Technology, Safety and Costs of Decommissioning a Reference Low-Level Waste Burial Ground. Main Report

Safety and cost information are developed for the conceptual decommissioning of commercial low-level waste (LLW) burial grounds. Two generic burial grounds, one located on an arid western site and the other located on a humid eastern site, are used as reference facilities for the study. The two burial grounds are assumed to have the same site capacity for waste, the same radioactive waste inventory, and similar trench characteristics and operating procedures. The climate, geology. and hydrology of the two sites are chosen to be typical of real western and eastern sites. Volume 1 (Main Report) contains background information and study results in summary form

Macro material flow modeling for analyzing solid waste management options

A Macro Material Flow Modeling (MMFM) concept and approach are being adopted to develop a predictive modeling capability. This capability is intended to provide part of the basis for evaluating potential impacts from various solid waste management system configurations and operating scenarios, as well as evaluating the impacts of various policies on solid waste quantities and compositions. The MMFM capability, as part of a broader Solid Waste Initiative at Pacific Northwest Laboratory, is intended to provide an increased understanding of solid waste as a disposal, energy, and resource problem on a national and global scale, particularly over the long term. This model is a macro-level simulation of the flows of the various materials through the solid waste management system, and also through the associated materials production and use system. Inclusion of materials production and use within the modeling context allows a systems approach to be used, providing a much more complete understanding of the origins of the solid waste materials and also of possible options for materials recovery and reuse than if a more traditional end-of-pipe'' view of solid waste is adopted. The MMFM is expected to be useful in evaluating longer-term, broader-ranging solid waste impacts than are traditionally evaluated by decision-makers involved in implementing solutions to local or regional solid waste management problems. This paper discusses the types of questions of interest in evaluating long-term, broad-range impacts from solid waste. It then identifies the basic needs for predictive modeling capabilities like the MMFM, and provides a basic description of the conceptual framework for the model and the associated data. Status of the MMFM implementation is also discussed

Peripheral blood marker of residual acute leukemia after hematopoietic cell transplantation using multi-plex digital droplet PCR

BACKGROUND Relapse remains the primary cause of death after hematopoietic cell transplantation (HCT) for acute leukemia. The ability to identify minimal/measurable residual disease (MRD) via the blood could identify patients earlier when immunologic interventions may be more successful. We evaluated a new test that could quantify blood tumor mRNA as leukemia MRD surveillance using droplet digital PCR (ddPCR). METHODS The multiplex ddPCR assay was developed using tumor cell lines positive for the tumor associated antigens (TAA: WT1, PRAME, BIRC5), with homeostatic ABL1. On IRB-approved protocols, RNA was isolated from mononuclear cells from acute leukemia patients after HCT (n = 31 subjects; n = 91 specimens) and healthy donors (n = 20). ddPCR simultaneously quantitated mRNA expression of WT1, PRAME, BIRC5, and ABL1 and the TAA/ABL1 blood ratio was measured in patients with and without active leukemia after HCT. RESULTS Tumor cell lines confirmed quantitation of TAAs. In patients with active acute leukemia after HCT (MRD+ or relapse; n=19), the blood levels of WT1/ABL1, PRAME/ABL1, and BIRC5/ABL1 exceeded healthy donors (p<0.0001, p=0.0286, and p=0.0064 respectively). Active disease status was associated with TAA positivity (1+ TAA vs 0 TAA) with an odds ratio=10.67, (p=0.0070, 95% confidence interval 1.91 - 59.62). The area under the curve is 0.7544. Changes in ddPCR correlated with disease response captured on standard of care tests, accurately denoting positive or negative disease burden in 15/16 (95%). Of patients with MRD+ or relapsed leukemia after HCT, 84% were positive for at least one TAA/ABL1 in the peripheral blood. In summary, we have developed a new method for blood MRD monitoring of leukemia after HCT and present preliminary data that the TAA/ABL1 ratio may may serve as a novel surrogate biomarker for relapse of acute leukemia after HCT

Exome sequencing identifies nonsegregating nonsense ATM and PALB2 variants in familial pancreatic cancer.

We sequenced 11 germline exomes from five families with familial pancreatic cancer (FPC). One proband had a germline nonsense variant in ATM with somatic loss of the variant allele. Another proband had a nonsense variant in PALB2 with somatic loss of the variant allele. Both variants were absent in a relative with FPC. These findings question the causal mechanisms of ATM and PALB2 in these families and highlight challenges in identifying the causes of familial cancer syndromes using exome sequencing

Building financial management capacity for community ownership of development initiatives in rural Zambia

Background: Building financial management capacity is increasingly important in low- and middle-income countries to help communities take ownership of development activities. Yet, many community members lack financial knowledge and skills. Methods: As part of a larger health intervention, we designed and conducted financial management training for 83 members from 10 community groups in rural Zambia. Change scores between pre- and post-tests on financial knowledge were calculated and multivariate linear regression models run. Qualitative feedback was elicited. Results: The training significantly improved knowledge of financial concepts. Participants with some or more than some secondary education had greater improvements in knowledge (by 1.8 and 2.9 points out of 10 respectively; p=0.003 and p\u3c0.001). Participants appreciated exercises to contextualize financial concepts within daily life, and liked opportunities to learn from peers in small groups. Language barriers were a particular challenge. Conclusion: Financial management training may contribute to the sustainability of community-managed interventions but needs to be tailored to the background and education level of the participants. Training should relate financial concept to more tangible applications and provide time for active learning. This training approach could be used in similar settings to improve community oversight of resources intended to strengthen developmental initiatives

The Iterative Signature Algorithm for the analysis of large scale gene expression data

We present a new approach for the analysis of genome-wide expression data. Our method is designed to overcome the limitations of traditional techniques, when applied to large-scale data. Rather than alloting each gene to a single cluster, we assign both genes and conditions to context-dependent and potentially overlapping transcription modules. We provide a rigorous definition of a transcription module as the object to be retrieved from the expression data. An efficient algorithm, that searches for the modules encoded in the data by iteratively refining sets of genes and conditions until they match this definition, is established. Each iteration involves a linear map, induced by the normalized expression matrix, followed by the application of a threshold function. We argue that our method is in fact a generalization of Singular Value Decomposition, which corresponds to the special case where no threshold is applied. We show analytically that for noisy expression data our approach leads to better classification due to the implementation of the threshold. This result is confirmed by numerical analyses based on in-silico expression data. We discuss briefly results obtained by applying our algorithm to expression data from the yeast S. cerevisiae.Comment: Latex, 36 pages, 8 figure

Six Human-Centered Artificial Intelligence Grand Challenges

Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the human condition in ways that are not yet well understood. Negative unintended consequences abound including the perpetuation and exacerbation of societal inequalities and divisions via algorithmic decision making. We present six grand challenges for the scientific community to create AI technologies that are human-centered, that is, ethical, fair, and enhance the human condition. These grand challenges are the result of an international collaboration across academia, industry and government and represent the consensus views of a group of 26 experts in the field of human-centered artificial intelligence (HCAI). In essence, these challenges advocate for a human-centered approach to AI that (1) is centered in human well-being, (2) is designed responsibly, (3) respects privacy, (4) follows human-centered design principles, (5) is subject to appropriate governance and oversight, and (6) interacts with individuals while respecting human’s cognitive capacities. We hope that these challenges and their associated research directions serve as a call for action to conduct research and development in AI that serves as a force multiplier towards more fair, equitable and sustainable societies

Grouping time series by pairwise measures of redundancy

A novel approach is proposed to group redundant time series in the frame of causality. It assumes that (i) the dynamics of the system can be described using just a small number of characteristic modes, and that (ii) a pairwise measure of redundancy is sufficient to elicit the presence of correlated degrees of freedom. We show the application of the proposed approach on fMRI data from a resting human brain and gene expression profiles from HeLa cell culture.Comment: 4 pages, 8 figure

Disorder-to-order transition in the magnetic and electronic properties of URh_2Ge_2

We present a study of annealing effects on the physical properties of tetragonal single--crystalline URh_2Ge_2. This system, which in as-grown form was recently established as the first metallic 3D random-bond heavy-fermion spin glass, is transformed by an annealing treatment into a long-range antiferromagnetically (AFM) ordered heavy-fermion compound. The transport properties, which in the as-grown material were dominated by the structural disorder, exhibit in the annealed material signs of typical metallic behavior along the crystallographic a axis. From our study URh_2Ge_2 emerges as exemplary material highlighting the role and relevance of structural disorder for the properties of strongly correlated electron systems. We discuss the link between the magnetic and electronic behavior and how they are affected by the structural disorder.Comment: Phys. Rev. B, in print (scheduled 1 Mar 2000