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Item MoveOn and E-motion : the paradox of cyberactivism in consumer society(Rensselaer Polytechnic Institute, Troy, NY, 2006-08) Dincki, Sandrine; Nadel, Alan, 1947-The relationship between media and democracy has always been characterized by a tension between public and private interests with a tendency for the latter to prevail. Mediated politics and consumption in a democratic society paradoxically enable “lifestyle politics” and degrade the “public sphere.” The political and the commercial realms are not necessarily exclusive as MoveOn illustrates. MoveOn is an online activist group with a conventional mass media approach to politics. The production, representation, and consumption dimensions of the “circuit of culture” are used to investigate MoveOn. It has strong ties with the conventional media industry and the Silicon Valley culture and heavily relies on marketing techniques, standardization and pseudo-individualization. MoveOn members are a crucial site of production that shows the tension between empowerment and control. MoveOn produces the conditions for action while members materialize action and become both producer and consumer. MoveOn also exemplifies the confluence of political and symbolic representations in that its members are both subjects of the former and objects of the latter. Its representation practices include pseudo-events and pseudo-heroes. These practices are mediated by the rules of the “public screen.” “Astroturfing” practices problematize the dichotomy artificial vs. real/grassroots. MoveOn follows two axes of representation: “voice” and “numbers.” MoveOn communicates via the “discourse of images” and e-motion, a process through which emotions are filtered, repackaged, and electronically mediated in order to set people in vicarious motion. E-motion encapsulates the convergence of mass media and the internet, and the confluence of activism and consumerism. MoveOn also complies with the “info-tainment” conventions via silent sound bites and the participation of celebrities in its campaigns. Consumption is viewed from the perspective of “consumer culture” that views consumption as mediation between the individual and the social. Consumer activism is one aspect of the convergence of activism and consumerism. “Activist consumerism,” in the form of repetitive participation in campaigns and as exemplified by MoveOn, is another aspect. MoveOn membership consists in “window shoppers,” “immobile activists,” and grassroots activists. Consumption practices can also be a form of dissent or resistance.Item Cell free production of isobutanol(Rensselaer Polytechnic Institute, Troy, NY, 2022-08) Wong, Matthew; Belfort, Georges; Koffas, Mattheos A. G.With a need for greener fuels, research into production of biofuels is essential. Isobutanol out preforms ethanol in key metrics such as engine compatibility, energy density, and gasoline blending. Current biofuel strategies of fermentation are constrained by the inherent toxicity of alcohol on microbial cells. While work has been performed on engineering these strains for higher tolerance, cell-free production with enzymes offers a novel approach to bypass the toxicity limitations altogether. These enzymes can also be immobilized to retain enzyme activity and facilitate separations. Based on previous work in the Belfort laboratory, the ketoisovaleric acid pathway was chosen for production of the biofuel, isobutanol. High preforming and stable enzymes were selected from the literature, cloned, expressed, and purified and tested for activity, kinetics, and stability. They were utilized in a novel in vivo to in vitro system, resulting isobutanol titer of 1.78 g/L and yield of 93%. An epoxy immobilized reaction scheme resulted in a titer of 2 g/L and 43% yield. The pathway enzymes were then fused to dockerins, which bound to a cohesin scaffold on cellulose. The reaction utilizing this immobilization scheme resulted in a titer of 5.92 g/L and 78.4% yield. Further work can be done to optimize this reaction, as well as to expand the pathway or scaffold, and incorporate separation of the isobutanol for eventual scaleup.Item Modeling efforts for improved meal prediction with application to blood glucose control(Rensselaer Polytechnic Institute, Troy, NY, 2022-08) Diamond, Travis; Bequette, B. WayneType 1 Diabetes Mellitus is a disease characterized by the loss of insulin production from beta cells in the pancreas, which results in unregulated blood glucose (BG). The condition is permanent, exacting a high toll on an individual in terms of both health outcomes and treatment burden. Acute risk of low BG includes coma, seizure, and death, while longer term risk of high BG includes damage to the circulatory and nervous systems. To mitigate the risk of both ends, individuals must constantly stay vigilant, regulating BG levels with insulin injections and constantly monitoring BG levels. The artificial pancreas aims to reduce both health and treatment burdens by automatic regulation of BG levels. It consists of an insulin pump that injects insulin, a continuous glucose monitor that provides BG measurements, and a control algorithm that calculates dosing decisions. The next step in the development of artificial pancreas systems is fully closed loop control around meals. Unannounced meals present a challenge for the control algorithm because of the uncertainty surrounding the presence and content of the meal in addition to the slow and irreversible action of insulin paired with the acute risk of low BG. We propose a meal model, developed on gold standard triple tracer data, that considers meal size and shape and explicitly estimates uncertainty within meals. To quantify the quality of prediction in the context of BG control, we propose a new metric that considers asymmetry of prediction error and assesses prediction distributions in addition to single point predictions. Using the proposed metric, we tune an extended version of the model on a large data-set of free-living patient data and compare to previous work. The proposed model is first compared against three simpler models using triple tracer meal data. Prediction root mean square error is improved by 11% relative to the next best non-linear model. A simple implementation of control for all models suggests improved control capability for the proposed model: the proposed model is the fastest to compensatefor a meal in 4 out of 6 cases and overcompensates the least (8% excess) in the worst case compared to other models (25% excess). The model is also validated on a large data-set by evaluating prediction capability and control performance. The proposed model improves predictions by 37% relative to previous work in terms of the proposed metric. In a retrospective simulation of control, the proposed model reduces clinical risk by 12% over previous work. An open source artificial pancreas system currently in use by many is Loop. Part of the presented work is an effort to introduce Loop into the control literature. We formulate the Loop control algorithm as a “coincidence point” model predictive control strategy paired with a linear state space model. We evaluate Loop in silico using error-prone scenarios and suggest improvements that can be made to the meal announcement functionality.Item A step towards the practical evaluation of wildlife identification algorithms(Rensselaer Polytechnic Institute, Troy, NY, 2022-08) Mankowski, Alexander R.; Stewart, Charles V.Computer vision approaches have shown to be an effective tool for wildlife identification across a wide range of species. As the field grows and the amount of available data grows with it, deep learning based approaches are beginning to enter as alternatives to previous methods. In this thesis we examine one of these newer deep learning methods --- Pose Invariant Embeddings (PIE) --- to determine how it performs in an environment representative of what we anticipate in practice. This environment is based on the idea of continual curation, where an initially small database evolves and grows over time. We find that the training data required for PIE results in an additional complication that can have a large impact on perceived performance when evaluating individuals seen and unseen during training. We compare PIE against a baseline algorithm HotSpotter, and find that under our current dataset sizes the baseline remains the preferred approach. However, PIE presents a greater opportunity as we move forward with additional data, which can eventually lead to better performance as our continually curated dataset develops.Item Reduced-order modeling of neutron transport by proper generalized decomposition(Rensselaer Polytechnic Institute, Troy, NY, 2022-08) Dominesey, Kurt A.; Ji, WeiThe numerical simulation of neutron transport within a nuclear reactor—for brevity, reactor physics—is the foundation on which analysts: design new reactors; license existing designs; prolong the licenses of operating plants; optimize loading patterns of fuel and burnable absorbers; perform fuel cycle analyses; evaluate a reactor’s ability to self-regulate in response to perturbations; model reactivity control systems; design adequate shielding; and predict the isotopic composition of spent fuel. It is, in short, how humans understand the neutronic inner workings of a nuclear reactor, second only to physical experimentation. It is also, unfortunately, extremely resource-intensive to deterministically compute at high fidelities, being described as a six- or seven-dimensional integro-differential equation. These dimensions refer to the neutron field’s position in space r⃗ ≡ (x,y,z), direction of travel (in angular coordinates μ and ω), speed (energy) E, and instant in time t (for transients). As such, discretizing the neutron transport equation with even a scant ten unknowns in each dimension would yield a seven-dimensional mesh containing ten million degrees-of-freedom. Unsurprisingly, in practical simulations of large reactors, this number often runs into the billions or trillions, requiring either vast High Performance Computing (HPC) resources or drastic simplifications. This phenomenon is known generally as the “curse of dimensionality” and is common to many fields of numerical analysis. Presently, we aim to circumvent the curse of dimensionality by seeking a separable, low-rank approximation of the neutron flux, or solution. Moreover, unlike a posteriori, or data-driven, Reduced-Order Models (ROMs), this decomposition will be computed progressively by way of a greedy algorithm, eliminating the need for full-order reference solutions. Specifically, the a priori model order reduction technique here applied to reactor physics is Proper Generalized Decomposition (PGD). Because PGD approximates the solution to high-dimensional problems like radiation transport as a finite series of M products of low(er)-dimensional modes, one avoids solving the high-dimensional (full-order) problem entirely. Instead, only M nonlinear systems of low-dimensional subproblems need be solved; as such, the PGD ROM may be drastically cheaper to compute than the original problem, especially if few modes M are needed. Particularly, we here separate energy (yielding spatio-angular and energetic subproblems) and axial space (yielding 2D and 1D subproblems). Both ROMs are then validated in prototypical reactor physics benchmarks. Our first application—model order reduction in energy by PGD—is motivated by the extreme (ultrafine) resolution required to resolve individual nuclear resonances—sharp peaks across a narrow range of energy—in the neutron interaction probabilities, or cross sections, of nuclear fuels and other materials. This regime of fidelity is so demanding as to be typically impractical for geometries larger than a 1D or 2D slice across a single fuel pin—let alone the hundreds of pins comprising an assembly (or the hundreds of assemblies comprising a core). For now, however, we consider the more modest energy meshes (70 to 361 groups) usually employed for infinite lattices of pins or assemblies (that is, lattice physics), such that it is tractable to compute the full-order solution for comparison. Benchmark cases are taken to be representative light water reactor (LWR) pins of UO2 or Mixed Oxide fuel with CASMO-70, XMAS-172, and SHEM-361 energy meshes. To begin, we establish that both the Galerkin and Minimax PGD ROMs are able to compute the flux at sufficient precision (0.36% L2 error or less) in a tractable number of modes (M = 50). Next, we apply the ROM to cross section generation—often the objective of lattice physics—achieving results comparable to a homogenized, infinite medium model with 1 to 3 modes and comparable to the full-order model by 10 to 20 modes, as assessed by the error of the coarse-group model. Subsequently, we compare the coarse(ned)-group flux against that given by cross section condensation, finding similar L2 errors (0.5%) with 10 modes. Given additional modes, the ROM is able to converge below this threshold. Finally, this ROM is extended to criticality (eigen)problems by means of an original algorithm, which achieves k-eigenvalue errors less than 2 × 10−4 by M = 50. Further, the eigenvalue ROM again compares favorably to the coarse-group model with as few as 10 to 20 modes. Based on these results, we anticipate this PGD ROM may be able to calculate detailed flux distributions and cross sections more economically than the full-order model, at a marginal or negligible detriment to accuracy. Moreover, the ROM presents an alternative means of approximation to cross section condensation, preferable in that it introduces neither a loss of fidelity nor irrecoverable error. Secondly, we apply PGD to separate the axial and (optionally) polar dimensions of neutron transport. As nuclear reactors (especially LWRs) tend to be tall, but geometrically simple, in the axial, or z direction, we expect this ROM may save substantial effort and rapidly converge to a low-rank approximation. Moreover, we anticipate this approach may compare favorably to the methodologically distinct, but practically analogous 2D/1D methods already practiced in reactor physics. First, we derive two original models: that of axial PGD—which separates only z and the axial streaming direction v ∈ {−1,+1}—and axial-polar PGD—which separates both z and polar angle μ from the radial domain. Additionally, we grant that the energy dependence E may be ascribed to either radial or axial modes, or both, bringing the total number of candidate 2D/1D ROMs to six. To assess performance, these PGD ROMs are then applied to two few-group benchmarks characteristic of LWRs. Therein, we find each ROM to be convergent and the axial-polar PGD to be often more economical than the axial PGD. Ultimately, given the popularity of 2D/1D methods in reactor physics, we expect a PGD ROM which achieves a similar effect, but perhaps with superior accuracy, a quicker runtime, and/or broader applicability, would be eminently useful, especially for full-core problems. Finally, we discuss the neutron transport software developed to implement both the the full-order and PGD models, Aether. More specifically, in order to meaningfully apply these ROMs it was necessary to first establish a basic set of features—namely, unstructured mesh geometry, spatial discretization by finite elements, and hyperbolic transport with matrix-freesweeps. Since no software was available that met these requirements, we here develop an original, C++ library, in turn using the deal.II finite element package. Despite the specialized research objectives above, the software is organized such that the particularities of PGD do not appear in the full-order model, but rather are implemented as wrappers around or modifications of it. This allows the library to serve as a general-purpose research tool for deterministic radiation transport, even outside of applications in PGD. Ultimately, we intend to release Aether as a permissively open-source software library, such that others can use and modify this implementation at will. Moreover, while some outstanding features (preconditioning, parallelism) would be practically required, we envision with a modest effort, Aether could be made a useful application for end-users, not just developers, akin to OpenMC or OpenMOC.