Abstract
A multi-AGV based logistic system is typically associated with two fundamental problems, critical for its overall performance: the AGV's route planning for collision and deadlock avoidance; and the task scheduling to determine which vehicle should transport which load. Several heuristic functions can be used according to the application. This paper proposes a time-based algorithm to dynamically control a fleet of Autonomous Guided Vehicles (AGVs) in an automatic warehouse scenario. Our approach includes a routing algorithm based on the A* heuristic search (TEA*-Time Enhanced A*) to generate free-collisions paths and a scheduling module to improve the results of the routing algorithm. These modules work cooperatively to provide an efficient task execution time considering as basis the routing algorithm information. Simulation experiments are presented using a typical industrial layout for 10 and 20 AGVs. Moreover, a comparison with an alternative approach from the state-of-the-art is also presented.

Abstract
Energy hubs (EHs) are units wherein multiple energy carriers can be converted, stored and conditioned to simultaneously supply different energy demands. In this paper, a new model is proposed for unit commitment in renewable EHs with electric, thermal and cooling demands, different storage systems, combined heat and power (CHP) unit, boiler, electric chiller, absorption chiller, PV module, wind turbine and battery charging station (BCS). Using information gap decision theory (IGDT), day-ahead EH scheduling is done from risk-neutral, risk-averse and risk-seeking perspectives, considering the un-certainties of electric demands, BCS demands, heat demands, cooling demands, PV and wind power and electricity prices. Comprehensive models are used for storage systems considering their degradation, charging loss, discharging loss and storage loss; the ramp-up and ramp-down rate limits, start-up and shut-down costs of CHP, boiler and cooling components are considered. The effect of risk as well as effect of critical cost deviation factor and target cost deviation factor on EH operation cost and schedule of EH components is investigated. The findings indicate that the sensitivity of EH operation cost may be very different with respect to different sets of uncertain input data. The findings also show the significant effect of risk-awareness on schedule of EH components and its operation cost.

Abstract
This study presents and applies fractal Brownian motion assessment of the center of pressure (COP) excursion during feet ground contact on standard vertical jump impulse phase with long and short countermovement (CM) in relation with lower limb muscle stretch-shortening cycle (SSC) comparing it with no CM and SSC. Fifty-four tests were performed by a group of six healthy male students of sports and physical education degree without previous injury, specific training, or fitness ability. Three repetitions were performed by each subject of a squat jump (SJ) without CM and SSC, countermovement jump (CMJ) with long CM and SSC, as well as drop jump (DJ) with short CM and SSC after depth jump from a 40 cm step. During trial tests ground reaction force and force moments were acquired with force platform and impulse phases were segmented for COP coordinates computation. Fractal Brownian motion analysis of COP excursion during impulse phases conduced to detection of differences between critical time and displacement as well as short and long-term diffusion coefficient (Ds, Dl) and Hurst index scale exponent (Hs, Hl), with Ds, Dl presenting statistical significative correlations -0.491, -0.559 and Hs, Hl non statistical significative correlations 0.266 and -0.424 with MVJ height (ht) at 5% significance for explaining underlying mechanisms on CM and SSC at MVJ. Clinical Relevance- This work contributes with new method for the study expansion of the center of pressure excursion and stability during feet ground contact from orthostatic standing position to the impulse phase during standard maximum vertical jump as the most adequate method for assessment of lower limb muscle stretch-shortening cycle.

Abstract
Tourism plays a very important role in society. However, it has many negative impacts, such as the increasing problem of food wasting in hotel restaurants, especially when providing all-inclusive/all-you-can-eat breakfasts and dinners. This study aims to propose some activities which could lead to food wasting reduction. Through a questionnaire (with 132 respondents, from various countries), the authors wanted to find out respondents' attitudes towards suggested solutions and this problem in general. As part of the questionnaire, four possible activities were proposed in order to help to reduce food wasting and contribute to better food security in today's world. The questionnaire results proved that respondents would appreciate such opportunities, therefore answering the research question. Fridges (in which people could put their untouched leftovers), samples (before people take the whole portion of food), special cards (containing the ingredients used for the preparation of the meal), and daily announcements (of food wasting in kilograms) are four possible ways to reduce food wasting in hotel restaurants.

Abstract
Up to one third of the global food production depends on the pollination of honey bees, making them vital. This study defines a methodology to create a bee hive health monitoring system through image processing techniques. The approach consists of two models, where one performs the detection of bees in an image and the other classifies the detected bee’s health. The main contribution of the defined methodology is the increased efficacy of the models, whilst maintaining the same efficiency found in the state of the art. Two databases were used to create models based on Convolutional Neural Network (CNN). The best results consist of 95% accuracy for health classification of a bee and 82% accuracy in detecting the presence of bees in an image, higher than those found in the state-of-the-art.

Abstract