Multifunctional cement composites strain and damage sensors applied on reinforced concrete (RC) structural elements

In this research, strain-sensing and damage-sensing functional properties of cement composites have been studied on a conventional reinforced concrete (RC) beam. Carbon nanofiber (CNFCC) and fiber (CFCC) cement composites were used as sensors on a 4 m long RC beam. Different casting conditions (in situ or attached), service location (under tension or compression) and electrical contacts (embedded or superficial) were compared. Both CNFCC and CFCC were suitable as strain sensors in reversible (elastic) sensing condition testing. CNFCC showed higher sensitivities (gage factor up to 191.8), while CFCC only reached gage factors values of 178.9 (tension) or 49.5 (compression). Furthermore, damage-sensing tests were run, increasing the applied load progressively up to the RC beam failure. In these conditions, CNFCC sensors were also strain sensitive, but no damage sensing mechanism was detected for the strain levels achieved during the tests. Hence, these cement composites could act as strain sensors, even for severe damaged structures near to their collapse.

Developing pre-service teachers’ noticing of students’ understanding of the derivative concept

This research study examines the development of the ability of pre-service teachers to notice signs of students’ understanding of the derivative concept. It analyses preservice teachers’ interpretations of written solutions to problems involving the derivative concept before and after participating in a teacher training module. The results indicate that the development of this skill is linked to pre-service teachers’ progressive understanding of the mathematical elements that students use to solve problems. We have used these results to make some suggestions for teacher training programmes.

The role of nutrients for improving seedling quality in drylands

Forest plantations have been extensively used to combat desertification. In drylands, harsh climate conditions and unfertile soils often preclude seedling establishment. The improvement in seedling quality by manipulating nutrient availability could contribute to increase planting success. However, morpho-functional traits defining optimum seedling quality in drylands, and the fertilization schemes to achieve them, are still under discussion. Several studies suggest that well fertilized seedlings may perform better than nutrient limited seedlings in these environments. However, recent works have shown opposite results. In this review, we discuss the concept of seedling quality in drylands based on an evaluation of the effects of nutrient manipulation on seedling morpho-functional traits and field performance. According to existing data, we hypothesize that nutrient-limited small seedlings may be better adapted to arid environments and unfavorable microsites, where access to water is uncertain and a conservative water use strategy may be advantageous. In contrast, in dry sub-humid areas, areas with deep soils, protected from excess radiation, and areas where irrigation is feasible, well-fertilized big seedlings with high root growth potential may have more chances of success. We discuss this theory in the context of the multiple objectives of dryland restoration and the environmental constrains posed by these areas, and identify knowledge gaps that should be targeted to test our hypothesis.

Assessment of University External Internships. Towards a Mixed Model for Measuring the Acquisition of Skills and the Satisfaction of Parties Involved

The continuous improvement of management and assessment processes for curricular external internships has led a group of university teachers specialised in this area to develop a mixed model of measurement that combines the verification of skill acquisition by those students choosing external internships with the satisfaction of the parties involved in that process. They included academics, educational tutors of companies and organisations and administration and services personnel in the latter category. The experience, developed within University of Alicante, has been carried out in the degrees of Business Administration and Management, Business Studies, Economics, Advertising and Public Relations, Sociology and Social Work, all part of the Faculty of Economics and Business. By designing and managing closed standardised interviews and other research tools, validated outside the centre, a system of continuous improvement and quality assurance has been created, clearly contributing to the gradual increase in the number of students with internships in this Faculty, as well as to the improvement in satisfaction, efficiency and efficacy indicators at a global level. As this experience of educational innovation has shown, the acquisition of curricular knowledge, skills, abilities and competences by the students is directly correlated with the satisfaction of those parties involved in a process that takes the student beyond the physical borders of a university campus. Ensuring the latter is a task made easier by the implementation of a mixed assessment method, combining continuous and final assessment, and characterised by its rigorousness and simple management. This report presents that model, subject in turn to a persistent and continuous control, a model all parties involved in the external internships are taking part of. Its short-term results imply an increase, estimated at 15% for the last course, in the number of students choosing curricular internships and, for the medium and long-term, a major interweaving between the academic world and its social and productive environment, both in the business and institutional areas. The potentiality of this assessment model does not lie only in the quality of its measurement tools, but also in the effects from its use in the various groups and in the actions that are carried out as a result of its implementation and which, without any doubt and as it is shown below, are the real guarantee of a continuous improvement.

An improvement of a SLAM RGB-D method with movement prediction derived from a study of visual features

This paper presents a method for the fast calculation of a robot’s egomotion using visual features. The method is part of a complete system for automatic map building and Simultaneous Location and Mapping (SLAM). The method uses optical flow to determine whether the robot has undergone a movement. If so, some visual features that do not satisfy several criteria are deleted, and then egomotion is calculated. Thus, the proposed method improves the efficiency of the whole process because not all the data is processed. We use a state-of-the-art algorithm (TORO) to rectify the map and solve the SLAM problem. Additionally, a study of different visual detectors and descriptors has been conducted to identify which of them are more suitable for the SLAM problem. Finally, a navigation method is described using the map obtained from the SLAM solution.