Land Use as a Predictor of Water Hyacinth (Eichhornia crassipes) Presence on the Entebbe Coast of Lake Victoria, Uganda

Lake Victoria is shared amongst Tanzania, Kenya, and Uganda and has tremendous ecological, economical, and cultural significance. Within the lake system, there are several problems, including the proliferation of an invasive weed, water hyacinth (Eichhornia crassipes). Therefore, this study aims to assess several factors that may correlate with water hyacinth proliferation. The specific objectives are (1) to identify possible correlations of water hyacinth density and land use around Entebbe, Uganda, and (2) to identify annual trends in water hyacinth coverage, to better inform policy and conservation efforts. Entebbe has a coastline of six land cover types: flooded vegetation, trees, grasses, shrub/scrub, crops, and built area. It was hypothesized that coastal areas adjacent to agriculture have a higher density of water hyacinth due to agricultural nutrient runoffs and flooded vegetation and built areas have higher abundances of water hyacinth due to a high amount of waste. The first specific objective employed a systematic sampling method, counting 41,615 water hyacinth around the coast of Entebbe, and was compared in QGIS with Sentinel-2 land use/land cover satellite imagery. The second specific objective employed remote sensing with a normalized difference vegetation index (NDVI). Twelve eMODIS satellite images were created on QGIS to map the percent coverage of water hyacinth in the Ugandan part of Lake Victoria. Flooded vegetation was found to have the highest density of water hyacinth, followed by crops, trees, built area, grass, and scrub/shrub. Additionally, 94% of water hyacinth was found on the left side of Entebbe. The most intense water hyacinth blooms occurred during June and July reaching 10.7% coverage, following the rainy season and maximumannual temperatures. The high densities within flooded vegetation and croplands are likely due to organic pollution runoffs. These results support previous research which found high temperatures and eutrophication to cause water hyacinth proliferation. This study theorizes that several unknown factors cause water hyacinth proliferation and thus control solely through mechanical, chemical, and biological means is treating a symptom, not the cause. Future research can explore this, adding to this study’s sample size, analyzing the different water dynamics for each land cover type, and further assessing the observation that water hyacinth presence may act as an indicator of organic pollution runoff

Simulation and economic evaluation of coal gasification with SETS reforming process for power production

Increasing natural gas prices have raised interest in alternate energy resources. Popular belief in the connection between carbon dioxide emissions and global warming has motivated the search for a technique to isolate carbon dioxide from combustion stack gases. Coal gasification with SETS reforming has been proposed as a solution to both of these issues in that it provides an alternate energy source and 100% carbon dioxide sequestration. The purpose of this research is to simulate this process using AspenPlus to perform the rigorous material and energy balances. The results of this simulation are used to carry out a complete economic evaluation of the process and estimate the overall cost of energy production (in 2003 dollars). Certain design parameters are modified from literature values. The simulations and economic evaluations are repeated for each case to study its effect on energy production cost. The final results of this study are compared with the current cost of electricity and the costs of other energy production methods

Senior Recital: Zachary Hoffman, Trombone

Kemp Recital Hall Novemher 16, 2018 Friday Evening 7:00p.m

Point-of-Care Diagnostic Device for the Quantitative Analysis of Human Estradiol at Low-Picomolar Concentrations

A fundamental issue in healthcare is the development of cost-effective and reliable diagnostic assays. While still a relatively new field, paper-based analytical devices are emerging as inexpensive and portable methods of providing healthcare professionals with real-time diagnostic information. Furthermore, these devices can often be used at the point of care, thus eliminating the need for a myriad of time-consuming laboratory techniques. While the original goal of this project was to develop a paper-based lateral flow immunoassay capable of colorimetric quantitation, the device design was altered over the course of the past year. Upon testing, the originally proposed lateral flow assay lacked adequate sensitivity and reliability. Therefore, a novel three-dimensional paper-based analytical device was developed. This new device design utilizes enzymatic amplification to break down a biomatrix, ultimately producing a chronometric readout. This unique biomatrix can detect \u3c1 femtomole (10-15) of analyte, with degradation time being directly correlated to analyte concentration. Thus far, device storage conditions, viable pH ranges, and viable temperature ranges have been determined. While further refinement is still needed, these diagnostic devices have the potential to revolutionize point-of-care assays through the quantification of analytes in both field and clinical settings

A Context-based Approach to Robot-human Interaction

AbstractCARIL (Context-Augmented Robotic Interaction Layer) is a human-robot interaction system that leverages cognitive representations of shared context as a basis for a fundamentally new approach to human-robotic interaction. CARIL gives a robot a human-like representation of context and an ability to reason about context in order to adapt its behavior to that of the humans around it. This capability is “action compliance.” A prototype CARIL implementation focuses on a fundamental form of action compliance called non-interference -- “not being underfoot or in a human's way”. Non-interference is key for the safety of human-co-workers, and is also foundational to more complex interactive and teamwork skills. CARIL is tested via simulation in a space-exploration use-case. The live CARIL prototype directs a single simulated robot in a simulated space station where four simulated astronauts are engaging in a variety of tightly-scheduled work activities. The robot is scheduled to perform background tasks away from the astronauts, but must quickly adapt and not be underfoot as astronaut activities diverge from plan and encroach on the robot's space. The robot, driven by CARIL, demonstrates non-interference action compliance in three benchmarks situations, demonstrating the viability of the CARIL technology and concept

Targeted polypharmacology: discovery of dual inhibitors of tyrosine and phosphoinositide kinases.

The clinical success of multitargeted kinase inhibitors has stimulated efforts to identify promiscuous drugs with optimal selectivity profiles. It remains unclear to what extent such drugs can be rationally designed, particularly for combinations of targets that are structurally divergent. Here we report the systematic discovery of molecules that potently inhibit both tyrosine kinases and phosphatidylinositol-3-OH kinases, two protein families that are among the most intensely pursued cancer drug targets. Through iterative chemical synthesis, X-ray crystallography and kinome-level biochemical profiling, we identified compounds that inhibit a spectrum of new target combinations in these two families. Crystal structures revealed that the dual selectivity of these molecules is controlled by a hydrophobic pocket conserved in both enzyme classes and accessible through a rotatable bond in the drug skeleton. We show that one compound, PP121, blocks the proliferation of tumor cells by direct inhibition of oncogenic tyrosine kinases and phosphatidylinositol-3-OH kinases. These molecules demonstrate the feasibility of accessing a chemical space that intersects two families of oncogenes

Deep Learning Approach for Mapping Arctic Vegetation using Multi-Sensor Remote Sensing Fusion

Land cover datasets are essential for modeling Arctic ecosystem structure and function and for understanding land–atmosphere interactions at high spatial resolutions. However, most Arctic land cover products are generated at a coarse resolution, and finding quality satellite remote sensing datasets to produce such maps is difficult due to cloud cover, polar darkness, and poor availability of high-resolution imagery. A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5 m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. The datasets from hyperspectral, multispectral, synthetic aperture radar (SAR) platforms, and terrain datasets were fused together using unsupervised and supervised classification techniques over a 343 km2 region to generate high-resolution (5 m) vegetation type maps. A unsupervised technique was developed to classify high-dimensional remote sensing datasets into cohesive clusters and a quantitative technique to add supervision to the unlabeled clusters was employed, producing a fully labeled vegetation map. Deep neural networks (DNNs) were developed using multi-sensor remote sensing datasets to map vegetation distributions using the original labels and the labels produced by the unsupervised method for training [1]. Fourteen different combinations of remote sensing imagery were analyzed to explore the optimization of multi-sensor remote sensing fusion. To validate the resulting DNN-based vegetation maps, field vegetation observations were conducted at 30 plots during the summer of 2016 and developed vegetation maps were evaluated against them for accuracy. Our analysis showed that the DNN models based on hyperspectral EO-1 Hyperion, integrated with the other remote sensing data, provided the most accurate mapping of vegetation types, increasing the average validation score from 0.56 to 0.70 based on field observation-based vegetation. REFERENCES: 1. Langford, Z. L., Kumar, J., and Hoffman, F. M., "Convolutional Neural Network Approach for Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion," 2017 IEEE International Conference on Data Mining Workshops (ICDMW), New Orleans, LA, 2017, pp. 322-331. doi: 10.1109/ICDMW.2017.4

Deployable Optical Receiver Array Cubesat

Small satellites and cubesats often have low data transmission rates due to the use of low-gain radio links in UHF and S bands. These links typically provide up to only 1 Mbps for communication between the ground and LEO, limiting the applications and mission operations of small satellites. Optical communication technology can enable much higher data rates and is rapidly gaining hold for larger satellites, including for crosslinks within SpaceX’s Starlink constellation and upcoming NASA deep space missions. However, it has been difficult to implement on small satellites and cubesats due to the need for precision pointing on the order of arcseconds to align the narrow optical laser beam between terminals--a laser transmitter in LEO may yield a footprint less than 100 meters wide at its receiving ground station. We report the development of a 3U cubesat to demonstrate new optical communication technology that eliminates precision pointing accuracy requirements on the host spacecraft. The deployable optical receiver aperture (DORA) aims to demonstrate 1 Gbps data rates over distances of thousands of kilometers. DORA requires an easily accommodated host pointing accuracy of only 10 degrees with minimal stability, allowing the primary mission to continue without reorienting to communicate and/or enabling small satellite missions using low-cost off-the-shelf ADCS systems. To achieve this performance, DORA replaces the traditional receiving telescope on the spacecraft with a collection of wide-angle photodiodes that can identify the angle of arrival for incoming communication lasers and steer the onboard transmitting laser in the corresponding direction. This work is motivated by NASA’s plans for a lunar communications and navigation network and supported by NASA’s Space Technology Program (STP). It is ideally suited for crosslink communications among small spacecraft, especially for those forming a swarm and/or a constellation, and for surface to orbit communications. We will implement the deployable optical receiver aperture and miniature transmission telescope as a 1U payload in the 3U cubesat and conduct the demonstration flight in LEO. Future implementations of the DORA technology are expected to further enable omnidirectional receiving of multiple optical communications simultaneously and accommodate multiple transmitting modules on a single cubesat