Abstract
Background: The role of mindful eating (ME) and intuitive eating (IE) in improving eating behavior, diet quality, and health is an area of increasing interest. Objective: The objective of this review was to identify the instruments used to assess ME and IE among higher education students and outcomes related to these dimensions. Methods: This review was carried out according to the PRISMA statement, through systematic searches in PubMed, Web of Science, PsycInfo, and Scopus. The inclusion criteria selected for higher education students, levels of ME and/or IE reported, and observational and clinical studies. The exclusion criteria selected against reviews, qualitative studies, and case studies. Quality was assessed using the Academy of Nutrition and Dietetics Quality Criteria Checklist. Results: A total of 516 initial records were identified, from which 75 were included. Cross-sectional studies were the most common research design (86.7%). Most studies were conducted with samples that were predominantly female (90.7%), White (76.0%), aged 18 to 22 years (88.4%), with BMI < 25 kg/m(2) (83.0%), and in the United States (61.3%). The Intuitive Eating Scale (IES), the Mindful Eating Questionnaire (MEQ), and their different versions were the most used instruments. The outcomes most studies included were eating behavior and disorders (77.3%), anthropometric assessments (47.8%), mental health (42.0%), and body image (40.6%). Regarding the quality of studies, 34.7% of studies were assigned a positive, 1.3% a negative, and 64.0% a neutral rate. Conclusions: IES and MEQ were the most used instruments. RCT and cohort studies are scarce, and future research with a higher level of quality is needed, especially on the topics of food consumption, diet quality, and biochemical markers.

Abstract

Abstract
The Puzzle -based Learning approach has been applied to several fields of knowledge. In education research papers, the instructional usage of puzzles is considered to improve learners' motivation and engagement and help them to develop critical skills but difficulties concerning learners' interaction with puzzles have also been pointed out. Our paper investigates the dynamics of the concept of a puzzle and its interface to provide a better understanding of its form and functions, and help learners interact with puzzles. We consider Puzzle -based Learning tenets as well as their educational impacts on both critical thinking and learner engagement and provide an original proposal concerning the understanding of puzzles. Our proposal centered on the dynamics of puzzles bears conceptual and educational facets. Conceptually, puzzle dynamics is viewed as composed of two elements: a mechanism, the Puzzle Trigger, and a process, the Puzzle -Solving. From an educational point of view, the rationale for integrating Puzzle Triggers in Puzzle -based Learning is meant to help learners interact with puzzles and consequently become motivated and engaged in the Puzzle -Solving process. This way, learners' critical thinking skills are reinforced and focused on finding solutions to challenges. We illustrate the implementation of Puzzle Triggers and Puzzle -Solving by considering two instructional activities in a Software Development undergraduate course of an online learning Informatics Engineering Program.

Abstract
Proactive participation of uncertain renewable generation in the day-ahead (DA) wholesale market effectively reduces the system marginal price and carbon emissions, whilst significantly increasing the volumes of real-time balancing mechanism prices to ensure system security and stability. To solve the conflicting interests over the two timescales, this article: 1) proposes a novel hierarchical optimization model to align with the actual operation paradigms of the hierarchical market, whereby the capacity allocation matrix is adopted to coordinate the DA and balancing markets; 2) mathematically formulates and quantitatively analyses the long-term driving factors of balancing actions, enabling system operators (SOs) to design efficient and well-functioning market structures to meet economic and environmental targets; 3) empowers renewable generating units and flexible loads to participate in the balancing market (BM) as 'active' actors and enforces the non-discriminatory provision of balancing services. The performance of the proposed model is validated on a modified IEEE 39-bus power system and a reduced GB network. Results reveal that with effective resource allocation in different timescales of the hierarchical market, the drop speed of balancing costs soars while the intermittent generation climbs. The proposed methodology enables SOs to make the most of all resources available in the market and balance the system flexibly and economically. It thus safeguards the climate mitigation pathways against the risks of substantially higher balancing costs.

Abstract
Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools in precision agriculture due to their ability to provide timely and detailed information over large agricultural areas. In this sense, this work aims to evaluate the semi-autonomous navigation capacity of a multirotor UAV when applied in the field of precision agriculture. For this, a small aircraft is used to identify and track a set of fiducial markers (Ar Track Alvar) in an environment that simulates inspections of insect traps in olive groves. The purpose of this marker is to provide a visual reference point for the drone's navigation system. Once the Ar Track Alvar marker is detected, the robot will receive navigation information based on the marker's position to approach the specific trap. The experimental setup evaluated the computer vision algorithm applied to the UAV to make it recognize the Ar Track Alvar marker and then reach the trap efficiently. Experimental tests were conducted in a indoor and outdoor environment using DJI Tello. The results demonstrated the feasibility of applying these fiducial markers as a solution for the UAV's navigation in this proposed scenario.

Abstract
Biofeedback is a promising tool to complement conventional physical therapy by fostering active participation of neurologically impaired patients during treatment. This work aims at a user-centered design and usability assessment for different age groups of a novel wearable augmented reality application composed of a multimodal sensor network and corresponding control strategies for personalized biofeedback during gait training. The proposed solution includes wearable AR glasses that deliver visual cues controlled in real-time according to mediolateral center of mass position, sagittal ankle angle, or tibialis anterior muscle activity from inertial and EMG sensors. Control strategies include positive and negative reinforcement conditions and are based on the user's performance by comparing real-time sensor data with an automatically user-personalized threshold. The proposed solution allows ambulatory practice on daily scenarios, physiotherapists' involvement through a laptop screen, and contributes to further benchmark biofeedback regarding the type of sensor. Although old healthy adults with low academic degrees have a preference for guidance from an expert person, excellent usability scores (SUS scores: 81.25-96.87) were achieved with young and middle-aged healthy adults and one neurologically impaired patient.