Resilient Power Project Case Study: Sterling Municipal Light Department

Sterling Municipal Light Department (SMLD) is a municipal utility serving the small New England town of Sterling, Massachusetts, with 3,700 residential, commercial, municipal, and industrial customers. In 2013, with a total of 3.2 megawatts (MW) of solar PV installed, SMLD became the number one utilityin the country for solar watts per customer. Solar accounted for approximately 30 percent of SMLD's peak load. At this high level of penetration, the variable nature of solar generation bagan to cause problems. Additionally, the costs of capacity and transmission services, based on SMLD"s peak demand for power purchased from the grid operator, were rising dramatically. These costs increased from $500,000 in 2010 to$1.2 million in 2017. SMLD needed a new strategy to firm the output of its solar generation and control rising costs linked to the utility's share of regional demand peak.The town of Sterling was considering adding a natural gas peaker plant to avoid rising capacity costs at its Municipal Light Department. But this idea was abandoned when the option of energy storage presented itself in the form of a state grant program offered through the Massachusetts Department of Energy Resources (DOER), called the Community Clean Energy Resiliency Initiative (CCERI). The grant program, initiated after Superstorm Sandy devastated the Northeast,w as designed to support municipal resilient clean energy systems. The town had also been hit by an ice storm in 2008, which had left residents without power for up to 14 days; thus, reciliency had been a longtime conern for the town. Energy storage presented an attractive means to firm the town's solar resources, add reciliency for critical infrastructure, and control rising costs

Economic aspects of the bee industry /

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Verification of Unstructured Grid Adaptation Components

Adaptive unstructured grid techniques have made limited impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic grid adaptation mechanics. Known differences and previously unknown differences in grid adaptation components and their integrated processes are identified here for study. Unstructured grid adaptation tools are verified using analytic functions and the Code Comparison Principle. Three analytic functions with different smoothness properties are adapted to show the impact of smoothness on implementation differences. A scalar advection-diffusion problem with an analytic solution that models a boundary layer is adapted to test individual grid adaptation components. Laminar flow over a delta wing and turbulent flow over an ONERA M6 wing are verified with multiple, independent grid adaptation procedures to show consistent convergence to fine-grid forces and a moment. The scalar problems illustrate known differences in a grid adaptation component implementation and a previously unknown interaction between components. The wing adaptation cases in the current study document a clear improvement to existing grid adaptation procedures. The stage is set for the infusion of verified grid adaptation into production fluid flow simulations

Verification of Unstructured Grid Adaptation Components

Adaptive unstructured grid techniques have made limited impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic grid adaptation mechanics. Known differences and previously unknown differences in grid adaptation components and their integrated processes are identified here for study. Unstructured grid adaptation tools are verified using analytic functions and the Code Comparison Principle. Three analytic functions with different smoothness properties are adapted to show the impact of smoothness on implementation differences. A scalar advection-diffusion problem with an analytic solution that models a boundary layer is adapted to test individual grid adaptation components. The scalar problems illustrate known differences in a grid adaptation component implementation and a previously unknown interaction between components. Laminar flow over a delta wing is verified with multiple, independent grid adaptation procedures to show consistent convergence to fine-grid forces and pitching moment

Rapid tests and urine sampling techniques for the diagnosis of urinary tract infection (UTI) in children under five years: a systematic review

Background: Urinary tract infection (UTI) is one of the most common sources of infection in children under five. Prompt diagnosis and treatment is important to reduce the risk of renal scarring. Rapid, cost-effective, methods of UTI diagnosis are required as an alternative to culture. Methods: We conducted a systematic review to determine the diagnostic accuracy of rapid tests for detecting UTI in children under five years of age. Results: The evidence supports the use of dipstick positive for both leukocyte esterase and nitrite (pooled LR+ = 28.2, 95% CI: 17.3, 46.0) or microscopy positive for both pyuria and bacteriuria (pooled LR+ = 37.0, 95% CI: 11.0, 125.9) to rule in UTI. Similarly dipstick negative for both LE and nitrite (Pooled LR- = 0.20, 95% CI: 0.16, 0.26) or microscopy negative for both pyuria and bacteriuria (Pooled LR- = 0.11, 95% CI: 0.05, 0.23) can be used to rule out UTI. A test for glucose showed promise in potty-trained children. However, all studies were over 30 years old. Further evaluation of this test may be useful. Conclusion: Dipstick negative for both LE and nitrite or microscopic analysis negative for both pyuria and bacteriuria of a clean voided urine, bag, or nappy/pad specimen may reasonably be used to rule out UTI. These patients can then reasonably be excluded from further investigation, without the need for confirmatory culture. Similarly, combinations of positive tests could be used to rule in UTI, and trigger further investigation

Geometric, kinematic, and erosional history of the central Andean Plateau, Bolivia (15–17°S)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95425/1/tect1910.pd

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment