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In this article, we manage the energy consumption of numerous intelligent homes and charging stations including several electric vehicles in real-time using a computationally efficient predictive controller. The studied scenario is made up of a couple of primary layers. At the low level of the hierarchical framework, users are clustered into different groups based on their vehicles' departure times. Meanwhile, the energy consumption of subordinate users is controlled by multiple aggregators, interaction among which is modeled as an aggregative game. The high-level interactive and distributed control problem can be solved by a predictive controller, wherein the terminal constraints related to the reference energy of each cluster's storage capacity are transferred to the end of the prediction horizon. Additionally, each aggregator can only exchange local data with some neighboring aggregators through an untrustable communication network. As a result of denial of service attacks on the aggregators' network, the strong connectivity of the communication graph may be directly destroyed, leading to performance degradation. To address such an issue, each aggregator reconstructs the attacked information of its neighbors using a linear combination of received data in the last two iterations. Furthermore, a time-ofuse pricing tariff whose value is small for faithful households is investigated so that convergence time remains unaltered. Practical examples are simulated to assess the usefulness of the proposed iterative algorithm. [ABSTRACT FROM AUTHOR]

In distribution networks, failure to smooth the load curve leads to voltage drop and power quality loss. In this regard, electric vehicle batteries can be used to smooth the load curve. However, to persuade vehicle owners to share their vehicle batteries, we must also consider the owners' profits. A challenging problem is that existing methods do not take into account the vehicle owner demands including initial and final states of charge and arrival and departure times of vehicles. Another problem is that battery capacity of each vehicle varies depending on the type of vehicle; which leads to uncertainties in the charging and discharging dynamics of batteries. In this paper, we propose a modified mean-field method so that the load curve is smoothed, vehicle owner demands are met, and different capacities of electric vehicle batteries are considered. The simulation results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Substance abuse is a maladaptive pattern of substance use through recurrent and significant adverse consequences related to the repeated use of substances appearing. Multiple variables affected on severity, duration and treatment of substance abuse disorders. In 2017, globally 271 million people were estimated to have used one or more illicit drugs. The aim of this causal-comparative study was the comparison of impulsiveness, ego strength, alexithymia and perceived social support in addicts who continued treatment and those who abandoned treatment. Methods: For this purpose, 180 participations referred to 3 drug rehabilitation center and after obtaining the consent and conveniently placed into three groups: medicinal, motivational and combined (medicinal-motivational) treatment randomly. Participations completed BIS (Barratt, 1994), Ego Strength Scale (Besharat, 2006), TAS-20 (Bagby, Parker & Taylor, 1994) and MSPSS (Zimet, Dahlem, Zimet & Farley, 1998) before and after the treatments. The number of people remained at the end of treatment were 45, 39 and 43 respectively in each group. For analyze the data non-parametric U Mann-Whitney test was used. Results: The results showed significant differences on impulsiveness, ego strength, alexithymia and perceived social support between Addicts Who Continued Treatment and Those Who Abandoned Treatment. Conclusion: Considering these variable can be effective in preventing, diagnosis and treatment of addiction. [ABSTRACT FROM AUTHOR]

In this paper, by introducing a new general state-space form for uncertain linear time-invariant fractional-order systems subjected to interval and polytopic uncertainties, two problems including robust stability analysis and robust stabilization of the presented systems are investigated. Subsequently, two sufficient conditions in terms of several linear matrix inequalities for the problems mentioned are concluded as two separate theorems. It is assumed that the fractional order α is a known constant belonging to 0 < α < 1 . Simulation results of two different numerical examples demonstrate that the provided sufficient conditions are applicable and effective for tackling robust stability and stabilization problems. [ABSTRACT FROM AUTHOR]