Functional Incapacity and Physical and Psychological Symptoms: How They Interconnect in Chronic Fatigue Syndrome

Background: It has been argued that perceived functional incapacity might be a primary characteristic of chronic fatigue syndrome ( CFS) and could be explained by physical symptoms. If so, it could be expected to be closely associated with physical, but not psychological symptoms. The study tests this hypothesis. Sampling and Methods: The sample consisted of 73 patients, with a diagnosis of CFS according to the Oxford criteria, randomly selected from clinics in the Departments of Immunology and Psychiatry at St. Bartholomew's Hospital, London. The degree of fatigue experienced by patients was assessed using the Chalder Fatigue Questionnaire and a visual analogue scale. Self-rated instruments were used to measure physical and social functioning, quality of life, and physical and psychological symptoms. Results: Principal-component analysis of all scale scores revealed 2 distinct components, explaining 53% of the total variance. One component was characterized by psychological symptoms and generic quality of life indicators, whilst the other component was made up of physical symptoms, social and physical functioning and indicators of fatigue. Conclusions: The findings suggest that perceived functional incapacity is a primary characteristic of CFS, which is manifested and/or explained by physical symptoms. Copyright (C) 2008 S. Karger AG, Base

Mean-Field Games for Distributed Caching in Ultra-Dense Small Cell Networks

In this paper, the problem of distributed caching in dense wireless small cell networks (SCNs) is studied using mean field games (MFGs). In the considered SCN, small base stations (SBSs) are equipped with data storage units and cooperate to serve users' requests either from files cached in the storage or directly from the capacity-limited backhaul. The aim of the SBSs is to define a caching policy that reduces the load on the capacity-limited backhaul links. This cache control problem is formulated as a stochastic differential game (SDG). In this game, each SBS takes into consideration the storage state of the other SBSs to decide on the fraction of content it should cache. To solve this problem, the formulated SDG is reduced to an MFG by considering an ultra-dense network of SBSs in which the existence and uniqueness of the mean-field equilibrium is shown to be guaranteed. Simulation results show that this framework allows an efficient use of the available storage space at the SBSs while properly tracking the files' popularity. The results also show that, compared to a baseline model in which SBSs are not aware of the instantaneous system state, the proposed framework increases the number of served files from the SBSs by more than 69%.Comment: Accepted for publication at American Control Conference 201

Load Shifting in the Smart Grid: To Participate or Not?

Demand-side management (DSM) has emerged as an important smart grid feature that allows utility companies to maintain desirable grid loads. However, the success of DSM is contingent on active customer participation. Indeed, most existing DSM studies are based on game-theoretic models that assume customers will act rationally and will voluntarily participate in DSM. In contrast, in this paper, the impact of customers' subjective behavior on each other's DSM decisions is explicitly accounted for. In particular, a noncooperative game is formulated between grid customers in which each customer can decide on whether to participate in DSM or not. In this game, customers seek to minimize a cost function that reflects their total payment for electricity. Unlike classical game-theoretic DSM studies which assume that customers are rational in their decision-making, a novel approach is proposed, based on the framework of prospect theory (PT), to explicitly incorporate the impact of customer behavior on DSM decisions. To solve the proposed game under both conventional game theory and PT, a new algorithm based on fictitious player is proposed using which the game will reach an epsilon-mixed Nash equilibrium. Simulation results assess the impact of customer behavior on demand-side management. In particular, the overall participation level and grid load can depend significantly on the rationality level of the players and their risk aversion tendency.Comment: 9 pages, 7 figures, journal, accepte

Cognitive Hierarchy Theory for Distributed Resource Allocation in the Internet of Things

In this paper, the problem of distributed resource allocation is studied for an Internet of Things (IoT) system, composed of a heterogeneous group of nodes compromising both machine-type devices (MTDs) and human-type devices (HTDs). The problem is formulated as a noncooperative game between the heterogeneous IoT devices that seek to find the optimal time allocation so as to meet their quality-of-service (QoS) requirements in terms of energy, rate and latency. Since the strategy space of each device is dependent on the actions of the other devices, the generalized Nash equilibrium (GNE) solution is first characterized, and the conditions for uniqueness of the GNE are derived. Then, to explicitly capture the heterogeneity of the devices, in terms of resource constraints and QoS needs, a novel and more realistic game-theoretic approach, based on the behavioral framework of cognitive hierarchy (CH) theory, is proposed. This approach is then shown to enable the IoT devices to reach a CH equilibrium (CHE) concept that takes into account the various levels of rationality corresponding to the heterogeneous computational capabilities and the information accessible for each one of the MTDs and HTDs. Simulation results show that the proposed CHE solution keeps the percentage of devices with satisfied QoS constraints above 96% for IoT networks containing up to 10,000 devices without considerably degrading the overall system performance.Comment: To appear in IEEE Transactions on Wireless Communications, 201

Integrating Energy Storage into the Smart Grid: A Prospect Theoretic Approach

In this paper, the interactions and energy exchange decisions of a number of geographically distributed storage units are studied under decision-making involving end-users. In particular, a noncooperative game is formulated between customer-owned storage units where each storage unit's owner can decide on whether to charge or discharge energy with a given probability so as to maximize a utility that reflects the tradeoff between the monetary transactions from charging/discharging and the penalty from power regulation. Unlike existing game-theoretic works which assume that players make their decisions rationally and objectively, we use the new framework of prospect theory (PT) to explicitly incorporate the users' subjective perceptions of their expected utilities. For the two-player game, we show the existence of a proper mixed Nash equilibrium for both the standard game-theoretic case and the case with PT considerations. Simulation results show that incorporating user behavior via PT reveals several important insights into load management as well as economics of energy storage usage. For instance, the results show that deviations from conventional game theory, as predicted by PT, can lead to undesirable grid loads and revenues thus requiring the power company to revisit its pricing schemes and the customers to reassess their energy storage usage choices.Comment: 5 pages, 4 figures, conferenc