Dimer percolation and jamming on simple cubic lattice

We consider site percolation of dimers (``neadles'') on simple cubic lattice. The percolation threshold is estimated as $p_c^\text{perc} \approx 0.2555 \pm 0.0001$. The jamming threshold is estimated as $p_c^\text{jamm} = 0.799 \pm 0.002$.Comment: 3 pages, 4 figures, submitted to EPJ

Latent-heat and non-linear vortex liquid at the vicinity of the first-order phase transition in layered high-Tc superconductors

In this work we revisit the vortex matter phase diagram in layered superconductors solving still open questions by means of AC and DC local magnetic measurements in the paradigmatic Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8}$ compound. We show that measuring with AC magnetic techniques is mandatory in order to probe the bulk response of vortex matter, particularly at high-temperatures where surface barriers for vortex entrance dominate. From the $T_{\rm FOT}$-evolution of the enthalpy and latent-heat at the transition we find that, contrary to previous reports, the nature of the dominant interlayer coupling is electromagnetic in the whole temperature range. By studying the dynamic properties of the phase located at $T \gtrsim T_{\rm FOT}$, we reveal the spanning in a considerable fraction of the phase diagram of a non-linear vortex phase suggesting bulk pinning might play a role even in the liquid vortex phase.Comment: arXiv admin note: substantial text overlap with arXiv:1212.456

Anatomically-aware Uncertainty for Semi-supervised Image Segmentation

Semi-supervised learning relaxes the need of large pixel-wise labeled datasets for image segmentation by leveraging unlabeled data. A prominent way to exploit unlabeled data is to regularize model predictions. Since the predictions of unlabeled data can be unreliable, uncertainty-aware schemes are typically employed to gradually learn from meaningful and reliable predictions. Uncertainty estimation methods, however, rely on multiple inferences from the model predictions that must be computed for each training step, which is computationally expensive. Moreover, these uncertainty maps capture pixel-wise disparities and do not consider global information. This work proposes a novel method to estimate segmentation uncertainty by leveraging global information from the segmentation masks. More precisely, an anatomically-aware representation is first learnt to model the available segmentation masks. The learnt representation thereupon maps the prediction of a new segmentation into an anatomically-plausible segmentation. The deviation from the plausible segmentation aids in estimating the underlying pixel-level uncertainty in order to further guide the segmentation network. The proposed method consequently estimates the uncertainty using a single inference from our representation, thereby reducing the total computation. We evaluate our method on two publicly available segmentation datasets of left atria in cardiac MRIs and of multiple organs in abdominal CTs. Our anatomically-aware method improves the segmentation accuracy over the state-of-the-art semi-supervised methods in terms of two commonly used evaluation metrics.Comment: Accepted at Medical Image Analysis. Code is available at: $\href{https://github.com/adigasu/Anatomically-aware_Uncertainty_for_Semi-supervised_Segmentation}{Github}

Dietary Intake of Natural Sources of Docosahexaenoic Acid and Folate in Pregnant Women of Three European Cohorts

Background: Folic acid plays a fundamental role in cell division and differentiation. Docosahexaenoic acid (DHA) has been associated with infantile neurological and cognitive development. Thus, optimal intrauterine development and growth requires adequate supply of these nutrients during pregnancy. Methods: Healthy pregnant women, aged 18-41 years, were recruited in Granada (Spain; n = 62), Munich (Germany; n = 97) and Pecs (Hungary; n = 152). We estimated dietary DHA and folate intake in weeks 20 (w20) and 30 of gestation (w30) using a food frequency questionnaire with specific focus on the dietary sources of folate and DHA. Results: Both w20 and w30 Spanish participants had significantly higher daily DHA intakes (155 +/- 13 and 161 +/- 9 mg/1,000 kcal) than the German (119 +/- 9 and 124 +/- 12 mg/1,000 kcal; p = 0.002) and Hungarian participants (122 +/- 8 and 125 +/- 10 mg/1,000 kcal; p = 0.005). Hungarian women had higher folate intakes in w20 and w30 (149 +/- 5 and 147 +/- 6 mu g/1,000 kcal) than Spanish (112 +/- 2 and 110 +/- 2 mu g/1,000 kcal; p < 0.001) and German participants (126 +/- 4 and 120 +/- 6 mu g/1,000 kcal; p < 0.001), respectively. Conclusion: Dietary DHA and folate intake of pregnant women differs significantly across the three European cohorts. Only 7% of the participants reached the recommended folate intake during pregnancy, whereas nearly 90% reached the DHA recommended intake of 200 mg per day. Copyright (C) 2008 S. Karger AG, Base

Study of turbocharger shaft motion by means of non-invasive optical techniques: Application to the behaviour analysis in turbocharger lubrication failures

[EN] This paper presents a novel non-invasive technique to estimate the turbocharger shaft whirl motion. The aim of this article is to present a system for monitoring the shaft motion of a turbocharger, which will be used in turbocharger destructive testing. To achieve this, a camera and a light source were installed in a turbocharger test bench with a controlled lubrication circuit. An image recording methodology and a process algorithm have been developed, in order to estimate the shaft motion. This processing consists on differentiating specific zones of the image, in order to obtain their coordinates. Two reference points have been configured on the compressor side, which help to calculate the relative position of the shaft, avoiding the errors due to structural vibrations. Maximum eccentricity of the turbocharger has been determined and it has been compared with shaft motion when it is spinning in different conditions. A luminosity study has been also done, in order to improve the process and to obtain locus of shaft position in a picture exposition time period. The technique has been applied to diagnosis of a lubrication failure test and the main results will be presented in this article: like shaft motion figures; thermodynamic variables and pictures of the shaft while it is spinning at abnormal lubrication conditions. The measuring components used in this technique have the ability to withstand the catastrophic failure of the turbocharger in this type of test. © 2012 Elsevier Ltd.Pastor, JV.; Serrano, J.; Dolz, V.; López Hidalgo, M.; Bouffaud, F. (2012). Study of turbocharger shaft motion by means of non-invasive optical techniques: Application to the behaviour analysis in turbocharger lubrication failures. Mechanical Systems and Signal Processing. 32:292-305. doi:10.1016/j.ymssp.2012.04.020S2923053

Trust your neighbours: Penalty-based constraints for model calibration

Ensuring reliable confidence scores from deep networks is of pivotal importance in critical decision-making systems, notably in the medical domain. While recent literature on calibrating deep segmentation networks has led to significant progress, their uncertainty is usually modeled by leveraging the information of individual pixels, which disregards the local structure of the object of interest. In particular, only the recent Spatially Varying Label Smoothing (SVLS) approach addresses this issue by softening the pixel label assignments with a discrete spatial Gaussian kernel. In this work, we first present a constrained optimization perspective of SVLS and demonstrate that it enforces an implicit constraint on soft class proportions of surrounding pixels. Furthermore, our analysis shows that SVLS lacks a mechanism to balance the contribution of the constraint with the primary objective, potentially hindering the optimization process. Based on these observations, we propose a principled and simple solution based on equality constraints on the logit values, which enables to control explicitly both the enforced constraint and the weight of the penalty, offering more flexibility. Comprehensive experiments on a variety of well-known segmentation benchmarks demonstrate the superior performance of the proposed approach.Comment: Under revie