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Evaluating Evo Morales: The Conflicts and Convergences of Populism, Resource Nationalism, and Ethno-Environmentalism in Bolivia
Get PDFThis thesis seeks to integrate existing scholarly frameworks of populism, resource nationalism, and ethno-environmentalism in order to create a comprehensive understanding of Morales and the MAS. From 2006 until 2019, President Evo Morales and the Movimiento al socialismo (MAS) led Bolivia to global prominence. Experts lauded Morales and the MAS for apparent development successes and democratic expansion in a nation long known for its chronic poverty and conflict. Still, by the time of his controversial resignation, several socioenvironmental conflicts had diminished his reputation as an ethno-environmental champion, revealing the tensions inherent in pursuing resource nationalist development in an ethnopopulist state. While existing scholarship on the subject views populist and resource nationalist strategies and policies separately, their functional convergence in the Isiboro Sécure National Park and Indigenous Territory (TIPNIS) conflict demonstrates the necessity of an integrated framework. An integrative examination of the TIPNIS conflict reveals that the MAS prioritization of modernist development above all else. The Bolivian case provides a unique avenue for insight into progressive populism and ethno-environmental governance across Latin American politics, where commitments to aggressive visions of developmentalism characterize parties and political actors across the political spectrum
Manufacturing Strategy for the Production of 200 Million Sterile Doses of an mRNA Vaccine for COVID-19
Get PDFmRNA vaccines are a new frontier of medicine. Unlike pre-existing vaccine technologies, mRNA vaccines present the human body with the genetic information to make a protein whose production incites a natural immune response. In this manner, mRNA vaccines create antibodies and build immunity towards pathogens resulting in the same protection as traditional vaccines yet without presenting the body with the foreign virus. Among the many advantages of this new technology is that the manufacturing process, rather than being specific to a virus or recombinant protein, is specific to mRNA. In this manner, the process is independent of the actual disease the vaccine targets and is only dependent on the biological properties of an mRNA strand. This is tremendously advantageous since the same manufacturing process can be used for the mRNA strand of any genetic mutation of a virus or even for a completely different pathogen.
This proposal is for a manufacturing process to produce 200 million sterile doses of an mRNA vaccine against SARS-CoV-2 in a 13-week period thereby vaccinating 100 million people. The process uses Pfizer\u27s pharmaceutical formulation and starts with a plasmid DNA that contains the genetic code for the entire viral spike (S) glycoprotein. The pDNA is fed to a WAVE bioreactor for an in vitro transcription (IVT) reaction that produces mRNA through phage T7 RNA polymerase. The mRNA is purified through two diafiltration steps with an 100 kDa MWCO, a chromatography column to remove undesired dsRNA and a sterile filter to remove biological impurities. The purified mRNA is then diluted in 50 mM sodium acetate and fed to one of the twenty-five 16X microfluidics devices along with a mixture of lipids in an ethanol buffer. With a flowrate ratio of 3:1, the mRNA is encapsulated into the lipid mixture in the microfluidics devices to make lipid nanoparticles (LNPs). This step is key since the lipid-based capsule serves as an envelope for the mRNA, when injected in the human body, to enter the cell\u27s cytoplasm with high stability and without disintegration. The LNPs are purified through a 100 kDa MWCO diafilter in a third tangential flow filtration device and a sterile filter. These purified LNPs are diluted with 1X PBS and sucrose to meet the desired concentration of all components in the pharmaceutical formulation and the mRNA concentration of 0.5 mg/mL. Each week this continuous manufacturing process will fully produce 15.4 sterile million doses that will be packaged into 2 million vials. The vials will be sent out in thermal containers following the regulatory storage and freezer conditions. Throughout the process, the quality of the product will be ensured through the use of sterile and FDA approved equipment, the control of the length of the mRNA produced from the IVT reactor and an endotoxin level test. The proposed process has an internal rate of return of 449%, a return on investment of 475% and a net present value of $19.6 billion dollars. Beyond its application in the strategy to address the current COVID-19 global pandemic, this proposed process will be part of pushing the frontiers of medicine with the novel use of mRNA vaccines
Thriving for Individuals with Disabilities: Towards a Collective Model in Midland County, Michigan
Get PDFMidland County, Michigan, is a progressive community in which positive psychology contributes to the flourishing of its citizens. They have formed a Steering Committee consisting of numerous organizations that serve people living with disabilities. The purpose of this project was to develop a collective model of success for individuals with disabilities that would enable agencies supporting this population to effectively partner and build flourishing for this community. This project identified four key pillars that support thriving for individuals with disabilities: character strengths, self-determination, mattering, and belonging. Through a series of 15-minute workshops facilitated by a Steering Committee member, they will understand the construct of each pillar, have the opportunity to practice specific interventions in their personal and professional lives, and develop ways to implement the key concepts within their agencies to serve the individuals with disabilities
MEMS Device Demonstration for High School Students or Nonspecialists
Get PDFMicro-electromechanical systems (MEMS) devices have many unique advantages, and offer an exciting entrance for students into the field of nanotechnology and nanofabrication. In this article, an educational hands-on laboratory protocol with MEMS devices is proposed. Using a paper airplane, an Arduino, and the MPU 6050 MEMS accelerometer/gyroscope sensor students are able to create a graphical aircraft attitude indicator. The data is then processed on the Arduino, which is connected to a computer. The computer can then run graphics software displaying a digital aircraft attitude indicator showing the roll and pitch of the aircraft live.https://repository.upenn.edu/scn_educational/1000/thumbnail.jp
\u27Nuove Prospettive sulla Tradizione della “Commedia.” Terza Serie (2020).\u27 Martina Cita, Federico Marchetti, and Paolo Trovato, eds. Padua: libreriauniversitaria.it edizioni, 2021.
Get PDFKatelynn Robinson. \u27The Sense of Smell in the Middle Ages: A Source of Certainty.\u27 London-New York: Routledge, 2020.
Get PDFMapping Spaces, Signatures, And Data
Get PDFTime-varying phenomena are ubiquitous across pure and applied mathematics, from path spaces and stochastic differential equations to multivariate time series and dynamic point clouds. The path signature provides a powerful characterization of such sequential data in terms of power series of tensors, weaving together these diverse concepts. Originally defined as part of Chen\u27s iterated integral cochain algebra, the path signature has since been used as the foundation for the theory of rough paths in stochastic analysis. More recently, it has been shown to be a universal and characteristic feature map for multivariate time series, providing theoretical guarantees for its application to time series analysis in the context of kernel methods in machine learning. This thesis extends the scope of the path signature to more complex parametrized data in two directions. First, we consider generalizations of the codomain of a path. We lift the theory of signatures to the setting of Lie group valued time series, adapting these tools for time series with underlying geometric constraints. Furthermore, we build a signature framework to study paths of persistence diagrams, objects which capture the evolving topological structure of dynamic data sets. Second, we consider maps parametrized by higher dimensional cubes by developing notions of the mapping space signature. Our approach returns to the topological origins of the signature as the 0-cochains of the Chen construction. We formulate a cubical variant of the mapping space construction, and use the resulting 0-cochains to define the mapping space signature and establish its basic properties
Learning To Compositionally Reason Over Natural Language
Get PDFThe human ability to understand the world in terms of reusable ``building blocks\u27\u27 allows us to generalize in near-infinite ways. Developing language understanding systems that can compositionally reason in a similar manner is crucial to achieve human-like capabilities. Designing such systems presents key challenges in the architectural design of machine learning models and the learning paradigm used to train them. This dissertation addresses aspects of both of these challenges by exploring compositional structured models that can be trained using end-task supervision.
We believe that solving complex problems in a generalizable manner requires decomposition into sub-tasks, which in turn are solved using reasoning capabilities that can be reused in novel contexts. Motivated by this idea, we develop a neuro-symbolic model with a modular architecture for language understanding and focus on answering questions requiring multi-step reasoning against natural language text. We design an inventory of freely-composable, learnable neural modules for performing various atomic language understanding and symbolic reasoning tasks in a differentiable manner. The question guides how these modules are dynamically composed to yield an end-to-end differentiable model that performs compositional reasoning and can be trained using end-task supervision. However, we show that when trained using such supervision, having a compositional model structure is not sufficient to induce the intended problem decomposition in terms of the modules; Lack of supervision for the sub-tasks leads to modules that do not freely compose in novel ways, hurting generalization. To address this, we develop a new training paradigm that leverages paired examples---instances that share sub-tasks---to provide an additional training signal to that provided by individual examples. We show that this paradigm induces the intended compositional reasoning and leads to improved in- and out-of-distribution generalization