1,081 research outputs found
The goldstone and goldstino of supersymmetric inflation
We construct the minimal effective field theory (EFT) of supersymmetric
inflation, whose field content is a real scalar, the goldstone for
time-translation breaking, and a Weyl fermion, the goldstino for supersymmetry
(SUSY) breaking. The inflating background can be viewed as a single
SUSY-breaking sector, and the degrees of freedom can be efficiently
parameterized using constrained superfields. Our EFT is comprised of a chiral
superfield X_NL containing the goldstino and satisfying X_NL^2 = 0, and a real
superfield B_NL containing both the goldstino and the goldstone, satisfying
X_NL B_NL = B_NL^3 = 0. We match results from our EFT formalism to existing
results for SUSY broken by a fluid background, showing that the goldstino
propagates with subluminal velocities. The same effect can also be derived from
the unitary gauge gravitino action after embedding our EFT in supergravity. If
the gravitino mass is comparable to the Hubble scale during inflation, we
identify a new parameter in the EFT related to a time-dependent phase of the
gravitino mass parameter. We briefly comment on the leading contributions of
goldstino loops to inflationary observables.Comment: 32 pages, 2 figures. v3: clarifications and references added. Matches
JHEP version. v2: typos fixed, footnote and references adde
A Mixed Effects Model of Crop Yields for Purposes of Premium Determination
Farm income is highly variable due to annual price and yield uncertainties. The federally subsidized crop insurance program is an important tool for managing this risk, and has grown from a relatively modest program to one that encompasses the majority of productive cropland in the country. The success of this program depends on identification of actuarially fair insurance premium rates, which in turn depends on accurate estimation of farm-level yield distributions. We use the confidential U.S. Department of Agriculture Risk Management Agency (RMA) panel dataset to estimate farm-specific distributions of yields and actually fair crop insurance premiums. Our ongoing work includes using the difference between our estimated actually fair premiums and RMA's to predict which insurance contracts farmers select. Ultimately, we will predict potential efficiency gains from using our empirical model for premium determination.Yield, Crop Insurance, Policy, Mixed Model, Agricultural and Food Policy,
Determining Material Structures and Surface Chemistry by Genetic Algorithms and Quantum Chemical Simulations
With the advent of modern computing, the use of simulation in chemistry has become just as important as experiment. Simulations were originally only applicable to small molecules, but modern techniques, such as density functional theory (DFT) allow extension to materials science. While there are many valuable techniques for synthesis and characterization in chemistry laboratories, there are far more materials possible than can be synthesized, each with an entire host of surfaces. This wealth of chemical space to explore begs the use of computational chemistry to mimic synthesis and experimental characterization. In this work, genetic algorithms (GA), for the former, and DFT calculations, for the latter, are developed and used for the in silico exploration of materials chemistry.
Genetic algorithms were first theorized in 1975 by John Holland and over the years subsequently expanded and developed for a variety of purposes. The first application to chemistry came in the early 1990’s and surface chemistry, specifically, appeared soon after. To complement the ability of a GA to explore chemical space is a second algorithmic technique: machine learning (ML) wherein a program is able to categorize or predict properties of an input after reviewing many, many examples of similar inputs. ML has more nebulous origins than GA, but applications to chemistry also appeared in the 1990’s. A history perspective and assessment of these techniques towards surface chemistry follows in this work.
A GA designed to find the crystal structure of layered chemical materials given the material’s X-ray diffraction pattern is then developed. The approach reduces crystals into layers of atoms that are transformed and stacked until they repeat. In this manner, an entire crystal need only be represented by its base layer (or two, in some cases) and a set of instructions on how the layers are to be arranged and stacked. Molecules that may be present may not quite behave in this fashion, and so a second set of descriptors exist to determine the molecule’s position and orientation. Finally, the lattice of the unit cell is specified, and the structure is built to match. The GA determines the structure’s X-ray diffraction pattern, compares it against a provided experimental pattern, and assigns it a fitness value, where a higher value indicates a better match and a more fit individual. The most fit individuals mate, exchanging genetic material (which may mutate) to produce offspring which are further subjected to the same procedure. This GA can find the structure of bulk, layered, organic, and inorganic materials.
Once a material’s bulk structure has been determined, surfaces of the material can be derived and analyzed by DFT. In this thesis, DFT is used to validate results from the GA regarding lithium-aluminum layered double hydroxide. Surface chemistry is more directly explored in the prediction of adsorbates on surfaces of lithiated nickel-manganese-cobalt oxide, a common cathode material in lithium-ion batteries. Surfaces are evaluated at the DFT+U level of theory, which reduces electron over-delocalization, and the energies of the surfaces both bare and with adsorbates are compared. By applying first-principles thermodynamics to predict system energies under varying temperatures and pressures, the behavior of these surfaces in experimental conditions is predicted to be mostly pristine and bare of adsorbates. For breadth, this thesis also presents an investigation of the electronic and optical properties of organic semiconductors via DFT and time-dependent DFT calculations
Green Chemistry Oxidative Modification of Peptoids Utilizing Bleach and TEMPO
Biotherapeutic drugs, derived from biological molecules such as proteins and DNA, are becoming an integral and exceptionally critical aspect of modern medicine. Compared to common pharmaceutical drugs, biotherapeutics are much larger in size and have greater target specificity, allowing them to treat many chronic diseases ranging from cancer to rheumatoid arthritis. The major issue with protein based therapeutics is that they readily undergo proteolysis, or enzymatic degradation, when administered through subcutaneous injections. Traditionally, biotherapeutic modification procedures have centered on the use of PEG derivatives. This process, called PEGylation, is unfavorable due to the increases in molecular weights of the proteins and the heterogeneous mixture of products formed. Instead of PEG derivatives, we propose peptoids with N- methoxyethylglycine (NMEG) side chains to decrease proteolysis. NMEG groups are more advantageous than PEG derivatives due to their low molecular weight and ability to form homogeneous products. Our work focuses on increasing the protease resistance of target biotherapeutic proteins by cross-linking a NMEG-5 peptoid to a cytochrome c via reductive amination. In the presence of a reducing agent, an imine bond is formed through the reduction of the peptoid’s aldehyde group and cytochrome c’s primary amine groups. Due to the expensive and unstable nature of commercially available aldehyde side chains, a green chemistry method, using only sodium hypochlorite (bleach) and 2,6,6-Tetramethylpiperidinoxy (TEMPO, free radical), oxidized the peptoid’s hydroxyl group into the desired aldehyde for cross linkage
Peptoid-Based Microsphere Coatings for Biomaterial Applications
Peptoids are peptidomimetic oligomers that predominantly harness similarities to peptides for biomimetic functionality. The incorporation of chiral, aromatic side chains in the peptoid sequence allows for the formation of distinct secondary structures and self-assembly into supramolecular assemblies, including microspheres. Peptoid microspheres can be coated onto substrates for potential use in biosensor technologies, tissue engineering platforms, and drug-delivery systems. They have the potential for use in biomedical applications due to their resistance to proteolytic degradation and low immunogenicity. This dissertation focuses on the physical characteristics and robustness of the peptoid microsphere coatings in various physiological conditions, along with their ability to serve as ELISA microarray and tissue engineering substrates. We have shown that the peptoid microspheres are suitable substrates for layer-by-layer technologies to create biomimetic artificial extracellular matrices for tissue engineering. Overall, this study demonstrates that peptoid microsphere coatings are suitable materials for many biological applications
Bunker, Lisa
Lisa Bunker is an author who lives in Exeter, New Hampshire and worked at WMPG at the University of Southern Maine for fourteen years during her process of coming out as transgender. She is the author of Felix Yz and an upcoming book called Zenobia July, but spent most of her life in broadcast radio before she left to pursue a full time career in writing.
Citation
Please cite as: Querying the Past: LGBTQ Maine Oral History Project Collection, Lesbian, Gay, Bisexual, Transgender, and Queer+ Collection, Jean Byers Sampson Center for Diversity in Maine, University of Southern Maine Libraries.
For more information about the Querying the Past: Maine LGBTQ Oral History Project, please contact Dr. Wendy Chapkis.https://digitalcommons.usm.maine.edu/querying_ohproject/1016/thumbnail.jp
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