Long-term energy scenarios for Mexico: Policy options for carbon savings and main barriers

This paper shows that possibilities exist for maintaining current energy-related carbon emissions per capita in Mexico at almost constant levels in the long term. It is argued, however, that the identified carbon emissions reductions will not be achieved easily or rapidly, as they require a restructuring of Mexico's current technological base and an unusual degree of coordination among the government, lending institutions, equipment manufacturers, and final users. Such changes also will entail surmounting major institutional and financial barriers and creating a better international environment for technology transfer and capital lending.     

Applying black-box testing to UML/OCL database models

Most Unified Modeling Language (UML) computer-aided software engineering tools have been insufficient in the development process because they provide little support for conceptual model testing. Model testing aims to ensure the correctness of a UML/OCL class diagram, or, in other words, that a given class diagram can perfectly meet the user’s requirements. This study proposes the validation of class diagrams with black-box testing, a technique used to test software without focusing on the software’s implementation or structure. An approach is proposed for the automatic transformation of the constraints of a UML/OCL class diagram into test cases. Following the creation of the test cases, they are executed with JUnit and the results produced are shown to the tester. To demonstrate the applicability of this approach, an effectiveness evaluation and an efficiency evaluation are performed here. Evaluation studies show that all faults included in a class diagram have been detected within an efficient time.     

Predictors of user perceptions of web recommender systems: How the basis for generating experience and search product recommendations affects user responses

One critical question suggested by Web 2.0 is as follows: When is it better to leverage the knowledge of other users vs. rely on the product characteristic-based metrics for online product recommenders? Three recent and notable changes of recommender systems have been as follows: (1) a shift from characteristic-based recommendation algorithms to social-based recommendation algorithms; (2) an increase in the number of dimensions on which algorithms are based; and (3) availability of products that cannot be examined for quality before purchase. The combination of these elements is affecting users’ perceptions and attitudes regarding recommender systems and the products recommended by them, but the psychological effects of these trends remain unexplored. The current study empirically examines the effects of these elements, using a 2 (recommendation approach: content-based vs. collaborative-based, within)×2 (dimensions used to generate recommendations: 6 vs. 30, between)×2 (product type: experience products (fragrances) vs. search products (rugs), between) Web-based study (N=80). Participants were told that they would use two recommender systems distinguished by recommendation approach (in fact, the recommendations were identical). There were no substantive main effects, but all three variables exhibited two-way interactions, indicating that design strategies must be grounded in a multi-dimensional understanding of these variables. The implications of this research for the psychology and design of recommender systems are presented.     

MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.     

Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems

In an adaptive and intelligent educational system (AIES), the process of learning pedagogical policies according the students needs fits as a Reinforcement Learning (RL) problem. Previous works have demonstrated that a great amount of experience is needed in order for the system to learn to teach properly, so applying RL to the AIES from scratch is unfeasible. Other works have previously demonstrated in a theoretical way that seeding the AIES with an initial value function learned with simulated students reduce the experience required to learn an accurate pedagogical policy. In this paper we present empirical results demonstrating that a value function learned with simulated students can provide the AIES with a very accurate initial pedagogical policy. The evaluation is based on the interaction of more than 70 Computer Science undergraduate students, and demonstrates that an efficient and useful guide through the contents of the educational system is obtained.     

Visual specification of measurements and redesigns for domain specific visual languages

Ensuring model quality is a key success factor in many computer science areas, and becomes crucial in recent software engineering paradigms like the one proposed by model-driven software development. Tool support for measurements and redesigns becomes essential to help developers improve the quality of their models. However, developing such helper tools for the wide variety of (frequently domain specific) visual notations used by software engineers is a hard and repetitive task that does not take advantage from previous developments, thus being frequently forgotten.In this paper we present our approach for the visual specification of measurements and redesigns for Domain Specific Visual Languages (DSVLs). With this purpose, we introduce a novel DSVL called SLAMMER that contains generalisations of some of the more used types of internal product measurements and redesigns. The goal is to facilitate the task of defining measurements and redesigns for any DSVL, as well as the generation of tools from such specification reducing or eliminating the necessity of coding. We rely on the use of visual patterns for the specification of the relevant elements for each measurement and redesign type. In addition, SLAMMER allows the specification of redesigns either procedurally or by means of graph transformation rules. These redesigns can be triggered when the measurements reach a certain threshold.These concepts have been implemented in the meta-modelling tool AToM³. In this way, when a DSVL is designed, it is possible to specify measurements and redesigns that will become available in the final modelling environment generated for the language. As an example, we show a case study in the web modelling domain.     

High-Performance Liquid Chromatography Method for the Monitoring of the <Emphasis Type="Italic">Allium</Emphasis> Derivative Propyl Propane Thiosulfonate Used as Natural Additive in Animal Feed

A new simple analytical method for monitoring propyl propane thiosulfonate (PTSO) in animal feed is presented. PTSO is an active ingredient from Allium spp. (like onion and shallot), proposed as a natural additive for feed being an efficient alternative to antibiotics used as growth promoter due to its efficiency improving animal health. Reversed-phase liquid chromatography with UV detection has been used and a previous sample treatment based on solid-liquid extraction has been developed and optimized in order to extract PTSO from a feed for laying hens using acetone as extraction solvent. The method has been characterized obtaining limits of detection and quantification of 11.2 and 37.3 mg kg^?1, respectively, which are lower than the concentrations expected in samples containing this additive. The intra- and interday relative standard deviations (RSDs) were lower than 8.3 % in all the cases, and recoveries varied from 90.2 to 94.6 %. Finally, in order to check the unequivocal identification of PTSO, mass spectrometry detection was applied. The proposed method is a simple procedure for monitoring PTSO in commercial feed, being possible to implement it in routine laboratories for quantification purposes and stability studies of the distributed products.