STREAMS DO WORK: MEASURING THE WORK OF LOW-ORDER STREAMS ON THE LANDSCAPE USING POINT CLOUDS

The mutable nature of low-order streams makes regular updating of surface water maps necessary for accurate representation. Low-order streams make up roughly half the streams in the conterminous United States by length, and small inaccuracies in stream head location can result in significant error in stream reach, order, and density. Reliable maps of stream features are vital for hydrologic modeling, ecosystem research, and boundary monitoring. High resolution digital elevation models derived from lidar data have shown promise in low order stream modeling yet forested high relief landscapes and low relief agricultural areas remain challenging. Here we present early results from research analyzing lidar point clouds to identify features and patterns that may be used in low-order stream identification and classification in challenging geographic conditions. This work has identified characteristics derived from point clouds that correlate with the presence of streams and stream heads and show promise for mapping small streams. In low topographic relief agricultural areas, cross sections collected at regular intervals along drainage channels extracted as 3D lines show a significant jump in value and variance of profile curvature standard deviation at stream heads. In high relief areas, observations show potential for stream mapping by identifying trends in riparian zone structure. Lidar return point density from riparian vegetation under 30 feet tall dips in the vicinity of intermittent stream heads. Also seen is an increase in point density above 60 feet downstream of stream heads. The trends found here likely reflect a change in vegetation structure relative to the presence of streams

AUTOMATED ROAD BREACHING TO ENHANCE EXTRACTION OF NATURAL DRAINAGE NETWORKS FROM ELEVATION MODELS THROUGH DEEP LEARNING

High-resolution (HR) digital elevation models (DEMs), such as those at resolutions of 1 and 3 meters, have increasingly become more widely available, along with lidar point cloud data. In a natural environment, a detailed surface water drainage network can be extracted from a HR DEM using flow-direction and flow-accumulation modeling. However, elevation details captured in HR DEMs, such as roads and overpasses, can form barriers that incorrectly alter flow accumulation models, and hinder the extraction of accurate surface water drainage networks. This study tests a deep learning approach to identify the intersections of roads and stream valleys, whereby valley channels can be burned through road embankments in a HR DEM for subsequent flow accumulation modeling, and proper natural drainage network extraction

Technoeconomic Analysis of Changing PV Array Convective Cooling Through Changing Array Spacing

Accuracy in photovoltaic (PV) module temperature modeling is crucial to achieving precision in energy performance yield calculations and subsequent economic evaluations of PV projects. While there have been numerous approaches to PV temperature modeling based on both the steady-state and transient thermal assumptions, there have been few attempts to account for changing convective cooling on PV module surfaces resulting from changes in the PV system layout. Changes in system row spacing, in particular, can have a meaningful impact on module electrical efficiency and subsequent economic performance, even when considering additional costs from the changes in row spacing. Using a heat transfer approach based on the spatial definition of a PV array, technoeconomic analyses of different plant configurations are presented here that show an improved system levelized cost of energy (LCOE) for fixed-tilt PV systems when increasing system row spacing. These LCOE improvements have been found to be as high as 2.15% in climates characterized by low ambient temperatures and higher average annual wind speeds in U.S. climates. While the LCOE improvements are primarily driven by incident irradiance changes for altered row spacing, the waterfall analysis of the different components of changing system LCOE show that modifications in the heat transfer dynamics have a 0.5% contribution to the LCOE reduction for the largest LCOE, compared with a 3.3% reduction from irradiance changes

Variation in contrast-associated acute kidney injury prophylaxis for percutaneous coronary intervention: Insights from the Veterans Affairs Clinical Assessment, Reporting, and Tracking (CART) program

BACKGROUND: Contrast-Associated Acute Kidney Injury (CA-AKI) is a serious complication associated with percutaneous coronary intervention (PCI). Patients with chronic kidney disease (CKD) have an elevated risk for developing this complication. Although CA-AKI prophylactic measures are available, the supporting literature is variable and inconsistent for periprocedural hydration and N-acetylcysteine (NAC), but is stronger for contrast minimization. METHODS: We assessed the prevalence and variability of CA-AKI prophylaxis among CKD patients undergoing PCI between October 2007 and September 2015 in any cardiac catheterization laboratory in the VA Healthcare System. Prophylaxis included periprocedural hydration with normal saline or sodium bicarbonate, NAC, and contrast minimization (contrast volume to glomerular filtration rate ratio ≤ 3). Multivariable hierarchical logistic regression models quantified site-specific prophylaxis variability. As secondary analyses, we also assessed CA-AKI prophylaxis measures in all PCI patients regardless of kidney function, periprocedural hydration in patients with comorbid CHF, and temporal trends in CA-AKI prophylaxis. RESULTS: From 2007 to 2015, 15,729 patients with CKD underwent PCI. 6928 (44.0%) received periprocedural hydration (practice-level median rate 45.3%, interquartile range (IQR) 35.5-56.7), 5107 (32.5%) received NAC (practice-level median rate 28.3%, IQR 22.8-36.9), and 4656 (36.0%) received contrast minimization (practice-level median rate 34.5, IQR 22.6-53.9). After adjustment for patient characteristics, there was significant site variability with a median odds ratio (MOR) of 1.80 (CI 1.56-2.08) for periprocedural hydration, 1.95 (CI 1.66-2.29) for periprocedural hydration or NAC, and 2.68 (CI 2.23-3.15) for contrast minimization. These trends were similar among all patients (with and without CKD) undergoing PCI. Among patients with comorbid CHF (n = 5893), 2629 (44.6%) received periprocedural hydration, and overall had less variability in hydration (MOR of 1.56 (CI 1.38-1.76)) compared to patients without comorbid CHF (1.89 (CI 1.65-2.18)). Temporal trend analysis showed a significant and clinically relevant decrease in NAC use (64.1% of cases in 2008 (N = 1059), 6.2% of cases in 2015 (N = 128, p = \u3c 0.0001)) and no significant change in contrast-minimization (p = 0.3907). CONCLUSIONS: Among patients with CKD undergoing PCI, there was low utilization and significant site-level variability for periprocedural hydration and NAC independent of patient-specific risk. This low utilization and high variability, however, was also present for contrast minimization, a well-established measure. These findings suggest that a standardized approach to CA-AKI prophylaxis, along with continued development of the evidence base, is needed

Characterization of the Gut Microbiota among Veterans with Unique Military-related Exposures and High Prevalence of Chronic Health Conditions: A United States-Veteran Microbiome Project (US-VMP) Study

The gut microbiome is impacted by environmental exposures and has been implicated in many physical and mental health conditions, including anxiety disorders, affective disorders, and trauma- and stressor-related disorders such as posttraumatic stress disorder (PTSD). United States (US) military Veterans are a unique population in that their military-related exposures can have consequences for both physical and mental health, but the gut microbiome of this population has been understudied. In this publication, we describe exposures, health conditions, and medication use of Veterans in the US Veteran Microbiome Project (US-VMP) and examine the associations between these characteristics and the gut microbiota. This cohort included 331 US Veterans seeking healthcare with the Veterans Health Administration who were 83% male with an average (±SD) age of 47.6 ± 13.4 years. The cohort displayed a high prevalence of PTSD (49.8%) and history of traumatic brain injuries (76.1%), and high current use of prescription medications (74.9%) to treat various acute and chronic conditions. We observed significant associations between the gut microbiota composition and gastroenteritis, peripheral vascular disease (PVD), bipolar disorders, symptoms of severe depression based on the Beck Depression Inventory, stimulant and opioid use disorders, beta-blockers, serotonin and norepinephrine reuptake inhibitor antidepressants, diabetes medications, and proton pump inhibitors. Many of the Veteran characteristics examined were associated with altered relative abundances of specific taxa. We found that PVD and cardiovascular disease were associated with lower microbiota diversity in the gut (i.e., α-diversity), while supplemental vitamin use was associated with higher α-diversity. Our study contributes novel insights as to whether the unique exposures of Veterans in this cohort correlate with gut microbiota characteristics and, in line with previous findings with other population-level studies of the microbiome, confirms associations between numerous health conditions and medications with the gut microbiome. © 2021 The Author

Military-Related Exposures, Social Determinants of Health, and Dysbiosis: The United States-Veteran Microbiome Project (US-VMP)

Significant effort has been put forth to increase understanding regarding the role of the human microbiome in health- and disease-related processes. In turn, the United States (US) Veteran Microbiome Project (US-VMP) was conceptualized as a means by which to serially collect microbiome and health-related data from those seeking care within the Veterans Health Administration (VHA). In this manuscript, exposures related to military experiences, as well as conditions and health-related factors among patients seen in VHA clinical settings are discussed in relation to common psychological and physical outcomes. Upon enrollment in the study, Veterans complete psychometrically sound (i.e., reliable and valid) measures regarding their past and current medical history. Participants also provide skin, oral, and gut microbiome samples, and permission to track their health status via the VHA electronic medical record. To date, data collection efforts have been cross-diagnostic. Within this manuscript, we describe current data collection practices and procedures, as well as highlight demographic, military, and psychiatric characteristics of the first 188 Veterans enrolled in the study. Based on these findings, we assert that this cohort is unique as compared to those enrolled in recent large-scale studies of the microbiome. To increase understanding regarding disease and health among diverse cohorts, efforts such as the US-VMP are vital. Ongoing barriers and facilitators to data collection are discussed, as well as future research directions, with an emphasis on the importance of shifting current thinking regarding the microbiome from a focus on normalcy and dysbiosis to health promotion and disease prevention

Military-Related Exposures, Social Determinants of Health, and Dysbiosis: The United States-Veteran Microbiome Project (US-VMP)

Significant effort has been put forth to increase understanding regarding the role of the human microbiome in health- and disease-related processes. In turn, the United States (US) Veteran Microbiome Project (US-VMP) was conceptualized as a means by which to serially collect microbiome and health-related data from those seeking care within the Veterans Health Administration (VHA). In this manuscript, exposures related to military experiences, as well as conditions and health-related factors among patients seen in VHA clinical settings are discussed in relation to common psychological and physical outcomes. Upon enrollment in the study, Veterans complete psychometrically sound (i.e., reliable and valid) measures regarding their past and current medical history. Participants also provide skin, oral, and gut microbiome samples, and permission to track their health status via the VHA electronic medical record. To date, data collection efforts have been cross-diagnostic. Within this manuscript, we describe current data collection practices and procedures, as well as highlight demographic, military, and psychiatric characteristics of the first 188 Veterans enrolled in the study. Based on these findings, we assert that this cohort is unique as compared to those enrolled in recent large-scale studies of the microbiome. To increase understanding regarding disease and health among diverse cohorts, efforts such as the US-VMP are vital. Ongoing barriers and facilitators to data collection are discussed, as well as future research directions, with an emphasis on the importance of shifting current thinking regarding the microbiome from a focus on normalcy and dysbiosis to health promotion and disease prevention

Military-Related Exposures, Social Determinants of Health, and Dysbiosis: The United States-Veteran Microbiome Project (US-VMP)

Significant effort has been put forth to increase understanding regarding the role of the human microbiome in health- and disease-related processes. In turn, the United States (US) Veteran Microbiome Project (US-VMP) was conceptualized as a means by which to serially collect microbiome and health-related data from those seeking care within the Veterans Health Administration (VHA). In this manuscript, exposures related to military experiences, as well as conditions and health-related factors among patients seen in VHA clinical settings are discussed in relation to common psychological and physical outcomes. Upon enrollment in the study, Veterans complete psychometrically sound (i.e., reliable and valid) measures regarding their past and current medical history. Participants also provide skin, oral, and gut microbiome samples, and permission to track their health status via the VHA electronic medical record. To date, data collection efforts have been cross-diagnostic. Within this manuscript, we describe current data collection practices and procedures, as well as highlight demographic, military, and psychiatric characteristics of the first 188 Veterans enrolled in the study. Based on these findings, we assert that this cohort is unique as compared to those enrolled in recent large-scale studies of the microbiome. To increase understanding regarding disease and health among diverse cohorts, efforts such as the US-VMP are vital. Ongoing barriers and facilitators to data collection are discussed, as well as future research directions, with an emphasis on the importance of shifting current thinking regarding the microbiome from a focus on normalcy and dysbiosis to health promotion and disease prevention

Animal tissue-based quantitative comparison of dual-energy CT to SPR conversion methods using high-resolution gel dosimetry

Dual-energy computed tomography (DECT) has been shown to allow for more accurate ion therapy treatment planning by improving the estimation of tissue stopping power ratio (SPR) relative to water, among other tissue properties. In this study, we measured and compared the accuracy of SPR values derived using both dual- and single-energy CT (SECT) based on different published conversion algorithms. For this purpose, a phantom setup containing either fresh animal soft tissue samples (beef, pork) and a water reference or tissue equivalent plastic materials was designed and irradiated in a clinical proton therapy facility. Dosimetric polymer gel was positioned downstream of the samples to obtain a three-dimensional proton range distribution with high spatial resolution. The mean proton range in gel for each tissue relative to the water sample was converted to a SPR value. Additionally, the homogeneous samples were probed with a variable water column encompassed by two ionization chambers to benchmark the SPR accuracy of the gel dosimetry. The SPR values measured with both methods were consistent with a mean deviation of 0.2%, but the gel dosimetry captured range variations up to 5 mm within individual samples. Across all fresh tissue samples the SECT approach yielded significantly greater mean absolute deviations from the SPR deduced using gel range measurements, with an average difference of 1.2%, compared to just 0.3% for the most accurate DECT-based algorithm. These results show a significant advantage of DECT over SECT for stopping power prediction in a realistic setting, and for the first time allow to compare a large set of methods under the same conditions