SIMULTANEOUS ZEROS OF A SYSTEM OF TWO QUADRATIC FORMS

In this dissertation we investigate the existence of a nontrivial solution to a system of two quadratic forms over local fields and global fields. We specifically study a system of two quadratic forms over an arbitrary number field. The questions that are of particular interest are: How many variables are necessary to guarantee a nontrivial zero to a system of two quadratic forms over a global field or a local field? In other words, what is the u-invariant of a pair of quadratic forms over any global or local field? What is the relation between u-invariants of a pair of quadratic forms over any global field and the local fields associated with it? How is the u-invariant of a pair of quadratic forms over any global field related to the u-invariant of its residue field? There are many known results that address 1, 2, and 3: (A) In the context of p-adic fields, a classical result by Dem\u27yanov states that two homogeneous quadratic forms over a p-adic field have a common nontrivial p- adic zero, provided that the number of variables is at least 9. In 1962, Birch- Lewis-Murphy gave an alternative proof to this result by Dem\u27yanov. (B) In a 1964 paper, Swinnerton-Dyer showed that a system of two quadratic forms over the field of rational numbers in 11 variables, satisfying certain number- theoretic conditions, has a nontrivial rational zero (C) An even more remarkable result proven by Colliot-Thélène, Sansuc, and Swinnerton-Dyer extends Dem\u27yanov\u27s result to an imaginary number field and also to an arbitrary number field if certain number-theoretic conditions are satisfied. Our work in this dissertation is motivated by the work on the results stated above. With respect to (A), we generalize the result as well as the proof techniques to prove an analogous result over a complete discretely valued field with characteristic not 2. With respect to (B), we demonstrate that this result, and the techniques used in the proof can be extended to a system of two quadratic forms in at least 11 variables over an arbitrary number field. With respect to (C), we give a more comprehensible and self-contained proof of this result over an arbitrary number field using primarily number-theoretic arguments

Integration Policy and Outcomes for the Russian-Speaking Minority in Estonia

Estonia’s integration policy vis-à-vis its Russian-speaking residents was developed and reformed several times since the dissolution of the Soviet Union in 1991. While comparative data from the international community certainly indicates that Estonia has progressed in the realm of social, political and societal integration, the ‘success’ for each individual policy is now increasingly measured—and contested— within broader considerations of geopolitical security and minority rights. The authors converge interview-based data compiled from various representatives and scholars of nongovernmental organizations, government agencies, and think tanks with secondary research on the topic of Russian minority integration in Estonia. The report will seek to address the ways in which various representatives in both mainstream and bottom-up organizations score and assess Estonia’s development in citizenship, education, and language policy domains for the Russian-speaking minorit

Assessing Cellulosic Biofuel Feedstock Production Across a Gradient of Agricultural Management Systems in the U.S. Midwest

While biofuels are widely considered to be a part of the solution to high oil prices, a comprehensive assessment of the environmental sustainability of existing and future biofuel systems is needed to assess their utility in meeting U.S. energy and food needs without exacerbating environmental harm. The following questions guide this research: 1. What is the spatial extent and composition of agricultural management systems that exist in the U.S. Midwest? 2. How does sub-grid scale edaphic variation impact our estimation of poplar biomass productivity across a gradient of spatial scales in the U.S. Midwest? 3. How do location and management interactions impact yield gap analysis of cellulosic ethanol production in U.S. Midwest? In the first chapter, I developed an algorithm to identify representative crop rotations in the U.S. Midwest, using remotely sensed data; and used this information to detect pronounced shifts from grassland to monoculture cultivation in the U.S. Midwest. In the second chapter, a new algorithm is developed to reduce the computational burden of high resolution ecosystem modeling of poplar plantations in U.S. Midwest, with the results from the high resolution modeling being used to estimate the impact of averaging and discretization of soil properties on poplar yield estimates. In the third chapter, a novel yield gap analysis of cellulosic feedstocks on marginal lands in the U.S. Midwest is conducted to determine the management inputs needed to reach their yield potential in a sustainable manner. The significance of this research lies in providing a spatially explicit regional scale analysis of the tradeoffs between food and fuel production and providing an understanding of which biofuel crops should be grown where to maximize production while mitigating environmental damage

National Geo-Database for Biofuel Simulations and Regional Analysis of Biorefinery Siting Based on Cellulosic Feedstock Grown on Marginal Lands

The goal of this project undertaken by GLBRC (Great Lakes Bioenergy Research Center) Area 4 (Sustainability) modelers is to develop a national capability to model feedstock supply, ethanol production, and biogeochemical impacts of cellulosic biofuels. The results of this project contribute to sustainability goals of the GLBRC; i.e. to contribute to developing a sustainable bioenergy economy: one that is profitable to farmers and refiners, acceptable to society, and environmentally sound. A sustainable bioenergy economy will also contribute, in a fundamental way, to meeting national objectives on energy security and climate mitigation. The specific objectives of this study are to: (1) develop a spatially explicit national geodatabase for conducting biofuel simulation studies and (4) locate possible sites for the establishment of cellulosic ethanol biorefineries. To address the first objective, we developed SENGBEM (Spatially Explicit National Geodatabase for Biofuel and Environmental Modeling), a 60-m resolution geodatabase of the conterminous USA containing data on: (1) climate, (2) soils, (3) topography, (4) hydrography, (5) land cover/ land use (LCLU), and (6) ancillary data (e.g., road networks, federal and state lands, national and state parks, etc.). A unique feature of SENGBEM is its 2008-2010 crop rotation data, a crucially important component for simulating productivity and biogeochemical cycles as well as land-use changes associated with biofuel cropping. ARRA support for this project and to the PNNL Joint Global Change Research Institute enabled us to create an advanced computing infrastructure to execute millions of simulations, conduct post-processing calculations, store input and output data, and visualize results. These computing resources included two components installed at the Research Data Center of the University of Maryland. The first resource was 'deltac': an 8-core Linux server, dedicated to county-level and state-level simulations and PostgreSQL database hosting. The second resource was the DOE-JGCRI 'Evergreen' cluster, capable of executing millions of simulations in relatively short periods. ARRA funding also supported a PhD student from UMD who worked on creating the geodatabases and executing some of the simulations in this study. Using a physically based classification of marginal lands, we simulated production of cellulosic feedstocks from perennial mixtures grown on these lands in the US Midwest. Marginal lands in the western states of the US Midwest appear to have significant potential to supply feedstocks to a cellulosic biofuel industry. Similar results were obtained with simulations of N-fertilized perennial mixtures. A detailed spatial analysis allowed for the identification of possible locations for the establishment of 34 cellulosic ethanol biorefineries with an annual production capacity of 5.6 billion gallons. In summary, we have reported on the development of a spatially explicit national geodatabase to conduct biofuel simulation studies and provided simulation results on the potential of perennial cropping systems to serve as feedstocks for the production of cellulosic ethanol. To accomplish this, we have employed sophisticated spatial analysis methods in combination with the process-based biogeochemical model EPIC. The results of this study will be submitted to the USDOE Bioenergy Knowledge Discovery Framework as a way to contribute to the development of a sustainable bioenergy industry. This work provided the opportunity to test the hypothesis that marginal lands can serve as sources of cellulosic feedstocks and thus contribute to avoid potential conflicts between bioenergy and food production systems. This work, we believe, opens the door for further analysis on the characteristics of cellulosic feedstocks as major contributors to the development of a sustainable bioenergy economy

A global view of shifting cultivation: Recent, current, and future extent

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing–based land cover and land use classifications, as these are unable to adequately capture such landscapes’ dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation at a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation—the majority in the Americas (41%) and Africa (37%)—this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation

Analyzing the Knock-on Impacts of 2022 Floods on Rabi 2023 Using Remote Sensing and Field Surveys

While the world's attention is focused on immediate relief and rescue operations for the affectees of the current floods in Pakistan, knock-on effects are expected to play further havoc with the country's economy and food security in the coming months. Significant crop yield losses had already occurred for Winter (Rabi) 2021-22 due to a heatwave earlier in the year and estimates for the Summer (Kharif) 2022 crop damage due to flood inundation have already been determined to be very high. With the next sowing season already upon the flood affectees, there is a big question mark over the resumption of agricultural activity in disaster-struck districts. This study is aimed at analyzing the range of influences of the 2022 floods on the upcoming winter (Rabi) crop. Satellite-based remote sensing data, state-of-the-art Earth system models, and field observations will be leveraged to estimate the impacts of the flood on the resumption of agricultural activity in the most impacted districts of Southern Punjab, Sindh, and Baluchistan. The field surveys are conducted during multiple visits to the study area to maximize the monitoring of on-ground conditions and provide a larger validation dataset for the satellite-based inundation and crop classification maps. The project leverages on the expertise and previous experiences of the LUMS team in performing satellite-based land/crop classification, estimation of soil moisture levels for irrigation activity, and determining changes in land-use patterns for detecting key agricultural activities. Delays in the sowing of the winter crop and its effects on crop-yield were analyzed through this study

Forensic Analysis in Wildlife Crime Cases: Microscopy, DNA Profiling and Isotope Analysis

Illegal wildlife trade is one of the biggest threats to the environment and biodiversity. The growing volume of illegal trade in wildlife jeopardizes all the conservation efforts across the globe. Many species have become extinct due to the illegal wildlife trade and many have reached the verge of extinction. According to some estimates, the monetary values of the illegal wildlife trade are estimated to be several billion US dollars. To deal with wildlife crime cases, it becomes imperative to have a sound knowledge of the techniques required in the analysis of wildlife crime exhibits. In this chapter, we have outlined the three frequently used techniques in wildlife forensics viz. microscopy, DNA and isotope analysis for addressing the problems of species and individual identification, and additionally identification of the geographical origin of a wildlife sample. The basic essentials of these techniques have been discussed in this chapter

Clinical validation of a multiplex PCR-based detection assay using saliva or nasopharyngeal samples for SARS-Cov-2, influenza A and B

The COVID-19 pandemic has resulted in significant diversion of human and material resources to COVID-19 diagnostics, to the extent that influenza viruses and co-infection in COVID-19 patients remains undocumented and pose serious public-health consequences. We optimized and validated a highly sensitive RT-PCR based multiplex-assay for the detection of SARS-CoV-2, influenza A and B viruses in a single-test. This study evaluated clinical specimens (n = 1411), 1019 saliva and 392 nasopharyngeal swab (NPS), tested using two-assays: FDA-EUA approved SARS-CoV-2 assay that targets N and ORF1ab gene, and the PKamp-RT-PCR based assay that targets SARS-CoV-2, influenza viruses A and B. Of the 1019 saliva samples, 17.0% (174/1019) tested positive for SARS-CoV-2 using either assay. The detection rate for SARS-CoV-2 was higher with the multiplex assay compared to SARS-specific assay [91.9% (160/174) vs. 87.9% (153/174)], respectively. Of the 392 NPS samples, 10.4% (41/392) tested positive for SARS-CoV-2 using either assay. The detection rate for SARS-CoV-2 was higher with the multiplex assay compared to SARS-specific assay [97.5% (40/41) vs. 92.1% (39/41)], respectively. This study presents clinical validation of a multiplex-PCR assay for testing SARS-CoV-2, influenza A and B viruses, using NPS and saliva samples, and demonstrates the feasibility of implementing the assay without disrupting the existing laboratory workflow

High-Throughput Next-Generation Sequencing Respiratory Viral Panel: A Diagnostic and Epidemiologic Tool for SARS-CoV-2 and Other Viruses

Two serious public health challenges have emerged in the current COVID-19 pandemic namely, deficits in SARS-CoV-2 variant monitoring and neglect of other co-circulating respiratory viruses. Additionally, accurate assessment of the evolution, extent, and dynamics of the outbreak is required to understand the transmission of the virus. To address these challenges, we evaluated 533 samples using a high-throughput next-generation sequencing (NGS) respiratory viral panel (RVP) that includes 40 viral pathogens. The performance metrics revealed a PPA, NPA, and accuracy of 95.98%, 85.96%, and 94.4%, respectively. The clade for pangolin lineage B that contains certain distant variants, including P4715L in ORF1ab, Q57H in ORF3a, and S84L in ORF8 covarying with the D614G spike protein mutation, were the most prevalent early in the pandemic in Georgia, USA. The isolates from the same county formed paraphyletic groups, indicating virus transmission between counties. The study demonstrates the clinical and public health utility of the NGS-RVP to identify novel variants that can provide actionable information to prevent or mitigate emerging viral threats and models that provide insights into viral transmission patterns and predict transmission/resurgence of regional outbreaks as well as providing critical information on co-circulating respiratory viruses that might be independent factors contributing to the global disease burden