Keyboardless Visual Programming Using Voice, Handwriting, and Gesture

Visual programming languages have facilitated the application development process, improving our ability to express programs, as well as our ability to view, edit and interact with them. Yet even in programming environments, productivity is restricted by the primary input sources: the mouse and the keyboard. As an alternative, we investigate a program development interface which responds to the most natural human communication technologies: voice, handwriting and gesture. Speech- and pen-based systems have yet to find broad acceptance in everyday life because they are insufficiently advantageous to overcome problems with reliability. However, we believe that a visual programming environment with a multimodal user interface properly constrained so as not to exceed the limits of the current technology has the potential to increase programming productivity for not only those people who are manually or visually impaired, but for the general population as well. In this paper we report on such a system

A User Interface for the Visualization and Manipulation of Arrays

The success of spreadsheets has shown that a visual representation of a 2D array greatly facilitates solving certain problems. However, spreadsheets are not general-purpose programming environments and are not suited to many problems that might naturally be solved using multi-dimensional arrays. Furthermore, spreadsheets employ a textual notation for cell references in formulas. This notation, which adds to the programmer\u27\u27s burden by distinguishing between relative and absolute addressing, can be difficult to understand and is error-prone even for the most experienced users. In this paper, we present a user interface for multi-dimensional arrays within Formulate, a form-based visual programming language. This implementation avoids textual array notation and supports the application of formulas to logical regions of an array, rather than just to individual elements

A Novel Approach to Monitoring the Cs-137 Contamination of Forest Soils in Bavaria, Germany

Regarding the radioactive fission product Cs-137, particularly forest soils are hot spots of long-term contamination. Previous studies have indicated that monitoring should take account of the exceptional role of humus for Cs-137 mobility and bioavailability to effectively evaluate contamination patterns and to enhance future protection strategies in forests. As official programmes in Bavaria lack such considerations, a new monitoring project has been established together with the Bavarian State Ministry of the Environment and Public Health, focussing on humus-controlling landscape parameters (relief, vegetation etc.) as crucial core criteria. Comprising a total of 48 sites, the project provides a solid base for future research. Both the site selection process and first results are presented here

Interactive Anatomy Online

The scientific community and general public can best take advantage of the benefits of 3D digital reconstructions if they are stored in a Web-accessible, easy-to-access database. We describe MorphologyNet/sup /spl copy// a Web-based digital library of realistic, 3D interactive and customizable images of anatomy currently in development at the University of Missouri-Rolla

Alternative Splicing: Associating Frequency with Isoforms

In the simplest model of protein production, a gene gives rise to a single protein; DNA is transcribed to form pre-mRNA, which is converted to mRNA by splicing or removing introns. The result is a chain of exons that is translated to form a protein. Alternative splicing of exons may result in the formation of multiple proteins from the same gene sequence. However, not all of these proteins may be functional. Thus, we ask whether we can predict and rank (in order of frequency of occurrence and functional importance) the set of possible proteins for a gene. Herein we describe a tool that predicts the relative frequencies of isoforms that can be produced from a given gene

Determining Domain Similarity and Domain-Protein Similarity using Functional Similarity Measurements of Gene Ontology Terms

Protein domains typically correspond to major functional sites of a protein. Therefore, determining similarity between domains can aid in the comparison of protein functions, and can provide a basis for grouping domains based on function. One strategy for comparing domain similarity and domain-protein similarity is to use similarity measurements of annotation terms from the Gene Ontology (GO). In this paper five methods are analyzed in terms of their usefulness for comparing domains, and comparing domains to proteins based on GO terms

A Visual Query System for the Specification and Scientific Analysis of Continual Queries

The lack of a facility that would allow nonprogrammers to easily formulate temporal ad hoc analyses over a network of heterogeneous, constantly-updated data sources has been a significant impediment to research, particularly in the scientific community. In this paper we describe WebFormulate, an Internet-based system which facilitates the development of analyses using information obtained from databases on the Internet. The main distinction between this system and existing Internet facilities to retrieve information and assimilate it into computations is that WebFormulate provides the necessary facilities to perform continual queries, developing and maintaining dynamic links such that computations and reports automatically maintain themselves. A further distinction is that this system is specifically designed for users of spreadsheet-level ability, rather than professional programmers

Protein Secondary Structure Prediction using Parallelized Rule Induction from Coverings

Protein 3D structure prediction has always been an important research area in bioinformatics. In particular, the prediction of secondary structure has been a well-studied research topic. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q3 accuracy of various computational prediction algorithms rarely has exceeded 75%. In a previous paper [1], this research team presented a rule-based method called RT-RICO (Relaxed Threshold Rule Induction from Coverings) to predict protein secondary structure. The average Q3 accuracy on the sample datasets using RT-RICO was 80.3%, an improvement over comparable computational methods. Although this demonstrated that RT-RICO might be a promising approach for predicting secondary structure, the algorithm\u27s computational complexity and program running time limited its use. Herein a parallelized implementation of a slightly modified RT-RICO approach is presented. This new version of the algorithm facilitated the testing of a much larger dataset of 396 protein domains [2]. Parallelized RTRICO achieved a Q3 score of 74.6%, which is higher than the consensus prediction accuracy of 72.9% that was achieved for the same test dataset by a combination of four secondary structure prediction methods [2]

Identifying Character Non-Independence in Phylogenetic Data using Data Mining Techniques

Undiscovered relationships in a data set may confound analyses, particularly those that assume data independence. Such problems occur when characters used for phylogenetic analyses are not independent of one another. A main assumption of phylogenetic inference methods such as maximum likelihood and parsimony is that each character serves as an independent hypothesis of evolution. When this assumption is violated, the resulting phylogeny may not reflect true evolutionary history. Therefore, it is imperative that character non-independence be identified prior to phylogenetic analyses. To identify dependencies between phylogenetic characters, we applied three data mining techniques: 1) Bayesian networks, 2) decision tree induction, and 3) rule induction from coverings. We briefly discuss the main ideas behind each strategy, show how each technique performs on a small sample data set, and apply each method to an existing phylogenetic data set. We discuss the interestingness of the results of each method, and show that, although each method has its own strengths and weaknesses, rule induction from coverings presents the most useful solution for determining dependencies among phylogenetic data at this time

DNase 2 Is the Main DNA-Degrading Enzyme of the Stratum Corneum

The cornified layer, the stratum corneum, of the epidermis is an efficient barrier to the passage of genetic material, i.e. nucleic acids. It contains enzymes that degrade RNA and DNA which originate from either the living part of the epidermis or from infectious agents of the environment. However, the molecular identities of these nucleases are only incompletely known at present. Here we performed biochemical and genetic experiments to determine the main DNase activity of the stratum corneum. DNA degradation assays and zymographic analyses identified the acid endonucleases L-DNase II, which is derived from serpinB1, and DNase 2 as candidate DNases of the cornified layer of the epidermis. siRNA-mediated knockdown of serpinB1 in human in vitro skin models and the investigation of mice deficient in serpinB1a demonstrated that serpinB1-derived L-DNase II is dispensable for epidermal DNase activity. By contrast, knockdown of DNase 2, also known as DNase 2a, reduced DNase activity in human in vitro skin models. Moreover, the genetic ablation of DNase 2a in the mouse was associated with the lack of acid DNase activity in the stratum corneum in vivo. The degradation of endogenous DNA in the course of cornification of keratinocytes was not impaired by the absence of DNase 2. Taken together, these data identify DNase 2 as the predominant DNase on the mammalian skin surface and indicate that its activity is primarily targeted to exogenous DNA