727 research outputs found
Critical animal and media studies: Expanding the understanding of oppression in communication research
Critical and communication studies have traditionally neglected the oppression conducted by humans towards other animals. However, our (mis)treatment of other animals is the result of public consent supported by a morally speciesist-anthropocentric system of values. Speciesism or anthroparchy, as much as any other mainstream ideologies, feeds the media and at the same time is perpetuated by them. The goal of this article is to remedy this neglect by introducing the subdiscipline of Critical Animal and Media Studies. Critical Animal and Media Studies takes inspiration both from critical animal studies – which is so far the most consolidated critical field of research in the social sciences addressing our exploitation of other animals – and from the normative-moral stance rooted in the cornerstones of traditional critical media studies. The authors argue that the Critical Animal and Media Studies approach is an unavoidable step forward for critical media and communication studies to engage with the expanded circle of concerns of contemporary ethical thinking
Z-extremization and F-theorem in Chern-Simons matter theories
The three dimensional exact R symmetry of N=2 SCFTs extremizes the partition
function localized on a three sphere. Here we verify this statement at weak
coupling. We give a detailed analysis for two classes of models. The first one
is an SU(N)_k gauge theory at large k with both fundamental and adjoint matter
fields, while the second is a flavored version of the ABJ theory, where the CS
levels are large but they do not necessarily sum up to zero. We study in both
cases superpotential deformations and compute the R charges at different fixed
points. When these fixed points are connected by an RG flow we explicitly
verify that the free energy decreases at the endpoints of the flow between the
fixed points, corroborating the conjecture of an F-theorem in three dimensions.Comment: 28 pages, 3 figures, JHEP.cls, minor corrections, references adde
Essential versus accessory aspects of cell death: recommendations of the NCCD 2015
Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
<p>Abstract</p> <p>Background</p> <p>In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space.</p> <p>Results</p> <p>The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability.</p> <p>Conclusions</p> <p>While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.</p
First observations of separated atmospheric nu_mu and bar{nu-mu} events in the MINOS detector
The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of nuµ and [overline nu ]µ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving Rup/downdata/Rup/downMC=0.62-0.14+0.19(stat.)±0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field nuµ and [overline nu ]µ interactions are separated. The ratio of [overline nu ]µ to nuµ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving R[overline nu ][sub mu]/nu[sub mu]data/R[overline nu ][sub mu]/nu[sub mu]MC=0.96-0.27+0.38(stat.)±0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for nuµ and [overline nu ]µ
Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron
We study the underlying event in proton-antiproton collisions by examining
the behavior of charged particles (transverse momentum pT > 0.5 GeV/c,
pseudorapidity |\eta| < 1) produced in association with large transverse
momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the
Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV
center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan
production) or the leading jet (in high-pT jet production) in each event to
define three regions of \eta-\phi space; toward, away, and transverse, where
\phi is the azimuthal scattering angle. For Drell-Yan production (excluding the
leptons) both the toward and transverse regions are very sensitive to the
underlying event. In high-pT jet production the transverse region is very
sensitive to the underlying event and is separated into a MAX and MIN
transverse region, which helps separate the hard component (initial and
final-state radiation) from the beam-beam remnant and multiple parton
interaction components of the scattering. The data are corrected to the
particle level to remove detector effects and are then compared with several
QCD Monte-Carlo models. The goal of this analysis is to provide data that can
be used to test and improve the QCD Monte-Carlo models of the underlying event
that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.
Precision measurement of the top quark mass from dilepton events at CDF II
We report a measurement of the top quark mass, M_t, in the dilepton decay
channel of
using an integrated luminosity of 1.0 fb^{-1} of p\bar{p} collisions collected
with the CDF II detector. We apply a method that convolutes a leading-order
matrix element with detector resolution functions to form event-by-event
likelihoods; we have enhanced the leading-order description to describe the
effects of initial-state radiation. The joint likelihood is the product of the
likelihoods from 78 candidate events in this sample, which yields a measurement
of M_{t} = 164.5 \pm 3.9(\textrm{stat.}) \pm 3.9(\textrm{syst.})
\mathrm{GeV}/c^2, the most precise measurement of M_t in the dilepton channel.Comment: 7 pages, 2 figures, version includes changes made prior to
publication by journa
Cross Section Measurements of High- Dilepton Final-State Processes Using a Global Fitting Method
We present a new method for studying high- dilepton events
(, , ) and simultaneously
extracting the production cross sections of , , and p\bar{p} \to \ztt at a center-of-mass energy of TeV. We perform a likelihood fit to the dilepton data in a parameter
space defined by the missing transverse energy and the number of jets in the
event. Our results, which use of data recorded with the CDF
II detector at the Fermilab Tevatron Collider, are pb, pb, and
\sigma(\ztt) =291^{+50}_{-46} pb.Comment: 20 pages, 2 figures, to be submitted to PRD-R
Measurement of the Ratios of Branching Fractions B(Bs -> Ds pi pi pi) / B(Bd -> Dd pi pi pi) and B(Bs -> Ds pi) / B(Bd -> Dd pi)
Using 355 pb^-1 of data collected by the CDF II detector in \ppbar collisions
at sqrt{s} = 1.96 TeV at the Fermilab Tevatron, we study the fully
reconstructed hadronic decays B -> D pi and B -> D pi pi pi. We present the
first measurement of the ratio of branching fractions B(Bs -> Ds pi pi pi) /
B(Bd -> Dd pi pi pi) = 1.05 pm 0.10 (stat) pm 0.22 (syst). We also update our
measurement of B(Bs -> Ds pi) / B(Bd -> Dd pi) to 1.13 pm 0.08 (stat) pm 0.23
(syst) improving the statistical uncertainty by more than a factor of two. We
find B(Bs -> Ds pi) = [3.8 pm 0.3 (stat) pm 1.3 (syst)] \times 10^{-3} and B(Bs
-> Ds pi pi pi) = [8.4 pm 0.8 (stat) pm 3.2 (syst)] \times 10^{-3}.Comment: 7 pages, 2 figure
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