DDLm: A New Dictionary Definition Language

A previous paper [Spadaccini and Hall J. Chem. Inf. Model. doi:10.1021/ci300074v] details extensions to the STAR File [Hall J. Chem. Inf. Comput. Sci.1991, 31, 326-333] syntax that will improve the exchange and archiving of electronic data. This paper describes a dictionary definition language (DDLm) for defining STAR File data items in a domain dictionary. A dictionary that defines the ontology and vocabulary of a discipline is built with DDLm, which is itself implemented in STAR, and is extensible and machine parsable. The DDLm is semantically rich and highly specific; provides strong data typing, data enumerations, and ranges; enables relationship keys between data items; and uses imbedded methods written in dREL [Spadaccini et al. J. Chem. Inf. Model. doi:10.1021/ci300076w] for data validation and evaluation and for refining data definitions. It promotes the modular definition of the discipline ontology and reuse through the ability to import definitions from other local and remote dictionaries, thus encouraging the sharing of data dictionaries within and across domains.     

SemanticEye: a semantic web application to rationalize and enhance chemical electronic publishing

SemanticEye, an ontology with associated tools, improves the classification and open accessibility of chemical information in electronic publishing. In a manner analogous to digital music management, RDF metadata encoded as Adobe XMP can be extracted from a variety of document formats, such as PDF, and managed in an RDF repository called Sesame. Users upload electronic documents containing XMP to a central server by "dropping" them into WebDAV folders. The documents can then be navigated in a Web browser via their metadata, and multiple documents containing identical metadata can then be aggregated. SemanticEye does not actually store any documents. By including unique identifiers within the XMP, such as the DOI, associated documents can be retrieved from the Web with the help of resolving agents. The power of this metadata driven approach is illustrated by including, within the XMP, InChI identifiers for molecular structures and finding relationships between articles based on their InChIs. SemanticEye will become increasingly more comprehensive as usage becomes more widespread. Furthermore, following the Semantic Web architecture enables the reuse of open software tools, provides a "semantically intuitive" alternative to search engines, and fosters a greater sense of trust in Web-based scientific information.     

Multimedia encyclopedia of nuclear science

We are developing a multimedia encyclopedia that provides a framework for students to leam nuclear science. A variety of media formats are used to present concepts, including text, static figures, animations, and video. Two special prsentation formats use dynamically produced simulations to expose students to nuclear science relationships. These media types provide greater interactivity and flexibility than simple animations. Students access information through tutorials, a dictionary of nuclear science terms, biographies of notable scientists, and a timeline of nuclear science history. The tutorial organization emphasizes the interrelationships among topics. We present an overview of the encyclopedia.     

Synthesis and spectroscopic characterization of copper(H)-dextran complexes

Synthesis of stable copper(II) complexes with reduced dextran derivatives can be realized with low molar polysaccharides of an average molar mass 5000 g mol⁻¹. A copper(II) content of 4–20% is achieved at pH 7–8 and at the boiling point. Copper(II) complex formation with dextran was analyzed by spectrophotometric VIS methods. The IR spectra of copper(II) complexes with dextran were analyzed to find the most stable conformation of the glucopyranose unit. The ESR parameters of the spectrum indicate a square-planar coordination of the Cu(II) ion with four oxygen ligand atoms in the same plane. Copper deficiency causes a number of pathological states [1]. In both human and veterinary medicine, commercial copper preparations based on dextran and its derivatives are used for such purposes [2]. According to the literature data, dextran has the ability of complex formation with various biometals (Zn, Fe, Co, Ca, and Mg) [3–6]. Iron complexes with different polysaccharides have special importance and they have been described in detail [7]. Synthetic procedures for the complex formation of Cu(II) with polysaccharides, including dextran, are described in scientific and patent literature [8]. However, literature data on the complex formation possibility of the Cu(II) ion with dextran derivatives are scarce. The text was submitted by the authors in English. An erratum to this article is available at .     

The O((1)D) + H2 (X (1)Σ+, v, j) → OH(X (2)Π, v', j') + H((2)S) reaction at low collision energy: when a simple statistical description of the dynamics works

In this communication, we highlight that statistical approaches for chemical reactions describe reasonably well the low energy dynamics of the title process. Consequently, such methods prove to be valuable to compute rate constants from low to room temperatures. Results are compared with experiment and recent precise quantum wave packet calculations [J. Phys. Chem. A, 2009, 113, 5285].     

Determination of retention indices in LPTGC

Summary A method is presented for the calculation of retention indices in linear programmed-temperature gas chromatography (LPTGC) on the basis of isothermal retention data and the operating conditions (initial temperature, programming rate, gas flow velocity) of the run. Part IV of a series; parts I, II and III see refs. [1], [2] and [3].     

Single molecule kinetics. I. Theoretical analysis of indicators

Single molecule experiments reveal intriguing phenomenon in chemical and biological systems. Several indicators of complex dynamics, including "intensity" correlations, "event" correlations, and characteristic functions have been proposed, but extraction of information from these indicators can be difficult since these indicators only observe certain characteristics of the system. Generally, for systems that follow Poisson kinetics, all of these indicators contain similar information about the relaxation times of the system and the connections between different relaxation times, but the information is convoluted in different ways so the strength of various indicators is system specific. The paper discusses the theoretical implications and information content of various data analysis methods for single molecule experiments and demonstrates the relationships between indicators. Under certain conditions, common indicators contain all available information about systems with Poisson kinetics between degenerate states, but extraction of this information is generally not numerically feasible. The paper also discusses practical issues associated with these analyses, which motivates a numerical study based on Bayes' formula in the companion paper [J. Witkoskie and J. S. Cao, J. Chem. Phys. 121, 6373 (2004), following paper].     

Reading Polymers: Sequencing of Natural and Synthetic Macromolecules

The sequencing of biopolymers such as proteins and DNA is among the most significant scientific achievements of the 20th century. Indeed, modern chemical methods for sequence analysis allow reading and understanding the codes of life. Thus, sequencing methods currently play a major role in applications as diverse as genomics, gene therapy, biotechnology, and data storage. However, in terms of fundamental science, sequencing is not really a question of molecular biology but rather a more general topic in macromolecular chemistry. Broadly speaking, it can be defined as the analysis of comonomer sequences in copolymers. However, relatively different approaches have been used in the past to study monomer sequences in biological and manmade polymers. Yet, these “cultural” differences are slowly fading away with the recent development of synthetic sequence‐controlled polymers. In this context, the aim of this Minireview is to present an overview of the tools that are currently available for sequence analysis in macromolecular science.     

Synthetic and analytical thinking

Summary It is shown that scientific research is not a linear process of information gaining, of accumulating data and facts, but is rather to be characterized by a model showing the cyclic structure of data gathering and construction of theories, of inductive and deductive methods. Analytical and synthetic methods are linked together and are building inseparable components of the texture of science.

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Synthetisches und analytisches Denken

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Presented at the First International Symposium on History and Philosophy in Analytical Chemistry, Vienna, November 22–23, 1985     

Smart templates for peak pattern matching with comprehensive two-dimensional liquid chromatography

Comprehensive two-dimensional liquid chromatography (LCxLC) generates information-rich but complex peak patterns that require automated processing for rapid chemical identification and classification. This paper describes a powerful approach and specific methods for peak pattern matching to identify and classify constituent peaks in data from LCxLC and other multidimensional chemical separations. The approach records a prototypical pattern of peaks with retention times and associated metadata, such as chemical identities and classes, in a template. Then, the template pattern is matched to the detected peaks in subsequent data and the metadata are copied from the template to identify and classify the matched peaks. Smart Templates employ rule-based constraints (e.g., multispectral matching) to increase matching accuracy. Experimental results demonstrate Smart Templates, with the combination of retention-time pattern matching and multispectral constraints, are accurate and robust with respect to changes in peak patterns associated with variable chromatographic conditions.     

全新设计的现代高分子化学实验课程建设

理科院系高分子化学实验教学发展缓慢,急需紧跟学科发展的前沿、注入新鲜而实用的内容。全新设计建设的现代高分子化学实验覆盖众多传统实验课鲜有涉及、但在科研中极为重要的前沿理念与技术,旨在提高学生科研素养和对学科前沿的把握能力,其成功开发为理科院系针对创新型人才培养的高分子化学实验提出了全新思路。     

Undergraduate Projects in the Application of Artificial Intelligence to Chemistry. II Self-Organizing Maps

It is often necessary in science to identify samples that have features in common. For example, one might wish to find those NMR spectra in a large database that have similar patterns of resonances or identify samples amongst a large number of specimens of river water that analysis shows have similar biochemical oxygen demand, heavy metals concentration, organochlorine content, and so on.The determination of relationships among samples is a task to which Artificial Intelligence is increasingly being applied. In this paper, we investigate the Self-Organizing Map (SOM), whose role is to perform just this kind of task; in other words, to cluster data samples so as to reveal the relationships that exist among them. The self-organizing map is a method, which, unusually, combines a mathematical foundation with an intuitive interpretation.We will describe how a simple SOM operates, what kinds of data may be analyzed using one, and how a computer program to run a SOM can be written by anyone-whether student or teacher-with modest programming skills. Portions of sample source code are included in this paper, and program listings for the examples that are discussed are available in the supporting materials. The supporting files can also be used to see the maps in operation.     

A view on future directions for macromolecular science

Polymer science has in recent years become one of the most dynamic components of materials science [1, 2, 3], which in turn is a powerful bridge between basic science and advanced technology. The National Science Foundation (NSF) has periodically reviewed the status of polymer science and engineering to ensure that this important field continues to develop in an appropriate fashion. Thus, the NSF asked the U.S. National Academy of Sciences on two previous occasions, in 1981 and again in 1994, to assess progress in polymer science and engineering and to make recommendations for the future. The resulting reports [4, 5] received wide circulation in many countries and helped to focus attention on the changing nature of the polymer field. A clear trend that was identified in these reports is the greater commonality with other materials‐related disciplines [1‐3] and with the biological sciences [1‐5]. Increasingly, these changes are being reflected in the programs of government agencies funding polymer research which are tending to be broader and more interdisciplinary than in the past.     

Recent Advances in Cross-Linking

Abstract

The topics of cross-linking methods and network polymers encompass an enormous literature covering many facets of polymer science. This review selects several areas from the broad field of cross-linking which represent more recent technology, particularly that not covered in earlier reviews [1].     

Non-isothermal Kinetics of the First-stage Decomposition Reaction of Cobalt Oxalate Dihydrate

Introduction Solid state kinetics has been extensively studied by means of thermal analysis methods[1]. The aim of the study is to determine the mechanism function f(α) , the activation energy E and the pre-exponential factor A. In recent years there have been many methods of processing thermal analysis kinetic data[2-11].     

Zherlock: an open source data analysis software

Zherlock is an open source software that provides state-of-the-art data analysis tools to the user in an intuitive and flexible way. It is a front-end to different numerical "engines" to produce a seamless integration of algorithms written in different computer languages. Of particular interest is creating an interface to high-level scientific languages such as Octave (a Matlab clone) and R (an S-PLUS clone) to enable efficient porting of new data analytical methods. Zherlock uses advanced scientific visualization tools in 2-D and 3-D and has been extended to work on virtual reality (VR) systems. Central to Zherlock is a visual programming environment (VPE) which enables diagram based programming. These diagrams consist of nodes and connection lines where each node is an operator or a method and lines describe the flow of data between nodes. A VPE is chosen for Zherlock because it forms an effective way to control the processing pipeline in complex data analyses. The VPE is similar in functionality to other programs such as IRIS Explorer, AVS or LabVIEW.