Abstract
Kidney exchange programs have been set in several countries within national, regional or hospital frameworks, to increase the possibility of kidney patients being transplanted. For the case of hospital programs, it has been claimed that hospitals would benefit if they collaborated with each other, sharing their internal pools and allowing transplants involving patients of different hospitals. This claim led to the study of multi-hospital exchange markets. We propose a novel direction in this setting by modeling the exchange market as an integer programming game. The analysis of the strategic behavior of the entities participating in the kidney exchange game allowed us to prove that the most rational game outcome maximizes the social welfare and that it can be computed in polynomial time.

Abstract
One of the challenges in a kidney exchange program (KEP) is to choose policies that ensure an effective and fair management of all participating patients. In order to understand the implications of different policies of patient allocation and pool management, decision makers should be supported by a simulation tool capable of tackling realistic exchange pools and modeling their dynamic behavior. In this paper, we propose a KEP simulator that takes into consideration the wide typology of actors found in practice (incompatible pairs, altruistic donors, and compatible pairs) and handles different matching policies. Additionally, it includes the possibility of evaluating the impact of positive crossmatch of a selected transplant, and of dropouts, in a dynamic environment. Results are compared to those obtained with a complete information model, with knowledge of future events, which provides an upper bound to the objective values. Final results show that shorter time intervals between matches lead to higher number of effective transplants and to shorter waiting times for patients. Furthermore, the inclusion of compatible pairs is essential to match pairs of specific patient-donor blood type. In particular, O-blood type patients benefit greatly from this inclusion.

Abstract
The reliability and safety of industrial machines depends on their timely maintenance. The integration of Cyber Physical Systems within the maintenance process enables both continuous machine monitoring and the application of advanced techniques for predictive and proactive machine maintenance. The building blocks for this revolution-embedded sensors, efficient preprocessing capabilities, ubiquitous connection to the internet, cloud-based analysis of the data, prediction algorithms, and advanced visualization methods-are already in place, but several hurdles have to be overcome to enable their application in real scenarios, namely: the integration with existing machines and existing maintenance processes. Current research and development efforts are building pilots and prototypes to demonstrate the feasibility and the merits of advanced maintenance techniques, and this paper describes a system for the industrial maintenance of sheet metal working machinery and its evolution towards a full proactive maintenance system.

Abstract
In a collaborative conceptualisation process, the existence of several solutions for a given domain is a very common problem. Given this, specialists must reach a consensus on the concepts that will encompass the final solution. Therefore, this work aims to provide a tool for the integration of conceptual models in order to help specialists during the negotiation phase of developing the final shared model. This approach analyses the concepts of two models and shows the similar concepts to the specialists. The semantic similarity is obtained after three stages, namely: normalization, syntax analysis and semantic analysis. To evaluate the proposed approach, the values of precision and recall measures were calculated in two practical application scenarios. The obtained results proved to be better when compared to the existing tools when applied to semi-formal models (conceptual maps), and very close to the best tools focused on formal models (ontologies) integration.

Abstract
Globalization and the rapid market changes increased the perception in the Portuguese footwear industry that success in the value chain is closely tied to information sharing, the creation and development of collaborative networks, and the management of the knowledge of the various partners. Business to Business (B2B) and e- Commerce (eC) are a key opportunity, and at the same time, a challenge for contemporary companies. We believe that the insights provided in this paper allow theory and practice to better understand the reasons for the success of the Portuguese footwear industry and of its key cluster of Felgueiras. Based on the research conducted, we argue that there is a lack of B2B-eC initiatives in the footwear industry and the existing ones are still incipient. Furthermore, the existence of only one platform that to some extent addresses B2B-eC, also indicates that there is a need for greater research and development of approaches/technology allowing companies to explore opportunities to collaborate and negotiate among themselves.

Abstract
Nascent entrepreneurship has long been studied from a variety of perspectives. A major stream of work by psychologists and sociologists suggests that nascent entrepreneurs have distinctive traits and competences. A second focus for research has been studying the environment in which nascent entrepreneurs operates. Recently, the identification and exploitation of entrepreneurial opportunities has emerged as a third focus. In this paper we will address the following questions: (1) what are the individual characteristics of those individuals who are attracted to becoming an entrepreneur? (2) What are the environmental factors contributing to new venture creation? (3) What are the steps in the creation process? We will attempt to answer these three questions by arguing that the central process of nascent entrepreneurship is centred on opportunity recognition, evaluation and exploitation, and influenced by contextual factors (e.g. external knowledge) and personal characteristics and competences (e.g. internal knowledge).