Journal of Clinical Psychology in Medical Settings, 2005
The aim of this study was to assess the relationships between depressive symptoms and symptom-cen... more The aim of this study was to assess the relationships between depressive symptoms and symptom-centered panic-fear (P-F), and reports of health-related quality of life (HRQOL), in persons with near-fatal asthma (NFA), controlling for age, gender, and pulmonary function. Forty persons with NFA were interviewed. Sociodemographic and clinical asthma-related information were collected. HRQOL was assessed by the SF-36 Health Questionnaire, depressive symptoms were assessed by the Beck Depression Inventory, and P-F was assessed by the P-F scale of the Asthma Symptom Checklist. Multiple regression analyses were carried out with the Physical Component Summary (PCS) and the Mental Component Summary (MCS) of the SF-36 as a dependent variable, and depressive symptoms, P-F, age, gender, and pulmonary function as independent variables. Results showed that P-F and age were associated with PCS, whereas depressive symptoms accounted for a marked percentage of the variance explained in MCS. Neither gender nor pulmonary function were related to HRQOL. In conclusion, depressive symptoms and P-F play an important role in how persons with NFA assess their HRQOL. These patient-centered variables are potentially modifiable and may offer new ways to intervene in order to improve HRQOL in persons with NFA.
Revista De La Real Academia De Ciencias Exactas Fisicas Y Naturales Serie A-matematicas
We define the class of upper staircase matrices on ω. Such matrices have a plethora of eigenvalue... more We define the class of upper staircase matrices on ω. Such matrices have a plethora of eigenvalues and eigenvectors, and they are hypercylic. We show that countably many strictly upper triangular matrices on ω which are also upper staircase have a common hypercyclic subspace. This last result partially extends a theorem of Bès and Conejero.
This paper presents a new algorithm for designing fuzzy systems. It automatically identifies the ... more This paper presents a new algorithm for designing fuzzy systems. It automatically identifies the optimum number of rules in the fuzzy knowledge base and adjusts the parameters defining them. This algorithm hybridizes the robustness and capability of evolutive algorithms with multiobjective optimization techniques which are able to minimize both the prediction error of the fuzzy system and its complexity, i.e. the number of parameters. In order to guide the search and accelerate the algorithm’s convergence, new specific genetic operators have been designed, which combine several heuristic and analytical methods. The results obtained show the validity of the proposed algorithm for the identification of fuzzy systems when applied to time-series prediction.
The aim of this work is to present a critical review on slurry bioreactors (SB) and their applica... more The aim of this work is to present a critical review on slurry bioreactors (SB) and their application to bioremediation of soils and sediments polluted with recalcitrant and toxic compounds. The scope of the review encompasses the following subjects: (i) process fundamentals of SB and analysis of advantages and disadvantages; (ii) the most recent applications of SB to laboratory scale and commercial scale soil bioremediation, with a focus on pesticides, explosives, polynuclear aromatic hydrocarbons, and chlorinated organic pollutants; (iii) trends on the use of surfactants to improve availability of contaminants and supplementation with degradable carbon sources to enhance cometabolism of pollutants; (iv) recent findings on the utilization of electron acceptors other than oxygen; (v) bioaugmentation and advances made on characterization of microbial communities of SB; (vi) developments on ecotoxicity assays aimed at evaluating bioremediation efficiency of the process.
Fuzzy systems comprise one of the models best suited to function approximation problems, but due ... more Fuzzy systems comprise one of the models best suited to function approximation problems, but due to the non linear dependencies between the parameters that define the system rules, the solution search space for this type of problems contains many local optima. Another important issue is the identification of the optimum structure for the fuzzy system. Depending on the complexity of the model, different solutions can be found with different compromises between their approximation error and their generalization properties. Thus, the problem becomes a multi-objective problem with two clearly competing objectives, the complexity of the model and its approximation error. The algorithms proposed in the literature to construct fuzzy systems from examples usually refine iteratively a unique model until a compromise between its complexity and its approximation error is found. This is not an adequate approach for this problem because there exists a set of Pareto-optimum solutions that can be considered equivalent. Thus, we propose the use of multi-objective evolutionary algorithms because, as they maintain a population of potential solutions for the problem, they are able to optimize both objectives simultaneously. We also incorporate some new expert evolutionary operators that try to avoid the generation of worse solutions in order to accelerate the convergence of the algorithm. The proposed algorithm is tested with some target functions widely used in the literature and the results obtained are compared to other approaches.
We have developed a classification function that is capable of discriminating between anticoccidi... more We have developed a classification function that is capable of discriminating between anticoccidial and nonanticoccidial compounds with different structural patterns. For this purpose, we calculated the Markovian electron delocalization negentropies of several compounds. These molecular descriptors, which act as molecular fingerprints, are derived from an electronegativity-weighted stochastic matrix (1Π). The method attempts to describe the delocalization of electrons with time during the process of molecule formation by considering the 3D environment of the atoms. Accordingly, the entropies of this random process are used as molecular descriptors. The present study involves a stochastic generalization of the original idea described by Kier, which concerned the use of molecular negentropies in QSAR. Linear discriminant analysis allowed us to fit the discriminant function. This function has given rise to a good classification of 82.35% (28 anticoccidials out of 34) and 91.8% of inactive compounds (56/61) in training series. An overall classification of 88.42% (84/95) was achieved. Validation of the model was carried out by means of an external predicting series and this gave a global predictability of 93.1%. Finally, we report the experimental assay (more than 95% of lesion control) of two compounds selected from a large data set through virtual screening. We conclude that the approach described here seems to be a promising 3D-QSAR tool based on the mathematical theory of stochastic processes.
Journal of Clinical Psychology in Medical Settings, 2005
The aim of this study was to assess the relationships between depressive symptoms and symptom-cen... more The aim of this study was to assess the relationships between depressive symptoms and symptom-centered panic-fear (P-F), and reports of health-related quality of life (HRQOL), in persons with near-fatal asthma (NFA), controlling for age, gender, and pulmonary function. Forty persons with NFA were interviewed. Sociodemographic and clinical asthma-related information were collected. HRQOL was assessed by the SF-36 Health Questionnaire, depressive symptoms were assessed by the Beck Depression Inventory, and P-F was assessed by the P-F scale of the Asthma Symptom Checklist. Multiple regression analyses were carried out with the Physical Component Summary (PCS) and the Mental Component Summary (MCS) of the SF-36 as a dependent variable, and depressive symptoms, P-F, age, gender, and pulmonary function as independent variables. Results showed that P-F and age were associated with PCS, whereas depressive symptoms accounted for a marked percentage of the variance explained in MCS. Neither gender nor pulmonary function were related to HRQOL. In conclusion, depressive symptoms and P-F play an important role in how persons with NFA assess their HRQOL. These patient-centered variables are potentially modifiable and may offer new ways to intervene in order to improve HRQOL in persons with NFA.
Revista De La Real Academia De Ciencias Exactas Fisicas Y Naturales Serie A-matematicas
We define the class of upper staircase matrices on ω. Such matrices have a plethora of eigenvalue... more We define the class of upper staircase matrices on ω. Such matrices have a plethora of eigenvalues and eigenvectors, and they are hypercylic. We show that countably many strictly upper triangular matrices on ω which are also upper staircase have a common hypercyclic subspace. This last result partially extends a theorem of Bès and Conejero.
This paper presents a new algorithm for designing fuzzy systems. It automatically identifies the ... more This paper presents a new algorithm for designing fuzzy systems. It automatically identifies the optimum number of rules in the fuzzy knowledge base and adjusts the parameters defining them. This algorithm hybridizes the robustness and capability of evolutive algorithms with multiobjective optimization techniques which are able to minimize both the prediction error of the fuzzy system and its complexity, i.e. the number of parameters. In order to guide the search and accelerate the algorithm’s convergence, new specific genetic operators have been designed, which combine several heuristic and analytical methods. The results obtained show the validity of the proposed algorithm for the identification of fuzzy systems when applied to time-series prediction.
The aim of this work is to present a critical review on slurry bioreactors (SB) and their applica... more The aim of this work is to present a critical review on slurry bioreactors (SB) and their application to bioremediation of soils and sediments polluted with recalcitrant and toxic compounds. The scope of the review encompasses the following subjects: (i) process fundamentals of SB and analysis of advantages and disadvantages; (ii) the most recent applications of SB to laboratory scale and commercial scale soil bioremediation, with a focus on pesticides, explosives, polynuclear aromatic hydrocarbons, and chlorinated organic pollutants; (iii) trends on the use of surfactants to improve availability of contaminants and supplementation with degradable carbon sources to enhance cometabolism of pollutants; (iv) recent findings on the utilization of electron acceptors other than oxygen; (v) bioaugmentation and advances made on characterization of microbial communities of SB; (vi) developments on ecotoxicity assays aimed at evaluating bioremediation efficiency of the process.
Fuzzy systems comprise one of the models best suited to function approximation problems, but due ... more Fuzzy systems comprise one of the models best suited to function approximation problems, but due to the non linear dependencies between the parameters that define the system rules, the solution search space for this type of problems contains many local optima. Another important issue is the identification of the optimum structure for the fuzzy system. Depending on the complexity of the model, different solutions can be found with different compromises between their approximation error and their generalization properties. Thus, the problem becomes a multi-objective problem with two clearly competing objectives, the complexity of the model and its approximation error. The algorithms proposed in the literature to construct fuzzy systems from examples usually refine iteratively a unique model until a compromise between its complexity and its approximation error is found. This is not an adequate approach for this problem because there exists a set of Pareto-optimum solutions that can be considered equivalent. Thus, we propose the use of multi-objective evolutionary algorithms because, as they maintain a population of potential solutions for the problem, they are able to optimize both objectives simultaneously. We also incorporate some new expert evolutionary operators that try to avoid the generation of worse solutions in order to accelerate the convergence of the algorithm. The proposed algorithm is tested with some target functions widely used in the literature and the results obtained are compared to other approaches.
We have developed a classification function that is capable of discriminating between anticoccidi... more We have developed a classification function that is capable of discriminating between anticoccidial and nonanticoccidial compounds with different structural patterns. For this purpose, we calculated the Markovian electron delocalization negentropies of several compounds. These molecular descriptors, which act as molecular fingerprints, are derived from an electronegativity-weighted stochastic matrix (1Π). The method attempts to describe the delocalization of electrons with time during the process of molecule formation by considering the 3D environment of the atoms. Accordingly, the entropies of this random process are used as molecular descriptors. The present study involves a stochastic generalization of the original idea described by Kier, which concerned the use of molecular negentropies in QSAR. Linear discriminant analysis allowed us to fit the discriminant function. This function has given rise to a good classification of 82.35% (28 anticoccidials out of 34) and 91.8% of inactive compounds (56/61) in training series. An overall classification of 88.42% (84/95) was achieved. Validation of the model was carried out by means of an external predicting series and this gave a global predictability of 93.1%. Finally, we report the experimental assay (more than 95% of lesion control) of two compounds selected from a large data set through virtual screening. We conclude that the approach described here seems to be a promising 3D-QSAR tool based on the mathematical theory of stochastic processes.
Uploads
Papers by Héctor Gónz