Decay of high-energy electron bound states in crystals

High-energy electrons that are used as a probe of specimens in transmission electron microscopy exhibit a complex and rich behavior due to multiple scattering. Among other things, understanding the dynamical effects is needed for a quantitative analysis of atomic-resolution images and spectroscopic data. In this study, state-correlation functions are computed within the multislice approach that allow to elucidate behaviors of transversely bound states in crystals. These states play an important role as a large fraction of current density can be coupled into them via focused electron probes. We show that bound states are generically unstable and decay monoexponentially with crystal depth. Their attenuation is accompanied by a resonant intensity transfer to Bessel-like wavefunctions that appear as Laue rings in the far-field diffraction patterns. Behaviors of bound states are also quantified when thermal effects are included, as well as point defects. This approach helps to bridge the Bloch wave and multisliced electron propagation pictures of dynamical scattering providing new insights into fundamental solutions of the wave equation, and may assist in developing quantitative STEM/TEM imaging techniques

Brevia and Demonstrations Presentations-- Proceedings –

Context is of crucial importance for research and applications in many disciplines, as evidenced by many workshops, symposia, seminars, and conferences on specific aspects of context. � The International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT), the oldest conference series focusing on context, provides a unique interdisciplinary emphasis, bringing together participants from a wide range of disciplines, including artificial intelligence, cognitive science, computer science, linguistics, organizational science, philosophy, psychology, ubiquitous computing, and application areas such as medicine and law, to discuss and report on context-related research and projects. Previous CONTEXT conferences have been held in Rio de Janeiro, Brazil (1997)

Personal Privacy through Understanding and Action: Five Pitfalls for Designers

To participate in meaningful privacy practice in the context of technical systems, people require opportunities to understand the extent of the systems' alignment with relevant practice and to conduct discernible social action through intuitive or sensible engagement with the system. It is a significant challenge to design for such understanding and action through the feedback and control mechanisms of today's devices. To help designers meet this challenge, we describe five pitfalls to beware when designing interactive systems---on or off the desktop---with personal privacy implications. These pitfalls are: obscuring potential information flow, obscuring actual information flow, emphasizing configuration over action, lacking coarse-grained control, and inhibiting existing practice. They are based on a review of the literature, on analyses of existing privacy-affecting systems, and on our own experiences designing a prototypical user interface for managing privacy in ubiquitous computing. We illustrate how some existing research and commercial systems---our prototype included---fall into these pitfalls and how some avoid them. We suggest that privacy-affecting systems that heed these pitfalls can help users appropriate and engage them in alignment with relevant privacy practice

Personal Privacy through Understanding and Action: Five Pitfalls for Designers

To participate in meaningful privacy practice in the context of technical systems, people require opportunities to understand the extent of the systems’ alignment with relevant practice and to conduct discernible social action through intuitive or sensible engagement with the system. It is a significant challenge to design for such understanding and action through the feedback and control mechanisms of today’s devices. To help designers meet this challenge, we describe five pitfalls to beware when designing interactive systems—on or off the desktop—with personal privacy implications. These pitfalls are: obscuring potential information flow, obscuring actual information flow, emphasizing configuration over action, lacking coarse-grained control, and inhibiting existing practice. They are based on a review of the literature, on analyses of existing privacy-affecting systems, and on our own experiences designing a prototypical user interface for managing privacy in ubiquitous computing. We illustrate how some existing research and commercial systems—our prototype included—fall into these pitfalls and how some avoid them. We suggest that privacy-affecting systems that heed these pitfalls can help users appropriate and engage them in alignment with relevant privacy practice

Senbay:a platform for instantly capturing, integrating, and restreaming of synchronized multiple sensor-data stream

Abstract The spread of smartphones allows us to freely capture video and diverse hardware sensors’ data (e.g., accel erometer, gyroscope). While recording such data is relatively simple, it is often challenging to share and restream this data to other people and applications. Such capability is very valuable for a range of applications such as a context-aware prototyping/developing platform, an integrated data recording and analysis tool, and a sensor-data based video editing system. To enable such complex operations, we propose Senbay, a platform for instant sensing, integrating, and restreaming multiple-sensor data streams. The platform embeds collected sensor data into a video frame using an animated two-dimensional barcode via real-time video processing. The video-embedded sensor data, dubbed Senbay Video, can be easily restreamed to other people and reused by data rich, context-aware applications

Estimation of symptom severity during chemotherapy from passively sensed data:exploratory study

Abstract Background: Physical and psychological symptoms are common during chemotherapy in cancer patients, and real-time monitoring of these symptoms can improve patient outcomes. Sensors embedded in mobile phones and wearable activity trackers could be potentially useful in monitoring symptoms passively, with minimal patient burden. Objective: The aim of this study was to explore whether passively sensed mobile phone and Fitbit data could be used to estimate daily symptom burden during chemotherapy. Methods: A total of 14 patients undergoing chemotherapy for gastrointestinal cancer participated in the 4-week study. Participants carried an Android phone and wore a Fitbit device for the duration of the study and also completed daily severity ratings of 12 common symptoms. Symptom severity ratings were summed to create a total symptom burden score for each day, and ratings were centered on individual patient means and categorized into low, average, and high symptom burden days. Day-level features were extracted from raw mobile phone sensor and Fitbit data and included features reflecting mobility and activity, sleep, phone usage (eg, duration of interaction with phone and apps), and communication (eg, number of incoming and outgoing calls and messages). We used a rotation random forests classifier with cross-validation and resampling with replacement to evaluate population and individual model performance and correlation-based feature subset selection to select nonredundant features with the best predictive ability. Results: Across 295 days of data with both symptom and sensor data, a number of mobile phone and Fitbit features were correlated with patient-reported symptom burden scores. We achieved an accuracy of 88.1% for our population model. The subset of features with the best accuracy included sedentary behavior as the most frequent activity, fewer minutes in light physical activity, less variable and average acceleration of the phone, and longer screen-on time and interactions with apps on the phone. Mobile phone features had better predictive ability than Fitbit features. Accuracy of individual models ranged from 78.1% to 100% (mean 88.4%), and subsets of relevant features varied across participants. Conclusions: Passive sensor data, including mobile phone accelerometer and usage and Fitbit-assessed activity and sleep, were related to daily symptom burden during chemotherapy. These findings highlight opportunities for long-term monitoring of cancer patients during chemotherapy with minimal patient burden as well as real-time adaptive interventions aimed at early management of worsening or severe symptoms

Challenges of Parkinson’s disease:user experiences with STOP

Abstract Parkinson’s disease (PD) is the second most common neurodegenerative disorder, impacting an estimated seven to ten million people worldwide. Measuring the symptoms and progress of the disease, and medication effectiveness is currently performed using subjective measures and visual estimation. We developed and evaluated a mobile application, STOP for tracking hand’s motor symptoms, and a medication journal for recording medication intake. We followed 13 PD patients from two countries for a 1-month long real-world deployment. We found that PD patients are willing to use digital tools, such as STOP, to track their medication intake and symptoms, and are also willing to share such data with their caregivers and medical personnel to improve their own care