Abstract
The design of retail backroom storage has a great impact on in-store operations, customer service levels and store life-cycle costs. Moreover, backroom storage in modern retail stores is crucial to several functions, such as acting as a buffer against strong demand lifts yielded by an increasing promotional activity, seasonal peak demand and e-commerce activities. Despite having similar functions to a distribution center, backroom storage facilities have particularities that deserve a distinct analysis. In this paper we aim to draw attention to the lack of research about this topic.

Abstract
Temperature and water status profiles during the growing season are the most important factors influencing the ripening of wine grapes. To model weather influences on the quality and productivity of the vintages, it is necessary to partition the growing season into smaller growth intervals in which weather variables are evaluated. A significant part of past and ongoing research on the relationships between weather and wine quality uses calendar-defined intervals to partition the growing season. The phenology of grapevines is not determined by calendar dates but by several factors such as accumulated heat. To examine the accuracy of different approaches, this work analyzed the difference in average temperature and accumulated precipitation using growth intervals with boundaries defined by means of estimated historical phenological dates and intervals defined by means of accumulated heat or average calendar dates of the Douro Valley of Portugal. The results show that in situations where there is an absence of historical phenological dates and/or no available data that makes the estimation of those dates possible, it is more accurate to use grapevine heat requirements than calendar dates to define growth interval boundaries. Additionally, we analyzed the ability of the length of growth intervals with boundaries based on grapevine heat requirements to differentiate the best from the worst vintage years with the results showing that vintage quality is strongly related to the phenological events. Finally, we analyzed the variability of growth interval lengths in the Douro Valley during 1980-2009 with the results showing a tendency for earlier grapevine physiology.

Abstract
It is crucial to promote the use of cleaner transport modes, and new technologies are key to achieve this goal. Most mobile-based solutions are focused on services related with the journey itself (mobile ticketing, real-time traffic information and trip planners). Adopting a holistic point of view, and considering every trip has a purpose (work, school, shopping and entertainment), a new service approach is considered. This paper presents a multiservice approach that links city services and public transport to encourage the use of sustainable transport modes. This multiservice approach is based on mobile technologies, which are a unique channel of interaction between service providers and customers. The conceptual model of this approach is materialized in a concrete example. This multiservice approach may represent a step towards a sustainable mobility, while improving the image and efficiency of Public Transport Operators (PTOs), boosting local businesses loyalty and sales and bringing convenience, better service quality and monetary savings to customers.

Abstract
In recent years, the significant advancements in miniaturised computing and pervasive communication networks have paved the way for ubiquitous computing environments. In such environments users interact with systems through novel and implicit methods. In this context, affective computing provides a dimension of interaction, raising a number of opportunities to address not only utilitarian but also hedonic needs. At the same time, a number of challenges arise beyond the technical aspects, that are related to the individual and other societal implications. A review of the main opportunities and challenges is presented, supporting the identification of the main requirements for the design and development of systems in interactive pervasive environments, focusing on an affective loop of interaction. A framework is proposed, identifying main modules and functionality alongside a methodology to instantiate in specific domains of application.

Abstract
In a time of economic austerity, more pressure is being put on the existing transport systems to be more sustainable and, at the same time, more equitable and socially inclusive. Regular public road transportation traditionally uses fixed routes and schedules, which can be extremely expensive in rural areas and certain periods of the day in urban areas due to low and unpredictable demand. Demand Responsive Transportation systems are a kind of hybrid transportation approach between a taxi and a bus that try to address these problems with routes and frequencies that may vary according to the actual observed demand. Demand Responsive Transportation seems to have potential to answer the sustainability and social inclusion challenges in a context of austerity. However, DRT projects may fail: it is not only important to solve the underlying model in an efficient way, but also to understand how different ways of operating the service affect customers and operators. To help design DRT services, we developed an innovative approach integrating simulation and optimization. Using this simulator, we compared a real night-time bus service in the city of Porto, Portugal, with a hypothetical flexible DRT service for the same scenario.

Abstract
In the last decade, public transportation providers have focused on improving infrastructure efficiency as well as providing travellers with relevant information. Ubiquitous environments have enabled traveller information systems to collect detailed transport data and provide information. In this context, journey prediction becomes a pivotal component to anticipate and deliver relevant information to travellers. Thus, in this work, to achieve this goal, three steps were defined: (i) firstly, data from smart cards were collected from the public transport network in Porto, Portugal; (ii) secondly, four different traveller groups were defined, considering their travel patterns; (iii) finally, decision trees (J48), Naive Bayes (NB), and the Top-K algorithm (Top-K) were applied. The results show that the methods perform similarly overall, but are better suited for certain scenarios. Journey prediction varies according to several factors, including the level of past data, day of the week and mobility spatiotemporal patterns.