2,164 research outputs found
Gallium(III)-Promoted Halocyclizations of 1,6-Diynes
Adrian Landreth was an REU student, summer 2014Cyclization of 1,6-diynes promoted by stoichiometric Ga(III) halides produces vinyl halides in good to excellent yields. Under acidic conditions, initially formed iodocyclization products undergo in situ Friedel-Crafts cyclizations, giving access to iodo-indenopyridines. The application of the vinyl halides in cross-coupling reactions has been explored, and mechanistic aspects of the cyclization are discussed.HIGMS CMLD Initiative (P50 GM067041)
NSF REU - Adrian Landreth support (CHE 1156666)
NSF - NMR purchase (CHE 0619339)
NSF - HRMS purchase (CHE0443618
The Lantern Vol. 7, No. 1, December 1938
• The Greatest Gift of All • Peace • Two Bums • October Paints the Valleys • Have the Notes Died? • America\u27s Defeatism Complex • Tahiti Jacques • When We Take Heed of Life • From The Sky Image • Still Moments • Noel • Foreign Hills • Just Beforehttps://digitalcommons.ursinus.edu/lantern/1012/thumbnail.jp
The Lantern Vol. 6, No. 3, June 1938
• Editorial • A Senior Muses • Affinity • From Darkness Into Light • Just an Old Bell! • Memories of a Friend • To a Small Animal as it Passes • The Sky and I • Between the Mountain and the River • Solace • Three Little Islands Far From Home • Beachcomberhttps://digitalcommons.ursinus.edu/lantern/1011/thumbnail.jp
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Apportionment of primary and secondary organic aerosols in Southern California during the 2005 Study of Organic Aerosols in Riverside (SOAR-1)
Ambient sampling was conducted in Riverside, California during the 2005 Study of Organic Aerosols in Riverside to characterize the composition and sources of organic aerosol using a variety of state-of-the-art instrumentation and source apportionment techniques. The secondary organic aerosol (SOA) mass is estimated by elemental carbon and carbon monoxide tracer methods, water soluble organic carbon content, chemical mass balance of organic molecular markers, and positive matrix factorization of high-resolution aerosol mass spectrometer data. Estimates obtained from each of these methods indicate that the organic fraction in ambient aerosol is overwhelmingly secondary in nature during a period of several weeks with moderate ozone concentrations and that SOA is the single largest component of PM1 aerosol in Riverside. Average SOA/OA contributions of 70−90% were observed during midday periods, whereas minimum SOA contributions of ~45% were observed during peak morning traffic periods. These results are contrary to previous estimates of SOA throughout the Los Angeles Basin which reported that, other than during severe photochemical smog episodes, SOA was lower than primary OA. Possible reasons for these differences are discussed
The Lantern Vol. 7, No. 3, June 1939
• Commencement Sonnet • Largo Appassionato • More Sonnets to Earth • Vladimir • Abe Lincoln in Illinois • Dark Lives • Enter Mr. Smithingham II • A Character is Sketched • Sonnet • Out of the Dawn • Wistaria • Poem Without a Name • You Have Loved the Nighthttps://digitalcommons.ursinus.edu/lantern/1018/thumbnail.jp
3D Printing in Zero-G ISS Technology Demonstration
The National Aeronautics and Space Administration (NASA) has a long term strategy to fabricate components and equipment on-demand for manned missions to the Moon, Mars, and beyond. To support this strategy, NASA's Marshall Space Fligth Center (MSFC) and Made in Space, Inc. are developing the 3D Printing In Zero-G payload as a Technology Demonstration for the International Space Station (ISS). The 3D Printing In Zero-G experiment ('3D Print') will be the frst machine to perform 3D printing in space
The Lantern Vol. 6, No. 2, March 1938
• Among Our Contributors • Of Special Interest To You! • Jenny Lee • The Arguments Against Isolation • The Note • Visit of the Grandchildren • One Finds God • To The North Lies New Hampshire • The Two Camps in Washington • Substitutes • At Times It Seems So Very Strange • Episode on a Lake Shore • My Campus Song • Irony • A Chinese Mysteryhttps://digitalcommons.ursinus.edu/lantern/1017/thumbnail.jp
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An AgMIP framework for improved agricultural representation in integrated assessment models
Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications
Family-specific, novel, deleterious germline variants provide a rich resource to identify genetic predispositions for BRCAx familial breast cancer
BACKGROUND: Genetic predisposition is the primary risk factor for familial breast cancer. For the majority of familial breast cancer, however, the genetic predispositions remain unknown. All newly identified predispositions occur rarely in disease population, and the unknown genetic predispositions are estimated to reach up to total thousands. Family unit is the basic structure of genetics. Because it is an autosomal dominant disease, individuals with a history of familial breast cancer must carry the same genetic predisposition across generations. Therefore, focusing on the cases in lineages of familial breast cancer, rather than pooled cases in disease population, is expected to provide high probability to identify the genetic predisposition for each family. METHODS: In this study, we tested genetic predispositions by analyzing the family-specific variants in familial breast cancer. Using exome sequencing, we analyzed three families and 22 probands with BRCAx (BRCA-negative) familial breast cancer. RESULTS: We observed the presence of family-specific, novel, deleterious germline variants in each family. Of the germline variants identified, many were shared between the disease-affected family members of the same family but not found in different families, which have their own specific variants. Certain variants are putative deleterious genetic predispositions damaging functionally important genes involved in DNA replication and damaging repair, tumor suppression, signal transduction, and phosphorylation. CONCLUSIONS: Our study demonstrates that the predispositions for many BRCAx familial breast cancer families can lie in each disease family. The application of a family-focused approach has the potential to detect many new predispositions
An AgMIP Framework for Improved Agricultural Representation in Integrated Assessment Models
Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications
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