A deep residual architecture for skin lesion segmentation

In this paper, we propose an automatic approach to skin lesion region segmentation based on a deep learning architecture with multi-scale residual connections. The architecture of the proposed model is based on UNet [22] with residual connections to maximise the learning capability and performance of the network. The information lost in the encoder stages due to the max-pooling layer at each level is preserved through the multi-scale residual connections. To corroborate the efficacy of the proposed model, extensive experiments are conducted on the ISIC 2017 challenge dataset without using any external dermatologic image set. An extensive comparative analysis is presented with contemporary methodologies to highlight the promising performance of the proposed methodology

Metallicity and absolute magnitude calibrations for F-G type main-sequence stars in the Gaia era

In this study, photometric metallicity and absolute magnitude calibrations were derived using F-G spectral type main-sequence stars in the Solar neighbourhood with precise spectroscopic, photometric and Gaia astrometric data for UBV photometry. The sample consists of 504 main-sequence stars covering the temperature, surface gravity and colour index intervals $5300<T_{eff} < 7300$ K, $\log g > 4$ (cgs) and $0.3<(B-V)_0<0.8$ mag, respectively. Stars with relative trigonometric parallax errors $\sigma_{\pi}/\pi\leq0.01$ were preferred from Gaia DR2 data for the estimation of their $M_V$ absolute magnitudes. In order to obtain calibrations, $(U-B)_0$ and $(B-V)_0$ colour indices of stars were preferred and a multi-variable second order equation was used. Calibrations are valid for main-sequence stars in the metallicity and absolute magnitude ranges $-2<{\rm [Fe/H]}<0.5$ dex and $2.5<M_V<6$ mag, respectively. The mean value and standard deviation of the differences between original and estimated values for the metal abundance and absolute magnitude are $\langle\Delta {\rm[Fe/H]}\rangle=0.00\pm0.11$ dex and $\langle\Delta M_V \rangle=0.00\pm0.22$ mag, respectively. In this work, it has been shown that more precise iron abundance and absolute magnitude values were obtained with the new calibrations, compared to previous calibrations in the literature.Comment: 14 pages, 10 figures and 4 tables, accepted for publication in Astrophysics and Space Scienc

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Mammalian Target of Rapamycin (mTOR), Aging, Neuroscience, and Their Association with Aging-Related Diseases

Normal aging is accompanied by cognitive impairment with subtle cellular and molecular changes in the brain, whereas, pathological brain aging manifests as severe behavioral impairments with cellular pathology. Understanding the factors that contribute to both states is undoubtedly important for determining appropriate interventions that alter their progression. Mammalian target of rapamycin (mTOR) signaling has been implicated in affecting lifespan and age-related diseases such as cancer. The relationship of mTOR signaling with pathological brain aging has been more extensively studied, whereas the association with normal brain aging is not well understood. In this chapter we present information about normal and pathological brain aging, the relationship with mTOR signaling and use information from other age-related diseases to suggest that mTOR may have a role in promoting the cellular and molecular changes that underlie age-related cognitive changes. Future work should be directed towards understanding the precise role of mTOR signaling in brain aging. © 2016 Elsevier Inc. All rights reserved

Betatrophin levels are related to the early histological findings in nonalcoholic fatty liver disease

Betatrophin, a liver hormone, regulates glucose and lipid metabolism. We investigated the betatrophin levels in nonalcoholic fatty liver disease (NAFLD) and searched for any relationship with histological severity and metabolic parameters. Fifty males with NAFLD [Nonalcoholic Steatohepati-tis (NASH) (n = 32); non-NASH (n = 18)] and 30 healthy controls were included. Plasma betatrophin was measured by ELISA method. Insulin sensitivity was assessed by HOMA-IR index. Histological features were scored by the semi quantitative classification and combined as the NAFLD activity score (NAS). Betatrophin levels in the non-NASH group were significantly higher than the controls. Betatrophin was positively correlated to the age, waist circumference, total cholesterol, triglycerides, LDL cholesterol, glucose, insulin, HOMA-IR index and gamma glutamyl transpeptidase levels, and negatively correlated to the steatosis and NAS. In the stepwise linear regression analysis, the triglyceride (β = 0.457, p &lt; 0.001), glucose (β = 0.281, p = 0.02) and NAS (β = −0.260, p = 0.03) were the independent determinants of betatrophin. Betatrophin levels are higher in the early stages of NAFLD and tend to decrease when the disease progresses. This could be an important preliminary mechanistic finding to explain the increased frequency of glucose intolerance during the course of NAFLD

Recorded Motions of the Mw6.3 April 6, 2009 L’Aquila (Italy) Earthquake and Implications for Building Structural Damage: Overview.

The normal-faulting earthquake of 6 April 2009 in the Abruzzo Region of central Italy caused heavy losses of life and substantial damage to centuriesold buildings of significant cultural importance and to modern reinforcedconcrete- framed buildings with hollow masonry infill walls. Although structural deficiencies were significant and widespread, the study of the characteristics of strong motion data from the heavily affected area indicated that the short duration of strong shaking may have spared many more damaged buildings from collapsing. It is recognized that, with this caveat of shortduration shaking, the infill walls may have played a very important role in preventing further deterioration or collapse of many buildings. It is concluded that better new or retrofit construction practices that include reinforcedconcrete shear walls may prove helpful in reducing risks in such seismic areas of Italy, other Mediterranean countries, and even in United States, where there are large inventories of deficient structures.Published651-6844.1. Metodologie sismologiche per l'ingegneria sismicaJCR Journalreserve