Abstract
Internships have been widely used in higher education in different scientific fields, which presupposes the training of students in a work context. There are some studies on the usefulness of internships undertaken at undergraduate and graduate levels. However, to the best of our knowledge, literature has been disregarding short-cycle higher technical courses (TESP). This paper aims to fill this gap, describing and presenting results of perceptions of students enrolled in the internship subject of one TESP. More specifically, the objectives for this paper are: (i) to identify the obstacles students face; (ii) to explore students' perceptions of internship benefits; and, (iii) to examine the skills students consider to have improved as a result of their internship. A survey comprising both qualitative and quantitative questions was conducted with the students enrolled in the internship subject of the Sales, Management and Marketing TESP course at the University of Aveiro, Portugal, in the second semester of 2018/2019. 25 students accepted to participate in the study (89%). Despite some difficulties pointed out by students in adapting to a work context in the first weeks, the results show that they considered having improved their learning outcomes, and some interpersonal skills, such as autonomy, ability to take initiative, ability to conduct research, collaboration, flexibility, time management, personal organization, task planning, responsibility, and decision making. Additionally, students stressed that the internship facilitates their future employment. Thus, this study provides relevant cues for teachers and course directors in order to minimize weaknesses and maximize strengths of internships, aiming at a better articulation between HEI and companies.

Abstract
This study aimed to estimate the daily crop evapotranspiration (ETc) of soilless cut 'Red Naomi' roses, cultivated in a commercial glass greenhouse, using climatic and crop predictors. A multiple stepwise regression technique was applied for estimating ETc using the daily relative humidity, stem leaf area and number of leaves of the bended stems. The model explained 90% of the daily ETc variability (R-2 = 0.90, n = 33, P < 0.0001) measured by weighing lysimeters. The mean relative difference between the observed and the estimated daily ETc was 9.1%. The methodology revealed a high accuracy and precision in the estimation of daily ETc.

Abstract
Rheumatic Heart Disease is the serious consequence of repeated episodes of Acute Rheumatic Fever, an autoimmune reaction of a group A streptococcal infection. It's the major cause of heart valve damage, responsible for thousands of deaths per year. The key evidences are changes in the thickness, shape and mobility of the mitral valve leaflets. In this work, an automatic approach is proposed for pathology classification based on motion patterns anterior mitral leaflet, as observed in an echocardiographic video, is proposed. The motion points are extracted from the morphological skeleton of the anterior mitral leaflet and motion velocity and directionality is observed. This data is processed with the Discrete Fourier Transform, and used by several types of classifiers to perform the pathology classification. A Random Forest classifier utilizing the processed data archived a 71% precision and negative predicated value of 58%.

Abstract
In this article, we present a solution for training the mouse input device handling, in order to improve the users' digital skills. Knowing that the widespread access to the computer and the Internet is still made by the use of traditional devices, such as, the keyboard and mouse device (and these devices does not provide natural interaction between people and technology), it is necessary to train for the correct handling. Specifically, mouse usage requires movement control, hand posture and finger positioning, as well as, precision clicks for different functions (one click, two clicks, drag and click) This training is often done in real interaction situations, that could led to inefficiency of use the digital environments and also user's frustration and discouragement. Thus, using simple and intuitive interfaces and providing a set of activities, we allow users to learn and train the motor coordination and basic movements with the mouse. The main results of the study showed that users had a pleasant experience of interaction, considered the interfaces intuitive and affirmed their availability to use it as a training tool.

Abstract

Abstract
Production scheduling is an optimizing problem that can contribute strongly to the competitive capacity of companies producing goods and services. A way to promote the survival and the sustainability of the organizations in this upcoming era of Industry 4.0 (I4.0) is the efficient use of the resources. A complete failure to stage tasks properly can easily lead to a waste of time and resources, which could result in a low level of productivity and high monetary losses. In view of the above, it is essential to analyse and continuously develop new models of production scheduling. This paper intends to present an I4.0 oriented decision support tool to the dynamic scheduling. After a fist solution has been generated, the developed prototype has the ability to create new solutions as tasks leave the system and new ones arrive, in order to minimize a certain measure of performance. Using a single machine environment, the proposed prototype was validated in an in-depth computational study through several instances of dynamic problems with stochastic characteristics. Moreover, a more robust analysis was done, which demonstrated that there is statistical evidence that the proposed prototype performance is better than single method of scheduling and proved the effectiveness of the prototype.