Abstract
Eco-design is focused on incorporating environmental criteria early in the design process to reduce the environmental impacts of new products. However, while services now represent the largest share of the world & rsquo;s economy, the incorporation of environmental sustainability in the design of new services is very limited. This research proposes the ECO-Service Design (ECO-SD) method that integrates eco-design and service design to conceptualize new environmentally sustainable services. The ECO-SD method bridges environmental criteria from eco-design with the human-centred approach of service design, to foster the environmental sustainability of new services, while offering a desirable user experience. To this end, this method encompasses four stages: service exploration, to understand the service context and how users interact with it; service visualization, to visually identify the barriers to environmental performance and user experience during service provision; service ideation, to conceptualize a new service that overcomes the identified barriers; and service assessment, to understand the changes in environmental sustainability and user experience of the newly designed service. The application of the ECO-SD method to two in-dividual shared transport services shows how it enables integrated identification of opportunities to overcome environmental and user experience barriers in the existing services.

Abstract
The usage of unmanned aerial vehicles (UAV) has increased in recent years and new application scenarios have emerged. Some of them involve tasks that require a high degree of autonomy, leading to increasingly complex systems. In order for a robot to be autonomous, it requires appropriate perception sensors that interpret the environment and enable the correct execution of the main task of mobile robotics: navigation. In the case of UAVs, flying at low altitude greatly increases the probability of encountering obstacles, so they need a fast, simple, and robust method of collision avoidance. This work covers the problem of navigation in unknown scenarios by implementing a simple, yet robust, environment-reactive approach. The implementation is done with both CPU and GPU map representations to allow wider coverage of possible applications. This method searches for obstacles that cross a cylindrical safety volume, and selects an escape point from a spiral for avoiding the obstacle. The algorithm is able to successfully navigate in complex scenarios, using both a high and low-power computer, typically found aboard UAVs, relying only on a depth camera with a limited FOV and range. Depending on the configuration, the algorithm can process point clouds at nearly 40 Hz in Jetson Nano, while checking for threats at 10 kHz. Some preliminary tests were conducted with real-world scenarios, showing both the advantages and limitations of CPU and GPU-based methodologies.

Abstract
The ability to select, isolate, and manipulate micron-sized particles or small clusters has made optical tweezers one of the emergent tools for modern biotechnology. In conventional setups, the classification of the trapped specimen is usually achieved through the acquired image, the scattered signal, or additional information such as Raman spectroscopy. In this work, we propose a solution that uses the temporal data signal from the scattering process of the trapping laser, acquired with a quadrant photodetector. Our methodology rests on a pre-processing strategy that combines Fourier transform and principal component analysis to reduce the dimension of the data and perform relevant feature extraction. Testing a wide range of standard machine learning algorithms, it is shown that this methodology allows achieving accuracy performances around 90%, validating the concept of using the temporal dynamics of the scattering signal for the classification task. Achieved with 500 millisecond signals and leveraging on methods of low computational footprint, the results presented pave the way for the deployment of alternative and faster classification methodologies in optical trapping technologies.

Abstract
The world society needs to produce more food with the highest quality standards to feed the world population with the same level of nutrition. Microfarms and local food production enable growing vegetables near the population and reducing the operational logistics costs related to post-harvest food handling. However, it isn't economical viable neither efficient to have one person devoted to these microfarms task. To overcome this issue, we propose an open-source robotic solution capable of performing multitasks in small polyculture farms. This robot is equipped with optical sensors, manipulators and other mechatronic technology to monitor and process both biotic and abiotic agronomic data. This information supports the consequent activation of manipulators that perform several agricultural tasks: crop and weed detection, sowing and watering. The development of the robot meets low-cost requirements so that it can be a putative commercial solution. This solution is designed to be relevant as a test platform to support the assembly of new sensors and further develop new cognitive solutions, to raise awareness on topics related to Precision Agriculture. We are looking for a rational use of resources and several other aspects of an evolved, economically efficient and ecologically sustainable agriculture.

Abstract

Abstract
Several companies in the information technology field are progressively adopting Agile methodologies. This change necessarily transforms the management paradigm and poses new challenges to the leadership process. In this sense, this study seeks to explore the challenges perceived by leaders and perceive the competencies they should have to manage projects and teams in an Agile environment. The study used a survey to obtain data from 387 professionals in the information technology sector. The findings reveal the most important skills include the ability to have people skills, team management competencies, provide feedback on employee performance, and have problem-solving skills. Additionally, this study reveals people's management dimension is key to increasing productivity in Agile environments, and furthermore, respondents' years of experience proved to be discriminating in perceiving the importance of these skills. The outcomes of this study are relevant for companies that are migrating to the agile paradigm and are facing challenges in managing the leadership of these projects.