From program to network: the evaluator’s role in today’s public problem-solving environment

Today's public policy discussions increasingly focus on how networks of public and private actors collaborate across organizational, sectoral, and geographical boundaries to solve increasingly complex problems. Yet, many of evaluation's key concepts, including the evaluator's role, assume an evaluand that is programmatically or organizationally defined and bounded. This article explores the implications of this changing public policy environment for the evaluator's role by examining one case: an evaluand that was a loose collaboration of four individuals in dispersed organizations working to reframe public policy and to change professional practice in early care and education. We describe this evaluand and the dimensions of it that challenged our evaluative role. We conclude by suggesting an alternative conception of the evaluator's role that can serve evaluators in this changing policy environment

PITTSBURGH’S RACIAL DEMOGRAPHICS: DIFFERENCES AND DISPARITIES

Pittsburgh’s Racial Demographics: Differences and Disparities provides indicators of quality of life by race and ethnicity in the Pittsburgh region. Data are provided for four groups (Whites, African Americans, Asians, and Hispanics) and for four geographic areas (city of Pittsburgh, Allegheny County, Pittsburgh Metropolitan Statistical Area, and the U.S.). The most recent data available for the Pittsburgh area and the nation were used in this report. In some instances, however, only data from the 2000 census were available to make comparisons. It is also the case that data were not available on all of our topic areas in the same years. It is our hope to update this report every three years, particularly if the American Community Survey (which is designed to replace the decennial census) produces regular, reliable data by race for cities, counties, and regions

miQC : An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data

Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a 'low-quality' cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC. Author summary We developed the miQC package to predict the low-quality cells in a given scRNA-seq dataset by jointly modeling both the proportion of reads mapping to mitochondrial DNA (mtDNA) genes and the number of detected genes using mixture models in a probabilistic framework. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses.Peer reviewe

The Sloan Digital Sky Survey Reverberation Mapping project : composite lags at z ≤ 1

Funding: STFC grant ST/M001296/1 (KH).We present composite broad-line region (BLR) reverberation mapping lag measurements for Hα, Hβ, He II λ4686, and Mg II for a sample of 144, z ≲ 1 quasars from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project. Using only the 32-epoch spectroscopic light curves in the first six-month season of SDSS-RM observations, we compile correlation function measurements for individual objects and then coadd them to allow the measurement of the average lags for our sample at mean redshifts of 0.4 (for Hα) and ∼0.65 (for the other lines). At similar quasar luminosities and redshifts, the sample-averaged lag decreases in the order of Mg II, Hα, Hβ, and He II. This decrease in lags is accompanied by an increase in the mean line width of the four lines, and is roughly consistent with the virialized motion for BLR gas in photoionization equilibrium. These are among the first RM measurements of stratified BLR structure at z > 0.3. Dividing our sample by luminosity, Hα shows clear evidence of increasing lags with luminosity, consistent with the expectation from the measured BLR size-luminosity relation based on Hβ. The other three lines do not show a clear luminosity trend in their average lags due to the limited dynamic range of luminosity probed and the poor average correlation signals in the divided samples, a situation that will be improved with the incorporation of additional photometric and spectroscopic data from SDSS-RM. We discuss the utility and caveats of composite lag measurements for large statistical quasar samples with reverberation mapping dataPostprintPeer reviewe

Human Impacts on Forest Biodiversity in Protected Walnut-Fruit Forests in Kyrgyzstan

We used a spatially explicit model of forest dynamics, supported by empirical field data and socioeconomic data, to examine the impacts of human disturbances on a protected forest landscape in Kyrgyzstan. Local use of 27 fruit and nut species was recorded and modeled. Results indicated that in the presence of fuelwood cutting with or without grazing, species of high socioeconomic impor- tance such as Juglans regia, Malus spp., and Armeniaca vulgaris were largely eliminated from the landscape after 50–150 yr. In the absence of disturbance or in the presence of grazing only, decline of these species occurred at a much lower rate, owing to competi- tive interactions between tree species. This suggests that the current intensity of fuelwood harvesting is not sustainable. Conversely, cur- rent grazing intensities were found to have relatively little impact on forest structure and composition, and could potentially play a positive role in supporting regeneration of tree species. These results indicate that both positive and negative impacts on biodiversity can arise from human populations living within a protected area. Potentially, these could be reconciled through the development of participatory approaches to conservation management within this reserve, to ensure the maintenance of its high conservation value while meeting human needs

Mapping SF-36 onto the EQ-5D index: how reliable is the relationship?

<p>Abstract</p> <p>Background</p> <p>Mapping from health status measures onto generic preference-based measures is becoming a common solution when health state utility values are not directly available for economic evaluation. However the accuracy and reliability of the models employed is largely untested, and there is little evidence of their suitability in patient datasets. This paper examines whether mapping approaches are reliable and accurate in terms of their predictions for a large and varied UK patient dataset.</p> <p>Methods</p> <p>SF-36 dimension scores are mapped onto the EQ-5D index using a number of different model specifications. The predicted EQ-5D scores for subsets of the sample are compared across inpatient and outpatient settings and medical conditions. This paper compares the results to those obtained from existing mapping functions.</p> <p>Results</p> <p>The model including SF-36 dimensions, squared and interaction terms estimated using random effects GLS has the most accurate predictions of all models estimated here and existing mapping functions as indicated by MAE (0.127) and MSE (0.030). Mean absolute error in predictions by EQ-5D utility range increases with severity for our models (0.085 to 0.34) and for existing mapping functions (0.123 to 0.272).</p> <p>Conclusion</p> <p>Our results suggest that models mapping the SF-36 onto the EQ-5D have similar predictions across inpatient and outpatient setting and medical conditions. However, the models overpredict for more severe EQ-5D states; this problem is also present in the existing mapping functions.</p

Toll-like receptor polymorphisms and cerebral malaria: <it>TLR2 </it>Δ22 polymorphism is associated with protection from cerebral malaria in a case control study

<p>Abstract</p> <p>Background</p> <p>In malaria endemic areas, host genetics influence whether a <it>Plasmodium falciparum</it>-infected child develops uncomplicated or severe malaria. TLR2 has been identified as a receptor for <it>P. falciparum</it>-derived glycosylphosphatidylinositol (GPI), and polymorphisms within the TLR2 gene may affect disease pathogenesis. There are two common polymorphisms in the 5' un-translated region (UTR) of TLR2, a 22 base pair deletion in the first unstranslated exon (Δ22), and a GT dinucleotide repeat in the second intron (GTn).</p> <p>Methods</p> <p>These polymorphisms were examined in a Ugandan case control study on children with either cerebral malaria or uncomplicated malaria. Serum cytokine levels were analysed by ELISA, according to genotype and disease status. In vitro TLR2 expression was measured according to genotype.</p> <p>Results</p> <p>Both Δ22 and GTn polymorphisms were highly frequent, but only Δ22 heterozygosity was associated with protection from cerebral malaria (OR 0.34, 95% confidence intervals 0.16, 0.73). In vitro, heterozygosity for Δ22 was associated with reduced pam3cys inducible TLR2 expression in human monocyte derived macrophages. In uncomplicated malaria patients, Δ22 homozygosity was associated with elevated serum IL-6 (<it>p </it>= 0.04), and long GT repeat alleles were associated with elevated TNF (<it>p </it>= 0.007).</p> <p>Conclusion</p> <p>Reduced inducible TLR2 expression may lead to attenuated pro-inflammatory responses, a potential mechanism of protection from cerebral malaria present in individuals heterozygous for the TLR2 Δ22 polymorphism.</p

Prime Focus Spectrograph (PFS) for the Subaru Telescope: Overview, recent progress, and future perspectives

PFS (Prime Focus Spectrograph), a next generation facility instrument on the 8.2-meter Subaru Telescope, is a very wide-field, massively multiplexed, optical and near-infrared spectrograph. Exploiting the Subaru prime focus, 2394 reconfigurable fibers will be distributed over the 1.3 deg field of view. The spectrograph has been designed with 3 arms of blue, red, and near-infrared cameras to simultaneously observe spectra from 380nm to 1260nm in one exposure at a resolution of ~1.6-2.7A. An international collaboration is developing this instrument under the initiative of Kavli IPMU. The project is now going into the construction phase aiming at undertaking system integration in 2017-2018 and subsequently carrying out engineering operations in 2018-2019. This article gives an overview of the instrument, current project status and future paths forward.Comment: 17 pages, 10 figures. Proceeding of SPIE Astronomical Telescopes and Instrumentation 201