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The objective of this research is to build a decision model for a comprehensive assessment of solar photovoltaic technologies using multiple perspectives. These perspectives include: social, technological, economic, environmental, and political (STEEP) with each perspective consisting of multiple criteria. Hierarchical decision modeling and expert judgment quantification are used to provide the relative ranking of the perspectives and criteria. Such modeling is effective in addressing technology evaluations with competing and contrasting perspectives and criteria where both quantitative and qualitative measurements are represented. The model is then operationalized by constructing desirability functions for each criterion. The combined results provide an overall numerical score for each technology under consideration as well as criteria desirability gaps. This model is useful for assessing photovoltaic technologies from varying worldviews such as the electric utility worldview, the photovoltaic manufacturer's worldview, or the national policy worldview. This model can also provide guidance to decision makers and practitioners on areas of improvement for a selected technology. The research utilizes the electric utility worldview as a case study. v

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Early detection of cancer will improve survival rates. The blood biomarker 5-hydroxymethylcytosine has been shown to discriminate cancer. In a large covariate-controlled study of over two thousand individual blood samples, we created, tested and explored the properties of a 5-hydroxymethylcytosine-based classifier to detect colorectal cancer (CRC). In an independent validation sample set, the classifier discriminated CRC samples from controls with an area under the receiver operating characteristic curve (AUC) of 90% (95% CI [87, 93]). Sensitivity was 55% at 95% specificity. Performance was similar for early stage 1 (AUC 89%; 95% CI [83, 94]) and late stage 4 CRC (AUC 94%; 95% CI [89, 98]). The classifier could detect CRC even when the proportion of tumor DNA in blood was undetectable by other methods. Expanding the classifier to include information about cell-free DNA fragment size and abundance across the genome led to gains in sensitivity (63% at 95% specificity), with similar overall performance (AUC 91%; 95% CI [89, 94]). We confirm that 5-hydroxymethylcytosine can be used to detect CRC, even in early-stage disease. Therefore, the inclusion of 5-hydroxymethylcytosine in multianalyte testing could improve sensitivity for the detection of early-stage cancer.

African-American-owned high-tech enterprises and innovations are underrepresented in industry in comparison to non-African-American-owned ones. Various complex and intertwined socio-economic factors hinder the innovation capability of African-Americanowned high-tech enterprises leading to underrepresentation of these businesses. Understanding the causal relationship between firm's interactions with internal and external entities and its ability to innovate can foster the efforts of a high-tech enterprise in increasing and sustaining innovation capabilities. Agent-based modeling (ABM) emerges as one of the popular approaches to the study of complex sociotechnological systems. Characterizing the organizational behavior of African-American-owned high-tech enterprises through the ABM perspective may provide a better understanding of the drivers, processes, and outcomes of this industry segment. By analyzing interview data among African-American entrepreneurs, this study proposes an ABM framework to represent and analyze the innovation capabilities of African-American-owned technology enterprises in comparison to other types of ownership. The ABM model illustrates the key involved agents, their attributes, actions, and the complex interactions amongst them. Simulation results indicate that African American population is underrepresented in the high-tech industry due to two significant factors of social and economic standings implying that the simulation trajectory is in the right direction. Model calibration, verification using real data and implementation plans related to policy development discussions and factors impacting African-American enterprises are also discussed in the study.