Classifying Forest Structure of Red-Cockaded Woodpecker Habitat Using Structure from Motion Elevation Data De-Rived from sUAS Imagery

Small unmanned aerial systems (sUAS) and relatively new photogrammetry software solutions are creating opportunities for forest managers to perform spatial analysis more efficiently and cost-effectively. This study aims to identify a method for leveraging these technologies to analyze vertical forest structure of red-cockaded woodpecker habitat in Montgomery County, Texas. Traditional sampling methods would require numerous hours of ground surveying and data collection using various measuring techniques. Structure from Motion (SfM), a photogrammetric method for creating 3-D structure from 2-D images, provides an alternative to relatively expensive LIDAR sensing technologies and can accurately model the high level of complexity found within our study area’s vertical structure. DroneDeploy, a photogrammetry processing app service, was used to post-process and create a point cloud, which was later further processed into a Canopy Height Model (CHM). Using supervised, object-based classification and comparing multiple classifier algorithms, classifications maps were generated with a best overall accuracy of 84.8% using Support Vector Machine in ArcGIS Pro software. Appropriately sized training sample datasets, correctly processed elevation data, and proper image segmentation were among the major factors impacting classification accuracy during the numerous classification iterations performed.

Vertebrate Subfossil Localities in Taylorsville MetroPark, Montgomery County, Ohio, USA

Karst features in the Silurian dolomites of Taylorsville MetroPark (Dayton Metropolitan Area, Ohio, United States) were explored from 2017 to 2018 to identify sites of paleontological interest. Initial landscape surveys recovered 124 skeletal elements (from 12 sites) that were attributed to 17 vertebrate species—including evidence of such extirpated animals as bobcats (Lynx rufus) and rattlesnakes (Crotalus sp.). Of the 12 sites, 9 sites contained remains from the historical era and 3 sites contained much older remains (n = 17) that were radiocarbon dated to approximately 1,400 years before present (YBP). Human remains at one site, butchered bones at another, and artifacts from a third suggest a long period of pre-colonial human use of the area. The presence of rare taxa expands pre-historical species lists and confirms the coexistence of many previously undocumented taxa from the area during the late, pre-colonial, Holocene Epoch.

No local birth sex ratio changes following the August 2019 shootings in Montgomery county, Ohio and in El Paso county, Texas

Objective In humans, males are born slightly in excess of females. Many factors have been shown to affect this ratio, including stressful events such as terrorist attacks. Two shootings in 2019 occurred in early August 2019 in the United States: in the Oregon District in Dayton, Montgomery county, Ohio and in El Paso county, Texas. This study was carried out in order to identify whether there were any effects on sex ratio at birth at state or county level 3-5 months later. Subject and Methods Births by sex, month of birth (2015-2019) and county were obtained for Ohio and Texas from the website of Centers for Disease Control and Prevention. Ordinary linear logistic regression was used to assess the time trend in the probability of boys and to investigate changes in the trend functions. Poisson regression (SAS GENMOD) and linear logistic regression using SAS procedure LOGISTIC was applied. Results This study analysed 2,623,714 live births, 1,939,938 in Texas (sex odds (SO) 1.044) and 683,776 in Ohio (SO 1.045). The only significant effect noted was seasonality (month) at the state level. Conclusion It has been postulated that male foetal loss in pregnant women during stressful periods may occur in accordance with the Trivers-Willard Hypothesis. Several studies have found significant effects after terrorist attacks in the United States (as well as in other countries) but this study failed to do so. This may be due to several reasons including underpowered datasets and the possibility that populations may be becoming relatively immured to these events.

145. SARS-CoV-2 (COVID-19) Testing Experience within a Military Treatment Facility

Background The Walter Reed National Military Medical Center (WRNMMC) established a consolidated COVID-19 screening area (CSA) beginning in March 2020 to provide beneficiary and staff testing via a drive-through site. Testing was available to all patients and WRNMMC staff regardless of beneficiary status. Presented is a descriptive analysis of our testing operations and positivity rates within a closed medical system from March 2020 to April 2021. Methods For quality and process improvement, we compiled daily testing logs from March 2020 to April 2021 from the CSA. These logs included patient demographics, reason for testing, test result, testing platform, and occupational status at the hospital. We determined positivity rates in various subgroups – asymptomatic, symptomatic, pre-operative, in order to track testing use and access. Additionally, we compared the overall positivity rate to the surrounding civilian community by pulling data from the Maryland Department of Health’s COVID database. Results Over the course of nearly 14 months of testing availability, 34,694 beneficiaries were screened with 41,582 individual tests. After May 2020, the monthly overall positivity rate varied from 1.99% to 11.92%, peaking in December 2020 (with high rates in November 2020, 7.52% and January 2021, 9.53%), correlating with or exceeding elevated positivity rates in Montgomery County (November 2020: 4.91%; December 2020: 6.48%; January 2021: 6.51%). When examining only symptomatic individuals, the positivity rate is notably much higher, with monthly rates varying from 6.40% to 21.10%, with a similar peak in December 2020. After full implementation of pre-operative screening for procedures with aerosolization potential in June 2020, the range of positivity rates was 0.28%-1.66%. Since vaccination for COVID-19 became widely available beginning in Feb 2021, the preoperative positivity rate has remained below 0.85%. Conclusion Our institutional experience is unique in its ability to offer universal access to COVID-19 testing for beneficiaries and staff of the DoD under direction of the ID service. Our process serves as a model for public and occupational health response, and may guide lab resource and real-time staffing management in support of COVID-19 diagnostics at a medical center. Disclosures All Authors: No reported disclosures

Land subsidence and aquifer compaction in Montgomery County, Texas, U.S.: 2000–2020

Groundwater-withdrawal-induced land subsidence has been a big concern in Montgomery County, Texas, U.S. since the 2000s. As of 2020, approximately half of the entire county is experiencing subsidence over 5 mm/year. This study aims to investigate ongoing land subsidence in Montgomery County using groundwater-level, extensometer, and GPS datasets. According to this study, land subsidence in Montgomery County since the mid-2000s is primarily contributed by sediment compaction in the Evangeline and Jasper aquifers; the compaction of Jasper aquifer contributes approximately one-third of the land subsidence since the mid-2000s; the pre-consolidation heads of the Chicot, Evangeline, and Jasper aquifers in Montgomery County are close to each other, approximately 15–25 m below mean sea level; the virgin-compaction/head-decline ratio is approximately 1:250 in the Evangeline aquifer and 1:800 in the Jasper aquifer in central and southern Montgomery County. As of 2020, the Jasper groundwater-level altitude is approximately 20–40 m below the pre-consolidation head in the central and southern Montgomery County; the Evangeline groundwater-level altitude is about 40–60 m below the pre-consolidation head. Land subsidence will continue to occur as long as the groundwater-level altitude in either the Evangeline or the Jasper aquifer remains below the pre-consolidation head.

They Deserve Better: Preventing Suicide in Skilled Nursing Facilities

Suicide in skilled nursing facilities—centers that provide around-the-clock treatment and rehabilitation—is a serious issue. Chronic physical ailments often take precedent over mental health issues, which can make it easy to overlook them. Tony Salvatore, director of Suicide Prevention at Montgomery County Emergency Services, provides insight into the problem and how we can better quantify it, and some simple fixes that can have a big impact.

Automatic Lung Segmentation in Chest X-ray Images Using Improved U-Net

Automatic and highly accurate lung segmentation in chest X-ray (CXR) images is the basis of computer-aided diagnosis systems, because the lung is the region of interest of many diseases, and it can show useful information through its contours. However, automatic lung segmentation is immensely challenging due to extreme variations in the shape, obscure lung area, or opacity caused by lung diseases reaches high-intensity values. In the face of these severe situations, the model may segment the lung boundary incorrectly. We designed an improved U-Net network: using the pre-training Efficientnet-b4 as the encoder, and the residual block and LeakyRelu activation function are used in the decoder. The network can not only extract features with high efficiency but also avoid the gradient explosion caused by the multiplication effect in gradient backpropagation. We constructed a CXR lung field segmentation dataset (Haut) based on the NIH CXR dataset. In particular, this lung segmentation dataset contains some serious abnormal cases, such as lung deformation, pleural effusion, covered by foreign matters, or CXR blur caused by severe lung disease. The improved U-Net is evaluated on Haut, JSRT, and Montgomery County (MC) datasets. Experimental results show that our network can achieve high-precision lung segmentation.