Abstract
We live in an age of constant technological evolution where we witness an increasing need for adaptation, in view of market challenges. These transformations create interactions between human beings and machines. This article is a case study based on qualitative and quantitative research, which approaches the implementation of a robotized system in a retail convenience shop, at a petrol station. The main objective was to focus on understanding the applicability of this type of system in a shop, as well as to ascertain its future in the short, medium and long term. Field research performed involved a personal interview with an executive at the Portuguese firm PRIO Energy – the Director of Research, Development and Innovation. The essence of the interview was to enquire about the robot experiment and to understand how innovation occurs, and where the ideas come from. Two other firm employees were also contacted for their testimonials on the project – the convenience store manager and the project innovation manager. Light was shed on which phases the innovation project went through. Finally, the authors has access to the results of a consumer survey involving 210 customers, who interacted with the robot station during its test phase. While not all feedback was good, namely some consumers are concerned that robots will be replacing humans in the workplace, leading to unemployment; the vast majority of the 210 survey respondents saw the experience as positive and one which they would repeat in the future. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Abstract
<p>The WATER4EVER Project (http://water4ever.eu/) was built on the premise that agriculture is by far the largest consumer of water, with about 70% of the diverted water being used in irrigation. Agriculture is also considered as a key source of diffuse pollution with inefficient practices resulting in high water and nutrient (particularly N and P) surpluses that are transferred to water bodies through diffuse processes (runoff and leaching), promoting eutrophication, with associated biodiversity loss. WATER4EVER aims thus to develop new monitoring strategies at the plot and catchment scales to provide detailed information of water and nutrient flow, and gain new insights on the connectivity between both scales. New monitoring strategies were developed and tested in agricultural fields in Portugal, Spain, Italy and Turkey and included: (i) crop physiological indicators assessment using static sensors for defining improved deficit irrigation strategies for woody crops; (ii) crop stress and productivity maps from measurements taken with a smart sensor mounted on a tractor and equipped with LIDAR 2D, normalized difference vegetation index (NDVI) and thermal cameras, and a GNSS receiver; (iii) leaf area index maps at 30 m resolution derived from ATCOR and Landsat 8 imagery data using the NDVI and the Soil Adjusted Vegetation Index (SAVI); (iv) soil moisture maps at 100 m resolution by combining the 10 m resolution synthetic-aperture radar (SAR) images from Sentinel 1 with the 10 m resolution NDVI computed from Sentinel 2 images, averaged into 100 m cells, and then by considering the backscatter difference with the driest day, or alternatively the backscatter difference between two consecutive dates; (v) soil moisture maps at 1 km resolution created with the DISaggregation based on a Physical And Theoretical scale CHange (DISPATCH) algorithm for the downscaling of the 40 km SMOS (Soil Moisture and Ocean Salinity) soil moisture data using land surface temperature (LST) and NDVI data; (vi) conventional monitoring techniques combined with modeling tools for assessing the impact of different soil managements (conventional tillage, tillage with grass trips, grass cover) on soil infiltration, soil water content, runoff and soil erosion of hillslope vineyards; (vii) an improved deterministic model for irrigation and fertigation management at the plot scale; and (viii) a decision support system for irrigation water management at the plot scale which integrated a deterministic model for irrigation scheduling and the NDVI computed from Sentinel 2 imagery data for crop growth monitoring. Preliminary results derived from the use of the innovative monitoring and mapping strategies, besides model applications are presented. The remote sensing products described above were also applied for catchment modeling validation of streamflow, which results fall outside the scope of this communication. WATER4EVER activities were thus wide and diverse, aimed at optimizing crop management practices which will help to promote the sustainability of different Mediterranean production systems.</p><p> </p><p>WATER4EVER is funded by the European Commission under the framework of the ERA-NET COFUND WATERWORKS 2015 Programme</p>

Abstract
We study the equilibria of an Ordinary Differencial Equation (ODE) system where CD4+ effector or helper T cells and Regulatory T cells (Tregs) are present. T cells trigger an immune response in the presence of their specific antigen. Regulatory T cells (Tregs) play a role in limiting auto-immune diseases due to their immune-suppressive ability. Here, we present explicit exact formulas that give the relationship between the concentration of T cells, the concentration of Tregs, and the antigenic stimulation of T cells, when the system is at equilibria, stable or unstable. We found a parameter region of bistability, limited by two thresholds of antigenic stimulation of T cells (hysteresis). Moreover, there are values of the slope parameter of the tuning for which an isola-center bifurcation appears, and, for some other values, there is a transcritical bifurcation. We also present time evolutions of the ODE system.

Abstract
Wind power curtailment (WPC) occurs because of the non-correlation between wind power generation (WPG) and load, and also due to the fast sub-hourly variations of WPG. Recently, advances in energy storage technologies facilitate the use of bulk energy storage units (ESUs) to provide the ramping required to respond to fast sub-hourly variations of WPGs. To minimize the sub-hourly WPC probability, this paper addresses a generic continuous-time risk-based model for sub-hourly scheduling of energy generating units and bulk ESUs in the day-ahead unit commitment (UC) problem. Accordingly, the Bernstein polynomials are hosted to model the continuous-time risk-based UC problem with ESU constraints. Also, the proposed continuous-time risk-based model ensures that the generating units and ESUs track the sub-hourly variations of WPG, while the load and generation are balanced in each sub-hourly intervals. Finally, the performance of the proposed model is demonstrated by simulating the IEEE 24-bus Reliability and Modified IEEE 118-bus test systems.

Abstract
In this paper it is described a Pilot that took place at Emidio Garcia School from Braganca, Portugal. The presented Pilot is based on a Challenge based Learning Approach, being an activity of the RoboSTEAM - Integrating STEAM and Computational Thinking development by using robotics and physical devices - ERASMUS+ Project. In the presented educational experiment it were used physical devices, being chosen the mBot robot, programmed using Scratch. The presented challenges had as research question a global problem that was Wildfires. Student had to propose and to develop solutions based on the use of robots to prevent and fight wildfires. The students that participated in the experiment were secondary school students, from Spain and Portugal, with their background in technology and arts respectively. Previously to the experiment the involved students filled a STEM semantic Survey and during the experiments their performance was evaluated.

Abstract
This paper addresses the topic of emergency landing spot detection for Unmanned Aerial Vehicles (UAVs). During operation, the vehicle is susceptible to faults and must be able to predict the land spot able to ensure that the UAV will be able to land without damages and injuries to humans and structures. A method was developed, based on geometric features extracted from Light Detection And Ranging (LIDAR) data. A simulation environment was developed in order to validate the effectiveness and the robustness of the proposed method.