Abstract
Knowledge generalization of ruled-based models, such as decision trees or decision rules, have emerged from different backgrounds. This particular kind of models, given their interpretability, offer several possibilities to be combined. Despite each distinct context, common patterns have emerged revealing the systemic nature of the problem. In this paper, we look at the problem of generalizing the knowledge contained in a set of models as a process formalizing the operations that can be addressed in alternative ways. We also include a set-up to evaluate gen-eralized models based on their ability to replace the base ones from a predictive performance perspective, without loss of interpretability.

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Abstract
Increasing wildfire threats and costs escalate the complexity of forest fire management challenges, which is grounded in complex interactions between ecological, social, economic, and policy factors. It is immersed in this difficult context that decision-makers must settle on an investment mix within a portfolio of available options, subject to limited funds and under great uncertainty. We model intra-annual fire management as a problem of multistage capacity investment in a portfolio of management resources, enabling fuel treatments and fire preparedness. We consider wildfires as the demand, with uncertainty in the severity of the fire season and in the occurrence, time, place, and severity of specific fires. We focus our analysis on the influence of changes in the volatility of wildfires and in the costs of escaped wildfires, on the postponement of capacity investment along the year, on the optimal budget, and on the investment mix. Using a hypothetical test landscape, we verify that the value of postponement increases significantly for scenarios of increased uncertainty (higher volatility) and higher escape costs, as also does the optimal budget (although not proportionally to the changes in the escape costs). Additionally, the suppression/prevention budget ratio is highly sensitive to changes in escape costs, while it remains mostly insensitive to changes in volatility. Furthermore, we show the policy implications of these findings at operational (e.g., spatial solutions) and strategic levels (e.g., climate change). Exploring the impact of increasing escape costs in the optimal investment mix, we identified in our instances four qualitative system stages, which can be related to specific socioecological contexts and used as the basis for policy (re)design. In addition to questioning some popular myths, our results highlight the value of fuel treatments and the contextual nature of the optimal portfolio mix.

Abstract
A system with fiber laser diodes and photodetector replaces the usual bulky and expensive systems for characterization of long period fiber gratings and high correlation is achieved when measuring refractive index, temperature and curvature.