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- Nijkamp, P., et al.
(författare)
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Towards a regional science academy : A manifesto
- 2016
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Ingår i: Region. - : European Regional Science Association. - 2409-5370. ; 3:1, s. R1-R16
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Tidskriftsartikel (refereegranskat)abstract
- This Manifesto provides a joint proposal to create a Regional Science Academy as a think-tank support platform for a strategic development of the spatial sciences. The Regional Science Academy is a strategic spatial knowledge catalyst: it acts as a global intellectual powerhouse for new knowledge network initiatives and scholarly views on regions and cities as vital centrepieces of interconnected spatial systems. This contribution highlights its role and presents various activity plans.
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- Banys-Paluchowski, M, et al.
(författare)
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Surgical Management of the Axilla in Clinically Node-Positive Breast Cancer Patients Converting to Clinical Node Negativity through Neoadjuvant Chemotherapy: Current Status, Knowledge Gaps, and Rationale for the EUBREAST-03 AXSANA Study
- 2021
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:7
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Tidskriftsartikel (refereegranskat)abstract
- In the last two decades, surgical methods for axillary staging in breast cancer patients have become less extensive, and full axillary lymph node dissection (ALND) is confined to selected patients. In initially node-positive patients undergoing neoadjuvant chemotherapy, however, the optimal management remains unclear. Current guidelines vary widely, endorsing different strategies. We performed a literature review on axillary staging strategies and their place in international recommendations. This overview defines knowledge gaps associated with specific procedures, summarizes currently ongoing clinical trials that address these unsolved issues, and provides the rationale for further research. While some guidelines have already implemented surgical de-escalation, replacing ALND with, e.g., sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) in cN+ patients converting to clinical node negativity, others recommend ALND. Numerous techniques are in use for tagging lymph node metastasis, but many questions regarding the marking technique, i.e., the optimal time for marker placement and the number of marked nodes, remain unanswered. The optimal number of SLNs to be excised also remains a matter of debate. Data on oncological safety and quality of life following different staging procedures are lacking. These results provide the rationale for the multinational prospective cohort study AXSANA initiated by EUBREAST, which started enrollment in June 2020 and aims at recruiting 3000 patients in 20 countries (NCT04373655; Funded by AGO-B, Claudia von Schilling Foundation for Breast Cancer Research, AWOgyn, EndoMag, Mammotome, and MeritMedical).
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| 7. |
- Bartlett, Madeleine, et al.
(författare)
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What Can You See? : Identifying Cues on Internal States From the Movements of Natural Social Interactions
- 2019
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Ingår i: Frontiers in Robotics and AI. - : Frontiers Research Foundation. - 2296-9144. ; 6:49
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the field of Human-Robot Interaction (HRI) has seen an increasingdemand for technologies that can recognize and adapt to human behaviors and internalstates (e.g., emotions and intentions). Psychological research suggests that humanmovements are important for inferring internal states. There is, however, a need to betterunderstand what kind of information can be extracted from movement data, particularlyin unconstrained, natural interactions. The present study examines which internal statesand social constructs humans identify from movement in naturalistic social interactions.Participants either viewed clips of the full scene or processed versions of it displaying2D positional data. Then, they were asked to fill out questionnaires assessing their socialperception of the viewed material. We analyzed whether the full scene clips were moreinformative than the 2D positional data clips. First, we calculated the inter-rater agreementbetween participants in both conditions. Then, we employed machine learning classifiersto predict the internal states of the individuals in the videos based on the ratingsobtained. Although we found a higher inter-rater agreement for full scenes comparedto positional data, the level of agreement in the latter case was still above chance,thus demonstrating that the internal states and social constructs under study wereidentifiable in both conditions. A factor analysis run on participants’ responses showedthat participants identified the constructs interaction imbalance, interaction valence andengagement regardless of video condition. The machine learning classifiers achieveda similar performance in both conditions, again supporting the idea that movementalone carries relevant information. Overall, our results suggest it is reasonable to expecta machine learning algorithm, and consequently a robot, to successfully decode andclassify a range of internal states and social constructs using low-dimensional data (suchas the movements and poses of observed individuals) as input.
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- Da Lio, Mauro, et al.
(författare)
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Exploiting Dream-Like Simulation Mechanisms to Develop Safer Agents for Automated Driving The "Dreams4Cars" EU Research and Innovation Action
- 2017
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Ingår i: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). - : IEEE. - 9781538615263 - 9781538615270
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Konferensbidrag (refereegranskat)abstract
- Automated driving needs unprecedented levels of reliably and safety before marked deployment. The average human driver fatal accident rate is 1 every 100 million miles. Automated vehicles will have to provably best these figures. This paper introduces the notion of dream-like mechanisms as a simulation technology to produce a large number of hypothetical design and test scenarios - especially focusing on variations of more frequent dangerous and near miss events. Grounded in the simulation hypothesis of cognition, we show here some principles for effective simulation mechanisms and an artificial cognitive system architecture that can learn from the simulated situations.
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