Anne R. Haake

eyePatterns: software for identifying patterns and similarities across fixation sequences

Fixation sequence analysis can reveal the cognitive strategies that drive eye movements. Unfortunately this type of analysis is not as common as other popular eye movement measures, such as fixation duration and trace length, because the proper tools for fixation sequence analysis are not incorporated into most popular eye movement software. This paper describes eyePatterns, a new tool for discovering similarities in fixation sequences and identifying the experimental variables that may influence their characteristics.

Here, there, anywhere: remote usability testing that works

Usability testing is regarded as a key element in user-centered design. Several studies from the Standish Group have shown that usability testing increases the chance of developing usable software. Companies are faced with many challenges: their customers demand usable products at reasonable costs and the customer base is distributed and diverse. Unfortunately, usability testing is often perceived as impractical due to the remote and distributed location of users, limited access to representative users, or a work context that is difficult to reproduce in a laboratory setting. Additionally, for some companies, the cost of transporting users or developers to remote locations can be prohibitive. Interest in remote usability testing has grown in response to these concerns. As the user advocate, the Information Technology student needs to be provided not only with hands-on experience in usability testing, but also with its nuances. These include an understanding of the wide range of formats and options available such as remote usability testing. Moreover, a remote format may be a solution for universities that do not have the resources to set up formal laboratories. There is a need to understand how best to facilitate remote testing in a classroom environment. The focus of our study was to identify appropriate tools and define methodologies for efficient and effective remote testing environments. We investigated commercial tools to determine their usefulness and cost-effectiveness for the classroom and then conducted an empirical study to compare traditional and remote usability testing of a web site using one of these tools. This paper will report on advantages and disadvantages of various remote testing tools, modifications to procedures and protocols of traditional testing, and the project findings, including usability problem identification, which establish the effectiveness of remote usability testing. Recommendations will be made for providing a credible environment for remote testing.

Bcl-2 Overexpression in the HaCaT Cell Line is Associated With A Different Membrane Fatty Acid Composition and Sensitivity to Oxidative Stress

Different mechanisms have been proposed for the activity of the Bcl-2 proto-oncogene product. A bona fide antioxidant activity and a pro-oxidant setting up of the cell have been suggested using different experimental models, yet many uncertainties exist about the biochemical mechanism of Bcl-2 action. In the present paper, we report the characterization of the cellular response to mild oxidative stress of a cultured cell line of immortalized keratinocytes (HaCaT), overexpressing the Bcl-2 oncogene product. A sublethal oxidative stress was induced by 1 h treatment with 200 microM tert-butyl-hydroperoxide (t-BOOH). Following peroxide treatment, the formation of reactive oxygen species was lower in Bcl-2 expressing cells, suggesting a better capacity to counter oxidative stress. Total Superoxide Dismutase activity was induced by oxidative t-BOOH treatment in bcl-2 transfected cells, which also accumulated less damage to membrane lipids and proteins, as assessed by TBA-RS and carbonyl formation respectively. On the other hand, the formation of 4-hydroxy-nonenal, a more specific marker of peroxidative damage to polyunsaturated fatty acids, was higher in bcl-2 transfected cells than in control cells. Bcl-2 over-expression was also associated with significant changes in the fatty acid composition of cell membranes. Transfected cells presented a higher proportion of mono-unsaturated fatty acids and omega6 poly unsaturated fatty acids and a lower proportion of penta-enoic PUFA, thus resulting in a higher unsaturation index with respect to control cells. Changes in protein kinase C activity were also associated to bcl-2 expression, possibly resulting from the differences in membrane fatty acid composition. These data may be an important background for the understanding of Bcl-2 involvement in the control of apoptotic response as well as in the induction of antioxidant cell defenses against oxidative stress.

The many facets of HCI

In the last ten years HCI, the study and practice of usability, has emerged as a multidisciplinary, multifaceted field. HCI is an essential knowledge area that pervades the computing field and should be included in every computing professionals education. Computing professionals need to create software, and other technologies, so that users will want to use them and will be able to effectively use them. User advocacy distinguishes the Information Technology discipline from the other computing disciplines. Graduates need to understand the many facets of HCI. These include not only understanding the design of the interface, but also the broader issues of the user experience, process and business concerns, challenges of distributed computing, the emergence of supportive technologies, and the impact of ubiquitous computing. This paper will introduce the key HCI concepts, and discuss the challenges, issues and future developments of the field that will drive Information Technology curriculum development.

Thalidomide inhibits UVB-induced mouse keratinocyte apoptosis by both TNF-α-dependent and TNF-α-independent pathways

Background: Thalidomide is an anti‐inflammatory pharmacologic agent that has been utilized as a therapy for a number of dermatologic diseases. Its anti‐inflammatory properties have been attributed to its ability to antagonize tumor necrosis factor‐alfa (TNF‐α) production by monocytes. However, its mechanism of action in the skin is not known.

An Expert-in-the-loop Paradigm for Learning Medical Image Grouping

Image grouping in knowledge-rich domains is challenging, since domain knowledge and expertise are key to transform image pixels into meaningful content. Manually marking and annotating images is not only labor-intensive but also ineffective. Furthermore, most traditional machine learning approaches cannot bridge this gap for the absence of experts’ input. We thus present an interactive machine learning paradigm that allows experts to become an integral part of the learning process. This paradigm is designed for automatically computing and quantifying interpretable grouping of dermatological images. In this way, the computational evolution of an image grouping model, its visualization, and expert interactions form a loop to improve image grouping. In our paradigm, dermatologists encode their domain knowledge about the medical images by grouping a small subset of images via a carefully designed interface. Our learning algorithm automatically incorporates these manually specified connections as constraints for re-organizing the whole image dataset. Performance evaluation shows that this paradigm effectively improves image grouping based on expert knowledge.

Decision Style in a Clinical Reasoning Corpus

The dual process model (Evans, 2008) posits two types of decision-making, which may be ordered on a continuum from intuitive to analytical (Hammond, 1981). This work uses a dataset of narrated image-based clinical reasoning, collected from physicians as they diagnosed dermatological cases presented as images. Two annotators with training in cognitive psychology assigned each narrative a rating on a four-point decision scale, from intuitive to analytical. This work discusses the annotation study, and makes contributions for resource creation methodology and analysis in the clinical domain.

Human-centric approaches to image understanding and retrieval

The amount of digital medical image data is increasing rapidly in terms of both quantity and heterogeneity. There exists a great need to format medical image archives so as to facilitate diagnostics and preventive medicine. To achieve this, in the past few decades great efforts have been made to investigate methods of applying content-based image retrieval (CBIR) techniques to retrieve images. However, several critical challenges remain. Recently, CBIR research has become intertwined with the fundamental problem of image understanding and it is recognized that computing solutions that bridge the “semantic gap” must capture higher-level domain knowledge of medical end users. We are investigating the incorporation of state-of-the-art visual categorization techniques into conventional CBIR approaches. Visual attention deployment strategies of medical experts serve as an objective measure to help us understand the perceptual and conceptual processes involved in identifying key visual features and selecting diagnostic regions of the images. Understanding these processes will inform and direct feature selection approaches on medical images, such as the dermatological images used in our study. We also explore systematic and effective information integration methods of image data and semantic descriptions with the long-term goals of building efficient human-centered multi-modal interactive CBIR systems.

SIMPLIFIED EYE TRACKING ENHANCES PROBLEM UNDERSTANDING AND SOLUTION DISCOVERY IN USABILITY TESTING

Identifying problems and generating recommendations for product user interface redesign are primary goals of usability testing. Typical methods seem inadequate for the deep understanding of usability problems needed for developing effective solutions. Sporadically over the past 50 years, usability teams have tracked user eye movements to achieve this deeper understanding, but high cost and complexity have prevented the widespread use of this technology. We investigated whether simplified eye tracking techniques, in combination with traditional usability testing methods, could enhance problem discovery and understanding. These techniques included: using a video-based eye tracking system, tracking only a few participants, and encoding gaze durations (not individual fixations) on only a few areas of interest. For each of three interface versions, we studied twelve participants with traditional usability testing techniques and eye tracked just two. Eye tracking yielded discovery of additional usability problems and detailed characterizations which led to more focused and appropriate solutions.

Towards Automatic Annotation of Clinical Decision-Making Style

Clinical decision-making has high-stakes outcomes for both physicians and patients, yet little research has attempted to model and automatically annotate such decision-making. The dual process model (Evans, 2008) posits two types of decision-making, which may be ordered on a continuum from intuitive to analytical (Hammond, 1981). Training clinicians to recognize decision-making style and select the most appropriate mode of reasoning for a particular context may help reduce diagnostic error (Norman, 2009). This study makes preliminary steps towards detection of decision style, based on an annotated dataset of image-based clinical reasoning in which speech data were collected from physicians as they inspected images of dermatological cases and moved towards diagnosis (Hochberg et al., 2014). A classifier was developed based on lexical, speech, disfluency, physician demographic, cognitive, and diagnostic difficulty features. Using random forests for binary classification of intuitive vs. analytical decision style in physicians’ diagnostic descriptions, the model improved on the baseline by over 30%. The introduced computational model provides construct validity for decision styles, as well as insights into the linguistic expression of decision-making. Eventually, such modeling may be incorporated into instructional systems that teach clinicians to become more effective decision makers.