Abstract
Multi-master replication in a distributed system setting allows each node holding a replica to update and query the local replica, and disseminate updates to other nodes. Obtaining high availability typically entails allowing replicas to diverge and requires a background mechanism for re-establishing consistency. Conflict-free Replicated Data Types (CRDTs) extend standard sequential data-Types with appropriate merge functions, and often can be composed together to create more complex ones. In this work we add a generic CRDT composition approach that explores the single-writer principle. By carefully controlling which part of the composition can be updated by each replica, we can derive efficient designs that cover new usecases. After introducing the new construction we exemplify some uses, including how to emulate a simple Doodle functionality for selecting a common meeting schedule among different participants.

Abstract
Cryptocurrency and blockchain technologies are recently gaining wide adoption since the introduction of Bitcoin, being distributed, authority-free, and secure. Proof of Work (PoW) is at the heart of blockchain's security, asset generation, and maintenance. Although simple and secure, a hash-based PoW like Bitcoin's puzzle is often referred to as "useless", and the used intensive computations are considered "waste" of energy. A myriad of Proof of "something" alternatives have been proposed to mitigate energy consumption; however, they either introduced new security threats and limitations, or the "work" remained far from being really "useful". In this work, we introduce Proof of eXercise (PoX): a sustainable alternative to PoW where an eXercise is a real world matrix-based scientific computation problem. We provide a novel study of the properties of Bitcoin's PoW, the challenges of a more "rational" solution as PoX, and we suggest a comprehensive approach for PoX.

Abstract
Meta-heuristic search methods are used to find near optimal global solutions for difficult optimization problems. These meta-heuristic processes usually require some kind of knowledge to overcome the local optimum locations. One way to achieve diversification is to start the search procedure from a solution already obtained through another method. Since this solution is already validated the algorithm will converge easily to a greater global solution. In this work, several well-known meta-heuristics are used to solve the problem of electricity markets participation portfolio optimization. Their search performance is compared to the performance of a proposed hybrid method (ad-hoc heuristic to generate the initial solution, which is combined with the search method). The addressed problem is the portfolio optimization for energy markets participation, where there are different markets where it is possible to negotiate. In this way the result will be the optimal allocation of electricity in the different markets in order to obtain the maximum return quantified through the objective function.

Abstract
In the last decade, several HRV based novel methodologies for describing and assessing heart rate dynamics have been proposed in the literature with the aim of risk assessment. Such methodologies attempt to describe the non-linear and complex characteristics of HRV, and hereby the focus is in two of these characteristics, namely long memory and heteroscedasticity with variance clustering. The ARFIMA-GARCH modeling considered here allows the quantification of long range correlations and time-varying volatility. ARFIMA-GARCH HRV analysis is integrated with multimodal brain monitoring in several acute cerebral phenomena such as intracranial hypertension, decompressive craniectomy and brain death. The results indicate that ARFIMA-GARCH modeling appears to reflect changes in Heart Rate Variability (HRV) dynamics related both with the Acute Brain Injury (ABI) and the medical treatments effects. © 2017, Springer International Publishing AG.

Abstract
Demand response is known as one of the basic components of smart grids that plays an important role in shaping load curves. In most of the prior reports on applying demand response programs, reactive power and load dependency to voltage magnitude have been ignored in distribution grids. In this paper, firstly, we show that the ignorance of the mentioned phenomena can cause a mismatch between the expected value of demand response and the experimental value. This mismatch is known as the demand response mismatch (DRM), which is dependent on some parameters such as load type, load reduction percentage, and network power factor. To overcome this problem, this paper presents a reactive power control model. In addition, a mixed integer nonlinear program is proposed to find the optimal size and location of STATCOMs and the optimal transformer tap settings that minimize the DRM. In this paper, the 16-bus U.K. generic distribution system (UKGDS) is employed to prove the capability of the presented method in DRM reduction.

Abstract
A long-period grating (LPG) written on a standard single mode fiber is investigated as a fiber optic sensor for vibration and magnetic field sensing. It is demonstrated the high sensitivity of the device to applied curvature and the possibility to monitor vibration in a wide range of frequencies from 30 Hz to 2000 Hz. The system was tested using intensity-based interrogation scheme, providing a frequency discrimination of 913 mHz. The goal of these tests was to evaluate the sensor as a passive vibration monitor in the detection of changes in resonant vibration frequencies of support infrastructures can provide information on its degradation. Furthermore, taking advantage of the intrinsic sensitivity to micro strain, alternating magnetic fields were also measured using an intensity-based interrogation scheme by coupling a Terfenol-D magnetostrictive rod to a pre-strained LPG sensor, providing a resolution below 5.61 mu T-rms/root Hz from 1.22 mT(rms) up to 2.53 mT(rms).