Abstract
Modern software engineering practices to enable reproducible and easy to deploy robotics solutions have been embraced in recent years, leading to an increasing adoption of container technologies within the Robot Operating System (ROS) community. However, there is still no common procedure or tools for creating, testing, and deploying containerized ROS packages. A common way to work with containerized ROS applications would prove beneficial by increasing even more the level of collaboration among development teams, help in reusing existing solutions, and automate the development of new ones. This paper presents a software framework to support the development of ROS applications using Docker containers, across all its stages. Besides containerizing ROS packages, the presented tool also assists in the deployment of containerized solutions as well as the creation of complex simulation environments for testing. The tool also provides a way for these simulations to be assessed at run-time using a property-specific language targeting ROS applications. An industrial and a scientific scenario are presented to portray the usage of the proposed tool.

Abstract
Cascade cropping systems in soilless horticulture (where drainage collected from the main crop is used in fertigation of secondary crops) are potentially interesting for Mediterranean countries as they enhance water and nutrient use efficiency. However, their agronomic and long-term environmental impact has been poorly addressed. In this case study, lettuce grown hydroponically or in soil (previously exposed to drainage for five years) was fertigated, throughout the cultivation period, with a nutrient solution composed of 0, 25, 50 or 100 % of drainage (0D, 25D, 50D and 100D) mixed with a fresh nutrient solution. Plant performance analysis included growth parameters and leaf mineral composition. Drainage was analyzed for nutrients and Plant Protection Products (PPP) residues, and bioassays were performed exposing aquatic organisms (Raphidocelis subcapitata, Aliivibrio fischeri and Daphnia magna) to drainage and soil elutriate. When analyzing plant performance in both cultivation systems, a significant effect was only found at 100D in hydroponics, resulting in 41 % less leaf area, 20 % smaller head diameter and 43 % lower yield. Drainage analysis showed high nutrient content, presence of PPP residues (up to 6 substances, reaching 3.29 mu g.L-1 in total) and revealed toxicity to D. magna (EC50 = 66.6 %). Moreover, soil elutriate presented toxicity to R. subcapitata (EC50 = 20.6 %) and to A. fischeri (EC50 = 14.9 %). This study demonstrates the potential of using relatively high drainage percentages (up to 50 %) from soilless cultivation systems if applied to hydroponically-grown secondary crops. However, attention should be paid to the use of cascade cropping systems when drainages are applied to fertigate soil-grown crops, as it may contribute to soil degradation and environmental pollution on a long run.

Abstract

Abstract
This work presents a novel methodology for the quality assessment of material extrusion parts through AI-based Computer Vision. To this end, different techniques are integrated using inspection methods that are applied to other areas in additive manufacturing field. The system is divided into four main points: (1) pre-processing, (2) color analysis, (3) shape analysis, and (4) defect location. The color analysis is performed in CIELAB color space, and the color distance between the part under analysis and the reference surface is calculated using the color difference formula CIE2000. The shape analysis consists of the binarization of the image using the Canny edge detector. Then, the Hu moments are calculated for images from the part under analysis and the results are compared with those from the reference part. To locate defects, the image of the part to be analyzed is first processed with a median filter, and both the original and filtered image are subtracted. Then, the resulting image is binarized, and the defects are located through a blob detector. In the training phase, a subset of parts was used to evaluate the performance of different methods and to set the values of parameters. Later, in a testing and validation phase, the performance of the system was evaluated using a different set of parts. The results show that the proposed system is able to classify parts produced by additive manufacturing, with an overall accuracy of 86.5%, and to locate defects on their surfaces in a more effective manner.

Abstract
This study aims to develop a new jig holding system that is able to be controlled by a Computer Numeric Control (CNC) installed on three-axis machining centers, which can drastically im-prove the productivity in machining operations, enabling the machining of unparallel plans in the same setup. An action research methodology was adopted for this work, which, through a practical approach, intends to generate transferrable knowledge to other organizations whose situations are like those in this study. Together, the practical actions and the knowledge acquired create the changes needed for improving these processes. By conducting a case study, it was observed that savings of about 40 % can be easily achieved for parts with low geometric complexity. If the complexity of the parts increases, it is expected that these savings can be even higher. The return of investment is less than 2 years, which is usually affordable for enterprises. Through this study, it was possible to develop a new jig holding system that can be attached to a three-axis CNC machining center and clearly expands its functions and productivity. With this system, it is possible to work in different planes of the part in sequence, as well as use a double-sided table for the jigs, doubling the production batch each time the machine is loaded. Moreover, a list of key settings has been created with the main requirements and recommendations to adopt this kind of production system, which can be highlighted as the main research output.

Abstract
To provide a safe and fair-value health service that ensures quality, hospitals must provide efficient processes, trained and committed personnel, appropriate technology and a strategic platform which integrates these aspects effectively. At present, a broad set of tools and methodologies are available, associated to the reconfiguration of processes for enhancing efficiency and enabling excellence and sustainability. Of these, the most noteworthy are Lean and Six-Sigma methodologies. A literature review was performed covering the implementation of these methodologies in health services over the last 5 years. The aim was to determine the current approach in this sector and propose guidelines aligned with the future challenges and the needs of healthcare managers. The influence of team management strategies in the final project outcomes has also been addressed representing a novelty.