Analysis of relativistic nucleus-nucleus interactions in emulsion chambers

The development of a computer-assisted method is reported for the determination of the angular distribution data for secondary particles produced in relativistic nucleus-nucleus collisions in emulsions. The method is applied to emulsion detectors that were placed in a constant, uniform magnetic field and exposed to beams of 60 and 200 GeV/nucleon O-16 ions at the Super Proton Synchrotron (SPS) of the European Center for Nuclear Research (CERN). Linear regression analysis is used to determine the azimuthal and polar emission angles from measured track coordinate data. The software, written in BASIC, is designed to be machine independent, and adaptable to an automated system for acquiring the track coordinates. The fitting algorithm is deterministic, and takes into account the experimental uncertainty in the measured points. Further, a procedure for using the track data to estimate the linear momenta of the charged particles observed in the detectors is included

Fluctuation analysis of relativistic nucleus-nucleus collisions in emulsion chambers

An analytical technique was developed for identifying enhanced fluctuations in the angular distributions of secondary particles produced from relativistic nucleus-nucleus collisions. The method is applied under the assumption that the masses of the produced particles are small compared to their linear momenta. The importance of particles rests in the fact that enhanced fluctuations in the rapidity distributions is considered to be an experimental signal for the creation of the quark-gluon-plasma (QGP), a state of nuclear matter predicted from the quantum chromodynamics theory (QCD). In the approach, Monte Carlo simulations are employed that make use of a portable random member generator that allow the calculations to be performed on a desk-top computer. The method is illustrated with data taken from high altitude emulsion exposures and is immediately applicable to similar data from accelerator-based emulsion exposures

The Host Galaxies of Type Ia Supernovae Discovered by the Palomar Transient Factory

We present spectroscopic observations of the host galaxies of 82 low-redshift type Ia supernovae (SNe Ia) discovered by the Palomar Transient Factory (PTF). We determine star-formation rates, gas-phase stellar metallicities, and stellar masses and ages of these objects. As expected, strong correlations between the SN Ia light-curve width (stretch) and the host age mass metallicity are found: fainter, faster-declining events tend to be hosted by older massive metal-rich galaxies. There is some evidence that redder SNe Ia explode in higher metallicity galaxies, but we found no relation between the SN colour and host galaxy extinction based on the Balmer decrement, suggesting that the colour variation of these SNe does not primarily arise from this source. SNe Ia in higher-mass metallicity galaxies also appear brighter after stretch colour corrections than their counterparts in lower mass hosts, and the stronger correlation is with gas-phase metallicity suggesting this may be the more important variable. We also compared the host stellar mass distribution to that in galaxy targeted SN surveys and the high-redshift untargeted Supernova Legacy Survey (SNLS). SNLS has many more low mass galaxies, while the targeted searches have fewer. This can be explained by an evolution in the galaxy stellar mass function, coupled with a SN delay-time distribution proportional to t1. Finally, we found no significant difference in the mass--metallicity relation of our SN Ia hosts compared to field galaxies, suggesting any metallicity effect on the SN Ia rate is small

Long-term ecological research in a human-dominated world

Author Posting. © American Institute of Biological Sciences, 2012. This article is posted here by permission of American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 62 (2012): 342-253, doi:10.1525/bio.2012.62.4.6.The US Long Term Ecological Research (LTER) Network enters its fourth decade with a distinguished record of achievement in ecological science. The value of long-term observations and experiments has never been more important for testing ecological theory and for addressing today's most difficult environmental challenges. The network's potential for tackling emergent continent-scale questions such as cryosphere loss and landscape change is becoming increasingly apparent on the basis of a capacity to combine long-term observations and experimental results with new observatory-based measurements, to study socioecological systems, to advance the use of environmental cyberinfrastructure, to promote environmental science literacy, and to engage with decisionmakers in framing major directions for research. The long-term context of network science, from understanding the past to forecasting the future, provides a valuable perspective for helping to solve many of the crucial environmental problems facing society today.2012-10-0

Individual variation in levels of haptoglobin-related protein in children from Gabon

Background: Haptoglobin related protein (Hpr) is a key component of trypanosome lytic factors (TLF), a subset of highdensity lipoproteins (HDL) that form the first line of human defence against African trypanosomes. Hpr, like haptoglobin (Hp) can bind to hemoglobin (Hb) and it is the Hpr-Hb complexes which bind to these parasites allowing uptake of TLF. This unique form of innate immunity is primate-specific. To date, there have been no population studies of plasma levels of Hpr, particularly in relation to hemolysis and a high prevalence of ahaptoglobinemia as found in malaria endemic areas. Methods and Principal Findings: We developed a specific enzyme-linked immunosorbent assay to measure levels of plasma Hpr in Gabonese children sampled during a period of seasonal malaria transmission when acute phase responses (APR), malaria infection and associated hemolysis were prevalent. Median Hpr concentration was 0.28 mg/ml (range 0.03-1.1). This was 5-fold higher than that found in Caucasian children (0.049 mg/ml, range 0.002-0.26) with no evidence of an APR. A general linear model was used to investigate associations between Hpr levels, host polymorphisms, parasitological factors and the acute phase proteins, Hp, C-reactive protein (CRP) and albumin. Levels of Hpr were associated with Hp genotype, decreased with age and were higher in females. Hpr concentration was strongly correlated with that of Hp, but not CRP

Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Hyperkalemia in People With Type 2 Diabetes: A Meta-Analysis of Individual Participant Data From Randomized, Controlled Trials

Background: Hyperkalemia increases risk of cardiac arrhythmias and death and limits the use of renin-angiotensin-aldosterone system (RAAS) inhibitors and mineralocorticoid receptor antagonists (MRAs), which improve clinical outcomes in people with chronic kidney disease (CKD) and/or systolic heart failure. Sodium-glucose cotransporter 2 (SGLT2) inhibitors reduce the risk of cardiorenal events in people with type 2 diabetes at high cardiovascular risk or with CKD. However, their effect on hyperkalemia has not been systematically evaluated. / Methods: A meta-analysis was conducted using individual participant data from randomized, double-blind, placebo-controlled clinical outcome trials with SGLT2 inhibitors in people with type 2 diabetes at high cardiovascular risk and/or with CKD, in which serum potassium levels were routinely measured. The primary outcome was time to serious hyperkalemia, defined as central laboratory determine serum potassium ≥6.0 mmol/L, with other outcomes including investigator-reported hyperkalemia events and hypokalemia (serum potassium ≤3.5 mmol/L). Cox regression analyses were performed to estimate treatment effects from each trial with hazards ratios (HR) and corresponding 95% CI pooled using random effects models to obtain summary treatment effects, overall and across key subgroups. / Results: Results from six trials were included comprising 49,875 participants assessing four SGLT2 inhibitors. 1,754 participants developed serious hyperkalemia and an additional 1,119 investigator-reported hyperkalemia events were recorded. SGLT2 inhibitors reduced the risk of serious hyperkalemia (HR 0.84, 95% CI 0.76-0.93), an effect consistent across studies (P-heterogeneity=0.71). The incidence of investigator-reported hyperkalemia was also lower with SGLT2 inhibitors (HR 0.80, 95% CI 0.68-0.93; P-heterogeneity=0.21). Reductions in serious hyperkalemia were observed across a range of subgroups including baseline kidney function, history of heart failure, RAAS inhibitor, diuretic and MRA use. SGLT2 inhibitors did not increase the risk of hypokalemia (HR 1.04, 95% CI 0.94-1.15; P-heterogeneity=0.42). / Conclusions: SGLT2 inhibitors reduce the risk of serious hyperkalemia in people with type 2 diabetes at high cardiovascular risk and/or with CKD, without increasing the risk of hypokalemia

Process-oriented analysis of dominant sources of uncertainty in the land carbon sink

The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO$_{2}$ and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO$_{2}$ (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink

Carbon budget for 1.5 and 2oC targets lowered by natural wetland and permafrost feedbacks

Methane emissions from natural wetlands and carbon release from permafrost thaw have a positive feedback on climate, yet are not represented in most state-of-the-art climate models. Furthermore, a fraction of the thawed permafrost carbon is released as methane, enhancing the combined feedback strength. We present simulations with an intermediate complexity climate model which follow prescribed global warming pathways to stabilisation at 1.5°C or 2.0°C above pre-industrial levels by the year 2100, and that incorporates a state-of-the-art global land surface model with updated descriptions of wetland and permafrost carbon release. We demonstrate that the climate feedbacks from those two processes are substantial. Specifically, permissible anthropogenic fossil fuel CO2 emission budgets are reduced by 17-23% (47-56 GtC) for stabilisation at 1.5°C, and 9-13% (52-57 GtC) for 2.0°C stabilisation. In our simulations these feedback processes respond faster at temperatures below 1.5°C, and the differences between the 1.5°C and 2°C targets are disproportionately small. This key finding is due to our interest in transient emission pathways to the year 2100 and does not consider the longer term implications of these feedback processes. We conclude that natural feedback processes from wetlands and permafrost must be considered in assessments of transient emission pathways to limit global warming

Quantum state preparation and macroscopic entanglement in gravitational-wave detectors

Long-baseline laser-interferometer gravitational-wave detectors are operating at a factor of 10 (in amplitude) above the standard quantum limit (SQL) within a broad frequency band. Such a low classical noise budget has already allowed the creation of a controlled 2.7 kg macroscopic oscillator with an effective eigenfrequency of 150 Hz and an occupation number of 200. This result, along with the prospect for further improvements, heralds the new possibility of experimentally probing macroscopic quantum mechanics (MQM) - quantum mechanical behavior of objects in the realm of everyday experience - using gravitational-wave detectors. In this paper, we provide the mathematical foundation for the first step of a MQM experiment: the preparation of a macroscopic test mass into a nearly minimum-Heisenberg-limited Gaussian quantum state, which is possible if the interferometer's classical noise beats the SQL in a broad frequency band. Our formalism, based on Wiener filtering, allows a straightforward conversion from the classical noise budget of a laser interferometer, in terms of noise spectra, into the strategy for quantum state preparation, and the quality of the prepared state. Using this formalism, we consider how Gaussian entanglement can be built among two macroscopic test masses, and the performance of the planned Advanced LIGO interferometers in quantum-state preparation