| 1. |
|
|
| 2. |
|
|
| 3. |
- Blaess, Julien, et al.
(författare)
-
Recommendations for physical activity and exercise in persons living with Systemic Lupus Erythematosus (SLE) : consensus by an international task force
- 2024
-
Ingår i: RMD Open. - : BMJ Publishing Group Ltd. - 2056-5933. ; 10:2
-
Forskningsöversikt (refereegranskat)abstract
- OBJECTIVE: This international task force aimed to provide healthcare professionals and persons living with systemic lupus erythematosus (SLE) with consensus-based recommendations for physical activity and exercise in SLE.METHODS: Based on evidence from a systematic literature review and expert opinion, 3 overarching principles and 15 recommendations were agreed on by Delphi consensus.RESULTS: The overarching principles highlight the importance of shared decision-making and the need to explain the benefits of physical activity to persons living with SLE and other healthcare providers. The 15 specific recommendations state that physical activity is generally recommended for all people with SLE, but in some instances, a medical evaluation may be needed to rule out contraindications. Pertaining to outdoor activity, photoprotection is necessary. Both aerobic and resistance training programmes are recommended, with a gradual increase in frequency and intensity, which should be adapted for each individual, and ideally supervised by qualified professionals.CONCLUSION: In summary, the consensus reached by the international task force provides a valuable framework for the integration of physical activity and exercise into the management of SLE, offering a tailored evidence-based and eminence-based approach to enhance the well-being of individuals living with this challenging autoimmune condition.
|
|
| 4. |
- Zhou, Zhicheng, et al.
(författare)
-
NDT-Transformer : Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation
- 2021
-
Ingår i: 2021 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE. - 9781728190778 - 9781728190785
-
Konferensbidrag (refereegranskat)abstract
- 3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-challenged environments and serves as an essential component (i.e. loop-closure detection) in lidar-based SLAM systems. This paper proposes a novel approach, named NDT-Transformer, for real-time and large-scale place recognition using 3D point clouds. Specifically, a 3D Normal Distribution Transform (NDT) representation is employed to condense the raw, dense 3D point cloud as probabilistic distributions (NDT cells) to provide the geometrical shape description. Then a novel NDT-Transformer network learns a global descriptor from a set of 3D NDT cell representations. Benefiting from the NDT representation and NDT-Transformer network, the learned global descriptors are enriched with both geometrical and contextual information. Finally, descriptor retrieval is achieved using a query-database for place recognition. Compared to the state-of-the-art methods, the proposed approach achieves an improvement of 7.52% on average top 1 recall and 2.73% on average top 1% recall on the Oxford Robotcar benchmark.
|
|
