Exploring Alumni Stories Through Qualitative Research

This presentation describes a project designed to connect current psychology undergraduates with alumni from the same program. Purposive sampling was used to recruit diverse alumni following different career paths (i.e., graduate school or straight to work), representing alumni who identified as first generation, nontraditional, Latina/Latino or as a student of color. Semi-structured interviews were conducted to understand alumni career paths and gather information about decision-making, barriers, supports, and advice for current psychology majors. Interviews were audio-taped and are currently being transcribed. Some alumni agreed to participate in an “Alumni Profile,” which highlighted specific alumni by name, shared details of individual’s specific story, and were made publicly available. The current presentation will share the experiences of the undergraduate researchers exploring qualitative research, learning about career options available after graduation, and benefits for current students

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Installation of a deinking plant to increase paper machine production : financial analysis and final report

CPP’s Raleigh, North Carolina uncoated freesheet mill has expressed the need for a capital project to generate incremental free cash flow in the coming decades. Two different capital project alternatives were proposed to CPP. The high-capital alternative involves installing a flotation deinking plant to supplement the mill’s virgin fiber and increase production. The low-capital alternative involves installing a hydropulper makedown system and purchasing market deinked pulp (MDIP) to increase production. In each case, the primary changes to the mill would be to the paper machines, waste treatment system, and effluent treatment system; there would be only limited effects to other mill operations (woodyard, bleaching, pulping, and recovery). The production off of each paper machine would increase by approximately 11% in each of the envisioned scenarios. Effluent generation would increase in both cases, more significantly in the case of flotation deinking. Flotation would also generate almost 40,000 ODt/yr of deinking sludge that would have to be landfilled. Each project would require significant additional energy (both to dry the incremental paper and to run the pulpers or deinking plant) and fresh water. The increases in energy and fresh water usage were larger in the case of flotation deinking, as per the WinGEMS model developed for this report. The total installed capital (TIC) cost of each of the proposed projects was estimated. Given the relative simplicity of the low-capital alternative, each individual piece of equipment was priced and a factored capital cost estimation method was used to estimate the TIC at around $2,400,000. Since the proposed flotation deinking plant would require numerous types of equipment for which reference quotes were unavailable, the Consulting Firm sought an all-inclusive vendor quote in the interest of accuracy. The total purchased equipment cost from the most pertinent quote ($6,900,000) was input into a factored capital cost estimator and the TIC of the high-capital investment was estimated at just under $28,000,000. Separate FEL-0 level financial analyses were completed for each of the two proposed capital projects. It was quickly found that the low-capital alternative of purchasing MDIP would not be profitable or feasible for the mill, with an IRR of around -17$50,000,000. The high-capital alternative of flotation deinking, on the other hand, had a much more financially feasible IRR of 10% and an NPV of approximately -$3,400,000. The Consulting Firm believes that, given CPP’s need for incremental free cash flow in the coming decades, it would be in CPP’s best interest to commission an FEL-1 analysis of the proposed flotation deinking plant investment. The FEL-0 analysis discussed in this report is accurate only to within ±40%, so it is possible that the information gathered by completing an FEL-1 analysis could indicate better financial performance. In addition, the Firm suggests that CPP no longer pursues the low-capital alternative (MDIP usage) given its extremely poor financial performance

DNA Methylation Profiling in Rare Sellar Tumors

The histologic diagnosis of sellar masses can be challenging, particularly in rare neoplasms and tumors without definitive biomarkers. Moreover, there is significant inter-observer variability in the histopathological diagnosis of many tumors of the CNS, and some rare tumors risk being misclassified. DNA methylation has recently emerged as a useful diagnostic tool. To illustrate the clinical utility of machine-learning-based DNA methylation classifiers, we report a rare case of primary sellar esthesioneuroblastoma histologically mimicking a non-functioning pituitary adenoma. The patient had multiple recurrences, and the resected specimens had unusual histopathology. A portion of the resected sellar lesion was profiled using clinically validated whole-genome DNA methylation and classification. DNA was extracted from the tissue, hybridized on DNA methylation chips, and analyzed using a clinically validated classifier. DNA methylation profiling of the lesion showed that the tumor classified best with the esthesioneuroblastoma reference cohort. This case highlights the difficulty in diagnosing atypical sellar lesions by standard histopathological methods. However, when phenotypic analyses were nonconclusive, DNA methylation profiling resulted in a change in diagnosis. We discuss the growing role of DNA methylation profiling in the classification and diagnosis of CNS tumors, finding that utilization of DNA methylation studies in cases of atypical presentation or diagnostic uncertainty may improve diagnostic accuracy with therapeutic and prognostic implications