Abstract
Assessing eco-efficiency of companies is important to ensure the creation of wealth without compromising the needs of future generations. This work aims to extend the eco-efficiency concept by including in the assessment new features related to environmental benefits and environmental burdens. This concept is implemented using an innovative Directional Distance Function model, which searches for improvements in the magnitude of the indicators and in the composition of the resources consumed. This framework can help firms to become more sustainable by replacing non-renewable inputs with "greener" alternatives. We present an empirical application to large mining companies. Different scenarios regarding managerial priorities for adjustments to firms' economic and environmental indicators are explored. The results obtained and their managerial implications are discussed in the context of mining firms activity.

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Abstract
The growth of wireless networks has resulted in part from requirements for connecting people and advances in radio technologies. Wireless sensor networks are an example of these networks in which a large number of tiny devices interacting with their environments may be internet-worked together and accessible through the Internet. As these devices may be scattered in an unplanned way, a routing protocol is needed. The RPL protocol is the IETF proposed standard protocol for IPv6-based multi-hop WSN. RPL requires that communication paths go through a central router which may provide suboptimal paths, not considering the characteristics of the applications the nodes run. In this paper is proposed an Application-Driven extension to RPL which enables to increase the WSN lifetime by limiting the routing and forwarding functions of the network mainly to nodes running the same application. As nodes may join a network at a non predictable time, they must be synchronized with respect to their application duty cycles. Therefore, nodes have to wake up and sleep in a synchronized way. In this paper it is also proposed such synchronization mechanism. The results confirm that the proposed solutions provide lower energy consumption and lower number of packets exchanged than the conventional RPL solution, while maintaining fairness and the packet reception ratio high.

Abstract
Inspection of railroad tracks is still predominantly performed visually by human inspectors. Due to the extension of the tracks this is a slow and tedious operation, significantly subjected to human errors and inconsistency. In this context, computer vision systems, composed of field-acquired images and processing algorithms, have a great potential to improve efficiency and to offer systematic inspection methodologies. In this paper the use of available point cloud and mesh generation algorithms to construct 3D surface of railroad tracks is investigated. To achieve this goal, images of a small track were acquired from several points-of-view. Next a comparison between several open and closed-source algorithms was performed, evaluating the number of 3D points, time consumption, RAM memory, GPU memory, number of faces, and the generated mesh. The results obtained demonstrate that with the right setup, current image processing methodologies can be used to construct 3D surfaces of uncontrolled scenarios, such as those of a real railroad environment. Regarding the comparison, SURE and Poisson presented the most accurate meshes. When comparing quantitative measures, though, Poisson presented a slightly better performance in time consumption, but SURE had a better RAM memory usage and a greater level of details. © 2017 IEEE.

Abstract
Knowledge regarding Ecosystem Services (ES) delivery and the socio-ecological factors that influence their proficiency is essential to allow cities to adopt policies that lead to resource-efficient planning and greater resilience. As one of the matrix elements of urban ecological structure, vegetation may play a major role in promoting ES proficiency through planting design. This research addresses the heterogeneity of ES delivered by the urban vegetation of Porto, a Portuguese city. A methodology is proposed to investigate associations between socioeconomic indicators and structural variables of the urban forest, and also which structural variables of the urban forest, if any, differ along a socioeconomic gradient. Our results reveal that before setting planning and management goals, it is crucial to understand local patterns of ES and their relationships with socioeconomic patterns, which can be affected by variables such as building age. This should be followed by the identification of structural variables of the urban forest that better explain the differences, in order to target these through planning and management goals. The conceptual framework adopted in this research can guide adaptation of our methodology to other cities, providing insights for planning and management suitable to site-specific conditions and directly usable by stakeholders.