Abstract
The usage of small-sized unmanned aerial systems (UAS) has increased in the last years, in many different areas, being agriculture and forestry those who benefit the most from this relatively new remote sensing platform. Leaf area index, canopy and plant volume are among the parameters that can be determined using the very high resolution aerial data obtained by sensors coupled in unmanned aerial vehicles (UAV). This remote sensing technology affords the possibility of monitoring the vegetative development, identifying different types of issues, enabling the application of the most appropriated treatments in the affected areas. In this paper, a methodology allowing to perform multi-temporal UAS-based data analysis obtained by different sensors is proposed. A case study in vineyards and chestnuts is used to prove the benefits of continuous crop monitoring in its management and productivity of agroforestry parcels/activities. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
The aim of this study is twofold: first, to present a survey of the actual and most advanced methods related to the use of unmanned aerial systems (UASs) that emerged in the past few years due to the technological advancements that allowed the miniaturization of components, leading to the availability of small-sized unmanned aerial vehicles (UAVs) equipped with Global Navigation Satellite Systems (GNSS) and high quality and cost-effective sensors; second, to advice the target audience - mostly farmers and foresters - how to choose the appropriate UAV and imaging sensor, as well as suitable approaches to get the expected and needed results of using technological tools to extract valuable information about agroforestry systems and its dynamics, according to their parcels' size and crop's types. Following this goal, this work goes beyond a survey regarding UAS and their applications, already made by several authors. It also provides recommendations on how to choose both the best sensor and UAV, in according with the required application. Moreover, it presents what can be done with the acquired sensors' data through theuse of methods, procedures, algorithms and arithmetic operations. Finally, some recent applications in the agroforestry research area are presented, regarding the main goal of each analysed studies, the used UAV, sensors, and the data processing stage to reach conclusions.

Abstract
A methodology to rapidly produce environments that combine the intuition of in situ augmented reality (AR) with the commodity of virtual reality (VR) is proposed in this paper, by bringing together unmanned aerial systems (UAS) imagery and procedural modelling. While fully synthesized environments provide a very accurate visualization of the conserved parts of the real-world, missing parts - namely ruins - can be complemented with procedurally modelled structures. Regarding methodology's steps, firstly, a UAS flight mission gathers georeferenced imagery data about the site of interest. Then, the image set is converted to an accurate 3D model of the referred site, through photogrammetry. By considering the geographic information that also results from the previous process, ruins are manually outlined for georeferencing purposes. To complement ruins' missing information, virtual models of buildings are produced too, in a procedural modelling tool. Finally, at the full VR environment setup step, all elements are imported and subjected to geometric transformations that aim to match the procedurally modelled buildings with the outlined ruins. To improve the insight about the process work-flow, system's architecture and implementation are presented along with a case-study regarding a historically relevant site - Vila Velha's city gates (Vila Real, Portugal) - and preliminary results.

Abstract
It is well-known that information and communication technologies enable many tasks in the context of precision agriculture. In fact, more and more farmers and food and agriculture companies are using precision agriculture-based systems to enhance not only their products themselves, but also their means of production. Consequently, problems arising from large amounts of data management and processing are arising. It would be very useful to have an infrastructure that allows information and agricultural tasks to be efficiently shared and handled. The cloud computing paradigm offers a solution. In this study, a cloud-based software architecture is proposed with the aim of enabling a complete crop management system to be deployed and validated. Such architecture includes modules developed by using Google App Engine, which allows the information to be easily retrieved and processed and agricultural tasks to be properly defined and planned. Additionally, Google's Datastore (which ensures a high scalability degree), hosts both information that describes such agricultural tasks and agronomic data. The architecture has been validated in a system that comprises a wireless sensor network with fixed nodes and a mobile node on an unmanned aerial vehicle (UAV), deployed in an agricultural farm in the Region of Murcia (Spain). Such a network allows soil water and plant status to be monitored. The UAV (capable of executing missions defined by an administrator) is useful for acquiring visual information in an autonomous manner (under operator supervision, if needed). The system performance has been analysed and results that demonstrate the benefits of using the proposed architecture are detailed.

Abstract
An emerging trend in industry 4.0 is to use wireless communication infrastructure and mesh networks in applications requiring high reliability and safety. Although not a typical industrial production process, railway vehicular networks are also an industrial application which come with stringent reliability and safety requirements. Current research is focusing on using vehicular networks as an enabling technology to actively control the separation between two consecutive vehicles, enforcing a safe distance which is nevertheless much shorter than currently used to maintain vehicle separation. In this respect, we analyze a hopping strategy for Time-Slotted Channel-Hopping (TSCH), which was introduced in the IEEE 802.15.4e amendment with a view of improving the reliability of IEEE 802.15.4 networks. We define a probability framework to estimate the chance of successful hopping assuming two previously merged vehicles, and we design a zero-sum game and propose a payoff function to always place communicating nodes in a Nash equilibrium by choosing whether to hop or not, and therefore maximizing the communication throughput by mitigating jamming signals.

Abstract
Sous vide cook-chill (SVCC) is characterized by vacuum-packaging raw or partially prepared foods before pasteurization, followed by rapid chilling and storage below 3C. The application of essential oils (EOs) to food products is a suitable strategy to control pathogens and to extend their shelf life by reducing microbial levels and oxidative processes. The aim of this study was to evaluate the efficacy of Rosmarinus officinalis L. (rosemary) and Thymus vulgaris L. (thyme) EOs against Listeria monocytogenes ATCC 679, inoculated in beef processed by SVCC stored at 2 and 8C for 1, 2, 3, 7, 14, 21 and 28 days. The composition of EOs was identified by gas chromatography-mass spectrometry analysis. The main compounds identified in rosemary EO were eucalyptol (13.05%), camphor (8.93%), verbenone (8.58%), endo-borneol (7.87%) and alpha-pinene (6.78%) and in thyme EO were linalool (18.18%), thymol (7.48%), limonene (6.49%), endo-borneol (5.86%) and terpinen-4-ol (5.66%). Using the minimum inhibitory concentration (MIC) method, L. monocytogenes was inhibited at 3.9 mu L/mL to thyme EO and at 62.5 mu L/mL to rosemary EO. Beef samples of M. longissimus thoracis et lumborum were packaged in bags, inoculated and one of each EO was added at MIC values. Bags were vacuum-sealed and samples were processed at 55C/65 min for 3log(10) CFU/g reduction. A reduction of the counts of L. monocytogenes was observed in all samples at 2C. At 8C counts of L. monocytogenes were almost similar in control samples and those with thyme EO with an increase of themicrobial counts since day 7. Inversely, counts of L. monocytogenes in beef samples with rosemary EO stored at 2 and 8C decreased about 2 log(10) CFU. These results support the possibility of using rosemary EO as natural preservative due to its antimicrobial effect against L. monocytogenes. Also, our results confirm that an adequate chilling storage is essential to guarantee the safety of SVCC product regarding L. monocytogenes to avoid foodborne outbreaks.