HindSight: Encouraging Exploration through Direct Encoding of Personal Interaction History

Physical and digital objects often leave markers of our use. Website links turn purple after we visit them, for example, showing us information we have yet to explore. These “footprints” of interaction offer substantial benefits in information saturated environments - they enable us to easily revisit old information, systematically explore new information, and quickly resume tasks after interruption. While applying these design principles have been successful in HCI contexts, direct encodings of personal interaction history have received scarce attention in data visualization. One reason is that there is little guidance for integrating history into visualizations where many visual channels are already occupied by data. More importantly, there is not firm evidence that making users aware of their interaction history results in benefits with regards to exploration or insights. Following these observations, we propose HindSight - an umbrella term for the design space of representing interaction history directly in existing data visualizations. In this paper, we examine the value of HindSight principles by augmenting existing visualizations with visual indicators of user interaction history (e.g. How the Recession Shaped the Economy in 255 Charts, NYTimes). In controlled experiments of over 400 participants, we found that HindSight designs generally encouraged people to visit more data and recall different insights after interaction. The results of our experiments suggest that simple additions to visualizations can make users aware of their interaction history, and that these additions significantly impact users\u27 exploration and insights

HindSight: Encouraging Exploration through Direct Encoding of Personal Interaction History

Physical and digital objects often leave markers of our use. Website links turn purple after we visit them, for example, showing us information we have yet to explore. These “footprints” of interaction offer substantial benefits in information saturated environments - they enable us to easily revisit old information, systematically explore new information, and quickly resume tasks after interruption. While applying these design principles have been successful in HCI contexts, direct encodings of personal interaction history have received scarce attention in data visualization. One reason is that there is little guidance for integrating history into visualizations where many visual channels are already occupied by data. More importantly, there is not firm evidence that making users aware of their interaction history results in benefits with regards to exploration or insights. Following these observations, we propose HindSight - an umbrella term for the design space of representing interaction history directly in existing data visualizations. In this paper, we examine the value of HindSight principles by augmenting existing visualizations with visual indicators of user interaction history (e.g. How the Recession Shaped the Economy in 255 Charts, NYTimes). In controlled experiments of over 400 participants, we found that HindSight designs generally encouraged people to visit more data and recall different insights after interaction. The results of our experiments suggest that simple additions to visualizations can make users aware of their interaction history, and that these additions significantly impact users\u27 exploration and insights

Beyond Detection: Investing in Practical and Theoretical Applications of Emotion + Visualization

Emotion is a dynamic variable that modulates how we perceive, reason about, and interact with our environment. Recent studies have established that emotion’s influence carries to data analysis and visualization, impacting performance in ways both positive and negative. While we are still in the infancy of understanding the role emotion plays in analytical contexts, advances in physiological sensing and emotion research have raised the possibility of creating emotion-aware systems. In this position paper, we argue that it is critical to consider the potential advances that can be made even in the face of imperfect sensing, while we continue to address the practical challenges of monitoring emotion in the wild. To underscore the importance of this line of inquiry, we highlight several key challenges related to detection, adaptation, and impact of emotional states for users of data visualization systems, and motivate promising avenues for future research in these areas

Learn Piano with BACh: An Adaptive Learning Interface that Adjusts Task Difficulty based on Brain State

We present Brain Automated Chorales (BACh), an adaptive brain-computer system that dynamically increases the levels of difficulty in a musical learning task based on pianists\u27 cognitive workload measured by functional near-infrared spectroscopy. As users\u27 cognitive workload fell below a certain threshold, suggesting that they had mastered the material and could handle more cognitive information, BACh automatically increased the difficulty of the learning task. We found that learners played with significantly increased accuracy and speed in the brain-based adaptive task compared to our control condition. Participant feedback indicated that they felt they learned better with BACh and they liked the timings of the level changes. The underlying premise of BACh can be applied to learning situations where a task can be broken down into increasing levels of difficulty

Thiosquaramides: pH switchable anion transporters

The transport of anions across cellular membranes is an important biological function governed by specialised proteins. In recent years, many small molecules have emerged that mimick the anion transport behaviour of these proteins, but only a few of these synthetic molecules also display the gating/switching behaviour seen in biological systems. A small series of thiosquar-amides was synthesised and their pH-dependent chloride binding and anion transport behaviour was investigated using 1H NMR titrations, single crystal X-ray diffraction and a variety of vesicle-based techniques. Spectrophotometric titrations and DFT calculations revealed that the thiosquaramides are significantly more acidic than their oxosquaramide analogues, with pKa values between 4.0 and 9.0. This led to the observation that at pH 7.2 the anion transport ability of the thiosquaramides is fully switched OFF due to deprotonation of the receptor, but is completely switched ON at lower pH

Life in the fast lane: Revisiting the fast growth—High survival paradigm during the early life stages of fishes

Early life survival is critical to successful replenishment of fish populations, and hypotheses developed under the Growth-Survival Paradigm (GSP) have guided investigations of controlling processes. The GSP postulates that recruitment depends on growth and mortality rates during early life stages, as well as their duration, after which the mortality declines substantially. The GSP predicts a shift in the frequency distribution of growth histories with age towards faster growth rates relative to the initial population because slow-growing individuals are subject to high mortality (via starvation and predation). However, mortality data compiled from 387 cases published in 153 studies (1971–2022) showed that the GSP was only supported in 56% of cases. Selection against slow growth occurred in two-thirds of field studies, leaving a non-negligible fraction of cases showing either an absence of or inverse growth-selective survival, suggesting the growth-survival relationship is more complex than currently considered within the GSP framework. Stochastic simulations allowed us to assess the influence of key intrinsic and extrinsic factors on the characteristics of surviving larvae and identify knowledge gaps on the drivers of variability in growth-selective survival. We suggest caution when interpreting patterns of growth selection because changes in variance and autocorrelation of individual growth rates among cohorts can invalidate fundamental GSP assumptions. We argue that breakthroughs in recruitment research require a comprehensive, population-specific characterization of the role of predation and intrinsic factors in driving variability in the distribution and autocorrelation of larval growth rates, and of the life stage corresponding to the endpoint of pre-recruited life. -- Keywords : critical period ; growth-mortality ; individual characteristics ; larval physiology ; predation ; recruitment endpoint

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Designing Brain-Computer Interfaces for Attention-Aware Systems

Brain-computer interfaces (BCIs) hold great promise for improving information delivery and preserving user attention, but this promise has not yet translated to practical use. A prototype BCI that optimizes email notifications in noisy, complex environments, CARSON combines multiple measures from the brain to predict both cognitive workload and message relevancy to determine the optimum time to interrupt the user