Darstellung und Molekülstrukturen von oligofunktionalen Dirheniumcarbonylderivaten aus Dirheniumnonacarbonylphosphan

Preparation and Molecular Structures of Oligofunctional Dirhenium Carbonyl Derivatives from Dirhenium Nonacarbonylphosphane Starting with dirheniumdecacarbonyl, one CO-Ligand was eliminated oxidatively and substituted by the labile acetonitrile ligand. As an intermediate eq-Re₂(CO)₉NCCH₃ was received. The reaction of this labilised carbonyl with tris(trimethylsilyl)phosphine and subsequent methanolysis gave ax-Re₂(CO)₉PH₃, which was isolated and characterized for the first time. Photochemical and thermal reaction of ax-Re₂(CO)₉PH₃ led to the new bi- and trinuclear complexes Re₂(μ-H)(μ₃-PHRe(CO)₅)(CO)₈, Re₂(μ-PH₂)₂(CO)₈ and Re₂(μ-H) · (μ-PH₂)(CO)₈, which were characterized by IR-, ¹H- and ³¹P-NMR spectroscopy. The structures of ax-Re₂(CO)₉PH₃, Re₂(μ-H)(μ₃-PHRe(CO)₅)(CO)₈ and Re₂(μ-PH₂)₂(CO)₈ were confirmed by single-crystal X-ray analysis. ax-Re₂(CO)₉PH₃ has a very short Re? P bond length of 228(2) pm.     

SINGLE MACHINE SCHEDULING WITH CONTROLLABLE PROCESSING TIMES AND COMPRESSION COSTS （PART I：EQUAL TIMES AND COSTS）

Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by realloeating resources. In this paper, authors consider a machine scheduling problemwith controllable processing times. In the first part of this paper, a special case where the pro-cessing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O（n^2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case, An effective heuristic to the genera/ problem will be presented.     

Structural and electrical properties of crystalline (1−x)Ta2O5−xTiO2 thin films fabricated by metalorganic decomposition

Polycrystalline (1−x)Ta₂O₅−xTiO₂ thin films were formed on Si by metalorganic decomposition (MOD) and annealed at various temperatures. As-deposited films were in the amorphous state and were completely transformed to crystalline after annealing above 600 °C. During crystallization, a thin interfacial SiO₂ layer was formed at the (1−x)Ta₂O₅−xTiO₂/Si interface. Thin films with 0.92Ta₂O₅–0.08TiO₂ composition exhibited superior insulating properties. The measured dielectric constant and dissipation factor at 1 MHz were 9 and 0.015, respectively, for films annealed at 900 °C. The interface trap density was 2.5×10¹¹ cm⁻² eV⁻¹, and flatband voltage was −0.38 V. A charge storage density of 22.8 fC/μm² was obtained at an applied electric field of 3 MV/cm. The leakage current density was lower than 4×10⁻⁹ A/cm² up to an applied electric field of 6 MV/cm.     

Extension of multivariate regression trees to interval data. Application to electricity load profiling

Summary  Several data can be presented as interval curves where intervals reflect a within variability. In particular, this representation is well adapted for load profiles, which depict the electricity consumption of a class of customers. Electricity load profiling consists in assigning a daily load curve to a customer based on their characteristics such as energy requirement. Within the load profiling scope, this paper investigates the extension of multivariate regression trees to the case of interval dependent (or response) variables. The tree method aims at setting up simultaneously load profiles and their assignment rules based on independent variables. The extension of multivariate regression trees to interval responses is detailed and a global approach is defined. It consists in a first stage of a dimension reduction of the interval response variables. Thereafter, the extension of the tree method is applied to the first principal interval components. Outputs are the classes of the interval curves where each class is characterized both by an interval load profile (e.g. the class prototype) and an assignment rule based on the independent variables.     

Holographic image subtraction using a polarization technique

A holographic image subtraction technique is proposed. The vector nature of light is utilized in introducing a phase difference of π between the two reconstructed object waves. The experimental results are also presented.     

Chemical imaging in biology and medicine using ion microscopy

The ability to quantitatively map the distribution of elements on the micrometer scale and smaller with high sensitivity and isotopic discrimination is unique to ion microscopy. The information contained in ion images can be crucial to the study of the solid state, where chemical heterogeneity is often directly related to observed behavior. The tools of digital image processing allow the extraction of quantitative information from the image data. These techniques coupled with improved instrumentation for the detection of ion images drastically increase the problem solving capabilities of the ion microscope. The use of such methods and instrumentation in the ion microscopic analyses of cell cultures and tissues of biological and biomedical relevance will be discussed.     

GS-221高速摄影测量仪测角信息的采集与处理

在GS-221高速摄影测量仪中,测角信息采集与处理速度的快慢是重要性能指标之一。本文讨论了如何在尽可能短的时间内对测角信息进行采集和处理的软件实现方法。     

Model-Free Analysis of Mixtures by NMR Using Blind Source Separation

The concept of blind source separation is described and examples of its use in 1D and 2D NMR spectroscopy are presented. The goal of this data processing method is to extract the spectra of components molecules when only mixtures are available.     

浅议物理实验教学环节改革

为进一步提高大学物理实验的教学质量，本文就实验课的预习、操作、实验报告的撰写及考核方法进行了探讨。     

Global Optimal Image Reconstruction from Blurred Noisy Data by a Bayesian Approach

In this paper, a procedure is presented which allows the optimal reconstruction of images from blurred noisy data. The procedure relies on a general Bayesian approach, which makes proper use of all the available information. Special attention is devoted to the informative content of the edges; thus, a preprocessing phase is included, with the aim of estimating the jump sizes in the gray level. The optimization phase follows; existence and uniqueness of the solution is secured. The procedure is tested against simple simulated data and real data.