4,675 research outputs found
The determination of the ground-state energy of an antiferromagnetic lattice by means of a renormalization procedure
An approximate value for the ground-state energy of an antiferromagnetic lattice of spins one-half is determined by means of a repeated renormalization procedure in which the lattice is divided into cells with an effective interaction. This effective interaction is determined on the basis of the spin-hamiltonian formalism
Large inverse tunneling magnetoresistance in CoCrFeAl/MgO/CoFe magnetic tunnel junctions
Magnetic tunnel junctions with the layer sequence
CoCrFeAl/MgO/CoFe were fabricated by magnetron sputtering
at room temperature (RT). The samples exhibit a large inverse tunneling
magnetoresistance (TMR) effect of up to -66% at RT. The largest value of -84%
at 20 K reflects a rather weak influence of temperature. The dependence on the
voltage drop shows an unusual behavior with two almost symmetric peaks at
mV with large inverse TMR ratios and small positive values around zero
bias
Structural and magneto-transport characterization of Co_2Cr_xFe_(1-x)Al Heusler alloy films
We investigate the structure and magneto-transport properties of thin films
of the Co_2Cr_xFe_(1-x)Al full-Heusler compound, which is predicted to be a
half-metal by first-principles theoretical calculations. Thin films are
deposited by magnetron sputtering at room temperature on various substrates in
order to tune the growth from polycrystalline on thermally oxidized Si
substrates to highly textured and even epitaxial on MgO(001) substrates,
respectively. Our Heusler films are magnetically very soft and ferromagnetic
with Curie temperatures up to 630 K. The total magnetic moment is reduced
compared to the theoretical bulk value, but still comparable to values reported
for films grown at elevated temperature. Polycrystalline Heusler films combined
with MgO barriers are incorporated into magnetic tunnel junctions and yield 37%
magnetoresistance at room temperature
Roofline-aware DVFS for GPUs
Graphics processing units (GPUs) are becoming increasingly popular for compute workloads, mainly because of their large number of processing elements and high-bandwidth to off-chip memory. The roofline model captures the ratio between the two (the compute-memory ratio), an important architectural parameter. This work proposes to change the compute-memory ratio dynamically, scaling the voltage and frequency (DVFS) of 1) memory for compute-intensive workloads and 2) processing elements for memory-intensive workloads. The result is an adaptive roofline-aware GPU that increases energy efficiency (up to 58%) while maintaining performance
A study of the potential of locality-aware thread scheduling for GPUs
Programming models such as CUDA and OpenCL allow the programmer to specify the independence of threads, effectively removing ordering constraints. Still, parallel architectures such as the graphics processing unit (GPU) do not exploit the potential of data-locality enabled by this independence. Therefore, programmers are required to manually perform data-locality optimisations such as memory coalescing or loop tiling. This work makes a case for locality-aware thread scheduling: re-ordering threads automatically for better locality to improve the programmability of multi-threaded processors. In particular, we analyse the potential of locality-aware thread scheduling for GPUs, considering among others cache performance, memory coalescing and bank locality. This work does not present an implementation of a locality-aware thread scheduler, but rather introduces the concept and identifies the potential. We conclude that non-optimised programs have the potential to achieve good cache and memory utilisation when using a smarter thread scheduler. A case-study of a naive matrix multiplication shows for example a 87% performance increase, leading to an IPC of 457 on a 512-core GPU
Literature Review: Justice in South Sudan
Effective Protection of Fundamental Rights in a pluralist worl
High dissimilarity within a multiyear annual record of pollen assemblages from a North American tallgrass prairie
Citation: Commerford, J. L., McLauchlan, K. K., & Minckley, T. A. (2016). High dissimilarity within a multiyear annual record of pollen assemblages from a North American tallgrass prairie. Ecology and Evolution, 6(15), 5273-5289. doi:10.1002/ece3.2259Grassland vegetation varies in composition across North America and has been historically influenced by multiple biotic and abiotic drivers, including fire, herbivory, and topography. Yet, the amount of temporal and spatial variability exhibited among grassland pollen assemblages, and the influence of these biotic and abiotic drivers on pollen assemblage composition and diversity has been relatively understudied. Here, we examine 4 years of modern pollen assemblages collected from a series of 28 traps at the Konza Prairie Long-Term Ecological Research Area in the Flint Hills of Kansas, with the aim of evaluating the influence of these drivers, as well as quantifying the amount of spatial and temporal variability in the pollen signatures of the tallgrass prairie biome. We include all terrestrial pollen taxa in our analyses while calculating four summative metrics of pollen diversity and composition -beta-diversity, Shannon index, nonarboreal pollen percentage, and Ambrosia: Artemisia -and find different roles of fire, herbivory, and topography variables in relation to these pollen metrics. In addition, we find significant annual differences in the means of three of these metrics, particularly the year 2013 which experienced high precipitation relative to the other 3 years of data. To quantify spatial and temporal dissimilarity among the samples over the 4-year study, we calculate pairwise squared-chord distances (SCD). The SCD values indicate higher compositional dissimilarity across the traps (0.38 mean) among all years than within a single trap from year to year (0.31 mean), suggesting that grassland vegetation can have different pollen signatures across finely sampled space and time, and emphasizing the need for additional long-term annual monitoring of grassland pollen
Predicting changes in ecosystem functioning from shifts in plant traits
Contains fulltext :
135500.pdf (publisher's version ) (Open Access
On the role of the cellular prion protein in the uptake and signaling of pathological aggregates in neurodegenerative diseases
Neurodegenerative disorders are associated with intra- or extra-cellular deposition of aggregates of misfolded insoluble proteins. These deposits composed of tau, amyloid-\u3b2 or \u3b1-synuclein spread from cell to cell, in a prion-like manner. Novel evidence suggests that the circulating soluble oligomeric species of these misfolded proteins could play a major role in pathology, while insoluble aggregates would represent their protective less toxic counterparts. Recent convincing data support the proposition that the cellular prion protein, PrPC, act as a toxicity-inducing receptor for amyloid-\u3b2 oligomers. As a consequence, several studies focused their investigations to the role played by PrPC in binding other protein aggregates, such as tau and \u3b1-synuclein, for its possible common role in mediating toxic signalling. The biological relevance of PrPC as key ligand and potential mediator of toxicity for multiple proteinaceous aggregated species, prions or PrPSc included, could lead to relevant therapeutic implications. Here we describe the structure of PrPC and the proposed interplay with its pathological counterpart PrPSc and then we recapitulate the most recent findings regarding the role of PrPC in the interaction with aggregated forms of other neurodegeneration-associated proteins
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