| 1. |
- Hall, C. Michael, et al.
(author)
-
Denying bogus skepticism in climate change and tourism research.
- 2015
-
In: Tourism Management. - : Elsevier BV. - 0261-5177 .- 1879-3193. ; 47, s. 352-356
-
Journal article (peer-reviewed)abstract
- This final response to the two climate change denial papers by Shani and Arad further highlights the inaccuracies, misinformation and errors in their commentaries. The obfuscation of scientific research and the consensus on anthropogenic climate change may have significant long-term negative consequences for better understanding the implications of climate change and climate policy for tourism and create confusion and delay in developing and implementing tourism sector responses.
|
|
| 2. |
- Hall, C. Michael, et al.
(author)
-
No time for smokescreen skepticism : A rejoinder to Shani and Arad
- 2015
-
In: Tourism Management. - : Elsevier BV. - 0261-5177 .- 1879-3193. ; 47, s. 341-347
-
Journal article (peer-reviewed)abstract
- Shani and Arad (2014) claimed that tourism scholars tend to endorse the most pessimistic assessments regarding climate change, and that anthropogenic climate change was a "fashionable" and "highly controversial scientific topic". This brief rejoinder provides the balance that is missing from such climate change denial and skepticism studies on climate change and tourism. Recent research provides substantial evidence that reports on anthropogenic climate change are accurate, and that human-induced greenhouse gas emissions, including from the tourism industry, play a significant role in climate change. Some positive net effects may be experienced by some destinations in the short-term, but in the long-term all elements of the tourism system will be impacted. The expansion of tourism emissions at a rate greater than efficiency gains means that it is increasingly urgent that the tourism sector acknowledge, accept and respond to climate change. Debate on tourism-related adaptation and mitigation measures is to be encouraged and welcomed. Climate change denial is not.
|
|
| 3. |
- Bouget, D., et al.
(author)
-
Preoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting
- 2022
-
In: Frontiers in Neurology. - : Frontiers Media SA. - 1664-2295. ; 13
-
Journal article (peer-reviewed)abstract
- For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the lack of standardized and automatic methods for tumor detection and generation of clinical reports, incorporating a wide range of tumor characteristics, represents a major hurdle. In this study, we investigate the most occurring brain tumor types: glioblastomas, lower grade gliomas, meningiomas, and metastases, through four cohorts of up to 4,000 patients. Tumor segmentation models were trained using the AGU-Net architecture with different preprocessing steps and protocols. Segmentation performances were assessed in-depth using a wide-range of voxel and patient-wise metrics covering volume, distance, and probabilistic aspects. Finally, two software solutions have been developed, enabling an easy use of the trained models and standardized generation of clinical reports: Raidionics and Raidionics-Slicer. Segmentation performances were quite homogeneous across the four different brain tumor types, with an average true positive Dice ranging between 80 and 90%, patient-wise recall between 88 and 98%, and patient-wise precision around 95%. In conjunction to Dice, the identified most relevant other metrics were the relative absolute volume difference, the variation of information, and the Hausdorff, Mahalanobis, and object average symmetric surface distances. With our Raidionics software, running on a desktop computer with CPU support, tumor segmentation can be performed in 16-54 s depending on the dimensions of the MRI volume. For the generation of a standardized clinical report, including the tumor segmentation and features computation, 5-15 min are necessary. All trained models have been made open-access together with the source code for both software solutions and validation metrics computation. In the future, a method to convert results from a set of metrics into a final single score would be highly desirable for easier ranking across trained models. In addition, an automatic classification of the brain tumor type would be necessary to replace manual user input. Finally, the inclusion of post-operative segmentation in both software solutions will be key for generating complete post-operative standardized clinical reports.
|
|
| 4. |
- Hall, C. Michael, et al.
(author)
-
On climate change skepticism and denial in tourism
- 2015
-
In: Journal of Sustainable Tourism. - : Taylor & Francis. - 0966-9582 .- 1747-7646. ; 23:1, s. 4-25
-
Journal article (peer-reviewed)abstract
- The period leading to and immediately after the release of the IPCC's fifth series of climate change assessments saw substantial efforts by climate change denial interests to portray anthropogenic climate change (ACC) as either unproven theory or a negligible contribution to natural climate variability, including the relationship between tourism and climate change. This paper responds to those claims by stressing that the extent of scientific consensus suggests that human-induced warming of the climate system is unequivocal. Second, it responds in the context of tourism research and ACC, highlighting tourism's significant contribution to greenhouse gas emissions, as well as climate change's potential impacts on tourism at different scales. The paper exposes the tactics used in ACC denial papers to question climate change science by referring to non-peer-reviewed literature, outlier studies, and misinterpretation of research, as well as potential links to think tanks and interest groups. The paper concludes that climate change science does need to improve its communication strategies but that the world-view of some individuals and interests likely precludes acceptance. The connection between ACC and sustainability illustrates the need for debate on adaptation and mitigation strategies, but that debate needs to be grounded in scientific principles not unsupported skepticism.
|
|
