A WAV file dataset of bottlenose dolphin whistles, clicks, and pulse sounds during trawling interactions.

Globally, interactions between fishing activities and dolphins are cause for concern due to their negative effects on both mammals and fishermen. The recording of acoustic emissions could aid in detecting the presence of dolphins in close proximity to fishing gear, elucidating their behavior, and guiding potential management measures designed to limit this harmful phenomenon. This data descriptor presents a dataset of acoustic recordings (WAV files) collected during interactions between common bottlenose dolphins (Tursiops truncatus) and fishing activities in the Adriatic Sea. This dataset is distinguished by the high complexity of its repertoire, which includes various different typologies of dolphin emission. Specifically, a group of free-ranging dolphins was found to emit frequency-modulated whistles, echolocation clicks, and burst pulse signals, including feeding buzzes. An analysis of signal quality based on the signal-to-noise ratio was conducted to validate the dataset. The signal digital files and corresponding features make this dataset suitable for studying dolphin behavior in order to gain a deeper understanding of their communication and interaction with fishing gear (trawl).

Disseminating STEM Subjects and Ocean Literacy through a Bioinspired Toolkit.

Over the last decade, education has been evolving to equip students with the fundamental skills required to cope with the challenges of sustainability and inclusivity, such as quality education, access to clean water, cultural heritage preservation and protection of marine life. Technology supports the learning process by providing useful tools that enrich the learning environment, encourage active participation, improve collaboration and prepare students for their future life. Educational Robotics is one of the most popular innovative methodologies that supports the development of many skills by assembling and programming robots in a meaningful way. In this paper, the authors aim at advancing their previous work in the field of Educational Robotics applied to the marine environment by proposing a novel bioinspired educational toolkit whose design and features support activities concerning sustainability, ocean literacy, as well as STEM subjects in kindergarten through to grade twelve education. Exploiting the established educational theories and methodologies underpinning Educational Robotics, the toolkit allows for marine-themed activities, as well promoting activities concerning STEM subjects. To explain the relevance of the toolkit, the authors present the robot design, the workshops that every teacher or student can explore as an Open Educational Resource (OERs), and the results of a case study. Interestingly, the latter shows that the use of the toolkit seems to have complemented the students' initial keen interest in technology itself, with awareness about urgent issues related to the climate and the environment.

Design of a Carangiform Swimming Robot through a Multiphysics Simulation Environment.

Bio-inspired solutions devised for autonomous underwater robots are currently being investigated by researchers worldwide as a way to improve propulsion. Despite efforts to harness the substantial potential payoffs of marine animal locomotion, biological system performance still has far to go. In order to address this very ambitious objective, the authors of this study designed and manufactured a series of ostraciiform swimming robots over the past three years. However, the pursuit of the maximum propulsive efficiency by which to maximize robot autonomy while maintaining acceptable maneuverability ultimately drove us to improve our design and move from ostraciiform to carangiform locomotion. In order to comply with the tail motion required by the aforementioned swimmers, the authors designed a transmission system capable of converting the continuous rotation of a single motor in the travelling wave-shaped undulations of a multijoint serial mechanism. The propulsive performance of the resulting thruster (i.e., the caudal fin), which constitutes the mechanism end effector, was investigated by means of computational fluid dynamics techniques. Finally, in order to compute the resulting motion of the robot, numerical predictions were integrated into a multibody model that also accounted for the mass distribution inside the robotic swimmer and the hydrodynamic forces resulting from the relative motion between its body and the surrounding fluid. Dynamic analysis allowed the performance of the robotic propulsion to be computed while in the cruising condition.

Identification of the Students Learning Process During Education Robotics Activities.

This paper presents the design of an assessment process and its outcomes to investigate the impact of Educational Robotics activities on students' learning. Through data analytics techniques, the authors will explore the activities' output from a pedagogical and quantitative point of view. Sensors are utilized in the context of an Educational Robotics activity to obtain a more effective robot-environment interaction. Pupils work on specific exercises to make their robot smarter and to carry out more complex and inspirational projects: the integration of sensors on a robotic prototype is crucial, and learners have to comprehend how to use them. In the presented study, the potential of Educational Data Mining is used to investigate how a group of primary and secondary school students, using visual programming (Lego Mindstorms EV3 Education software), design programming sequences while they are solving an exercise related to an ultrasonic sensor mounted on their robotic artifact. For this purpose, a tracking system has been designed so that every programming attempt performed by students' teams is registered on a log file and stored in an SD card installed in the Lego Mindstorms EV3 brick. These log files are then analyzed using machine learning techniques (k-means clustering) in order to extract different patterns in the creation of the sequences and extract various problem-solving pathways performed by students. The difference between problem-solving pathways with respect to an indicator of early achievement is studied.

Digital chest tomosynthesis: the 2017 updated review of an emerging application.

Lung cancer is the leading cause of cancer death and second most common cancer among both men and women, but most of them are detected when patients become symptomatic and in late-stage. Chest radiography (CR) is a basic technique for the investigation of lung cancer and has the benefit of convenience and low radiation dose, but detection of malignancy is often difficult. The introduction of computed tomography (CT) for screening has increased the proportion of lung cancer detected but with higher exposure dose and higher costs. Digital chest tomosynthesis (DCT), a tomographic technique, may offer an alternative to CT. DCT uses a conventional radiograph tube, a flat-panel detector, a computer-controlled tube mover and reconstruction algorithms to produce section images. It shows promise in the detection of potentially malignant lung nodules, with higher sensibility than CR, and is emerging as a low-dose and low-cost alternative to CT to improve treatment decisions. In fact, an increasing number of researchers are showing that tomosynthesis could have a role in the detection of lung cancer, in addition to its present role in breast screening. However, DCT offers some limitations, such as limited depth resolution, which may explain the difficulty in detecting pathologies in the subpleural region and the occurrence of artefacts from medical devices. Once solved these limitations and once more studies supporting its use will be available, DCT could become the first-line lung cancer screening tool among patients at considerable risk of lung cancer.

Testing methods to support management decisions in coralligenous and cave environments. A case study at Portofino MPA.

Baseline data on the distribution, condition and extent of coralligenous and cave bioconcretions is one of the main requirements of the European Marine Strategy Framework Directive (MSFD) necessary to assess the achievement of a Good Environmental Status (GES) by 2020. In this study the potential of remote sensing and distribution modelling techniques to map, measure descriptors and choose indicators were tested, that could provide standard methods for the assessment of the health status and assist in monitoring activities. It is demonstrated how, by combining different methodologies, it is possible to map the distribution of the bioconcretions with acceptable accuracy and to discriminate the main habitat types and facies. In addition, zonal statistical analysis revealed that fishing activities primarily coincide with areas of high coverage of the bioconcretions. Results demonstrate that the presented methodology is a valuable simple tool to assess several MSFD descriptors and indicators, and could strengthen management efficiency when making informed, ecologically relevant decisions.