Overwintering Habitat of American Dipper, Cinclus mexicanus, Observed in an Arctic Groundwater Spring Feeding on Dolly Varden, Salvelinus malma

Perennial groundwater springs along the Alaska and Yukon North Slope provide overwintering habitat for various organisms, including birds and fishes. We observed an American Dipper, Cinclus mexicanus, in the open water of a perennial spring situated in Fish Creek, Yukon, in Ivvavik National Park on 8 March 2018. The observation at Fish Creek was among the most northern documented sightings of an American Dipper during the winter in North America. Moreover, the observation was approximately 650 km farther north than where American Dippers have been documented overwintering in Yukon, making this the most northern Canadian observation documented for this species in any season. Additionally, the American Dipper was photographed feeding on a juvenile Dolly Varden, Salvelinus malma. Although American Dippers are known to feed on small fish, our observation was a novel documentation of a trophic interaction between both species during winter. The open-water habitat in Fish Creek, which is important for both species and has not been previously described, was short (~730 m long), shallow (mean = 20 cm deep), narrow (mean = 2.8 m wide), and cold (mean water temperature = 0.34ºC). While there is little information regarding the ecological interactions of American Dipper overwintering in the Arctic, we note that all observations in the North Slope area during winter occurred in river systems also used by Dolly Varden, which indicates that juvenile Dolly Varden could be an important source of food for American Dipper in winter.Les sources d’eau souterraine pérennes le long du versant nord de l’Alaska et du Yukon procurent un habitat d’hivernage à divers organismes, y compris les oiseaux et les poissons. Le 8 mars 2018, nous avons observé un cincle d’Amérique (Cinclus mexicanus) dans l’eau libre d’une source pérenne située au ruisseau Fish, dans le parc national Ivvavik, au Yukon. L’observation faite au ruisseau Fish figurait parmi les observations hivernales les plus nordiques du cincle d’Amérique à avoir été répertoriées en Amérique du Nord. Cette observation a été faite à environ 650 km plus au nord que l’endroit où l’habitat d’hivernage des cincles d’Amérique a été documenté au Yukon, ce qui représente l’observation la plus nordique au Canada à avoir été consignée pour cette espèce à n’importe quelle saison. Par surcroît, le cincle d’Amérique a été photographié en train de se nourrir d’un omble malma juvénile (Salvelinus malma). Bien que l’on sache que les cincles d’Amérique se nourrissent de petits poissons, l’observation que nous avons documentée constituait un nouveau cas d’interaction trophique entre les deux espèces pendant l’hiver. L’habitat en eau libre du ruisseau Fish, qui est important pour les deux espèces et n’a pas encore été décrit, était court (environ 730 m de long), peu profond (moyenne de 20 cm de profondeur), étroit (moyenne de 2,8 m de largeur) et froid (moyenne de la température de l’eau = 0,34 ºC). Bien qu’il existe peu d’information sur les interactions écologiques du cincle d’Amérique hivernant dans l’Arctique, notons qu’en hiver, toutes les observations faites dans la région du versant nord ont eu lieu dans des réseaux hydrographiques où vit également l’omble malma, ce qui laisse croire que l’omble malma juvénile pourrait représenter une source de nourriture importante pour le cincle d’Amérique en hiver

Multi-Modal Models for Fine-grained Action Segmentation in Situated Environments

Automated methods for analyzing human activities from video or sensor data are critical for enabling new applications in human-robot interaction, surgical data modeling, video summarization, and beyond. Despite decades of research in the fields of robotics and computer vision, current approaches are inadequate for modeling complex activities outside of constrained environments or without using heavily instrumented sensor suites. In this dissertation, I address the problem of fine-grained action segmentation by developing solutions that generalize from domain-specific to general-purpose for applications in surgical workflow, surveillance, and cooking. A key technical challenge, which is central to this dissertation, is how to capture complex temporal patterns from sensor data. For a given task, users may perform the same action at different speeds or styles, and each user may carry out actions in a different order. I present a series of temporal models that address these modes of variability. First, I define the notion of a convolutional action primitive, which captures how low-level sensor signals change as a function of the action a user is performing. Second, I generalize this idea to video with a Spatiotemporal Convolutional Neural Network, which captures relationships between objects in an image and how they change temporally. Lastly, I discuss a hierarchical variant that applies to video or sensor data, called a Temporal Convolutional Network (TCN), which models actions at multiple temporal scales. In certain domains (e.g., surgical training), TCNs can be used to successfully bridge the gap in performance between domain-specific and general-purpose solutions. A key scientific challenge concerns the evaluation of predicted action segmentations. In many applications, action labels may be ill-defined and if one asks two different annotators when a given action starts and stops they may give answers that are seconds apart. I argue that the standard action segmentation metrics are insufficient for evaluating real-world segmentation performance and propose two alternatives. Qualitatively, these metrics are better at capturing the efficacy of models in the described applications. I conclude with a case-study on surgical workflow analysis, which has the potential to improve surgical education and operating room efficiency. Current work almost exclusively relies on extensive instrumentation, which is difficult and costly to acquire. I show that our spatiotemporal video models are capable of capturing important surgical attributes (e.g., organs, tools) and achieve state-of-the-art performance on two challenging datasets. The models and methodology described have demonstrably improved the ability to temporally segment complex human activities, in many cases without sophisticated instrumentation

Reflow: Automatically Improving Touch Interactions in Mobile Applications through Pixel-based Refinements

Touch is the primary way that users interact with smartphones. However, building mobile user interfaces where touch interactions work well for all users is a difficult problem, because users have different abilities and preferences. We propose a system, Reflow, which automatically applies small, personalized UI adaptations, called refinements -- to mobile app screens to improve touch efficiency. Reflow uses a pixel-based strategy to work with existing applications, and improves touch efficiency while minimally disrupting the design intent of the original application. Our system optimizes a UI by (i) extracting its layout from its screenshot, (ii) refining its layout, and (iii) re-rendering the UI to reflect these modifications. We conducted a user study with 10 participants and a heuristic evaluation with 6 experts and found that applications optimized by Reflow led to, on average, 9% faster selection time with minimal layout disruption. The results demonstrate that Reflow's refinements useful UI adaptations to improve touch interactions

Latent Phrase Matching for Dysarthric Speech

Many consumer speech recognition systems are not tuned for people with speech disabilities, resulting in poor recognition and user experience, especially for severe speech differences. Recent studies have emphasized interest in personalized speech models from people with atypical speech patterns. We propose a query-by-example-based personalized phrase recognition system that is trained using small amounts of speech, is language agnostic, does not assume a traditional pronunciation lexicon, and generalizes well across speech difference severities. On an internal dataset collected from 32 people with dysarthria, this approach works regardless of severity and shows a 60% improvement in recall relative to a commercial speech recognition system. On the public EasyCall dataset of dysarthric speech, our approach improves accuracy by 30.5%. Performance degrades as the number of phrases increases, but consistently outperforms ASR systems when trained with 50 unique phrases

‘Learning to sing together’: developing a community of research practice through dialogue

This paper explores the processes involved when a group of academics within a small teaching-led institution set out to build a community of research practice. Through a narrative account that gives voice to each member of the group, the paper depicts the dialogic processes by which members of the group explored their current academic identities, in a search for new research identities. In establishing a community of research practice the group were able, through dialogue, to move away from hierarchical conceptions of ‘novice’ and ‘experienced researcher’ towards a ‘mutuality’ which set aside hierarchical power relations. In this way the authors add their collective voice to recent challenges to the dominant discourse of academic knowledge production. The paper concludes by arguing for the need to have such communities of research practice in order to facilitate the time and/or space for meaningful, transformative dialogue, at a time of increasing demands upon academic staff

Knowledge-driven stock trend prediction and explanation via temporal convolutional network

The authors would like to acknowledge that this work is funded by NSFC 61473260/91846204, national key research program YS2018YFB140004 as well as Natural Science Foundation of Zhejiang Province of China (LQ19F030001), and supported by Alibaba-Zhejiang University Joint Institute of Frontier Technologies.Publisher PD

The cytotoxic domain of colicin E9 is a channel-forming endonuclease

Bacterial toxins commonly translocate cytotoxic enzymes into cells using dedicated channelforming subunits or domains as conduits. We demonstrate that the small cytotoxic endonuclease domain from the bacterial toxin colicin E9 (the E9 DNase) exhibits nonvoltage- gated, channel-forming activity in planar lipid bilayers and that this activity is linked to toxin translocation into cells. A disulfide bond engineered into the DNase abolished channel activity and colicin toxicity but left endonuclease activity unaffected, with NMR experiments suggesting decreased conformational flexibility as the likely reason for these alterations. Concomitant with the reduction of the disulfide bond was the restoration of conformational flexibility, DNase channel activity and colicin toxicity. Our data suggest that endonuclease domains of colicins may mediate their own translocation across the bacterial inner membrane through an intrinsic channel activity that is dependent on structural plasticity in the protein

Following Lives Undergoing Change (Flux) study: Implementation and baseline prevalence of drug use in an online cohort study of gay and bisexual men in Australia

Background: Drug use among gay and bisexual men (GBM) is higher than most populations. The use of crystal methamphetamine, erectile dysfunction medication (EDM), and amyl nitrite have been associated with sexual risk behaviour and HIV infection among gay and bisexual men (GBM). Objective: This paper describes an online prospective observational study of licit and illicit drug use among GBM and explores baseline prevalence of drug use in this sample. Capturing these data poses challenges as participants are required to disclose potentially illegal behaviours in a geographically dispersed country. To address this issue, an entirely online and study specific methodology was chosen. Methods: Men living in Australia, aged 16.5 years of age or older, who identified as homosexual or bisexual or had sex with at least one man in the preceding 12 months were eligible to enrol. Results: Between September 2014 and July 2015, a total of 2250 participants completed the baseline questionnaire, of whom, 1710 (76.0%) consented to six-monthly follow-up. The majority (65.7%) were recruited through Facebook targeted advertising. At baseline, over half (50.5%) the men reported the use of any illicit drug in the previous six months, and 28.0% had used party drugs. In the six months prior to enrolment, 12.0% had used crystal methamphetamine, 21.8% had used EDM, and 32.1% had used amyl nitrite. Among the 1710 men enrolled into the cohort, 790 men had used none of these drugs. Conclusion: Ease of entry and minimal research burden on participants helped ensure successful recruitment into this online cohort study. Study outcomes will include the initiation and cessation of drug use, associated risk behaviours, and health consequences, over time. Results will provide insights into the role gay community plays in patterns of drug use among GBM