A probabilistic model to resolve diversity-accuracy challenge of recommendation systems

Recommendation systems have wide-spread applications in both academia and industry. Traditionally, performance of recommendation systems has been measured by their precision. By introducing novelty and diversity as key qualities in recommender systems, recently increasing attention has been focused on this topic. Precision and novelty of recommendation are not in the same direction, and practical systems should make a trade-off between these two quantities. Thus, it is an important feature of a recommender system to make it possible to adjust diversity and accuracy of the recommendations by tuning the model. In this paper, we introduce a probabilistic structure to resolve the diversity-accuracy dilemma in recommender systems. We propose a hybrid model with adjustable level of diversity and precision such that one can perform this by tuning a single parameter. The proposed recommendation model consists of two models: one for maximization of the accuracy and the other one for specification of the recommendation list to tastes of users. Our experiments on two real datasets show the functionality of the model in resolving accuracy-diversity dilemma and outperformance of the model over other classic models. The proposed method could be extensively applied to real commercial systems due to its low computational complexity and significant performance.Comment: 19 pages, 5 figure

Optimistic Parallel State-Machine Replication

State-machine replication, a fundamental approach to fault tolerance, requires replicas to execute commands deterministically, which usually results in sequential execution of commands. Sequential execution limits performance and underuses servers, which are increasingly parallel (i.e., multicore). To narrow the gap between state-machine replication requirements and the characteristics of modern servers, researchers have recently come up with alternative execution models. This paper surveys existing approaches to parallel state-machine replication and proposes a novel optimistic protocol that inherits the scalable features of previous techniques. Using a replicated B+-tree service, we demonstrate in the paper that our protocol outperforms the most efficient techniques by a factor of 2.4 times

Protective effect of Harmine on kidney disorders induced by nicotine in male mice

Introduction: Harmine is one of the Harmal-deived alkaloids with anti-proliferatory effect on cell lines. Nicotine is a major toxic component of cigarette smoke and it is a major risk factor in the development of functional disorder of several organ systems. Nicotine from tobacco products is absorbed into the blood across the lungs,  nasal and buccal mucosa. The current study aimed to investigate the effect of Harmine and Nicotine on the weight of kidney and number of glumeruli and glomerular diameter, kidney tissue and serum levels of nitric oxide, BUN, Creatinine and TAC in mice. Methods and Results: In this study, 48 male Mice were divided in to 8 groups: control, nicotine–treated group (2.5 mg/kg/day); harmine-treated groups (5,10, 15 mg/kg./day); and nicotine and harmine treated group intraperitoneal administration for successive 14 days. These mice were randomly assigned to 8 groups(n=6). After 24 hours animal were killed , the kidney was sampled: tissue sections were prepared and examined by light microscope. weight of kidney  and number of glumeruli and glomerular diameter and serum levels of nitric oxide, BUN, Creatinine and TAC (Total antioxidant capacity) were analyzed (one-way ANOVA). Then data were P<0.05 was considered significant. The results indicate that nicotine administration significantly increased BUN, creatinine and nitric oxide levels compared to saline group (P<0/05). Harmine   (10, 15 mg/kg./day) significantly decreased BUN, creatinine and nitric oxide levels  compared to control group and nicotine group (p<0.05). Nicotine treatment significantly increased glomerular diameter compared to control group (p<0.05). as well as, nicotine administration significantly decreased TAC levels compared to saline group (P<0/05). Histopathology of the kidney confirmed the changes induced by nicotine and the renal protection effect of harmine. Conclusions: It seems that harmine administration could improve kidney changes and prevented nicotine-induced adverse effects on serum levels of nitric oxide, BUN and Creatinine and Total antioxidant capacity

Dynamic Compression of in situ Grown Living Polymer Brush: Simulation and Experiment

A comparative dynamic Monte Carlo simulation study of polydisperse living polymer brushes, created by surface initiated living polymerization, and conventional polymer monodisperse brush, comprising linear polymer chains, grafted to a planar substrate under good solvent conditions, is presented. The living brush is created by end-monomer (de)polymerization reaction after placing an array of initiators on a grafting plane in contact with a solution of initially non-bonded segments (monomers). At equilibrium, the monomer density profile \phi(z) of the LPB is found to decline as \phi(z) ~ z^{-\alpha} with the distance from the grafting plane z, while the distribution of chain lengths in the brush scales as c(N) ~ N^{-\tau}. The measured values \alpha = 0.64 and \tau = 1.70 are very close to those, predicted within the framework of the Diffusion-Limited Aggregation theory, \alpha = 2/3 and \tau = 7/4. At varying mean degree of polymerization (from L = 28 to L = 170) and effective grafting density (from \sigma_g = 0.0625 to \sigma_g = 1.0), we observe a nearly perfect agreement in the force-distance behavior of the simulated LPB with own experimental data obtained from colloidal probe AFM analysis on PNIPAAm brush and with data obtained by Plunkett et. al., [Langmuir 2006, 22, 4259] from SFA measurements on same polymer

Efficient Rewirings for Enhancing Synchronizability of Dynamical Networks

In this paper, we present an algorithm for optimizing synchronizability of complex dynamical networks. Based on some network properties, rewirings, i.e. eliminating an edge and creating a new edge elsewhere, are performed iteratively avoiding always self-loops and multiple edges between the same nodes. We show that the method is able to enhance the synchronizability of networks of any size and topological properties in a small number of steps that scales with the network size.Although we take the eigenratio of the Laplacian as the target function for optimization, we will show that it is also possible to choose other appropriate target functions exhibiting almost the same performance. The optimized networks are Ramanujan graphs, and thus, this rewiring algorithm could be used to produce Ramanujan graphs of any size and average degree