1,369 research outputs found
Disorder effects in the quantum Heisenberg model: An Extended Dynamical mean-field theory analysis
We investigate a quantum Heisenberg model with both antiferromagnetic and
disordered nearest-neighbor couplings. We use an extended dynamical mean-field
approach, which reduces the lattice problem to a self-consistent local impurity
problem that we solve by using a quantum Monte Carlo algorithm. We consider
both two- and three-dimensional antiferromagnetic spin fluctuations and
systematically analyze the effect of disorder. We find that in three dimensions
for any small amount of disorder a spin-glass phase is realized. In two
dimensions, while clean systems display the properties of a highly correlated
spin-liquid (where the local spin susceptibility has a non-integer power-low
frequency and/or temperature dependence), in the present case this behavior is
more elusive unless disorder is very small. This is because the spin-glass
transition temperature leaves only an intermediate temperature regime where the
system can display the spin-liquid behavior, which turns out to be more
apparent in the static than in the dynamical susceptibility.Comment: 15 pages, 7 figure
Study of the Boson Peak and Fragility of Bioprotectant Glass-Forming Mixtures by Neutron Scattering
The biological relevance of trehalose, glycerol, and their mixtures in several anhydrobiotic and cryobiotic organisms has recently promoted both experimental and simulation studies. In addition, these systems are employed in different industrial fields, such as pharmaceutical and cosmetic industries, as additives in mixtures for cryopreservation and in several formulations. This review article shows an overview of Inelastic Neutron Scattering (INS) data, collected at different temperature values by the OSIRIS time-of-flight spectrometer at the ISIS Facility (Rutherford Appleton Laboratory, Oxford, UK) and by the IN4 and IN6 spectrometers at the Institut Laue Langevin (ILL, Grenoble, France), on trehalose/glycerol mixtures as a function of the glycerol content. The data analysis allows determining the Boson peak behavior and discussing the findings in terms of fragility in relation to the bioprotective action of trehalose and glycerol
IXIAM: ISA EXtension for Integrated Accelerator Management
During the last few years, hardware accelerators have been gaining popularity thanks to their ability to achieve higher performance and efficiency than classic general-purpose solutions. They are fundamentally shaping the current generations of Systems-on-Chip (SoCs), which are becoming increasingly heterogeneous. However, despite their widespread use, a standard, general solution to manage them while providing speed and consistency has not yet been found. Common methodologies rely on OS mediation and a mix of user-space and kernel-space drivers, which can be inefficient, especially for fine-grained tasks. This paper addresses these sources of inefficiencies by proposing an ISA eXtension for Integrated Accelerator Management (IXIAM), a cost-effective HW-SW framework to control a wide variety of accelerators in a standard way, and directly from the cores. The proposed instructions include reservation, work offloading, data transfer, and synchronization. They can be wrapped in a high-level software API or even integrated into a compiler. IXIAM features also a user-space interrupt mechanism to signal events directly to the user process. We implement it as a RISC-V extension in the gem5 simulator and demonstrate detailed support for complex accelerators, as well as the ability to specify sequences of memory transfers and computations directly from the ISA and with significantly lower overhead than driver-based schemes. IXIAM provides a performance advantage that is more evident for small and medium workloads, reaching around 90x in the best case. This way, we enlarge the set of workloads that would benefit from hardware acceleration
Intrinsic susceptibility and bond defects in the novel 2D frustrated antiferromagnet BaSnZnCrGaO
We present microscopic and macroscopic magnetic properties of the highly
frustrated antiferromagnet BaSnZnCrGaO,
respectively probed with NMR and SQUID experiments. The -variation of the
intrinsic susceptibility of the Cr frustrated kagom\'{e} bilayer,
, displays a maximum around 45 K. The dilution of the magnetic
lattice has been studied in detail for . Novel dilution
independent defects, likely related with magnetic bond disorder, are evidenced
and discussed. We compare our results to SrCrGaO. Both
bond defects and spin vacancies do not affect the average susceptibility of the
kagom\'{e} bilayers.Comment: Published in Phys. Rev. Lett. 92, 217202 (2004). Only minor changes
as compared to previous version. 4 pages, 4 figure
Molecular Deuterion crystallitation under cuasi-1D confienment
ECNS 2015, Zaragoza (Spain), August 30th-September 4th 2015A particularly interesting aspect of Carbon Nanotubes is their use as nearly one-dimensional nano-containers. Apart of their possibilities for controlled chemistry in nano- fluidics devices new phenomena induced by confinement are also expected, such as liquid like ordered structures or exotic crystalline phases. Here, we present a series of neutron diffraction measurements (instrument D20, ILL, Grenoble) of molecular deuterium confined within Multiple Wall Carbon Nanotubes (MWCTNs). Bulk liquid D2 at its vapour pressure crystallises in an hcp structure at ~18.7 K. At low uptakes we have found a clear depression of the solidification temperature down to ~13.25 K. Interestingly, at the lowest uptake the diffraction pattern is consistent with the minimal fcc lattice compatible with a cylindrical symmetry.Peer Reviewe
Collective excitations in liquid D2 confined within the mesoscopic pores of a MCM-41 molecular sieve
We present a comparative study of the excitations in bulk and liquid D2
confined within the pores of MCM-41. The material (Mobile Crystalline
Material-41) is a silicate obtained by means of a template that yields a
partially crystalline structure composed by arrays of nonintersecting hexagonal
channels of controlled width having walls made of amorphous SiO2. Its porosity
was characterized by means of adsorption isotherms and found to be composed by
a regular array of pores having a narrow distribution of sizes with a most
probable value of 2.45 nm. The assessment of the precise location of the sample
within the pores is carried out by means of pressure isotherms. The study was
conducted at two pressures which correspond to pore fillings above the
capillary condensation regime. Within the range of wave vectors where
collective excitations can be followed up (0.3<Q<3.0 −1), we found
confinement brings forward a large shortening of the excitation lifetimes that
shifts the characteristic frequencies to higher energies. In addition, the
coherent quasielastic scattering shows signatures of reduced diffusivity.Comment: 6 page
White matter integrity as a predictor of response to treatment in first episode psychosis
The integrity of brain white matter connections is central to a patient's ability to respond to pharmacological interventions. This study tested this hypothesis using a specific measure of white matter integrity, and examining its relationship to treatment response using a prospective design in patients within their first episode of psychosis. Diffusion tensor imaging data were acquired in 63 patients with first episode psychosis and 52 healthy control subjects (baseline). Response was assessed after 12 weeks and patients were classified as responders or non-responders according to treatment outcome. At this second time-point, they also underwent a second diffusion tensor imaging scan. Tract-based spatial statistics were used to assess fractional anisotropy as a marker of white matter integrity. At baseline, non-responders showed lower fractional anisotropy than both responders and healthy control subjects (P < 0.05; family-wise error-corrected), mainly in the uncinate, cingulum and corpus callosum, whereas responders were indistinguishable from healthy control subjects. After 12 weeks, there was an increase in fractional anisotropy in both responders and non-responders, positively correlated with antipsychotic exposure. This represents one of the largest, controlled investigations of white matter integrity and response to antipsychotic treatment early in psychosis. These data, together with earlier findings on cortical grey matter, suggest that grey and white matter integrity at the start of treatment is an important moderator of response to antipsychotics. These findings can inform patient stratification to anticipate care needs, and raise the possibility that antipsychotics may restore white matter integrity as part of the therapeutic response
BioWorkbench: A High-Performance Framework for Managing and Analyzing Bioinformatics Experiments
Advances in sequencing techniques have led to exponential growth in
biological data, demanding the development of large-scale bioinformatics
experiments. Because these experiments are computation- and data-intensive,
they require high-performance computing (HPC) techniques and can benefit from
specialized technologies such as Scientific Workflow Management Systems (SWfMS)
and databases. In this work, we present BioWorkbench, a framework for managing
and analyzing bioinformatics experiments. This framework automatically collects
provenance data, including both performance data from workflow execution and
data from the scientific domain of the workflow application. Provenance data
can be analyzed through a web application that abstracts a set of queries to
the provenance database, simplifying access to provenance information. We
evaluate BioWorkbench using three case studies: SwiftPhylo, a phylogenetic tree
assembly workflow; SwiftGECKO, a comparative genomics workflow; and RASflow, a
RASopathy analysis workflow. We analyze each workflow from both computational
and scientific domain perspectives, by using queries to a provenance and
annotation database. Some of these queries are available as a pre-built feature
of the BioWorkbench web application. Through the provenance data, we show that
the framework is scalable and achieves high-performance, reducing up to 98% of
the case studies execution time. We also show how the application of machine
learning techniques can enrich the analysis process
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