Holistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models

The steady growth of graph data from social networks has resulted in wide-spread research in finding solutions to the influence maximization problem. In this paper, we propose a holistic solution to the influence maximization (IM) problem. (1) We introduce an opinion-cum-interaction (OI) model that closely mirrors the real-world scenarios. Under the OI model, we introduce a novel problem of Maximizing the Effective Opinion (MEO) of influenced users. We prove that the MEO problem is NP-hard and cannot be approximated within a constant ratio unless P=NP. (2) We propose a heuristic algorithm OSIM to efficiently solve the MEO problem. To better explain the OSIM heuristic, we first introduce EaSyIM - the opinion-oblivious version of OSIM, a scalable algorithm capable of running within practical compute times on commodity hardware. In addition to serving as a fundamental building block for OSIM, EaSyIM is capable of addressing the scalability aspect - memory consumption and running time, of the IM problem as well. Empirically, our algorithms are capable of maintaining the deviation in the spread always within 5% of the best known methods in the literature. In addition, our experiments show that both OSIM and EaSyIM are effective, efficient, scalable and significantly enhance the ability to analyze real datasets.Comment: ACM SIGMOD Conference 2016, 18 pages, 29 figure

A Robust Regression-Based Stock Exchange Forecasting and Determination of Correlation between Stock Markets

Knowledge-based decision support systems for financial management are an important part of investment plans. Investors are avoiding investing in traditional investment areas such as banks due to low return on investment. The stock exchange is one of the major areas for investment presently. Various non-linear and complex factors affect the stock exchange. A robust stock exchange forecasting system remains an important need. From this line of research, we evaluate the performance of a regression-based model to check the robustness over large datasets. We also evaluate the effect of top stock exchange markets on each other. We evaluate our proposed model on the top 4 stock exchanges—New York, London, NASDAQ and Karachi stock exchange. We also evaluate our model on the top 3 companies—Apple, Microsoft, and Google. A huge (Big Data) historical data is gathered from Yahoo finance consisting of 20 years. Such huge data creates a Big Data problem. The performance of our system is evaluated on a 1-step, 6-step, and 12-step forecast. The experiments show that the proposed system produces excellent results. The results are presented in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE)

Sunflower (Helianthus annuus) Hybrids Evaluation for Oil Quality and Yield Attributes under Spring Planting Conditions of Haripur, Pakistan

Field experiment was conducted at the University of Haripur, Pakistan, to explore the role of photothermal units on oil contents, fatty acids profile, yield and yield traits of four sunflower hybrids viz SMH-0917, NK-S-278, SMH-0907 and Hysun-33. These sunflower hybrids were selected because the farmers of that area are mostly relying on these hybrids for sunflower production. Sunflower hybrids were sown in spring and arranged under Randomized Complete Block Design with 3 replications under field conditions. Significant variation (p 0.05%) was found among the sunflower hybrids for photothermal unit requirements for flower completion and physiological maturity. Highest photothermal unit accumulation was found in Hysun-33 followed by SMH-0917 and SMH-0907. Highest seed oil content and oil composition (linoleic and oleic acid were most abundant, whereas palmitic acid was least) was recorded in Hysun-33, SMH-0917 and SMH-0907. Overall Hysun-33, SMH-0917 and SMH-0907 performed better for plant height, head diameter, number of achenes per head and achene yield under field conditions. It was also observed that temperature and moisture availability positively influenced the oil quality of sunflower hybrids under spring planting conditions. The significant amount of variation within the sunflower population for photothermal unit accumulation, oil content, oil quality, and yield traits under these uniform field conditions reveals potential genetic variation that could be useful in breeding early maturing and high yielding local sunflower hybrids

Integrative Molecular Analysis of DNA Methylation Dynamics Unveils Molecules with Prognostic Potential in Breast Cancer

DNA methylation acts as a major epigenetic modification in mammals, characterized by the transfer of a methyl group to a cytosine. DNA methylation plays a pivotal role in regulating normal development, and misregulation in cells leads to an abnormal phenotype as is seen in several cancers. Any mutations or expression anomalies of genes encoding regulators of DNA methylation may lead to abnormal expression of critical molecules. A comprehensive genomic study encompassing all the genes related to DNA methylation regulation in relation to breast cancer is lacking. We used genomic and transcriptomic datasets from the Cancer Genome Atlas (TGCA) Pan-Cancer Atlas, Genotype-Tissue Expression (GTEx) and microarray platforms and conducted in silico analysis of all the genes related to DNA methylation with respect to writing, reading and erasing this epigenetic mark. Analysis of mutations was conducted using cBioportal, while Xena and KMPlot were utilized for expression changes and patient survival, respectively. Our study identified multiple mutations in the genes encoding regulators of DNA methylation. The expression profiling of these showed significant differences between normal and disease tissues. Moreover, deregulated expression of some of the genes, namely DNMT3B, MBD1, MBD6, BAZ2B, ZBTB38, KLF4, TET2 and TDG, was correlated with patient prognosis. The current study, to our best knowledge, is the first to provide a comprehensive molecular and genetic profile of DNA methylation machinery genes in breast cancer and identifies DNA methylation machinery as an important determinant of the disease progression. The findings of this study will advance our understanding of the etiology of the disease and may serve to identify alternative targets for novel therapeutic strategies in cancer

Features of the power-law fluid over cylinders in a channel via gap aspects: Galerkin finite element method (GFEM)-based study

The goal of this investigation is to carry out a comprehensive analysis of hydrodynamic forces, with particular attention being paid to the power-law fluid flow across cylinders and presence gap considerations. With the assistance of the Galerkin finite element method (GFEM), the discretization of the two-dimensional system of non-linear partial differential equations was successfully completed. The research is carried out with a significant variance of the flow behavior index n from .3 to 1.7, gap aspects Gp from 0 .0 to .3, and fixed Reynolds number Re 20. To obtain an extremely accurate solution, first, a coarse hybrid computational mesh needs to be developed, and then, more refinement must take place. The selection of the best possible case can be determined by comparing flow patterns, coefficients of drag and lift, and cylinder gaps. The shear-thickening behavior of fluids has a substantially greater influence on the drag characteristics than either the Newtonian or the shear-thinning behavior of fluids do. In addition to this, the shear-thickening action causes the upstream obstacle’s drag coefficient to increase because the gap spacing becomes more widespread

Recycled materials in railroad substructure: an energy perspective

Given that the current ballasted tracks in Australia may not be able to support faster and significantly heavier freight trains as planned for the future, the imminent need for innovative and sustainable ballasted tracks for transport infrastructure is crucial. Over the past two decades, a number of studies have been conducted by the researchers of Transport Research Centre (TRC) at the University of Technology Sydney (UTS) to investigate the ability of recycled rubber mats, as well as waste tyre cells and granulated rubber to improve the stability of track substructure including ballast and subballast layers. This paper reviews four applications of these novel methods, including using recycled rubber products such as CWRC mixtures (i.e., mixtures of coal wash (CW) and rubber crumbs (RC)) and SEAL mixtures (i.e., mixtures of steel furnace slag, CW and RC) to replace subballast/capping materials, tyre cells reinforcements for subballast/capping layer and under ballast mats; and investigates the energy dissipation capacity for each application based on small-scale cyclic triaxial tests and large-scale track model tests. It has been found that the inclusion of these rubber products increases the energy dissipation effect of the track, hence reducing the ballast degradation efficiently and increasing the track stability. Moreover, a rheological model is also proposed to investigate the effect of different rubber inclusions on their efficiency to reduce the transient motion of rail track under dynamic loading. The outcomes elucidated in this paper will lead to a better understanding of the performance of ballast tracks upgraded with resilient rubber products, while promoting environmentally sustainable and more affordable ballasted tracks for greater passenger comfort and increased safety

Correlation between maternal and neonatal blood Vitamin D level; A cross sectional study of 416 participants visiting a tertiary care hospital in Pakistan

In Pakistan there is limited evidence for the levels and relationship of 25 (OH) Vitamin D [25(OH)D] status in pregnant women and their newborns while the association between maternal 25(OH)D and newborn anthropometric measurements remains unexplored. Sociodemographic data was collected from 213 pregnant mothers during their visit to a tertiary care hospital at the time of childbirth. Anthropometric measurements were performed on all mothers and their newborns and blood samples collected from both for 25(OH)D levels. Participants were classified into two groups according to their 25(OH)D status: Sufficient (25(OH)D ≥50nmol/l) and Deficient (25(OH)D 0.05). Our study shows a high prevalence of 25(OH)D deficiency in pregnant women and their newborns and a strong positive association between maternal and newborn 25(OH)D levels. Findings of this study indicate the importance of maintaining sufficient 25(OH)D levels during pregnancy

Pre-therapeutic efficacy of the CDK inhibitor dinaciclib in medulloblastoma cells

Medulloblastoma (MB) is the most common aggressive paediatric brain tumour and, despite the recent progress in the treatments of MB patients, there is still an urgent need of complementary or alternative therapeutic options for MB infants. Cyclin Dependent Kinase inhibitors (CDKi) are at the front-line of novel targeted treatments for multiple cancers and the CDK4/6 specific inhibitor palbociclib has been pre-clinically identified as an effective option for MB cells. Herein, we identified the pan-CDKi dinaciclib as a promising alternative to palbociclib for the suppression of MB cells proliferation. We present evidence supporting dinaciclib’s ability to inhibit MB cells in vitro proliferation at considerably lower doses than palbociclib. Sequencing data and pathway analysis suggested that dinaciclib is a potent cell death inducer in MB cells. We found that dinaciclib-induced apoptosis is triggered by CDK9 inhibition and the resultant reduction in RNA pol II phosphorylation, which leads to the downregulation of the oncogenic marker MYC, and the anti-apoptotic protein MCL-1. Specifically, we demonstrated that MCL-1 is a key apoptotic mediator for MB cells and co-treatment of dinaciclib with BH3 mimetics boosts the therapeutic efficacy of dinaciclib. Together, these findings highlight the potential of multi-CDK inhibition by dinaciclib as an alternative option to CDK4/6 specific inhibition, frequently associated with drug resistance in patients