Molecular and genetic analyses of Fgf signaling during cardiac outflow tract development

Epithelial-mesenchymal tissue interactions regulate the development of derivatives of the caudal pharyngeal arches (PAs) to govern the ultimate morphogenesis of the aortic arch and outflow tract (OFT) of the heart. Disruption of these signaling pathways is thought to contribute to the pathology of a significant proportion of congenital cardiovascular defects in humans. In this study, I tested whether Fibroblast Growth Factor 15 (Fgf15), a secreted signaling molecule expressed within the PAs, is an extracellular mediator of tissue interactions during PA and OFT development. Analyses of Fgf15−/− mouse embryonic hearts revealed abnormalities primarily localized to the OFT, correlating with aberrant cardiac neural crest cell behavior. The T-box-containing transcription factor Tbx1 has been implicated in the cardiovascular defects associated with the human 22q11 Deletion Syndromes, and regulates the expression of other Fgf family members within the mouse PAs. However, expression and genetic interaction studies incorporating mice deficient for Tbx1, its upstream regulator, Sonic Hedgehog (Shh), or its putative downstream effector, Fgf8, indicated that Fgf15 functions during OFT development in a manner independent of these factors. Rather, analyses of compound mutant mice indicated that Fgf15 and Fgf9, an additional Fgf family member expressed within the PAs, genetically interact, providing insight into the factors acting in conjunction with Fgf15 during OFT development. Finally, in an effort to further characterize this Fgf15-mediated developmental pathway, promoter deletion analyses were employed to isolate a 415bp sequence 7.1Kb 5′ to the Fgf15 transcription start site both necessary and sufficient to drive reporter gene expression within the epithelium of the PAs. Sequence comparisons among multiple mammalian species facilitated the identification of evolutionarily conserved potential trans-acting factor binding sites within this fragment. Subsequent studies will investigate the molecular pathway(s) through which Fgf15 functions via identification of factors that bind to this element to govern Fgf15 gene expression. Furthermore, targeted deletion of this element will establish the developmental requirement for pharyngeal epithelium-derived Fgf15 signaling function. Taken as a whole, these data demonstrate that Fgf15 is a component of a novel, Tbx1-independent molecular pathway, functioning within the PAs in a manner cooperative with Fgf9, required for proper development of the cardiac OFT. ^

Studies of pseudoachondroplasia chondrocytes and knockdown of the cartilage oligomeric matrix protein

Cartilage oligomeric matrix protein (COMP) is a large, homopentameric, extracellular matrix glycoprotein. Mutations in COMP cause two skeletal dysplasias: pseudoachondroplasia (PSACH) and multiple epiphyseal dysplasia (EMD1). These dwarfing conditions are caused by retention of misfolded mutant COMP with type IX collagen and matrilin-3 (MATN3) in the rough endoplasmic reticulum (rER) of the chondrocyte. These proteins form a matrix in the rER that continues to expand until it fills the entire cell, eventually causing cell death. Interestingly, loss of COMP in COMP null mice does not affect normal bone development or growth, suggesting that elimination of COMP (wildtype and mutant) expression may prevent PSACH. The hypothesis of these studies was that a hammerhead ribozyme could eliminate or knockdown COMP mRNA expression in PSACH chondrocytes . To test this hypothesis, a human chondrocyte model system that recapitulates the PSACH chondrocyte phenotype was developed by over-expressing mutant (mt-) COMP in normal chondrocytes using a recombinant adenovirus. Chondrocytes over-expressing mt-COMP developed giant rER cisternae containing COMP, type IX collagen and MATN3. Deconvolution microscopy and computer modeling showed that these proteins formed an ordered matrix surrounding a type II pro-collagen core. Additionally, the results show that a hammerhead ribozyme, ribozyme 56 (Ribo56) reduced over-expressed mt-COMP in COS cells and endogenous COMP in normal chondrocytes and mt-COMP in three PSACH chondrocytes cell line (with different mutations) by 40-70%. Altogether, these studies show that the PSACH cellular phenotype can be created in vitro and that the mt-COMP protein burden can be reduced by the presence of a COMP-specific ribozyme. Future studies will focus on designing ribozymes or short interfering RNA (siRNA) technologies that will result in better knockdown of COMP expression as well as the temporal constraints imposed by the PSACH phenotype. ^

Anal warts and their predictors among HIV-infected women

Human papillomavirus (HPV) is a necessary cause of cervical cancer and is also strongly associated with anal cancer. While different factors such as CD4+ cell count, HIV RNA viral load, smoking status, and cytological screening results have been identified as risk factors for the infection of HPV high-risk types and associated cancers, much less is known about the association between those risk factors and the infection of HPV low-risk types and anogential warts. In this dissertation, a public dataset (release P09) obtained from the Women's Interagency HIV Study (WIHS) was used to examine the effects of those risk factors on the size of the largest anal warts in HIV-infected women in the United States. Linear mixed modeling was used to address this research question. ^ The prevalence of anal warts at baseline for WIHS participants was higher than other populations. Incidence of anal warts in HIV-infected women was significantly higher than that of HIV-uninfected women [4.15 cases per 100 person-years (95% CI: 3.83–4.77) vs. 1.30 cases per 100 person-years (95% CI: 1.00–1.58), respectively]. There appeared to be an inverse association between the size of the largest anal wart and CD4+ cell count at baseline visit, however it was not statistically significant. There was no association between size of the largest anal wart and CD4+ cell count or HIV RNA viral load over time among HIV-infected women. There was also no association between the size of the largest anal wart and current smoking over time in HIV-infected women, even though smokers had larger warts at baseline than non-smokers. Finally, even though a woman with Pap smear results of ASCUS/LGSIL was found to have an anal wart larger than a woman with normal cervical Pap smear results the relationship between the size of the largest anal wart with cervical Pap smear results over time remains unclear. ^ Although the associations between these risk factors and the size of the largest anal wart over time in HIV-infected women could not be firmly established, this dissertation poses several questions concerning anal wart development for further exploration: (1) the role of immune function (i.e., CD4+ cell count), (2) the role of smoking status and the interaction between smoking status with other risk factors (e.g., CD4+ cell count or HIV RNA viral load), (3) the molecular mechanism of smoking on anal warts over time, (4) the potential for development of a screening program using anal Pap smear in HIV-infected women, and (5) how cost-effective and efficacious would an anal Pap smear screening program be in this high-risk population. ^

NOVEL PHANTOMS AND POST-PROCESSING FOR DIFFUSION SPECTRUM IMAGING

High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.

Design, Calibration, and Evaluation of Depth-of-Interaction-Capable PET Detector Modules

High-resolution, small-bore PET systems suffer from a tradeoff between system sensitivity, and image quality degradation. In these systems long crystals allow mispositioning of the line of response due to parallax error and this mispositioning causes resolution blurring, but long crystals are necessary for high system sensitivity. One means to allow long crystals without introducing parallax errors is to determine the depth of interaction (DOI) of the gamma ray interaction within the detector module. While DOI has been investigated previously, newly available solid state photomultipliers (SSPMs) well-suited to PET applications and allow new modules for investigation. Depth of interaction in full modules is a relatively new field, and so even if high performance DOI capable modules were available, the appropriate means to characterize and calibrate the modules are not. This work presents an investigation of DOI capable arrays and techniques for characterizing and calibrating those modules. The methods introduced here accurately and reliably characterize and calibrate energy, timing, and event interaction positioning. Additionally presented is a characterization of the spatial resolution of DOI capable modules and a measurement of DOI effects for different angles between detector modules. These arrays have been built into a prototype PET system that delivers better than 2.0 mm resolution with a single-sided-stopping-power in excess of 95% for 511 keV g's. The noise properties of SSPMs scale with the active area of the detector face, and so the best signal-to-noise ratio is possible with parallel readout of each SSPM photodetector pixel rather than multiplexing signals together. This work additionally investigates several algorithms for improving timing performance using timing information from multiple SSPM pixels when light is distributed among several photodetectors.

Understanding and Characterizing Shared Decision-Making and Behavioral Intent in Medical Uncertainty

Applying Theoretical Constructs to Address Medical Uncertainty Situations involving medical reasoning usually include some level of medical uncertainty. Despite the identification of shared decision-making (SDM) as an effective technique, it has been observed that the likelihood of physicians and patients engaging in shared decision making is lower in those situations where it is most needed; specifically in circumstances of medical uncertainty. Having identified shared decision making as an effective, yet often a neglected approach to resolving a lack of information exchange in situations involving medical uncertainty, the next step is to determine the way(s) in which SDM can be integrated and the supplemental processes that may facilitate its integration. SDM involves unique types of communication and relationships between patients and physicians. Therefore, it is necessary to further understand and incorporate human behavioral elements - in particular, behavioral intent - in order to successfully identify and realize the potential benefits of SDM. This paper discusses the background and potential interaction between the theories of shared decision-making, medical uncertainty, and behavioral intent. Identifying Shared Decision-Making Elements in Medical Encounters Dealing with Uncertainty A recent summary of the state of medical knowledge in the U.S. reported that nearly half (47%) of all treatments were of unknown effectiveness, and an additional 7% involved an uncertain tradeoff between benefits and harms. Shared decision-making (SDM) was identified as an effective technique for managing uncertainty when two or more parties were involved. In order to understand which of the elements of SDM are used most frequently and effectively, it is necessary to identify these key elements, and understand how these elements related to each other and the SDM process. The elements identified through the course of the present research were selected from basic principles of the SDM model and the “Data, Information, Knowledge, Wisdom” (DIKW) Hierarchy. The goal of this ethnographic research was to identify which common elements of shared decision-making patients are most often observed applying in the medical encounter. The results of the present study facilitated the understanding of which elements patients were more likely to exhibit during a primary care medical encounter, as well as determining variables of interest leading to more successful shared decision-making practices between patients and their physicians. Understanding Behavioral Intent to Participate in Shared Decision-Making in Medically Uncertain Situations Objective: This article describes the process undertaken to identify and validate behavioral and normative beliefs and behavioral intent of men between the ages of 45-70 with regard to participating in shared decision-making in medically uncertain situations. This article also discusses the preliminary results of the aforementioned processes and explores potential future uses of this information which may facilitate greater understanding, efficiency and effectiveness of doctor-patient consultations.Design: Qualitative Study using deductive content analysisSetting: Individual semi-structure patient interviews were conducted until data saturation was reached. Researchers read the transcripts and developed a list of codes.Subjects: 25 subjects drawn from the Philadelphia community.Measurements: Qualitative indicators were developed to measure respondents’ experiences and beliefs related to behavioral intent to participate in shared decision-making during medical uncertainty. Subjects were also asked to complete the Krantz Health Opinion Survey as a method of triangulation.Results: Several factors were repeatedly described by respondents as being essential to participate in shared decision-making in medical uncertainty. These factors included past experience with medical uncertainty, an individual’s personality, and the relationship between the patient and his physician.Conclusions: The findings of this study led to the development of a category framework that helped understand an individual’s needs and motivational factors in their intent to participate in shared decision-making. The three main categories include 1) an individual’s representation of medically uncertainty, 2) how the individual copes with medical uncertainty, and 3) the individual’s behavioral intent to seek information and participate in shared decision-making during times of medically uncertain situations.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

The cDNA cloning of murine HIP /L29 and the functional analysis of HIP/L29 domains

Human heparin/heparan sulfate interacting protein/L29 (HIP/L29) is a heparin/heparan sulfate (Hp/HS) binding protein found in many adult human tissues. Potential functions of this protein are promotion of embryo adhesion, modulation of blood coagulation, and control of cell growth. While these activities are diverse, the ability of human HIP/L29 to interact with Hp/HS at the cell surface may be a unifying mechanism of action since Hp/HS influences all of these processes. A murine ortholog has been identified that has 78.8% homology over the entire sequence and identity over the N-terminal 64 amino acids when compared to human HIP/L29. Northern, Western, and immunohistochemical analysis shows that murine HIP/L29 mRNA and protein are expressed in a tissue specific manner. Murine HIP/L29 is enriched in the membrane fraction of NmuMG cells where it is eluted with high salt, suggesting that it is a peripheral membrane protein. The ability of murine HIP/L29 to bind Hp is verified by studies using native and recombinant forms of murine HIP/L29. A synthetic peptide (HIP peptide-2) derived from the identical N-terminal region of HIP/L29 proteins was tested for the ability to bind Hp and support cell adhesion. This peptide was chosen because it conforms to a proposed consensus sequence for Hp/HS binding peptides. HIP peptide-2 binds Hp in a dose-dependent, saturable, and selective manner and supports Hp-dependent cell adhesion. However, a scrambled form of this peptide displayed similar activities indicating a lack of peptide sequence specificity required for activity. Lastly, an unbiased approach was used to identify sequences within human and mouse HIP/L29 proteins necessary for Hp/HS binding. A panel of recombinant proteins was made that collectively are deficient in every human HIP/L29 domain. The activities of these deletion mutants and recombinant murine HIP/L29 were compared to the activity of recombinant human HIP/L29 in a number of assays designed to look at differences in the ability to bind Hp/HS. These studies suggest that each domain within human HIP/L29 is important for binding to Hp/HS and divergences in the C-terminus of human and mouse HIP/L29 account for a decrease in murine HIP/L29 affinity for Hp/HS. It is apparent that multiple domains within human and mouse HIP/L29 contribute to the function of Hp/HS binding. The interaction of multiple HIP/L29 domains with Hp/HS will influence the biological activity of HIP/L29 proteins. ^

The computer paradigm in vocational guidance

The technological advances in last decades have transformed the external resources of Vocational Counseling, Occupational Information and assessment of clients. Most computer systems follow a behaviorist-cognitive approach. However, the use of vocational counseling software is not exclusive to one conceptual approach. Computers are introduced in education from primary school; counselors and other educators are expected to use those systems. The attitude of counselors ranges from enthusiastic acceptance to complete refusal. Many counselors fear that computers will replace them. An underlying theory holds that counseling is based on the counselor-client interaction. A computer- client interaction cannot be considered vocational counseling. Counseling has five basic aims: prevention, assistance, education and development, service of diverse groups and research. The most relevant trends in computer-based counseling are: tests and questionnaires based on computers, adaptive development, computarized information, vocational counseling systems and research. Basic aims and the potential role of computers in achieving them are discussed. Present vocational counselors can use the technology of computers to link the past of our profession to its promising future. In view of these premises we have developed two computer systems that assist the vocational counseling process: "Professional Interests Questionnaire, Computer Version", and "Computer-based System of Vocational Counseling".

The computer paradigm in vocational guidance

The technological advances in last decades have transformed the external resources of Vocational Counseling, Occupational Information and assessment of clients. Most computer systems follow a behaviorist-cognitive approach. However, the use of vocational counseling software is not exclusive to one conceptual approach. Computers are introduced in education from primary school; counselors and other educators are expected to use those systems. The attitude of counselors ranges from enthusiastic acceptance to complete refusal. Many counselors fear that computers will replace them. An underlying theory holds that counseling is based on the counselor-client interaction. A computer- client interaction cannot be considered vocational counseling. Counseling has five basic aims: prevention, assistance, education and development, service of diverse groups and research. The most relevant trends in computer-based counseling are: tests and questionnaires based on computers, adaptive development, computarized information, vocational counseling systems and research. Basic aims and the potential role of computers in achieving them are discussed. Present vocational counselors can use the technology of computers to link the past of our profession to its promising future. In view of these premises we have developed two computer systems that assist the vocational counseling process: "Professional Interests Questionnaire, Computer Version", and "Computer-based System of Vocational Counseling".

The computer paradigm in vocational guidance

The technological advances in last decades have transformed the external resources of Vocational Counseling, Occupational Information and assessment of clients. Most computer systems follow a behaviorist-cognitive approach. However, the use of vocational counseling software is not exclusive to one conceptual approach. Computers are introduced in education from primary school; counselors and other educators are expected to use those systems. The attitude of counselors ranges from enthusiastic acceptance to complete refusal. Many counselors fear that computers will replace them. An underlying theory holds that counseling is based on the counselor-client interaction. A computer- client interaction cannot be considered vocational counseling. Counseling has five basic aims: prevention, assistance, education and development, service of diverse groups and research. The most relevant trends in computer-based counseling are: tests and questionnaires based on computers, adaptive development, computarized information, vocational counseling systems and research. Basic aims and the potential role of computers in achieving them are discussed. Present vocational counselors can use the technology of computers to link the past of our profession to its promising future. In view of these premises we have developed two computer systems that assist the vocational counseling process: "Professional Interests Questionnaire, Computer Version", and "Computer-based System of Vocational Counseling".

Usability-Oriented Software Development Process

Usability is the capability of the software product to be understood, learned, used and attractive to the user, when used under specified conditions. Many studies demonstrate the benefits of usability, yet to this day software products continue to exhibit consistently low levels of this quality attribute. Furthermore, poor usability in software systems contributes largely to software failing in actual use. One of the main disciplines involved in usability is that of Human-Computer Interaction (HCI). Over the past two decades the HCI community has proposed specific features that should be present in applications to improve their usability, yet incorporating them into software continues to be far from trivial for software developers. These difficulties are due to multiple factors, including the high level of abstraction at which these HCI recommendations are made and how far removed they are from actual software implementation. In order to bridge this gap, the Software Engineering community has long proposed software design solutions to help developers include usability features into software, however, the problem remains an open research question. This doctoral thesis addresses the problem of helping software developers include specific usability features into their applications by providing them with a structured and tangible guidance in the form of a process, which we have termed the Usability-Oriented Software Development Process. This process is supported by a set of Software Usability Guidelines that help developers to incorporate a set of eleven usability features with high impact on software design. After developing the Usability-oriented Software Development Process and the Software Usability Guidelines, they have been validated across multiple academic projects and proven to help software developers to include such usability features into their software applications. In doing so, their use significantly reduced development time and improved the quality of the resulting designs of these projects. Furthermore, in this work we propose a software tool to automate the application of the proposed process. In sum, this work contributes to the integration of the Software Engineering and HCI disciplines providing a framework that helps software developers to create usable applications in an efficient way.

Software Design Guidelines for Usability

For years, the Human Computer Interaction (HCI) community has crafted usability guidelines that clearly define what characteristics a software system should have in order to be easy to use. However, in the Software Engineering (SE) community keep falling short of successfully incorporating these recommendations into software projects. From a SE perspective, the process of incorporating usability features into software is not always straightforward, as a large number of these features have heavy implications in the underlying software architecture. For example, successfully including an “undo” feature in an application requires the design and implementation of many complex interrelated data structures and functionalities. Our work is focused upon providing developers with a set of software design patterns to assist them in the process of designing more usable software. This would contribute to the proper inclusion of specific usability features with high impact on the software design. Preliminary validation data show that usage of the guidelines also has positive effects on development time and overall software design quality.

Improving Speech Interaction in Vehicles Using Context-Aware Information through A SCXML Framework

Speech Technologies can provide important benefits for the development of more usable and safe in-vehicle human-machine interactive systems (HMIs). However mainly due robustness issues, the use of spoken interaction can entail important distractions to the driver. In this challenging scenario, while speech technologies are evolving, further research is necessary to explore how they can be complemented with both other modalities (multimodality) and information from the increasing number of available sensors (context-awareness). The perceived quality of speech technologies can significantly be increased by implementing such policies, which simply try to make the best use of all the available resources; and the in vehicle scenario is an excellent test-bed for this kind of initiatives. In this contribution we propose an event-based HMI design framework which combines context modelling and multimodal interaction using a W3C XML language known as SCXML. SCXML provides a general process control mechanism that is being considered by W3C to improve both voice interaction (VoiceXML) and multimodal interaction (MMI). In our approach we try to anticipate and extend these initiatives presenting a flexible SCXML-based approach for the design of a wide range of multimodal context-aware HMI in-vehicle interfaces. The proposed framework for HMI design and specification has been implemented in an automotive OSGi service platform, and it is being used and tested in the Spanish research project MARTA for the development of several in-vehicle interactive applications.

Usability Planner: A Tool to Support the Process of Selecting Usability Methods

There is increasing pressure on developers to produce usable systems, which requires the use of appropriate methods to support user centred design during development. There is currently no consistent advice on which methods are appropriate in which circumstances, so the selection of methods relies on individual experience and expertise. Considerable effort is required to collate information from various sources and to understand the applicability of each method in a particular situation. Usability Planner is a tool aimed to support the selection of the most appropriate methods depending on project and organizational constraints. Many of the rules employed are derived from ISO standards, complemented with rules from the authors’ experience.