Sweet Tooth for Empire: Sugar and the British Atlantic World

With increasing productivity and rising standards of living, a new spirit of consumerism reached Britain. After its entry into the Atlantic World economy, though Scotland never fully benefited until the 1707 Act of Union, all classes eventually gained access to a wide variety and exotic assortment of consumer products. Among them, sugar, valued for its sweetness since the Middle Ages, maintained a special position, dominating all exports from British America. Embraced by the British populace, sugar provided an impetus for colonization and required imported African labor. Sugar and a newfound consumerism at home drove the British Atlantic World

“Bloody Outrages of a Most Barbarous Enemy:” The Cultural Implications of the Massacre at Fort William Henry

The August 10, 1757 massacre at Fort William Henry contradicted eighteenth-century European standards for warfare. Although British colonial opinion blamed it on Native American depravity, France‘s Native American allies acted within their own cultural parameters. Whereas the French and their British enemies believed in the supremacy of the state as the model for conduct, Native Americans defined their political and military relations on a personal level that emphasized mutual obligations. With the fort‘s surrender, however, the French and British attempted and failed to bring European cultural norms into the American wilderness. While the French triumphed in Fort William Henry‘s capitulation, Native Americans required plunder, scalps, and prisoners to prove individual valor and an honorable victory. Denied the spoils of victory with the surrender, they seized the initiative in their assault on the siege‘s survivors. The massacre at Fort William Henry revealed a gruesome divergence between two differing concepts of diplomacy and warfare

Location Prediction for Context-Aware Applications

Context-aware applications are programs that are able to improve their performance by adapting to the current conditions, which include the user's behavior, networking conditions, and charging opportunities. In many cases, the user’s location is an excellent predictor of the context. Thus, by predicting the user’s future location, we can predict the future conditions. In this thesis, we develop techniques to identify and predict the user's location over the next 24 hours with a minimum median accuracy of 82%. We start by describing the user study that we conducted, and some salient conclusions from our analysis. These include our observation that cell phones sample the towers in their vicinity, which makes cell towers as-is inappropriate for use as landmarks. Motivated by this observation, we develop two techniques for processing the cell tower traces so that landmarks more closely correspond to locations, and cell tower transitions more closely correspond to user movement. Then, we present our prediction engine, which is based on simple sampling distributions of the form f(t, c), where t is the predicted tower, and c is a set of conditions. The conditions that we considered include the time of the day, the day of the week, the current regime, and the current tower. Our family of algorithms, called TomorrowToday, achieves 89% prediction precision across all prediction trials for predictions 30 minutes in the future. This decreases slowly for predictions further in the future, and levels off for predictions approximately 4~hours in the future, at which point we achieve 82% prediction precision across all prediction trials up to 24 hours in the future. This represents a significant improvement over NextPlace, a well-cited prediction algorithm based on non-linear time series, which achieves appropriately 80% prediction precision (self reported) for predictions 30~minutes in the future, but, unlike our predictors, which try all prediction attempts, NextPlace only attempts 7% of the prediction trials on our data set

Location Prediction for Context-Aware Applications

Context-aware applications are programs that are able to improve their performance by adapting to the current conditions, which include the user's behavior, networking conditions, and charging opportunities. In many cases, the user’s location is an excellent predictor of the context. Thus, by predicting the user’s future location, we can predict the future conditions. In this thesis, we develop techniques to identify and predict the user's location over the next 24 hours with a minimum median accuracy of 82%. We start by describing the user study that we conducted, and some salient conclusions from our analysis. These include our observation that cell phones sample the towers in their vicinity, which makes cell towers as-is inappropriate for use as landmarks. Motivated by this observation, we develop two techniques for processing the cell tower traces so that landmarks more closely correspond to locations, and cell tower transitions more closely correspond to user movement. Then, we present our prediction engine, which is based on simple sampling distributions of the form f(t, c), where t is the predicted tower, and c is a set of conditions. The conditions that we considered include the time of the day, the day of the week, the current regime, and the current tower. Our family of algorithms, called TomorrowToday, achieves 89% prediction precision across all prediction trials for predictions 30 minutes in the future. This decreases slowly for predictions further in the future, and levels off for predictions approximately 4~hours in the future, at which point we achieve 82% prediction precision across all prediction trials up to 24 hours in the future. This represents a significant improvement over NextPlace, a well-cited prediction algorithm based on non-linear time series, which achieves appropriately 80% prediction precision (self reported) for predictions 30~minutes in the future, but, unlike our predictors, which try all prediction attempts, NextPlace only attempts 7% of the prediction trials on our data set

The Replication and Turnover-Synthesis of Chloroplast Deoxyribonucleic Acid From Euglena Gracilis

170 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1977.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Misalignment of V and J gene segments resulting in a nonfunctional immunoglobulin gene.

The myeloma variant NS-1n has lost the functional immunoglobulin kappa gene which is present in its parent, myeloma MOPC-21. The variant retains a nonfunctional rearranged gene, M.21N, which undergoes RNA transcription and processing to yield a mature size kmRNA. This kRNA, however, is not translated into kappa polypeptide chains. The nonfunctional gene was cloned into Charon 4A to determine the basis for its inactivity. Nucleotide sequence analysis of a DNA fragment overlapping the V-J recombination site in the M.21N gene indicated that a misalignment had taken place during somatic recombination. This misalignment results in a deletion of four nucleotides at the 3' end of the V gene and, thus, a translational reading frame shift. In other respects the M.21n V gene, which corresponds to a different VK subgroup than the functional gene of MOPC-21, appears normal

Comparison of different rearranged immunoglobulin kappa genes of a myeloma by electronmicroscopy and restriction mapping of cloned DNA: implications for "allelic exclusion".

We have studied the organization and function of different rearranged kappa genes in a myeloma, MOPC-21. Two kappa genes were cloned into Charon 4A and compared with each other and with a cloned germline CK gene by restriction mapping and electron microscopy. One MOPC-21 clone corresponds to the gene coding for the MOPC-21 kappa chain polypeptide; it has the V21 gene joined with the CK gene at the J2 sequence. The other MOPC-21 clone corresponds to a nonfunctional rearranged MOPC-21 kappa gene, except for a lkb deletion, 3' of J4. A similar deletion is also found in a "new" kappa gene present in NS-1, a cellular subclone of MOPC-21. The clone of the "nonfunctional" kappa gene has a V gene which is distinct from V21 which is joined to CK in the vicinity of J2. The undeleted form of this gene codes for a KRNA having the size of mature KmRNA which, however, is not translated into kappa chains. Thus the defect of the "nonfunctional" gene manifests itself at a late step of gene expression. The basis for "allelic exclusion" of antibody genes may simply be the complexity of the processes between genes and gene products, resulting in the expression of only one gene