A GIS based spatial decision support system for modelling contaminant intrusion into water distribution systems

The paper presents a GIS based spatial decision support system for modelling contaminant intrusion into water distribution system. Three models have been developed to simulate the process and risk of contamination. A seepage model predicts the contaminant zone of pollution sources and the change of concentration during migration through soil. A pipe condition assessment model ranks the condition of water pipe in terms of the potential of contaminant ingress. An ingress model combines the geometry algorithm with contaminant zone to obtain the potential pollution areas of water distribution pipe. The three models were integrated with ArcView GIS for supporting decision making for risk mitigation. Zone VIII of water supply system in Guntur, India was selected for the case study. The contaminant ingress potential and potential pollution area of water pipes were displayed as thematic maps in GIS. The areas resulting in high risk were identified from the GIS maps. The availability of resources for maintenance activities are limited in developing countries. Thus GIS based spatial decision support system helps to achieve maximum risk reduction

A Family of Maximum Margin Criterion for Adaptive Learning

In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D^2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are compenent to be adopted in complicated application scenarios.Comment: 14 page

On the Complex Network Structure of Musical Pieces: Analysis of Some Use Cases from Different Music Genres

This paper focuses on the modeling of musical melodies as networks. Notes of a melody can be treated as nodes of a network. Connections are created whenever notes are played in sequence. We analyze some main tracks coming from different music genres, with melodies played using different musical instruments. We find out that the considered networks are, in general, scale free networks and exhibit the small world property. We measure the main metrics and assess whether these networks can be considered as formed by sub-communities. Outcomes confirm that peculiar features of the tracks can be extracted from this analysis methodology. This approach can have an impact in several multimedia applications such as music didactics, multimedia entertainment, and digital music generation.Comment: accepted to Multimedia Tools and Applications, Springe

Isolated heart models for studying cardiac electrophysiology: a historical perspective and recent advances

Experimental models used in cardiovascular research range from cellular to whole heart preparations. Isolated whole hearts show higher levels of structural and functional integration than lower level models such as tissues or cellular fragments. Cardiovascular diseases are multi-factorial problems that are dependent on highly organized structures rather than on molecular or cellular components alone. This article first provides a general introduction on the animal models of cardiovascular diseases. It is followed by a detailed overview and a historical perspective of the different isolated heart systems with a particular focus on the Langendorff perfusion method for the study of cardiac arrhythmias. The choice of species, perfusion method, and perfusate composition are discussed in further detail with particular considerations of the theoretical and practical aspects of experimental settings

Hepatitis C virus cell-cell transmission and resistance to direct-acting antiviral agents

Hepatitis C virus (HCV) is transmitted between hepatocytes via classical cell entry but also uses direct cell-cell transfer to infect neighboring hepatocytes. Viral cell-cell transmission has been shown to play an important role in viral persistence allowing evasion from neutralizing antibodies. In contrast, the role of HCV cell-cell transmission for antiviral resistance is unknown. Aiming to address this question we investigated the phenotype of HCV strains exhibiting resistance to direct-acting antivirals (DAAs) in state-of-the-art model systems for cell-cell transmission and spread. Using HCV genotype 2 as a model virus, we show that cell-cell transmission is the main route of viral spread of DAA-resistant HCV. Cell-cell transmission of DAA-resistant viruses results in viral persistence and thus hampers viral eradication. We also show that blocking cell-cell transmission using host-targeting entry inhibitors (HTEIs) was highly effective in inhibiting viral dissemination of resistant genotype 2 viruses. Combining HTEIs with DAAs prevented antiviral resistance and led to rapid elimination of the virus in cell culture model. In conclusion, our work provides evidence that cell-cell transmission plays an important role in dissemination and maintenance of resistant variants in cell culture models. Blocking virus cell-cell transmission prevents emergence of drug resistance in persistent viral infection including resistance to HCV DAAs

Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equations

The semiparametric accelerated failure time model is not as widely used as the Cox relative risk model mainly due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations provide promising tools to make the accelerate failure time models more attractive in practice. For semiparametric multivariate accelerated failure time models, we propose a generalized estimating equation approach to account for the multivariate dependence through working correlation structures. The marginal error distributions can be either identical as in sequential event settings or different as in parallel event settings. Some regression coefficients can be shared across margins as needed. The initial estimator is a rank-based estimator with Gehan's weight, but obtained from an induced smoothing approach with computation ease. The resulting estimator is consistent and asymptotically normal, with a variance estimated through a multiplier resampling method. In a simulation study, our estimator was up to three times as efficient as the initial estimator, especially with stronger multivariate dependence and heavier censoring percentage. Two real examples demonstrate the utility of the proposed method

A systematic review of randomised controlled trials on the effectiveness of exercise programs on lumbo pelvic pain among postnatal women

Background: A substantial number of women tend to be affected by Lumbo Pelvic Pain (LPP) following child birth. Physical exercise is indicated as a beneficial method to relieve LPP, but individual studies appear to suggest mixed findings about its effectiveness. This systematic review aimed to synthesise evidence from randomised controlled trials on the effectiveness of exercise on LPP among postnatal women to inform policy, practice and future research. Methods: A systematic review was conducted of all randomised controlled trials published between January 1990 and July 2014, identified through a comprehensive search of following databases: PubMed, PEDro, Embase, Cinahl, Medline, SPORTDiscus, Cochrane Pregnancy and Childbirth Group’s Trials Register, and electronic libraries of authors’institutions. Randomised controlled trials were eligible for inclusion if the intervention comprised of postnatal exercise for women with LPP onset during pregnancy or within 3 months after delivery and the outcome measures included changes in LPP. Selected articles were assessed using the PEDro Scale for methodological quality and findings were synthesised narratively as meta-analysis was found to be inappropriate due to heterogeneity among included studies. Results: Four randomised controlled trials were included, involving 251 postnatal women. Three trials were rated as of ‘good’ methodological quality. All trials, except one, were at low risk of bias. The trials included physical exercise programs with varying components, differing modes of delivery, follow up times and outcome measures. Intervention in one trial, involving physical therapy with specific stabilising exercises, proved to be effective in reducing LPP intensity. An improvement in gluteal pain on the right side was reported in another trial and a significant difference in pain frequency in another. Conclusion: Our review indicates that only few randomised controlled trials have evaluated the effectiveness of exercise on LPP among postnatal women. There is also a great amount of variability across existing trials in the components of exercise programs, modes of delivery, follow up times and outcome measures. While there is some evidence to indicate the effectiveness of exercise for relieving LPP, further good quality trials are needed to ascertain the most effective elements of postnatal exercise programs suited for LPP treatment

Regulation of mammalian horizontal gene transfer by apoptotic DNA fragmentation

Previously it was shown that horizontal DNA transfer between mammalian cells can occur through the uptake of apoptotic bodies, where genes from the apoptotic cells were transferred to neighbouring cells phagocytosing the apoptotic bodies. The regulation of this process is poorly understood. It was shown that the ability of cells as recipient of horizontally transferred DNA was enhanced by deficiency of p53 or p21. However, little is known with regard to the regulation of DNA from donor apoptotic cells. Here we report that the DNA fragmentation factor/caspase-activated DNase (DFF/CAD), which is the endonuclease responsible for DNA fragmentation during apoptosis, plays a significant role in regulation of horizontal DNA transfer. Cells with inhibited DFF/CAD function are poor donors for horizontal gene transfer (HGT) while their ability of being recipients of HGT is not affected

Enhancement of the Nernst effect by stripe order in a high-Tc superconductor

The Nernst effect in metals is highly sensitive to two kinds of phase transition: superconductivity and density-wave order. The large positive Nernst signal observed in hole-doped high-Tc superconductors above their transition temperature Tc has so far been attributed to fluctuating superconductivity. Here we show that in some of these materials the large Nernst signal is in fact caused by stripe order, a form of spin / charge modulation which causes a reconstruction of the Fermi surface. In LSCO doped with Nd or Eu, the onset of stripe order causes the Nernst signal to go from small and negative to large and positive, as revealed either by lowering the hole concentration across the quantum critical point in Nd-LSCO, or lowering the temperature across the ordering temperature in Eu-LSCO. In the latter case, two separate peaks are resolved, respectively associated with the onset of stripe order at high temperature and superconductivity near Tc. This sensitivity to Fermi-surface reconstruction makes the Nernst effect a promising probe of broken symmetry in high-Tc superconductors