A Comparison of Correlation-Agnostic Techniques for Magnetic Navigation

Navigation using a Global Navigation Satellite System (GNSS) is common for autonomous vehicles (ground or air). Unfortunately, GNSS-based navigation solutions are often susceptible to jamming, interference, and a limited number of satellites. A proposed technique to aid in navigation when a GNSS-based system fails is magnetic navigation - navigation using the Earth\u27s magnetic anomaly field. This solution comes with its own set of problems including the need for quality magnetic maps in every area in which magnetic navigation will be used. Many of the currently available magnetic maps are generated from a combination of dated magnetic surveys, resulting in maps riddled with spatially correlated errors, the correlation structure of which is largely unknown. The correlations are further confounded while navigating because they depend on how fast a vehicle moves through the map in addition to the original correlated error structure. Traditionally, this spatial correlation has been handled by introducing a First Order Gauss-Markov (FOGM) noise model into the estimation routine, with the FOGM parameters set somewhat arbitrarily. In this paper, we investigate the possibility of using correlation agnostic fusion techniques (i.e., Covariance Intersection and Probabilistically Conservative Fusion) for magnetic navigation. These techniques have the advantage of not requiring any parameter tuning; the same method and tuning parameters are used regardless of the spatial correlation. We demonstrate that utilizing probabilistically conservative fusion leads to navigation results that are better than many tuned approaches and reasonably close to the best possible tuning parameters of a FOGM

A number or a person?: perspectives on credit scoring and fair mortgage lending: article four in a five-part series

This fourth article in a five-part series on credit scoring showcases three different perspectives. Up for debate is how lenders can ensure fair treatment to all mortgage applicants and how consumers can be educated about the effect their credit score has on loan pricing.Mortgage loans

It\u27s Not Where You Start, It\u27s How You Finish: Predicting Law School and Bar Success

In this study, we examine the extent to which academic and student engagement factors explain law school grades and first-time bar exam performance. Applying fixed effects linear and logit modeling, our analysis leverages law student transcript data and responses to the Law School Survey of Student Engagement (LSSSE) among students from a diverse group of 20 law schools to estimate academic performance and odds of bar passage. Most notably, we find that GPA improvement during law school is associated with greater odds of passing the bar exam, particularly among students who struggle the most during the first semester. Furthermore, while we find that LSAT scores and undergraduate GPA are predictive (p \u3c 0.05) of both law school performance and bar success (as in previous research), these effects are quite modest. Based on these findings, we propose and discuss several recommendations. These should be helpful to higher education scholars and practitioners, particularly law school deans, administrators, faculty, and academic support staff

Depression Following a Traumatic Brain Injury: Uncovering Cytokine Dysregulation as a Pathogenic Mechanism

A substantial number of individuals have long-lasting adverse effects from a traumatic brain injury (TBI). Depression is one of these long-term complications that influences many aspects of life. Depression can limit the ability to return to work, and even worsen cognitive function and contribute to dementia. The mechanistic cause for the increased depression risk associated with a TBI remains to be defined. As TBI results in chronic neuroinflammation, and priming of glia to a secondary challenge, the inflammatory theory of depression provides a promising framework for investigating the cause of depression following a TBI. Increases in cytokines similar to those seen in depression in the general population are also increased following a TBI. Biomarker levels of cytokines peak within hours-to-days after the injury, yet pro-inflammatory cytokines may still be elevated above physiological levels months-to-years following TBI, which is the time frame in which post-TBI depression can persist. As tumor necrosis factor α and interleukin 1 can signal directly at the neuronal synapse, pathophysiological levels of these cytokines can detrimentally alter neuronal synaptic physiology. The purpose of this review is to outline the current evidence for the inflammatory hypothesis of depression specifically as it relates to depression following a TBI. Moreover, we will illustrate the potential synaptic mechanisms by which tumor necrosis factor α and interleukin 1 could contribute to depression. The association of inflammation with the development of depression is compelling; however, in the context of post-TBI depression, the role of inflammation is understudied. This review attempts to highlight the need to understand and treat the psychological complications of a TBI, potentially by neuroimmune modulation, as the neuropsychiatric disabilities can have a great impact on the rehabilitation from the injury, and overall quality of life

Weight-Bearing Asymmetry in Individuals Post-Hip Fracture During the Sit to Stand Task

Background: Individuals post hip fracture decrease force on the involved limb during sit to stand tasks, creating an asymmetry in vertical ground reaction force. Joint specific differences that underlie asymmetry of the vertical ground reaction force are unknown. The purpose of this study was to compare differences in vertical ground reaction force variables and joint kinetics at the hip and knee in participants post-hip fracture, who were recently discharged from home care physical therapy to controls. Methods: Forty-four community-dwelling older adults, 29 who had a hip fracture and 15 elderly control participant’s completed the sit to stand task on an instrumented chair with 3 force plates. T-tests were used to compare clinical tests (Berg Balance Scale, activity balance confidence and gait speed, isokinetic knee strength) and vertical ground reaction force variables. Two-way analyses of variance compared vertical ground reaction force variables and kinetics at the hip and knee between hip fracture and elderly control groups. Pearson correlation coefficients were used to determine correlations between clinical and vertical ground reaction force variables. Findings: Vertical ground reaction force variables were significantly lower on the involved side for the hip fracture group compared to the uninvolved side and controls. Lower involved side hip and knee moments and power contributed to lower involved side vertical ground reaction force. Vertical ground reaction force variables and strength had moderate to high correlations with clinical measures. Interpretation: Uninvolved side knee movements and powers were the largest contributors to asymmetrical vertical ground reaction force in participants post-hip fracture. The association of vertical ground reaction force variables and clinical measures of function suggesting reducing vertical ground reaction force asymmetry may contribute to higher levels of function post-hip fracture. Functional and strength training should target the involved knee to reduce vertical ground reaction force asymmetry. Background Individuals post hip fracture decrease force on the involved limb during sit to stand tasks, creating an asymmetry in vertical ground reaction force. Joint specific differences that underlie asymmetry of the vertical ground reaction force are unknown. The purpose of this study was to compare differences in vertical ground reaction force variables and joint kinetics at the hip and knee in participants post-hip fracture, who were recently discharged from homecare physical therapy to controls. Methods Forty-four community-dwelling older adults, 29 who had a hip fracture and 15 elderly control participant’s completed the sit to stand task on an instrumented chair with 3 force plates. T-tests were used to compare clinical tests (Berg Balance Scale, activity balance confidence and gait speed, isokinetic knee strength) and vertical ground reaction force variables. Two-way analyses of variance compared vertical ground reaction force variables and kinetics at the hip and knee between hip fracture and elderly control groups. Pearson correlation coefficients were used to determine correlations between clinical and vertical ground reaction force variables. Findings Vertical ground reaction force variables were significantly lower on the involved side for the hip fracture group compared to the uninvolved side and controls. Lower involved side hip and knee moments and power contributed to lower involved side vertical ground reaction force. Vertical ground reaction force variables and strength had moderate to high correlations with clinical measures. Interpretation Uninvolved side knee moments and powers were the largest contributors to asymmetrical vertical ground reaction force in participants post-hip fracture. The association of vertical ground reaction force variables and clinical measures of function suggesting reducing vertical ground reaction force asymmetry may contribute to higher levels of function post-hip fracture. Functional and strength training should target the involved knee to reduce vertical ground reaction force asymmetry

A search for rapidly pulsating hot subdwarf stars in the GALEX survey

NASA's Galaxy Evolution Explorer (GALEX) provided near- and far-UV observations for approximately 77 percent of the sky over a ten-year period; however, the data reduction pipeline initially only released single NUV and FUV images to the community. The recently released Python module gPhoton changes this, allowing calibrated time-series aperture photometry to be extracted easily from the raw GALEX data set. Here we use gPhoton to generate light curves for all hot subdwarf B (sdB) stars that were observed by GALEX, with the intention of identifying short-period, p-mode pulsations. We find that the spacecraft's short visit durations, uneven gaps between visits, and dither pattern make the detection of hot subdwarf pulsations difficult. Nonetheless, we detect UV variations in four previously known pulsating targets and report their UV pulsation amplitudes and frequencies. Additionally, we find that several other sdB targets not previously known to vary show promising signals in their periodograms. Using optical follow-up photometry with the Skynet Robotic Telescope Network, we confirm p-mode pulsations in one of these targets, LAMOST J082517.99+113106.3, and report it as the most recent addition to the sdBVr class of variable stars.Comment: 11 Pages, 8 Figures, Accepted for publication in the Astrophysical Journa

Regional Scale Dryland Vegetation Classification with an Integrated Lidar-Hyperspectral Approach

The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral mixture analysis (MESMA) for optical vegetation classification. Lidar-derived maximum vegetation height and delineated riparian zones were then used to modify the optical classification. Incorporating the lidar information into the classification scheme increased the overall accuracy from 60% to 89%. Canopy structure can have a strong influence on spectral variability and the lidar provided complementary information for SAM’s sensitivity to shape but not magnitude of the spectra. Similar approaches to map large regions of drylands with low uncertainty may be readily implemented with unmixing algorithms applied to upcoming space-based imaging spectroscopy and lidar. This study advances our understanding of the nuances associated with mapping xeric and mesic regions, and highlights the importance of incorporating complementary algorithms and sensors to accurately characterize the heterogeneity of dryland ecosystems