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With the rise of digital transformation in the pharmaceutical industry, digital therapeutics are being integrated in drug development clinical trials. In the TWINKLE study, information about asthmatic patients' disease control and quality-of-life (QoL) was measured by daily video recording, in conjunction with daily electronic questionnaires and home-based spirometry. From the video messages, sentiment and emotion AI was applied to detect subtle QoL changes in asthmatic patients after receiving treatments. Sentiment scores, derived from patients' daily messages via natural language processing, correlated strongly with metrics of lung functions and outcomes of electronic questionnaires. However, video-derived emotional analysis exhibited strong interpersonal variations and systematic biases, yet still showed utility in detecting QoL changes after personalized calibration and signal aggregation. Compared to traditional patient-reported outcomes, all three categories of digital measurements were able to detect significantly improved asthma control from patients who responded to treatments. The result provides insights into developing novel digital outcomes through the application of connected digital devices and advanced AI tailored to clinical settings.Clinical relevance- Digital outcomes involving connected digital devices and AI for sentiment/emotion analysis could capture subtle QoL changes reliably and earlier than hospital visits, reducing burden and improving disease management. Integrating digital therapeutics in asthma drug development trials may prove to be feasible and valuable.

For systems that require complete metallic enclosures, it is impossible to power and communicate with interior electronics using conventional electromagnetic techniques. Instead, pairs of ultrasonic transducers can be used to send and receive elastic waves through the enclosure, forming an equivalent electrical transmission line that bypasses the Faraday cage effect. These mechanical communication systems introduce the possibility for electromechanical crosstalk between channels on the same barrier, in which receivers output erroneous electrical signals due to ultrasonic guided waves generated by transmitters in adjacent communication channels. To minimize this crosstalk, this work investigates the use of a phononic crystal/metamaterial machined into the barrier via periodic grooving. Barriers with simultaneous ultrasonic power and data transfer are fabricated and tested to measure the effect of grooving on crosstalk between channels.

Landmark localisation in medical imaging has achieved great success using deep encoder-decoder style networks to regress heatmap images centered around the target landmarks. However, these networks are large and computationally expensive. Moreover, their clinical use often requires human interaction, opening the door for manual correction of low confidence predictions. We propose PHD-Net: a lightweight, multi-task Patch-based network combining Heatmap and Displacement regression. We design a simple Candidate Smoothing strategy to fuse its two-task outputs, generating the final prediction with quantified confidence. We evaluate PHD-Net on hundreds of Short Axis and Four Chamber cardiac MRIs, showing promising results.

Indoor asset tracking is an essential task in many areas of industry such as shipping and warehousing. Widely-used asset tracking technologies typically require supporting infrastructure (signal transponders) to communicate with active tags on the assets. Continuous asset tracking in large indoor spaces like warehouses can be costly, and reliable reference points are needed to calculate asset positions accurately. In this paper, we describe an indoor asset tracking technique for augmented reality (AR) that combines the use of (passive) fiducial markers together with flexible spatial anchors. Our approach, called SABIAT, continuously tracks the approximate location of an asset using spatial anchors and, when needed, the precise location of that asset using fiducial markers. We have applied our SABIAT technique to build a demonstrator system, AR-IPS, to show how assets can be tracked and located inside of a large, multi-level building.

Live coding is an artistic performance practice where computer music and graphics are created, displayed and manipulated in front of a live audience together with projections of the (predominantly text based) computer code. Although the pressures of such performance practices are considerable, until now only familiar programming aids (for example syntax highlighting and textual overlays) have been used to assist live coders. In this paper we integrate an intelligent agent into a live coding system and examine how that agent performed in two contrasting modes of operation—as a recommender, where on request the the agent would generate (but not execute) domain-appropriate code transformations in the performer’s text editor, and as a disruptor, where the agent generated and immediately executed changes to the code and the streaming music being performed. A within-subjects study of six live coders suggested that participants of the study preferred the agent’s disruptive mode as a mechanism for enhancing the creativity of their live coding performances.

In this paper, we share our experiences with a Trans-Pacific, collaborative mixed-reality (MR) based plant walk tour involving three geographical locations: (i) Dallas, Texas; (ii) Denver, Colorado; and (iii) Yokohama, Japan. The Wide Area Network (WAN) from Japan to Denver and from Denver to Dallas was through 100 Gbps optical links. These links were a mixture of leased and dedicated infrastructure. The average observed latency was around 131 ms and the maximum available bandwidth was 26.6 Gbps. The tour developed using a component-based framework, provided group travel with a leader-follower criterion involving a semi-active travel technique. By applying a “modified Virtual Reality” (mVR) triangle paradigm, we examined the user experience of this collaborative tour. We considered Visualization, Synchronization, and Exploration design choices as the three key aspects of the mVR triangle. We assessed the user experience of the tour through a Gibbs triangle, with each of the composition of the Gibbs triangle being a key aspect of the mVR triangle. We obtained users’ scores on the three aspects of the mVR using a seven-point, Likert scale questionnaire. We conducted 14 sessions of group travel. Overall, we found the user experience of the trans-pacific plant walk tour to be in the Balanced Experience Region (BER) region or the center part of the Gibbs triangle, which conveys that the majority of the participants experienced a balanced influence of mVR aspects throughout the tour.

The increase in data generation and the decrease in the cost of storage increases the need for intelligent data management. One avenue that would allow storage systems to manage data better is to feed it with an accurate prediction of how many disk operations are expected on that data. In this paper, we introduce a method to predict the data heat in a storage system. Our method is derived from two insights. The first is that we can use a set of quick to compute signals which constrain the set of possible future heat patterns. The underlying assumption in this is that the signals provide a description of the access pattern and the requests that have similar signals have a similar set of future behavior. The second is that the storage requests can be partitioned into groups based on their signal. Our method generates a unique prediction model for each group from the corresponding heat patterns. This makes the model generation process easier and more precise. The results of our method on public datasets show that it is a viable way to predict heat. Our method is able to accurately almost all inactive regions and provides useful predictions for active regions.

We demonstrate a prototype cross-linked small-sat communication system at 4 GHz. A single prototype satellite consists of a reflecting spherical surface and transceiver system. The spherical antenna is built from a Zorb balloon in which a metal adhesive vinyl is applied to create a reflecting antenna along with two oppositely polarized linear grids for communication cross-linking. The transceiver system uses a phased array line feed that corrects the focus of the spherical antenna and provides electronic steerability. The electronics including the transceivers and phase shifters are contained in a box approximately the size of a 2U form factor making this design suitable for deployment in a CubeSat. We present s-parameter measurements from the phased array line feeds and using a second prototype we demonstrate cross-linked communications through measured line spectra at 4 GHz. This design is easily scalable to higher frequencies for large bandwidth communications.

The severity of the glaucoma eye disease is usually measured by the Advanced Glaucoma Intervention Studies (AGIS) metric. The metric provides a value between zero and twenty inclusive, where the former represents no evidence of glaucoma and the latter the most advanced of measurements. In a previous study by Montolio et al., the season in which the test was undertaken was shown to affect the value of eye measurements; the lowest sensitivity was found in Summer and the highest sensitivity found in Winter and Spring. In this paper, we partially replicate that study with a different set of data from 2468 patients obtained from Moorfields Eye Hospital, London. We decomposed the data according to the four seasonal dates to determine if extra sensitivity meant that patients' results improved in Winter.

There is a great deal of debate over the importance of explanation in AI models inferred from health data. In particular, there is a balance that needs to be made between the accuracy of complex 'deep' models such as convolutional neural networks and the transparency of models that aim to model data in a more 'human' way such as expert systems. In this paper, we explore the use of temporal association rules to validate and uncover the meaning behind discrete hidden variables that have been inferred from clinical diabetes data. We use a recently published technique based upon the IC* (Induction Causation) algorithm that limits the number of hidden variables and places them within a network structure. Here, we take the hidden variables and compare their underlying discrete states to clusters that have been generated from temporal association rules. This allows us to characterise the hidden states based upon different sequences of complications. Results are very promising, with many hidden states aligning with the discovered clusters giving us a direct interpretation.

Phasor Measurement Unit (PMU) design and application requires knowledge of various mathematical and electrical engineering fundamentals. The fundamental theories are covered in lower level courses offered at the undergraduate level in a typical electrical engineering and energy related curriculum. Furthermore, laboratory equipment/device based courses help students to improve their practical skills. Since students find experimental, product development and group work related courses more engaging, they are motivated to enroll in such courses. This paper summarizes a PMU design and application course suitable for electrical engineering/renewable energy undergraduate and graduate students. The paper is aimed towards helping course developers who plan to develop similar courses in the future.

The US Department of Energy Advanced Research Projects Agency - Energy (ARPA-E) MacroAlgae Research Inspiring Novel Energy Research (MARINER) program is encouraging technologies for the sustainable harvest of large funding research of macroalgae for biofuels at less than $80 per dry metric ton (DMT). The Ocean Forests team, led by the University of Southern Mississippi, is developing a complete managed ecosystem where nutrients are transformed and recycled. The team's designs address major bottlenecks in profitability of offshore aquaculture systems including economical moored structures that can withstand storms, efficient planting, managing and harvesting systems, and sustainable nutrient supply. The work is inspired by Lapointe [1] who reported yields of Gracilaria tikvahiae equivalent to 127 DMT per hectare per year (compared with standard aquaculture systems in the range of 20 to 40 DMT/ha/yr). This approach offers the potential for breakthrough yields for many macroalgae species. Moreover, mini-ecosystems in offshore waters create communities of macroalgae, shellfish, and penned finfish, supplemented by visiting free-range fish that can increase productivity, produce quality products, and create jobs and income for aquafarmers. Additional benefits include reduced disease in fish pens, cleaning contaminated coastal waters, and maximizing nutrient recycling. Cost projections for a successful, intensive, scaled system are competitive with current prices for fossil fuels.

This paper describes the “SeaweedPaddock” system to profitably grow and harvest open-ocean Sargassum sp. as a sustainable source of macroalgal biomass and biofuel. The US Department of Energy Advanced Research Projects Agency - Energy (ARPA-E) initiated the MacroAlgae Research Inspiring Novel Energy Research (MARINER) program to develop technologies to eventually sustainably harvest macroalgae at 80 per dry metric ton (DMT). The University of Southern Mississippi team is characterizing an unmoored SeaweedPaddock; analyses include tow speed and energy required to avoid hazards, farm design to minimize biomass loss, economical harvesting, and nutrient supply. Initial results indicate that nighttime “smart towing” could allow the SeaweedPaddock system to produce macroalgae at full scale at costs below the ARPA-E goal provided that Sargassum grows at sufficient rates during the day after having been confined all night in a moving fence and that sufficient nutrients are made available. Cost projections for a successful, intensive, scaled system could be competitive with current prices for fossil fuels.

Brain-computer interfaces (BCIs) have been employed in rehabilitation training for post-stroke patients. In this study, we present the results of the intervention based on BCI triggered functional electrical stimulation (FES) and avatar mirroring. Seven chronic stroke patients participated in 25 sessions of training over 13 weeks. Seven assessments were conducted to observe any behavioral changes before and after the intervention. The primary outcome measure, i.e. the Fugl-Meyer Assessment of the Upper Extremity (FMA-UE), increased significantly by 6.4 points (p=0.048), which is above the minimal clinically important difference (MCID). The Modified Ashworth Scale (MAS), one of the secondary outcome measures, reduced significantly in both the wrist and the finger (p=0.046 and p=0.047 respectively). This study demonstrated motor function improvement and spasticity reduction in chronic stroke patients (n=7) after BCI triggered FES and avatar mirroring. One limitation of this study is that the small sample size may not adequately represent the diverse stroke population. Further work should include a randomized controlled trial to investigate the effectiveness of BCI triggered FES compared to conventional therapies.

In a previous empirical study by Bavota et al., multiple releases of three open-source systems reported the extent to which refactorings induced defect-fixes. In a much earlier study, van Deursen and Moonen (vD&M) provided a test taxonomy in which Fowler's seventy-two refactorings were categorized according to the post refactoring test burden of each (i.e., the changes required to unit tests after each refactoring had been undertaken). A refactoring was categorized as 'Type B' if it required no change to the original tests and 'Type E' if significant changes were necessary. In this paper, we investigate nine refactorings spread across vD&M's taxonomy and the corresponding defect-fix data provided by Bavota et al., to explore the relationship between defect-fixes due to refactoring and vD&M's taxonomy. Results showed that, in contrast to our intuition, the most defect-fix prone refactorings were of Types C and D and not, as we thought, of Type E. The 'Extract method' refactoring stood out as particularly 'defect-fix' inducing, suggesting that while it may solve one problem (i.e., in decomposing an excessively long method), it may well introduce other problems and required defect-fixes as a by-product.

Recent proton and heavy ion SEE data are presented for selected Virtex-7 architectural features requiring dynamic in-beam testing: I/O blocks in various modes, IOSERDES, digital- and phase-locked loop clocks, and block memory’s error correction circuitry.

Small spot size laser testing for single-event effects has proven to be a particularly productive path to insights on the physics of charge collection and circuit response that are difficult or impossible to obtain through broad ion beam tests. As a result, there are a number of such laser facilities; for example, four of them were compared in 2012 [1], but a relatively new facility at the facility at the University of Saskatchewan offers a unique galvo-mirror, laser-spot scanning capability in addition to the usual micrometer-based DUT motion stage [2]. Operating in a fashion similar to LASIX eye surgery, fast pin-point redirection of the laser beam makes tractable (seconds, not hours or days) comprehensive scanning of a millimeter size field-of-view. Combined with auto-stepping the field-of-view, this new spot scanning capability opens up the possibility of comprehensively covering a large die and finding all SEE sites, including the rare, but important, ones such as SEFIs.

We present a pilot study of a socially assistive robot interacting with intergenerational groups. The system is designed to improve the social well-being of older adults by supporting interactions within families. Six intergenerational family groups interacted with the robot in four tablet-based games. Users' behavior during the sessions was used to compare the games and understand how members of different generations and different families interact with the robot. Interviews with users provide insight into users' priorities for in-home deployment of socially assistive robots, as well as preferences about the activities, appearance, and behavior of the robot.

Electrical cortical stimulation (ECS) is often used in presurgical evaluation procedures for patients suffering from pharmacoresistant epilepsy. Real-time functional mapping (RTFM) is an alternative brain mapping methodology that can accompany traditional functional mapping approaches like ECS. In this paper, we present a combined RTFM/ECS system that aims to exploit the common ground and the advantages of the two procedures for improved time/effort effectiveness, patients' experience and safety. Using the RTFM and ECS data from four patients who suffer epilepsy, we demonstrate that the RTFM-guided ECS procedure hypothetically reduces the number of electrical stimulations necessary for eloquent cortex detection by 40%.

Gary M. Swift has spent the last twenty-five plus years going to accelerators and testing electrical components for their suitability for use in space radiation environments. Gary received a B.S. in Engineering Physics from the University of Oklahoma in 1975 and did graduate work in Nuclear Engineering at the University of Illinois at Urbana-Champaign. After almost two decades at NASA's Jet Propulsion Laboratory in Pasadena, he “retired” as a principal engineer in 2007, and moved to Xilinx, Inc. to help develop and test their space-worthy FPGAs. Currently, Gary is the Principal Engineer at the independent consulting firm Swift Engineering and Radiation Services, LLC which he founded, specializing in best-practice SEE testing of complex ICs such as FPGAs and microprocessors. He has publications on a broad range of radiation effects testing including total dose and displacement damage and many single-event effects; for example, in 1992, he coined the now widely used term SEFI. He is co-author on two paper papers that received the NSREC Outstanding Paper Award (in 1999 and 2015). Back in 2001, Gary, then at JPL, and Carl Carmichael of Xilinx started the Xilinx Radiation Test Consortium, a voluntary group of national labs, universities and aerospace companies that collaborate on SEE testing, and he has served as the XRTC main test coordinator and weekly telecom moderator to the present day.

In medical practice, glaucoma severity is usually measured using the Advanced Glaucoma Intervention Studies (AGIS) metric. In a previous study [2], we replicated the work of Montolio et al., [5] and demonstrated that, for a larger dataset, time of day of test using the AGIS metric did make a difference to the measurement of glaucoma, supporting Montolio et als work. However, in our earlier study, we used the AGIS scores for both eyes combined. In this paper, we use the measurement from just one eye at a time. A dataset of 14389 left eye AGIS scores and the same number for the right eye from 2468 Moorfield Eye Hospital patients was used as the empirical basis. We then re-compared time of test results with those of Montolios study. Results revealed that using the values from just one eye (as opposed to both) may give a distorted picture of the AGIS scores; differences in the same time period were found between the two eyes. This may have implications for choice of sampling data and analysis of glaucoma using the AGIS metric.