Semi‐preparative LC‐SPE‐cryoflow NMR for impurity identifications: use of mother liquor as a better source of impurities

Unambiguous structural elucidation of active pharmaceutical ingredients (API) impurities is a particularly challenging necessity of pharmaceutical development, particularly if the impurities are low level (0.1% level). In many cases, this requires acquiring high‐quality NMR data on a pure sample of each impurity. High‐quality, high signal‐to‐noise (S/N) one‐ and two‐dimensional NMR data can be obtained using liquid chromatography‐solid phase extraction‐cryoflow NMR (LC‐SPE‐cryoflow NMR) with a combination of semi‐preparative column for separation and mother liquor as a source of concentrated impurities. These NMR data, in conjunction with mass spectrometry data, allowed for quick and unambiguous structural elucidations of four impurities found at low level in the crystallized API but found at appreciable levels in the mother liquor that was used as the source for these impurities. These data show that semi‐preparative columns can be used at lower than ideal flow rates to facilitate trapping of HPLC components for LC‐SPE‐cryoflow NMR analysis without compromising chromatographic resolution. Also, despite the complex chromatography encountered with the use of mother liquor as a source of impurities, acceptably pure analytes were obtained for acquiring NMR data for unambiguous structure elucidations. Copyright © 2013 John Wiley & Sons, Ltd.     

On-Line Reconstruction of Inputs to Distributed Parameter Systems with Accessible Sources

In this paper, we consider a distributed system that represents a diffusion process. We assume that sources of “signals”, for example, source of inquinants, have a known and accessible position. We show that it is possible to monitor the concentration of inquinants to on-line reconstruct the rate of immission.     

A novel 2D partial unwinding adaptive Fourier decomposition method with application to frequency domain system identification

This paper proposes a two‐dimensional (2D) partial unwinding adaptive Fourier decomposition method to identify 2D system functions. Starting from Coifman in 2000, one‐dimensional (1D) unwinding adaptive Fourier decomposition and later a type called unwinding AFD have been being studied. They are based on the Nevanlinna factorization and a maximal selection. This method provides fast‐converging rational approximations to 1D system functions. However, in the 2D case, there is no genuine unwinding decomposition. This paper proposes a 2D partial unwinding adaptive Fourier decomposition algorithm that is based on algebraic transforms reducing a 2D case to the 1D case. The proposed algorithm enables rational approximations of real coefficients to 2D system functions of real coefficients. Its fast convergence offers efficient system identification. Numerical experiments are provided, and the advantages of the proposed method are demonstrated.     

Identifying tampering operations in image operator chains based on decision fusion

There has been great interest in image forensics in recent years. However, most of the existing research focuses on detecting a certain tampering operation, which means that the introduced features usually depend on the investigated operation and only binary classification is considered. Given the case where the image tampering process involves diverse processing operations, we propose a decision fusion method for identifying tampering operations in operator chains in this work. The proposed method permits the integration of knowledge provided by available image forensic algorithms. Under this method, a similarity coefficient function is introduced to assign the weight of the output of each forensic classifier. Then, we utilize a combination rule based on local conflict management to merge these outputs. Comparison with the previous works shows an improvement in operations identification accuracy when an image has experienced multiple falsifications.     

An efficient dynamical model of reluctance actuators with flux fringing and magnetic hysteresis

This paper presents an efficient and accurate dynamical model of reluctance actuators, suitable for prediction and control applications. It is a hybrid lumped-parameter state-space model that takes into account the mechanical and electromagnetic dynamics, including eddy currents, flux fringing, magnetic hysteresis and saturation. Special emphasis is placed on the hysteresis model, which is based on the Jiles–Atherton theory. The novel parts of the model – the gap reluctance expression and the modified Jiles–Atherton hysteresis model – are identified, showing that the simulated results fit very well the experimental data. Furthermore, its potential application for control is exemplified with a feedback strategy, in which the design of the controller and observer are based on the proposed dynamical model.     

The pre-stack migration imaging technique for damages identification in concrete structures

Pre-stack migration imaging (PMI) method, which is used in geophysical exploration by the performance of single side detection and visually display, can be used to identify the location, orientation, and severity of damages in concrete structure. In particular, this letter focuses on the experimental study by using a finite number of sensors for further practical applications. A concrete structure with a surface-mounted linear PZT transducers array is illustrated. Three types of damages, horizontal, dipping and V-shaped crack damage, have been studied. A pre-stack reverse time migration technique is used to back-propagate the scattering waves and to image damages in concrete structure. The migration results from the scattering waves of an artificial damage are presented. It is shown that the existence of the damage in concrete structure is correctly revealed through migration process.     

Synthesis and evaluation of halogenated nitrophenoxazinones as nitroreductase substrates for the detection of pathogenic bacteria

The synthesis and microbiological evaluation of 7-, 8- and 9-nitro-1,2,4-trihalogenophenoxazin-3-one substrates with potential in the detection of nitroreductase-expressing pathogenic microorganisms are described. The 7- and 9-nitrotrihalogenophenoxazinone substrates were reduced by most Gram-negative microorganisms and were inhibitory to the growth of certain Gram-positive bacteria; however, the majority of Gram-positive strains that were not inhibited by these agents, along with the two yeast strains evaluated, did not reduce the substrates. These observations suggest there are differences in the active site structures and substrate requirements of the nitroreductase enzymes from different strains; such differences may be exploited in the future for differentiation between pathogenic microorganisms. The absence of reduction of the 8-nitrotrihalogenophenoxazinone substrates is rationalized according to their electronic properties and correlates well with previous findings.     

基于多普勒频谱特征的空中目标识别

分析了直升机和固定翼飞机两类空中目标的多普勒频谱测量能力，并在测量能力得到满足的前提下，对其目标的多普勒频谱特征进行了分析，找出了它们之间的不同之处，提出了对其目标进行分类识别的方法，通过对18种直升机和固定翼飞机的仿真数据以及现场实测数据的检验，证明该方法是有效的，并且适用于悬停直升机的探测与识别。