Surface diffusion in reversed-phase liquid chromatography using silica gels bonded with C1 and C18 ligands of different densities

Surface diffusion in reversed-phase liquid chromatography (RPLC) using silica gels bonded with C₁ and C₁₈ alkyl ligands of different densities was studied from the viewpoints of two extrathermodynamic relationships, i.e., enthalpy-entropy compensation (EEC) and linear free energy relationship (LFER). First, according to the four methods proposed by Krug et al., the values of surface diffusion coefficient (D_s) were analyzed to confirm that an actual EEC resulting from substantial physico-chemical effects takes place for surface diffusion. Then, it was also demonstrated that a LFER is observed between surface diffusion and the retention equilibrium. The establishment of EEC and LFER suggests a mechanistic similarity of molecular migration by surface diffusion, irrespective of the alkyl chain length and the densities of C₁ and C₁₈ ligands. Finally, a thermodynamic model for the LFER based on the real EEC was used to estimate D_s values under various RPLC conditions. The D_s values can be estimated with a mean square deviation of about 25–30%. The agreement between the D_s values estimated and those experimentally measured suggests that the total mass flux by surface diffusion consists of the two contributions due to C₁ and C₁₈ ligands and that the contribution of each ligand is proportional to the ligand density.     

Reduced matrix effects for anionic compounds with paired ion electrospray ionization mass spectrometry

It is well-known that matrix effects in high performance liquid chromatography coupled to electrospray ionization mass spectrometry (HPLC-ESI-MS) can seriously compromise quantitative analysis and affect method reproducibility. Paired ion electrospray ionization (PIESI) mass spectrometry is an approach for analyzing ultra-low levels of anions in the positive ion mode. This approach uses a structurally optimized ion pairing reagent to post-column associate with the anionic analyte, subsequently forming positively charged complexes. These newly formed complex ions are often more surface-active as compared to either the native anion or the ion pairing reagent. No studies have examined whether or not the PIESI approach mitigates matrix effects. Consequently, a controlled study was done using five analytes in highly controlled and reproducible synthetic groundwater and urine matrices. In addition, two different mass spectrometers (linear ion trap and triple quadrupole) were used. Compared to the negative ion mode, the PIESI-MS approach was less susceptible to matrix effects when performed on two different MS platforms. Using PIESI-MS, less dilution of the sample is needed to eliminate ionization suppression which, in turn, permits lower limits of detection and quantitation.     

Active wavelength selection for mixture identification with tunable mid-infrared detectors

This article presents a wavelength selection framework for mixture identification problems. In contrast with multivariate calibration, where the mixture constituents are known and the goal is to estimate their concentration, in mixture identification the goal is to determine which of a large number of chemicals is present. Due to the combinatorial nature of this problem, traditional wavelength selection algorithms are unsuitable because the optimal set of wavelengths is mixture dependent. To address this issue, our framework interleaves wavelength selection with the sensing process, such that each subsequent wavelength is determined on-the-fly based on previous measurements. To avoid early convergence, our approach starts with an exploratory criterion that samples the spectrum broadly, then switches to an exploitative criterion that selects increasingly more relevant wavelengths as the solution approaches the true constituents of the mixture. We compare this “active” wavelength selection algorithm against a state-of-the-art passive algorithm (successive projection algorithm), both experimentally using a tunable spectrometer and in simulation using a large spectral library of chemicals. Our results show that our active method can converge to the true solution more frequently and with fewer measurements than the passive algorithm. The active method also leads to more compact solutions with fewer false positives.     

铜掺杂氧化锌纳米纤维宽线性响应乙醇气体传感器

采用电纺丝技术结合高温煅烧制备了铜掺杂氧化锌复合纳米纤维,并通过XRD,XPS,SEM和TEM等手段对材料进行表征.将所得材料作为敏感层构筑了气体传感器,器件对乙醇蒸气具有很好的传感特性,特别是当Cu/Zn摩尔比为1∶60时,由于Cu组分的活化作用,所得传感器不仅具有高灵敏度、快速响应恢复(2 s/7 s)特性及优良的稳定性,而且在5~104μg/g超大乙醇蒸气浓度范围内都能保持良好的线性关系(R2=0.99),这不仅有利于乙醇实际检测,而且对宽响应范围及高灵敏传感器的发展具有重要意义.     

A computer program for searching the best model for describing different experimental systems

An algorithm for searching the best polynomial analytical function for describing different experimental systems is presented. It is based

1. (1)on the generation of all possible analytical functions of a given order, with a given number of terms and with a given number of independent variables, and

2. (2)on the calculation of the parameters of all selected functions using the linear regression method.

To show the ability of the program two different examples are given:

1. (1) searching the best univariate polynomial model, and

2. (2) modelling of the stability of a two-component mixture as a function of three factors.

Resplendent models and $${\Sigma_1^1}$$ -definability with an oracle

In this article we find some sufficient and some necessary -conditions with oracles for a model to be resplendent or chronically resplendent. The main tool of our proofs is internal arguments, that is analogues of classical theorems and model-theoretic constructions conducted inside a model of first-order Peano Arithmetic: arithmetised back-and-forth constructions and versions of the arithmetised completeness theorem, namely constructions of recursively saturated and resplendent models from the point of view of a model of arithmetic. These internal arguments are used in conjunction with Pabion’s theorem that ensures that certain oracles are coded in a sufficiently saturated model of arithmetic. Examples of applications are provided for the theories of dense linear orders and of discrete linear orders. These results are then generalised to other ω-categorical theories and theories with a unique countable recursively saturated model.      

Sampled-data nonlinear observer design for chaos synchronization: A Lyapunov-based approach

This paper considers sampled-data based chaos synchronization using observers in the presence of measurement noise for a large class of chaotic systems. We study discretized model of chaotic systems which are perturbed by white noise and employ Lyapunov-like theorems to come up with a simple yet effective observer design. For the choice of observer gain, a suboptimal criterion is obtained in terms of LMI. We present semiglobal as well as global results. The proposed scheme can also be extended for discrete-time chaotic systems. Numerical simulations have been carried out to verify the effectiveness of theoretical results.     

Stability Relationships Among the Gibbs Sampler and its Subchains

The use of Gibbs samplers driven by improper posteriors has been a controversial issue in the statistics literature over the last few years. It has recently been demonstrated that it is possible to make valid statistical inferences through such Gibbs samplers. Furthermore, theoretical and empirical evidence has been given to support the idea that there are actually computational advantages to using these nonpositive recurrent Markov chains rather than more standard positive recurrent chains. These results provide motivation for a general study of the behavior of the Gibbs Markov chain when it is not positive recurrent. This article concerns stability relationships among the two-variable Gibbs sampler and its subchains. We show that these three Markov chains always share the same stability; that is, they are either all positive recurrent, all null recurrent, or all transient. In addition, we establish general results concerning the ways in which positive recurrent Markov chains can arise from null recurrent and transient Gibbs chains. Six examples of varying complexity are used to illustrate the results.     

CARTscans: A Tool for Visualizing Complex Models

We present CARTscans, a graphical tool that displays predicted values across a fourdimensional subspace. We show how these plots are useful for understanding the structure and relationships between variables in a wide variety of models, including (but not limited to) regression trees, ensembles of trees, and linear regressions with varying degrees of interactions. In addition, the common visualization framework allows diverse complex models to be visually compared in a way that illuminates the similarities and differences in the underlying methods, facilitates the choice of a particular model structure, and provides a useful check for implausible predictions of future observations in regions with little or no data.