A Model to Measure the Spread Power of Rumors

Nowadays, a significant portion of daily interacted posts in social media are infected by rumors. This study investigates the problem of rumor analysis in different areas from other researches. It tackles the unaddressed problem related to calculating the Spread Power of Rumor (SPR) for the first time and seeks to examine the spread power as the function of multi-contextual features. For this purpose, the theory of Allport and Postman will be adopted. In which it claims that there are two key factors determinant to the spread power of rumors, namely importance and ambiguity. The proposed Rumor Spread Power Measurement Model (RSPMM) computes SPR by utilizing a textual-based approach, which entails contextual features to compute the spread power of the rumors in two categories: False Rumor (FR) and True Rumor (TR). Totally 51 contextual features are introduced to measure SPR and their impact on classification are investigated, then 42 features in two categories "importance" (28 features) and "ambiguity" (14 features) are selected to compute SPR. The proposed RSPMM is verified on two labelled datasets, which are collected from Twitter and Telegram. The results show that (i) the proposed new features are effective and efficient to discriminate between FRs and TRs. (ii) the proposed RSPMM approach focused only on contextual features while existing techniques are based on Structure and Content features, but RSPMM achieves considerably outstanding results (F-measure=83%). (iii) The result of T-Test shows that SPR criteria can significantly distinguish between FR and TR, besides it can be useful as a new method to verify the trueness of rumors

Automatic Personality Prediction; an Enhanced Method Using Ensemble Modeling

Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically the Internet and social media), human communications have reformed notably from face to face communication. Generally, Automatic Personality Prediction (or Perception) (APP) is the automated forecasting of the personality on different types of human generated/exchanged contents (like text, speech, image, video, etc.). The major objective of this study is to enhance the accuracy of APP from the text. To this end, we suggest five new APP methods including term frequency vector-based, ontology-based, enriched ontology-based, latent semantic analysis (LSA)-based, and deep learning-based (BiLSTM) methods. These methods as the base ones, contribute to each other to enhance the APP accuracy through ensemble modeling (stacking) based on a hierarchical attention network (HAN) as the meta-model. The results show that ensemble modeling enhances the accuracy of APP

Arbutin attenuates nephrotoxicity induced by gentamicin

Objective: In this study, the impact of arbutin was examined in a gentamicin (GM)-induced nephrotoxicity model. Materials and Methods: Forty adult male Wistar rats were randomly assigned to five groups including control group; GM group, and three groups of GM+arbutin (25, 50 and 75 mg/kg). One day after the last injection of GM, creatinine, urea, carbonyl, thiobarbituric acid-reacting substance (TBARs), ferric reducing antioxidant power (FRAP) and 8-hydroxyguanosine levels were assessed in serum samples. Left and right kidneys were used for biochemical assays and histological evaluation, respectively. Results: Our data showed that the FRAP level (p<0.05), urea (p<0.001), creatinine (p<0.001), and 8-hydroxyguanosine (p<0.001) levels of serum samples, were increased in GM-treated rats compared to the controls. The serum levels of TBARS (p<0.001) and carbonyl increased in serum and renal tissue (p<0.001) of GM-treated animals. Conversely, arbutin attenuated serum creatinine, urea and 8-hydroxyguanosine, and TBARS (p<0.001). Administration of arbutin significantly decreased carbonyl levels in serum and renal tissue samples (p<0.001). Furthermore, the levels of FRAP increased in the serum (p<0.01) and renal tissue samples (p<0.001) of arbutin-treated animals. Histological staining showed that arbutin significantly inhibits kidney damages. Conclusion: Our data suggest that arbutin attenuates GM-induced nephrotoxicity through its free radicals-scavenging activity

High temperature optical absorption investigation into the electronic transitions in sol–gel derived C12A7 thin films

Optical absorption into 6 mm thick sol–gel derived films, annealed at 1300 °C of 12CaO·7Al2O3 calcium aluminate binary compound on MgO〈100〉 single crystal substrates was studied at temperatures ranging from room temperature to 300 °C. Experimental data were analysed in both Tauc and Urbach regions. The optical band gap decreased from 4.088 eV at 25 °C to 4.051 eV at 300 °C, while Urbach energy increased from 0.191 eV at 25 °C to 0.257 eV at 300 °C. The relationship between the optical band gap and the Urbach energy at different temperatures showed an almost linear relationship from which the theoretical values of 4.156 and 0.065 eV were evaluated for the band gap energy and Urbach energy of a 12CaO·7Al2O3 crystal with zero structural disorder at 0 K

Study of improved design and physical properties of 12CaO.7Al2O3 thin films

Calcium aluminate compound, 12CaO.7Al203, was prepared via an improved sol-gel technique in the form of thin film on magnesium oxide (MgO) single crystal substrate as well as powder. The microstructures of the films were observed before and after crystallization, and the effect of solution processing parameters, including the molar fractions of the ingredients, on the continuity of the films and the formation of surface defects was studied. An optimized sol-gel process using a new solution recipe was developed based on the microstructural observations. Homogeneous thin films of 12CaO.7Al203 with high critical thickness (~5 - 6 urn) were produced using this optimized technique. The chemical composition of the films was determined using energy dispersive spectroscopy and X-ray photoelectron spectroscopy. Raman and Fourier transform infrared (FTIR) spectral analyses were employed in order to investigate the effect of heat treatment temperature on the crystallization of 12CaO.7Al203 film on magnesium oxide substrate. The results of the phase analysis show that a single-phase film of 12CaO.7Al203 is formed at a temperature of 1300 QC. A crystallized structure with well-defined grain boundaries is obtained after 2 hr of heat treatment at this temperature under normal air atmosphere. The phase formation of 12CaO.7Al203 in powder form was investigated via room-temperature and high-temperature X-ray diffraction (XRO) and crystallization of 12CaO.7Al203 and CaO.Al203 powders started taking place simultaneously at a temperature of ~ 900°C. A comparison between the FTIR results of the films with XRD results of the powder proved the crystallization of 12CaO.7Al203 thin film to start at a higher temperature compared to the powder. Furthermore, a single-phase 12CaO.7Ah03 tends to form in thin film on MgO sub strate , whereas the formation of 12CaO.7Al203 is accompanied by the formation of secondary phases of CaO.Al203 and 3CaO.Al203. The optical absorption properties of the 12CaO.7Al203 films were investigated at different temperatures from room temperature to 300°C and the experimental data were analysed in Tauc and Urbach regions. The optical band gap decreased from 4.088 eV at 25°C to 4.051 eV at 300°C, while Urbach energy increased from 0.178- e V at 25°C to 0.257 e V at 300°C. The relationship between the optical band gap and the Urbach energy at different temperatures showed an almost linear relationship from which the theoretical values of 4.156 and 0.065 eV were evaluated for the band gap energy and Urbach energy of a 12CaO.7Al203 crystal with zero structural disorder at OK.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Review and Comparison between Clustering Algorithms with Duplicate Entities Detection Purpose

the issue of identifying iterative records issue is one of the challenging issues in the field of databases. As a result, finding appropriate algorithms in this field helps significantly to organize information and extract the correct answer from different queries of database. One of steps of duplicate detection is clustering. Clustering is a classification process of existing data sets into different clusters so that, the similarity among data within each cluster is maximum and similarity among the data of different clusters is at least. The aim of this paper is to find appropriate clustering algorithms for Iteration Detection issues on existing data set. In this paper, 4 algorithms, K-Means, Single-Linkage, DBSCAN and Self-Organizing Maps have been implemented and compared. F1 measure was used in order to measure accuracy and quality of clustering, that according to the obtained results, SOM algorithm obtained high accuracy. F1 measure was used in order to evaluate precision and quality of clustering that by studying the obtained results, the SOM algorithm obtained high F1 measure. Also a comparison between 2 methods, mapping to two dimensional space and statistical average, performed, that according to the results, mapping method is better than average method

The Effect of Number of Agents on Optimization of adaptivity Join Queries in Heterogeneous Distributed Databases

Distributed systems signify data distribution, association of activities, and controlling the distributed components of the system. Distributed systems are mostly used to share the workload or transfer data processing functions to a place nearer to those functions. This important task should be mentioned in database query optimization. The growing need for optimizing query processing in databases has given rise to many methods of doing this. This article provides a multi-agent system for heterogeneous distributed databases by combining optimization techniques for processing queries in databases and adaptivity. In this system the effect of the number of agents on optimization of query processing in Heterogeneous distributed databases will be analyzed. In this system an agent has been added to make the database adaptable. In this system the greatness of the effect of number of agents on optimization of processing of joined queries has been analyzed