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Given the integrated nature of food-energy-water systems (FEWS), stakeholder engagement is central to developing solution-oriented projects. However, effective engagement requires substantial time and resources, by both the organization conducting the project and the stakeholders themselves, making effective engagement challenging for many projects. To help teams prioritize, prepare, and sustain stakeholder-engaged environmental projects, we propose a methodological foundation for effective engagement based on six gears: diversity, listening, value, trust, accountability, and flexibility/adaptability. The application of these gears is demonstrated using a set of case studies in Arizona, Idaho, Mexico, and Guatemala. In practice, incorporating all the gears during stakeholder engagement can be challenging. This framework can help teams implement and foster more sustained, comprehensive, robust, actionable, equitable, inclusive, and timely engagement, processes, and outcomes. 

The LHCb upgrade represents a major change of the experiment. The detectors have been almost completely renewed to allow running at an instantaneous luminosity five times larger than that of the previous running periods. Readout of all detectors into an all-software trigger is central to the new design, facilitating the reconstruction of events at the maximum LHC interaction rate, and their selection in real time. The experiment's tracking system has been completely upgraded with a new pixel vertex detector, a silicon tracker upstream of the dipole magnet and three scintillating fibre tracking stations downstream of the magnet. The whole photon detection system of the RICH detectors has been renewed and the readout electronics of the calorimeter and muon systems have been fully overhauled. The first stage of the all-software trigger is implemented on a GPU farm. The output of the trigger provides a combination of totally reconstructed physics objects, such as tracks and vertices, ready for final analysis, and of entire events which need further offline reprocessing. This scheme required a complete revision of the computing model and rewriting of the experiment's software.