3,405 research outputs found
Beyond-one-loop quantum gravity action yielding both inflation and late-time acceleration
A unified description of early-time inflation with the current cosmic
acceleration is achieved by means of a new theory that uses a quadratic model
of gravity, with the inclusion of an exponential -gravity contribution
for dark energy. High-curvature corrections of the theory come from
higher-derivative quantum gravity and yield an effective action that goes
beyond the one-loop approximation. It is shown that, in this theory, viable
inflation emerges in a natural way, leading to a spectral index and
tensor-to-scalar ratio that are in perfect agreement with the most reliable
Planck results. At low energy, late-time accelerated expansion takes place. As
exponential gravity, for dark energy, must be stabilized during the matter and
radiation eras, we introduce a curing term in order to avoid nonphysical
singularities in the effective equation of state parameter. The results of our
analysis are confirmed by accurate numerical simulations, which show that our
model does fit the most recent cosmological data for dark energy very
precisely.Comment: 20 pages, to appear in NP
Black hole and de Sitter solutions in a covariant renormalizable field theory of gravity
It is shown that Schwarzschild black hole and de Sitter solutions exist as
exact solutions of a recently proposed relativistic covariant formulation of
(power-counting) renormalizable gravity with a fluid. The formulation without a
fluid is also presented here. The stability of the solutions is studied and
their corresponding entropies are computed, by using the covariant Wald method.
The area law is shown to hold both for the Schwarzschild and for the de Sitter
solutions found, confirming that, for the case, one is dealing with a
minimal modification of GR.Comment: 7 paages, latex fil
On the mass of atoms in molecules: Beyond the Born-Oppenheimer approximation
Describing the dynamics of nuclei in molecules requires a potential energy
surface, which is traditionally provided by the Born-Oppenheimer or adiabatic
approximation. However, we also need to assign masses to the nuclei. There, the
Born-Oppenheimer picture does not account for the inertia of the electrons and
only bare nuclear masses are considered. Nowadays, experimental accuracy
challenges the theoretical predictions of rotational and vibrational spectra
and requires to include the participation of electrons in the internal motion
of the molecule. More than 80 years after the original work of Born and
Oppenheimer, this issue still is not solved in general. Here, we present a
theoretical and numerical framework to address this problem in a general and
rigorous way. Starting from the exact factorization of the electron-nuclear
wave function, we include electronic effects beyond the Born-Oppenheimer regime
in a perturbative way via position-dependent corrections to the bare nuclear
masses. This maintains an adiabatic-like point of view: the nuclear degrees of
freedom feel the presence of the electrons via a single potential energy
surface, whereas the inertia of electrons is accounted for and the total mass
of the system is recovered. This constitutes a general framework for describing
the mass acquired by slow degrees of freedom due to the inertia of light,
bounded particles. We illustrate it with a model of proton transfer, where the
light particle is the proton, and with corrections to the vibrational spectra
of molecules. Inclusion of the light particle inertia allows to gain orders of
magnitude in accuracy
Deriving the respiratory sinus arrhythmia from the heartbeat time series using Empirical Mode Decomposition
Heart rate variability (HRV) is a well-known phenomenon whose characteristics
are of great clinical relevance in pathophysiologic investigations. In
particular, respiration is a powerful modulator of HRV contributing to the
oscillations at highest frequency. Like almost all natural phenomena, HRV is
the result of many nonlinearly interacting processes; therefore any linear
analysis has the potential risk of underestimating, or even missing, a great
amount of information content. Recently the technique of Empirical Mode
Decomposition (EMD) has been proposed as a new tool for the analysis of
nonlinear and nonstationary data. We applied EMD analysis to decompose the
heartbeat intervals series, derived from one electrocardiographic (ECG) signal
of 13 subjects, into their components in order to identify the modes associated
with breathing. After each decomposition the mode showing the highest frequency
and the corresponding respiratory signal were Hilbert transformed and the
instantaneous phases extracted were then compared. The results obtained
indicate a synchronization of order 1:1 between the two series proving the
existence of phase and frequency coupling between the component associated with
breathing and the respiratory signal itself in all subjects.Comment: 12 pages, 6 figures. Will be published on "Chaos, Solitons and
Fractals
Migration on request, a practical technique for preservation
Maintaining a digital object in a usable state over time is a crucial aspect of digital preservation. Existing methods of preserving have many drawbacks. This paper describes advanced techniques of data migration which can be used to support preservation more accurately and cost effectively.
To ensure that preserved works can be rendered on current computer systems over time, âtraditional migrationâ has been used to convert data into current formats. As the new format becomes obsolete another conversion is performed, etcetera. Traditional migration has many inherent problems as errors during transformation propagate throughout future transformations.
CAMiLEONâs software longevity principles can be applied to a migration strategy, offering improvements over traditional migration. This new approach is named âMigration on Request.â Migration on Request shifts the burden of preservation onto a single tool, which is maintained over time. Always returning to the original format enables potential errors to be significantly reduced
CTprintNet: An Accurate and Stable Deep Unfolding Approach for Few-View CT Reconstruction
In this paper, we propose a new deep learning approach based on unfolded neural networks for the reconstruction of X-ray computed tomography images from few views. We start from a model-based approach in a compressed sensing framework, described by the minimization of a least squares function plus an edge-preserving prior on the solution. In particular, the proposed network automatically estimates the internal parameters of a proximal interior point method for the solution of the optimization problem. The numerical tests performed on both a synthetic and a real dataset show the effectiveness of the framework in terms of accuracy and robustness with respect to noise on the input sinogram when compared to other different data-driven approaches
Effects of indenter geometry on microâscale fracture toughness measurement by Pillar splitting
In this presentation, we will show the improvements to a recently developed pillar splitting technique that can be used to characterize the fracture toughness of materials at the micrometer scale. Micro-pillars with different aspect ratios were milled from bulk Si (100) and TiN and CrN thin films, and pillar splitting tests were carried out using four different triangular pyramidal indenters with centerline-to-face angles varying from 35.3° to 65.3°. Cohesive zone finite element modelling (CZ-FEM) was to evaluate the effect of different material parameters and indenter geometries on the splitting behavior. Pillar splitting experiments revealed a linear relationship between the splitting load and the indenter angle, while CZ-FEM simulations provided the dimensionless coefficients needed to estimate the fracture toughness from the splitting load. The results provide novel insights into the fracture toughness of small-scale materials using the pillar spitting technique and provide a simple and reliable way to measure fracture toughness over a broad range of material properties.
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MicroRNA profiling in sera of patients with type 2 diabetes mellitus reveals an upregulation of miR-31 expression in subjects with microvascular complications
Type 2 diabetes (T2D) is a metabolic disease characterized by chronic hyperglycaemia due to a combination of resistance to insulin action and an inadequate compensatory insulin secretory response. Chronic hyperglycemia is associated with long-term micro- and macrovascular complications leading to dysfunction of several organs including kidney, heart, eye and nervous system. Early identification of chronic diabetic complications is necessary in order to prevent dysfunction and failure of these different organs. MicroRNAs (or miRNAs) are small endogenous RNAs, which negatively regulate gene expression. Recently, it has been demonstrated that miRNAs can be secreted by cells, thus being detectable in serum and in other biological fluids. Circulating microRNAs have been proposed as possible biomarkers of several diseases. Here, we performed a miRNAs expression profiling in the sera of T2D patients with or without vascular complications in order to find specific biomarkers to characterize T2D complications. We analyzed the expression of 384 microRNAs in serum pools from 3 groups of T2D patients: 12 T2D patients without any chronic complications, 12 T2D patients with macrovascular complications and 12 with microvascular complications. We found 223 miRNAs expressed in T2D,224 inT2D with microvascular and221 inT2D with macrovascular complications. Among expressed microRNAs, 45 resulted upregulated and 23 downregulated in microvascular patients sera, while 13 upregulated and 41 downregulated in macrovascular T2D patients compared to those without complications. We focused and validated microRNA miR-31 expression in single sera from each group, which resulted significantly upregulated in patients with microvascular complications and may be indeed related to the presence of microangiopathy. In conclusion, our study has identified miR-31 as a promising biomarker for diabetic microvascular complications; further prospective studies in the clinical setting are however required to establish the real utility of measuring serum circulating levels of this microRNA
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