Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently the case, for example, in the monitoring and study of massive, online social networks. We study the problem of how to estimate the degree distribution-an object of fundamental interest-of a true underlying network from its sampled network. In particular, we show that this problem can be formulated as an inverse problem. Playing a key role in this formulation is a matrix relating the expectation of our sampled degree distribution to the true underlying degree distribution. Under many network sampling designs, this matrix can be defined entirely in terms of the design and is found to be ill-conditioned. As a result, our inverse problem frequently is ill-posed. Accordingly, we offer a constrained, penalized weighted least-squares approach to solving this problem. A Monte Carlo variant of Stein's unbiased risk estimation (SURE) is used to select the penalization parameter. We explore the behavior of our resulting estimator of network degree distribution in simulation, using a variety of combinations of network models and sampling regimes. In addition, we demonstrate the ability of our method to accurately reconstruct the degree distributions of various sub-communities within online social networks corresponding to Friendster, Orkut and LiveJournal. Overall, our results show that the true degree distributions from both homogeneous and inhomogeneous networks can be recovered with substantially greater accuracy than reflected in the empirical degree distribution resulting from the original sampling.

Non-lethal macular diseases greatly impact patients' life quality, and will cause vision loss at the late stages. Visual inspection of the optical coherence tomography (OCT) images by the experienced clinicians is the main diagnosis technique. We proposed a computer-aided diagnosis (CAD) model to discriminate age-related macular degeneration (AMD), diabetic macular edema (DME) and healthy macula. The linear configuration pattern (LCP) based features of the OCT images were screened by the Correlation-based Feature Subset (CFS) selection algorithm. And the best model based on the sequential minimal optimization (SMO) algorithm achieved 99.3% in the overall accuracy for the three classes of samples.

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Background Body posture is a fundamental indicator for assessing health and quality of life, especially for elderly people. Deciphering the changes in body posture occurring with age is a current topic in the field of geriatrics. The aims of this study were to assess the parameters of standing body posture in the global sagittal plane and to determine the dynamics of changes in standing body posture occurring with age and differences between men and women. Methods The measurements were performed on 226 individuals between the ages of 20 to 89 with a new photogrammetry, via which we assessed five postural angles - neck, thorax, waist, hip and knee. The data were analyzed with t-test, one-way ANOVA, linear regression model and generalized additive model. Results Among these segments studied here, neck changed most, while the middle segments of the body, waist and hip, were relative stable. Significant differences between men and women were found with respect to the angles of neck, thorax and hip. Three of the five postural angles were significantly influenced with aging, including increasing cervical lordosis, thoracic kyphosis and knee flexion, starting from no older than around 50 yrs. showed by fitting curve derived with generalized additive model. These changes were more marked among women. Besides, this study highlights the effects of age and gender on the complex interrelation between adjacent body segments in standing. Conclusions The presented results showed changes in the parameters describing body posture throughout consecutive ages and emphasized that for an individualized functional analysis, it is essential to consider age-and gender-specific changes in the neck, thorax and knee. This paper presents useful externally generalizable information not only for clinical purposes but also to inform further research on larger numbers of subjects. Electronic supplementary material The online version of this article (10.1186/s12877-019-1096-0) contains supplementary material, which is available to authorized users.