Comparing the quality of three models of postabortion care in public hospitals in Mexico City

artículo publicado en la revista Int Fam Plan Perspect. 2003 Sep;29(3):112-20

Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas

Sediment samples and hydrographic conditions were studied at 28 stations around Iceland. At these sites, Conductivity-Temperature-Depth (CTD) casts were conducted to collect hydrographic data and multicorer casts were conductd to collect data on sediment characteristics including grain size distribution, carbon and nitrogen concentration, and chloroplastic pigment concentration. A total of 14 environmental predictors were used to model sediment characteristics around Iceland on regional geographic space. For these, two approaches were used: Multivariate Adaptation Regression Splines (MARS) and randomForest regression models. RandomForest outperformed MARS in predicting grain size distribution. MARS models had a greater tendency to over- and underpredict sediment values in areas outside the environmental envelope defined by the training dataset. We provide first GIS layers on sediment characteristics around Iceland, that can be used as predictors in future models. Although models performed well, more samples, especially from the shelf areas, will be needed to improve the models in future.

Abundance and community structures of heterotrophic and oligotrophic bacteria from the Sierra Leone Abbyssal Plain

Colony counts on high and low-nutrient agar media incubated at 2 and 20 °C, Acridine Orange Direct Counts and biomasses are reported for sediments of the Sierra Leone Abyssal Plain. All isolates from low-nutrient agars also grew in nutrient-rich seawater broth (100 % SWB). However, a greater proportion of the 2 °C than of the 20 °C isolates grew in 2.5% SWB, containing 125 mg/l peptone and 25 mg/l yeast extract. Only 14 strains or 12.7% of the 2 °C isolates, but none of the 20 °C isolates, grew in 0.25 % SWB. Psychrophilic bacteria with maximum growth temperatures below 12 °C, isolated at 2 °C, were predominant among the cultivable bacteria from the surface layer. They required seawater for growth and belonged mainly to the Gram-negative genera Alteromonas and Vibrio. In contrast to the earlier view that psychrophily is connected with the Gram-negative cell type, it was found that cold-adapted bacteria of the Gram-positive genus Bacillus predominated in the 4 to 6 cm layer. The 20 °C isolates, however, were mostly Gram-positive, mesophilic, not dependent on seawater for growth, not able to utilize organic substrates at 4 °C, and belonged mainly to the genus Bacillus and to the Gram-positive cocci. The majority of the mesophilic bacilli most likely evolved from dormant spores, but not from actively metabolizing cells. It can be concluded that only the strains isolated at 2 °C can be regarded as indigenous to the deep-sea.

Comparison of several models for calculating ozone stomatal fluxes on a Mediterranean wheat cultivar (Triticum durum Desf. cv. Camacho)

Ozone stomatal fluxes were modeled for a 3-year period following different approaches for a commercial variety of durum wheat (Triticum durum Desf. cv. Camacho) at the phenological stage of anthesis. All models performed in the same range, although not all of them afforded equally significant results. Nevertheless, all of them suggest that stomatal conductance would account for the main percentage of ozone deposition fluxes. A new modeling approach was tested, based on a 3-D architectural model of the wheat canopy, and fairly accurate results were obtained. Plant species-specific measurements, as well as measurements of stomatal conductance and environmental parameters, were required. The method proposed for calculating ozone stomatal fluxes (FO(3_3-D)) from experimental gs data and modeling them as a function of certain environmental parameters in conjunction with the use of the YPLANT model seems to be adequate, providing realistic estimates of the canopy FO(3_3-D), integrating and not neglecting the contribution of the lower leaves with respect to the flag leaf, although a further development of this model is needed.

Application of Deadlock Risk Evaluation of Architectural Models

Software architectural evaluation is a key discipline used to identify, at early stages of a real-time system (RTS) development, the problems that may arise during its operation. Typical mechanisms supporting concurrency, such as semaphores, mutexes or monitors, usually lead to concurrency problems in execution time that are difficult to be identified, reproduced and solved. For this reason, it is crucial to understand the root causes of these problems and to provide support to identify and mitigate them at early stages of the system lifecycle. This paper aims to present the results of a research work oriented to the development of the tool called ‘Deadlock Risk Evaluation of Architectural Models’ (DREAM) to assess deadlock risk in architectural models of an RTS. A particular architectural style, Pipelines of Processes in Object-Oriented Architectures–UML (PPOOA) was used to represent platform-independent models of an RTS architecture supported by the PPOOA –Visio tool. We validated the technique presented here by using several case studies related to RTS development and comparing our results with those from other deadlock detection approaches, supported by different tools. Here we present two of these case studies, one related to avionics and the other to planetary exploration robotics. Copyright © 2011 John Wiley & Sons, Ltd.

Towards resource usage analysis of miniZinc models

We present a method for the static resource usage analysis of MiniZinc models. The analysis can infer upper bounds on the usage that a MiniZinc model will make of some resources such as the number of constraints of a given type (equality, disequality, global constraints, etc.), the number of variables (search variables or temporary variables), or the size of the expressions before calling the solver. These bounds are obtained from the models independently of the concrete input data (the instance data) and are in general functions of sizes of such data. In our approach, MiniZinc models are translated into Ciao programs which are then analysed by the CiaoPP system. CiaoPP includes a parametric analysis framework for resource usage in which the user can define resources and express the resource usage of library procedures (and certain program construets) by means of a language of assertions. We present the approach and report on a preliminary implementation, which shows the feasibility of the approach, and provides encouraging results.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

Rational invariants on the space of all structures of algebras on a two-dimensional vector space

Rational invariants on the space of all structures of algebras on a two-dimensional vector space

Development of mathematical models to elaborate strategies, select alternatives and development of plans for adaptation of communities to climate change in different geographical areas including costs to implement it.

There is evidence that the climate changes and that now, the change is influenced and accelerated by the CO2 augmentation in atmosphere due to combustion by humans. Such ?Climate change? is on the policy agenda at the global level, with the aim of understanding and reducing its causes and to mitigate its consequences. In most countries and international organisms UNO (e.g. Rio de Janeiro 1992), OECD, EC, etc . . . the efforts and debates have been directed to know the possible causes, to predict the future evolution of some variable conditioners, and trying to make studies to fight against the effects or to delay the negative evolution of such. The Protocol of Kyoto 1997 set international efforts about CO2 emissions, but it was partial and not followed e.g. by USA and China . . . , and in Durban 2011 the ineffectiveness of humanity on such global real challenges was set as evident. Among all that, the elaboration of a global model was not boarded that can help to choose the best alternative between the feasible ones, to elaborate the strategies and to evaluate the costs, and the authors propose to enter in that frame for study. As in all natural, technological and social changes, the best-prepared countries will have the best bear and the more rapid recover. In all the geographic areas the alternative will not be the same one, but the model must help us to make the appropriated decision. It is essential to know those areas that are more sensitive to the negative effects of climate change, the parameters to take into account for its evaluation, and comprehensive plans to deal with it. The objective of this paper is to elaborate a mathematical model support of decisions, which will allow to develop and to evaluate alternatives of adaptation to the climatic change of different communities in Europe and Latin-America, mainly in especially vulnerable areas to the climatic change, considering in them all the intervening factors. The models will consider criteria of physical type (meteorological, edaphic, water resources), of use of the ground (agriculturist, forest, mining, industrial, urban, tourist, cattle dealer), economic (income, costs, benefits, infrastructures), social (population), politician (implementation, legislation), educative (Educational programs, diffusion) and environmental, at the present moment and the future. The intention is to obtain tools for aiding to get a realistic position for these challenges, which are an important part of the future problems of humanity in next decades.

Development of mathematical models to elaborate strategies, to select alternatives and the development of plans for the adaptation of communities to climate change in different geographical areas including costs to implement it

Climate change is on the policy agenda at the global level, with the aim of understanding and reducing its causes and to mitigate its consequences. In most of the countries and international organisms UNO, OECD, EC, etc … the efforts and debates have been directed to know the possible causes, to predict the future evolution of some variable conditioners, and trying to make studies to fight against the effects or to delay the negative evolution of such. Nevertheless, the elaboration of a global model was not boarded that can help to choose the best alternative between the feasible ones, to elaborate the strategies and to evaluate the costs. As in all natural, technological and social changes, the best-prepared countries will have the best bear and the more rapid recover. In all the geographic areas the alternative will not be the same one, but the model should help us to make the appropriated decision. It is essential to know those areas that are more sensitive to the negative effects of climate change, the parameters to take into account for its evaluation, and comprehensive plans to deal with it. The objective of this paper is to elaborate a mathematical model support of decisions, that will allow to develop and to evaluate alternatives of adaptation to the climatic change of different communities in Europe and Latin-America, mainly, in vulnerable areas to the climatic change, considering in them all the intervening factors. The models will take into consideration criteria of physical type (meteorological, edaphic, water resources), of use of the ground (agriculturist, forest, mining, industrial, urban, tourist, cattle dealer), economic (income, costs, benefits, infrastructures), social (population), politician (implementation, legislation), educative (Educational programs, diffusion), sanitary and environmental, at the present moment and the future.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

A CAD framework for the characterization and use of Memristor models

In the recent years the missing fourth component, the memristor, was successfully synthesized. However, the mathematical complexity and variety of the models behind this component, in addition to the existence of convergence problems in the simulations, make the design of memristor-based applications long and difficult. In this work we present a memristor model characterization framework which supports the automated generation of subcircuit files. The proposed environment allows the designer to choose and parameterize the memristor model that best suits for a given application. The framework carries out characterizing simulations in order to study the possible non-convergence problems, solving the dependence on the simulation conditions and guaranteeing the functionality and performance of the design. Additionally, the occurrence of undesirable effects related to PVT variations is also taken into account. By performing a Monte Carlo or a corner analysis, the designer is aware of the safety margins which assure the correct device operation.