Estimation of partially specified spatial panel data models with random-effects

In this article, we study estimation of a partially specified spatial panel data linear regression with random-effects. Under the conditions of exogenous spatial weighting matrix and exogenous regressors, we give an instrumental variable estimation. Under certain sufficient assumptions, we show that the proposed estimator for the finite dimensional parameter is root-N consistent and asymptotically normally distributed and the proposed estimator for the unknown function is consistent and asymptotically distributed. Consistent estimators for the asymptotic variance-covariance matrices of both the parametric and unknown components are provided. The Monte Carlo simulation results verify our theory and suggest that the approach has some practical value.     

基于化学史和数据探究的“化学平衡常数”教学研究

分析了“化学平衡常数”的教材内容和相关教学设计,针对实际教学中存在的2个问题：简化的数据探究难以让学生体会到科学研究的复杂性;纯粹的知识性教学难以体现科学知识的价值和意义。提出在教学中融合化学史和数据探究,能帮助学生全面深入地理解概念,促进学生进一步认识科学本质和学科价值。     

Bordism of two commuting involutions

In this paper we obtain conditions for a Whitney sum of three vector bundles over a closed manifold, , to be the fixed data of a -action; these conditions yield the fact that if is the fixed data of a -action, where is the trivial one dimensional bundle, then the same is true for . The results obtained, together with techniques previously developed, are used to obtain, up to bordism, all possible -actions fixing the disjoint union of an even projective space and a point.

     

Studies on the analytical performance of a non-covalent coating with N,N-didodecyl-N,N-dimethylammonium bromide for separation of basic proteins by capillary electrophoresis in acidic buffers in 25-and 50-μm capillaries

Capillaries (25-and 50-μm inner diameter) coated with a double-alkyl-chain cationic surfactant N,N-didodecyl-N,N-dimethylammonium bromide (DDAB) were used for the separation of four basic standard proteins in buffers of pH 4 at various ionic strengths. The choice of buffer is critical for the analytical performance. Ammonium ions must be avoided in the buffer used in the non-covalent coating procedure owing to competition with the surfactant. Phosphate buffer gave a better separation performance than some volatile buffers; the reason seems to be a complex formation between the proteins and dihydrogenphosphate ions, which decreases tendencies for adsorption to the capillary surface. The DDAB coating was easy to produce and stable enough to permit, without recoating, consecutive separations of the proteins for up to 100 min with good precision in migration times and peak areas. A strong electroosmotic flow gives rapid separations, which is of special importance when commercial instruments are used, since the choice of the length of the capillary is restricted. Figure EOF stability in 25 micrometer i.d. capillaries. Consecutive injections of mesityloxide performed after an initial coating with 1.0     

Improved binary PSO for feature selection using gene expression data

Gene expression profiles, which represent the state of a cell at a molecular level, have great potential as a medical diagnosis tool. Compared to the number of genes involved, available training data sets generally have a fairly small sample size in cancer type classification. These training data limitations constitute a challenge to certain classification methodologies. A reliable selection method for genes relevant for sample classification is needed in order to speed up the processing rate, decrease the predictive error rate, and to avoid incomprehensibility due to the large number of genes investigated. Improved binary particle swarm optimization (IBPSO) is used in this study to implement feature selection, and the K-nearest neighbor (K-NN) method serves as an evaluator of the IBPSO for gene expression data classification problems. Experimental results show that this method effectively simplifies feature selection and reduces the total number of features needed. The classification accuracy obtained by the proposed method has the highest classification accuracy in nine of the 11 gene expression data test problems, and is comparative to the classification accuracy of the two other test problems, as compared to the best results previously published.     

An efficient one-step method for the synthesis of 2-(indolizin-2-yl)benzimidazoles from quinoxalinones and α-picoline via a novel rearrangement

A highly efficient one-step and versatile method for the synthesis of 2-(indolizin-2-yl)benzimidazoles has been developed on the basis of the novel ring contraction of 3-arylchloromethyl- and alkylchloromethylquinoxalin-2-ones with α-picoline.     

Estimation of partial linear error-in-variables models for ρ<Superscript>−</Superscript>-mixing dependence data

Consider the partly linear regression model Y = xβ + g(t) + e where the explanatory x is erroneously measured, and both t and the response Y are measured exactly, the random error e is ρ⁻-mixing. Let be a surrogate variable observed instead of the true x in the primary survey data. Assume that in addition to the primary data set containing N observations of , which is ρ⁻-mixing data sets, an independent validation data containing n observations of is available. The exact observations on x may be obtained by some expensive or diffcult procedures for only a small subset of subjects enrolled in the study. In this paper, inspired by Berberan-Santos et al. [J. Math. Chem. 37 (2005)101], a semiparametric method with the primary data is employed to obtain the estimators of β and g(·) based on the least squares criterion with the help of validata. The proposed estimators are proved to be strongly consistent.      

SMART: A data reporting standard for mass spectrometry imaging By Ying Xi,Alexandria L. Sohn,Alena N. Joignant,Stephanie M. Cologna,Boone M. Prentice and David C. Muddiman

Mass spectrometry imaging (MSI) is an important analytical technique that simultaneously reports the spatial location and abundance of detected ions in biological, chemical, clinical, and pharmaceutical studies. As MSI grows in popularity, it has become evident that data reporting varies among different research groups and between techniques. The lack of consistency in data reporting inherently creates additional challenges in comparing intra- and inter-laboratory MSI data. In this tutorial, we propose a unified data reporting system, SMART, based on the common features shared between techniques. While there are limitations to any reporting system, SMART was decided upon after significant discussion to more easily understand and benchmark MSI data. SMART is not intended to be comprehensive but rather capture essential baseline information for a given MSI study; this could be within a study (e.g., effect of spot size on the measured ion signals) or between two studies (e.g., different MSI platform technologies applied to the same tissue type). This tutorial does not attempt to address the confidence with which annotations are made nor does it deny the importance of other parameters that are not included in the current SMART format. Ultimately, the goal of this tutorial is to discuss the necessity of establishing a uniform reporting system to communicate MSI data in publications and presentations in a simple format to readily interpret the parameters and baseline outcomes of the data.