516 research outputs found
The dark side of economic freedom: neoliberalism has deleterious effects on labour rights
The common criticism is that market-liberalising policies sacrifice social and political rights. Robert Blanton and Dursun Peksen adopt a novel approach, finding more nuanced insights concerning the dynamics between neoliberalism and labour rights. Overall, their findings confirm that the relationship between the two is markedly negative, in spite of the mounting empirical evidence that worker rights may be conducive to a competitive economy. As they argue, achieving a more equitable balance is an issue that needs to be urgently addressed
An Efficient Targeting Strategy for Multiobject Spectrograph Surveys: the Sloan Digital Sky Survey "Tiling" Algorithm
Large surveys using multiobject spectrographs require automated methods for deciding how to efficiently point observations and how to assign targets to each pointing. The Sloan Digital Sky Survey (SDSS) will observe around 10 6 spectra from targets distributed over an area of about 10,000 deg2, using a multiobject fiber spectrograph that can simultaneously observe 640 objects in a circular field of view (referred to as a "tile") 1°.49 in radius. No two fibers can be placed closer than 55Prime; during the same observation; multiple targets closer than this distance are said to "collide." We present here a method of allocating fibers to desired targets given a set of tile centers that includes the effects of collisions and that is nearly optimally efficient and uniform. Because of large-scale structure in the galaxy distribution (which form the bulk of the SDSS targets), a naive covering of the sky with equally spaced tiles does not yield uniform sampling. Thus, we present a heuristic for perturbing the centers of the tiles from the equally spaced distribution that provides more uniform completeness. For the SDSS sample, we can attain a sampling rate of greater than 92% for all targets, and greater than 99% for the set of targets that do not collide with each other, with an efficiency greater than 90% (defined as the fraction of available fibers assigned to targets). The methods used here may prove useful to those planning other large surveys
An Efficient Targeting Strategy for Multiobject Spectrograph Surveys: the Sloan Digital Sky Survey âTilingâ Algorithm
Large surveys using multiobject spectrographs require automated methods for deciding how to efficiently point observations and how to assign targets to each pointing. The Sloan Digital Sky Survey (SDSS) will observe around 106 spectra from targets distributed over an area of about 10,000 deg2 , using a multiobject fiber spectrograph that can simultaneously observe 640 objects in a circular field of view (referred to as a ââ tile ââ) 1= 49 in radius. No two fibers can be placed closer than 5500 during the same observation; multiple targets closer than this distance are said to ââ collide.ââ We present here a method of allocating fibers to desired targets given a set of tile centers that includes the effects of collisions and that is nearly optimally efficient and uniform. Because of large-scale structure in the galaxy distribution (which form the bulk of the SDSS targets), a naive covering of the sky with equally spaced tiles does not yield uniform sampling. Thus, we present a heuristic for perturbing the centers of the tiles from the equally spaced distribution that provides more uniform completeness. For the SDSS sample, we can attain a sampling rate of greater than 92% for all targets, and greater than 99% for the set of targets that do not collide with each other, with an efficiency greater than 90% (defined as the fraction of available fibers assigned to targets). The methods used here may prove useful to those planning other large surveys
A Commons for a Supply Chain in the Post-COVID-19 Era: The Case for a Reformed Strategic National Stockpile
The article of record as published may be found at http://dx.doi.org/10.1111/1468-0009.12485Policy Points: Reflecting on current response deficiencies, we offer a model for a na- tional contingency supply chain cell (NCSCC) construct to manage the medical materials supply chain in support of emergencies, such as COVID-19. We develop the following: a framework for governance and response to enable a globally independent supply chain; a flexible structure to accommodate the requirements of state and r county health systems for receiving and distributing materials; and a national material "control tower" to improve transparency and real- time access to material status and location.Office of Naval Research grants N00014-04-1-0118, N00014-10- 1-0200, N00014-11-1-0783, N00014-10-1-0811, N00014-16-1-2567, and N00014-04-1-0018. A.N. acknowledges support from an NSF CAREER and NOAA OGP. A.B.M. acknowledges support from the Mexican National Council for Science and Technology (CONACyT).Office of Naval Research grants N00014-04-1-0118, N00014-10- 1-0200, N00014-11-1-0783, N00014-10-1-0811, N00014-16-1-2567, and N00014-04-1-0018
How covariant is the galaxy luminosity function?
We investigate the error properties of certain galaxy luminosity function
(GLF) estimators. Using a cluster expansion of the density field, we show how,
for both volume and flux limited samples, the GLF estimates are covariant. The
covariance matrix can be decomposed into three pieces: a diagonal term arising
from Poisson noise; a sample variance term arising from large-scale structure
in the survey volume; an occupancy covariance term arising due to galaxies of
different luminosities inhabiting the same cluster. To evaluate the theory one
needs: the mass function and bias of clusters, and the conditional luminosity
function (CLF). We use a semi-analytic model (SAM) galaxy catalogue from the
Millennium run N-body simulation and the CLF of Yang et al. (2003) to explore
these effects. The GLF estimates from the SAM and the CLF qualitatively
reproduce results from the 2dFGRS. We also measure the luminosity dependence of
clustering in the SAM and find reasonable agreement with 2dFGRS results for
bright galaxies. However, for fainter galaxies, L<L*, the SAM overpredicts the
relative bias by ~10-20%. We use the SAM data to estimate the errors in the GLF
estimates for a volume limited survey of volume V~0.13 [Gpc/h]^3. We find that
different luminosity bins are highly correlated: for L<L* the correlation
coefficient is r>0.5. Our theory is in good agreement with these measurements.
These strong correlations can be attributed to sample variance. For a
flux-limited survey of similar volume, the estimates are only slightly less
correlated. We explore the importance of these effects for GLF model parameter
estimation. We show that neglecting to take into account the bin-to-bin
covariances can lead to significant systematic errors in best-fit parameters.Comment: 19 pages, 12 figures. Accepted for publication in MNRAS. Refs
updated; Fig 6 added; Figs 7 and 10 improve
JNK and cardiometabolic dysfunction
Cardiometabolic syndrome (CMS) describes the cluster of metabolic and cardiovascular diseases that are generally characterized by impaired glucose tolerance, intra-abdominal adiposity, dyslipidemia, and hypertension. CMS currently affects more than 25% of the world\u27s population and the rates of diseases are rapidly rising. These CMS conditions represent critical risk factors for cardiovascular diseases including atherosclerosis, heart failure, myocardial infarction, and peripheral artery disease (PAD). Therefore, it is imperative to elucidate the underlying signaling involved in disease onset and progression. The c-Jun N-terminal Kinases (JNKs) are a family of stress signaling kinases that have been recently indicated in CMS. The purpose of this review is to examine the in vivo implications of JNK as a potential therapeutic target for CMS. As the constellation of diseases associated with CMS are complex and involve multiple tissues and environmental triggers, carefully examining what is known about the JNK pathway will be important for specificity in treatment strategies
Evolution of the Clustering of Photometrically Selected SDSS Galaxies
We measure the angular auto-correlation functions (w) of SDSS galaxies
selected to have photometric redshifts 0.1 < z < 0.4 and absolute r-band
magnitudes Mr < -21.2. We split these galaxies into five overlapping redshift
shells of width 0.1 and measure w in each subsample in order to investigate the
evolution of SDSS galaxies. We find that the bias increases substantially with
redshift - much more so than one would expect for a passively evolving sample.
We use halo-model analysis to determine the best-fit
halo-occupation-distribution (HOD) for each subsample, and the best-fit models
allow us to interpret the change in bias physically. In order to properly
interpret our best-fit HODs, we convert each halo mass to its z = 0 passively
evolved bias (bo), enabling a direct comparison of the best-fit HODs at
different redshifts. We find that the minimum halo bo required to host a galaxy
decreases as the redshift decreases, suggesting that galaxies with Mr < -21.2
are forming in halos at the low-mass end of the HODs over our redshift range.
We use the best-fit HODs to determine the change in occupation number divided
by the change in mass of halos with constant bo and we find a sharp peak at bo
~ 0.9 - corresponding to an average halo mass of ~ 10^12Msol/h. We thus present
the following scenario: the bias of galaxies with Mr < -21.2 decreases as the
Universe evolves because these galaxies form in halos of mass ~ 10^12Msol/h
(independent of redshift), and the bias of these halos naturally decreases as
the Universe evolves.Comment: 17 pages, 14 figures, matches version accepted for publication in
MNRA
Hubble Residuals of Nearby Type Ia Supernovae Are Correlated with Host Galaxy Masses
From Sloan Digital Sky Survey u'g'r'i'z' imaging, we estimate the stellar
masses of the host galaxies of 70 low redshift SN Ia (0.015 < z < 0.08) from
the hosts' absolute luminosities and mass-to-light ratios. These nearby SN were
discovered largely by searches targeting luminous galaxies, and we find that
their host galaxies are substantially more massive than the hosts of SN
discovered by the flux-limited Supernova Legacy Survey. Testing four separate
light curve fitters, we detect ~2.5{\sigma} correlations of Hubble residuals
with both host galaxy size and stellar mass, such that SN Ia occurring in
physically larger, more massive hosts are ~10% brighter after light curve
correction. The Hubble residual is the deviation of the inferred distance
modulus to the SN, calculated from its apparent luminosity and light curve
properties, away from the expected value at the SN redshift. Marginalizing over
linear trends in Hubble residuals with light curve parameters shows that the
correlations cannot be attributed to a light curve-dependent calibration error.
Combining 180 higher-redshift ESSENCE, SNLS, and HigherZ SN with 30 nearby SN
whose host masses are less than 10^10.8 solar masses in a cosmology fit yields
1+w=0.22 +0.152/-0.143, while a combination where the 30 nearby SN instead have
host masses greater than 10^10.8 solar masses yields 1+w=-0.03 +0.217/-0.108.
Progenitor metallicity, stellar population age, and dust extinction correlate
with galaxy mass and may be responsible for these systematic effects. Host
galaxy measurements will yield improved distances to SN Ia.Comment: 16 pages, 6 figures, published in ApJ, minor change
- âŠ