Analysis of underivatized amino acids and their D/L-enantiomers by sheathless capillary electrophoresis/electrospray ionization mass spectrometry

Capillary electrophoresis/electrospray ionization-mass spectrometry (CE/ESI-MS) was applied to the analysis of underivatized amino acids and the separation of their D/L-enantiomers. Under full-scan mode, all standard protein amino acids were separated and detected at low-femtomole levels using a 130-cm-long, 20-microm-i.d., 150-microm-o.d. underivatized fused-silica capillary with 1 M formic acid as the background electrolyte. The CE/ESI-MS technique was also applied to the separation of L-arginine from L-canavanine (a close analogue of arginine where the terminal methylene linked to the guanidine group of arginine is replaced by an oxygen atom) in a complex mixture containing all standard protein amino acids. The utility of CE/ESI-MS in the analysis of real-world samples was demonstrated by the identification of two metabolic diseases (PKU and tyrosinemia) through blood analysis with minimal sample preparation. In addition, the on-line separation of 11 underivatized L-amino acids from their D-enantiomers was achieved by using a 30 mM solution of (+)-(18-crown-6)-2,3,11,12-tetracarboxylic acid as the background electrolyte.     

CE/electrospray ionization-MS analysis of underivatized d/l-amino acids and several small neurotransmitters at attomole levels through the use of 18-crown-6-tetracarboxylic acid as a complexation reagent/background electrolyte

A new capillary electrophoresis/mass spectrometry technique is introduced for attomole detection of primary amines (including several neurotransmitters), amino acids, and their d/l enantiomers in one run through the use of a complexation reagent while using only approximately 1 nL of sample. The technique uses underivatized amino acids in conjunction with an underivatized capillary, which significantly reduces cost and analysis time. It was found that when (+)-(18-crown-6)-2,3,11,12-tetracarboxylic acid (18-C-6-TCA, MW 440) was used as the background electrolyte/complexation reagent during the capillary electrophoresis/electrospray ionization-mass spectrometry (CE/ESI-MS) analysis of underivatized amino acids, stable complexes were formed between the amino acids and the 18-C-6-TCA molecules. These complexes, which exhibited high ionization efficiencies, were detectable at attomole levels for most amino acids. The detection limits of the AA/18-C-6-TCA complexes were on the average more than 2 orders of magnitude lower than that of the free amino acids in solution. In addition to lower detection limits under CE/ESI-MS, a solution of 18-C-6-TCA in the concentration range of 5-30 mM provided high separation efficiency for mixtures of l-amino acids as well as mixtures of d/l-amino acids. By using a solution of 18-C-6-TCA as the background electrolyte in conjunction with an underivatized, 130-cm-long, 20-microm-i.d., 150-microm-o.d. fused-silica capillary and by monitoring the m/z range of the amino acid/18-C-6-TCA complexes (m/z 515-700), most of the standard amino acids and many of their enantiomers were separated and detected with high separation efficiency and high sensitivity (nanomolar concentration detection limits) in one run. The solutions of 18-C-6-TCA also worked well as the CE/ESI-MS BGE for low-level detection of several neurotransmitters and some of their d/l enantiomers as well as for the analysis of amino acids at endogenous levels in lysed red blood cells.     

Identifying a control function in parabolic partial differential equations from overspecified boundary data

Determination of an unknown time-dependent function in parabolic partial differential equations, plays a very important role in many branches of science and engineering. In the current investigation, the Adomian decomposition method is used for finding a control parameter p(t) in the quasilinear parabolic equation u_t=u_xx+p(t)u+, in [0,1]×(0,T] with known initial and boundary conditions and subject to an additional condition in the form of which is called the boundary integral overspecification. The main approach is to change this inverse problem to a direct problem and then solve the resulting equation using the well known Adomian decomposition method. The decomposition procedure of Adomian provides the solution in a rapidly convergent series where the series may lead to the solution in a closed form. Furthermore due to the rapid convergence of Adomian’s method, a truncation of the series solution with sufficiently large number of implemented components can be considered as an accurate approximation of the exact solution. This method provides a reliable algorithm that requires less work if compared with the traditional techniques. Some illustrative examples are presented to show the efficiency of the presented method.     

Ranking function-based solutions of fully fuzzified minimal cost flow problem

The aim of minimal cost flow problem (MCFP) is to find the least transportation cost of a single commodity through a capacitated network. This paper presents a model to deal with one particular group of such problems in which the supply and demand of nodes and the capacity and cost of edges are represented as fuzzy numbers. For easier reference, hereafter, we refer to this group of problems as fully fuzzified MCFP. To represent our model, Hukuhara’s difference and approximated multiplication are used. Thereafter, we sort fuzzy numbers by an order using a ranking function and show that it is a total order, i.e., a reflexive, anti-symmetric, transitive and complete binary relation. Utilizing the proposed ranking function, we transform the fully fuzzified MCFP into three crisp problems solvable in polynomial time. From this standpoint, combinatorial algorithms are provided to solve the above-mentioned problem and find the fuzzy optimal flow. Furthermore, the proposed order is related to the importance weights of the center, the left spread and the right spread of each fuzzy number. Thus, this method is capable of handling the decision maker’s risk taking. By comparing some previous ranking function-based works with our method, the efficiency of the latter is revealed. Finally, an application of our proposed method to petroleum industry is presented.     

Velocity Distributions in Spatially Varied Flow with Increasing Discharge

The experimental study presented in this paper explores the distribution of the mean velocities for a channel receiving spatially varied (SV) inflow from directly above the centerline of the channel via sets of nozzles. The velocity components u, v, and w have been measured using a laser Doppler velocimeter. Initially the validity of the law of the wall in the channel receiving SV inflow was investigated. It was found that the measured velocity profile within the inertial sublayer region near the channel bed falls below the line representing the log law. Further, if the SV inflow enters at the center of the channel, the degree that the data depart from the log law increases from the sidewall toward the center of the channel. The structures of the velocity distributions are also presented in detail. The results include both near field, that is the area close to where the flow enters the channel, and far field measurements. It was found that the influence of the SV inflow on velocity profiles is largely contained within the SV inflow zone and that the influence within this zone reduces in the downstream direction. At any one section within this zone the influence reduces from the center of the channel toward the sidewall. In addition, some features of the secondary flow established by the SV inflow are described.     

Failure Analysis of AISI 321 Austenitic Stainless Steel Water Piping in a Power Plant

The objective of this work was to analyze a reported pitting damage mechanism in water piping of a power plant. The investigated material was a longitudinal-seam welded pipe which was made of AISI 321 austenitic stainless steel. Pitting occurred on the internal surfaces of the pipe and adjacent to the girth welds. Optical emission spectrometry, metallography, and electrochemical testing were the techniques employed to analyze the failure. The investigation showed that the flowing water contained chloride ions in which AISI 321 austenitic stainless steel is not immune against pitting corrosion. In addition, the polarization data showed the susceptibility of the material to pitting corrosion in the service conditions. Furthermore, the result of double loop electrochemical potentiokinetic reactivation tests showed that the material was sensitized during welding. It was found that the damage was due to pitting corrosion in chloride-containing water. Thus, it was recommended to replace the pipe with material having higher pitting resistance equivalent number to be more resistant against pitting corrosion.     

An uncertainty compensator for robust control of wheeled mobile robots

This paper proposes an uncertainty compensator to design a novel robust control for mobile robots with dynamic and kinematic uncertainties. A novel gradient-based adaptive fuzzy estimator is developed to compensate uncertainties with minimum required feedback signals. As a novelty, the proposed approach uses the tracking error and its first time derivative to form the estimation error of uncertainty, and guarantees that both the estimation error and tracking error converge asymmetrically to ignorable value. Advantages of the proposed robust control are simplicity in design, robustness against uncertainties, guaranteed stability, and good control performance. The control approach is verified by stability analysis. Simulation results and experimental results illustrate the effectiveness of the proposed control. Experimental evaluation of the proposed controller is expressed for two different low-cost nonholonomic wheeled mobile robots. The proposed control design is compared with an adaptive control approach to confirm the superiority of the proposed approach in terms of precision, simplicity of design, and computations.     

LAMR: learning automata based multicast routing protocol for multi-channel multi-radio wireless mesh networks

Multicast routing is a crucial issue in wireless networks in which the same content should be delivered to a group of recipients simultaneously. Multicast is also considered as a key service for audio and video applications as well as data dissemination protocols over the last-mile backhaul Internet connectivity provided by multi-channel multi-radio wireless mesh networks (MCMR WMNs). The multicast problem is essentially related to a channel assignment strategy which determines the most suitable channel-radio associations. However, channel assignment brings about its own complications and hence, solving the multicast problem in MCMR WMNs will be more complicated than that of traditional networks. This problem has been proved to be NP-hard. In the major prior art multicast protocols developed for these networks, channel assignment and multicast routing are considered as two separate sub-problems to be solved sequentially. The work in this article is targeted at promoting the adoption of learning automata for joint channel assignment and multicast routing problem in MCMR WMNs. In the proposed scheme named LAMR, contrary to the existing methods, these two sub-problems will be solved conjointly. Experimental results demonstrate that LAMR outperforms the LCA and MCM proposed by Zeng et al. (IEEE Trans. Parallel. Distrib. Syst. 21(1):86–99, 2010) as well as the genetic algorithm-, tabu search-, and simulated annealing-based methods by Cheng and Yang (Int. J. Appl. Soft Comput. 11(2):1953–1964, 2011) in terms of achieved throughput, end-to-end delay, average packet delivery ratio, and multicast tree total cost.