Defending recommender systems by influence analysis

Collaborative filtering (CF) is a popular method for personalizing product recommendations for e-commerce applications. In order to recommend a product to a user and predict that user’s preference, CF utilizes product evaluation ratings of like-minded users. The process of finding like-minded users forms a social network among all users and each link between two users represents an implicit connection between them. Users having more connections with others are the most influential users. Attacking recommender systems is a new issue for these systems. Here, an attacker tries to manipulate a recommender system in order to change the recommendation output according to her wish. If an attacker succeeds, her profile is used over and over again by the recommender system, making her an influential user. In this study, we applied the established attack detection methods to the influential users, instead of the whole user set, to improve their attack detection performance. Experiments were conducted using the same settings previously used to test the established methods. The results showed that the proposed influence-based method had better detection performance and improved the stability of a recommender system for most attack scenarios. It performed considerably better than established detection methods for attacks that inserted low numbers of attack profiles (20–25 %).     

Understanding the rise of e-participation in non-democracies: Domestic and international factors

While it has often been suggested that information and communication technologies (ICTs) provide an important means of increasing citizen participation (which is at the core of democratic government), few commentators have expected non-democracies to create online environments in which citizens can take an active part in political processes. In recent years, however, some non-democracies have begun to outperform countries with long-standing democratic traditions in terms of e-participation development. According to the 2010 United Nations (UN) e-government survey, Bahrain outranks France, Kazakhstan beats Sweden and Malaysia ranks higher than Germany. This article sets out to understand the recent rise of e-participation initiatives in non-democracies. Drawing on comparative longitudinal data from the UN e-government surveys, we tested the assertion that international drivers of change are competing with the dominant focus on domestic factors, especially in the non-democratic world, and are influencing the patterns of reform. The empirical analysis demonstrated important differences between the drivers of change in democratic and non-democratic countries and found economic globalization to be the strongest predictor of e-participation initiatives in non-democratic countries. In conclusion, we argue that economic globalization alters the context of e-participation and necessitates a re-examination of many of its premises and tenets.     

Investigating the potential of using acoustic frequency on the degradation of linear alkylbenzen sulfonates from aqueous solution

The effectiveness of using acoustical (sonochemical) reactor for degradation of linear alkylbenzen sulfonate (LAS) from aqueous solution was investigated. LASs are anionic surfactants,found in relatively high amounts in domestic and industrial wastewaters. In this study,experiments on LAS solution were performed using methylene blue active substances (MBAS) method. The effectiveness of acoustical processor reactor for LAS degradation is evaluated with emphasis on the effect of treatment time and initial LAS concentration. Experiments were performed at initial concentrations of 0.2,0.5,0.8 and 1.0 mg/L,acoustic fre-quency of 130 kHz,applied power of 500 W and temperature of 18 °C～20 °C. At the conditions involved,LAS degradation was found to increase with increasing sonochemical time. In addition,as the concentration increased,the LAS degradation rate de-creased in the acoustical processor reactor.     

Examining learning approaches of science student teachers according to the class level and gender

There are many factors influence the level of students＇ achievement in education. Studies show that one of these factors is ＂learning approach of a student＂. Research findings generally have identified two approaches of learning： deep and surface. When a student uses the deep approach, he/she has an intrinsic interest in subject matter and is interested in ideas and conclusions to understand the subject matter. When a student employs the surface approach, he/she merely memorizes knowledge to pass any exam in school. The aim of this study is to determine learning approaches of science student teachers and to examine the relationships among the variables, such as level of students＇ class and gender. The sample of this study consists of 108 student teachers from the Science Education Program at Department of Primary Science Education in Karadeniz Technical University. Approaches to learning of science student teachers are assessed using the Revised Two-factor Study Process Questionnaire （R-SPQ-2F）, a scale developed by Biggs, et al （2001） consisting of 20 items on a 5 point Likert Scale. According to findings, science student teachers generally have deep learning approaches. Moreover, learning approaches of science student teachers have not changed related to gender.     

The Assessment of Oxidative Stress on Patients with Chronic Renal Failure at Different Stages and on Dialysis Patients Receiving Different Hypertensive Treatment

The aim of this study is to evaluate the oxidative stress in predialysis, hemodialysis (HD) and peritoneal dialysis patients and to test the effects of antihypertensive drugs and volume control on oxidative stress parameters. The study was composed of five groups as follows: control group (n = 30), predialysis group (n = 30), peritoneal dialysis group (n = 30), hemodialysis group, (normotensive with strict volume control, n = 30), hemodialysis group (normotensive with medication, n = 30). Plasma malondialdehyde (MDA), erythrocyte superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSHPx) and routine biochemical parameters were studied in all patients. Hemodialysis patients with strict volume control (HD_vc) had lower levels of MDA than other patient groups (p < 0.001), and CAT, SOD values had highest level other patient groups (p < 0.001). The treatment of hypertension with strict volume control in chronic renal failure patients causes less damage to the antioxidant capacity.     

Science Letters: Low-cost fault tolerance in evolvable multiprocessor systems: a graceful degradation approach

The evolvable multiprocessor (EvoMP), as a novel multiprocessor system-on-chip (MPSoC) machine with evolvable task decomposition and scheduling, claims a major feature of low-cost and efficient fault tolerance. Non-centralized control and adaptive distribution of the program among the available processors are two major capabilities of this platform, which remarkably help to achieve an efficient fault tolerance scheme. This letter presents the operational as well as architectural details of this fault tolerance scheme. In this method, when a processor becomes faulty, it will be eliminated of contribution in program execution in remaining run-time. This method also utilizes dynamic rescheduling capability of the system to achieve the maximum possible efficiency after processor reduction. The results confirm the efficiency and remarkable advantages of the proposed approach over common redundancy based techniques in similar systems.     

Robust simultaneous fault detection and control for a class of nonlinear stochastic switched delay systems under asynchronous switching

This paper concerns the simultaneous fault detection and control (SFDC) problem for a class of nonlinear stochastic switched systems with time-varying state delay and parameter uncertainties. The switching signal of detector/controller unit (DCU) is assumed to be with switching delay, which results in the asynchronous switching between the subsystems and DCU. By constructing a switching strategy depending on the state and switching delays, new sufficient conditions expressed by a set of linear matrix inequalities (LMIs) is derived to design DCU gains. This problem is formulated as an H_∞ optimization problem and both mean square exponential stability and fault detection of augmented system are considered. A numerical example is finally exploited to verify the effectiveness and potential of the achieved scheme.     

Design of a H∞ model reference tracking control for interconnected nonlinear systems by decentralized dynamic output-feedback

This study investigates the problem of robust tracking control for interconnected nonlinear systems affected by uncertainties and external disturbances. The designed H_∞ dynamic output-feedback model reference tracking controller is parameterized in terms of linear matrix inequalities (LMIs), which is formulated within a convex optimization problem readily implementable. The resolution of such a problem, guarantying not only the quadratic stability but also a prescribed performance level of the resulting closed-loop system, enables to calculate concurrently the robust decentralized control and observation gain matrices. The established LMI conditions are computed in a single-step resolution to obtain all the controller/observer parameters and therefore to overcome the problem of iterative algorithm based on a multi-stage resolution leading in most cases to conservative and suboptimal solutions. Numerical simulations on diverse applications ranging from a numerical academic example to coupled inverted double pendulums and a 3-strongly interconnected machine power system are provided to corroborate the merit of the proposed control scheme.     

Evaluation of C4b as an adjunct marker in symptomatic RT-PCR negative Covid-19 cases

IntroductionDetecting low viral load has been a challenge in this pandemic, which has led to its escalated transmission. Complement activation has been implicated in pathogenesis of Covid-19 infection. Thus, evaluation of complement activation in suspected Covid-19 infection may help to detect infection and limit false negative cases thus limiting transmission of infection. We speculate that measuring C4b, produced from an activated complement system due to the presence of Covid-19 may help in its detection, even when the viral titers are low.MethodsPlasma C4b levels of symptomatic RT-PCR positive patients (cases, n = 40); symptomatic RT-PCR negative patients (n = 35) and asymptomatic RT-PCR negative controls (n = 40) were evaluated. Plasma C5b-9, IL-6, D-dimer and C1-Inhibitor (C1-INH) were also measured in cases and controls. ELISA kits were used for all measurements. Statistical analyses were carried out using Stata, version 12 (Stata Corp., Texas, USA).ResultsC4b levels were found to be significantly increased in RT-PCR positive patients as compared to asymptomatic RT-PCR negative controls. RT-PCR negative but symptomatic patients still showed increased C4b levels. The significantly higher levels of C4b in cases with a cut-off value of ≥ 116 ng/ml with optimum sensitivity and specificity of 80% and 52% respectively is indicative of its possible use as an adjunct marker. Increased levels of D-dimer, IL6, along with decreased levels of C1-INH were found in cases compared to controls. Whereas, C5b-9 levels were not significantly raised in cases.ConclusionsThe results of our study suggests that plasma C4b may help to detect infection in false negative cases of RT-PCR that escape detection owing to low viral load. However, to confirm it a large-scale study is needed.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12291-022-01033-z.