VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

With the advent of affordable depth sensors, 3D capture becomes more and more ubiquitous and already has made its way into commercial products. Yet, capturing the geometry or complete shapes of everyday objects using scanning devices (e.g. Kinect) still comes with several challenges that result in noise or even incomplete shapes. Recent success in deep learning has shown how to learn complex shape distributions in a data-driven way from large scale 3D CAD Model collections and to utilize them for 3D processing on volumetric representations and thereby circumventing problems of topology and tessellation. Prior work has shown encouraging results on problems ranging from shape completion to recognition. We provide an analysis of such approaches and discover that training as well as the resulting representation are strongly and unnecessarily tied to the notion of object labels. Thus, we propose a full convolutional volumetric auto encoder that learns volumetric representation from noisy data by estimating the voxel occupancy grids. The proposed method outperforms prior work on challenging tasks like denoising and shape completion. We also show that the obtained deep embedding gives competitive performance when used for classification and promising results for shape interpolation

Craniofacial proportions and anthropometric measurements among growth hormone deficient Egyptian children

Introduction: Untreated children with growth hormone deficiency (GHD) have typical somatic features, including short stature, acromicria and distinctive craniofacial features including small head circumference. Patients and Methods: By using a cross sectional study design, we investigated the effect of GHD on craniofacial growth with photographic facial morphometrics & various anthropometric measurements, in 20 children with GHD compared with 20 healthy children and normal first degree relatives of the same age and sex group. Results: Untreated children with GHD had retarded facial height & width (

A Trial of a 7-Valent Pneumococcal Conjugate Vaccine in HIV-Infected Adults.

BACKGROUND: Streptococcus pneumoniae is a leading and serious coinfection in adults with human immunodeficiency virus (HIV) infection, particularly in Africa. Prevention of this disease by vaccination with the current 23-valent polysaccharide vaccine is suboptimal. Protein conjugate vaccines offer a further option for protection, but data on their clinical efficacy in adults are needed. METHODS: In this double-blind, randomized, placebo-controlled clinical efficacy trial, we studied the efficacy of a 7-valent conjugate pneumococcal vaccine in predominantly HIV-infected Malawian adolescents and adults who had recovered from documented invasive pneumococcal disease. Two doses of vaccine were given 4 weeks apart. The primary end point was a further episode of pneumococcal infection caused by vaccine serotypes or serotype 6A. RESULTS: From February 2003 through October 2007, we followed 496 patients (of whom 44% were male and 88% were HIV-seropositive) for 798 person-years of observation. There were 67 episodes of pneumococcal disease in 52 patients, all in the HIV-infected subgroup. In 24 patients, there were 19 episodes that were caused by vaccine serotypes and 5 episodes that were caused by the 6A serotype. Of these episodes, 5 occurred in the vaccine group and 19 in the placebo group, for a vaccine efficacy of 74% (95% confidence interval [CI], 30 to 90). There were 73 deaths from any cause in the vaccine group and 63 in the placebo group (hazard ratio in the vaccine group, 1.18; 95% CI, 0.84 to 1.66). The number of serious adverse events within 14 days after vaccination was significantly lower in the vaccine group than in the placebo group (3 vs. 17, P=0.002), and the number of minor adverse events was significantly higher in the vaccine group (41 vs. 13, P=0.003). CONCLUSIONS: The 7-valent pneumococcal conjugate vaccine protected HIV-infected adults from recurrent pneumococcal infection caused by vaccine serotypes or serotype 6A. (Current Controlled Trials number, ISRCTN54494731.) Copyright 2010 Massachusetts Medical Society

Top and Bottom Seesaw from Supersymmetric Strong Dynamics

We propose a top and bottom seesaw model with partial composite top and bottom quarks. Such composite quarks and topcolor gauge bosons are bound states from supersymmetric strong dynamics by Seiberg duality. Supersymmetry breaking also induces the breaking of topcolor into the QCD gauge coupling. The low energy description of our model reduces to a complete non-minimal extension of the top seesaw model with bottom seesaw. The non-minimal nature is crucial for Higgs mixings and the appearance of light Higgs fields. The Higgs fields are bound states of partial composite particles with the lightest one compatible with a 125 GeV Higgs field which was discovered at the LHC.Comment: Minor changes, Published Versio

Community Aliveness: Discovering Interaction Decay Patterns in Online Social Communities

Online Social Communities (OSCs) provide a medium for connecting people, sharing news, eliciting information, and finding jobs, among others. The dynamics of the interaction among the members of OSCs is not always growth dynamics. Instead, a $\textit{decay}$ or $\textit{inactivity}$ dynamics often happens, which makes an OSC obsolete. Understanding the behavior and the characteristics of the members of an inactive community help to sustain the growth dynamics of these communities and, possibly, prevents them from being out of service. In this work, we provide two prediction models for predicting the interaction decay of community members, namely: a Simple Threshold Model (STM) and a supervised machine learning classification framework. We conducted evaluation experiments for our prediction models supported by a $\textit{ground truth}$ of decayed communities extracted from the StackExchange platform. The results of the experiments revealed that it is possible, with satisfactory prediction performance in terms of the F1-score and the accuracy, to predict the decay of the activity of the members of these communities using network-based attributes and network-exogenous attributes of the members. The upper bound of the prediction performance of the methods we used is $0.91$ and $0.83$ for the F1-score and the accuracy, respectively. These results indicate that network-based attributes are correlated with the activity of the members and that we can find decay patterns in terms of these attributes. The results also showed that the structure of the decayed communities can be used to support the alive communities by discovering inactive members.Comment: pre-print for the 4th European Network Intelligence Conference - 11-12 September 2017 Duisburg, German

On the Hardness of SAT with Community Structure

Recent attempts to explain the effectiveness of Boolean satisfiability (SAT) solvers based on conflict-driven clause learning (CDCL) on large industrial benchmarks have focused on the concept of community structure. Specifically, industrial benchmarks have been empirically found to have good community structure, and experiments seem to show a correlation between such structure and the efficiency of CDCL. However, in this paper we establish hardness results suggesting that community structure is not sufficient to explain the success of CDCL in practice. First, we formally characterize a property shared by a wide class of metrics capturing community structure, including "modularity". Next, we show that the SAT instances with good community structure according to any metric with this property are still NP-hard. Finally, we study a class of random instances generated from the "pseudo-industrial" community attachment model of Gir\'aldez-Cru and Levy. We prove that, with high probability, instances from this model that have relatively few communities but are still highly modular require exponentially long resolution proofs and so are hard for CDCL. We also present experimental evidence that our result continues to hold for instances with many more communities. This indicates that actual industrial instances easily solved by CDCL may have some other relevant structure not captured by the community attachment model.Comment: 23 pages. Full version of a SAT 2016 pape

On Counting Triangles through Edge Sampling in Large Dynamic Graphs

Traditional frameworks for dynamic graphs have relied on processing only the stream of edges added into or deleted from an evolving graph, but not any additional related information such as the degrees or neighbor lists of nodes incident to the edges. In this paper, we propose a new edge sampling framework for big-graph analytics in dynamic graphs which enhances the traditional model by enabling the use of additional related information. To demonstrate the advantages of this framework, we present a new sampling algorithm, called Edge Sample and Discard (ESD). It generates an unbiased estimate of the total number of triangles, which can be continuously updated in response to both edge additions and deletions. We provide a comparative analysis of the performance of ESD against two current state-of-the-art algorithms in terms of accuracy and complexity. The results of the experiments performed on real graphs show that, with the help of the neighborhood information of the sampled edges, the accuracy achieved by our algorithm is substantially better. We also characterize the impact of properties of the graph on the performance of our algorithm by testing on several Barabasi-Albert graphs.Comment: A short version of this article appeared in Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2017

Antioxidant and antimicrobial activities of Morchella conica Pers.

Antioxidant capacity and antimicrobial activities of Morchella conica Pers. extracts obtained with ethanol were investigated in this study. Four complementary test systems; namely DPPH free radical scavenging, -carotene/linoleic acid systems, total phenolic compounds and total flavonoid concentration were used. Inhibition values of M. conica ethanol extracts, buthylated hydroxyanisol (BHA) and -tocopherol standards were found to be 96.9, 98.9 and 99.2%, respectively, at aconcentration of 160 ìg/ml. When compared the inhibition levels of methanol extract of M. conica and standards in linoleic acid system, it was observed that the higher the concentration of both M. conicaethanol extract and the standards the higher the inhibition effect. Total flavonoid amount was 9.17±0.56ìg mg-1 quercetin equivalent while the phenolic compound amount was 41.93±0.29 ìg mg-1 pyrocatecholequivalent in the ethanolic extract. The antimicrobial effect of M. conica ethanol extract was tested against six species of Gram-positive bacteria, seven species of Gram-negative bacteria and one speciesof yeast. The M. conica ethanol extract had a narrow antibacterial spectrum against tested microorganisms. The most susceptible bacterium was M. flavus. The crude extract was found active on S. aureus ATCC 25923 and S. aureus Cowan I. The M. conica ethanol extract did not exhibit anticandidal activity against C. albican

Free-radical scavenging capacity and antimicrobial activity of wild edible mushroom from Turkey

Antioxidant capacity and antimicrobial activities of Ramaria flava (Schaeff) Quel. (RF) extracts obtained with ethanol were investigated in this study. Four complementary test systems; namely DPPH freeradical scavenging, -carotene/linoleic acid systems, total phenolic compounds and total flavonoid concentration have been used. Inhibition values of R. flava extracts, BHA and -tocopherol standardswere found to be 94.7, 98.9 and 99.2%, respectively, at 160ƒÊg/ml. When compared the inhibition levels of ethanol extract of R. flava and standards in linoleic acid system, it was observed that the higher theconcentration of both RF ethanol extract and the standards the higher the inhibition effect. Total flavonoid amount was 8.27}0.28 ƒÊg mg-1 quercetin equivalent while the total phenolic compound amountwas 39.83}0.32 ƒÊg mg-1 pyrocatechol equivalent in the ethanolic extract. The ethanol extract of R. flava inhibited the growth of Gram-positive bacteria better than Gram-negative bacteria and yeast. The crude extract showed no antibacterial activity against Pseudomonas aeruginosa, Escherichia coli, Morganella morganii and Proteus vulgaris. The antimicrobial activity profile of R. flava against tested strains indicated that Micrococcus flavus, Micrococcus luteus and Yersinia enterocolitica was the most susceptible bacteria of all the test strains. R. flava was found to be inactive against Candida albicans