| 1. |
- Vigorito, Elena, et al.
(författare)
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Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers
- 2016
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:7
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Tidskriftsartikel (refereegranskat)abstract
- Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95% CI: 0.68 to 0.79, p-value 2x 10-16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95% CI: 0.59 to 0.80, p-value 1.0 x 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.
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| 2. |
- Alomari, Muhannad, et al.
(författare)
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Grounding of human environments and activities for autonomous robots
- 2017
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Ingår i: Proceedings Of The Twenty-Sixth International Joint Conference On Artificial Intelligence. - California : International Joint Conferences on Artificial Intelligence. ; , s. 1395-1402
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Konferensbidrag (refereegranskat)abstract
- With the recent proliferation of human-oriented robotic applications in domestic and industrial scenarios, it is vital for robots to continually learn about their environments and about the humans they share their environments with. In this paper, we present a novel, online, incremental framework for unsupervised symbol grounding in real-world, human environments for autonomous robots. We demonstrate the flexibility of the framework by learning about colours, people names, usable objects and simple human activities, integrating stateofthe-art object segmentation, pose estimation, activity analysis along with a number of sensory input encodings into a continual learning framework. Natural language is grounded to the learned concepts, enabling the robot to communicate in a human-understandable way. We show, using a challenging real-world dataset of human activities as perceived by a mobile robot, that our framework is able to extract useful concepts, ground natural language descriptions to them, and, as a proof-ofconcept, generate simple sentences from templates to describe people and the activities they are engaged in.
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| 3. |
- Bleser, Gabriele, et al.
(författare)
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Cognitive Learning, Monitoring and Assistance of Industrial Workflows Using Egocentric Sensor Networks
- 2015
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:6
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Tidskriftsartikel (refereegranskat)abstract
- Today, the workflows that are involved in industrial assembly and production activities are becoming increasingly complex. To efficiently and safely perform these workflows is demanding on the workers, in particular when it comes to infrequent or repetitive tasks. This burden on the workers can be eased by introducing smart assistance systems. This article presents a scalable concept and an integrated system demonstrator designed for this purpose. The basic idea is to learn workflows from observing multiple expert operators and then transfer the learnt workflow models to novice users. Being entirely learning-based, the proposed system can be applied to various tasks and domains. The above idea has been realized in a prototype, which combines components pushing the state of the art of hardware and software designed with interoperability in mind. The emphasis of this article is on the algorithms developed for the prototype: 1) fusion of inertial and visual sensor information from an on-body sensor network (BSN) to robustly track the user’s pose in magnetically polluted environments; 2) learning-based computer vision algorithms to map the workspace, localize the sensor with respect to the workspace and capture objects, even as they are carried; 3) domain-independent and robust workflow recovery and monitoring algorithms based on spatiotemporal pairwise relations deduced from object and user movement with respect to the scene; and 4) context-sensitive augmented reality (AR) user feedback using a head-mounted display (HMD). A distinguishing key feature of the developed algorithms is that they all operate solely on data from the on-body sensor network and that no external instrumentation is needed. The feasibility of the chosen approach for the complete action-perception-feedback loop is demonstrated on three increasingly complex datasets representing manual industrial tasks. These limited size datasets indicate and highlight the potential of the chosen technology as a combined entity as well as point out limitations of the system.
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| 4. |
- Dubba, Krishna Sandeep Reddy, et al.
(författare)
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Learning Relational Event Models from Video
- 2015
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Ingår i: The journal of artificial intelligence research. - : AI Access Foundation. - 1076-9757 .- 1943-5037. ; 53, s. 41-90
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Tidskriftsartikel (refereegranskat)abstract
- Event models obtained automatically from video can be used in applications ranging from abnormal event detection to content based video retrieval. When multiple agents are involved in the events, characterizing events naturally suggests encoding interactions as relations. Learning event models from this kind of relational spatio-temporal data using relational learning techniques such as Inductive Logic Programming (ILP) hold promise, but have not been successfully applied to very large datasets which result from video data. In this paper, we present a novel framework REMIND (Relational Event Model INDuction) for supervised relational learning of event models from large video datasets using ILP. Efficiency is achieved through the learning from interpretations setting and using a typing system that exploits the type hierarchy of objects in a domain. The use of types also helps prevent over generalization. Furthermore, we also present a type-refining operator and prove that it is optimal. The learned models can be used for recognizing events from previously unseen videos. We also present an extension to the framework by integrating an abduction step that improves the learning performance when there is noise in the input data. The experimental results on several hours of video data from two challenging real world domains (an airport domain and a physical action verbs domain) suggest that the techniques are suitable to real world scenarios.
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| 5. |
- Wilder-Smith, Annelies, et al.
(författare)
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Internet-based media coverage on dengue in Sri Lanka between 2007 and 2015
- 2016
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Ingår i: Global Health Action. - : Informa UK Limited. - 1654-9716 .- 1654-9880. ; 9, s. 1-5
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Tidskriftsartikel (refereegranskat)abstract
- Background: Internet-based media coverage to explore the extent of awareness of a disease and perceived severity of an outbreak at a national level can be used for early outbreak detection. Dengue has emerged as a major public health problem in Sri Lanka since 2009. Objective: To compare Internet references to dengue in Sri Lana with references to other diseases (malaria and influenza) in Sri Lanka and to compare Internet references to dengue in Sri Lanka with notified cases of dengue in Sri Lanka. Design: We examined Internet-based news media articles on dengue queried from Health Map for Sri Lanka, for the period January 2007 to November 2015. For comparative purposes, we compared hits on dengue with hits on influenza and malaria. Results: There were 565 hits on dengue between 2007 and 2015, with a rapid rise in 2009 and followed by a rising trend ever since. These hits were highly correlated with the national epidemiological trend of dengue. The volume of digital media coverage of dengue was much higher than of influenza and malaria. Conclusions: Dengue in Sri Lanka is receiving increasing media attention. Our findings underpin previous claims that digital media reports reflect national epidemiological trends, both in annual trends and inter-annual seasonal variation, thus acting as proxy biosurveillance to provide early warning and situation awareness of emerging infectious diseases.
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| 6. |
- Wölfl, Anne-Cathrin, et al.
(författare)
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Seafloor Mapping - The Challenge of a Truly Global Ocean Bathymetry
- 2019
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Ingår i: Frontiers in Marine Science. - : Frontiers Media SA. - 2296-7745. ; 6
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Forskningsöversikt (refereegranskat)abstract
- Detailed knowledge of the shape of the seafloor is crucial to humankind. Bathymetry data is critical for safety of navigation and is used for many other applications. In an era of ongoing environmental degradation worldwide, bathymetry data (and the knowledge derived from it) play a pivotal role in using and managing the world's oceans in a way that is in accordance with the United Nations Sustainable Development Goal 14 - conserve and sustainably use the oceans, seas and marine resources for sustainable development. However, the vast majority of our oceans is still virtually unmapped, unobserved, and unexplored. Only a small fraction of the seafloor has been systematically mapped by direct measurement. The remaining bathymetry is predicted from satellite altimeter data, providing only an approximate estimation of the shape of the seafloor. Several global and regional initiatives are underway to change this situation. This paper presents a selection of these initiatives as best practice examples for bathymetry data collection, compilation and open data sharing as well as the Nippon Foundation-GEBCO (The General Bathymetric Chart of the Oceans) Seabed 2030 Project that complements and leverages these initiatives and promotes international collaboration and partnership. Several non-traditional data collection opportunities are looked at that are currently gaining momentum as well as new and innovative technologies that can increase the efficiency of collecting bathymetric data. Finally, recommendations are given toward a possible way forward into the future of seafloor mapping and toward achieving the goal of a truly global ocean bathymetry.
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| 7. |
- Årdal, Christine, et al.
(författare)
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International cooperation to improve access to and sustain effectiveness of antimicrobials
- 2016
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 387:10015, s. 296-307
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Tidskriftsartikel (refereegranskat)abstract
- Securing access to effective antimicrobials is one of the greatest challenges today. Until now, efforts to address this issue have been isolated and uncoordinated, with little focus on sustainable and international solutions. Global collective action is necessary to improve access to life-saving antimicrobials, conserving them, and ensuring continued innovation. Access, conservation, and innovation are beneficial when achieved independently, but much more effective and sustainable if implemented in concert within and across countries. WHO alone will not be able to drive these actions. It will require a multisector response (including the health, agriculture, and veterinary sectors), global coordination, and financing mechanisms with sufficient mandates, authority, resources, and power. Fortunately, securing access to effective antimicrobials has finally gained a place on the global political agenda, and we call on policy makers to develop, endorse, and finance new global institutional arrangements that can ensure robust implementation and bold collective action.
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