Understanding the Use of Inheritance with Visual Patterns

International audienceThe goal of this work is to visualize inheritance in object-oriented programs to help its comprehension. We propose a single, compact view of all class hierarchies at once using a custom Sunburst layout. It enables to quickly discover interesting facts across classes while preserving the essential relationship between parent and children classes. We explain how standard inheritance metrics are mapped into our visualization. Additionally, we define a new metric characterizing similar children classes. Using these metrics and the proposed layout, a set of common visual patterns is derived. These patterns allow the programmer to quickly understand how inheritance is used and provide answers to some essential questions when performing program comprehension tasks. Our approach is evaluated through a case study that involves examples from large programs, demonstrating its scalability

Family health narratives : midlife women’s concepts of vulnerability to illness

Perceptions of vulnerability to illness are strongly influenced by the salience given to personal experience of illness in the family. This article proposes that this salience is created through autobiographical narrative, both as individual life story and collectively shaped family history. The paper focuses on responses related to health in the family drawn from semi-structured interviews with women in a qualitative study exploring midlife women’s health. Uncertainty about the future was a major emergent theme. Most respondents were worried about a specified condition such as heart disease or breast cancer. Many women were uncertain about whether illness in the family was inherited. Some felt certain that illness in the family meant that they were more vulnerable to illness or that their relatives’ ageing would be mirrored in their own inevitable decline, while a few expressed cautious optimism about the future. In order to elucidate these responses, we focused on narratives in which family members’ appearance was discussed and compared to that of others in the family. The visualisation of both kinship and the effects of illness, led to strong similarities being seen as grounds for worry. This led to some women distancing themselves from the legacies of illness in their families. Women tended to look at the whole family as the context for their perceptions of vulnerability, developing complex patterns of resemblance or difference within their families

Neural Mechanisms for Information Compression by Multiple Alignment, Unification and Search

This article describes how an abstract framework for perception and cognition may be realised in terms of neural mechanisms and neural processing. This framework — called information compression by multiple alignment, unification and search (ICMAUS) — has been developed in previous research as a generalized model of any system for processing information, either natural or artificial. It has a range of applications including the analysis and production of natural language, unsupervised inductive learning, recognition of objects and patterns, probabilistic reasoning, and others. The proposals in this article may be seen as an extension and development of Hebb’s (1949) concept of a ‘cell assembly’. The article describes how the concept of ‘pattern’ in the ICMAUS framework may be mapped onto a version of the cell assembly concept and the way in which neural mechanisms may achieve the effect of ‘multiple alignment’ in the ICMAUS framework. By contrast with the Hebbian concept of a cell assembly, it is proposed here that any one neuron can belong in one assembly and only one assembly. A key feature of present proposals, which is not part of the Hebbian concept, is that any cell assembly may contain ‘references’ or ‘codes’ that serve to identify one or more other cell assemblies. This mechanism allows information to be stored in a compressed form, it provides a robust mechanism by which assemblies may be connected to form hierarchies and other kinds of structure, it means that assemblies can express abstract concepts, and it provides solutions to some of the other problems associated with cell assemblies. Drawing on insights derived from the ICMAUS framework, the article also describes how learning may be achieved with neural mechanisms. This concept of learning is significantly different from the Hebbian concept and appears to provide a better account of what we know about human learning

A Role for Actin, Cdc1p, and Myo2p in the Inheritance of Late Golgi Elements in \u3cem\u3eSaccharomyces cerevisiae\u3c/em\u3e

In Saccharomyces cerevisiae, Golgi elements are present in the bud very early in the cell cycle. We have analyzed this Golgi inheritance process using fluorescence microscopy and genetics. In rapidly growing cells, late Golgi elements show an actin-dependent concentration at sites of polarized growth. Late Golgi elements are apparently transported into the bud along actin cables and are also retained in the bud by a mechanism that may involve actin. A visual screen for mutants defective in the inheritance of late Golgi elements yielded multiple alleles of CDC1. Mutations in CDC1 severely depolarize the actin cytoskeleton, and these mutations prevent late Golgi elements from being retained in the bud. The efficient localization of late Golgi elements to the bud requires the type V myosin Myo2p, further suggesting that actin plays a role in Golgi inheritance. Surprisingly, early and late Golgi elements are inherited by different pathways, with early Golgi elements localizing to the bud in a Cdc1p- and Myo2p-independent manner. We propose that early Golgi elements arise from ER membranes that are present in the bud. These two pathways of Golgi inheritance in S. cerevisiae resemble Golgi inheritance pathways in vertebrate cells

SODA: Generating SQL for Business Users

The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to the data warehouses and their schemas have become increasingly complex. These systems still work great in order to generate pre-canned reports. However, with their current complexity, they tend to be a poor match for non tech-savvy business analysts who need answers to ad-hoc queries that were not anticipated. This paper describes the design, implementation, and experience of the SODA system (Search over DAta Warehouse). SODA bridges the gap between the business needs of analysts and the technical complexity of current data warehouses. SODA enables a Google-like search experience for data warehouses by taking keyword queries of business users and automatically generating executable SQL. The key idea is to use a graph pattern matching algorithm that uses the metadata model of the data warehouse. Our results with real data from a global player in the financial services industry show that SODA produces queries with high precision and recall, and makes it much easier for business users to interactively explore highly-complex data warehouses.Comment: VLDB201

The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem

Several important and fundamental aspects of disease genetics models have yet to be described. One such property is the relationship of disease association statistics at a marker site closely linked to a disease causing site. A complete description of this two-locus system is of particular importance to experimental efforts to fine map association signals for complex diseases. Here, we present a simple relationship between disease association statistics and the decline of linkage disequilibrium from a causal site. Specifically, the ratio of Chi-square disease association statistics at a marker site and causal site is equivalent to the standard measure of pairwise linkage disequilibrium, r2. A complete derivation of this relationship from a general disease model is shown. Quite interestingly, this relationship holds across all modes of inheritance. Extensive Monte Carlo simulations using a disease genetics model applied to chromosomes subjected to a standard model of recombination are employed to better understand the variation around this fine mapping theorem due to sampling effects. We also use this relationship to provide a framework for estimating properties of a non-interrogated causal site using data at closely linked markers. Lastly, we apply this way of examining association data from high-density genotyping in a large, publicly-available data set investigating extreme BMI. We anticipate that understanding the patterns of disease association decay with declining linkage disequilibrium from a causal site will enable more powerful fine mapping methods and provide new avenues for identifying causal sites/genes from fine-mapping studies