Synthetic routes towards spin probe-grafted copolymers

Nitroxide spin labels can be useful as oxygen probes since the shape of the characteristic three line electron spin resonance (ESR) spectrum broadens in the presence of molecular oxygen. In order to use these probes in. vivo to measure oxygen content of tumors, contact of toxic nitroxides with tissues must be prevented. This study describes synthesis and characterization of several styrene/maleic anhydride copolymers containing grafted 2,2,6,6-tetramethyl-4-aminopiperidine-1- oxyl (TEMPO) spin probes. Infrared (IR) spectroscopy was used to determine the structure of the copolymers. ESR spectroscopy was used to contrast the free radical activity of the copolymer in an nitrogen-rich and oxygen-rich environment. The changes observed in the ESR spectra were that dissolved oxygen noticeably broadens the peaks, but significant free radical activity remains in the copolymers. Attempts to graft TEMPO to 92/8 [styrene/maleic anhydride] copolymers achieved 67% success and to 50/50 [styrene/maleic anhydride] copolymers achieved k0% success

Guppie: A Coordination Framework for Parallel Processing Using Shared Memory Featuring A Master-Worker Relationship

Most programs can be parallelized to some extent. The processing power available in computers today makes parallel computing more desirable and attainable than ever before. Many machines today have multiple processors or multiple processing cores making parallel computing more available locally, as well as over a network. In order for parallel applications to be written, they require a computing language, such as C++, and a coordination language (or library), such as Linda. This research involves the creation and implementation of a coordination framework, Guppie, which is easy to use, similar to Linda, but provides more efficiency when dealing with large amounts of messages and data. Greater efficiency can be achieved in coarse-grained parallel computing through the use of shared memory managed through a master-worker relationship

Three essays on U.S. foreign assistance spending and U.S. politico-military integration

2021 Spring.Includes bibliographical references.Simulations show that recipient nations are directly impacted by U.S. foreign assistance spending (in the form of U.S. economic and military aid) in a manner similar to transfer payments, spurring growth, and easing liquidity constraints. U.S. foreign assistance spending is often accompanied by U.S. politico-military integration, which is defined by the presence of the: (1) receipt of U.S. economic aid, (2) receipt of U.S. military aid, and (3) integration into the U.S. security apparatus through hosting U.S. troops and/or bases or through military or political treaties. Using a new comprehensive RAND database of all U.S. security-related agreements since 1955, I create a new database showing which country-years have active (a) U.S. military treaties (b) U.S. political treaties. Also new is the inclusion of David Vine's Base Nation database, detailing the location and existence of all recognized, unrecognized, and U.S.-funded bases. Lastly, I update another of RAND's databases, one detailing U.S. troop deployment abroad to include the most recent years. Empirical analysis shows a more complicated set of results than those derived in the simulations. Using deep lags and controlling for politico-military integration and U.S. military aid, I find limited evidence that U.S. economic aid is effective in development. This associated positive impact of U.S. economic aid is never large enough to overcome the associated negative impact of U.S. military aid and U.S. politico-military integration. While U.S. political treaties show a slight impact on economic growth, U.S. military aid, U.S. military bases, and U.S. military treaties overwhelm any positive impact on growth and FDI, with a resulting net effect that is significantly negative for the recipient

Finding strong lenses in CFHTLS using convolutional neural networks

We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging for the identification of potential strong lensing systems. An ensemble of four convolutional neural networks was trained on images of simulated galaxy-galaxy lenses. The training sets consisted of a total of 62,406 simulated lenses and 64,673 non-lens negative examples generated with two different methodologies. The networks were able to learn the features of simulated lenses with accuracy of up to 99.8% and a purity and completeness of 94-100% on a test set of 2000 simulations. An ensemble of trained networks was applied to all of the 171 square degrees of the CFHTLS wide field image data, identifying 18,861 candidates including 63 known and 139 other potential lens candidates. A second search of 1.4 million early type galaxies selected from the survey catalog as potential deflectors, identified 2,465 candidates including 117 previously known lens candidates, 29 confirmed lenses/high-quality lens candidates, 266 novel probable or potential lenses and 2097 candidates we classify as false positives. For the catalog-based search we estimate a completeness of 21-28% with respect to detectable lenses and a purity of 15%, with a false-positive rate of 1 in 671 images tested. We predict a human astronomer reviewing candidates produced by the system would identify ~20 probable lenses and 100 possible lenses per hour in a sample selected by the robot. Convolutional neural networks are therefore a promising tool for use in the search for lenses in current and forthcoming surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope.Comment: 16 pages, 8 figures. Accepted by MNRA

Deletion of AIF1 but not of YCA1/MCA1 protects Saccharomyces cerevisiae and Candida albicans cells from caspofungin-induced programmed cell death

Caspofungin was the first member of a new class of antifungals called echinocandins to be approved by a drug regulatory authority. Like the other echinocandins, caspofungin blocks the synthesis of β(1,3)-D-glucan of the fungal cell wall by inhibiting the enzyme, β(1,3)-D-glucan synthase. Loss of β(1,3)-D-glucan leads to osmotic instability and cell death. However, the precise mechanism of cell death associated with the cytotoxicity of caspofungin was unclear. We now provide evidence that Saccharomyces cerevisiae cells cultured in media containing caspofungin manifest the classical hallmarks of programmed cell death (PCD) in yeast, including the generation of reactive oxygen species (ROS), the fragmentation of mitochondria, and the production of DNA strand breaks. Our data also suggests that deleting AIF1 but not YCA1/MCA1 protects S. cerevisiae and Candida albicans from caspofungin-induced cell death. This is not only the first time that AIF1 has been specifically tied to cell death in Candida but also the first time that caspofungin resistance has been linked to the cell death machinery in yeast

Global Stability of a Class of Difference Equations on Solvable Lie Algebras

Motivated by the ubiquitous sampled-data setup in applied control, we examine the stability of a class of difference equations that arises by sampling a right- or left-invariant flow on a matrix Lie group. The map defining such a difference equation has three key properties that facilitate our analysis: 1) its power series expansion enjoys a type of strong convergence; 2) the origin is an equilibrium; 3) the algebraic ideals enumerated in the lower central series of the Lie algebra are dynamically invariant. We show that certain global stability properties are implied by stability of the Jacobian linearization of dynamics at the origin. In particular global asymptotic stability. If the Lie algebra is nilpotent, then the origin enjoys semiglobal exponential stability