Reconnecting a fragmented landscape: a multi-scale ecological approach to green space design in Wichita, Kansas

Master of Landscape ArchitectureDepartment of Landscape Architecture/Regional and Community PlanningHyung Jin KimAs the impact of urbanization is felt more and more in cities around the world the preservation of nature has become less of a priority. This has led to a lack of nature in many urban cities which is causing many social and environmental problems. One of the main issues is the high degree of fragmentation that is occurring in cities, which disrupts natural processes and creates unequal access to nature for the city’s residents. The City of Wichita, Kansas is currently experiencing some of these problems due to its sprawling development patterns. The study objectives were: (a) to contribute to the development of a multi-scale ecological design approach that links spatial landscape analysis and ecological site-design modeling; and, (b) to reconnect fragmented landscapes by reclaiming and redistributing urban green spaces as social and ecological assets in Wichita, Kansas. This objective was accomplished through a two-phase process. The first phase focused on a city-level analysis. In this phase GIS and FRAGSTATS were used in combination to identify different patterns within the fragmented landscape. Solutions and suggestions were then made for each of the types of fragmentation that were found to be occurring. Following this analysis, one of the most fragmented sites was chosen. In the second phase, the selected site was then analyzed to determine which type or types of fragmentation were occurring. Using the typological solutions generated in phase one, a site design was developed to demonstrate how the higher-level ideas in phase one can be applied at the site level. This project serves as an example of how landscape architects can use a more data-driven method to design green space in an urban context, such as landscape pattern analysis techniques which allows them to collaborate with other professionals more effectively

Data-driven Methods for Partial Differential Equations

This research explores recent advancements in solving Partial Differential Equations (PDEs) through a fusion of data-driven methods and Physics-Informed Neural Networks (PINNs). Traditional numerical techniques encounter challenges with complex systems in modeling diverse physical phenomena. The study focuses on applying PINNs to efficiently solve elliptic PDEs, crucial equations in scientific and engineering disciplines. Elliptic PDEs, known for their steady-state nature, pose challenges for traditional methods due to high computational costs over complex domains. The research utilizes a comprehensive dataset, synthetically generated for PINN training and accuracy validation. The study introduces a novel approach to constructing a PINN that not only efficiently solves elliptic PDEs but also quantifies prediction uncertainties. This dual capability is crucial for applications where decision-making relies on understanding the reliability of model outputs. The results demonstrate the potential of PINNs to revolutionize elliptic PDE solving, offering a fast, accurate, and physically consistent method that inherently accounts for uncertainty, advancing computational science

Understanding the different challenges facing students in transitioning to university particularly with a focus on ethnicity

A positive and successful transition into University is crucial if students are to stay the course in higher education and experience successful outcomes. However, challenges exist in ensuring a connected transition from secondary and further education to higher education that is inclusive and supports the diversity in our current undergraduate student body. We set out to explore the diverse experiences that first year students report about their recent transition to a post-1992 University. We were particularly interested in how these experiences and challenges differed by ethnicity. This is incredibly important given the disparity, recognised in the sector, in the attainment of Black and Minority Ethnic (BME) students compared to their White counterparts and particularly pertinent that this trend reverses attainment patterns in secondary education. This paper summarises some of our key findings in determining the challenges facing students from different backgrounds in their transition to university. It argues that Universities will have to change their transition and wider offer to ensure that diverse students feel welcomed and develop a sense belonging in Higher Education in order for them to achieve successful outcomes

First record of the non-native suckermouth armored catfish \u3cem\u3eHypostomus cf. niceforoi\u3c/em\u3e (Fowler 1943) (Siluriformes: Loricariidae) from Central America

We document the first record of Hypostomus cf. niceforoi in Central America. Two specimens of these suckermouth armored catfishes were collected in Lake Nicaragua (Nicaragua) and identified as H. cf. niceforoi. Hypostomus niceforoi is endemic to Andean streams of Colombia, Venezuela, Ecuador, and Peru. We hypothesize that its introduction in Central America is related to the aquarium trade, as is the case of other armored catfish species introductions

The Spectral Ocean Color Imager (SPOC) – An Adjustable Multispectral Imager

SPOC (SPectral Ocean Color) is a 3U small satellite mission that will use an adjustable multispectral imager to map sensitive coastal regions and off coast water quality of Georgia and beyond. SPOC is being developed by the University of Georgia’s (UGA) Small Satellite Research Laboratory (SSRL) through NASA’s Undergraduate Student Instrument Project (USIP). UGA is working with Cloudland Instruments to develop a small scale (\u3c 1000 \u3ecm3) multispectral imager, ranging from 400-850nm, for Earth science applications which will fly as part of the NASA CubeSat Launch Initiative. The project is UGA’s first satellite mission and is built by a team of undergraduates from a wide range of backgrounds and supervised by a multidisciplinary team of graduate students and faculty. Development, assembly, testing, and validation of the multispectral imager, as well integrating it into the satellite are all being done in house. At an orbit of 400 km the resulting images will be 90 km x 100 km in size, with a default spatial resolution and spectral resolution of 130 m and 4 nm, respectively

AVERTING MATERNAL DEATH AND DISABILITY Using a GIS to model interventions to strengthen the emergency referral system for maternal and newborn health in Ethiopia

a b s t r a c t a r t i c l e i n f o Objectives: To show how GIS can be used by health planners to make informed decisions about interventions to increase access to emergency services. Methods: A combination of data sources, including the 2008 national Ethiopian baseline assessment for emergency obstetric and newborn care that covered 797 geo-coded health facilities, LandScan population data, and road network data, were used to model referral networks and catchment areas across 2 regions of Ethiopia. STATA and ArcGIS software extensions were used to model different scenarios for strengthening the referral system, defined by the structural inputs of transportation and communication, and upgrading facilities, to compare the increase in access to referral facilities. Results: Approximately 70% of the population of Tigray and Amhara regions is served by facilities that are within a 2-hour transfer time to a hospital with obstetric surgery. By adding vehicles and communication capability, this percentage increased to 83%. In a second scenario, upgrading 7 strategically located facilities changed the configuration of the referral networks, and the percentage increased to 80%. By combining the 2 strategies, 90% of the population would be served by midlevel facilities within 2 hours of obstetric surgery. The mean travel time from midlevel facilities to surgical facilities would be reduced from 121 to 64 minutes in the scenario combining the 2 interventions. Conclusions: GIS mapping and modeling enable spatial and temporal analyses critical to understanding the population's access to health services and the emergency referral system. The provision of vehicles and communication and the upgrading of health centers to first level referral hospitals are short-and medium-term strategies that can rapidly increase access to lifesaving services

Transcript-indexed ATAC-seq for precision immune profiling.

T cells create vast amounts of diversity in the genes that encode their T cell receptors (TCRs), which enables individual clones to recognize specific peptide-major histocompatibility complex (MHC) ligands. Here we combined sequencing of the TCR-encoding genes with assay for transposase-accessible chromatin with sequencing (ATAC-seq) analysis at the single-cell level to provide information on the TCR specificity and epigenomic state of individual T cells. By using this approach, termed transcript-indexed ATAC-seq (T-ATAC-seq), we identified epigenomic signatures in immortalized leukemic T cells, primary human T cells from healthy volunteers and primary leukemic T cells from patient samples. In peripheral blood CD4+ T cells from healthy individuals, we identified cis and trans regulators of naive and memory T cell states and found substantial heterogeneity in surface-marker-defined T cell populations. In patients with a leukemic form of cutaneous T cell lymphoma, T-ATAC-seq enabled identification of leukemic and nonleukemic regulatory pathways in T cells from the same individual by allowing separation of the signals that arose from the malignant clone from the background T cell noise. Thus, T-ATAC-seq is a new tool that enables analysis of epigenomic landscapes in clonal T cells and should be valuable for studies of T cell malignancy, immunity and immunotherapy