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Vision-Based Dynamic Tasking for Earth-Observing Satellite Constellations
Get PDFUnpredictable phenomena such as cloud coverage pose a challenge for conventional Earth observation. Long lead times can cause conditions to change between forecasting, scheduling, and image capture, leading to suboptimal observations. To combat this, dynamic tasking has been proposed as a mission concept, where perception and autonomy are moved onboard the spacecraft in order to quickly respond to changes in the spacecraft’s imaging schedule, leveraging the compute power available in modern Earth-observing spacecraft. In this work, we explore the use of a wide field-of-view body-fixed lookahead sensor, separate from the main imaging payload, to evaluate the real-time utility of upcoming imaging activities, specifically looking at the planning problem of scheduling imaging tasks combined with incorporating slews ahead of the orbit track to re-assess utility and re-optimize the schedule. We apply dynamic tasking with a lookahead instrument to the case of cloud avoidance for an Earth-observing satellite, extending to a leader-follower constellation of identical satellites. In this work we use areas of Europe as a simulation case due to the extremely dense cluster of imaging accesses requiring carefully balancing tradeoffs of performing the lookahead and optimizing the schedule against the opportunity costs of maneuvering the spacecraft. In our single-satellite case, throughput of cloud-free imagery improves by approximately 24%, and an improvement is found in 76 out of 100 simulated trials, even in perhaps the most challenging geographic region for this mission type
On-Orbit Validation of an AI-Enabled Cloud Removal and Compression Solution for EO Satellites
Get PDFOptical Earth Observation (EO) sensors can be significantly affected by atmospheric conditions, particularly cloud cover, which can obscure their images and reduce the information content in the final image. It is estimated that over 50% of the Earth’s surface is covered by clouds at any given moment. As a result, up to half of the data captured by visible EO satellite imagers is rendered unusable for most applications. Transmitting this unusable data, even in a compressed form, unnecessarily utilises valuable communications downlink bandwidth. This is particularly acute for hyperspectral EO missions, where the tens to hundreds of bands per acquisition result in a large redundancy due to cloud obscuration across bands. This paper presents flight results of an AI-driven on-board Cloud Removal and Compression (CRC) approach that couples automatic detection and removal of cloudy image regions with hardware compression of the remaining data. This approach provides lossless EO data compression of non-cloudy regions, while achieving increased compression ratios as a result of the cloud removal, resulting in an increase in the useful data transmitted to ground and thereby significantly enhancing transmission efficiency and increasing satellite asset utilisation. An on-orbit experimental campaign involving five hyperspectral images captured by the CogniSAT-6 satellite across various global locations verified the CRC solution in-flight and demonstrated enhanced compression ratios over and above content-unaware compression approaches. This effectively showcased the utility and capability of an AI-driven on-board processing solution for downlink efficiency enhancement on EO spacecraft
Changing Fire Regimes in the Great Basin USA
Get PDFWildfire is a natural disturbance in landscapes of the Western United States, but the effects and extents of fire are changing. Differences between historical and contemporary fire regimes can help identify reasons for observed changes in landscape composition. People living and working in the Great Basin, USA, are observing altered fire conditions, but spatial information about the degree and direction of change and departure from historical fire regimes is lacking. This study estimates how fire regimes have changed in the major Great Basin vegetation types over the past 60 years with comparisons to historical (pre-1900) fire regimes. We explore potential drivers of fire regime changes using existing spatial data and analysis. Across vegetation types, wildfires were larger and more frequent in the contemporary period (1991–2020) than in the recent past (1961–1990). Contemporary fires were more frequent than historical in two of three ecoregions for the most widespread vegetation type, basin and Wyoming big sagebrush. Increases in fire frequency also occurred in saltbrush, greasewood, and blackbrush shrublands, although current fire return intervals remain on the order of centuries. Persistent juniper and pinyon pine woodlands burned more frequently in contemporary times than in historical times. Fire frequency was relatively unchanged in mixed dwarf sagebrush shrublands, suggesting they remain fuel-limited. Results suggest that quaking aspen woodlands may be burning less frequently now than historically, but more frequently in the contemporary period than in the recent past. We found that increased fire occurrence in the Great Basin is associated with increased abundance and extent of nonnative annual grasses and areas with high concentrations of anthropogenic ignitions. Findings support the need for continuing efforts to reduce fire occurrences in Great Basin plant communities experiencing excess fire and to implement treatments in communities experiencing fire deficits. Results underscore the importance of anthropogenic ignitions and discuss more targeted education and prevention efforts. Knowledge about signals of fire regime changes across the region can support effective deployment of resources to protect or restore plant communities and human values
Potential of Using Trembling Aspen to Make Structural Engineered Wood Products
Get PDFTrembling aspen (Populus tremuloides) is abundant in Canada but is widely considered an underutilized species. This study was aimed at evaluating the potential of using aspen lumber to produce cross-laminated timber (CLT), glued-laminated timber (glulam), and wood I-joists. The key mechanical properties of these engineered wood products, which were fabricated using a modified grading criterion, were examined. It was found that 1) The mean effective bending stiffness and characteristic bending moment resistance of 5-layer CLT specimens in the major-strength direction were 5,069x109 N·mm2/m and 97.65x106 N·mm/m; 2) The mean apparent MOE and characteristic modulus of rupture of glulam specimens were 12,315 MPa and 27.00 MPa; and 3) The mean effective stiffness and characteristic bending moment resistance of wood I-joist specimens were 899x106 kN·mm2 and 9,730 kN·mm. It could be concluded that properly sorted aspen lumber could be used in the production of CLT, glulam, and wood I-joists for specific applications
Optimization and Utilization of Microbial Electrolysis Cells in Waste to Product Applications
Get PDFAs the world searches for cleaner and more sustainable energy solutions, turning waste into fuel is an increasingly attractive strategy. This research focuses on microbial electrolysis cells, a new technology that uses bacteria and a small amount of electricity to convert organic waste—like food scraps or wastewater—into useful gases such as hydrogen and methane. These gases can be used as energy sources to reduce dependency on more traditional fuels.
This thesis tackles two key challenges that limit the real-world use of microbial electrolysis systems. First, it introduces a simpler and more effective method to stop hydrogen losses in single-chamber cells. This was done by periodically applying a short electric shock to the system, which produced small amounts of oxygen that disrupted the microbes responsible for hydrogen consumption. With this approach, hydrogen production improved dramatically, while disruptive microbes were inhibited without inhibition of the beneficial, electroactive microbes.
Second, the research studied how different system settings affect performance in a combined process known as bioelectrochemical anaerobic digestion. This process merges microbial electrolysis with traditional anaerobic digestion—used in many wastewater treatment systems—to further improve organic degradation and energy recovery. The study tested how electrode surface area, applied voltage, and salinity levels in the system influenced gas production, energy recovery, and microbial activity. The results showed that all tested conditions increased biogas output and organic degradation compared to traditional systems. The best performance was achieved with moderate salt levels, which balanced electrical conductivity with microbial health, leading to twice the biogas output and 350% energy efficiency.
In summary, this research presents practical innovations that improve both the efficiency and sustainability of waste-to-energy systems. These findings offer valuable insights for designing future technologies that convert waste into clean energy while reducing costs
Re-Interpreting Bodies (of Water) in a Rhetorical Climate of Ableism: Designing New Normals for Environmental Technical Communication at Bear Lake
No full textThis research asks a simple but powerful question: what happens when we plan for the environment using the same standards we use to judge bodies—like being efficient, independent, or normal? Focusing on Bear Lake, a large natural lake that has been turned into an artificial reservoir on the Utah–Idaho border, this dissertation shows how ideas rooted in ableism—biases against disability and dependence—have shaped how the lake is managed, valued, and talked about. It draws from disability studies and communication research to reveal how environmental decisions often assume that both people and landscapes should function in specific, productive ways.
By analyzing the lake\u27s planning history, government documents, interviews, and public feedback, the project finds that these hidden assumptions influence everything from how problems are defined to what kinds of solutions are considered valid. For example, if a shoreline becomes too weedy or unpredictable, it\u27s often treated as a failure to stay normal. But not all change, not all abnormalities, signal degradation. This work shows how rethinking what counts as normal can help us build more flexible, fair, and inclusive approaches to caring for places like Bear Lake—especially in a time of rapid environmental change
Evacuaidi: An AI-Driven, Causal-Informed Framework for Probabilistic and Disability-Inclusive Evacuation Guidance
No full textWhen emergencies such as fires or natural disasters occur in large buildings, it is crucial that people evacuate quickly and safely. Today, new technologies like artificial intelligence (AI) can help guide people during these emergencies by suggesting the best evacuation routes. However, not everyone will always follow these instructions, especially when there is confusion, fear, or a lack of trust in the system. This is particularly important for individuals with disabilities, who may have different needs or challenges during evacuation. This dissertation focuses on designing smarter and safer evacuation systems that work well even when not everyone follows directions. It uses real data from evacuation drills at a university building, including participants with and without disabilities, to study how people move and respond to AI-based guidance systems. A new computer model was created to simulate how people behave in different emergency situations and how changes in trust or building occupancy affect the overall safety. The model also uses advanced statistics to account for uncertainty, which helps decision-makers see how safe or risky different scenarios could be. The results show that systems need to be flexible and consider human behavior in all its complexity. For example, increasing trust in the system can make evacuations faster and safer, but the benefits eventually level off. By understanding how much improvement is possible and when those improvements slow down, building managers and emergency planners can make better decisions about where to invest time and money. This research offers a new approach to designing inclusive evacuation plans that are both realistic and adaptable. It also highlights the importance of combining technology with a deep understanding of human behavior to protect everyone, especially those who are often overlooked in emergency planning
Using Disposition-Based Tools to Identify Highly Effective Teachers for School Hiring
Get PDFA principal can impact student learning by hiring great teachers, but identifying great teachers is difficult. The goal of this study was to determine whether using a survey of teacher dispositions would be a useful tool to find effective teachers, in other words, teachers who help students grow academically at high rates. The study included a survey of teachers and a review of their students\u27 academic performance on a reading assessment to see whether there was a correlation between self-reported surveys and student results
Promising Practices to Address Healthcare Needs Voiced By Local Native Americans
Get PDFPurpose
To examine barriers and facilitators to nursing education among Native Americans and identify evidence-based strategies to increase the number of Native American nurses working in their local communities to address health disparities.
Background
Native Americans experience significantly higher rates of chronic illnesses such as diabetes and heart disease, and lower life expectancies. Only 4% of registered nurses identify as Native American, with no growth despite increased funding for diversity in nursing education. This underrepresentation contributes to culturally insensitive care and persistent healthcare inequities stemming from historical marginalization and trauma.
Methods
A comprehensive literature review was conducted using CINAHL, PubMed, and Google Scholar databases to identify peer-reviewed scholarly literature focused on barriers and facilitators to nursing education among Native Americans in the United States.
Findings
Among 167 articles identified, 34 met inclusion criteria, with minimal research conducted in the past five years. Major barriers included historical oppression, geographic isolation, resource limitations, cultural disconnect between Western nursing education and Indigenous values, a lack of role models, and persistent healthcare underfunding.
Recommendations
Successful interventions included: implementing culturally sensitive mentorship programs, creating culturally safe learning environments that incorporate Indigenous healing practices, developing mobile health training programs in partnership with tribal communities, integrating Native American theoretical frameworks into nursing curricula, establishing community partnerships for clinical placements in tribal settings, and providing targeted scholarships with service commitments to tribal communities.
Conclusion
Addressing the complex barriers facing Native American nursing students requires a holistic, culturally informed approach. Integrating Indigenous perspectives into nursing education can improve recruitment, retention, and graduation rates while developing a workforce equipped to provide culturally responsive care. Increasing Native American representation in nursing is essential to reducing health disparities and honoring the valuable contributions of Indigenous healing traditions to healthcare practice.
Key Words: Native American, Nursing Education, Health Disparities, Nursing Shortage, Access to Healthcar
STARI: STarlight Acquisition and Reflection toward Interferometry
Get PDFWe introduce the NASA-funded mission STARI (STarlight Acquisition and Reflection toward Interferometry). We plan to demonstrate the first transfer of starlight between two separate spacecraft, a key technology step towards long-baseline interferometry. Consisting of two propulsive 6U CubeSats flying in Low Earth Orbit separated by ∼100 meters, STARI will reflect a small beam of starlight from the Chief spacecraft toward the Deputy spacecraft, where the light will be collected by an off-axis parabola and focused into a single-mode fiber. With the use of differential Global Positioning System (GPS), visual LED beacons and fast-steering-mirrors (FSMs), we aim for continuous high-throughput fiber coupling to demonstrate both diffraction-limited control of the starlight beam angle and mm-level control of the beam’s trajectory, paving the way for a science-focused space interferometer in a follow-up mission. Here, we give an overview of the top-level science and technical requirements for STARI, along with an update to our Concept of Operations. Novel orbital geometries are proposed that advance the state-of-the-art for conducting interferometry operations in LEO. Lastly, we provide mission-specific requirements and details for each payload subsystem. We hope that a successful STARI mission (expected launch 2029) will accelerate the development of the Large Interferometer for Exoplanets (LIFE) Mission, our best chance for detecting biomarkers in the atmospheres of nearby Earthlike planets