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In addition to the direct implications for prediction of risk of abuse, the general modelling framework presented here has far reaching potential implications for automated screening of other clinical conditions where longitudinal historical information can be useful for estimating clinical risk.
The modelling framework presented in this paper fits the model-based design approach used for the development of this prototype and shows the potential benefits of this design strategy by establishing the desired engineering parameters and by enabling the engineer to assess mechanical tolerances and material options.
The modelling framework presented here, Probabilistic Volcanic Ash Hazard Analysis (PVAHA), adapts the seismologically based PSHA technique for volcanic ash.
The modelling framework presented integrates climate, economic, agronomic and hydrological scenarios to design a programme of adaptation measures at the river basin scale.
We also show that when the temperature evolution due to viscous heating is properly accounted for the modelling framework presented can be effectively used to describe the premature failure occurring due to this heating effect.
A multimedia approach will be required as an extension of the modelling framework presented here.
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The model framework presented in this paper can be modified and transferred to other species.
The potential of the general modeling framework presented here is in the understanding and design of more complex cases of wastewater-fed microbial fuel cells.
The general modeling framework presented here, with components representing molecular events, cancer onset, and disease natural history, is designed to be flexible, allowing models to be added and modified in a modular fashion and developed iteratively.
Thus, the model framework presented in the previous paper [ 10], and substantiated here with incursion data, should be considered as indicating the spatial and temporal nature of dispersal, and the relative frequency of such dispersal from specific source sites, and to arrival regions.
A coupled thermodynamic/mean field modelling framework is presented and applied to describe the particle size evolution.
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