MATERIALISM, HEDONISM, SPIRITUALITY, AND SUBJECTIVE WELL-BEING: AN EMPIRICAL STUDY OF RISALE-I NUR (RN) READERS

Since the Enlightenment, particularly in the West, the quest for happiness has been primarily sought through material consumption. Although global capitalism has been successful in producing more wealth, many studies reveal that more wealth and consumption have not increased human happiness. Muslim scholar, Said Nursi, has argued that this failure to achieve happiness is due to the adherence to hedonic and materialist values at the expense of spiritual and moral values. He links the success of the Islamic exegesis, the Risale-i Nur (RN) to its novel approach to happiness. The purpose of this empirical study is to determine whether pleasures of Paradise or true happiness are more likely attained with a life that focuses on good deeds, virtues and spirituality. We designed and conducted a comprehensive internet-based electronic survey among 1523 Risale-i Nur readers to test Nursi’s argument. The survey was designed to capture the values/goals of RN readers and their subjective well-being through over 100 questions. The survey included the Satisfaction with Life Scale, the Social Well-Being Scale, and the Aspiration Index as well as additional items that queried three additional domains of intellectual life, honesty and fairness, and aesthetical life. The study reveals that the more participants read the RN, the more they report the value of spirituality, fairness and honesty, family and friendship, intellectual activities, personal growth, aesthetics experience, conformity, altruism, and health. Conversely, the more they read the RN, the less they value hedonic pleasures, popularity and fame, money and material gains, image making, and fear and anxiety

A Study of Superconducting Transformer with Short-Circuit Current Limitation

The paper presents physico-mathematical models for analyzing transient processes in electrical networks having transformers with a high temperature superconducting winding. One of the main purposes of the study is the investigation of the short circuit current limitation process with the use of a transformer with a high temperature superconducting winding, that allows the combination of two series-connected elements, transformer and reactor, in one device. The efficiency of this method for short circuit current limitation is provided by the fact that the critical value of superconducting winding temperature is exceeded under short circuit current flowing, then it passes into the normal state with a high impedance winding, thus limiting a short circuit current. It is important to know the moment when superconducting material passes into the normal state with the loss of superconductivity. For this purpose, the program for calculating the quantity of heat under short circuit current flowing before its interruption was developed. If a 40 MVA transformer with a high temperature superconducting winding is considered, short circuit should be cleared after 100 ms without transformer disconnection. It is proposed to use a hybrid winding in addition to the main winding for short circuit current limitation. Conducted investigations showed that the return of a winding into the superconducting state depends primarily on the ratio between a short circuit current and a rated load current. This represents the criterion for returning or not returning into the superconducting state for transformer windings

Management Options for Patients with Chronic Back Pain Without an Etiology

The treatment and management of low back pain is complex when there is no specific etiology such as cancer, fracture, or herniated disc. An organized approach to management that follows evidence based guidelines will facilitate care in a problem that reflects a lifetime prevalence of over 70 percent. The purpose of this review is to present a guideline to care for a common disabling process with a very heterogeneous etiology

A Study of Thermal Behaviour of HTS Devices at Alternating Current

The paper presents a study on thermal behavior of a coil made of a high-temperature supercon-ducting tape representing operation of a superconducting device (for example, a transformer). Based on the results of a physical experiment, a mathematical model of superconducting coil op-eration under short circuit conditions at the load side was developed. Regimes of overheating by variable short circuit currents were investigated. In this case, short circuit current amplitudes ex-ceeded a critical current of a superconductor, and coil parameters (e.g. an average nonlinearity parameter of a current-voltage characteristic, a superconductor length, and others) were varied. Permissible overheating for a coil with the possibility of its return into the superconducting state after emergency conditions in a dead-time period of automatic reclosing was considered. A crite-rion for return of a superconducting device into the superconducting state within a dead-time period of automatic reclosing has been obtained

Swarm algorithms in dynamic optimization problem of reactive power compensation units control

Optimization of a power supply system is one of the main directions in power engineering research. The reactive power compensation reduces active power losses in transmission lines. In general, researches devoted to allocation and control of the compensation units consider this issue as a static optimization problem. However, it is dynamic and stochastic optimization problem that requires a real-time solution. To solve the dynamic optimization NP-hard problem, it is advisable to use Swarm Intelligence. This research deals with the problem of the compensation units power control as a dynamic optimization problem, considering the possible stochastic failures of the compensation units. The Particle Swarm Optimization and the Bees Algorithm were applied to solve it to compare the effectiveness of these algorithms in the dynamic optimization of a power supply system

Swarm intelligence algorithms for the problem of the optimal placement and operation control of reactive power sources into power grids

Deep reactive power compensation allows for reduction of active power losses in transmission lines of power supply systems. The efficiency of the compensation depends on the allocation of reactive power compensation units (RPCUs) at the nodes of a network. In general, investigations devoted to the study of optimal allocation of the compensation units have revealed that it is a static and deterministic optimization problem that can be solved by heuristic methods. However, in real systems, it is reasonable to consider such optimization problems, taking into account the dynamic and stochastic properties of the problems. These properties are the result of equipment failures and operational changes in technical systems. In addition, optimizing the allocation of the compensation units is the NP-hard multifactor problem. Under these circumstances, it is advisable to use the swarm intelligence algorithms. Swarm intelligence is a relatively new approach to solving the optimization problem, which takes inspiration from the behaviour of ants, birds, and other animals. Advantages of swarm algorithms are most evident if problems involve the dynamic or stochastic nature of the objective function and constraints. Contrary to a number of similar studies, this research considers the problem of the optimal allocation of compensation units as a dynamic problem, taking into account the possible random failures of the compensation equipment. The optimization problem has been solved by two Swarm Intelligence algorithms (the Particle Swarm optimization and the Artificial Bee Colony optimization) and Genetic algorithms. It has been aimed at comparing the effectiveness of the algorithms for solving such problems. It was found that swarm algorithms could be successfully applied in the operation control of compensation units in real-time. © 2017 WIT Press

Implementation of Population Algorithms to Minimize Power Losses and Cable Cross-Section in Power Supply System

The article dues to the arrangement of the reactive power sources in the power grid to reduce the active power losses in transmission lines and minimize cable cross-sections of the lines. The optimal arrangement is considered from two points of view. In the first case, it is possible to minimize the active power losses only. In the second case, it is possible to change the cross-sections of the supply lines to minimize both the active power losses and the volume of the cable lines. The sum of the financial cost of the active power losses, the capital investment to install the deep reactive power compensation, and cost of the cable volume is introduced as the single optimization criterion. To reduce the losses, the deep compensation of reactive power sources in nodes of the grid are proposed. This optimization problem was solved by the Genetic algorithm and the Particle Swarm optimization algorithm. It was found out that the deep compensation allows minimizing active power losses the cable cross-section. The cost-effectiveness of the suggested method is shown. It was found out that optimal allocation of the reactive power sources allows increasing from 9% to 20% the financial expenses for the enterprise considered