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Characterization of injectable liquid embolic particles
Get PDFCerebral aneurysms can be found in over 2% of the American population, and their rupture into hemorrhagic stroke carries a 40% mortality rate. This makes their treatment important to clinicians trying to prevent this from happening to millions of people. A novel polymer, poly(propylene glycol) diacrylate and pentaerythritol tetrakis (3-mercaptopropionate) (PPODA-QT), has been developed in order to successfully embolize these aneurysms. It is injected through a catheter into the aneurysm, where it cures and the aneurysm can heal itself, eliminating the risk of rupture and stroke. This thesis focuses on the embolic risks presented during the injection and curing of PPODA-QT.
The first aim of this project was to build an endovascular flow model that could accurately mimic conditions found in the human body. This was used to practice procedures and evaluate embolic risk. In the second aim, multiple microscopy methods were used to capture and analyze particles shed downstream during the procedure to ensure that the injection would be safe for use in living models. In the final aim, rabbit aneurysm models were used to confirm that no negative embolic effects were observed.
A model was built that could control pressure, temperature, and pressure. The model was designed with customizable inserts that could be changed to model various anatomies. Differential interference contrast (DIC) microscopy was used to analyze filters that captured downstream particles produced during the procedure. Feasibility of inline digital holography was also performed. Finally, a rabbit aneurysm model was developed in order to treat different aneurysm morphologies. This thesis presents a series of methods that can be used to study of the embolic risks of a novel aneurysm treatment with the potential to impact millions of lives
Remote Heart Monitoring: A Predictive Modeling Approach for Biomedical Signal Processing
Get PDFSmart healthcare is an emerging field with the goal of harnessing technological advances to enhance healthcare quality. Several research projects in recent years are devoted to design of electronic devices and networking platforms to facilitate technology-based health service. One important paradigm in smart healthcare is developing tools for biomedical signal processing. Biomedical signals can directly reflect the information about patient health and therefore have been widely investigated by the research community. The essence of most signal analysis systems is to process a large training dataset and build a reference model to asses the health status of new patients. While the majority of these methods focus on improving classification performance on a collection of signals in large datasets, the predictive modeling of biomedical signals is rarely emphasized. In this work, we go one step beyond the conventional methods and intend to predict potential upcoming abnormalities before their occurrence. The approach is to build a patient-specific model and identify minor deviations from the normal signal, which can be indicative of potential upcoming significant deviations.
To enable an accurate deviation analysis, a controlled nonlinear transformation is proposed to reshape the feature space into a more symmetric geometry. We applied the developed algorithms on Electrocardiogram (ECG) signals and the results confirm the effectiveness of the proposed method in predicting upcoming heart abnormalities before their occurrence. For instance, the probability of observing a specific abnormality class increases by 10% after triggering a yellow alarm of the same type. This approach is general and has the potential to be applied to a wide range of physiological signals
Polychlorinated biphenyl (pcb) contamination on Unalaska Island in the Aleutian archipelago
Get PDFPolychlorinated biphenyls (PCBs) are a group of man-made, hydrophobic organochlorines that persist at highly toxic levels in the environment and biomagnify within food webs. Although banned, their continued release from pre-banned products and persistence in the environment impact human and wildlife health. PCBs are transported to the Arctic via global distillation and biomagnify to high levels in the lipid-rich food web. Thus the long-range transportation capacity of PCBs can affect food webs far from the area of release. In addition, the Arctic contains thousands of World War II and Cold War formerly used defense (FUD) sites, many of which are also a local source of PCB contamination. PCBs have the ability to modify or suppress thyroid, reproductive and immune function. Exposure can reduce cognitive function and greatly increase the risk of developing cancer, hypothyroidism and a host of other negative health effects. Human and animal exposure occurs via ingestion of contaminated food. PCB concentrations were analyzed in threespine stickleback (Gasterosteus aculeatus) and subsistence foods important to the Qawalangin Tribe of Unalaska (i.e., salmonid species and blue mussels (Mytilus edulis)). PCBs were extracted from samples using a modified QuEChERS method. Mean PCB concentrations were quantified in target species to assess potential risks associated with subsistence foods and to detect a difference between global and local sources of PCB contamination. Two FUD sites showed elevated levels of PCBs that exceed safe consumption guidelines. These results support the need to remediate the FUD sites of “Building 551/T Dock to Airport” and “Delta Western”. More generally, these results provide further evidence of the continued problem of PCB contamination at FUD sites in the Arctic
One−dimensional energy balance ocean model with application to environmental impact of climate change due to global warming
No full textThe IPCC (Intergovernmental Panel on Climate Change) report on climate change presents some conclusions expressed with “high degree of confidence” regarding changes in the climate system. “Warming of the climate system is unequivocal …”, and the anthropogenic increase in greenhouse gases caused the rise in ocean temperatures and consequently the rise in sea levels. “Over the period 1901 to 2010, global mean sea level rose by 0.19 [0.17 to 0.21] m” [IPCC, 2013].
According to models and alternative scenarios considered [IPCC, 2013] “thermal expansion accounts for 30 to 55% of 21st century global mean sea level rise” and melting of “glaciers for 15 to 35%”. The sea level rise is being considered a predominant effect adverse to the sustainable human life on earth mainly because of the threat of flooding of coastal cities and islands [IPCC, 2013], [OECD, Environmental Outlook to 2050, 2012].
There have been different types of models that were developed to evaluate and predict the sea level rise [IPCC, 2013]. All these models use as input the radiation and heat fluxes occurring at the water surface. The latter include prediction of atmospheric radiation that is estimated by other models.
The present research describes a one-cell ocean model with using existing data of past sea level measurements as input and producing the net amount of heat flux into the ocean as output. Therefore, the model can evaluate the radiation forcing indirectly, via the known values of measured sea levels. Thus, this is an inverse problem type of model that can provide a means of validation of the radiation forcing, the latter being a result of a more complicated modeling
Enhancing security and radio spectrum efficiency in cognitive IoT networks
No full textThe emergence of Internet of Things (IoT) has led to a technology breakthrough by facilitating a new generation of sensing and control applications such as smart cities, smart health, and smart homes to only name a few. However, such a large-scale network of sensors and actuators involve a set of new challenges including security, radio spectrum scarcity, complexity of network, data management, and lack of global standards. In order to accommodate the growing number of IoT devices which is predicted to be over 20.4 billion by the year 2020, a new generation wireless protocols are required to scale up to such huge networks. In this thesis, the problem of dynamic spectrum management and security in IoT networks are considered.
Security is one of the critical challenges in IoT networks, where the connected devices need to be protected from potential malicious and selfish attacks. The malicious attacks refer to the attacks where illegitimate and intruding entities attempt to disrupt the network performance through jamming or other unauthorized actions. Several cryptographic methods have been widely utilized to protect the communication devices from such attacks. However, such conventional methods are not easily scalable to large-scale IoT networks as they often rely on generation, distribution, and storing secret keys in the devices and are prone to several attacks such as man-in-the-middle attacks. Hardware-based security methods attempt to utilize the unique variations in the electronic devices as a metric for identification, authentication, and even secret key generation. While such methods have been fairly successful in identification and authentication applications, they still cannot offer a reliable solution for key generation applications as the performance of such methods highly depends on the physical and environmental factors. In this work, we developed a hardware-based secret key generation mechanism that utilizes the random variations in embedded memories in IoT devices to generate reproducible and reliable cryptographic keys by proposing a new error correction and fuzzy extractor structure.
Furthermore, we developed a reputation-based spectrum leasing mechanism to provide a potential solution for spectrum scarcity in IoT networks. While the current static approaches of spectrum management resulted in inefficient usage of spectrum which is an expensive resource, the recent advancements in communication devices led to development of dynamic spectrum management techniques. Such dynamic spectrum management can be in the forms of spectrum sharing without involving the licensed users or more sophisticated methods of spectrum leasing, where the spectrum owners can willingly allocate a part of their spectrum to the unlicensed users in exchange for some benefit. While such spectrum sharing solutions can generally enhance the efficiently of spectrum utilization and the Quality of Service (QoS) for spectrum owners, they are highly sensitive to potential selfish attacks. Selfish attacks refer to the attacks by authenticated users who try to increase their own benefits. For example, in cooperative spectrum leasing scenarios, the selfish users may attempt to increase their own transmission rate by using the leased spectrum for their own selfish transmissions by not allocating enough power for relaying licensed user packets. Here, we propose a reputation-based spectrum leasing model to monitor the behavior of self-interested users to enhance the performance of common spectrum leasing techniques against selfish attacks
A second difference matrix for the Laplacian in Elliptical Coordinates
No full textWe use finite differences and a matrix approach to approximate the Laplacian in Elliptical coordinates which is known to be
∆Φ = 1 (∂2Φ + ∂2Φ). c2(sinh2 μ + sin2 ν) ∂μ ∂ν
Using Matlab, we code our construction of the Laplacian in Elliptical coordinates and use it to compute eigenvalues for the Elliptical Laplacian with an error of order O(h2). We compare our eigenvalues against published eigenvalues on the ellipse with zero-Dirichlet boundary conditions, and eigenvalues on the disk with zero-Neumann boundary conditions. We also compute eigenvalues with an error of order O(h2) for the ellipse with zero-Neumann boundary conditions for several cases, and we use our Elliptical Laplacian to solve the heat and wave equations as well as a semi-linear application
Preceramic cave use in Belize
Get PDFLittle evidence for human use of caves in Belize is available for the long span of time from the first human habitation of the area until the beginnings of Maya civilization. This thesis seeks to further the understanding of preceramic people in Belize by examining the information that is available from the few archaeological projects which have uncovered evidence of Paleoindian and Archaic use of caves throughout the Maya area and surrounding region, but with an emphasis on Belize, and explores what those data might indicate as to the nature and extent of preceramic cave use.
The conclusions of this research suggest that significant cave use by preceramic peoples occurred throughout Mesoamerica, primarily for practical and not necessarily ritual purposes, such as short-term seasonal habitation and water procurement. While there is currently little evidence for this in Belize, the paucity of data probably stems from a lack of focused research, logistical challenges, the ephemeral nature of the preceramic archaeological record, and subsequent destruction or obfuscation of cultural residue by later Maya use of caves
The achievement gap of 3rd-8th graders in Title I and non-Title I schools
Get PDFThe purpose of this research study was to determine if there was an academic achievement gap between third through eighth-grade students in Title I and Non-Title I schools in the academic content areas of English Language Arts and Mathematics. The study focused on the following subgroup: economically disadvantaged students. The data was gathered from an analysis of a standardized test in English Language Arts and Mathematics of third through eighth-grade students. Within the suburban southwest school district that was being studied, the district formation of schools varied: fifteen schools in the district service kindergarten through fifth-grade students, four schools in the district service kindergarten through eighth-grade students, and five schools in the district service sixth through eighth-grade students. The data was collected from the 2017 Arizona's Measurement of Educational Readiness to Inform Teaching (AzMerit) scores. The Arizona's Measurement of Educational Readiness to Inform Teaching (AzMerit) assessment is a yearly standardized assessment test, starting in the third-grade, used to evaluate student academic progress in the state of Arizona.
In summary, in grades third through fifth, there was a significant difference between students in both English Language Arts and Mathematics scores between Title I and Non-Title I schools. Also, in grades third through fifth, there was a significant difference between socioeconomically disadvantaged students in both English Language Arts and Mathematics scores between Title I and Non-Title I schools.
When it came to the middle school grades, the data results changed. In grades sixth through eighth, there was no significant difference between students in both English Language Arts and Mathematics scores between Title I and Non-Title I schools. But, when looking at socioeconomically disadvantaged students in grades sixth through eighth the data showed there was a significant student achievement gap difference between sixth and eighth-grade students English Language Arts (ELA) scores between Title I schools and Non-Title I schools
Springs geomorphology influences on physical and vegetation ecosystem characteristics, Grand Canyon Ecoregion, USA
Get PDFThe Grand Canyon Ecoregion (GCE) represents the entire landscape that drains into Grand Canyon. This region encompasses a wide array of environments and corresponding plant communities of biological interest. Springs are numerous in the GCE and play a multitude of roles in this generally arid land. Springs serve as critical sources of water and support many endangered and endemic species, many of which are springs-dependent species including Flaveria mcdougalii, Epipactis gigantea, and Eleocharis palustris. I conducted a statistical community analysis of 352 springs in the Grand Canyon Ecoregion across four spring types – helocrene wet meadows; hanging gardens; rheocrene flowing springs; and hillslope springs – and examined their physical traits and floral assemblages. Mann-Whitney tests were used to detect differences between spheres of discharge and correlation and multiple regression were used to determine relations of physical and geomorphic traits with plant species diversity. An astounding species packing was demonstrated with nearly 1000 species recorded across all springs, representing over 45% of the region’s entire flora in less than one square kilometer of springs habitat area. Geomorphic microhabitat diversity was positively related to springs diversity (p<0.00001; multiple linear regression).
All springs types were distinguished by differences in physical site characters which in turn were associated with plant community structure and specific species. Geomorphic features including microhabitat features and substrate composition were important in distinguishing springs types. There were also different physical characteristics distinguishing springs types including elevation and water chemistry. These features were correlated strongly with plant assemblages at springs and sets of indicator species were associated with each spring type.
Multivariate regression analysis identified suites of variables related to springs biodiversity metrics explaining nearly half of the variation in species richness between springs. Microhabitat richness, area, and elevation were most important in explaining species richness. Grazing intensity did not have any discernable impact on species richness but did have a negative relation to the percentage of native species found at springs.
In this study, I identified key differences between spring types; however, springs are highly individualistic and each spring needs to be understood in an individual context. Stewardship efforts should aim to protect geomorphic microhabitats and restore them to natural conditions. Their concentrations of biodiversity warrant further conservation and additional inventory and study will prove useful in furthering understanding of springs of the GCE
Numerical evaluation of the validity domain of Lorenz equations
Get PDFNatural convection in a two-dimensional rectangular domain heated at the bottom and cooled at the top with perfectly insulated sidewalls is the topic of interest for this research. For Rayleigh numbers less than the critical value, Ra_cr, any disturbances will decay to a motionless solution and heat transfer will occur via conduction only. Above Ra_cr, natural convection develops in the domain. At some second critical Rayleigh number, Ra_t, the steady convection cells lose stability and the solution transitions to a weakly turbulent (chaotic) state. The Lorenz system was previously derived from the governing equations using a truncated Galerkin expansion. This research investigates the validity domain of the Lorenz system as a model for natural convection in porous media. The temperature and velocity fields given by the Lorenz system are compared to a numerical solution for the temperature and velocity fields for increasing Rayleigh numbers. Results show that near Ra = 80 the number of convection cells predicted by the numerical solution increases from two to three as a result of the chosen wavenumber becoming unstable. The result is a significant difference between the Lorenz system and the numerical solution. To provide a comparison between the Lorenz solution and the numerical solution that is global in scale relative to the problem domain, we compared the Nusselt numbers resulting from each solution to experimental data