Autonomous Vehicles Operating Collaboratively to Avoid Debris and Obstructions

The purpose of this project is to demonstrate the safety and increased fuel efficiency of an automated collision avoidance system in collaborative vehicle platooning. This project was cosponsored by Daimler Trucks North America headquartered in Portland, Oregon, as well as Dr. Birdsong, and Dr. DeBruhl of Cal Poly. The mechanical engineering team consists of Cole Oppenheim, James Gildart, Toan Le, and Kyle Bybee who worked in coordination with a team of computer engineers. Vehicle platooning is a driving technique to increase the fuel efficiency of a group of vehicles by following a lead vehicle closely to reduce the drag experienced by the group. Specifically, large tractor trailer trucks could become more efficient utilizing vehicle platooning. To implement this system most effectively would require an automatic system for collision avoidance. The goal for the mechanical engineering team working on this project was build and design two scale model vehicles, a test track, and dynamic models of the vehicles. These were then interface with computer vision software and hardware (created in collaboration of a team of computer engineers) that allows the vehicles to autonomously platoon and avoid objects that would otherwise cause a collision. Interactions with the computer engineering team occurred at minimum on a weekly basis and more whenever necessary. Interactions between the team’s original occurred as meetings to determine each team individual progress until integration could be accomplished. When the systems were being integrated, meetings occurred regularly (2-3 times a week) to ensure the vehicles could properly execute their design function. The goal of this project is to demonstrate how this system could be implemented in truck platooning safely and to demonstrate the advantages of platooning with system developed. This project was intended and will be presented to compete at the Enhanced Safety of Vehicles conference in the Netherlands in June of 2019. This report covers the scope of work of this project, the preliminary design direction, and the final design direction, and the final design for the assembly of the two 1/10 scale cars, the track design, and the controls strategy to interface with the CPE’s software

Feasibility of brain age predictions from clinical T1-weighted MRIs

An individual's brain predicted age minus chronological age (brain-PAD) obtained from MRIs could become a biomarker of disease in research studies. However, brain age reports from clinical MRIs are scant despite the rich clinical information hospitals provide. Since clinical MRI protocols are meant for specific clinical purposes, performance of brain age predictions on clinical data need to be tested. We explored the feasibility of using DeepBrainNet, a deep network previously trained on research-oriented MRIs, to predict the brain ages of 840 patients who visited 15 facilities of a health system in Florida. Anticipating a strong prediction bias in our clinical sample, we characterized it to propose a covariate model in group-level regressions of brain-PAD (recommended to avoid Type I, II errors), and tested its generalizability, a requirement for meaningful brain age predictions in new single clinical cases. The best bias-related covariate model was scanner-independent and linear in age, while the best method to estimate bias-free brain ages was the inverse of a scanner-independent and quadratic in brain age function. We demonstrated the feasibility to detect sex-related differences in brain-PAD using group-level regression accounting for the selected covariate model. These differences were preserved after bias correction. The Mean-Average Error (MAE) of the predictions in independent data was ∼8 years, 2-3 years greater than reports for research-oriented MRIs using DeepBrainNet, whereas an R2 (assuming no bias) was 0.33 and 0.76 for the uncorrected and corrected brain ages, respectively. DeepBrainNet on clinical populations seems feasible, but more accurate algorithms or transfer-learning retraining is needed

Lake-size dependency of wind shear and convection as controls on gas exchange

High-frequency physical observations from 40 temperate lakes were used to examine the relative contributions of wind shear (u*) and convection (w*) to turbulence in the surface mixed layer. Seasonal patterns of u* and w* were dissimilar; u* was often highest in the spring, while w * increased throughout the summer to a maximum in early fall. Convection was a larger mixed-layer turbulence source than wind shear (u */w*-1 for lakes* and w* differ in temporal pattern and magnitude across lakes, both convection and wind shear should be considered in future formulations of lake-air gas exchange, especially for small lakes. © 2012 by the American Geophysical Union.Jordan S. Read, David P. Hamilton, Ankur R. Desai, Kevin C. Rose, Sally MacIntyre, John D. Lenters, Robyn L. Smyth, Paul C. Hanson, Jonathan J. Cole, Peter A. Staehr, James A. Rusak, Donald C. Pierson, Justin D. Brookes, Alo Laas, and Chin H. W

The Validity and Reliability of Commercially Available Resistance Training Monitoring Devices: A Systematic Review

Background Monitoring resistance training has a range of unique difficulties due to differences in physical characteristics and capacity between athletes, and the indoor environment in which it often occurs. Traditionally, methods such as volume load have been used, but these have inherent flaws. In recent times, numerous portable and affordable devices have been made available that purport to accurately and reliably measure kinetic and kinematic outputs, potentially offering practitioners a means of measuring resistance training loads with confidence. However, a thorough and systematic review of the literature describing the reliability and validity of these devices has yet to be undertaken, which may lead to uncertainty from practitioners on the utility of these devices. Objective A systematic review of studies that investigate the validity and/or reliability of commercially available devices that quantify kinetic and kinematic outputs during resistance training. Methods Following PRISMA guidelines, a systematic search of SPORTDiscus, Web of Science, and Medline was performed; studies included were (1) original research investigations; (2) full-text articles written in English; (3) published in a peer-reviewed academic journal; and (4) assessed the validity and/or reliability of commercially available portable devices that quantify resistance training exercises. Results A total of 129 studies were retrieved, of which 47 were duplicates. The titles and abstracts of 82 studies were screened and the full text of 40 manuscripts were assessed. A total of 31 studies met the inclusion criteria. Additional 13 studies, identified via reference list assessment, were included. Therefore, a total of 44 studies were included in this review. Conclusion Most of the studies within this review did not utilise a gold-standard criterion measure when assessing validity. This has likely led to under or overreporting of error for certain devices. Furthermore, studies that have quantified intradevice reliability have often failed to distinguish between technological and biological variability which has likely altered the true precision of each device. However, it appears linear transducers which have greater accuracy and reliability compared to other forms of device. Future research should endeavour to utilise gold-standard criterion measures across a broader range of exercises (including weightlifting movements) and relative loads

The Velocity Function of Galaxies

We present a galaxy circular velocity function, Psi(log v), derived from existing luminosity functions and luminosity-velocity relations. Such a velocity function is desirable for several reasons. First, it enables an objective comparison of luminosity functions obtained in different bands and for different galaxy morphologies, with a statistical correction for dust extinction. In addition, the velocity function simplifies comparison of observations with predictions from high-resolution cosmological N-body simulations. We derive velocity functions from five different data sets and find rough agreement among them, but about a factor of 2 variation in amplitude. These velocity functions are then compared with N-body simulations of a LCDM model (corrected for baryonic infall) in order to demonstrate both the utility and current limitations of this approach. The number density of dark matter halos and the slope of the velocity function near v_*, the circular velocity corresponding to an ~L_* spiral galaxy, are found to be comparable to that of observed galaxies. The primary sources of uncertainty in construction of Psi(log v) from observations and N-body simulations are discussed and explanations are suggected to account for these discrepancies.Comment: Latex. 28 pages, 4 figures. Accepted by Ap

Distinct patterns of neurodegeneration after TBI and in Alzheimer's disease

INTRODUCTION: Traumatic brain injury (TBI) is a dementia risk factor, with Alzheimer's disease (AD) more common following injury. Patterns of neurodegeneration produced by TBI can be compared to AD and aging using volumetric MRI. METHODS: A total of 55 patients after moderate to severe TBI (median age 40), 45 with AD (median age 69), and 61 healthy volunteers underwent magnetic resonance imaging over 2 years. Atrophy patterns were compared. RESULTS: AD patients had markedly lower baseline volumes. TBI was associated with increased white matter (WM) atrophy, particularly involving corticospinal tracts and callosum, whereas AD rates were increased across white and gray matter (GM). Subcortical WM loss was shared in AD/TBI, but deep WM atrophy was TBI-specific and cortical atrophy AD-specific. Post-TBI atrophy patterns were distinct from aging, which resembled AD. DISCUSSION: Post-traumatic neurodegeneration 1.9-4.0 years (median) following moderate-severe TBI is distinct from aging/AD, predominantly involving central WM. This likely reflects distributions of axonal injury, a neurodegeneration trigger. HIGHLIGHTS: We compared patterns of brain atrophy longitudinally after moderate to severe TBI in late-onset AD and healthy aging. Patients after TBI had abnormal brain atrophy involving the corpus callosum and other WM tracts, including corticospinal tracts, in a pattern that was specific and distinct from AD and aging. This pattern is reminiscent of axonal injury following TBI, and atrophy rates were predicted by the extent of axonal injury on diffusion tensor imaging, supporting a relationship between early axonal damage and chronic neurodegeneration