Borel singularities at small x

D.I.S. at small Bjorken $x$ is considered within the dipole cascade formalism. The running coupling in impact parameter space is introduced in order to parametrize effects that arise from emission of large size dipoles. This results in a new evolution equation for the dipole cascade. Strong coupling effects are analyzed after transforming the evolution equation in Borel ($b$) space. The Borel singularities of the solution are discussed first for the universal part of the dipole cascade and then for the specific process of D.I.S. at small $x$. In the latter case the leading infrared renormalon is at $b=1/\beta_0$ indicating the presence of $1/Q^2$ power corrections for the small-$x$ structure functions.Comment: 5 pages, Latex (Talk presented at DIS'97, Chicago, IL

Seasonality in consumption: An economic analysis of the alimentary patterns in Greece (1957-2005)

This paper attempts to explore financial expenditure of households in post-war Greece (1957-2005) in our endeavour to describe annual seasonality patterns of food consumption. Agricultural/industrial, animal/plant-based, in-house/away-from-home alimentation features are examined in an effort to understand and qualitatively categorise the evolution and progression of food consumption over time. Our analysis is performed presenting descriptive statistics and data gathered from the "Household Budget Surveys" (H.B.S.) of the National Statistical Service of Greece (E.S.Y.E)

Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution

In this work, we investigate the value of uncertainty modeling in 3D super-resolution with convolutional neural networks (CNNs). Deep learning has shown success in a plethora of medical image transformation problems, such as super-resolution (SR) and image synthesis. However, the highly ill-posed nature of such problems results in inevitable ambiguity in the learning of networks. We propose to account for intrinsic uncertainty through a per-patch heteroscedastic noise model and for parameter uncertainty through approximate Bayesian inference in the form of variational dropout. We show that the combined benefits of both lead to the state-of-the-art performance SR of diffusion MR brain images in terms of errors compared to ground truth. We further show that the reduced error scores produce tangible benefits in downstream tractography. In addition, the probabilistic nature of the methods naturally confers a mechanism to quantify uncertainty over the super-resolved output. We demonstrate through experiments on both healthy and pathological brains the potential utility of such an uncertainty measure in the risk assessment of the super-resolved images for subsequent clinical use.Comment: Accepted paper at MICCAI 201

Automatic, fast and robust characterization of noise distributions for diffusion MRI

Knowledge of the noise distribution in magnitude diffusion MRI images is the centerpiece to quantify uncertainties arising from the acquisition process. The use of parallel imaging methods, the number of receiver coils and imaging filters applied by the scanner, amongst other factors, dictate the resulting signal distribution. Accurate estimation beyond textbook Rician or noncentral chi distributions often requires information about the acquisition process (e.g. coils sensitivity maps or reconstruction coefficients), which is not usually available. We introduce a new method where a change of variable naturally gives rise to a particular form of the gamma distribution for background signals. The first moments and maximum likelihood estimators of this gamma distribution explicitly depend on the number of coils, making it possible to estimate all unknown parameters using only the magnitude data. A rejection step is used to make the method automatic and robust to artifacts. Experiments on synthetic datasets show that the proposed method can reliably estimate both the degrees of freedom and the standard deviation. The worst case errors range from below 2% (spatially uniform noise) to approximately 10% (spatially variable noise). Repeated acquisitions of in vivo datasets show that the estimated parameters are stable and have lower variances than compared methods.Comment: v2: added publisher DOI statement, fixed text typo in appendix A

RubiX: combining spatial resolutions for Bayesian inference of crossing fibers in diffusion MRI

The trade-off between signal-to-noise ratio (SNR) and spatial specificity governs the choice of spatial resolution in magnetic resonance imaging (MRI); diffusion-weighted (DW) MRI is no exception. Images of lower resolution have higher signal to noise ratio, but also more partial volume artifacts. We present a data-fusion approach for tackling this trade-off by combining DW MRI data acquired both at high and low spatial resolution. We combine all data into a single Bayesian model to estimate the underlying fiber patterns and diffusion parameters. The proposed model, therefore, combines the benefits of each acquisition. We show that fiber crossings at the highest spatial resolution can be inferred more robustly and accurately using such a model compared to a simpler model that operates only on high-resolution data, when both approaches are matched for acquisition time

Jumping Ability, Reactive Strength and Anthropometric Characteristics of Elite Junior Women Volleyball Players

Body size and dimensions, in conjunction with jumping ability, may constitute critical components for successful performance in Volleyball. The purpose of this study was: to measure a number of anthropome- tric characteristics and vertical jump performance of elite youth women volleyball players, from the national teams of the Balkan countries, and make comparisons based on nationality and players positions. The sam- ple consisted of eighty six athletes (age: 15.5–18.5 years) from Greece (GR, n=21), Bulgaria (BU, n=20), Serbia (SER, n=11), Moldavia (MOL, n= 9), Turkey (TUR, n=12) and Romania (RO, n=13), distributed also as setters (n=14), outside hitters (n=31), universals (n=12), middle blockers (n=22) and liberos (n=7). The subjects were measured for body height, body mass, body mass index (BMI) and body fat percentage and performed four types of vertical jump; a squat jump initiated from a knee flexion of 90o, a counter-movement jump, a coun- ter-movement jump with arm swing and a drop jump from a dropping height of 40 cm from which reactive strength was also calculated. According to the results, GR and RO had higher body fat percentage than MOL and BU (p<.05). Middle blockers were taller than the setters, the outside hitters and the liberos (p<.01). Uni- versals were taller than the setters and the liberos (p<.01) and the outside hitters than the liberos (p<.01). No differences were observed in BMI between the players and the teams (p>.05), though middle blockers had higher body mass than the setters, the outside hitters and the liberos (p<.05). In squat jump, counter move- ment jump and drop jump TUR had higher values than GR and BU (p<.05). In counter-movement jump with arm swing, TUR had also higher values than GR, BU and MOL (p<.05). Furthermore, TUR and SER had higher reactive strength values than GR and BU (p<.05) and TUR had also higher values than RO (p<.05). The evaluation of the physical characteristics and capacities provide the coaches useful information about the selection and development of young athletes as well as the effectiveness of the training programs

The amyloidogenic potential and behavioral correlates of stress

Observations of elevated basal cortisol levels in Alzheimer's disease (AD) patients prompted the hypothesis that stress and glucocorticoids (GC) may contribute to the development and/or maintenance of AD. Consistent with that hypothesis, we show that stress and GC provoke misprocessing of amyloid precursor peptide in the rat hippocampus and prefrontal cortex, resulting in increased levels of the peptide C-terminal fragment 99 (C99), whose further proteolytic cleavage results in the generation of amyloid-beta (Abeta). We also show that exogenous Abeta can reproduce the effects of stress and GC on C99 production and that a history of stress strikingly potentiates the C99-inducing effects of Abeta and GC. Previous work has indicated a role for Abeta in disruption of synaptic function and cognitive behaviors, and AD patients reportedly show signs of heightened anxiety. Here, behavioral analysis revealed that like stress and GC, Abeta administration causes spatial memory deficits that are exacerbated by stress and GC; additionally, Abeta, stress and GC induced a state of hyperanxiety. Given that the intrinsic properties of C99 and Abeta include neuroendangerment and behavioral impairment, our findings suggest a causal role for stress and GC in the etiopathogenesis of AD, and demonstrate that stressful life events and GC therapy can have a cumulative impact on the course of AD development and progression.CC and IS were supported by stipends from the Max Planck Society and EU Marie Curie Training Fellowships (at University College London, UK). The collaboration between the German and Portuguese laboratories was supported through the German–Portuguese Luso-Alemas Program (DAAD/GRICES). This study was conducted within the framework of the EU-supported integrated project ‘CRESCENDO’ (Contract FP6-018652)