Aortomesenteric fat thickness with ultrasound predicts metabolic diseases in obese patients

BACKGROUND:: The relation between visceral fat accumulation and development of cardiovascular and metabolic disorders has been demonstrated. The aim of this study was to determine the relationship between a new ultrasound visceral fat thickness (VFT) measurement and clinical and anthropometric data in a consecutive series of obese patients. METHODS:: Fifty-five consecutive male obese patients underwent ultrasound evaluation and metabolic and anthropometric parameters determination at baseline and after 3 weeks of a very low-calorie diet (VLCD) therapy. The new ultrasound measurement, the thickness of the fat between the aorta and the superior mesenteric artery (AMFT), was determined along with the maximum thickness of preperitoneal fat and the global VFT. RESULTS:: AMFT showed a better correlation than VFT and preperitoneal fat with all anthropometric and metabolic parameters, both at baseline and after VLCD regimen. At baseline, patients in the middle and high AMFT and VFT tertiles had a significantly higher prevalence of metabolic diseases with respect to AMFT and VFT low tertile patients, whereas after VLCD period, AMFT only showed significant difference within tertiles. The odds ratios for the various metabolic diseases were higher in the middle and high AMFT tertiles than those in the middle and high VFT tertiles, remaining significant after adjustment for age, body mass index and VLCD regimen only in the middle and high AMFT tertiles. CONCLUSIONS:: The ultrasonographic AMFT evaluation is strongly correlated to the presence of metabolic syndrome and could be a valuable tool to predict metabolic diseases and associated cardiovascular risks in men. © 2013 Lippincott Williams and Wilkins

A blind method to recover the mask of a deep galaxy survey

We present a blind method to determine the properties of a foreground contamination, given by a visibility mask, that affects a deep galaxy survey. Angular cross correlations of density fields in different redshift bins are expected to vanish (apart from a contribution due to lensing), but are sensitive to the presence of a foreground that modulates the flux limit across the sky. After formalizing the expected effect of a foreground mask on the measured galaxy density, under a linear, luminosity-dependent bias model for galaxies, we construct two estimators that single out the mask contribution if a sufficient number of independent redshift bins is available. These estimators are combined to give a reconstruction of the mask. We use Milky-Way reddening as a prototype for the mask. Using a set of 20 large mock catalogs covering $1/4$-th of the sky and number-matched to $H\alpha$ emitters to mimic an Euclid-like sample, we demonstrate that our method can reconstruct the mask and its angular clustering at scales $\ell<100$, beyond which the cosmological signal becomes dominant. The uncertainty of this reconstruction is quantified to be $1/3$-rd of the sample variance of the signal. Such a reconstruction requires knowledge of the average and square average of the mask, but we show that it is possible to recover this information either from external models or internally from the data. It also relies on knowledge of how the impact of the foreground changes with redshift (due to the extinction curve in our case), but this can be tightly constrained by cross correlations of different redshift bins. The strong points of this blind reconstruction technique lies in the ability to find "unknown unknowns" that affect a survey, and in the facility to quantify, using sets of mock catalogs, how its uncertainty propagates to clustering measurements. [Abridged]Comment: 43 pages, 16 figures, JCAP, in pres

EXISTING-BIM: INTEGRATED SURVEY PROCEDURES FOR THE MANAGEMENT OF MODERN ARCHITECTURE

Abstract. This paper is aimed at illustrating the operation workflow to create a BIM model of an existing building, by highlighting its process starting from photogrammetric acquisitions and indicating its critical elements as regards data structure and the following modeling. The subject of this study is a reinforced concrete building of the 1960s on six levels. At present, it is undergoing an extensive refurbishment with the purpose of converting its original function, from the US Navy Hospital into offices. Since it was possible to access archive documents concerning the executive design and to carry out even invasive surveys for acquiring specific data about building details, BIM modeling could refer to a significant amount of qualitative and quantitative data. This circumstance characterized the work steps of a BIM modeling which, although referred to an existing building, may also be applied to new constructions. Building technology has implicitly facilitated the identification of the constructive elements and the creation of a list, although the unusual shape of the structure has caused specific problems differently discussed and documented in the text.</p

Multi-agent quality of experience control

In the framework of the Future Internet, the aim of the Quality of Experience (QoE) Control functionalities is to track the personalized desired QoE level of the applications. The paper proposes to perform such a task by dynamically selecting the most appropriate Classes of Service (among the ones supported by the network), this selection being driven by a novel heuristic Multi-Agent Reinforcement Learning (MARL) algorithm. The paper shows that such an approach offers the opportunity to cope with some practical implementation problems: in particular, it allows to face the so-called “curse of dimensionality” of MARL algorithms, thus achieving satisfactory performance results even in the presence of several hundreds of Agents