Abstract
An integrated view of the information system has been an objective to deal with complexity. However, bibliography proposes many solutions with many synonyms depending on the layer, methodology, framework or tool used, that does not allow a broad view of the system. In this work we chose three basic elements of the information systems and we demonstrate how they are enough to integrate a set of essential UML diagrams. The proposed model firstly defines a set of UML diagrams for each layer of the Enterprise Architecture, and then heuristic rules are detailed in order to ensure vertical and horizontal alignment. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The offshore wind power industry is an emerging and exponentially growing sector, which calls to a necessity for a cyclical monitoring and inspection to ensure the safety and efficiency of the wind farm facilities. Thus, the emersed (aerial) and immersed (underwater) scenarios must be reconstructed to create a more complete and reliable map that maximizes the observability of all the offshore structures from the wind turbines to the cable arrays, presenting a multi domain scenario.This work proposes the use of an Autonomous Surface Vehicle (ASV) to map both domains simultaneously. As such, it will produce a multi-domain map through the fusion of navigational sensors, GPS and IMU, to localize the vehicle and aid the registration process for the perception sensors, 3D Lidar and Multibeam echosounder sonar. The performed experiments demonstrate the ability of the multi-domain mapping architecture to provide an accurate reconstruction of both scenarios into a single representation using the odometry system as the initial seed to further improve the map with data filtering and registration processes. An error of 0.049 m for the odometry estimation is observed with the GPS/IMU fusion for simulated data and 0.07 m for real field tests. The multi-domain map methodology requires an average of 300 ms per iteration to reconstruct the environment, with an error of at most 0.042 m in simulation.

Abstract
Simple Summary Ensuring animal welfare is essential in protocols using laboratory animals. Applying a score sheet with 14 biological parameters, we assessed the welfare of 29 male Wistar rats used as models of colorectal carcinogenesis (CRC). We found a uniformity of characteristics preceding the premature animals' death, including an increase of 10% in body weight, swollen abdomen, diarrhea, and priapism. In addition, we observed that surface abdominal temperature was higher in animals with CRC. We considered that the parameters already described in other cancer models are insufficient and considered assessing the abdominal temperature, priapism, and sudden increase in the body weight in the model of CRC. This study aimed to define appropriate humane endpoints (HEs) for an animal model of colorectal carcinogenesis (CRC). Twenty-nine male Wistar rats were divided into two control groups (CTRL1 and CTRL2) injected with ethylenediamine tetraacetic acid (EDTA)-saline solutions and two induced groups (CRC1 and CRC2) injected with 1,2-dimethylhydrazine (DMH) for seven weeks. A score sheet with 14 biological parameters was used to assess animal welfare. Groups CRC1 and CTRL1 and groups CRC2 and CTRL2 were euthanized 11 and 17 weeks after the first DMH administration, respectively. Five animals from the induced groups died unexpectedly during the protocol (survival rates of 75.0% and 66.7% for groups CRC1 and CRC2, respectively). The final mean body weight (BW) was smaller in the CRC groups when compared with that in the CTRL groups. A uniformity of characteristics preceding the premature animals' death was observed, namely an increase of 10% in mean BW, swollen abdomen, diarrhea, and priapism. The surface abdominal temperature of group CRC2 was significantly higher, when compared with that of group CTRL2. The parameters already described in other cancer models proved to be insufficient. For the CRC model, we considered assessing the abdominal temperature, priapism, and sudden increase in the BW.

Abstract
We propose a mechanism to raise the abstraction level of source-code analysis and robustly support multiple languages. Built on top of the LARA framework, it allows sharing language specifications between LARA source-to-source compilers, and enables the mapping of a virtual AST over the nodes of ASTs provided by different, unrelated parsers. We use this approach to create a language specification for Object-Oriented (OO) languages and add support for three different LARA compilers. We evaluate it by implementing a library of 18 software metrics using this language specification and apply the metrics to source code in four programming languages (C, C++, Java, and JavaScript). We compare the results with other tools to evaluate the approach.

Abstract
In this paper we present a Deep Learning-based methodology to automatically classify 12 of the most representative grapevarieties existing in the Douro Demarked region, Portugal. The dataset used consisted of images of leaves at different stages of development, collected on their natural environment. The development of such methodologies becomes particularly important, in a scenario in which ampeleographers are disappearing, creating a gap in the task of inspection of grape varieties. Our approach was based on the transfer learning of the Xcepetion model, using Focal Loss, adaptive learning rate decay and SGD. The model obtained a F1 score of 0.93. To clearly understand the predictions of the model, and realize which regions of the image contributed the most to the classification, the LIME library was used. This way it was possible to identify the parts of the images that were considered for and against each prediction.

Abstract
This tool paper presents the High-Assurance ROS (HAROS) framework. HAROS is a framework for the analysis and quality improvement of robotics software developed using the popular Robot Operating System (ROS). It builds on a static analysis foundation to automatically extract models from the source code. Such models are later used to enable other sorts of analyses, such as Model Checking, Runtime Verification, and Property-based Testing. It has been applied to multiple real-world examples, helping developers find and correct various issues.