6 resultados para REPRESENTATIONS OF PARTIALLY ORDERED SETS
em Digital Commons - Michigan Tech
Resumo:
Phosphomolybdic acid (H3PMo12O40) along with niobium,pyridine and niobium exchanged phosphomolybdic acid catalysts were prepared. Ammonia adsorption microcalorimetry and methanol oxidation studies were carried out to investigate the acid sites strength acid/base/redox properties of each catalyst. The addition of niobium, pyridine or both increased the ammonia heat of adsorption and the total uptake. The catalyst with both niobium and pyridine demonstrated the largest number of strong sites. For the parent H3PMo12O40 catalyst, methanol oxidation favors the redox product. Incorporation of niobium results in similar selectivity to redox products but also results in no catalyst deactivation. Incorporation of pyridine instead changes to the selectivity to favor the acidic product. Finally, the inclusion of both niobium and pyridine results in strong selectivity to the acidic product while also showing no catalyst deactivation. Thus the presence of pyridine appears to enhance the acid property of the catalyst while niobium appears to stabilize the active site.
Resumo:
Nitrogen and water are essential for plant growth and development. In this study, we designed experiments to produce gene expression data of poplar roots under nitrogen starvation and water deprivation conditions. We found low concentration of nitrogen led first to increased root elongation followed by lateral root proliferation and eventually increased root biomass. To identify genes regulating root growth and development under nitrogen starvation and water deprivation, we designed a series of data analysis procedures, through which, we have successfully identified biologically important genes. Differentially Expressed Genes (DEGs) analysis identified the genes that are differentially expressed under nitrogen starvation or drought. Protein domain enrichment analysis identified enriched themes (in same domains) that are highly interactive during the treatment. Gene Ontology (GO) enrichment analysis allowed us to identify biological process changed during nitrogen starvation. Based on the above analyses, we examined the local Gene Regulatory Network (GRN) and identified a number of transcription factors. After testing, one of them is a high hierarchically ranked transcription factor that affects root growth under nitrogen starvation. It is very tedious and time-consuming to analyze gene expression data. To avoid doing analysis manually, we attempt to automate a computational pipeline that now can be used for identification of DEGs and protein domain analysis in a single run. It is implemented in scripts of Perl and R.
Resumo:
Titanium oxide is an important semiconductor, which is widely applied for solar cells. In this research, titanium oxide nanotube arrays were synthesized by anodization of Ti foil in the electrolyte composed of ethylene glycol containing 2 vol % H2O and 0.3 wt % NH4F. The voltages of 40V-50V were employed for the anodizing process. Pore diameters and lengths of the TiO2 nanotubes were evaluated by field emission scanning electron microscope (FESEM). The obtained highly-ordered titanium nanotube arrays were exploited to fabricate photoelectrode for the Dye-sensitized solar cells (DSSCS). The TiO2 nanotubes based DSSCS exhibited an excellent performance with a high short circuit current and open circuit voltage as well as a good power conversion efficiency. Those can be attributed to the high surface area and one dimensional structure of TiO2 nanotubes, which could hold a large amount of dyes to absorb light and help electron percolation process to hinder the recombination during the electrons diffusion in the electrolyte.
Resumo:
Posttraumatic stress and PTSD are becoming familiar terms to refer to what we often call the invisible wounds of war, yet these are recent additions to a popular discourse in which images of and ideas about combat-affected veterans have long circulated. A legacy of ideas about combat veterans and war trauma thus intersects with more recent clinical information about PTSD to become part of a discourse of visual media that has defined and continues to redefine veteran for popular audiences. In this dissertation I examine realist combat veteran representations in selected films and other visual media from three periods: during and after World Wars I and II (James Allen from I Am a Fugitive from a Chain Gang, Fred Derry and Al Stephenson from The Best Years of Our Lives); after the Vietnam War (Michael from The Deer Hunter, Eriksson from Casualties of War), and post 9/11 (Will James from The Hurt Locker, a collection of veterans from Wartorn: 1861-2010.) Employing a theoretical framework informed by visual media studies, Barthes’ concept of myth, and Foucault’s concept ofdiscursive unity, I analyze how these veteran representations are endowed with PTSD symptom-like behaviors and responses that seem reasonable and natural within the narrative arc. I contend that veteran myths appear through each veteran representation as the narrative develops and resolves. I argue that these veteran myths are many and varied but that they crystallize in a dominant veteran discourse, a discursive unity that I term veteranness. I further argue that veteranness entangles discrete categories such as veteran, combat veteran, and PTSD with veteran myths, often tying dominant discourse about combat-related PTSD to outdated or outmoded notions that significantly affect our attitudes about and treatment of veterans. A basic premise of my research is that unless and until we learn about the lasting effects of the trauma inherent to combat, we hinder our ability to fulfill our responsibilities to war veterans. A society that limits its understanding of posttraumatic stress, PTSD and post-war experiences of actual veterans affected by war trauma to veteranness or veteran myths risks normalizing or naturalizing an unexamined set of sociocultural expectations of all veterans, rendering them voice-less, invisible, and, ultimately disposable.
Resumo:
This dissertation seeks to contribute to film, feminist and Latino/a studies by exploring the construction and ideological implications of representations of Latinas in four recent, popular U.S. films: Girlfight (Kusama 2000), Maid in Manhattan (Wang 2002), Real Women Have Curves (Cardoso 2002) and Spanglish (Brooks 2004). These films were released following a time of tremendous growth in the population and the political and economic strength of the Latina/o community as well as a rise in popularity and visibility in the 1990s of entertainers like Selena and actresses such as Jennifer Lopez and Salma Hayek. Drawing on the critical concepts of hybridity, Latinidad, and Bakhtinian dialogism, I analyze these films from a cultural and historical perspective to consider whether and to what degree, assuming changes in the situation of Latinas/os in the 1990’s, representations of Latinas have also changed. Specifically, in this dissertation I consider the ways in which the terrain of the Latina body is articulated in these films in relation to competing societal, cultural and familial conflicts, focusing on the body as a site of struggle where relationships collide, interact and are negotiated. In this dissertation I argue that most of the representations of Latinas in these films defy easy categorization, featuring complex characters grappling with economic issues, intergenerational differences, abuse, mother-daughter relationships, notions of beauty, familial expectations and the very real tensions between Latina/o cultural beliefs and practices and the dominant Anglo culture of the United States. Specifically, I argue that narrative and visual representation of Latina bodies in these films reflects a change in the Latinas offered for consumption to film viewers, presenting us with what some critics have called ‘emergent’ Latinas: conflicted and multilayered representations that in some cases challenge dominant ideologies and offer new demonstrations of Latina agency.
Resumo:
The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.