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A Pilot Randomized Controlled Trial of a Single-Session Digital Acceptance and Commitment Therapy Intervention
Get PDFAdherence challenges are common among digital mental health interventions (DMHIs). Single-session DMHIs may help by providing a low-intensity intervention that takes less time to complete. This pilot randomized controlled trial sought to evaluate the acceptability and preliminary efficacy of a single-session DMHI based on acceptance and commitment therapy (ACT) in a non-clinical sample of college students. The trial was pre-registered (NCT06139718). A total of 61 students were recruited, which was below the target of 100 participants. The participants were randomized to the single-session ACT DMHI or to a waitlist condition, with assessments completed at 1-week and 1-month follow-ups. The vast majority of participants (87%) completed the single-session ACT program. The participants provided high program satisfaction ratings. There were no differences between conditions on psychological flexibility, distress, or mental health help seeking. However, the participants assigned to ACT improved significantly more than the waitlist on well-being from baseline to 1-month follow-up (d = 0.29). Overall, the results were mixed, with some support for the acceptability and potential efficacy of a single-session ACT DMHI but also a lack of effect, most notably on psychological flexibility as the process of change in ACT
Utah Farmers Markets: Statewide Social and Economic Impacts
Get PDFUtah is home to over 45 markets where local farmers and artisans sell their homegrown food and homemade wares. These markets gather community, stimulate regional commerce, champion nutrition for Utahns from all backgrounds, and most of all, create a home for local agriculture to flourish
Scheduling Charging for Fleets of Battery Electric Vehicles: Techniques for Modeling and Real-Time Operation
Get PDFWhile electric vehicles (EVs) are becoming increasingly popular and can provide cost, maintenance, and environmental benefits, they present unique challenges for regular operation, especially in fleets of vehicles. The limited range, long charging times, and high power requirements of EVs complicate the operations of fleets comprised of EVs. Additionally, the charging costs of EVs can be complex, depending on the time of charging, the energy charged, and the power level of the charging session. These complex charging costs can be significantly affected by the presence of uncontrolled loads. These challenges are further complicated by the inevitable variations in the real world, caused by conditions such as traffic congestion, weather, and equipment malfunctions.
Accordingly, the scheduling of EV charging in fleets is a complex, but necessary, problem to address. This research develops methods to schedule the charging of fleets of EVs that are cost-effective, robust, and scalable. Exact, but computationally expensive, approaches are developed to schedule when and how much each vehicle should charge to minimize the cost of charging while maintaining the operational constraints of the fleet. A technique for adjusting the schedules based on up-to-date arrival time, battery level, and other feedback is demonstrated. These developments are significant steps towards addressing the challenges of scheduling the charging of EVs in fleets and enabling the further adoption of EVs in vehicle fleets
Evolution of the USU Extension Farm and Ranch Succession Program
Get PDFThe Utah State University (USU) Extension Farm and Ranch Succession Program has been operating for five years, providing critical support to agricultural producers across Utah. Although its impacts were previously documented (Dallin et al., 2021), the program has since been revised and better adapted to meet the needs of producers. This publication highlights USU Extension’s efforts to address the growing need for farm and ranch succession training and examines the program’s ongoing impacts on agricultural communities throughout the state
Validation of Head Above and Head Submerged Hydrostatic Weighing Equations and Air Displacement Plethysmography
Get PDFTraditional hydrostatic weighing (HW) involves full body submersion at residual volume (RV), which may be uncomfortable. Thus, the purpose of this study was to investigate a more comfortable way to perform this method. HW with the head above water (HWHAW) was compared to the traditional method of HW with head below water (HWHBW) and to another method that also measures density by displacement, air displacement plethysmography (ADP). Equivalence was tested by comparing the body fat percentage (BF%), body volume (Vb), and body density (Db) of 27 subjects (15 M, 12 F) between the three methods. Results showed evidence of a significant mean difference in BF% when comparing HWHAW to both HWHBW (5.6 (90% CI 4.9 to 6.3) %fat, p \u3c .001) and ADP (5.1 (90% CI, 4.0 to 6.1) %fat, p \u3c .001). In addition, a statistically significant difference was reported in Vb between HWHAW to both HWHBW (0.890 (90% CI, 0.772 to 1.007) L, p \u3c .001) and ADP (0.734 (90% CI, 0.487 to 0.980) L, p \u3c .001). This trend continues when comparing Db from HWHAW to HWHBW (0.012 (90% CI, 0.011 to 0.014) kg/m3, p \u3e .001) and to ADP (0.011 (90% CI, 0.009 to 0.013) kg/m3, p \u3e .001). While HWHAW has a low standard error of estimate (SEE) when compared to HWHBW (1.7% BF), its total error is much larger (5.8% BF). This new method has potential; however, further studies are necessary to investigate the source of this larger total error (TE)
DREAM Pilot Project: Analysis of Groundwater Development at Six Villages in Ethiopia
No full textThis study presents a hydrogeologic assessment of the Distributed Renewable Energy Agriculture Modalities (DREAM) pilot project, an ongoing groundwater development initiative in rural Ethiopia. This project integrates solar-powered groundwater infrastructure across six villages to improve water access, agricultural productivity, and economic stability.
Fourteen production wells were installed at Murche, four at Dalle, and additional test wells at Murche, Dalle, Chefe Kora, and Huluku. Transmissivity values and the number of wells at Murche suggest that local water needs are currently being met. In contrast, fewer wells were drilled at Dalle. This reflects the high cost of well construction relative to yield, not a lack of demand. Given the lower transmissivity values at Dalle, alternative water sources such as adjacent river water may be needed to meet irrigation demands. Test wells at Chefe Kora and Huluku yielded high transmissivity values, highlighting their potential for future expansion.
Several challenges were identified, including excessive screened intervals, short recovery test durations, and high ion balance errors in water chemistry analyses. These practices can lead to reduced well efficiency, misinterpretation of aquifer recovery characteristics, and uncertainty in water quality assessments. To address these issues, this report recommends (1) limiting screened intervals to geologically appropriate zones, (2) extending recovery monitoring to ensure accurate estimation of aquifer properties, and (3) improving water sample quality control and ion balance verification.
In addition to presenting hydrogeologic data, this report provides educational materials tailored to DREAM stakeholders, illustrating groundwater properties such as drawdown and well yield, and engineering concepts like screen placement and well log interpretation. Overall, this work summarizes test and production well data, analyzes pump test results, and offers recommendations to support ongoing groundwater development for the DREAM pilot project and others like it
Small Satellites, Big Impact: Advancing Space Innovation from Earth to Orbit With the Catapult’s ISAM Test Facility
No full textThe In-orbit Servicing Assembly & Manufacturing (ISAM) Test Facility at Westcott, UK is a testbed providing realistic environmental conditions for orbital operations here on Earth, with the primary objective of accelerating the readiness level of emerging ISAM technologies and reducing the time to market for commercial space systems. As a result of continuous feedback from campaigns, the Facility has seen recent upgrades to both infrastructure and capabilities, which has created a unique operational environment that acts as an enabler for space activities in the UK and internationally. Moreover, as a constantly evolving system, it is uniquely positioned to adapt to user requirements, as existing features are tested and new feedback is received for improvements and upgrades. The Facility is not just a building; it is a combination of customised robotic systems, dedicated engineering and facilities teams with cross-disciplinary expertise, and the support of the wider Catapult in terms of world-leading experience in satellite applications
Orbital Decay Analysis of UAE Nanosatellites in Low Earth Orbit
No full textGiven the continuous efforts in the United Arab Emirates (UAE) to develop its local capabilities in space technology through the deployment of nanosatellites (cubesats) in Low Earth Orbit (LEO), understanding cubesats orbital dynamics and decay patterns is crucial for both future mission planning and space debris management. This study investigates the orbital decay characteristics of cubesats deployed by the UAE in LEO. We analyzed the orbital decay rates of seven UAE cubesats namely Nayif-1, Mysat-1, Meznsat, QMR-KWT, Ghalib, Dhabisat, and Light-1 by examining observational data, orbital parameters, and environmental factors. The results offer insights into the effectiveness of current satellite design practices in mitigating debris risks and inform future satellite missions and space policy. The findings contribute to the broader understanding of nanosatellite behavior in LEO and support the UAE’s objectives in advancing space technology and sustainability
Extremely Low-Cost Optical Receiver for Extremely Low Resource Optical Identifiers
No full textSpace object identification (SOI) is essential for space traffic management, situational awareness, and mission operations. The Extremely Low Resource Optical Identifier (ELROI), developed by Los Alamos National Laboratory, provides a persistent and interference-free identification method for small satellites through a self-powered optical beacon. ELROI transmits a unique identification code via low-power laser pulses, enabling ground stations to identify spaceborne assets without relying on traditional radio beacons. However, the efficacy of the ELROI system relies on the widespread availability of highly sensitive and cost-effective ground-based optical receivers. To address this need, we are developing a low-cost optical receiver capable of detecting and decoding ELROI signals, leveraging commercial off-the shelf (COTS) components and novel signal processing techniques. This research is based at the University of Auckland, with tests conducted at the Taiaho Observatory, a prototype optical ground station in New Zealand*. Furthermore, this group is developing Ko Au, a 1U Low Earth Orbit (LEO) CubeSat equipped with an ELROI-inspired, omnidirectional beacon. This mission will provide a full test of our ground-based receiver\u27s capability to detect and decode optical signals from orbital assets. The next steps in improving detection capabilities are also outlined, including long-range validation and possible collaborations for global deployment. By making ELROI-compatible optical receivers more accessible and affordable, the aim is to enable widespread adoption of optical identification for small satellites, contributing to improved space situational awareness and sustainable orbital operations
Attitude Control of a Floating Satellite (FloatSat) via Deep Reinforcement Learning
Get PDFIn this work, attitude determination and control (ADC) of a Floating–Satellite(FloatSat)1 through artificial intelligence is proposed. More specifically, Deep Reinforcement Learning (DRL) will be used to generate an optimal control policy for small satellites. This project evaluated an attitude control policy based on deep reinforcement learning using stable–baseline3 (a library which implements the DRL algorithms in PyTorch).2 This Artificially intelligent attitude control was realized for a one-dimensional laboratory-based satellite, which is specifically designed to train the students for satellites and their subsystems