Abstract
The liquefied natural gas (LNG) trade provides the means of trading gas globally and represents about 10% of the gas trade. The forecasts show the LNG business will grow, over the next 20 years, at about twice the rate of the whole gas trade. Although the current state of LNG trade is well studied, the literature on the future business structure of it is limited and conflictual. This work considers the future LNG business structure by comparing the development trajectories of the oil and LNG sectors. In addition, it assesses the conclusions drawn by researchers against this background and the current pattern of change in the industry. The comparison involves three stages: (1) trade flows-oil and LNG trade flows are very similar, mainly due to the common distribution of the oil and gas reserves. (2) Supply chain configuration-the international trade for both fuels is tanker based thus allowing for a similar market responsive trade policy, i.e., real-time destination selection (spot sale) at a global scale. (3) Institutional developments-the current transparent and competitive global oil trade, with prices dominated by physical and paper markets, was driven previously by long-term contracts, in the same manner as the current LNG business. This analysis, together with transaction cost economics, supports the argument that, in future, LNG spot trade will increase and give rise to a competitive and globally unified LNG market. Further-more, LNG pricing will become transparent and would be dominated by physical and paper markets benchmark prices. (C) 2016 John Wiley & Sons, Ltd.

Abstract
Time series forecasting is a challenging task, where the non-stationary characteristics of data portray a hard setting for predictive tasks. A common issue is the imbalanced distribution of the target variable, where some values are very important to the user but severely under-represented. Standard prediction tools focus on the average behaviour of the data. However, the objective is the opposite in many forecasting tasks involving time series: predicting rare values. A common solution to forecasting tasks with imbalanced data is the use of resampling strategies, which operate on the learning data by changing its distribution in favour of a given bias. The objective of this paper is to provide solutions capable of significantly improving the predictive accuracy on rare cases in forecasting tasks using imbalanced time series data. We extend the application of resampling strategies to the time series context and introduce the concept of temporal and relevance bias in the case selection process of such strategies, presenting new proposals. We evaluate the results of standard forecasting tools and the use of resampling strategies, with and without bias over 24 time series data sets from six different sources. Results show a significant increase in predictive accuracy on rare cases associated with using resampling strategies, and the use of biased strategies further increases accuracy over non-biased strategies. © 2017, Springer International Publishing Switzerland.

Abstract
The aim of this article is to give at least a partial answer to the question made in the title. Several works analyze the evolution of the corruption in different societies. Most of such papers show the necessity of several controls displayed by a central authority to deter the expansion of the corruption. However there is not much literature that addresses the issue of who controls the controller. This article aims to approach an answer to this question. Indeed, as it is well known, in democratic societies an important role should be played by citizens. We show that politically active citizens can prevent the spread of corruption. More precisely, we introduce a game between government and officials where both can choose between a corrupt or honest behavior. Citizens have a political influence that results in the prospects of a corrupt and a non-corrupt government be re-elected or not. This results in an index of intolerance to corruption. We build an evolutionary version of the game by means of the replicator dynamics and we analyze and fully characterize the possible trajectories of the system according to the index of intolerance to corruption and other relevant quantities of the model.

Abstract
The use of games in Education can encourage/demand students to apply deeper levels of knowledge and competences in solving problems - even if these are simulated or of controlled difficulty level - requiring more than the simple memorization and repetition expressed in tests. Game based approaches have a considerable potential in stimulating critical and strategic thinking that is highly compatible with Bologna's competency model and also make it possible to make learning a more collaborative social activity, which is crucial in the XXI century. The pedagogical team of the course in Human Resources Management of the Integrated Masters in Industrial Engineering and Management developed a gamification model based on a literature review and a reflection in order to support the development of competences, strategies and frameworks in the area of Social Sciences that typically these students somewhat resisted. This paper presents the rationale, system, platform and strategies as well as the main reflections this experiment sparked in students and professors. We believe this work can contribute to the development of game centred approaches in higher education, providing thinking points and insights for other researchers and lecturers.

Abstract
ObjectiveThe capacity of hair to absorb water causes changes in its physical and cosmetic properties under different environmental conditions. Hence, the control of hair volume in variable relative humidity settings is an important topic in cosmetics. The behaviour of two types of hair, Caucasian and Asian, was studied regarding their volume change in different relative humidity conditions. The ability of a peptide as a hair volume treatment was evaluated in two climate control formulations. MethodsTresses of the two types of hair were tested in two relative humidity (RH) conditions: (A) variable relative humidity (2h 40% RH, followed by 2h 90% RH and 2h of 40% RH), and (B) continuous high relative humidity (90% RH for 6h). Changes in the hair tress volume were assessed throughout time. Hair treated with two climate control formulations, with and without a peptide (KP peptide), were tested under the two relative humidity conditions. ResultsCaucasian hair had a higher change in volume compared to the Asian hair in variable and high relative humidity conditions. The hair volume increase when subject to high air humidity, and it was lower with the incorporation of a peptide into climate control formulations. ConclusionCaucasian hair showed higher volume than Asian hair when submitted to both relative humidity conditions. The incorporation of the peptide into the climate control formulations, a base (mostly composed of water approximate to 94%) and an ethanolic, was found to reduce the volume of Caucasian hair tresses. The presence of the peptide improved the hair volume change more than 60% in high relative humidity conditions.

Abstract
The IEC 61499 standard provides means to specify distributed control systems in terms of function blocks. For the deployment, each device may hold one or many logical resources, each consisting of a function block network with service interface blocks at the edges. The execution model is event driven (asynchronous), where triggering events may be associated with data (and seen as messages). In this paper, we propose a low-complexity implementation technique allowing to assess end-to-end response times of event chains spanning over a set of networked devices. Based on a translation of IEC 61499 to RTFM1-tasks and resources, the response time for each task in the system at the device-level can be derived using established scheduling techniques. In this paper, we develop a holistic method to provide safe end-to-end response times taking both intra and interdevice delivery delays into account. The novelty of our approach is the accuracy of the system scheduling overhead characterization. While the device-level (RTFM) scheduling overhead was discussed in previous works, the network-level scheduling overhead for switched Ethernets is discussed in this paper. The approach is generally applicable to a wide range of commercial off-the-shelf Ethernet switches without a need for expensive custom solutions to provide hard real-time performance. A behavior characterization of the utilized switch determines the guaranteed response times. As a use case, we study the implementation onto (single-core) Advanced RISC Machine (ARM)-cortex-based devices communicating over a switched Ethernet network. For the analysis, we define a generic switch model and an experimental setup allowing us to study the impact of network topology as well as 802.1Q quality of service in a mixed critical setting. Our results indicate that safe sub millisecond end-to-end response times can be obtained using the proposed approach.