Building Height Using the UAS DJI Phantom 3 and Drone2Map Software

At Stephen F. Austin State University, the Arthur Temple College of Forestry and Agriculture has invested in the most current drone technology in order to keep up with the new trends in Geographic Information System (GIS). Students and faculty can fly the drone and get up to date images of the area. When it comes to analyzing data and creating maps, all measurements must be extremely accurate in order for the map to be reliable. With this in mind, the objective of this project is to determine if the height measurements from DJI Phantom 3 drone are as accurate as the real-world measurements

Accuracy of Unmanned Aerial System (Drone) Height Measurements

Vertical height estimates of earth surface features using an Unmanned Aerial System (UAS) are important in natural resource management quantitative assessments. An important research question concerns both the accuracy and precision of vertical height estimates acquired with a UAS and to determine if it is necessary to land a UAS between individual height measurements or if GPS derived height versus barometric pressure derived height while using a DJI Phantom 3 would affect height accuracy and precision. To examine this question, height along a telescopic height pole on the campus of Stephen F. Austin State University (SFASU) were estimated at 2, 5, 10 and 15 meters above ground using a DJI Phantom 3 UAS. The DJI Phantom 3 UAS (i.e., drone) was flown up and down the telescopic height pole to estimate height at the 2, 5, 10 and 15 meter locations using four different user controlled flight modes with a total of 30 observations per flight mode. Flight mode configurations consisted of having GPS estimate height while landing the drone between flights, non-GPS mode to estimate height via barometric pressure while landing the drone between flights, flying continuously up and down the height pole while estimating height with GPS on, and flying continuously up and down the height pole in non-GPS mode to estimate height via barometric pressure. A total of 480 height measurements were recorded (30 measurements per height interval per all four flight mode combinations). Standard deviation results indicated that height measurements taken with the drone were less precise when landing was not reset between measurements. Root mean square error (RMSE) analysis indicated that having the landing reset without GPS on achieved the highest accuracy of all measurements taken. An ANOVA conducted on the absolute errors reconfirmed that having the landing reset before each height measurement using the drone achieved higher accuracy compared to flying the drone continuously. This indicates the practical application of height measurement of the DJI Phantom 3 UAS and the importance of resetting the UAS before each height measurement

Accuracy of Unmanned Aerial System (Drone) Height Measurements

Vertical height estimates of earth surface features using an Unmanned Aerial System (UAS) are important in natural resource management quantitative assessments. An important research question concerns both the accuracy and precision of vertical height estimates acquired with a UAS and to determine if it is necessary to land a UAS between individual height measurements or if GPS derived height versus barometric pressure derived height while using a DJI Phantom 3 would affect height accuracy and precision. To examine this question, height along a telescopic height pole on the campus of Stephen F. Austin State University (SFASU) were estimated at 2, 5, 10 and 15 meters above ground using a DJI Phantom 3 UAS. The DJI Phantom 3 UAS (i.e., drone) was flown up and down the telescopic height pole to estimate height at the 2, 5, 10 and 15 meter locations using four different user controlled flight modes with a total of 30 observations per flight mode. Flight mode configurations consisted of having GPS estimate height while landing the drone between flights, non-GPS mode to estimate height via barometric pressure while landing the drone between flights, flying continuously up and down the height pole while estimating height with GPS on, and flying continuously up and down the height pole in non-GPS mode to estimate height via barometric pressure. A total of 480 height measurements were recorded (30 measurements per height interval per all four flight mode combinations). Standard deviation results indicated that height measurements taken with the drone were less precise when landing was not reset between measurements. Root mean square error (RMSE) analysis indicated that having the landing reset without GPS on achieved the highest accuracy of all measurements taken. An ANOVA conducted on the absolute errors reconfirmed that having the landing reset before each height measurement using the drone achieved higher accuracy compared to flying the drone continuously. This indicates the practical application of height measurement of the DJI Phantom 3 UAS and the importance of resetting the UAS before each height measurement

Integrating Faculty Led Service Learning Training to Quantify Height of Natural Resources from a Spatial Science Perspective

Arthur Temple College of Forestry and Agriculture (ATCOFA) faculty members were trained how to integrate service learning activities within senior level classes at Stephen F. Austin State University (SFASU) in Nacogdoches, Texas. The service learning training, taught under the acronym Mentored Undergraduate Scholarship (MUGS), involved meeting with fellow faculty members over the course of an academic year during the fall semester to first learn how to incorporate service learning activities in a senior level class followed by its incorporation into a class the following spring semester. The service learning model was applied to students in GIS 420, a senior level Landscape Modeling, Spatial Analysis, and Quantitative Assessment course within ATCOFA. The students were instructed within a hands-on interactive environment on how to use geospatial analysis to quantify natural resources. The overall goal was for a student to demonstrate proficiency in understanding how to apply aerial photo interpretation, satellite remote sensing, global positioning system and geographic information systems technology to quantify, qualify, map, monitor and manage natural and environmental resources at the local and landscape scales. Students applied this concept within a quantitative resource assessment, whereby students compared the conventional methodology of measuring height of vertical features within a landscape using a clinometer with the newer ways of measuring height using Pictometry hyperspatial imagery and drone acquired digital imagery. Conventional results were compared to newer technological methodologies to determine the most efficient and accurate way to quantify vertical resources from a spatial perspective

Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (Harmony Outcomes): a double-blind, randomised placebo-controlled trial

Background: Glucagon-like peptide 1 receptor agonists differ in chemical structure, duration of action, and in their effects on clinical outcomes. The cardiovascular effects of once-weekly albiglutide in type 2 diabetes are unknown. We aimed to determine the safety and efficacy of albiglutide in preventing cardiovascular death, myocardial infarction, or stroke. Methods: We did a double-blind, randomised, placebo-controlled trial in 610 sites across 28 countries. We randomly assigned patients aged 40 years and older with type 2 diabetes and cardiovascular disease (at a 1:1 ratio) to groups that either received a subcutaneous injection of albiglutide (30–50 mg, based on glycaemic response and tolerability) or of a matched volume of placebo once a week, in addition to their standard care. Investigators used an interactive voice or web response system to obtain treatment assignment, and patients and all study investigators were masked to their treatment allocation. We hypothesised that albiglutide would be non-inferior to placebo for the primary outcome of the first occurrence of cardiovascular death, myocardial infarction, or stroke, which was assessed in the intention-to-treat population. If non-inferiority was confirmed by an upper limit of the 95% CI for a hazard ratio of less than 1·30, closed testing for superiority was prespecified. This study is registered with ClinicalTrials.gov, number NCT02465515. Findings: Patients were screened between July 1, 2015, and Nov 24, 2016. 10 793 patients were screened and 9463 participants were enrolled and randomly assigned to groups: 4731 patients were assigned to receive albiglutide and 4732 patients to receive placebo. On Nov 8, 2017, it was determined that 611 primary endpoints and a median follow-up of at least 1·5 years had accrued, and participants returned for a final visit and discontinuation from study treatment; the last patient visit was on March 12, 2018. These 9463 patients, the intention-to-treat population, were evaluated for a median duration of 1·6 years and were assessed for the primary outcome. The primary composite outcome occurred in 338 (7%) of 4731 patients at an incidence rate of 4·6 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an incidence rate of 5·9 events per 100 person-years in the placebo group (hazard ratio 0·78, 95% CI 0·68–0·90), which indicated that albiglutide was superior to placebo (p<0·0001 for non-inferiority; p=0·0006 for superiority). The incidence of acute pancreatitis (ten patients in the albiglutide group and seven patients in the placebo group), pancreatic cancer (six patients in the albiglutide group and five patients in the placebo group), medullary thyroid carcinoma (zero patients in both groups), and other serious adverse events did not differ between the two groups. There were three (<1%) deaths in the placebo group that were assessed by investigators, who were masked to study drug assignment, to be treatment-related and two (<1%) deaths in the albiglutide group. Interpretation: In patients with type 2 diabetes and cardiovascular disease, albiglutide was superior to placebo with respect to major adverse cardiovascular events. Evidence-based glucagon-like peptide 1 receptor agonists should therefore be considered as part of a comprehensive strategy to reduce the risk of cardiovascular events in patients with type 2 diabetes. Funding: GlaxoSmithKline

The large enriched germanium experiment for neutrinoless double beta decay (LEGEND)

The observation of neutrinoless double-beta decay (0νββ) would show that lepton number is violated, reveal that neu-trinos are Majorana particles, and provide information on neutrino mass. A discovery-capable experiment covering the inverted ordering region, with effective Majorana neutrino masses of 15 − 50 meV, will require a tonne-scale experiment with excellent energy resolution and extremely low backgrounds, at the level of ∼0.1 count /(FWHM·t·yr) in the region of the signal. The current generation 76Ge experiments GERDA and the Majorana Demonstrator, utilizing high purity Germanium detectors with an intrinsic energy resolution of 0.12%, have achieved the lowest backgrounds by over an order of magnitude in the 0νββ signal region of all 0νββ experiments. Building on this success, the LEGEND collaboration has been formed to pursue a tonne-scale 76Ge experiment. The collaboration aims to develop a phased 0νββ experimental program with discovery potential at a half-life approaching or at 1028 years, using existing resources as appropriate to expedite physics results.JRC.G.2-Standards for Nuclear Safety, Security and Safeguard

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating.Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 7