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2020 Democratic presidential candidates tweets about climate change
No full textDatabase of four 2020 Democratic presidential candidates' tweets about climate change, including Joe Biden, Pete Buttigieg, Bernie Sanders, and Elizabeth Warren.Climate change is a consensus issue among US Democrats, yet even within this agreement there can be divergence. Rooted in scholarship on rational choice theory and framing, this study content analyzes how the top four 2020 Democratic presidential candidates differentially framed climate change on Twitter. Results revealed that (a) progressive versus moderate Democrats constructed climate change narratives befitting their intraparty ideologies, (b) candidates created cohesive framing strategies across Entman’s (1993) framing functions and a newly proposed function of framing affected publics, and (c) climate change frames were integrated with the campaign’s overarching themes and issue foci.NoneYesDouble blind peer review process for the accepted article which uses the database
Fundamental and Translational Applications of LC-MS/MS Based Metabolomics in Infectious Diseases
No full textMetabolomics is the study of small molecules (metabolites) <1500 Da. It combines analytical and biochemical techniques to help understand disease pathogenesis. Metabolites also change dynamically in response to disease and hence corresponds closely to host phenotype. They can ultimately present information related to host and disease metabolism. Liquid chromatography tandem mass spectrometry (LCMS/MS) is a technique most used for metabolomics because it is the most sensitive, it has high statistical power, large software availability to analyze data output, and has a high structure annotation confidence. It also can analyze several sample types including tissues, biofluids, and cells. Combining LCMS/MS with a technique called ‘spatial metabolomics or chemical cartography’ can address knowledge gaps in the realm of infectious diseases. Spatial metabolomics/chemical cartography integrates analytical, biochemical, and computational techniques to study metabolites in 3D space. It allows the mapping of metabolites onto 3D organs to determine pathogen and metabolite location, tropism, and distribution. Ultimately, it helps to understand the relationship between local tissue metabolic perturbation and clinical disease symptoms and gives insight to disease pathogenesis. Chagas disease is a neglected tropical disease that is severely understudied and understood, yet affects millions of people worldwide. The influenza virus is one of the most concerning viral based diseases due to its high infection rate. LCMS/MS based spatial metabolomics can be implemented to study these diseases to reveal novel information about how host and disease/disease causing agents interact in the body. In this dissertation, I present fundamental and translational applications of LCMS/MS-based metabolomics in infectious diseases. The data presented here supports the use of spatial metabolomics/chemical cartography in infectious diseases to further understand disease pathogenesis and how infection, whether viral or parasitic, affects host metabolism
Tortuosity of Tight Rocks
Get PDFTortuosity is a rock property that controls transport processes in porous media. It is essential in advective, diffusive transport and flow of electric current, especially in tight rocks which are characterized by low porosity and low permeability such as unconventional shale reservoirs. However, experimental values of diffusional and electrical tortuosity of tight rocks are scarce in the literature. To improve the understanding of diffusive transport and electrical flow in unconventional tight rock reservoirs, I have measured and compared the diffusional and electrical tortuosities of 12 tight rock samples from Utica, Bakken, Wolfcamp, and Eagle Ford formations and 3 sandstones from Berea, Lyon and Illinois Basin.
For this study, the samples selected were characterized by measurements of total organic carbon (TOC), mineralogy, porosity, and pore size distributions using scanning electron microscopy image analysis, mercury injection capillary pressure, and subcritical nitrogen adsorption. Upon characterization, the samples were soxhlet-extracted with methanol and dried at 100°C before saturating with 25,000 ppm KCl brine. To measure diffusional tortuosity, the brine saturated samples were immersed into D2O to allow the diffusion of D2O into the samples. The rates at which D2O diffused into the samples were measured with 12 MHz NMR instruments. The effective pore fluid diffusion coefficient of D2O and the bulk diffusion coefficient of D2O were used to compute the diffusional tortuosities.
To measure the electrical tortuosities, the samples were resaturated with 25,000 ppm KCl brine before immersion into 60,000 ppm KCl brine. The measurements of the samples’ resistivities as a function of time after the immersion into the 60,000 ppm KCl brine were used to compute effective pore ionic diffusion coefficients. These effective pore ionic diffusion coefficients were used in combination with the ionic bulk diffusion coefficient to compute the electrical tortuosity of the samples.
Our measurements show that the diffusional tortuosity and electrical tortuosity have similar values. Therefore fluid diffusion and electrical conduction are controlled by the same flow path.
These tortuosities in the tight rock samples range between 1.8 to 5.8, while the sandstones range between 1.4 to 3.9.
A method to determine effective porosity was also developed and it was observed that the effective porosity in the tight rocks ranged between 45 - 93% of the total porosity, while the sandstones had effective porosities approximately equal to the total porosity.
For the unconventional tight rock samples studied, it is observed that TOC exerts a primary control on the diffusional and electrical tortuosity as well as effective porosity of tight rocks.
The observations made in this study indicate that electrical and diffusive flow are controlled by the same flow path. Therefore, electrical tortuosity from resistivity formation factor measurements can be used in place of diffusional tortuosities in huff-n-puff EOR design and optimization because the electrical tortuosity measurements can be performed in minutes while diffusional tortuosity measurements take weeks to complete. Also, the knowledge of electrical tortuosity is important in determining electrical parameters to accurately determine the water saturation
Using correlated imaging and difference frequency generation to determine the group delay for an unknown ultra short optical pulse: An analytical and numerical simulation calculation
Get PDFA pulse laser emits ultrashort optical pulses with pulse widths on the order of pico-seconds and narrower. A full characterization of these optical pulses requires complete knowledge of their corresponding spectral amplitude and phase. Once complete knowledge of the corresponding spectral amplitude and phase are known for a pulse it can then pass through a pulse modulator to be manipulated to nearly any desired shape. While spectral amplitude is easy to achieve, the square root of measured spectral intensity, spectral phase is unobtainable with current measuring equipment. Group delay is the derivative of spectral phase with respect to frequency. Spectral phase is the integral of group delay with respect to frequency plus a constant frequency independent phase. While group delay can be determined by the following techniques: frequency resolved optical gating (FROG), spectral phase interferometry for direct electric-field reconstruction (SPIDER), and multiphoton intrapulse interference phase scan (MIIPS) a new way of determining group delay is presented.
Determining group delay is achieved through the combination of four things: difference frequency generation in a nonlinear material, a frequency to spatial conversion, a binary spatial light modulator (BSLM), and correlated imaging (aka ghost imaging). A newly generated frequency due to difference frequency generation has a phase that is a result of an integral sum of phase differences. This phase can be determined as a result of frequency down shift due to difference frequency generation. Correlated imaging uses two detectors: one detector spatially resolves an incident field upon an object while the other detector which has no spatial resolution measures the fields response to the object. An image of the object is formed through the cross correlation of the two detectors involving many different realizations. By using a frequency to spatial conversion and BSLM we can select which frequencies contribute to the integral sum of phase differences. By correlating the contributing frequencies to the resulting phase of the newly generated frequency through many different BSLM realizations group delay can be determined. Group delay is shown to be able to be determined this way through analytical calculations and numerical simulation
Exploring the careers of professional academic advisors at Oklahoma community colleges: a multiple-case study
Get PDFThis qualitative, multiple-case study explored the career choice and development of academic advisors at Oklahoma community colleges Data for this study were derived from participant interviews and information about the community colleges from which the participants were employed. There were nine participants from five Oklahoma community colleges in this study. Data were analyzed using a constructivist approach and Social Cognitive Career Theory (SCCT) as a theoretical framework. The study found three overarching themes connected to the SCCT framework that explain the career choice of academic advisors at Oklahoma community colleges: 1) helping others is an innate characteristic of their personality and influences their approach to advising students; 2) participants identified positive learning experiences in school or college that influenced their desire to work in higher education; 3) the location of the institution was a salient factor in their career decision. In addition to the analytical themes of SCCT, the data revealed observations from the findings that extend beyond the scope and theoretical framework of this study; yet warrant further exploration: 1) working at a rural community college, and 2) the impact of state and institutional budget cuts on Oklahoma community colleges
A conductor's guide and analysis to Korean traditional choral music techniques in Creo by Hyowon Woo
Get PDFThe music of Korean choral composer Hyowon Woo (b.1974) is known throughout the world. Woo’s oratorio, Creo was commissioned for Dr. Hakwon Yoon and the Incheon City Chorale, and was premiered in 2012 in Incheon, South Korea. Creo, which means "Create," is an oratorio composed of 11 movements. The Latin text used by Woo is based on the first chapter of Genesis, the first book of the Bible. Creo is an outstanding example of Woo's compositional style. The combination of traditional Korean music and Western music elements in her choral work, Creo, has created a new musical genre.
This dissertation will explore the compositional background of Creo wherein are combined characteristic elements of both East Asian and Western music. By way of examining Creo, Korean choral music in general will be treated from a historical and stylistic perspective. It is interesting to note that Woo used Korean traditional elements of vocal style, scale, texture, and structure, in addition to variety of choral composition techniques. In particular, the combination of Latin text and instruments depicts scenes in Genesis, such as the light and the darkness, the firmament, the earth and plants, the firmament of heaven, the seasons, the living and moving creatures, and the story of Adam and Eve. Text painting, and Korean traditional instruments play a very important role in expressing the beauty and sound of Korea.
Since the beginning of the twenty-first century, Korean choral music enjoyed a dramatic expansion in terms of quantity and quality. Nevertheless, resources for Western conductors of Korean choral music remains limited, thus hindering a wider international reception of this distinctive and engaging music. This document is written with the goal of providing the necessary historical and stylistic information that will give conductors an understanding to perform Hyowon Woo’s Creo to the highest possible artistic standard
Scaling up Labeling, Mining, and Inferencing on Event Extraction
Get PDFNumerous important events happen every day and are reported in different media sources with varying narrative styles across different knowledge domains and languages. Detecting the real-world events that have been reported from online articles and posts is one of the main tasks in event extraction. Other tasks include identifying event triggers and trigger types, identifying event arguments and argument types, clustering and tracking similar events from different texts, event prediction, and event evolution. As one of the most important research themes in natural language processing and understanding, event extraction has wide applications in diverse domains and has been intensively researched for decades. This work targets a scaling-up of End-to-End event extraction task through three ways. First, scaling up the event labeling process to different languages and domains. We designed and implemented four approaches to accurately and efficiently produce multi-lingual labels for events. Using the approaches we developed, we were able to complete Arabic actor and verb dictionaries with coverage equivalent to English in less than two years of work, compared to two decades for English dictionary development. Second, scaling up event extraction by using the document topics information in a topic-aware deep learning framework. We propose a domain-aware event extraction method by using the topic name embeddings to enrich the sentences' contextual representations and multi-task setup of event extraction and topic classification task. With the topic-aware model we developed, we were able to improve F1 by 1.8% on all event types, and F1 by 13.34% on few-shot event types. Third, scaling up event extraction by designing containerized and efficient pipelines, which researchers can comfortably adopt. The pipeline has a container-based architecture that adapts to the available systems and load to process text. With the Kalman filter based batch size optimization, we were able to achieve 20.33% improvement on processing time compared to static batch size. Using the pipeline we developed, we were able to publish largest machine-coded political event dataset covering 1979 to 2016 (2TB, 300 million documents)