Evaluation of high-field asymmetric waveform ion mobility spectrometry coupled to nanoelectrospray ionization for bioanalysis in drug discovery

The potential of high-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to nanoelectrospray ionization (nanoESI) as a method to improve sample throughput for bioanalysis in a discovery pharmaceutical setting was explored in this work. The ability of FAIMS to separate gas-phase ions in the millisecond timescale was exploited to eliminate the need for liquid chromatography. Samples were introduced into the FAIMS electrodes/mass spectrometer using offline nanoESI at 20 nL/min and 1.5 kV. Signals were averaged for 30 s after which the next sample could be analyzed. The separation of simple mixtures, e.g., the removal of metabolite and endogenous interferences from parent drug, was demonstrated. Moreover, the application of nanoESI attenuated the ion suppression effects that normally plague conventional electrospray. On average, approximately two-thirds of the neat sample signal intensity was preserved in extracted plasma samples. Standard curves were prepared for several compounds and linearity was obtained over approximately two to three orders of magnitude. This methodology was further tested with the analysis of plasma samples from a mouse pharmacokinetic study. Concentration values determined using nanoESI-FAIMS were comparable to those determined using conventional LC/MS as demonstrated by percent differences of less than 30%. This work demonstrated the proof of concept that the combination of FAIMS and nanospray ionization can be a potentially useful tool to improve the throughput of discovery bioanalysis.     

Subsystem fault tolerance with the Bacon-Shor code

We discuss how the presence of gauge subsystems in the Bacon-Shor code [D. Bacon, Phys. Rev. A 73, 012340 (2006)10.1103/PhysRevA.73.012340 (2006)] leads to remarkably simple and efficient methods for fault-tolerant error correction (FTEC). Most notably, FTEC does not require entangled ancillary states, and it can be implemented with nearest-neighbor two-qubit measurements. By using these methods, we prove a lower bound on the quantum accuracy threshold, 1.94 x 10(-4) for adversarial stochastic noise, that improves previous lower bounds by nearly an order of magnitude.     

The reduction of computation times of upper and lower tolerances for selected combinatorial optimization problems

Due to the growing interest in approximation for multiobjective optimization problems (MOPs), a theoretical framework for defining and classifying sets representing or approximating solution sets for MOPs is developed. The concept of tolerance function is proposed as a tool for modeling representation quality. This notion leads to the extension of the traditional dominance relation to \(t\hbox {-}\)dominance. Two types of sets representing the solution sets are defined: covers and approximations. Their properties are examined in a broader context of multiple solution sets, multiple cones, and multiple quality measures. Applications to complex MOPs are included.     

Filled functions for unconstrained global optimization

This paper is concerned with filled function techniques for unconstrained global minimization of a continuous function of several variables. More general forms of filled functions are presented for smooth and non-smooth optimization problems. These functions have either one or two adjustable parameters. Conditions on functions and on the values of parameters are given so that the constructed functions have the desired properties of filled functions.     

Fundamental equation of the dual flow rate-solvent gradient elution in liquid chromatography

An alternative expression of the fundamental equation of multi-mode gradient elution involving simultaneous changes in mobile phase composition and flow rate is derived using simple kinetic arguments and graphic interpretation. The new expression consists of a system of two integral equations and provides an easy and direct way of predicting retention times under dual-mode gradient conditions.     

Bilinear modeling solution approach for fixed charge network flow problems

We present a continuous, bilinear formulation for the fixed charge network flow problem. This formulation is used to derive an exact algorithm for the fixed charge network flow problem converging in a finite number of steps. Some preliminary computational experiments are reported to show the performance of the algorithm.     

An Algorithm for Solving the Shortest Path Improvement Problem on Rooted Trees Under Unit Hamming Distance

Shortest path problems play important roles in computer science, communication networks, and transportation networks. In a shortest path improvement problem under unit Hamming distance, an edge-weighted graph with a set of source–terminal pairs is given. The objective is to modify the weights of the edges at a minimum cost under unit Hamming distance such that the modified distances of the shortest paths between some given sources and terminals are upper bounded by the given values. As the shortest path improvement problem is NP-hard, it is meaningful to analyze the complexity of the shortest path improvement problem defined on rooted trees with one common source. We first present a preprocessing algorithm to normalize the problem. We then present the proofs of some properties of the optimal solutions to the problem. A dynamic programming algorithm is proposed for the problem, and its time complexity is analyzed. A comparison of the computational experiments of the dynamic programming algorithm and MATLAB functions shows that the algorithm is efficient although its worst-case complexity is exponential time.