Reference and Gestures in Dialogue Generation: Three Studies with Embodied Conversational Agents

This paper reports on three studies into social presence cues which were carried out in the context of the NECA (Net-environment for Embodied Emotional Conversational Agents) project and the EPOCH network. The first study concerns the generation of referring expressions. We adopted an existing algorithm for generating referring expressions such that it could run according to an egocentric and a neutral strategy. In an evaluation study, we found that the two strategies were correlated with the perceived friendliness of the speaker. In the second and the third study, we evaluated the gestures that were generated by the NECA system. In this paper, we briefly summarize the most salient results of these two studies. They concern the effect of gestures on perceived quality of speech and information retention

Towards operational sea ice type retrieval using L-band Synthetic aperture radar

Source at https://doi.org/10.1109/IGARSS.2019.8900458.Operational ice services around the world have recognized the economic and environmental benefits that come from the increased capabilities and uses of space-borne Synthetic Aperture Radar (SAR) observation system. The two major objectives in SAR based remote sensing of sea ice is on the one hand to have a large areal coverage, and on the other hand to obtain a radar response that carries as much information as possible. Although until now, L-Band SAR sensors are rarely used in an operational context, it offers greater capabilities for sea ice type retrieval and is more robust during the melt season compared to higher frequency bands. With the help of JAXA’s ALOS-2 PALSAR-2 sensor, we are able to explore the potential of polarimetric L-band acquisitions for sea ice analysis and classification in an operational environment. In this study we investigated the incidence angle related variation on the L-band backscatter and recommended optimal scenarios for Artificial Neural Network based sea ice type retrieval schemes

The Clinical Ultrasonography Elective in Clerkship (CUSEC): A pilot elective for senior clerkship students at the University of Saskatchewan

We created a clinical ultrasound (CUS) elective in clerkship, which gave medical students the opportunity to enhance their knowledge and technical skills while refining their CUS-related clinical decision making. This elective uniquely allowed medical students to integrate their CUS knowledge and skills into real patient care within the clinical environment (discipline) of their choice. As such, beyond supporting increasing technical competence, students learned to advocate for appropriate use of CUS, an important skill for trainees to develop.&nbsp

Spatial variability of snow chemistry in western Dronning Maud Land, Antarctica

During the austral summer of 1993-94 a number of 1-2 m deep snow pits were sampled in connection with firn-coring in western Dronning Maud Land, Antarctica. The traverse went from 800 to about 3000 m a.s.l. upon the high-altitude plateau. Profiles of cations (Na+, K+, Mg2+, Ca2+), anions (Cl−, NO3-, SO4 2- , CH3SO3 −) and stable oxygen isotopes (δ18O) from 11 snow pils are presented here. Close to the coast 2 m of snow accumulates in about 2-3 years, whilst at sites on the high-altitude plateau 2 m of snow accumulates in 10—14 years. The spatial variation in ion concentrations shows that the ions can be divided into two groups, one with sea-salt elements and methane sulfonate and the other with nitrate and sulfate. For the sca-salt elements and methane sulfonate the concentrations decrease with increasing altitude and increasing distance from the coast, as well as with decreasing temperature and decreasing accumulation rate. For nitrate and sulfate the concentrations are constant or increase with respect to these parameters. This pattern suggests that the sources for sca-salt elements and methane sulfonate are local, whereas the sources for nitrate and sulfate are a mixture of local and long-range transport

Automatic Detection of Low-Backscatter Targets in the Arctic Using Wide Swath Sentinel-1 Imagery

Low backscatter signatures in synthetic aperture radar (SAR) imagery are characteristic to surfaces that are highly smooth and specular reflective of microwave radiation. In the Arctic, these typically represent newly formed sea ice, oil spills, and localized weather phenomena such as low wind or rain cells. The operational monitoring of low backscatter targets can benefit from a stronger integration of freely available SAR imagery from Sentinel-1. We, therefore, propose a detection method applicable to Sentinel-1 extra wide-swath (EW) SAR scenes. Using intensity values coupled with incidence angle and noise-equivalent sigma zero (NESZ) information, the image segmentation method is able to detect the low backscatter targets as one segment across subswaths. We use the Barents Sea as a test site due to the abundant presence of low backscatter targets with different origins, and of long-term operational monitoring services that help cross-validate our observations. Utilizing a large set of scenes acquired in the Barents Sea during the freezing season (November–April), we demonstrate the potential of performing large-scale operational monitoring of local phenomena with low backscatter signatures

Oxford unicompartmental knee arthroplasty: medial pain and functional outcome in the medium term

<p>Abstract</p> <p>Background</p> <p>In our experience results of the Oxford unicompartmental knee replacement have not been as good as had been expected. A common post operative complaint is of persistent medial knee discomfort, it is not clear why this phenomenon occurs and we have attempted to address this in our study.</p> <p>Methods</p> <p>48 patients were retrospectively identified at a mean of 4.5 years (range = 3 to 6 years) following consecutive Oxford medial Unicompartmental Knee arthroplasties for varus anteromedial osteoarthritis. The mean age at implantation was 67 years (range 57-86). Of these 48 patients, 4 had died, 4 had undergone revision of their unicompartmental knee replacements and 2 had been lost to follow up leaving 38 patients with 40 replaced knees available for analysis using the 'new Oxford Knee Score' questionnaire. During assessment patients were asked specifically whether or not they still experienced medial knee discomfort or pain.</p> <p>Results</p> <p>The mean 'Oxford score' was only 32.7 (range = 16 to 48) and 22 of the 40 knees were uncomfortable or painful medially.</p> <p>The accuracy of component positioning was recorded, using standard post operative xrays, by summing the angulation or displacement of each component in two planes from the ideal position (according to the 'Oxford knee system radiographic criteria'). No correlation was demonstrated between the radiographic scores and the 'Oxford scores', or with the presence or absence of medial knee discomfort or pain.</p> <p>Conclusion</p> <p>In our hands the functional outcome following Oxford Unicompartmental knee replacement was variable, with a high incidence of medial knee discomfort which did not correlate with the postoperative radiographic scores, pre-op arthritis and positioning of the prosthesis.</p

A multicenter randomized controlled clinical pilot study of buccally micro‐veneered lithium‐disilicate and zirconia crowns supported by titanium base abutments: 1‐year outcomes

Objectives: To investigate survival rates, technical and biologic outcomes of buccally micro-veneered all-ceramic single implant crowns. Material and methods: Sixty subjects randomly received immediately or early placed implants. Crowns out of lithium-disilicate (n = 30) and zirconia-ceramic (n = 30) were bonded to titanium-base-abutments. Restorations were inspected at baseline (BL) and during follow-up visits (6, 12 months). Technical and biologic parameters were recorded. Data were analysed descriptively. Differences between groups were tested with Student's t-test. Paired T-test was used when comparing data from the same implant or tooth over time. Linear model repeated measures were used to test differences between materials over time. Differences in counts were evaluated using Pearson Chi-square test. The level of significance was at p < .05. Results: After a mean observation time of 13.2 ± 2.4 months, 54 restorations were re-examined. The implant survival rate was 98.3%, and the restoration survival rate was 100%. One early implant failure occurred. Two minor chippings occurred in lithium-disilicate restorations. No chippings or fractures occurred in any zirconia restorations at 1 year (0%). The technical complication rate was 3.7%, with 7.7% complications among the lithium-disilicate restorations and no differences between the two materials (p = .558). At 1-year follow-up, mean Bleeding on Probing (BOP) was higher at implants (0.27 ± 0.3) than adjacent teeth (0.17 ± 0.18) (p = .046) with no differences between materials (p = .36). Differences in pocket probing depth (PPD) between implants and adjacent teeth were significant (p < .01). Jemt Index improved significantly from BL to 1-y-follow-up (p < .001). Conclusions: Preliminary results were good, suggesting that the ceramic type does not impact technical and biologic parameters. Keywords: all-ceramic single crowns; chipping; clinical trials; implant-borne reconstructions; technical outcome

Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture

We provide sea ice classification maps of a subweekly time series of single (horizontal–horizontal, HH) polarization X-band TerraSAR-X scanning synthetic aperture radar (TSX SC) images from November 2019 to March 2020, covering the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This classified time series benefits from the wide spatial coverage and relatively high spatial resolution of TSX SC data and is a useful basic dataset for future MOSAiC studies on physical sea ice processes and ocean and climate modeling. Sea ice is classified into leads, young ice with different backscatter intensities, and first-year ice (FYI) or multiyear ice (MYI) with different degrees of deformation. We establish the per-class incidence angle (IA) dependencies of TSX SC intensities and gray-level co-occurrence matrix (GLCM) textures and use a classifier that corrects for the class-specific decreasing backscatter with increasing IAs, with both HH intensities and textures as input features. Optimal parameters for texture calculation are derived to achieve good class separation while maintaining maximum spatial detail and minimizing textural collinearity. Class probabilities yielded by the classifier are adjusted by Markov random field contextual smoothing to produce classification results. The texture-based classification process yields an average overall accuracy of 83.70 % and good correspondence to geometric ice surface roughness derived from in situ ice thickness measurements (correspondence consistently close to or higher than 80 %). A positive logarithmic relationship is found between geometric ice surface roughness and TSX SC HH backscatter intensity, similar to previous C- and L-band studies. Areal fractions of classes representing ice openings (leads and young ice) show prominent increases in middle to late November 2019 and March 2020, corresponding well to ice-opening time series derived from in situ data in this study and those derived from satellite synthetic aperture radar (SAR) and optical data in other MOSAiC studies

How are excellence and trust for using artificial intelligence ensured? Evaluation of its current use in EU healthcare

Context: Artificial intelligence (AI) could be a key driver in different healthcare dossiers, ranging from preventive to diagnostic and treatment purposes. The establishment of the Artificial Intelligence High-Level Expert Group in the European Commission, as well as their White Paper, show first attempts of creating policies in the domain of artificial intelligence in the EU. Despite these policy approaches, there is a need for a coherent regulatory framework that enables the efficient use of AI in the field of health. The aim of this policy brief is to evaluate current legislative gaps in terms of the introduction of AI in healthcare, focusing on the domains of Data Protection, Liability &amp; Transparency, as well as Robustness &amp; Accuracy. Policy Options: This policy brief identified a high degree of eHealth infrastructure fragmentation on member state level and limited action towards a structured and coherent framework for AI in healthcare, under the domains of Data Protection, Liability &amp; Transparency, and Robustness &amp; Accuracy. Recommendations: A unified approach at EU-level, based on proposed recommendations and merged into the form of a Directive, is advised. The development of the Health-AI-Directive will bring progress and improvement to legal certainty in the European AI-landscape. The introduction of the Health-AI-Directive is recommended to ensure trust and excellence in the use of AI in healthcare. &nbsp; Acknowledgments: The authors of this policy brief would like to thank all our tutors, lecturers and professors of the M.Sc. Governance and Leadership in European Public Health, with special thanks to Kasia Czabanowska and Rok Hržič, for enabling and encouraging us in the creation of this policy brief. Authors’ contributions: All authors contributed equally to this work &nbsp; Conflict of interest: None declared &nbsp; Source of funding: None declare

How are excellence and trust for using artificial intelligence ensured? Evaluation of its current use in EU healthcare

Context:&nbsp;Artificial intelligence (AI) could be a key driver in different healthcare dossiers, ranging from preventive to diagnostic and treatment purposes. The establishment of the Artificial Intelligence High-Level Expert Group in the European Commission, as well as their White Paper, show first attempts of creating policies in the domain of artificial intelligence in the EU. Despite these policy approaches, there is a need for a coherent regulatory framework that enables the efficient use of AI in the field of health. The aim of this policy brief is to evaluate current legislative gaps in terms of the introduction of AI in healthcare, focusing on the domains of Data Protection, Liability &amp; Transparency, as well as Robustness &amp; Accuracy. Policy Options:&nbsp;This policy brief identified a high degree of eHealth infrastructure fragmentation on member state level and limited action towards a structured and coherent framework for AI in healthcare, under the domains of Data Protection, Liability &amp; Transparency, and Robustness &amp; Accuracy. Recommendations:&nbsp;A unified approach at EU-level, based on proposed recommendations and merged into the form of a Directive, is advised. The development of the Health-AI-Directive will bring progress and improvement to legal certainty in the European AI-landscape. The introduction of the Health-AI-Directive is recommended to ensure trust and excellence in the use of AI in healthcare