Entanglement and non-locality are different resources

Bell's theorem states that, to simulate the correlations created by measurement on pure entangled quantum states, shared randomness is not enough: some "non-local" resources are required. It has been demonstrated recently that all projective measurements on the maximally entangled state of two qubits can be simulated with a single use of a "non-local machine". We prove that a strictly larger amount of this non-local resource is required for the simulation of pure non-maximally entangled states of two qubits $\ket{\psi(\alpha)}= \cos\alpha\ket{00}+\sin\alpha\ket{11}$ with $0<\alpha\lesssim\frac{\pi}{7.8}$.Comment: 8 pages, 3 figure

On the relationship between stomatal characters and atmospheric CO2

Leaf stomatal characters influence the response of terrestrial evapotranspiration to climate change and are used as proxies for the reconstruction of past atmospheric [CO2]. We examined the phenotypic response of stomatal index (SI), density (SD) and aperture (AP) to rising atmospheric CO2 in 15 species after four years exposure to a field CO2 gradient (200 to 550 μmol mol−1 atmospheric [CO2]) or at three Free Air CO2 Enrichment (FACE) sites. Along the CO2 gradient, SI and SD showed no evidence of a decline to increasing [CO2], while AP decreased slightly. There was no significant change in SI, SD or AP with CO2 across FACE experiments. Without evolutionary changes, SI and SD may not respond to atmospheric [CO2] in the field and are unlikely to decrease in a future high CO2 world

Oak forest carbon and water simulations:Model intercomparisons and evaluations against independent data

Models represent our primary method for integration of small-scale, process-level phenomena into a comprehensive description of forest-stand or ecosystem function. They also represent a key method for testing hypotheses about the response of forest ecosystems to multiple changing environmental conditions. This paper describes the evaluation of 13 stand-level models varying in their spatial, mechanistic, and temporal complexity for their ability to capture intra- and interannual components of the water and carbon cycle for an upland, oak-dominated forest of eastern Tennessee. Comparisons between model simulations and observations were conducted for hourly, daily, and annual time steps. Data for the comparisons were obtained from a wide range of methods including: eddy covariance, sapflow, chamber-based soil respiration, biometric estimates of stand-level net primary production and growth, and soil water content by time or frequency domain reflectometry. Response surfaces of carbon and water flux as a function of environmental drivers, and a variety of goodness-of-fit statistics (bias, absolute bias, and model efficiency) were used to judge model performance. A single model did not consistently perform the best at all time steps or for all variables considered. Intermodel comparisons showed good agreement for water cycle fluxes, but considerable disagreement among models for predicted carbon fluxes. The mean of all model outputs, however, was nearly always the best fit to the observations. Not surprisingly, models missing key forest components or processes, such as roots or modeled soil water content, were unable to provide accurate predictions of ecosystem responses to short-term drought phenomenon. Nevertheless, an inability to correctly capture short-term physiological processes under drought was not necessarily an indicator of poor annual water and carbon budget simulations. This is possible because droughts in the subject ecosystem were of short duration and therefore had a small cumulative impact. Models using hourly time steps and detailed mechanistic processes, and having a realistic spatial representation of the forest ecosystem provided the best predictions of observed data. Predictive ability of all models deteriorated under drought conditions, suggesting that further work is needed to evaluate and improve ecosystem model performance under unusual conditions, such as drought, that are a common focus of environmental change discussions

Modeling anaerobic soil organic carbon decomposition in Arctic polygon tundra: insights into soil geochemical influences on carbon mineralization

Rapid warming of Arctic ecosystems exposes soil organic matter (SOM) to accelerated microbial decomposition, potentially leading to increased emissions of carbon dioxide (CO2) and methane (CH4) that have a positive feedback on global warming. Current estimates of the magnitude and form of carbon emissions from Earth system models include significant uncertainties, partially due to the oversimplified representation of geochemical constraints on microbial decomposition. Here, we coupled modeling principles developed in different disciplines, including a thermodynamically based microbial growth model for methanogenesis and iron reduction, a pool-based model to represent upstream carbon transformations, and a humic ion-binding model for dynamic pH simulation to build a more versatile carbon decomposition model framework that can be applied to soils under varying redox conditions. This new model framework was parameterized and validated using synthesized anaerobic incubation data from permafrost-affected soils along a gradient of fine-scale thermal and hydrological variabilities across Arctic polygonal tundra. The model accurately simulated anaerobic CO2 production and its temperature sensitivity using data on labile carbon pools and fermentation rates as model constraints. CH4 production is strongly influenced by water content, pH, methanogen biomass, and presence of competing electron acceptors, resulting in high variability in its temperature sensitivity. This work provides new insights into the interactions of SOM pools, temperature increase, soil geochemical feedbacks, and resulting CO2 and CH4 production. The proposed anaerobic carbon decomposition framework presented here builds a mechanistic link between soil geochemistry and carbon mineralization, making it applicable over a wide range of soils under different environmental settings.</p

Evaluation of mTOR-regulated mRNA translation.

mTOR, the mammalian target of rapamycin, regulates protein synthesis (mRNA translation) by affecting the phosphorylation or activity of several translation factors. Here, we describe methods for studying the impact of mTOR signalling on protein synthesis, using inhibitors of mTOR such as rapamycin (which impairs some of its functions) or mTOR kinase inhibitors (which probably block all functions).To assess effects of mTOR inhibition on general protein synthesis in cells, the incorporation of radiolabelled amino acids into protein is measured. This does not yield information on the effects of mTOR on the synthesis of specific proteins. To do this, two methods are described. In one, stable-isotope labelled amino acids are used, and their incorporation into new proteins is determined using mass spectrometric methods. The proportions of labelled vs. unlabeled versions of each peptide from a given protein provide quantitative information about the rate of that protein's synthesis under different conditions. Actively translated mRNAs are associated with ribosomes in polyribosomes (polysomes); thus, examining which mRNAs are found in polysomes under different conditions provides information on the translation of specific mRNAs under different conditions. A method for the separation of polysomes from non-polysomal mRNAs is describe

Effects of acid deposition on calcium nutrition and health of Southern Appalachian spruce fir forests

The role of acid deposition in the health of spruce fir forests in the Southern Appalachian Mountains has been investigated by a wide variety of experimental approaches during the past 10 years. These studies have proceeded from initial dendroecological documentation of altered growth patterns of mature trees to increasingly more focused ecophysiological research on the causes and characteristics of changes in system function associated with increased acidic deposition. Field studies across gradients in deposition and soil chemistry have been located on four mountains spanning 85 km of latitude within the Southern Appalachians. The conclusion that calcium nutrition is an important component regulating health of red spruce in the Southern Appalachians and that acid deposition significantly reduces calcium availability in several ways has emerged as a consistent result from multiple lines or research. These have included analysis of trends in wood chemistry, soil solution chemistry, foliar nutrition, gas exchange physiology, root histochemistry, and controlled laboratory and field studies in which acid deposition and/or calcium nutrition has been manipulated and growth and nutritional status of saplings or mature red spruce trees measured. This earlier research has led us to investigate the broader implications and consequences of calcium deficiency for changing resistance of spruce-fir forests to natural stresses. Current research is exploring possible relationships between altered calcium nutrition and shifts in response of Fraser fir to insect attack by the balsam wooly adelgid. In addition, changes in wood ultrastructural properties in relation to altered wood chemistry is being examined to evaluate its possible role in canopy deterioration, under wind and ice stresses typical of high elevation forests

Spatially resolved spectroscopy of monolayer graphene on SiO2

We have carried out scanning tunneling spectroscopy measurements on exfoliated monolayer graphene on SiO$_2$ to probe the correlation between its electronic and structural properties. Maps of the local density of states are characterized by electron and hole puddles that arise due to long range intravalley scattering from intrinsic ripples in graphene and random charged impurities. At low energy, we observe short range intervalley scattering which we attribute to lattice defects. Our results demonstrate that the electronic properties of graphene are influenced by intrinsic ripples, defects and the underlying SiO$_2$ substrate.Comment: 6 pages, 7 figures, extended versio

Bispecific PD1-IL2v and anti-PD-L1 break tumor immunity resistance by enhancing stem-like tumor-reactive CD8⁺ T cells and reprogramming macrophages.

Immunotherapies have shown remarkable, albeit tumor-selective, therapeutic benefits in the clinic. Most patients respond transiently at best, highlighting the importance of understanding mechanisms underlying resistance. Herein, we evaluated the effects of the engineered immunocytokine PD1-IL2v in a mouse model of de novo pancreatic neuroendocrine cancer that is resistant to checkpoint and other immunotherapies. PD1-IL2v utilizes anti-PD-1 as a targeting moiety fused to an immuno-stimulatory IL-2 cytokine variant (IL2v) to precisely deliver IL2v to PD-1 &lt;sup&gt;+&lt;/sup&gt; T cells in the tumor microenvironment. PD1-IL2v elicited substantial infiltration by stem-like CD8 &lt;sup&gt;+&lt;/sup&gt; T cells, resulting in tumor regression and enhanced survival in mice. Combining anti-PD-L1 with PD1-IL2v sustained the response phase, improving therapeutic efficacy both by reprogramming immunosuppressive tumor-associated macrophages and enhancing T cell receptor (TCR) immune repertoire diversity. These data provide a rationale for clinical trials to evaluate the combination therapy of PD1-IL2v and anti-PD-L1, particularly in immunotherapy-resistant tumors infiltrated with PD-1 &lt;sup&gt;+&lt;/sup&gt; stem-like T cells

Entropy in general physical theories

Information plays an important role in our understanding of the physical world. We hence propose an entropic measure of information for any physical theory that admits systems, states and measurements. In the quantum and classical world, our measure reduces to the von Neumann and Shannon entropy respectively. It can even be used in a quantum or classical setting where we are only allowed to perform a limited set of operations. In a world that admits superstrong correlations in the form of non-local boxes, our measure can be used to analyze protocols such as superstrong random access encodings and the violation of `information causality'. However, we also show that in such a world no entropic measure can exhibit all properties we commonly accept in a quantum setting. For example, there exists no`reasonable' measure of conditional entropy that is subadditive. Finally, we prove a coding theorem for some theories that is analogous to the quantum and classical setting, providing us with an appealing operational interpretation.Comment: 20 pages, revtex, 7 figures, v2: Coding theorem revised, published versio

Composability in quantum cryptography

In this article, we review several aspects of composability in the context of quantum cryptography. The first part is devoted to key distribution. We discuss the security criteria that a quantum key distribution protocol must fulfill to allow its safe use within a larger security application (e.g., for secure message transmission). To illustrate the practical use of composability, we show how to generate a continuous key stream by sequentially composing rounds of a quantum key distribution protocol. In a second part, we take a more general point of view, which is necessary for the study of cryptographic situations involving, for example, mutually distrustful parties. We explain the universal composability framework and state the composition theorem which guarantees that secure protocols can securely be composed to larger applicationsComment: 18 pages, 2 figure