Prediction of Depressive Behaviors in Social Networks with Nave Bayes Algorithm

Hoy en día, la depresión se ha convertido en una de las enfermedades más graves y, con mucha frecuencia, fatales para cada uno de sus pacientes en todo el mundo que padecen esta afección. Incluso para miles y miles de seres humanos que la padecen, ni siquiera conocen su existencia, o no saben diferenciar entre lo que sienten y lo que sufren por ello. Actualmente con todas las nuevas tecnologías que nos acompañan existen algunas dedicadas a la investigación, la gestión rápida de datos, algoritmos inteligentes y algunos lenguajes de programación que hacen que los estudios científicos sean más fáciles y maleables en su procesamiento. Uno de ellos es muy innovador por el tiempo que se ha empleado, especialmente para bases de datos y todo lo que tiene que ver con parámetros que nos ayudan a medir, indagar, comparar. Además de esto, también tenemos variable aleatoria (RV) o aprendizaje bayesiano, las posibilidades de un evento A pueden ser determinantes, también con el conocimiento de que A opta por una cierta peculiaridad que determina sus posibilidades. El teorema de Bayes (BT) comprende posibilidades inversas al teorema de la posibilidad total. El teorema de posibilidades totales hace inferencia sobre un evento B, a partir de los resultados de los eventos A. Por su parte, Bayes calcula la posibilidad de A condicional a B. Existen numerosas aplicaciones de las mismas, pero suelen estar más dedicadas a redes convolucionales, clasificatorias de imágenes, detección de otras enfermedades en el tiempo, procesamiento del lenguaje natural y también sistemas de pronóstico financiero, en el caso de la depresión como enfermedad o condición médica, ciencia de datos y uno de los programas de código más poderosos Python, y algunas bibliotecas existentes como Keras ya sincronizado con TensorFlow como marco, podríamos hacer numerosos hallazgos en muchas áreas no estudiadas relacionadas con la depresión como reconocimiento de texto (TR). Muchos de los hallazgos más recientes relacionados con la depresión son muy fáciles de analizar en las redes sociales, siendo los más utilizados por 7 de cada 10 personas en todo el mundo. Cada uno de ellos deja una huella de emociones, sentimientos, reacciones, fotografías, incluso textos. Python es uno de los lenguajes de programación más usados y amigables en su procesamiento y construcción de código, por lo que estas investigaciones y nuevos descubrimientos suceden de manera continua y fructífera al mismo tiempo.ITESO, A. C

Decision-Making Model for Offshore Offloading Operations Based on Probabilistic Risk Assessment

To explore offshore oil fields in deepwater, the use of a floating production storage and offloading (FPSO) unit coupled to a shuttle tanker is economically and technically feasible. Shuttle tankers like system for oil transportation are increasingly being accepted as a preferred transportation method for remote and deepwater offshore developments. The offloading operation is considered one of the riskiest operations in offshore environment. The chapter presents a risk-based analysis method aiming at defining the risk profile associated with an offloading operation. For offloading operations, the risk profile is usually evaluated considering that the offloading operation has an approximate duration of 24 hours. The method follows three basic steps: identification of hazard, definition of failure scenarios and their probability of occurrence, and evaluation of failure consequences. The decision-making theory is used to evaluate the possibility of emergency disconnection during the operation. The method is applied to evaluate the risk profile of an offloading operation in Campos Basin, Brazil, considering a FPSO moored with Differentiated Complacent Anchoring System (DICAS). The method is used to model the risk scenario associated with shuttle tanker main engine failure as initiating event. The changes in environmental conditions have great influence in risk profile and increase the probability of disconnection

De los marcadores a la marcación en el discurso.

The category of discourse marker (DM) has been aplied in diverse senses and theoretical perspectives in hispanic linguistics that make imposible to find a term including all kind of phenomena classified as discourse markers. The hypothesis of this paper is that this diversity is vinculated to a methodological perspective where most of the work is based on studying the function of each marker, rather than analyzing the slots where discourse markers operate, including other kinds of constructions that are not always grammaticalized. On this base, the paper proposes the category of discourse marking as a macrofunction that can be subcategorized in diferent marking functions, rather than the perpective of describing units on the basis of other marking functions that are not fixed and grammaticalizedEl concepto de marcador del discurso (MD) ha sido utilizado en diversas acepciones y desde distintas perspectivas teóricas, por lo que resulta complejo encontrar una definición precisa del término que se ajuste a todas las unidades que suelen ser así clasificadas. La hipótesis de partida es que esta diversidad de conceptualizaciones está ligada a que los estudios se han dedicado a describir el funcionamiento de unidades, y en pocas ocasiones se centran sus funciones discursivas en calidad de huecos funcionales que pueden ser desempeñados por distintas construcciones. A partir de esta premisa, se propone el término de marcación del discurso como una macrofunción que puede ser subcategorizada a partir de las funciones marcadoras, más que de las unidades específicas que realizan esta función, basados en ejemplos no gramaticalizados que funcionan en este nivel

Transmitter and Receiver Equalizers Optimization Methodologies for High-Speed Links in Industrial Computer Platforms Post-Silicon Validation

As microprocessor design scales to nanometric technology, traditional post-silicon validation techniques are inappropriate to get a full system functional coverage. Physical complexity and extreme technology process variations introduce design challenges to guarantee performance over process, voltage, and temperature conditions. In addition, there is an increasingly higher number of mixed-signal circuits within microprocessors. Many of them correspond to high-speed input/output (HSIO) links. Improvements in signaling methods, circuits, and process technology have allowed HSIO data rates to scale beyond 10 Gb/s, where undesired effects can create multiple signal integrity problems. With all of these elements, post-silicon validation of HSIO links is tough and time-consuming. One of the major challenges in electrical validation of HSIO links lies in the physical layer (PHY) tuning process, where equalization techniques are used to cancel these undesired effects. Typical current industrial practices for PHY tuning require massive lab measurements, since they are based on exhaustive enumeration methods. In this work, direct and surrogate-based optimization methods, including space mapping, are proposed based on suitable objective functions to efficiently tune the transmitter and receiver equalizers. The proposed methodologies are evaluated by lab measurements on realistic industrial post-silicon validation platforms, confirming dramatic speed up in PHY tuning and substantial performance improvement

Mercury and selenium binding biomolecules in terrestrial mammals (Cervus elaphus and Sus scrofa) from a mercury exposed area

Acknowledgements The authors are grateful to Junta de Comunidades de Castilla-La Mancha (PCC-05-004-2, PAI06-0094, PCI-08-0096, PEII09-0032-5329) and the Ministerio de Economía y Competitividad (CTQ2013-48411-P) for financial support. M.J. Patiño Ropero acknowledges the Junta de Comunidades de Castilla-La Mancha for her PhD. fellowship.Peer reviewedPostprin

Methane emission by alpaca and sheep fed on lucerne hay or grazed on pastures of perennial ryegrass/white clover or birdsfoot trefoil

Based on the knowledge that alpaca (Lama pacos) have a lower fractional outflow rate of feed particles (particulate FOR) from their forestomach than sheep (San Martin 1987), the current study measured methane (CH4) production and other digestion parameters in these species in three successive experiments (1, 2 and 3): Experiment 1, lucerne hay fed indoors; Experiment 2, grazed on perennial ryegrass/white clover pasture (PRG/WC); and Experiment 3, grazed on birdsfoot trefoil (Lotus corniculatits) pasture (Lotus). Six male alpaca and six castrated Romney sheep were simultaneously and successively fed on the forages either ad libitium or at generous herbage allowances (grazing). CH4 production (g/day) (using the sulphur hexafluoride tracer technique), voluntary feed intake (VFI), diet quality, and protozoa counts and volatile fatty acid concentrations in samples of forestomach contents were determined. In addition, feed digestibility, energy and nitrogen (N) balances and microbial N supply from the forestomach (using purine derivatives excretion) were measured in Experiment 1. Diets selected by alpaca were of lower quality than those selected by sheep, and the voluntary gross energy intakes (GEI, MJ) per kg of liveweight(0.75) were consistently lower (P0.05) in their CH4 yields (% GEI) when fed on lucerne hay (5.1 v. 4.7), but alpaca had a higher CH4 yield when fed on PRG/WC (9.4 v. 7.5, P0.05) in diet N partition or microbial N yield, but alpaca had higher (P<0.05) neutral detergent fibre digestibility (0.478 v. 0.461) and lower (P<0.01) urinary energy losses (5.2 v. 5.8 % GEI) than sheep. It is suggested that differences between these species in forestomach particulate FOR might have been the underlying physiological mechanism responsible for the differences in CH4 yield, although the between-species differences in VFI and diet quality also had a major effect on it

The Unequal Effects of Covid-19 on Economists' Research Productivity

The current lock-down measures are expected to disproportionately reduce women's labor productivity in the short run. This paper analyzes the effects of these measures on economists' research productivity. We explore the patterns of working papers publications using data from the NBER Working Papers Series, the CEPR Discussion Paper Series, the newly established research repository Covid Economics: Vetted and Real Time Papers and VoxEU columns. Our analysis suggests that although the relative number of female authors in non-pandemic related research has remained stable with respect to recent years (at around 20%), women constitute only 12% of total number of authors working on COVID-19 research. Moreover, we see that it is primarily senior economists who are contributing to this new area. Mid-career and junior economists record the biggest gap between non-COVID and COVID research, and the gender di erences are particularly stark at the mid-career level. Mid-career female economists have not yet started working on this new research area: only 12 mid-career female authors have contributed to COVID-19 related research so far, out of a total of 647 distinct authors in our dataset of papers (NBER, CEPR and CEPR Covid Economics)

Análisis espacial cuantitativo de la transformación dehumedales continentales en Colombia

Wetlands are among the most productive ecosystems in the world, but its importance is not yet widely recognized. Although these ecosystems are constantly subject to natural changes, human activity has accelerated change rates significantly and it is estimated that more than half the area of wetlands in the world was lost during the last century. This trend was verified in Colombia and almost a quarter of wetlands surface has been converted to other land covers. Using spatial data and quantitative methods, this study quantifies the transformation of wetland areas in the country, identifies the drivers of this transformation and explores the association with other socioeconomic factors. Results indicate that cattle raising and agriculture are the main drivers of wetland change in the country, and to a lesser extent mining, urbanization, and infrastructure. The relationships of wetland transformation with change drivers vary throughout the territory, which should be considered for wetland management and conservation policies in the country.Los humedales están entre los ecosistemas más productivos del mundo, pero su importancia todavía no es ampliamente reconocida. Aunque son ecosistemas sujetos constantemente a cambios naturales, la acción humana ha acelerado las tasas de cambio de forma significativa y se estima que más de la mitad del área de humedales en el mundo se perdió durante el último siglo. En Colombia se verificó esta tendencia y se estimó que casi una cuarta parte de la superficie de humedales ha sido transformada a otro tipo de coberturas terrestres. Este estudio cuantifica las áreas de humedal que se han transformado por intervención antrópica, identifica los disturbios responsables de esa transformación y explora la asociación con otros factores socioeconómicos usando datos espaciales y métodos cuantitativos. Los resultados indican que la mayor parte de áreas de humedal transformadas en el país están dedicadas a la ganadería y la agricultura, y en menor medida a la minería, la urbanización, la construcción de vías y obras civiles. Las relaciones entre la transformación de humedales y los factores de cambio varían a lo largo del territorio, lo cual debe tenerse en cuenta para la gestión y conservación de los humedales del país