The relevance of seed size in modulating leaf physiology and early plant performance in two tree species

he size of seeds and the microsite of seed dispersal may affect the early establishment of seedlings through different physiological processes. Here, we examined the effects of seed size and light availability on seedling growth and survival, and whether such effects were mediated by water use efficiency. Acorns of Quercus petraea and the more drought-tolerant Quercus pyrenaica were sowed within and around a tree canopy gap in a sub-Mediterranean forest stand. We monitored seedling emergence and measured predawn leaf water potential (Ψpd), leaf nitrogen per unit area (Na), leaf mass per area, leaf carbon isotope composition (δ13C) and plant growth at the end of the first summer. Survival was measured on the next year. Path analysis revealed a consistent pattern in both species of higher δ13C as Ψpd decreased and higher δ13C as seedlings emerged later in the season, indicating an increase in 13C as the growing season is shorter and drier. There was a direct positive effect of seed size on δ13C in Q. petraea that was absent in Q. pyrenaica. Leaf δ13C had no effect on growth but the probability of surviving until the second year was higher for those seedlings of Q. pyrenaica that had lower δ13C on the first year. In conclusion, leaf δ13C is affected by seed size, seedling emergence time and the availability of light and water, however, leaf δ13C is irrelevant for first year growth, which is directly dependent on the amount of seed reserves.

Evaluation of a User-Adapted Spoken Language Dialogue System: Measuring the Relevance of the Contextual Information Sources

We present an evaluation of a spoken language dialogue system with a module for the management of userrelated information, stored as user preferences and privileges. The flexibility of our dialogue management approach, based on Bayesian Networks (BN), together with a contextual information module, which performs different strategies for handling such information, allows us to include user information as a new level into the Context Manager hierarchy. We propose a set of objective and subjective metrics to measure the relevance of the different contextual information sources. The analysis of our evaluation scenarios shows that the relevance of the short-term information (i.e. the system status) remains pretty stable throughout the dialogue, whereas the dialogue history and the user profile (i.e. the middle-term and the long-term information, respectively) play a complementary role, evolving their usefulness as the dialogue evolves.

Relevance of motion-related assessment metrics in laparoscopic surgery

INTRODUCTION: Motion metrics have become an important source of information when addressing the assessment of surgical expertise. However, their direct relationship with the different surgical skills has not been fully explored. The purpose of this study is to investigate the relevance of motion-related metrics in the evaluation processes of basic psychomotor laparoscopic skills, as well as their correlation with the different abilities sought to measure. METHODS: A framework for task definition and metric analysis is proposed. An explorative survey was first conducted with a board of experts to identify metrics to assess basic psychomotor skills. Based on the output of that survey, three novel tasks for surgical assessment were designed. Face and construct validation study was performed, with focus on motion-related metrics. Tasks were performed by 42 participants (16 novices, 22 residents and 4 experts). Movements of the laparoscopic instruments were registered with the TrEndo tracking system and analyzed. RESULTS: Time, path length and depth showed construct validity for all three tasks. Motion smoothness and idle time also showed validity for tasks involving bi-manual coordination and tasks requiring a more tactical approach respectively. Additionally, motion smoothness and average speed showed a high internal consistency, proving them to be the most task-independent of all the metrics analyzed. CONCLUSION: Motion metrics are complementary and valid for assessing basic psychomotor skills, and their relevance depends on the skill being evaluated. A larger clinical implementation, combined with quality performance information, will give more insight on the relevance of the results shown in this study.

Relevance of the glottal pulse and the vocal tract in gender detection

Gender detection is a very important objective to improve efficiency in tasks as speech or speaker recognition, among others. Traditionally gender detection has been focused on fundamental frequency (f0) and cepstral features derived from voiced segments of speech. The methodology presented here consists in obtaining uncorrelated glottal and vocal tract components which are parameterized as mel-frequency coefficients. K-fold and cross-validation using QDA and GMM classifiers showed that better detection rates are reached when glottal source and vocal tract parameters are used in a gender-balanced database of running speech from 340 speakers.

Expressive power of binary relevance and chain classifiers based on Bayesian Networks for multi-label classification

Bayesian network classifiers are widely used in machine learning because they intuitively represent causal relations. Multi-label classification problems require each instance to be assigned a subset of a defined set of h labels. This problem is equivalent to finding a multi-valued decision function that predicts a vector of h binary classes. In this paper we obtain the decision boundaries of two widely used Bayesian network approaches for building multi-label classifiers: Multi-label Bayesian network classifiers built using the binary relevance method and Bayesian network chain classifiers. We extend our previous single-label results to multi-label chain classifiers, and we prove that, as expected, chain classifiers provide a more expressive model than the binary relevance method.

Non uniform embedding based on relevance analysis with reduced computational complexity: application to the detection of pathologies from biosignal recordings

Nonlinear analysis tools for studying and characterizing the dynamics of physiological signals have gained popularity, mainly because tracking sudden alterations of the inherent complexity of biological processes might be an indicator of altered physiological states. Typically, in order to perform an analysis with such tools, the physiological variables that describe the biological process under study are used to reconstruct the underlying dynamics of the biological processes. For that goal, a procedure called time-delay or uniform embedding is usually employed. Nonetheless, there is evidence of its inability for dealing with non-stationary signals, as those recorded from many physiological processes. To handle with such a drawback, this paper evaluates the utility of non-conventional time series reconstruction procedures based on non uniform embedding, applying them to automatic pattern recognition tasks. The paper compares a state of the art non uniform approach with a novel scheme which fuses embedding and feature selection at once, searching for better reconstructions of the dynamics of the system. Moreover, results are also compared with two classic uniform embedding techniques. Thus, the goal is comparing uniform and non uniform reconstruction techniques, including the one proposed in this work, for pattern recognition in biomedical signal processing tasks. Once the state space is reconstructed, the scheme followed characterizes with three classic nonlinear dynamic features (Largest Lyapunov Exponent, Correlation Dimension and Recurrence Period Density Entropy), while classification is carried out by means of a simple k-nn classifier. In order to test its generalization capabilities, the approach was tested with three different physiological databases (Speech Pathologies, Epilepsy and Heart Murmurs). In terms of the accuracy obtained to automatically detect the presence of pathologies, and for the three types of biosignals analyzed, the non uniform techniques used in this work lightly outperformed the results obtained using the uniform methods, suggesting their usefulness to characterize non-stationary biomedical signals in pattern recognition applications. On the other hand, in view of the results obtained and its low computational load, the proposed technique suggests its applicability for the applications under study.

Local relevance evaluation in the accreditation bodies for engineering masters programs

Accreditation models in the international context mainly consider the evaluation of learning outcomes and the ability of programs (or higher education institutions) to achieve the educational objectives stated in their mission. However, it is not clear if these objectives and therefore their outcomes satisfy real national and regional needs, a critical point in engineering master's programs, especially in developing countries. The aim of this paper is to study the importance of the local relevancy evaluation of these programs and to analyze the main models of quality assurance and accreditation bodies of USA, Europe and Latin America, in order to ascertain whether the relevancy is evaluated or not. After a literature review, we found that in a free-market economic context and international education, the accreditation of master's programs follows an international accreditation model, and doesńt take in account in most cases criteria and indicators for local relevancy. It concludes that it is necessary both, international accreditation to ensure the effectiveness of the program (achievement of learning outcomes) and the national accreditation through which it could ensure local relevancy of programs, for which we are giving some indicators.

Relevance evaluation of engineering masters program in Peru

In a context of mass higher education, it is necessary to ensure not only quality but also the relevance of engineering master's programs, namely the appropriateness of the objectives and outcomes to the needs and interests of the program beneficiaries. After a literature review we analyzed the evaluation models of three organizations in Peru: the Board of Evaluation, Accreditation and Certification of the University Education Quality CONEAU, the Institute of Quality and Accreditation of Computing, Engineering and Technology - ICACIT and the Pontificia Universidad Catolica del Peru. The result of this study is a model for relevance evaluation for an engineering master¿s program in Peru.

Relevance of Higher Education. How to measure it? The case of masters of engineering in Peru

Existing evaluation models for higher education have, mainly, accreditation purposes, and evaluate the efficiency of training programs, that is to say, the degree of suitability between the educational results and the objectives of the program. However, it is not guaranteed that those objectives adequate to the needs and real interests of students and stakeholders, that is to say, they do not assess the relevance of the programs, a very important aspect in developing countries. From the review of experiences, this paper proposes a model for evaluating the relevance of engineering masters program, and applies it to the case of a master?s degree at the University of Piura, Peru. We conclude that the proposed model is applicable to other masters program, offers an objective way for determining is a training program keep being relevant, and identifies improvement opportunities