Integrated Human-Robotic Missions to the Moon and Mars: Mission Operations Design Implications

For most of the history of space exploration, human and robotic programs have been independent, and have responded to distinct requirements. The NASA Vision for Space Exploration calls for the return of humans to the Moon, and the eventual human exploration of Mars; the complexity of this range of missions will require an unprecedented use of automation and robotics in support of human crews. The challenges of human Mars missions, including roundtrip communications time delays of 6 to 40 minutes, interplanetary transit times of many months, and the need to manage lifecycle costs, will require the evolution of a new mission operations paradigm far less dependent on real-time monitoring and response by an Earthbound operations team. Robotic systems and automation will augment human capability, increase human safety by providing means to perform many tasks without requiring immediate human presence, and enable the transfer of traditional mission control tasks from the ground to crews. Developing and validating the new paradigm and its associated infrastructure may place requirements on operations design for nearer-term lunar missions. The authors, representing both the human and robotic mission operations communities, assess human lunar and Mars mission challenges, and consider how human-robot operations may be integrated to enable efficient joint operations, with the eventual emergence of a unified exploration operations culture

Groundwater level assessment and prediction in the Nebraska Sand Hills using LIDAR-derived lake water level

The spatial variability of groundwater levels is often inferred from sparsely located hydraulic head observations in wells. The spatial correlation structure derived from sparse observations is associated with uncertainties that spread to estimates at unsampled locations. In areas where surface water represents the nearby groundwater level, remote sensing techniques can estimate and increase the number of hydraulic head measurements. This research uses light detection and ranging (LIDAR) to estimate lake surface water level to characterize the groundwater level in the Nebraska Sand Hills (NSH), an area with few observation wells. The LIDAR derived lake groundwater level accuracy was within 40 cm mean square error (MSE) of the nearest observation wells. The lake groundwater level estimates were used to predict the groundwater level at unsampled locations using universal kriging (UK) and kriging with an external drift (KED). The results indicate unbiased estimates of groundwater level in the NSH. UK showed the influence of regional trends in groundwater level while KED revealed the local variation present in the groundwater level. A 10-fold cross-validation demonstrated KED with better mean squared error (ME) [–0.003, 0.007], root mean square error (RMSE) [2.39, 4.46], residual prediction deviation (RPD) [1.32, 0.71] and mean squared deviation ratio (MSDR) [1.01, 1.49] than UK. The research highlights that the lake groundwater level provides an accurate and cost-effective approach to measure and monitor the subtle changes in groundwater level in the NSH. This methodology can be applied to other locations where surface water bodies represent the water level of the unconfined aquifer and the results can aid in groundwater management and modeling

Seasonal variation in the canopy color of temperate evergreen conifer forests

Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near‐surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on‐the‐ground phenological observations, leaf‐level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower‐based CO₂ flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter‐dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy‐level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature‐based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color‐based vegetation indices

Анализ виброустойчивости роботов

Материалы XV Междунар. науч.-техн. конф. студентов, аспирантов и молодых ученых, Гомель, 23–24 апр. 2015 г

Nebraska\u27s Advantage: Productive Agriculture and Bountiful Natural Resources

Nebraska\u27s Advantage: Productive Agriculture and Bountiful Natural Resources You can’t talk about healthy production systems and natural resource systems without also thinking about the resilience. We need to harmonize production agriculture in a way that ensures the resilience of our natural ecosystems and rural communities—all while addressing bundles of grand challenges

Role of Secreted Conjunctival Mucosal Cytokine and Chemokine Proteins in Different Stages of Trachomatous Disease

Trachoma, a disease of antiquity dating back to the 16th century B.C.E., predominates among developing countries, where it remains the primary cause of preventable blindness worldwide. In trachoma, recurrent Chlamydia trachomatis bacterial infections during childhood are thought to result in inflammation and subsequent conjunctival scarring that can progress to trichiasis (TT; chronic trachoma; inversion of ≥1 eyelash that touches the globe of the eye). The trachomatous follicular grade (TF; active disease) is a self-limiting disease, suggesting the coexistence of protective inflammatory proteins. The trachomatous inflammatory grade (TI; active disease) is more likely to progress to trachomatous scarring (TS; chronic trachoma). To date, there are only a handful of studies that have examined the immune response in trachoma, and these were primarily based on gene expression. Characterizing quantified conjunctival mucosal immune differences for secreted proteins among individuals with no, active, and chronic trachoma may identify protein biomarkers associated with protection versus disease, which would greatly aid our understanding of the immunopathogenesis of trachoma. In this study, we characterized 25 cytokine and chemokine proteins for all trachoma grades. We identified eight cytokines and chemokines as risk factors for chronic trachoma and four as protective. Together, these findings further characterize the immunopathologic responses involved during trachoma, which will likely aid in the design of a vaccine and immunomodulating therapeutics for trachoma