Abstract
Autonomous underwater vehicles (AUVs) are increasingly being used to perform search operations but its capabilities are limited by the efficiency of the planning process. The objective of the paper is to propose new survey planning methods for AUVs. In particular, the problem of multi-objective search mission planning with an AUV navigating in known or unknown 3D environments is studied. The vehicle should completely cover the operating area while maximizing the probability of detecting the targets and minimizing the required energy and time to complete the mission. The approach presented here differs from other CPP methods in that paths for coverage are generated based on a coverage map that is actively maintained as the vehicle executed its mission. Our replanning approach borrows ideas from case-based reasoning (CBR) in which old problem and solution information helps solve a new problem. The resulting combination takes advantage of both paradigms where our evolutionary approach in conjunction with an artificial neural network (ANN), presented earlier, delivers robustness and adaptive learning while the case-based component speeds up the replanning process. The experiments show that the online algorithm was able to successfully replan missions in varied scenarios and guarantee full area coverage while minimizing resource consumption.

Abstract
The most widely used resiliency approach today, based on Checkpoint and Restart (C/R) recovery, is not expected to remain viable in the presence of the accelerated fault and error rates in future Exascale-class systems. In this paper, we introduce a series of pragma directives and the corresponding source-to-source transformations that are designed to convey to a compiler, and ultimately a fault-aware run-time system, key information about the tolerance to memory errors in selected sections of an application. These directives, implemented in the ROSE compiler infrastructure, convey information about storage mapping and error tolerance but also amelioration and recovery using externally provided functions and multi-threading. We present preliminary results of the use of a subset of these directives for a simple implementation of the conjugate-gradient numerical solver in the presence of uncorrected memory errors, showing that it is possible to implement simple recovery strategies with very low programmer effort and execution time overhead. © Springer International Publishing AG 2017.

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.

Abstract
Oxidative stress and mitochondrial dysfunction have been associated with metabolic and agerelated diseases. Thus, the prevention of mitochondrial oxidative damage is nowadays a recognized pharmacological strategy to delay disease progression. Epidemiological studies suggested an association between the consumption of polyphenol-rich diet and the prevention of different pathologies, including diseases with a mitochondrial etiology. The development of mitochondrialtargeted antioxidants based on dietary antioxidants may decrease mitochondrial oxidative damage. Herein, we report the design and synthesis of two new mitochondriotropic antioxidants based on hydroxybenzoic acids (AntiOxBENs). The results obtained showed that the novel antioxidants are accumulated inside rat liver mitochondria driven by the organelle transmembrane electric potential and prevented lipid peroxidation, exhibiting low toxicity. Some of the observed effects on mitochondrial bioenergetics resulted from an increase of proton leakage through the mitochondrial inner membrane. The new derivatives present a higher lipophilicity than the parent compounds (protocatechuic and gallic acids) and similar antioxidant and iron chelating properties. AntiOxBENs are valid mitochondriotropic antioxidant prototypes, which can be optimized and used in a next future as drug candidates to prevent or slow mitochondrial oxidative stress associated to several pathologies.

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.