Neural network recognition of nuclear power plant transients

The objective of this report is to describe results obtained during the first year of funding that will lead to the development of an artificial neural network (ANN) fault - diagnostic system for the real - time classification of operational transients at nuclear power plants. The ultimate goal of this three-year project is to design, build, and test a prototype diagnostic adviser for use in the control room or technical support center at Duane Arnold Energy Center (DAEC); such a prototype could be integrated into the plant process computer or safety - parameter display system. The adviser could then warn and inform plant operators and engineers of plant component failures in a timely manner. This report describes the work accomplished in the first of three scheduled years for the project. Included herein is a summary of the first year's results as, well as individual descriptions of each of the major topics undertaken by the researchers. Also included are reprints of the articles written under this funding as well as those that were published during the funded period

Neural Network Recognition of Nuclear Power Plant Transients. First Annual Report, April 15, 1992--April 15, 1993, Revision 1

The objective of this report is to describe results obtained during the first year of funding that will lead to the development of an artificial neural network (ANN) fault - diagnostic system for the real - time classification of operational transients at nuclear power plants. The ultimate goal of this three-year project is to design, build, and test a prototype diagnostic adviser for use in the control room or technical support center at Duane Arnold Energy Center (DAEC); such a prototype could be integrated into the plant process computer or safety - parameter display system. The adviser could then warn and inform plant operators and engineers of plant component failures in a timely manner. This report describes the work accomplished in the first of three scheduled years for the project. Included herein is a summary of the first year`s results as, well as individual descriptions of each of the major topics undertaken by the researchers. Also included are reprints of the articles written under this funding as well as those that were published during the funded period

Correlation of PD-L1 Expression with Tumor Mutation Burden and Gene Signatures for Prognosis in Early-Stage Squamous Cell Lung Carcinoma

Objectives: Anti\u2013programmed cell death 1 (PD-1)/programmed death ligand 1 (PD-L1) immunotherapy has demonstrated success in the treatment of advanced NSCLC. Recently, PD-1/PD-L1 blockade also has demonstrated interesting results in small trials of neoadjuvant treatment in stage IB to IIIA NSCLC. In addition, several clinical trials using anti\u2013PD-1/PD-L1 immunotherapy as an adjuvant or neoadjuvant treatment in patients with resectable stage NSCLC are ongoing. However, few analyses of anti\u2013PD-1/PD-L1 immunotherapy\u2013related biomarkers in early-stage squamous cell lung carcinoma (SqCLC) have been reported. In this study, we evaluated PD-L1 protein expression, tumor mutation burden, and expression of an immune gene signature in early-stage SqCLC, providing data for identifying the potential role for patients with anti\u2013PD-1/PD-L1 treatment in early-stage SqCLC. Methods: A total of 255 specimens from patients with early-stage SqCLC were identified within participating centers of the Strategic Partnering to Evaluate Cancer Signatures program. PD-L1 protein expression by immunohistochemistry was evaluated by using the Dako PD-L1 22C3 pharmDx kit on the Dako Link 48 auto-stainer (Dako, Carpinteria, CA). Tumor mutation burden (TMB) was calculated on the basis of data from targeted genome sequencing. The T-effector and interferon gamma (IFN-\u3b3) gene signature was determined from Affymetrix gene chip data (Affymetrix, Santa Clara, CA) from frozen specimens. Results: The prevalence of PD-L1 expression was 9.8% at a tumor proportion score cutoff of at least 50%. PD-L1 mRNA and programmed cell death 1 ligand 2 mRNA positively correlated with PD-L1 protein expression on tumor cells (TCs) and tumor-infiltrating immune cells. PD-L1 protein expression on tumor-infiltrating immune cells was correlated with the T-effector and IFN-\u3b3 gene signature (p < 0.001), but not with TMB. For TCs, all of these biomarkers were independent of each other and neither PD-L1 protein expression, TMB, or T-effector and IFN-\u3b3 gene signatures were independently prognostic for patient outcomes. Conclusions: Evaluation of PD-L1 expression, TMB, and T-effector and IFN-\u3b3 gene signatures in the cohort with early-stage SqCLC found them to be independent of each other, and none was associated with overall survival. Our results also support the hypothesis that PD-L1 expression is regulated by an intrinsic mechanism on TCs and an adaptive mechanism on immune cells