Technical Note: Practical Challenges Facing the Selection of Conditional Spectrum-Compatible Accelerograms

2016 ◽  
Vol 21 (1) ◽  
pp. 169-180 ◽  
Author(s):  
Bekİr Özer Ay ◽  
Matthew James Fox ◽  
Timothy John Sullivan
Keyword(s):  
Neurosurgery ◽  
2002 ◽  
Vol 50 (3) ◽  
pp. 669-671 ◽  
Author(s):  
Steven L. Giannotta

Abstract OBJECTIVE: Appropriate clip selection frequently becomes a matter of trial and error because of inadequate dissection of the pathway for each clip blade. To facilitate selection of the proper clip size, a series of dissectors have been designed that mimic the exact caliber of each category of Sugita clips. METHODS: Three lines of sizer-dissectors reflecting the wire size of the most commonly used Sugita clips were developed by attaching a single aneurysm clip blade to a rounded microdissector handle. Each sizer-dissector is scaled in millimeters and is available in straight and angled configurations. Once dissection is presumed to be complete, the device is passed through the pathway of the intended aneurysm clip blades, and the clip with the appropriate caliber and length for permanent occlusion is selected. RESULTS: During dissection and clip ligation of 83 aneurysms, the sizer-dissector was used to select the blade length in 16 lesions and the blade caliber in 5 lesions. There were no complications associated with deployment of the device. CONCLUSION: By use of the sizer-dissector before attempting clip placement, clip selection is facilitated, safety is enhanced, and clip wastage is reduced.


2021 ◽  
Vol 25 (7) ◽  
pp. 3937-3973
Author(s):  
Paul C. Astagneau ◽  
Guillaume Thirel ◽  
Olivier Delaigue ◽  
Joseph H. A. Guillaume ◽  
Juraj Parajka ◽  
...  

Abstract. Following the rise of R as a scientific programming language, the increasing requirement for more transferable research and the growth of data availability in hydrology, R packages containing hydrological models are becoming more and more available as an open-source resource to hydrologists. Corresponding to the core of the hydrological studies workflow, their value is increasingly meaningful regarding the reliability of methods and results. Despite package and model distinctiveness, no study has ever provided a comparison of R packages for conceptual rainfall–runoff modelling from a user perspective by contrasting their philosophy, model characteristics and ease of use. We have selected eight packages based on our ability to consistently run their models on simple hydrology modelling examples. We have uniformly analysed the exact structure of seven of the hydrological models integrated into these R packages in terms of conceptual storages and fluxes, spatial discretisation, data requirements and output provided. The analysis showed that very different modelling choices are associated with these packages, which emphasises various hydrological concepts. These specificities are not always sufficiently well explained by the package documentation. Therefore a synthesis of the package functionalities was performed from a user perspective. This synthesis helps to inform the selection of which packages could/should be used depending on the problem at hand. In this regard, the technical features, documentation, R implementations and computational times were investigated. Moreover, by providing a framework for package comparison, this study is a step forward towards supporting more transferable and reusable methods and results for hydrological modelling in R.


2012 ◽  
Vol 9 (5) ◽  
pp. 6185-6201 ◽  
Author(s):  
L. Gudmundsson ◽  
J. B. Bremnes ◽  
J. E. Haugen ◽  
T. Engen Skaugen

Abstract. The impact of climate change on water resources is usually assessed at the local scale. However, regional climate models (RCM) are known to exhibit systematic biases in precipitation. Hence, RCM simulations need to be post-processed in order to produce reliable estimators of local scale climate. A popular post-processing approach is quantile mapping (QM), which is designed to adjust the distribution of modeled data, such that it matches observed climatologies. However, the diversity of suggested QM methods renders the selection of optimal techniques difficult and hence there is a need for clarification. In this paper, QM methods are reviewed and classified into: (1) distribution derived transformations, (2) parametric transformations and (3) nonparametric transformations; each differing with respect to their underlying assumptions. A real world application, using observations of 82 precipitation stations in Norway, showed that nonparametric transformations have the highest skill in systematically reducing biases in RCM precipitation.


2012 ◽  
Vol 16 (9) ◽  
pp. 3383-3390 ◽  
Author(s):  
L. Gudmundsson ◽  
J. B. Bremnes ◽  
J. E. Haugen ◽  
T. Engen-Skaugen

Abstract. The impact of climate change on water resources is usually assessed at the local scale. However, regional climate models (RCMs) are known to exhibit systematic biases in precipitation. Hence, RCM simulations need to be post-processed in order to produce reliable estimates of local scale climate. Popular post-processing approaches are based on statistical transformations, which attempt to adjust the distribution of modelled data such that it closely resembles the observed climatology. However, the diversity of suggested methods renders the selection of optimal techniques difficult and therefore there is a need for clarification. In this paper, statistical transformations for post-processing RCM output are reviewed and classified into (1) distribution derived transformations, (2) parametric transformations and (3) nonparametric transformations, each differing with respect to their underlying assumptions. A real world application, using observations of 82 precipitation stations in Norway, showed that nonparametric transformations have the highest skill in systematically reducing biases in RCM precipitation.


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