Los conceptos de salud financiera, riesgo y epidemiología en los estados financieros de las compañías del sector de extracción de petróleo crudo y gas natural en Colombia

El presente proyecto tiene como objeto identificar cuáles son los conceptos de salud, enfermedad, epidemiología y riesgo aplicables a las empresas del sector de extracción de petróleo y gas natural en Colombia. Dado, el bajo nivel de predicción de los análisis financieros tradicionales y su insuficiencia, en términos de inversión y toma de decisiones a largo plazo, además de no considerar variables como el riesgo y las expectativas de futuro, surge la necesidad de abordar diferentes perspectivas y modelos integradores. Esta apreciación es pertinente dentro del sector de extracción de petróleo y gas natural, debido a la creciente inversión extranjera que ha reportado, US$2.862 millones en el 2010, cifra mayor a diez veces su valor en el año 2003. Así pues, se podrían desarrollar modelos multi-dimensional, con base en los conceptos de salud financiera, epidemiológicos y estadísticos. El termino de salud y su adopción en el sector empresarial, resulta útil y mantiene una coherencia conceptual, evidenciando una presencia de diferentes subsistemas o factores interactuantes e interconectados. Es necesario mencionar también, que un modelo multidimensional (multi-stage) debe tener en cuenta el riesgo y el análisis epidemiológico ha demostrado ser útil al momento de determinarlo e integrarlo en el sistema junto a otros conceptos, como la razón de riesgo y riesgo relativo. Esto se analizará mediante un estudio teórico-conceptual, que complementa un estudio previo, para contribuir al proyecto de finanzas corporativas de la línea de investigación en Gerencia.

Distribución hiperbólica generalizada: una aplicación en la selección de portafolios y en la cuantificación de medidas de riesgo de mercado

En este trabajo se implementa una metodología para incluir momentos de orden superior en la selección de portafolios, haciendo uso de la Distribución Hiperbólica Generalizada, para posteriormente hacer un análisis comparativo frente al modelo de Markowitz.

Comparing intergroup contact effects on blatant and subtle prejudice in adolescents : a multivariate multilevel model

Resumen tomado de la publicación

Anàlisi polifàsica de soques de "Pseudomonas fluorescens" potencials agents de biocontrol de malalties de fruiters

Molts bacteris del grup fluorescent del gènere Pseudomonas són capaços de controlar malalties de les plantes causades per fongs i bacteris fitopatògens (ACBs) o mostren activitat com a bacteris promotors del creixement de les plantes (BPCPs). S'han descrit diversos metabòlits que intervenen de manera important en la seva activitat com a ACBs i BPCPs entre els quals en destaquen el 2,4-diacetilfloroglucinol (Phl), àcid fenazin-1-carboxílic (PCA), Pirrolnitrina (Prn), àcid cianhídric (HCN), àcid 3-indolacètic (IAA), sideròfors i quitinases. L'objectiu principal del nostre treball ha estat la comparació de les característiques d'un grup de Pseudomonas del grup fluorescent utilitzant una aproximació polifàsica amb la finalitat d'establir possibles relacions entre algunes de les característiques i la capacitat d'actuar com a ACB o BPCP. Atesa la importància en el biocontrol de la producció de metabòlits com Phl, PCA i Prn, l'objectiu preliminar ha estat la recerca i obtenció de soques productores d'aquests metabòlits. Per assolir aquest objectiu s'ha emprat una aproximació molecular basada en la detecció dels gens biosintètics implicats en la seva producció en lloc de la detecció directa dels metabòlits per evitar els efectes que poden tenir les condicions de cultiu en la inducció o repressió de la seva síntesi. S'han realitzat diferents protocols basats (i) en la cerca assistida de productors mitjançant l'ús de marcadors fenotípics i posterior confirmació per PCR i, (ii) en l'ús de la PCR per a la detecció dels gens directament dels extractes bacterians, d'enriquiments d'aquests extractes i la realització de la hibridació en colònies per al posterior aïllament. La cerca assistida de productors de Phl mitjançant marcadors fenotípics i posteriorment la utilització de tècniques moleculars (amplificació per PCR del gen phlD), ha estat el millor mètode en el tipus de mostres processades en el nostre treball, on la proporció de productors és relativament baixa. En total s'han aïllat a partir de diversos ambients 4 soques portadores dels gens de la síntesi de PCA, 15 de Phl i 1 de Prn. S'ha constituït una col·lecció de 72 soques de Pseudomonas del grup fluorescent que inclou 18 aïllats propis portadors dels gens biosintètics necessaris per la producció de Phl PCA i Prn; 6 soques de referència procedents de col·leccions de cultius tipus, 14 soques productores dels diferents antibiòtics cedides per altres investigadors i una selecció de 34 soques procedents d'un treball previ realitzat en el nostre grup de recerca. A la col·lecció s'hi troben soques candidates a ACB i BPCP de diverses malalties i plantes. Les 72 soques s'han caracteritzat fenotípica i genotípicament. La caracterització fenotípica s'ha portat a terme mitjançant la identificació a nivell d'espècie amb galeries API 20NE i proves bioquímiques específiques; la producció de metabòlits com PCA, Phl, Prn, IAA, HCN, quitinases i sideròfors mitjançant l'ús de diferents tècniques; antagonisme in vitro en diversos medis enfront dos fongs (Stemphylium vesicarium i Penicillium expansum) i tres bacteris fitopatògens (Erwinia amylovora, Pseudomonas syringae pv. syringae i Xanthomonas arboricola pv. juglandis); l'eficàcia de la inhibició de la infecció en bioassaigs in vivo sobre material vegetal enfront els fongs P. expansum en poma i S. vesicarium en fulles de perera i enfront el bacteri E. amylovora en fruits immadurs de perera i, finalment, en assaigs de promoció de creixement en dos portaempelts comercials de Prunus. Cal destacar que P. expansum causa la podridura blava en pomes i peres en postcollita, S. vesicarium la taca bruna de la perera i E. amylovora el foc bacterià de les rosàcies. El nombre de soques de Pseudomonas, sobre el total de les 72 estudiades, productores d'IAA (4) i quitinases (6) és baix, mentre que és elevat en el cas del HCN (32), que a més està associat a la producció de Phl. Els resultats obtinguts en l'antagonisme in vitro han mostrat en el cas dels bacteris que és dependent del patogen indicador i del medi de cultiu. La presència o absència de ferro no sembla ser un factor que potencií l'antagonisme. En el cas dels fongs no s'ha observat però, influència del medi de cultiu emprat. En el total de 72 soques s'ha observat un percentatge baix de soques que manifesten antagonisme en tots els medis assajats vers 3 o 4 dels patògens (7). Solament 2 d'aquestes 7 soques han mostrat ser també efectives en bioassaigs d'inhibició de les infeccions causades per 2 dels 3 patògens assajats. Algunes de les soques efectives en els bioassaigs no són antagonistes in vitro en cap dels medis assajats enfront el mateix patogen. En el cas de la promoció del creixement, s'han observat més soques promotores del creixement del portaempelts de prunera Marianna 2624 que no en l'híbrid de presseguer-ametller GF677 i les eficàcies assolides són també majors en el cas de Marianna 2624, detectant una elevada especificitat soca/portaempelts La caracterització genotípica s'ha realitzat mitjançant l'anàlisi dels polimorfismes en la longitud dels fragments de restricció de DNA ribosomal (RFLP-rDNA) i l'anàlisi dels polimorfismes en la longitud dels fragments de macrorestricció genòmica de DNA cromosòmic separats per electroforesi en camp polsant (MRFLP-PFGE). Ambdues anàlisis van mostrar una gran heterogeneïtat genètica entre les soques caracteritzades i no s'ha pogut relacionar les agrupacions obtingudes amb les característiques fenotípiques o capacitat d'actuar com a ACB o BPCP. Els patrons de macrorestricció genòmica (MRFLP-PFGE) del bacteri model P. fluorescens EPS288 són estables en el temps i independents de les condicions de cultiu assajades al laboratori o en mostres naturals, mostrant ser una tècnica eficaç en la identificació de reaïllats de mostres naturals inoculades prèviament amb el bacteri. Una selecció de soques que comparteixen el fet de produir floroglucinol s'han caracteritzat mitjançant RFLP i seqüenciació del gen phlD. S'ha establert una relació entre les agrupacions obtingudes en les anàlisis RFLP-rDNA, RFLP-phlD i les seqüències del gen. En l'anàlisi filogenètica de les seqüències del gen phlD s'ha observat un elevat grau de polimorfisme obtenint-se 3 agrupacions principals. Les agrupacions semblen relacionar-se amb els patrons de producció de metabòlits (Phl, HCN i Prn en una primera agrupació; Phl i HCN en la segona i solament Phl en la tercera), però aquestes no s'han pogut relacionar amb l'origen geogràfic de les soques o la seva activitat com a ACBs i/o BPCP. Amb les dades obtingudes de la caracterització fenotípica i genotípica s'ha realitzat una anàlisi multivariant (correspondències, correlacions d'Spearman i de freqüències amb variables categòriques). S'ha demostrat la importància de disposar d'una tècnica que permeti depurar una col·lecció de soques descartant les soques genèticament idèntiques, ja que influeixen en els resultats de les anàlisis. Pels tres patògens assajats com a indicadors i els dos portaempelts emprats, no s'ha observat cap correlació entre la inhibició de la infecció o la promoció del creixement amb les característiques fenotípiques i genotípiques de les soques que fos significatiu i consistent en les tres tècniques emprades.

Artificial Cavities and Nest Site Selection by Puerto Rican Parrots: a Multiscale Assessment

We examined nest site selection by Puerto Rican Parrots, a secondary cavity nester, at several spatial scales using the nest entrance as the central focal point relative to 20 habitat and spatial variables. The Puerto Rican Parrot is unique in that, since 2001, all known nesting in the wild has occurred in artificial cavities, which also provided us with an opportunity to evaluate nest site selection without confounding effects of the actual nest cavity characteristics. Because of the data limitations imposed by the small population size of this critically endangered endemic species, we employed a distribution-free statistical simulation approach to assess site selection relative to characteristics of used and unused nesting sites. Nest sites selected by Puerto Rican Parrots were characterized by greater horizontal and vertical visibility from the nest entrance, greater density of mature sierra palms, and a more westerly and leeward orientation of nest entrances than unused sites. Our results suggest that nest site selection in this species is an adaptive response to predation pressure, to which the parrots respond by selecting nest sites offering advantages in predator detection and avoidance at all stages of the nesting cycle. We conclude that identifying and replicating the “nest gestalt” of successful nesting sites may facilitate conservation efforts for this and other endangered avian species.

Patch Scale Nest-Site Selection by Marbled Murrelets (Brachyramphus marmoratus)

The Marbled Murrelet (Brachyramphus marmoratus) is a threatened alcid that nests almost exclusively in old-growth forests along the Pacific coast of North America. Nesting habitat has significant economic importance. Murrelet nests are extremely difficult and costly to find, which adds uncertainty to management and conservation planning. Models based on air photo interpretation of forest cover maps or assessments by low-level helicopter flights are currently used to rank presumed Marbled Murrelet nesting habitat quality in British Columbia. These rankings are assumed to correlate with nest usage and murrelet breeding productivity. Our goal was to find the models that best predict Marbled Murrelet nesting habitat in the ground-accessible portion of the two regions studied. We generated Resource Selection Functions (RSF) using logistic regression models of ground-based forest stand variables gathered at plots around 64 nests, located using radio-telemetry, versus 82 random habitat plots. The RSF scores are proportional to the probability of nests occurring in a forest patch. The best models differed somewhat between the two regions, but include both ground variables at the patch scale (0.2-2.0 ha), such as platform tree density, height and trunk diameter of canopy trees and canopy complexity, and landscape scale variables such as elevation, aspect, and slope. Collecting ground-based habitat selection data would not be cost-effective for widespread use in forestry management; air photo interpretation and low-level aerial surveys are much more efficient methods for ranking habitat suitability on a landscape scale. This study provides one method for ground-truthing the remote methods, an essential step made possible using the numerical RSF scores generated herein.

Using near infrared reflectance spectroscopy (NIRS) to predict the biological parameters of maize silage

The microbial fermentability, ruminal degradability and digestibility of 48 maize silages were determined using in vitro gas production (GP), in situ degradability and in vitro digestibility procedures. The silages were produced from forage maize harvested throughout the summer of 1998, and represent a wide range of physiological maturities. Large variations among samples were observed for all biological parameters, with the exception of in vitro digestibility and the asymptote of in vitro GP. The potential of near infrared reflectance spectroscopy (NIRS) to predict the biological parameters measured was determined by regression of the biological data against the respective spectral profile. NIRS demonstrated only a moderate ability (R-2 > 0.60-0.80) to predict in vitro digestibility, modelled kinetics of gas production (excluding the asymptote of gas production) and the modelled ruminally soluble dry matter (DM) fraction. Calibration statistics for remaining biological parameters were unacceptably poor (R-2 = 0.60). (C) 2004 Elsevier B.V. All rights reserved.

On the utility of input selection and pruning for financial distress prediction models

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe

Producing projections of future crop yields requires careful thought about the appropriate use of atmosphere-ocean global climate model (AOGCM) simulations. Here we describe and demonstrate multiple methods for ‘calibrating’ climate projections using an ensemble of AOGCM simulations in a ‘perfect sibling’ framework. Crucially, this type of analysis assesses the ability of each calibration methodology to produce reliable estimates of future climate, which is not possible just using historical observations. This type of approach could be more widely adopted for assessing calibration methodologies for crop modelling. The calibration methods assessed include the commonly used ‘delta’ (change factor) and ‘nudging’ (bias correction) approaches. We focus on daily maximum temperature in summer over Europe for this idealised case study, but the methods can be generalised to other variables and other regions. The calibration methods, which are relatively easy to implement given appropriate observations, produce more robust projections of future daily maximum temperatures and heat stress than using raw model output. The choice over which calibration method to use will likely depend on the situation, but change factor approaches tend to perform best in our examples. Finally, we demonstrate that the uncertainty due to the choice of calibration methodology is a significant contributor to the total uncertainty in future climate projections for impact studies. We conclude that utilising a variety of calibration methods on output from a wide range of AOGCMs is essential to produce climate data that will ensure robust and reliable crop yield projections.

The gender gap in real estate sales: negotiation skill or agent selection?

This study examines differences in net selling price for residential real estate across male and female agents. A sample of 2,020 home sales transactions from Fulton County, Georgia are analyzed in a two-stage least squares, geospatial autoregressive corrected, semi-log hedonic model to test for gender and gender selection effects. Although agent gender seems to play a role in naïve models, its role becomes inconclusive as variables controlling for possible price and time on market expectations of the buyers and sellers are introduced to the models. Clear differences in real estate sales prices, time on market, and agent incomes across genders are unlikely due to differences in negotiation performance between genders or the mix of genders in a two-agent negotiation. The evidence suggests an interesting alternative to agent performance: that buyers and sellers with different reservation price and time on market expectations, such as those selling foreclosure homes, tend to select agents along gender lines.

Forecasting with Bayesian multivariate vintage-based VARs

We consider the forecasting of macroeconomic variables that are subject to revisions, using Bayesian vintage-based vector autoregressions. The prior incorporates the belief that, after the first few data releases, subsequent ones are likely to consist of revisions that are largely unpredictable. The Bayesian approach allows the joint modelling of the data revisions of more than one variable, while keeping the concomitant increase in parameter estimation uncertainty manageable. Our model provides markedly more accurate forecasts of post-revision values of inflation than do other models in the literature.

Automated identification of neural correlates of continuous variables

Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.

Calibration and evaluation of individual-based models using Approximate Bayesian Computation

This paper investigates the feasibility of using approximate Bayesian computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain. Rejection-ABC was applied to an existing 14-parameter earthworm energy budget IBM for which the available data consist of body mass growth and cocoon production in four experiments. ABC was able to narrow the posterior distributions of seven parameters, estimating credible intervals for each. ABC’s accepted values produced slightly better fits than literature values do. The accuracy of the analysis was assessed using cross-validation and coverage, currently the best available tests. Of the seven unnarrowed parameters, ABC revealed that three were correlated with other parameters, while the remaining four were found to be not estimable given the data available. It is often desirable to compare models to see whether all component modules are necessary. Here we used ABC model selection to compare the full model with a simplified version which removed the earthworm’s movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimizing an IBM’s structure and parameters within an established statistical framework, thereby making the process more transparent and objective.

Use of a predictive model for food insecurity estimates in Brazil

In 2004 the National Household Survey (Pesquisa Nacional par Amostras de Domicilios - PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p=0.561) and ROC curve (area=0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.

Selection of operational parameters for the production of instant soy protein isolate by pulsed fluid bed agglomeration

The objective of this study was to select the optimal operational conditions for the production of instant soy protein isolate (SPI) by pulsed fluid bed agglomeration. The spray-dried SPI was characterized as being a cohesive powder, presenting cracks and channeling formation during its fluidization (Geldart type A). The process was carried out in a pulsed fluid bed, and aqueous maltodextrin solution was used as liquid binder. Air pulsation, at a frequency of 600 rpm, was used to fluidize the cohesive SPI particles and to allow agglomeration to occur. Seventeen tests were performed according to a central composite design. Independent variables were (i) feed flow rate (0.5-3.5 g/min), (ii) atomizing air pressure (0.5-1.5 bar) and (iii) binder concentration (10-50%). Mean particle diameter, process yield and product moisture were analyzed as responses. Surface response analysis led to the selection of optimal operational parameters, following which larger granules with low moisture content and high process yield were produced. Product transformations were also evaluated by the analysis of size distribution, flowability, cohesiveness and wettability. When compared to raw material, agglomerated particles were more porous and had a more irregular shape, presenting a wetting time decrease, free-flow improvement and cohesiveness reduction. (C) 2010 Elsevier B.V. All rights reserved.