FOS Observations of Four NLS1s

Ultraviolet through optical spectroscopy of four NLS1s shows strong absorption features in the high-ionization UV resonance lines such as C IV, N V, and Si IV. Mg II is not absorbed. The absorption could originate in the warm absorber.Comment: Contributed talk presented at the Joint MPE,AIP,ESO workshop on NLS1s, Bad Honnef, Dec. 1999, to appear in New Astronomy Reviews; also available at http://wave.xray.mpe.mpg.de/conferences/nls1-worksho

1A1: Conflicted Loyalties: Austro-Hungarian Immigrants in Michigan and the Great War

On 1 July 1918, US Army PFC Mario Ruconich of 2nd Division, 23rd Infantry Regiment, Company L was killed by German machine gun fire near the village of Vaux, France. He had volunteered for the US Army in January 1917, mustering at the Columbus Barracks in Ohio, where he listed his home as Michigan. His military service record listed his nationality as “Austrian.” PFC Ruconich’s three older brothers also died, or were POWs. Yet they fought for the Central Powers as loyal Austrians on the Italian and Russian Fronts. The Ruconich family spoke Istriot (an Italian dialect) and Croatian came from Istria and – now part of independent Croatia, previously part of Yugoslavia, previously annexed by Italy, previously part of Austria (all within 90 years). During those years, the family named was forcibly Italianized to Rocconi and then forcibly Slavicized to Rukonic (descendants now have all three surnames). The case of PFC Ruconich opens issues of Austro-Hungarian immigrant identity in Michigan against the backdrop of conscription in World War One in the United States and the Habsburg Monarchy. Perhaps half of all Michiganders descend from the lands of the Habsburg Monarchy (southern Poland, Czechia, Slovakia, Austria, Hungary, western Ukraine, Moldova, northwestern Romania, northern Serbia, Croatia, Slovenia, Bosnia-Herzegovina, and northern Italy all were part of the Monarchy). The question of identity and loyalty for migrants involved a complicated understanding and a delicate balance rooted as much in Europe’s historical context as in that of Michigan – a balance that modern war utterly destabilized. In Austria-Hungary most men served loyally in the imperial Army (Mario’s brothers); some emigrated to avoid service (perhaps the case for Mario); and a few, under extenuating circumstances, served the enemy (perhaps the case for Mario, though his motives are unclear and he was fighting Germans not Austrians). Migrants fought loyally for the USA and embraced a new identity, but they also retained strong ties to their homelands. When called upon to serve in a war that ultimately pit their old homeland against the new, the choice was not always easy and more determined by contingency. And following the war, with the disintegration of the old political realities of Central and Eastern Europe, a process of nationalist reinterpretation of the past began that treated the history of each language group as a single, organic struggle for an ethnically homogenous nation-state; Austria-Hungary was now reimagined as an exclusively oppressive force against this allegedly natural, inevitable, and just struggle for ethnic self-determination while each national-ethnic group was reimagined as the oppressed minority. Former Austro-Hungarians readily integrated this new history into their identities and merged it with their new Michigan ones. They became Polish-Americans, Hungarian-Americans and Ukrainian-Americans, adopting many of the symbolic legacies we now find in each of these communities. And today they proudly assert their collective military service for the US as part of that identity – heedless of the fact that, had they been alive in the Great War in Europe, most would have fought loyally for the Austrian Kaiser

Analysis of the Precipitation Detection Algorithm for the GEONOR T-200B Precipitation Gauge to Improve Accuracy

In an effort to improve the precipitation detection algorithm for the Geonor All Weather Precipitation Gauge, an automated truth algorithm has been created to detect errors in the original algorithm. The original algorithm detects precipitation in real time and uses the rate of precipitation to indicate an event. The automated truth does not detect in real time, and focuses on precipitation accumulation to indicate an event. Since the automated truth is delayed, it is able to consider the data collected before and after the point it is analyzing. The automated truth is already more accurate than the original algorithm but the accuracy can be improved further. The goal of this study was to develop ways to improve the automated truth algorithm’s accuracy in order to compare it to the original algorithm to detect errors. Ultimately, this will be used to detect errors in the original algorithm for years of data. In order to improve the truth algorithm, we created a human truth output using data collected over a four month time period by four Geonor gauges located at NCAR’s Marshall Test Field in Boulder, CO. The human truth was created by two individuals who observed the Geonor accumulation data and indicated when an event occurred. Because humans are able to process and analyze images more precisely than computers, this human truth is considered the most accurate output. It was completed using a web based plotting tool to create graphs that can be further analyzed. The human truth output will be compared to the automated truth output in order to detect errors in the algorithm so that scientists will be able to correct these errors and improve the automated truth algorithm

Recent Trends and Results for Organ Donation and Transplantation in the United States, 2005

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72853/1/j.1600-6143.2006.01268.x.pd