Abstract

Abstract
Localization and Mapping of autonomous robots in an harsh and unstable environment such as a steep slope vineyard is a challenging research topic. Dead Reckoning systems can fail due to the harsh conditions of the terrain, and the Global Position System can be affected by noise or even be unavailable. Agriculture is moving towards precision agriculture, with advanced monitoring systems and wireless sensor networks. These systems and wireless sensors are installed in the crop field and can be considered relevant landmarks for robot localization. In this paper the distance accuracy provided by bluetooth based sensors is deeply studied and characterized. It is considered a multi antenna receiver bluetooth system and obtained the transfer functions (from Received Signal Strength Indication (RSSI) to distance estimation) for each set of antenna and sensors. The performance of this technology is compared against Time-of-flight based technologies (Pozyx). The obtained results show that the agricultural wireless sensors can be used as redundant artificial landmarks for localization purposes. Besides, the RSSI characterization allowed to improve the previous results of our Beacon Mapping Procedure (BMP) required for accurate and reliable localization systems.

Abstract
In Portugal, tetrahydrobiopterin (BH4)-responsive patients with phenylketonuria (PKU) are identified using a loading test (LT). Phenylalanine/natural protein (Phe/NP) intake is increased to elevate blood Phe prior to the LT. In a longitudinal retrospective study, the impact of Phe/NP titration post-LT in 58 patients (19.6 ± 8.2 years) with PKU during 4 study periods (SPs) was examined. In SP1 (2010-2013), patients were diet treated only; in SP2 (2014), the Phe/NP titration was followed by the LT in SP3 (2015). In SP4 (2016), patients received diet treatment only (n = 49) or BH4 + diet (n = 9). The median percentage blood Phe within the target range was higher in SP1 versus SP4 (64 [28-85] vs 45 [0-66]; P <.001). Our results suggest that transient Phe/NP titration, associated with a deliberate increase in NP, may adversely affect metabolic control. Controlled studies are necessary to examine the longer term impact of temporary increased NP with BH4 LT in non-BH4-responsive patients.

Abstract
This article presents original probabilistic price forecasting meta-models (PPFMCP models), by aggregation of competitive predictors, for day-ahead hourly probabilistic price forecasting. The best twenty predictors of the EEM2016 EPF competition are used to create ensembles of hourly spot price forecasts. For each hour, the parameter values of the probability density function (PDF) of a Beta distribution for the output variable (hourly price) can be directly obtained from the expected and variance values associated to the ensemble for such hour, using three aggregation strategies of predictor forecasts corresponding to three PPFMCP models. A Reliability Indicator (RI) and a Loss function Indicator (LI) are also introduced to give a measure of uncertainty of probabilistic price forecasts. The three PPFMCP models were satisfactorily applied to the real-world case study of the Iberian Electricity Market (MIBEL). Results from PPFMCP models showed that PPFMCP model 2, which uses aggregation by weight values according to daily ranks of predictors, was the best probabilistic meta-model from a point of view of mean absolute errors, as well as of RI and LI. PPFMCP model 1, which uses the averaging of predictor forecasts, was the second best meta-model. PPFMCP models allow evaluations of risk decisions based on the price to be made.

Abstract
Industrial Symbiosis (IS) envisages a collaborative approach to resource efficiency, encouraging companies to recover, reprocess and reuse waste within the industrial network. Several challenges regarding the effective application of IS continue to limit a broader implementation of this area of Industrial Ecology. The MAESTRI project encompasses an Industrial Symbiosis approach within the scope of sustainable manufacturing for process industries that fosters the sharing of resources (energy, water, residues, etc.) between different processes of a single company or between multiple companies. The Industrial Symbiosis approach is integrated with Efficiency Framework in the so-called MAESTRI Total Efficiency Framework. Efficiency Framework is devoted to the combination of eco-efficiency (via ecoPROSYS) and the efficiency assessment (via MSM – Multi-Layer Stream Mapping). In this manuscript the benefit of the combination of the Efficiency Framework as an facilitator to a more effective application of Industrial Symbiosis, within or outside the company’s boundaries, is explored. © 2018 Taylor & Francis Group, London, UK.

Abstract
The use of the odometry and SLAM visual methods in autonomous vehicles has been growing. Optical sensors provide valuable information from the scenario that enhance the navigation of autonomous vehicles. Although several visual techniques are already available in the literature, their performance could be significantly affected by the scene captured by the optical sensor. In this context, this paper presents a comparative analysis of three monocular visual odometry methods and three stereo SLAM techniques. The advantages, particularities and performance of each technique are discussed, to provide information that is relevant for the development of new research and novel robotic applications. © Springer International Publishing AG 2018.