Monomial, Gorenstein and Bass Orders

In this article we study a class of orders called {\it monomial orders} in a central simple algebra over a non-Archimedean local field. Monomial orders are easily represented and they may be also viewed as a direct generalization of Eichler orders in quaternion algebras. A criterion for monomial orders to be Gorenstein or to be Bass is given. It is shown that a monomial order is Bass if and only if it is either a hereditary or an Eichler order of period two.Comment: 13 pages; fix typos in the proof of Theorem 3.

Little Elongation Complex (lec) And Super Elongation Complex (sec) As Regulators Of Tdp-43-Associated Neurodegeneration

TDP-43 aggregation is the pathological hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with ubiquitinated inclusions (FTLD-TDP). To define pathways important in TDP-43 proteinopathy, a genetic screen for modifiers of TDP-43-mediated eye degeneration was conducted in the fruit fly (Drosophila melanogaster). This approach and the following studies in the fly identified transcriptional elongation factor Ell as a potent dose-dependent modifier. Ell is a shared component of little elongation complex (LEC) and super elongation complex (SEC). Our studies show that downregulation of additional components in LEC or SEC partially but consistently ameliorates TDP-43-associated eye degeneration, implicating both Ell-associated complexes in TDP-43 toxicity. LEC regulates transcription of RNA Polymerase II (Pol II)-transcribed small nuclear RNAs (snRNAs), while SEC mainly regulates transcription of select inducible genes harboring paused Pol II including stress-induced loci. We hypothesized that, in the disease state, TDP-43 increases the activity of LEC and SEC, leading to enhanced expression of select target genes that contribute to neurodegeneration. Our results support this hypothesis by showing that select targets of LEC and SEC become upregulated in fly heads expressing TDP-43 compared to controls. Among upregulated targets, U12 snRNA and a stress-induced long non-coding RNA (lncRNA) Hsr were shown to functionally contribute to TDP-43-induced degeneration in Drosophila. The increase in U12 snRNA leads to elevated activity of the U12-dependent spliceosome, assessed by examining U12-dependent splicing events. Among the known U12 targets, the splicing of genes CG15735, CG16941 and CG11839 were shown to be upregulated selectively by TDP-43. In addition, the novel target of TDP-43 Hsr was identified by polytene chromosome association of TDP-43 and SEC components Lilli and Ell in the fly. We extended the findings of Hsr to show that the human orthologue Satellite III repeat (Sat III) is elevated in both a human cellular disease model of TDP-43 toxicity, and FTLD-TDP patient tissue. Furthermore, TDP-43 was shown to interact with human ELL2 by co-immunoprecipitation from human HEK293 cells. These findings support a model whereby TDP-43 promotes the LEC and SEC activities through an interaction with ELL2, leading to abnormal activation of LEC and SEC target genes that contribute to degeneration. These studies reveal the critical roles of Ell and Ell-associated complexes in TDP-43 toxicity, identify important downstream targets, and provide potential therapeutic strategies to combat TDP-43-associated neurodegeneration

Supersingular abelian surfaces and Eichler class number formula

Let $F$ be a totally real field with ring of integers $O_F$, and $D$ be a totally definite quaternion algebra over $F$. A well-known formula established by Eichler and then extended by K\"orner computes the class number of any $O_F$-order in $D$. In this paper we generalize the Eichler class number formula so that it works for arbitrary $\mathbb{Z}$-orders in $D$. The motivation is to count the isomorphism classes of supersingular abelian surfaces in a simple isogeny class over a prime finite field $\mathbb{F}_p$. We give explicit formulas for the number of these isomorphism classes for all primes $p$.Comment: 29 pages, 3 numerical tables, shortened revised version with same results, Sections 7-9 of v2 are remove

Automated video processing and scene understanding for intelligent video surveillance

Title from PDF of title page (University of Missouri--Columbia, viewed on December 7, 2010).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dissertation advisor: Dr. Zhihai He.Vita.Ph. D. University of Missouri--Columbia 2010.Recent advances in key technologies have enabled the deployment of surveillance video cameras on various platforms. There is an urgent need to develop advanced computational methods and tools for automated video processing and scene understanding to support various applications. In this dissertation, we concentrate our efforts on the following four tightly coupled tasks: Aerial video registration and moving object detection. We develop a fast and reliable global camera motion estimation and video registration for aerial video surveillance. 3-D change detection from moving cameras. Based on multi-scale pattern, we construct a hierarchy of image patch descriptors and detect changes in the video scene using multi-scale information fusion. Cross-view building matching and retrieval from aerial surveillance videos. Identifying and matching buildings between camera views is our central idea. We construct a semantically rich sketch-based representation for buildings which is invariant under large scale and perspective changes. Collaborative video compression for UAV surveillance network. Based on distributed video coding, we develop a collaborative video compression scheme for a UAV surveillance network. Our extensive experimental results demonstrate that the developed suite of tools for automated video processing and scene understanding are efficient and promising for surveillance applications.Includes bibliographical reference

Estimating the Impacts of Climate Change on Mortality in OECD Countries

The major contribution of this study is to combines both climatic and macroeconomic factors simultaneously in the estimation of mortality using the capital city of 22 OECD countries from the period 1990 to 2008. The empirical results provide strong evidences that higher income and a lower unemployment rate could reduce mortality rates, while the increases in precipitation and temperature variation have significantly positive impacts on the mortality rates. The effects of changing average temperature on mortality rates in summer and winter are asymmetrical and also depend on the location. Combining the future climate change scenarios with the estimation outcomes show that mortality rates in OECD countries in 2100 will be increased by 3.77% to 5.89%.Climate change; mortality; panel data model