide ribotide (GAR) to fGAR. Our bioinformatics analysis of fhs and purT genes (encoding Fhs and PurT) showed that in a majority of bacteria (similar to 94%), their presence was mutually exclusive. A large number of organisms possessing fhs lacked purT and vice versa. The phenomenon is so penetrating that even within a genus (Bacillus) if a species possessed fhs it lacked purT and vice versa. To investigate physiological importance of this phenomenon, we used Escherichia coli, which naturally lacks fhs (and possesses purT) as model. We generated strains, which possessed fhs and purT genes in singles or together. Deletion of purT from E. coli in the presence or absence of fhs did not confer a detectable growth disadvantage in pure cultures. However, growth competition assays revealed that the strains possessing either of the single genes outcompeted those possessing both the genes suggesting that mutual exclusion of purT and fhs in organisms confers fitness advantage in mixed cultures.
Resumo:
NMR-based approach to metabolomics typically involves the collection of two-dimensional (2D) heteronuclear correlation spectra for identification and assignment of metabolites. In case of spectral overlap, a 3D spectrum becomes necessary, which is hampered by slow data acquisition for achieving sufficient resolution. We describe here a method to simultaneously acquire three spectra (one 3D and two 2D) in a single data set, which is based on a combination of different fast data acquisition techniques such as G-matrix Fourier transform (GFT) NMR spectroscopy, parallel data acquisition and non-uniform sampling. The following spectra are acquired simultaneously: (1) C-13 multiplicity edited GFT (3,2)D HSQC-TOCSY, (2) 2D H-1- H-1] TOCSY and (3) 2D C-13- H-1] HETCOR. The spectra are obtained at high resolution and provide high-dimensional spectral information for resolving ambiguities. While the GFT spectrum has been shown previously to provide good resolution, the editing of spin systems based on their CH multiplicities further resolves the ambiguities for resonance assignments. The experiment is demonstrated on a mixture of 21 metabolites commonly observed in metabolomics. The spectra were acquired at natural abundance of C-13. This is the first application of a combination of three fast NMR methods for small molecules and opens up new avenues for high-throughput approaches for NMR-based metabolomics.
Resumo:
We prove that given a Hecke-Maass form f for SL(2, Z) and a sufficiently large prime q, there exists a primitive Dirichlet character chi of conductor q such that the L-values L(1/2, f circle times chi) and L(1/2, chi) do not vanish.
Resumo:
We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
The inverse coupled dependence of electrical conductivity and thermopower on carrier concentration presents a big challenge in achieving a high figure of merit. However, the simultaneous enhancement of electrical conductivity and thermopower can be realized in practice by carefully engineering the electronic band structure. Here by taking the example of Bi2S3, we report a simultaneous increase in both electrical conductivity and thermopower under hydrostatic pressure. Application of hydrostatic pressure enables tuning of electronic structure in such a way that the conductivity effective mass decreases and the density of states effective mass increases. This dependence of effective masses leads to simultaneous enhancement in electrical conductivity and thermopower under n-type doping leading to a huge improvement in the power factor. Also lattice thermal conductivity exhibits very weak pressure dependence in the low pressure range. The large power factor together with low lattice thermal conductivity results in a high ZT value of 1.1 under n-type doping, which is nearly two times higher than the previously reported value. Hence, this pressure-tuned behaviour can enable the development of efficient thermoelectric devices in the moderate to high temperature range. We further demonstrate that similar enhancement can be observed by generating chemical pressure by doping Bi2S3 with smaller iso-electronic elements such as Sb at Bi sites, which can be achieved experimentally.
Resumo:
Controlled variation of the electronic properties of. two-dimensional (2D) materials by applying strain has emerged as a promising way to design materials for customized applications. Using density functional theory (DFT) calculations, we show that while the electronic structure and indirect band gap of SnS2 do not change significantly with the number of layers, they can be reversibly tuned by applying biaxial tensile (BT), biaxial compressive (BC), and normal compressive (NC) strains. Mono to multilayered SnS2 exhibit a reversible semiconductor to metal (S-M) transition with applied strain. For bilayer (2L) SnS2, the S-Mtransition occurs at the strain values of 17%,-26%, and -24% under BT, BC, and NC strains, respectively. Due to weaker interlayer coupling, the critical strain value required to achieve the S-Mtransition in SnS2 under NC strain is much higher than for MoS2. From a stability viewpoint, SnS2 becomes unstable at very low strain values on applying BC (-6.5%) and BT strains (4.9%), while it is stable even up to the transition point (-24%) in the case of NC strain. In addition to the reversible tuning of the electronic properties of SnS2, we also show tunability in the phononic band gap of SnS2, which increases with applied NC strain. This gap increases three times faster than for MoS2. This simultaneous tunability of SnS2 at the electronic and phononic levels with strain, makes it a potential candidate in field effect transistors (FETs) and sensors as well as frequency filter applications.