On the Parameterized Complexity of Sparsest Cut and Small-set Expansion Problems

We study the NP-hard \textsc{$k$-Sparsest Cut} problem ($k$SC) in which, given an undirected graph $G = (V, E)$ and a parameter $k$, the objective is to partition vertex set into $k$ subsets whose maximum edge expansion is minimized. Herein, the edge expansion of a subset $S \subseteq V$ is defined as the sum of the weights of edges exiting $S$ divided by the number of vertices in $S$. Another problem that has been investigated is \textsc{$k$-Small-Set Expansion} problem ($k$SSE), which aims to find a subset with minimum edge expansion with a restriction on the size of the subset. We extend previous studies on $k$SC and $k$SSE by inspecting their parameterized complexity. On the positive side, we present two FPT algorithms for both $k$SSE and 2SC problems where in the first algorithm we consider the parameter treewidth of the input graph and uses exponential space, and in the second we consider the parameter vertex cover number of the input graph and uses polynomial space. Moreover, we consider the unweighted version of the $k$SC problem where $k \geq 2$ is fixed and proposed two FPT algorithms with parameters treewidth and vertex cover number of the input graph. We also propose a randomized FPT algorithm for $k$SSE when parameterized by $k$ and the maximum degree of the input graph combined. Its derandomization is done efficiently. \noindent On the negative side, first we prove that for every fixed integer $k,\tau\geq 3$, the problem $k$SC is NP-hard for graphs with vertex cover number at most $\tau$. We also show that $k$SC is W[1]-hard when parameterized by the treewidth of the input graph and the number~$k$ of components combined using a reduction from \textsc{Unary Bin Packing}. Furthermore, we prove that $k$SC remains NP-hard for graphs with maximum degree three and also graphs with degeneracy two. Finally, we prove that the unweighted $k$SSE is W[1]-hard for the parameter $k$

Beyond Distributed Subgraph Detection: Induced Subgraphs, Multicolored Problems and Graph Parameters

Subgraph detection has recently been one of the most studied problems in the CONGEST model of distributed computing. In this work, we study the distributed complexity of problems closely related to subgraph detection, mainly focusing on induced subgraph detection. The main line of this work presents lower bounds and parameterized algorithms w.r.t structural parameters of the input graph: - On general graphs, we give unconditional lower bounds for induced detection of cycles and patterns of treewidth 2 in CONGEST. Moreover, by adapting reductions from centralized parameterized complexity, we prove lower bounds in CONGEST for detecting patterns with a 4-clique, and for induced path detection conditional on the hardness of triangle detection in the congested clique. - On graphs of bounded degeneracy, we show that induced paths can be detected fast in CONGEST using techniques from parameterized algorithms, while detecting cycles and patterns of treewidth 2 is hard. - On graphs of bounded vertex cover number, we show that induced subgraph detection is easy in CONGEST for any pattern graph. More specifically, we adapt a centralized parameterized algorithm for a more general maximum common induced subgraph detection problem to the distributed setting. In addition to these induced subgraph detection results, we study various related problems in the CONGEST and congested clique models, including for multicolored versions of subgraph-detection-like problems

Free Reducing Agent, One Pot, and Two Steps Synthesis of Ag@SiO[2] Core-shells using Microwave Irradiation

In this work a new method for the fabrication of Ag@SiO[2] nanoparticles have been proposed that is completely different from Stober method. Ag nanoparticles were synthesized using microwave irradiation. polyvinylpyrrolidone was used as stabilizer and capping agent, 3-Aminopropyltriethoxysilane as functionalizer of silver particles in fully ethanol solution. The Ag nanoparticles were used subsequently without any subtraction and treatment in the preparation of Ag@SiO[2] core-shell nanoparticles. UV-Vis spectroscopy shows a characteristic plasmon peak at 400 nm and 430 nm for Ag nanoparticles and Ag@SiO[2] coreshells. Transmission electron microscope images show that Ag nanoparticles have the average size of 10 nm. It is also depicted that SiO[2] shell structure was formed uniformly with the average size of 10 nm. The application of 3-Aminopropyltriethoxysilane in the preparation of core-shells yields single Ag core structure

A COMPARATIVE STUDY ON THE CYTOTOXIC EFFECT OF DIFFERENT CONCENTRATIONS OF HYDROGEN PEROXIDE AND CARBAMIDE PEROXIDE ON THE SURVIVAL OF HUMAN DENTAL PULP STEM CELLS IN VITRO

Abstract. Background: Tooth discoloration due to different causes (systemic or acquired) is one of the major issues that has involved the dentists to itself. up to now, dental bleaching has been reported as the most conservative method of treating teeth discoloration. In most bleaching methods, hydrogen peroxide and carbamide peroxide derivatives are used at different concentrations. Considering that these materials are oxidative materials, in this study, we are trying to evaluate and compare the toxicity of different concentrations of these two materials on dental pulp stem cells. Materials andmethods: Human dental pulp stem cells (DPSCs) were extracted and cultured, and they were treated with 50, 100, 180, 250 and 300 μM concentrations of hydrogen peroxide and 1.9, 0.95, 0.71, 0.47 and 0.24 mg/ml concentrations of carbamide peroxide. Metabolic activity of the cells was evaluated by MTT test. Objective: The purpose of this study was to evaluate and compare the cytotoxic effects of various concentrations of hydrogen peroxide and carbamide peroxide on the survival of human dental pulp stem cells. Results: The results showed that viability of treated cells with hydrogen peroxide andcarbamide peroxide has decreased at high concentrations. IC50 was at 180 μM concentration from HP and 1.9 mg concentration of CP, which was statistically significant (P<0.05). Conclusion: The results of our studies showed that these two materials affect the growth of stem cells in a dose-dependent manner. These materials, at low concentrations, cause a esistance to oxidative stress, however, at high concentrations, they have toxic effects on cell growth. The fatal effect of hydrogen peroxide on cells is much more than the effect of carbamide peroxide on the same cell line. It can be concludedthat carbamide peroxide has less side effects than hydrogen peroxide and its use at a lower dose compared to hydrogen peroxide can be a good method for tooth bleaching.Keywords: Stem cells, Dental pulp, Apoptosis, Hydrogen peroxide, Carbamide peroxid

A closed-loop supply chain network in the edible oil industry using a novel robust stochastic-possibilistic programming

In recent years, the complexity of the environment, the intense competition of organizations, the pressure of governments on producers to manage waste products, environmental pressures and most importantly, the benefits of recycling products have added to the importance of designing a closed loop supply chain network. Also, the existence of inherent uncertainties in the input parameters is another important factor that the lack of attention them can affect the strategic, tactical and operational decisions of organizations. Given these reasons, this research aims to design a multi-product and multi period closed loop supply chain network model in uncertainty conditions. To this aim, first a mixed-integer linear programming model is proposed to minimize supply chain costs. Then, for coping with hybrid uncertain parameters effectively, randomness and epistemic uncertainty, a novel robust stochastic-possibilistic programming (RSPP) approach is proposed. Furthermore, several varieties of RSPP models are developed and their differences, weaknesses, strengths and the most suitable conditions for being used are discussed. Finally, usefulness and applicability of the RSPP model are tested via the real case study in an edible oil industry

Demand forecasting in a Supply Chain using Machine Learning Algorithms

Abstract—the purpose of this paper is to compare two artificial intelligence algorithms for forecasting supply chain demand. In first step data are prepared for entering into forecasting models. In next step, the modeling step, an artificial neural network and support vector machine is presented. The structure of artificial neural network is selected based on previous researchers' results. For measuring errors we use Mean squared error and we use another index for time which is used running the algorithms. The results show that artificial neural network can forecast more accurate meanwhile support vector machine is faster

A hybrid algorithm for unrelated parallel machines scheduling

In this paper, a new hybrid algorithm based on multi-objective genetic algorithm (MOGA) using simulated annealing (SA) is proposed for scheduling unrelated parallel machines with sequence-dependent setup times, varying due dates, ready times and precedence relations among jobs. Our objective is to minimize makespan (Maximum completion time of all machines), number of tardy jobs, total tardiness and total earliness at the same time which can be more advantageous in real environment than considering each of objectives separately. For obtaining an optimal solution, hybrid algorithm based on MOGA and SA has been proposed in order to gain both good global and local search abilities. Simulation results and four well-known multi-objective performance metrics, indicate that the proposed hybrid algorithm outperforms the genetic algorithm (GA) and SA in terms of each objective and significantly in minimizing the total cost of the weighted function

An Integrated Fuzzy Model for Selecting Resilient Suppliers in Electronics Industry of Iran

Selecting appropriate and resilient suppliers is an important issue in supply chain management (SCM) literature. Making an effective decision on this issue can decrease external risks and disruptions, purchase costs, and delay times and also guarantees business continuity in the event of disruptions and, consequently, increases company competitiveness and customer satisfaction. This paper aims to provide a model based on identifying and investigating related criteria to evaluate suppliers’ resilience and select the most resilient suppliers in Iran’s electronic industry. To this purpose, the screening technique, the best-worst methodology (BWM), and goal programming (GP) have been applied in the fuzzy environment. The proposed model has been implemented and demonstrated by a case study of the electronic industry, as a real-life example. The results show that agility (0.227), compatibility (0.153), and vulnerability (0.102) are the most important factors for a resilient supplier

A framework for online social networking features

Social networks form a basis for maintaining social contacts, finding users with common interests, creating local content and sharing information. Recently networks have created a fundamental framework for analyzing and modeling the complex systems. Users' behavior studies and evaluates the system performance and leads to better planning and implementation of advertising policies on the web sites. Therefore, this study offers a framework for online social networks' characteristics. In terms of objective, this survey is practical descriptive. Sampling has been done among 384 of graduate students who have good experiences of membership in online social network. Confirmatory factor analysis is used to evaluate the validity of variables in research model. Characteristics of online social networks are defined based on six components and framework's indexes are analyzed through factor analysis. The reliability is calculated separately for each dimension and since they are all above 0.7, the reliability of the study can be confirmed. According to our research results, in terms of size, the number of people who apply for membership in various online social networking is an important index. In terms of individual preference to connect with, people who are relative play essential role in social network development. In terms of homogeneity variable, the number of people who visit their friends’ pages is important for measuring frequency variable. In terms of frequency, the use of entertainment and recreation services is more important index. In terms of proximity, being in the same city is a more important index and index of creating a sense of belonging and confidence is more important for measuring reciprocity variable