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Addressing the challenges of wildland fire requires that fire science be relevant to management and integrated into management decisions. Co-production is often touted as a process that can increase the utility of science for management, by involving scientists and managers in knowledge creation and problem solving. Despite the documented benefits of co-production, these efforts face a number of institutional barriers. Further research is needed on how to institutionalise support and incentivise co-production. To better understand how research organisations enable and constrain co-production, this study examined seven co-produced wildland fire projects associated with the US Department of Agriculture Forest Service Rocky Mountain Research Station (RMRS), through in-depth interviews with scientists, managers and community members. Results provide insights into how organisational structures and cultures influence the co-production of fire science. Research organisations like RMRS may be able to institutionalise co-production by adjusting the way they incentivise and evaluate researchers, increasing investment in science delivery and scientific personnel overall, and supplying long-term funding to support time-intensive collaborations. These sorts of structural changes could help transform the culture of fire science so that co-production is valued alongside more conventional scientific activities and products. 

Abstract For many planar bipedal models, each step is divided into a finite time single support period and an instantaneous double support period. During single support, the biped is typically underactuated and thus has limited ability to reject disturbances. The instantaneous nature of the double support period prevents nonimpulsive control during this period. However, if the double support period is expanded to finite time, it becomes overactuated. While it has been hypothesized that this overactuation during a finite-time double support period may improve disturbance rejection capabilities, this has not yet been tested. This paper presents a refined biped model by developing a finite-time, adaptive double support controller capable of handling the overactuation and limiting slip. Using simulations, we quantify the disturbance rejection capabilities of this controller and directly compare them to a typical, instantaneous double support model for a range of gait speeds and perturbations. We find that the finite-time double support controller increased the walking stability of the biped in approximately half of the cases, indicating that a finite-time double support period does not automatically increase disturbance rejection capabilities. We also find that the timing and magnitude of the perturbation can affect if a finite-time double support period enhances stability. Finally, we demonstrate that the adaptive controller reduces slipping. 

For many planar bipedal models, each step is divided into a finite time single support period and an instantaneous double support period. During single support, the biped is typically underactuated and thus has limited ability to reject disturbances. The instantaneous nature of the double support period prevents control during this period. However, if the double support period is expanded to finite time, this introduces an overactuated period into the model which may improve disturbance rejection capabilities. This paper derives and compares the performance of two finite-time double support controllers. The first controller uses time to drive the progression of the double support period and controls the joint angles. The second controller uses a time-invariant phase variable to drive the progression of the double support period and controls the joint velocities since it is not possible to control the joint positions. The disturbance rejection capabilities of both controllers are then quantified using simulations. The instantaneous double support model is also simulated for comparison. The instantaneous double support model can recover from the largest disturbances but it requires the greatest number of steps to do. The time-based double support controller can recover from the smallest range of disturbances but requires the fewest number of steps for a given perturbation size. 

Acquiring accurate high temperature laboratory‐based infrared emission spectra of geologic samples is important to constrain their radiative and spectral properties. This is important in calculations of lava flow cooling, crust formation, and ultimately lava flow propagation modeling. However, measuring accurate emission at high temperatures remains a challenge. A new micro‐furnace design was created to integrate with a Fourier transform infrared spectrometer, replacing the previous furnace and improving the performance and error metrics. Importantly, this approach accounts for all significant error sources and uses only one spectrometer to acquire sample and calibration emission data over greater temperature (473–1,573 K) and spectral (4,000–500 cm⁻¹, 2.5–20 μm) ranges. Emissivity spectra of forsterite and quartz samples were acquired to test the calibration procedure. Forsterite, with no expected phase transitions over the temperature range, showed spectral change above ∼1140 K, potentially due to amorphization–a process not well described in past studies. The quartz results revealed the expected polymorph transformations at ∼846 and ∼1323 K. A Hawaiian basalt sample served as a representative rock test and showed an increase in emissivity (∼25%) with decreasing temperature. The greatest emissivity increase (∼60%) occurred in the middle infrared region (3,333–2,000 cm⁻¹, 3–5 μm). This is significant for thermal/mass flux calculations using satellite data in this spectral region, which rely on emissivity to derive accurate temperatures. All results are consistent with our previous investigations, but with improved mean accuracy (<2%), uncertainty (<4%), and spectral contrast (<20%). The improved metrics were achieved by constraining the sample measurement geometry, sample temperature stability, and environmental contamination within the experiment.