The Moldable Inspector

Object inspectors are an essential category of tools that allow developers to comprehend the run-time of object-oriented systems. Traditional object inspectors favor a generic view that focuses on the low-level details of the state of single objects. Based on 16 interviews with software developers and a follow-up survey with 62 respondents we identified a need for object inspectors that support different high-level ways to visualize and explore objects, depending on both the object and the current developer need. We propose the Moldable Inspector, a novel inspector model that enables developers to adapt the inspection workflow to suit their immediate needs by making the inspection context explicit, providing multiple interchangeable domain-specific views for each object, and supporting a workflow that groups together multiple levels of connected objects. We show that the Moldable Inspector can address multiple kinds of development needs involving a wide range of objects.

Towards moldable development tools

Developers commonly ask detailed and domain-specific questions about the software systems they are developing and maintaining. Integrated development environments (IDEs) form an essential category of tools for developing software that should support software engineering decision making. Unfortunately, rigid and generic IDEs that focus on low-level programming tasks, that promote code rather than data, and that suppress customization, offer limited support for informed decision making during software development. We propose to improve decision making within IDEs by moving from generic to context-aware IDEs through moldable tools. In this paper, we promote the idea of moldable tools, illustrate it with concrete examples, and discuss future research directions.

Évaluation des connaissances morphologiques dérivationnelles d’apprentis-lecteurs présentant une dysphasie

La dysphasie consiste en une atteinte sévère et persistante de l’acquisition et du développement du langage oral. Les élèves qui en sont atteints peinent à devenir des lecteurs habiles et sont à haut risque d’échec scolaire. Si ce trouble très complexe est étudié dans différents domaines (la santé et l’éducation, entre autres), peu d’études se sont spécifiquement intéressées à vérifier si les élèves dysphasiques possèdent des connaissances morphologiques dérivationnelles. Or, depuis un certain nombre d’années, de nombreux chercheurs soutiennent que ces connaissances, qui concernent la forme des mots et leurs règles de formation, peuvent constituer une stratégie supplémentaire aidante pour les élèves aux prises avec un déficit phonologique, comme les élèves dysphasiques. C’est dans ce cadre que se situe la présente étude, dont l’objectif général est d’évaluer les connaissances morphologiques dérivationnelles d’apprentis-lecteurs dysphasiques francophones du primaire. Pour y parvenir, trois tâches morphologiques, soit une tâche de jugement de relation, une tâche de dérivation et une tâche de plausibilité, ont été soumises à trois groupes de participants dont un groupe d’élèves dysphasiques (D=30) et deux groupes contrôles, c’est-à-dire des élèves du même âge chronologique (CA, n=30) et des élèves plus jeunes, mais du même niveau de lecture (CL, n=30). Nos résultats montrent que l’ensemble des trois groupes de participants a tiré profit des unités morphologiques contenues dans les items pour réussir les tâches proposées, les dysphasiques obtenant des résultats inférieurs aux CA mais comparables aux CL. Toutefois, ces résultats ne s’apparentent pas tout à fait au continuum de développement des connaissances morphologiques dérivationnelles établi par Tyler et Nagy (1989). De plus, aucun effet du type d’affixation (items préfixés vs suffixés) n’a été observé. Les résultats obtenus nous permettent de proposer des pistes d’interventions orthodidactiques visant l’enseignement de la morphologie dérivationnelle auprès des élèves aux prises avec des difficultés de lecture, à l’instar des participants dysphasiques qui ont participé à cette étude.

Hodgkin's lymphoma cell lines express a fusion protein encoded by intergenically spliced mRNA for the multilectin receptor DEC-205 (CD205) and a novel C-type lectin receptor DCL-1

Classic Hodgkin's lymphoma (HL) tissue contains a small population of morphologically distinct malignant cells called Hodgkin and Reed-Sternberg (HRS) cells, associated with the development of HL. Using 3'-rapid amplification of cDNA ends ( RACE) we identified an alternative mRNA for the DEC-205 multilectin receptor in the HRS cell line L428. Sequence analysis revealed that the mRNA encodes a fusion protein between DEC-205 and a novel C-type lectin DCL-1. Although the 7.5-kb DEC-205 and 4.2-kb DCL-1 mRNA were expressed independently in myeloid and B lymphoid cell lines, the DEC-205/DCL-1 fusion mRNA (9.5 kb) predominated in the HRS cell lines ( L428, KM-H2, and HDLM-2). The DEC-205 and DCL-1 genes comprising 35 and 6 exons, respectively, are juxtaposed on chromosome band 2q24 and separated by only 5.4 kb. We determined the DCL-1 transcription initiation site within the intervening sequence by 5'-RACE, confirming that DCL-1 is an independent gene. Two DEC-205/DCL-1 fusion mRNA variants may result from cotranscription of DEC-205 and DCL-1, followed by splicing DEC-205 exon 35 or 34-35 along with DCL-1 exon 1. The resulting reading frames encode the DEC-205 ectodomain plus the DCL-1 ectodomain, the transmembrane, and the cytoplasmic domain. Using DCL-1 cytoplasmic domain-specific polyclonal and DEC-205 monoclonal antibodies for immunoprecipitation/Western blot analysis, we showed that the fusion mRNA is translated into a DEC-205/DCL-1 fusion protein, expressed in the HRS cell lines. These results imply an unusual transcriptional control mechanism in HRS cells, which cotranscribe an mRNA containing DEC-205 and DCL-1 prior to generating the intergenically spliced mRNA to produce a DEC-205/DCL-1 fusion protein.

The application of cognitive orientation to daily occupational performance (CO-OP) with children 5-7 years with developmental coordination disorder

There has been an increase in the use of cognitive frameworks in occupational therapy with children with developmental coordination disorder (DCD). Investigations into the utility of one such cognitive approach, namely Cognitive Orientation to (daily) Occupational Performance (CO-OP), with children with DCD have shown the intervention to be effective with children over 7 years. However, there has been limited research into its utility with younger children. This paper presents two case studies to demonstrate the use of CO-OP with children aged 5-7 years. Two boys with DCD engaged in 10 sessions of CO-OP. These younger children were found to be able to use the global framework (Goal, Plan, Do, Check) to improve their task performance, to develop plans using domain-specific strategies and to engage in checking strategies. Issues relating to attention, motivation and goal setting are discussed in the context of the two case studies.

Fitness assessment of document model

Document classification is a supervised machine learning process, where predefined category labels are assigned to documents based on the hypothesis derived from training set of labelled documents. Documents cannot be directly interpreted by a computer system unless they have been modelled as a collection of computable features. Rogati and Yang [M. Rogati and Y. Yang, Resource selection for domain-specific cross-lingual IR, in SIGIR 2004: Proceedings of the 27th annual international conference on Research and Development in Information Retrieval, ACM Press, Sheffied: United Kingdom, pp. 154-161.] pointed out that the effectiveness of document classification system may vary in different domains. This implies that the quality of document model contributes to the effectiveness of document classification. Conventionally, model evaluation is accomplished by comparing the effectiveness scores of classifiers on model candidates. However, this kind of evaluation methods may encounter either under-fitting or over-fitting problems, because the effectiveness scores are restricted by the learning capacities of classifiers. We propose a model fitness evaluation method to determine whether a model is sufficient to distinguish positive and negative instances while still competent to provide satisfactory effectiveness with a small feature subset. Our experiments demonstrated how the fitness of models are assessed. The results of our work contribute to the researches of feature selection, dimensionality reduction and document classification.

A reference architecture for instructional educational software

Our extensive research has indicated that high-school teachers are reluctant to make use of existing instructional educational software (Pollard, 2005). Even software developed in a partnership between a teacher and a software engineer is unlikely to be adopted by teachers outside the partnership (Pollard, 2005). In this paper we address these issues directly by adopting a reusable architectural design for instructional educational software which allows easy customisation of software to meet the specific needs of individual teachers. By doing this we will facilitate more teachers regularly using instructional technology within their classrooms. Our domain-specific software architecture, Interface-Activities-Model, was designed specifically to facilitate individual customisation by redefining and restructuring what constitutes an object so that they can be readily reused or extended as required. The key to this architecture is the way in which the software is broken into small generic encapsulated components with minimal domain specific behaviour. The domain specific behaviour is decoupled from the interface and encapsulated in objects which relate to the instructional material through tasks and activities. The domain model is also broken into two distinct models - Application State Model and Domainspecific Data Model. This decoupling and distribution of control gives the software designer enormous flexibility in modifying components without affecting other sections of the design. This paper sets the context of this architecture, describes it in detail, and applies it to an actual application developed to teach high-school mathematical concepts.

A PROPAGANDA NA ERA DA CONVERGÊNCIA Um estudo comparativo da linguagem publicitária audiovisual nos meios internet e televisão.

Desde sua criação a internet tem recebido por parte dos anunciantes réplicas propagandas desenvolvidas para outras mídias, porém com o passar dos anos a internet ganhou espaço e recebeu a atenção dos anunciantes desejosos por utilizar suas forças à favor da venda de seus produtos. Contudo conhece-se muito pouco a respeito das características de linguagem específicas da internet, e a literatura existente e pouca e inconclusiva. Com base nesse quadro o trabalho comparou vídeos publicitários desenvolvidos especificamente para a internet com outros desenvolvidos originalmente para a televisão e publicados na internet a fim de identificar pontos de paridade e convergência entre eles no que se refere à linguagem. O trabalho baseou-se nas teorias da Cibercultura e da Sociedade em Rede e nos estudos de Marshall McLuhan e em uma análise comparativa dos vídeos a fim de entender a linguagem técnica, discursiva e visual dos mesmos. A pesquisa apontou diferenças entre os dois grupos de investigados, sobretudo no que se refere à interatividade, potencial de viralização e maximização de visualização. O estudo identificou também que no que se refere à linguagem técnico-discursiva os vídeos apresentaram pouca diferenciação embora tenha-se comprovado que os vídeos desenvolvidos para a internet são mais recentes o que evidencia um início do processo de adaptação da linguagem publicitária ao meio internet.

Background and foreground knowledge in dynamic ontology construction

Ontologies have become a key component in the Semantic Web and Knowledge management. One accepted goal is to construct ontologies from a domain specific set of texts. An ontology reflects the background knowledge used in writing and reading a text. However, a text is an act of knowledge maintenance, in that it re-enforces the background assumptions, alters links and associations in the ontology, and adds new concepts. This means that background knowledge is rarely expressed in a machine interpretable manner. When it is, it is usually in the conceptual boundaries of the domain, e.g. in textbooks or when ideas are borrowed into other domains. We argue that a partial solution to this lies in searching external resources such as specialized glossaries and the internet. We show that a random selection of concept pairs from the Gene Ontology do not occur in a relevant corpus of texts from the journal Nature. In contrast, a significant proportion can be found on the internet. Thus, we conclude that sources external to the domain corpus are necessary for the automatic construction of ontologies.

The dyslexia candidate locus on 2p12 is associated with general cognitive ability and white matter structure

Independent studies have shown that candidate genes for dyslexia and specific language impairment (SLI) impact upon reading/language-specific traits in the general population. To further explore the effect of disorder-associated genes on cognitive functions, we investigated whether they play a role in broader cognitive traits. We tested a panel of dyslexia and SLI genetic risk factors for association with two measures of general cognitive abilities, or IQ, (verbal and non-verbal) in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort (N>5,000). Only the MRPL19/C2ORF3 locus showed statistically significant association (minimum P = 0.00009) which was further supported by independent replications following analysis in four other cohorts. In addition, a fifth independent sample showed association between the MRPL19/C2ORF3 locus and white matter structure in the posterior part of the corpus callosum and cingulum, connecting large parts of the cortex in the parietal, occipital and temporal lobes. These findings suggest that this locus, originally identified as being associated with dyslexia, is likely to harbour genetic variants associated with general cognitive abilities by influencing white matter structure in localised neuronal regions.

Self-training from labeled features for sentiment analysis

Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon with preferences on expectations of sentiment labels of those lexicon words being expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie-review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than existing weakly-supervised sentiment classification methods despite using no labeled documents.

Learning sentiment classification model from labeled features

We propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon. Preferences on expectations of sentiment labels of those lexicon words are expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than exiting weakly-supervised sentiment classification methods despite using no labeled documents.

Case based design of knitwear

In the developed world we are surrounded by man-made objects, but most people give little thought to the complex processes needed for their design. The design of hand knitting is complex because much of the domain knowledge is tacit. The objective of this thesis is to devise a methodology to help designers to work within design constraints, whilst facilitating creativity. A hybrid solution including computer aided design (CAD) and case based reasoning (CBR) is proposed. The CAD system creates designs using domain-specific rules and these designs are employed for initial seeding of the case base and the management of constraints. CBR reuses the designer's previous experience. The key aspects in the CBR system are measuring the similarity of cases and adapting past solutions to the current problem. Similarity is measured by asking the user to rank the importance of features; the ranks are then used to calculate weights for an algorithm which compares the specifications of designs. A novel adaptation operator called rule difference replay (RDR) is created. When the specifications to a new design is presented, the CAD program uses it to construct a design constituting an approximate solution. The most similar design from the case-base is then retrieved and RDR replays the changes previously made to the retrieved design on the new solution. A measure of solution similarity that can validate subjective success scores is created. Specification similarity can be used as a guide whether to invoke CBR, in a hybrid CAD-CBR system. If the newly resulted design is suffciently similar to a previous design, then CBR is invoked; otherwise CAD is used. The application of RDR to knitwear design has demonstrated the flexibility to overcome deficiencies in rules that try to automate creativity, and has the potential to be applied to other domains such as interior design.

The impact of general intellectual ability and white matter volume on the functional outcome of patients with bipolar disorder and their relatives

Background: There is substantial evidence that cognitive deficits and brain structural abnormalities are present in patients with Bipolar Disorder (BD) and in their first-degree relatives. Previous studies have demonstrated associations between cognition and functional outcome in BD patients but have not examined the role of brain morphological changes. Similarly, the functional impact of either cognition or brain morphology in relatives remains unknown. Therefore we focused on delineating the relationship between psychosocial functioning, cognition and brain structure, in relation to disease expression and genetic risk for BD. Methods: Clinical, cognitive and brain structural measures were obtained from 41 euthymic BD patients and 50 of their unaffected first-degree relatives. Psychosocial function was evaluated using the General Assessment of Functioning (GAF) scale. We examined the relationship between level of functioning and general intellectual ability (IQ), memory, attention, executive functioning, symptomatology, illness course and total gray matter, white matter and cerebrospinal fluid volumes. Limitations: Cross-sectional design. Results: Multiple regression analyses revealed that IQ, total white matter volume and a predominantly depressive illness course were independently associated with functional outcome in BD patients, but not in their relatives, and accounted for a substantial proportion (53%) of the variance in patients' GAF scores. There were no significant domain-specific associations between cognition and outcome after consideration of IQ. Conclusions: Our results emphasise the role of IQ and white matter integrity in relation to outcome in BD and carry significant implications for treatment interventions. © 2010 Elsevier B.V.

SemSearch:a search engine for the semantic web

Existing semantic search tools have been primarily designed to enhance the performance of traditional search technologies but with little support for ordinary end users who are not necessarily familiar with domain specific semantic data, ontologies, or SQL-like query languages. This paper presents SemSearch, a search engine, which pays special attention to this issue by providing several means to hide the complexity of semantic search from end users and thus make it easy to use and effective.