Efectos del consumo de cigarrillo en la presentación y severidad de la dismenorrea

Introducción: La dismenorrea se presenta como una patología cada vez más frecuente en mujeres de 16-30 años. Dentro de los factores asociados a su presentación, el consumo de tabaco ha revelado resultados contradictorios. El objetivo del presente estudio es explorar la asociación entre el consumo de cigarrillo y la presentación de dismenorrea, y determinar si los trastornos del ánimo y la depresión, alteran dicha asociación. Materiales y métodos: Se realizó un estudio de prevalencia analítica en mujeres de la Universidad del Rosario matriculadas en pregrado durante el primer semestre de 2013, para determinar la asociación entre el consumo de tabaco y la presentación de dismenorrea. En el estudio se tuvieron en cuenta variables tradicionalmente relacionadas con dismenorrea, incluyendo las variables ansiedad y depresión como potenciales variables de confusión. Los registros fueron analizados en el programa Estadístico IBM SPSS Statistics Versión 20.0. Resultados: Se realizaron 538 cuestionarios en total. La edad promedio fue 19.92±2.0 años. La prevalencia de dismenorrea se estimó en 89.3%, la prevalencia de tabaquismo 11.7%. No se encontró una asociación entre dismenorrea y tabaquismo (OR 3.197; IC95% 0.694-14.724). Dentro de las variables analizadas, la depresión y la ansiedad constituyen factores de riesgo independientes para la presentación de dismenorrea con una asociación estadísticamente significativa p=0.026 y p=0.024 respectivamente. El análisis multivariado encuentra como factor determinante en la presentación de dismenorrea, la interacción de depresión y ansiedad controlando por las variables tradicionales p<0.0001. Sin embargo, esta asociación se pierde cuando se analiza en la categoría de dismenorrea severa y gana relevancia el uso de métodos de anticoncepción diferentes a los hormonales, mientras que el hecho de haber iniciado la vida sexual presenta una tendencia limítrofe de riesgo. Conclusiones: No se puede demostrar que el tabaco es un factor asociado a la presentación de dismenorrea. Los trastornos del ánimo y la ansiedad constituyen factores determinantes a la presentación de dismenorrea independientemente de la presencia de otros concomitantes. Las variables de asociación se modifican cuando la variable dependiente se categoriza en su estado más severo. Se necesitan estudios más amplios y detallados para establecer dicha asociación.

La satisfacción del cliente bancario en Canadá: Diferencias entre canadienses e inmigrantes de la América Latina – Revisión y traducción

The measure of customer satisfaction level is one of the most important topics at present time in marketing science. In addition, its measure in the bank field takes force in view of the high level of competition inside it, even more so if the study counts “immigrants” as a variable in analysis, a much important variable in the demographic situation of Canada. Oliver (1980) proposes the model of “disconfirmation” to measure customer satisfaction level; this model confirms that the difference between customer perceived performance and customer expectations gives as result his satisfaction level (additional model). Presently multiple scales exist to evaluate and to quantify this satisfaction level, Parasuraman (1987) is the creator of the servqual scale, while Avkiran (1999) developed the bankserv scale in order to evaluate customer expectations and customer satisfaction level specifically inside the bank field; this scale was divided in four factors via factorial analysis. Literature suggests the presence of a relation between individual expectations and/or satisfaction level, and the individual tolerance level towards non-constructed situations (Newman, 2001). Hofstede (1980) developed five cultural dimensions worldwide; among these is the Uncertainty Avoidance Index (uai) that fits to the dimension directly related to customer expectations and customer satisfaction levels, since it measures the tolerance levels towards non-structured ituations. For this research I focused on the satisfaction model analysis proposed by Oliver (1980) based on Avkiran´s scale (1999), having the Latin American or Canadian origin as variables. The concept of Hofstede’s cultural differences leads me to propose two samples: 50 Canadian French speakers and 50 Latin American individuals (Canadian residents). Results demonstrate that in the Latin American group the expectations are in average higher that in the Canadian group, considering all four factors (Avkiran). Perceived performance and satisfaction level are higher in the Latin American group that in the Canadian group for “personal branch conduct” and “access to personalized services” factors, nevertheless, no statistically significant difference has been proved for “credibility” and “communication” factors. The expectations variable presents a mediating effect over the relation between variables uai (Latin American or Canadian origin) and satisfaction level. This effect is partial for “personal branch conduct” and perfect for “access to personalized services”.

Análisis económico de las vacunas 10-valente y 13-valente contra neumococo: revisión sistemática

Introducción: Las vacunas clásicamente han representado un método económico y eficaz para el control y prevención de múltiples enfermedades infecciosas. En los últimos años se han introducido nuevas vacunas contra neumococo a precios elevados, y los diferentes análisis económicos a nivel mundial de estas vacunas no muestran tendencias. El objetivo de este trabajo era resumir la evidencia existente a través de los diferentes estudios económicos evaluando las dos vacunas de segunda generación contra neumococo en la población a riesgo. Metodología: En este trabajo se realizo una revisión sistemática de la literatura en 8 bases de datos localizadas en diferentes partes del mundo y también que tuvieran literatura gris. Los artículos fueron inicialmente evaluados acorde a su titulo y resumen, posteriormente los elegidos se analizaron en su totalidad. Resultados: Se encontraron 404 artículos, de los cuales 20 fueron incluidos en el análisis final. Se encontró que la mayoría de los estudios se realizaron en áreas donde la enfermedad tiene una carga baja, como es Norte América y Europa, mientras que en los lugares del mundo donde la carga es mas alta, se realizaron pocos estudios. De igual manera se observo que la mayoría de los estudios mostraron por los menos ser costo efectivos respecto a la no vacunación, y en su totalidad las dos vacunas de segunda generación mostraron costo efectividad respecto a la vacunación con PCV-7. Los resultados de los estudios son muy heterogéneos, hasta dentro del mismo país, señalando la necesidad de guías para la conducción de este tipo de estudios. De igual manera, la mayoría de los estudios fueron financiados por farmacéuticas, mientras en un numero muy reducido por entes gubernamentales. Conclusiones: La mayoría de los estudios económicos sobre las vacunas de segunda generación contra neumococo han sido realizados en países con un alto índice de desarrollo económico y patrocinados por farmacéuticas. Dado que la mayoría de la carga de la enfermedad se encuentran en regiones con un menor nivel de desarrollo económico se deberían realizar mas en estas zonas. De igual manera, al ser la vacunación un asunto de salud publica y con un importante impacto económico los gobiernos deberían estar mas involucrados en los mismos.

Efectividad en redes Inter-Organizacionales : una aproximación al concepto y su medición

El concepto de efectividad en Redes Inter-organizacionales se ha investigado poco a pesar de la gran importancia en el desarrollo y sostenibilidad de la red. Es muy importante entender este concepto ya que cuando hablamos de Red, nos referimos a un grupo de más de tres organizaciones que trabajan juntas para alcanzar un objetivo colectivo que beneficia a cada miembro de la red. Esto nos demuestra la importancia de evaluar y analizar este fenómeno “Red Inter-organizacional” de forma más detallada para poder analizar que estructura, formas de gobierno, relaciones entre los miembros y entre otros factores, influyen en la efectividad y perdurabilidad de la Red Inter-organizacional. Esta investigación se desarrolla con el fin de plantear una aproximación al concepto de medición de la efectividad en Redes Inter-organizacionales. El trabajo se centrara en la recopilación de información y en la investigación documental, la cual se realizará por fases para brindarle al lector una mayor claridad y entendimiento sobre qué es Red, Red Inter-Organizacional, Efectividad. Y para finalizar se estudiara Efectividad en una Red Inter-organizacional.

¿Hacia una recentralización en Colombia?: una mirada desde el control fiscal excepcional

En materia de control fiscal territorial, se ha evidenciado la urgencia de una reforma en su estructura orgánica como consecuencia de los casos de corrupción que se han presentado en las entidades territoriales, los cuales han generado la intervención de la Contraloría General de la República en asuntos de carácter territorial, a través de una facultad constitucional denominada control fiscal excepcional. Dicha facultad no es ampliamente conocida y genera inquietud, pues no ha recibido un profundo estudio que permita determinar con claridad su carácter de excepcional, ya que en ciertos casos limita la competencia de las contralorías territoriales que puede traducirse en una nueva centralización. Es entonces que se emprende un análisis desde la perspectiva de la estructura del Estado, en el modelo descentralizado de las funciones de la Contraloría General de la República, donde el carácter limitante del control fiscal excepcional puede ser parte de un fenómeno que se denomina “recentralización. Es así que, a través del primer capítulo se desarrollan los conceptos de control fiscal, terminando con el análisis del modelo en la constitución de 1991, en el cual quedó establecido la facultad excepcional objeto de estudio. En el mismo sentido se estudia los pronunciamientos jurisprudenciales, como también los conceptos de descentralización y centralización para entender la finalidad del objeto de análisis, asimismo se revisó los casos relevantes entorno al control fiscal excepcional. Adicionalmente se construye un marco jurisprudencial para identificar la posición dominante de la Corte Constitucional y del Consejo de Estado, respecto al control fiscal excepcional. En la segunda parte del documento, primero se analiza cómo ha sido el proceso de centralización a la descentralización respecto del control fiscal, asimismo se expondrá el concepto de recentralización. Finalmente, se establece cuáles son los retos que se presentan en el fortalecimiento del control fiscal territorial, el papel en la lucha contra la corrupción y cómo se ha planteado desde otras esferas, un cambio del modelo del control fiscal territorial y una propuesta que recoge las apreciaciones estudiadas a lo largo de los cuatro capítulos de la investigación. Sobre la base de las consideraciones anteriores, se pretende dar un punto de vista diferente a la comunidad académica y además un estudio que permita una visión sobre la necesidad de reforzar el control fiscal territorial, como también frenar el retroceso que ha tenido a través del control fiscal excepcional, y de la misma manera la descentralización en Colombia.

Ecological and life-history traits predict bee species responses to environmental disturbances

The ability to predict the responses of ecological communities and individual species to human-induced environmental change remains a key issue for ecologists and conservation managers alike. Responses are often variable among species within groups making general predictions difficult. One option is to include ecological trait information that might help to disentangle patterns of response and also provide greater understanding of how particular traits link whole clades to their environment. Although this ‘‘trait-guild” approach has been used for single disturbances, the importance of particular traits on general responses to multiple disturbances has not been explored. We used a mixed model analysis of 19 data sets from throughout the world to test the effect of ecological and life-history traits on the responses of bee species to different types of anthropogenic environmental change. These changes included habitat loss, fragmentation, agricultural intensification, pesticides and fire. Individual traits significantly affected bee species responses to different disturbances and several traits were broadly predictive among multiple disturbances. The location of nests – above vs. below ground – significantly affected response to habitat loss, agricultural intensification, tillage regime (within agriculture) and fire. Species that nested above ground were on average more negatively affected by isolation from natural habitat and intensive agricultural land use than were species nesting below ground. In contrast below-ground-nesting species were more negatively affected by tilling than were above-ground nesters. The response of different nesting guilds to fire depended on the time since the burn. Social bee species were more strongly affected by isolation from natural habitat and pesticides than were solitary bee species. Surprisingly, body size did not consistently affect species responses, despite its importance in determining many aspects of individuals’ interaction with their environment. Although synergistic interactions among traits remain to be explored, individual traits can be useful in predicting and understanding responses of related species to global change.

Impact of menstrual cycle phase on insulin sensitivity measures and fasting lipids

There is evidence to suggest that insulin sensitivity may vary in response to changes in sex hormone levels. However, the results Of human studies designed to investigate changes in insulin sensitivity through the menstrual cycle have proved inconclusive. The aims of this Study were to 1) evaluate the impact of menstrual cycle phase on insulin sensitivity measures and 2) determine the variability Of insulin sensitivity measures within the same menstrual cycle phase. A controlled observational study of 13 healthy premenopausal women, not taking any hormone preparation and having regular menstrual cycles, was conducted. Insulin sensitivity (Si) and glucose effectiveness (Sg) were measured using an intravenous glucose tolerance test (IVGTT) with minimal model analysis. Additional Surrogate measures Of insulin sensitivity were calculated (homoeostasis model for insulin resistance [HOMA IR], quantitative insulin-to-glucose check index [QUICKI] and revised QUICKI [rQUICKI]), as well as plasma lipids. Each woman was tested in the luteal and follicular phases of her Menstrual cycle, and duplicate measures were taken in one phase of the cycle. No significant differences in insulin sensitivity (measured by the IVGTT or Surrogate markers) or plasma lipids were reported between the two phases of the menstrual cycle or between duplicate measures within the same phase. It was Concluded that variability in measures of insulin sensitivity were similar within and between menstrual phases.

A combined Bayesian Markovian approach for behaviour recognition

Numerous techniques exist which can be used for the task of behavioural analysis and recognition. Common amongst these are Bayesian networks and Hidden Markov Models. Although these techniques are extremely powerful and well developed, both have important limitations. By fusing these techniques together to form Bayes-Markov chains, the advantages of both techniques can be preserved, while reducing their limitations. The Bayes-Markov technique forms the basis of a common, flexible framework for supplementing Markov chains with additional features. This results in improved user output, and aids in the rapid development of flexible and efficient behaviour recognition systems.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.

Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.

Threshold-free object and ground point separation in LIDAR data

Light Detection And Ranging (LIDAR) is an important modality in terrain and land surveying for many environmental, engineering and civil applications. This paper presents the framework for a recently developed unsupervised classification algorithm called Skewness Balancing for object and ground point separation in airborne LIDAR data. The main advantages of the algorithm are threshold-freedom and independence from LIDAR data format and resolution, while preserving object and terrain details. The framework for Skewness Balancing has been built in this contribution with a prediction model in which unknown LIDAR tiles can be categorised as “hilly” or “moderate” terrains. Accuracy assessment of the model is carried out using cross-validation with an overall accuracy of 95%. An extension to the algorithm is developed to address the overclassification issue for hilly terrain. For moderate terrain, the results show that from the classified tiles detached objects (buildings and vegetation) and attached objects (bridges and motorway junctions) are separated from bare earth (ground, roads and yards) which makes Skewness Balancing ideal to be integrated into geographic information system (GIS) software packages.

Part load operation coefficient of air-conditioning system of public building

IPLV overall coefficient, presented by Air-Conditioning and Refrigeration Institute (ARI) of America, shows running/operation status of air-conditioning system host only. For overall operation coefficient, logical solution has not been developed, to reflect the whole air-conditioning system under part load. In this research undertaking, the running time proportions of air-conditioning systems under part load have been obtained through analysis on energy consumption data during practical operation in all public buildings in Chongqing. This was achieved by using analysis methods, based on the statistical energy consumption data distribution of public buildings month-by-month. Comparing with the weight number of IPLV, part load operation coefficient of air-conditioning system, based on this research, does not only show the status of system refrigerating host, but also reflects and calculate energy efficiency of the whole air-conditioning system. The coefficient results from the processing and analyzing of practical running data, shows the practical running status of area and building type (actual and objective) – not clear. The method is different from model analysis which gets IPLV weight number, in the sense that this method of coefficient results in both four equal proportions and also part load operation coefficient of air-conditioning system under any load rate as necessary.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

Auto-associative memory using n-tuple techniques

The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.