Financial Determinants of Yield Rates for Bachelor of Arts and Sciences Colleges

This paper investigates the effects of financial factors on the yield rates of Bachelor of Arts and Sciences colleges. We define the yield rate as the percentage of students accepted who choose to enroll. Our data is drawn from the Integrated Post-secondary Education Data System (IPEDS) and consists of 107 Bachelor of Arts and Sciences colleges during the period from 2010 to 2016. Controlling for institutional factors, we find that the responses of the yield rate to increases in federal student loans and increases in tuition and room and board costs are negative and inelastic, while the response to changes in grant aid is not statistically significant

Personal Intelligence in the Workplace and Relationships

The predictive ability of personal intelligence (PI), the ability to understand and apply personality-related information, was examined in relation to the workplace and social relationships. We predicted that two measures of PI, an objective test, the mini (12 item) test of personal intelligence (TOPI), and a self-estimated test, the self-estimated personal intelligence scale (SEPI), would relate to job satisfaction, indicators of leadership, positive organizational workplace behavior, and social support. Vocabulary tests and the backwards digit span served as traditional intelligence measures. Several measures of workplace behavior and social support were administered. Participants were 378 adults who worked full-time in the U.S. PI was related to some workplace related characteristics, especially the absence of deviant behaviors, as well as social support in general. PI was associated with workplace behaviors and social outcomes above and beyond traditional measures of intelligence, supporting PI’s usefulness as a novel form of intelligence. However, the study was limited by the low variance/reliability of the TOPI scores relative to the SEPI. Future research should use the longer TOPI version or redevelop the mini TOPI. The study findings suggest that understanding personality may relate to some positive workplace characteristics and support healthy relationships.Bachelor of Scienc

Reading ability and print exposure: item response theory analysis of the author recognition test

In the Author Recognition Test (ART) participants are presented with a series of names and foils and are asked to indicate which ones they recognize as authors. The test is a strong predictor of reading skill, with this predictive ability generally explained as occurring because author knowledge is likely acquired through reading or other forms of print exposure. This large-scale study (1012 college student participants) used Item Response Theory (IRT) to analyze item (author) characteristics to facilitate identification of the determinants of item difficulty, provide a basis for further test development, and to optimize scoring of the ART. Factor analysis suggests a potential two factor structure of the ART differentiating between literary vs. popular authors. Effective and ineffective author names were identified so as to facilitate future revisions of the ART. Analyses showed that the ART is a highly significant predictor of time spent encoding words as measured using eye-tracking during reading. The relationship between the ART and time spent reading provided a basis for implementing a higher penalty for selecting foils, rather than the standard method of ART scoring (names selected minus foils selected). The findings provide novel support for the view that the ART is a valid indicator of reading volume. Further, they show that frequency data can be used to select items of appropriate difficulty and that frequency data from corpora based on particular time periods and types of text may allow test adaptation for different populations

Chancellor\u27s Citations for Extraordinary Campus Leadership and Service (2014)

The Chancellor’s Citations for Extraordinary Campus Leadership and Service recognize graduating students who are extraordinary campus leaders for their significant service to others

Conversations With Myself

This purpose of this project was to grow and evolve as a storyteller. Ti is of great importance of the author to be able to communicate her ideas effectively while being able to affect the emotions of those around her. It explores the process of taking words from a piece a paper and turning them into a living breathing sonic environment, in the hopes of developing the voice and music production process for the author. Interestingly enough, it resulted in a full length spoken word album. Each track (or piece) consists of an original prose or poem, musical composition, and sound design. Major challenges, originating from mental illness, greatly impacted the project execution and its contents both positively and negatively. The resulting album will be released on all digital platforms in September of 2019. This entire process allowed the author to realize her artistry and grow not only as an artist, but as a person as well.https://remix.berklee.edu/graduate-studies-production-technology/1170/thumbnail.jp

Virtual 3D Modeling of Two Historic Barns in Bulloch County, GA: Both barns are southwest of Statesboro

This service-learning work is part of a larger project consisting in laser scanning and producing virtual, three-dimensional, computer-based, detailed models of eight (8) historic barns in Bulloch County, GA. The resulting spatial models (point clouds) will assist in the historical preservation of these now delicate and aging structures. In particular, this authoring group of students is currently working and focusing on two of those eight barns: (i) Bonnie Dekle Howard\u27s Barn, and (ii) Remer Dekle\u27s Barn. Both barns are southwest of Statesboro, near Register, GA. After completion, the models will be donated to Dr. Brent W. Tharp who represents both, the Bulloch County Historical Society and the Georgia Southern Museum. This project gave our Civil Engineering and Construction team an opportunity to assist and serve our community in a service-learning format while understanding and learning state-of-the-art laser scanning techniques and their post-processing tasks

Individual differences in reading: Separable effects of reading experience and processing skill

A large-scale eye-tracking study examined individual variability in measures of word recognition during reading among 546 college students, focusing on two established individual-differences measures: the Author Recognition Test (ART) and Rapid Automatized Naming (RAN). ART and RAN were only slightly correlated, suggesting that the two tasks reflect independent cognitive abilities in this large sample of participants. Further, individual variability in ART and RAN scores were related to distinct facets of word-recognition processes. Higher ART scores were associated with increased skipping rates, shorter gaze duration, and reduced effects of word frequency on gaze duration, suggesting that this measure reflects efficiency of basic processes of word recognition during reading. In contrast, faster times on RAN were associated with enhanced foveal-on-parafoveal effects, fewer first-pass regressions, and shorter second-pass reading times, suggesting that this measure reflects efficient coordination of perceptual-motor and attentional processing during reading. These results demonstrate that ART and RAN tasks make independent contributions to predicting variability in word-recognition processes during reading

Of Mojave milkweed and mirrors: The population genomic structure of a species impacted by solar energy development

Abstract A rapid renewable energy transition has facilitated the development of large, ground‐mounted solar energy facilities worldwide. Deserts, and other sensitive aridland ecosystems, are the second most common land‐cover type for solar energy development globally. Thus, it is necessary to understand existing diversity within environmentally sensitive desert plant populations to understand spatiotemporal effects of solar energy siting and design. Overall, few population genomic studies of desert plants exist, and much of their biology is unknown. To help fill this knowledge gap, we sampled Mojave milkweed (Asclepias nyctaginifolia) in and around the Ivanpah Solar Electric Generating Station (ISEGS) in the Mojave Desert of California to understand the species' population structure, standing genetic variation, and how that intersects with solar development. We performed Restriction‐site Associated Sequencing (RADseq) and discovered 9942 single nucleotide polymorphisms (SNPs). Using these data, we found clear population structure over small spatial scales, suggesting each site sampled comprised a genetically distinct population of Mojave milkweed. While mowing, in lieu of blading, the vegetation across the solar energy facility's footprint prevented the immediate loss of the ISEGS Mojave milkweed population, we show that the effects of land‐cover change, especially those impacting desert washes, may impact long‐term genetic diversity and persistence. Potential implications of this include a risk of overall loss of genetic diversity, or even hastened extirpation. These findings highlight the need to consider the genetic diversity of impacted species when predicting the impact and necessary conservation measures of large‐scale land‐cover changes on species with small population sizes

Of Mojave milkweed and mirrors: The population genomic structure of a species impacted by solar energy development

<p>A rapid renewable energy transition has facilitated the development of large, ground‐mounted solar energy facilities worldwide. Deserts, and other sensitive aridland ecosystems, are the second most common land‐cover type for solar energy development globally. Thus, it is necessary to understand existing diversity within environmentally sensitive desert plant populations to understand spatiotemporal effects of solar energy siting and design. Overall, few population genomic studies of desert plants exist, and much of their biology is unknown. To help fill this knowledge gap, we sampled Mojave milkweed (<em>Asclepias</em> <em>nyctaginifolia</em>) in and around the Ivanpah Solar Electric Generating Station (ISEGS) in the Mojave Desert of California to understand the species' population structure, standing genetic variation, and how that intersects with solar development. We performed Restriction‐site Associated Sequencing (RADseq) and discovered 9942 single nucleotide polymorphisms (SNPs). Using these data, we found clear population structure over small spatial scales, suggesting each site sampled comprised a genetically distinct population of Mojave milkweed. While mowing, in lieu of blading, the vegetation across the solar energy facility's footprint prevented the immediate loss of the ISEGS Mojave milkweed population, we show that the effects of land‐cover change, especially those impacting desert washes, may impact long‐term genetic diversity and persistence. Potential implications of this include a risk of overall loss of genetic diversity, or even hastened extirpation. These findings highlight the need to consider the genetic diversity of impacted species when predicting the impact and necessary conservation measures of large‐scale land‐cover changes on species with small population sizes.</p><p>Funding provided by: California Energy Commission<br>Crossref Funder Registry ID: https://ror.org/05eaakg28<br>Award Number: Electric Program Investment Charge-15-060</p><p>Funding provided by: Bureau of Land Management<br>Crossref Funder Registry ID: https://ror.org/01sy5zn44<br>Award Number: L19AC00279</p><h3>Sample Collection</h3> <p>In 2015, we sampled leaf tissue of all vegetative Mojave milkweed plants at four locations: three sites undisturbed by facility construction and throughout ISEGS. The first of these sites ("Excelsior") is approximately 21 kilometers west of ISEGS. The other two locations are approximately five kilometers north ("Umberci)," and 60 kilometers south ("Bobcat") of the solar facility (Fig.1). We cut small sections of green leaf tissue from mature plants and stored them in individually labeled coin envelopes with desiccant packets to promote drying. When present, we collected seeds for subsequent growth in a greenhouse, where leaves were cut and similarly stored once the plants reached sufficient maturity. It is important to note that while we collected all the plants present at the time, there is the possibility that some plants died back prior to our ability to collect them or remained dormant as rhizomes that season.</p> <p>We collected additional samples in the fall of 2018 from plants previously identified within the ISEGS halos (n= 8) as well as plants that emerged in halos after the 2015 sampling (n= 30). We also collected any previously unidentified plants that grew within the facility but outside of designated halo areas (n= 51). We acquired additional samples from the Umberci site of previously identified but unsampled plants (n= 32) and newly emerged plants (n= 16). We designated Individuals (genets) based on the distance from other plants and sampled multiple ramets per genet if possible. We collected leaves from juvenile or adult individuals. For both years, we recorded the location of all plants present, even if they were too small to sample, to establish a census size. See Table 1 for a summary of our sampling scheme and Figure 1 for a map of the sites.</p> <h3>Sequencing</h3> <p>For both the 2015 and 2018 samples, we disrupted the dried plant tissue with steel beads using a bead mill prior to extracting DNA. We performed DNA extractions using the DNeasy Plant Mini kit (QIAGEN Inc., Valencia, CA, USA) and quantified the resulting concentrations of DNA using a Qubit fluorometer (Invitrogen, Carlsbad, CA, USA). We diluted the purified DNA to a concentration of 10.0 ng/ul using low TE in preparation for Restriction site Associated DNA Sequencing (RADSeq) using the Best-RAD method (Ali et al. 2016). A modification to Ali et al. (2016) is that we used the restriction endonuclease pstI to digest the DNA due to the more favorable number of cut sites given the GC content and size of the Asclepias syriaca reference genome (Weitemier et al. 2019) (Genbank accession GFXT01000000). We sonicated samples to a fragment length of 200 base pairs for the 2015 samples and 300 base pairs for the 2018 samples using a Covaris m220 (Covaris, Woburn, MA, USA). Following library preparation with the NEBnext Ultra DNA kit for Illumina (New England Biolabs, Inc., Ipswich, MA), we performed library trace analysis using a Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). We sequenced the 2015 samples on the Illumina HiSeq3000 platform at the University of California Davis DNA Technologies Core (PE-2x100bp). For the 2018 samples, we sequenced on the Illumina HiSeq X platform (PE-2x150bp) at the UC Davis Sequencing Center (Novogene Corporation Inc.). The longer read length for the 2018 samples was due to the technical specifications of the sequencing platform. For analyses combining datasets from both sampling years, we trimmed the 2018 samples to the same length as the 2015 samples (100bp) using trimmomatic v0.38 (Bolger et al. 2014).</p> <h3>SNP Discovery</h3> <p>Following sequencing, we demultiplexed data for all individuals (n=233) using -process_radtags in STACKS v2.4 (Catchen et al. 2011, 2013) and the following tags: --bestrad, -c, -r, -D. We aligned the files to the <em>Asclepias</em> <em>syriaca</em> reference genome (Weitemier et al. 2019) (Genbank accession GFXT01000000) using the --very-sensitive-local wrapper in Bowtie2 v2.3.4 (Langmead & Salzberg 2012). We used the -ref_map.pl pipeline in STACKS v2.4 to call random SNPs (--write_random_snp) inhe dataset. We retained loci that were present in at least 30% of individuals per population within a single population and proceeded with quality filtration on the resulting VCF file. </p> <p>We quality filtered the resulting file using VCFtools v0.1.15 (Danecek et al. 2011). Initially, we identified and removed individuals that were not genotyped at greater than 95% of loci and genotypes with a minimum read depth of less than 5. We then filtered out all genotypes with a gene quality score of less than 20. We subsequently removed loci with a minor allele count (MAC) of less than three [see (O'Leary et al. 2018)], followed by filtering out SNPs with a call rate of less than 90%. The final filtration step again identified and removed individuals with less than 85% of loci genotyped. We performed the SNP discovery on all samples combined and separated out the individual sampling years during for downstream analysis. We removed any remaining monomorphic loci using informloci in the R (R Core Team, 2020) package poppr (Kamvar et al. 2014, 2015) prior to proceeding with further analyses.</p> <h3>Genetic Diversity</h3> <p>We analyzed the resulting sequence data to determine genetic diversity using allelic richness, effective population size (N<sub>e</sub>), inbreeding coefficients (Fis), population differentiation, and observed/expected heterozygosity. We calculated heterozygosity, Fis, and allelic richness using the basic.stats and allelic.richness functions of hierfstat (Goudet 2005). Private alleles were determined using the private_alleles function in the R package poppr (Kamvar et al. 2014, 2015). In the private allele calculations, we used datasets from 2015 and a combined 2015 and 2018 dataset that excluded clones. We calculated the effective population size using NeEstimator v2.1 (Do et al. 2014) under the linkage disequilibrium model with an allele frequency of 0.05 using our clone-free dataset from 2015 (see below).</p> <h3>Population Structure</h3> <p>When determining population structure, we removed clonal ramets from the 2015 dataset according to their multilocus genotypes, using the mlg.filter function with a genetic distance threshold of 0.04 as calculated by the bitwise.dist function in poppr (Kamvar et al. 2014). We incorporated relatedness by calculating pairwise φ among all samples using the relatedness2 estimator in VCFtools (Manichaikul et al. 2010; Danecek et al. 2011). We removed individuals with pairwise φ values greater than 0.177, which corresponds with first-degree relatives such as full siblings and parent-offspring pairs, as clustering algorithms can be influenced by close relatives (Rodríguez‐Ramilo & Wang 2012; Rodríguez-Ramilo et al. 2014). For each dataset, we evaluated the population structure of the plants using discriminant analysis of principle components via the R package adegenet (Jombart 2008; Jombart et al. 2010). We coss-referenced these results using the program <em>structure</em> (Pritchard et al. 2000; Falush et al. 2003; FALUSH et al. 2007; HUBISZ et al. 2009) and Structure Harvester (Earl & vonHoldt 2011). We also assessed population differentiation (Fst) using the method outlined by Weir and Cockerham (Weir & Cockerham 1984). To further investigate the relationships between individuals, we calculated Minimum Spanning Networks (MSN) in poppr using the bitwise.dist and poppr.msn functions. Finally, we tested isolation by distance in the samples using the R package conStruct (Bradburd et al. 2018). </p&gt