Decision-Making for High Renewable Electricity Futures in the United States
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Unlike the power sector—which can transmit electricity over long distances via established grids—the industrial sector poses a unique challenge due to its geographically concentrated large-scale heat processes. Enhancing energy security in such industrial parks provides a dual benefit: reduced exposure to volatile fossil fuel prices and improved economic viability, largely driven by economies of scale in energy supply and distribution. This study presents a comprehensive technoeconomic analysis of a nuclear energy hub, employing a mechanism-focused approach to evaluate uncertainties in operational strategies and capacity optimization. Load profiles from three major energy intesive industries—chemical, refinery, and steelmaking—are examined, each presenting unique challenges and opportunities for nuclear energy integration. We adopt a multi-objective optimization framework, converting multiple objectives into a single objective function through the e-constraint method. The findings highlight clear trade-offs between system conditions and varying levels of energy independence. Overall, this analysis is granular enough to address industry-specific concerns yet sufficiently generalizable to provide actionable insights into the feasibility of nuclear-based clean heat solutions for the industrial sector.
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The US DOE-funded National Risk Assessment Partnership (NRAP) has developed an integrated assessment model (NRAP-IAM-CS) that can be used to simulate carbon dioxide (CO 2 ) injection, migration, and associated impacts at a geologic carbon storage site. The model, NRAP-IAM-CS, incorporates a system-modeling-based approach while taking into account the full subsurface system from the storage reservoir to groundwater aquifers and the atmosphere. The approach utilizes reduced order models (ROMs) that allow fast computations of entire system performance even for periods of hundreds to thousands of years. The ROMs are run in Monte Carlo mode allowing estimation of uncertainties of the entire system without requiring long computational times. The NRAP-IAM-CS incorporates ROMs that realistically represent several key processes and properties of storage reservoirs, wells, seals, and groundwater aquifers. Results from the NRAP-IAM-CS model are used to quantify risk profiles for selected parameter distributions of reservoir properties, seal properties, numbers of wells, well properties, thief zones, and groundwater aquifer properties. A series of examples is used to illustrate how the risk under different storage conditions evolves over time, both during injection, in the near-term post injection period, and over the long term. Finally, it is also shown how results from NRAP-IAM-CS can be used to investigate the importance of different parameters on risk of leakage and risk of groundwater contamination under different storage conditions.
Purpose: The role of consolidative radiation therapy (RT) for stage III and IV diffuse large B-cell lymphoma (DLBCL) in the era of rituximab is not well defined. There is evidence that some patients with bulky disease may benefit, but patient selection criteria are not well established. We sought to identify a subset of patients who experienced a high local failure rate after receiving rituximab-based chemotherapy alone and hence may benefit from the addition of consolidative RT. Methods and Materials: Two hundred eleven patients with stage III and IV DLBCL treated between August 1999 and January 2012 were reviewed. Of these, 89 had a complete response to systemic therapy including rituximab and received no initial RT. Kaplan-Meier analysis and Cox proportional hazards regression were performed, with local recurrence (LR) as the primary outcome. Results: The median follow-up time was 43.9 months. Fifty percent of patients experienced LR at 5 years. In multivariate analysis, tumor ≥5 cm and stage III disease were associated with increased risk of LR. The 5-year LR-free survival was 47.4% for patients with ≥5-cm lesions versus 74.7% for patients with <5-cm lesions (P=.01). In patients with <5-cm tumors, the maximum standardized uptake value (SUVmax) was ≥15 in all patients with LR. The 5-year LR-free survival was 100% in SUV<15 versus 68.8% in SUV≥15 (P=.10). Conclusions: Advanced-stage DLBCL patients with stage III disease or with disease ≥5 cm appear to be at an increased risk for LR. Patients with <5-cm disease and SUVmax ≥15 may be at higher risk for LR. These patients may benefit from consolidative RT after chemoimmunotherapy.
Tumor biomarkers are used routinely in oncology to assign risk categorization, screen and assist in diagnosis of malignancy, allow for prognostication and prediction of outcomes and treatment response, and allow for monitoring of patients after treatment completion. Although tissue-based biomarkers have a long history of use, the emergence of liquid-based biomarkers, including circulating tumor cells (CTCs), may soon revolutionize the management of patients with cancer. Here, we review the discovery of CTCs and their role as prognostic and predictive biomarkers, with an emphasis on breast cancer. We discuss the platforms for CTC enumeration and focus on studies using the only US Food and Drug Administration–approved platform for CTC enumeration (CellSearch). In addition, we examine the role of CTCs in women with metastatic, inflammatory, and nonmetastatic breast cancer, as well as the clinical evidence for their use as a surrogate for radiation treatment response as well as surveillance after treatment. Finally, we conclude by investigating ongoing clinical studies assessing CTCs as radiation response predictors and discuss unanswered questions.
Cardiac toxicity is a well-recognized risk after radiation therapy (RT) in patients with non-small cell lung cancer (NSCLC). However, the extent to which treatment planning optimization can reduce mean heart dose (MHD) without untoward increases in lung dose is unknown.
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